Paths
@@ -495,29 +497,20 @@Edgewise Comparisons
it identical to the other.Take, for example, the following two graphs. The first is the - reference graph, the second is the graph to be compared to it.
+ reference graph, the second is the graph to be compared to it. + When the Edgewise Comparison box is opened, a comparison like this + appears: -
-
- 
-
- When these two graphs are input into the graph compare box, a - window appears which allows you to specify which of the two graphs is the - reference graph. When the comparison is complete, the following window - results
- -
+ 
+ You may choose (by a menu in the upper left part of the box) whether the + graph being compared is the original DAG, or the CPDAG of the original + DAG, of the PAG of the original DAG
When the listed changes have been made to the second graph, it will be identical to the first graph.
-If one of the parent boxes contains multiple graphs, each graph - will be compared separately to the reference graph (or the estimated - graph will be compared separately to each reference graph, depending on - which parent box is selected as the reference), and each comparison will - be housed in its own tab, located on the left side of the window.
Stats List Graph Comparisons
@@ -531,6 +524,10 @@Stats List Graph Comparisons
+ You may choose (by a menu in the upper left part of the box) whether the + graph being compared is the original DAG, or the CPDAG of the original + DAG, of the PAG of the original DAG
+The first columns gives an abbreviation for the statistic; the second columns gives a definition of the statistic. The third columns gives the statistic value.
@@ -547,12 +544,7 @@Misclassifications
will be a 3 in the (undirected, directed) cell of the matrix. An analogous method is used to represent endpoint errors. For example: -
-
- If one of the parent boxes contains multiple graphs, then each - estimated graph will be individually compared to the reference graph (or - vice versa), and the results housed in their own tab, found on the - left.
+
Graph Intersections
@@ -1887,9 +1879,9 @@Updater
independent of their causes in the graph, and probabilities for variables
that are causes of the manipulated variables are unchanged.
- There are five available updater algorithms in Tetrad: the
- approximate updater, the row summing exact updater, the CPT invariant
- updater, the Junction Tree Updater, and the SEM updater. All except for
+
There are four available updater algorithms in Tetrad: the
+ approximate updater, the row summing exact updater, and the Junction Tree Updater,
+ and the SEM updater. All except for
the SEM updater function only when given Bayes instantiated models as
input; the SEM updater functions when given a SEM instantiated model as
input. None of the updaters work on cyclic models.
@@ -2019,13 +2011,13 @@ Row Summing Exact Updater
see conditional as well as marginal probabilities, and in “Single
Variable” mode, you can see joint values.
- CPT Invariant Exact Updater
+
- The CPT invariant exact updater is more accurate than the
- approximate updater, but slightly faster than the row summing exact
- updater. Ifs window functions exactly as the approximate updater down,
- with one exception: in “Multiple Variables” mode, you can see conditional
- as well as marginal probabilities.
+
+
+
+
+
Junction Tree Exact Updater
@@ -2328,6 +2320,12 @@ Random Forward DAG
specify graph parameters such as number of variables, maximum and minimum
degrees, and connectedness.
+ Erdos Renyi DAG
+
+ This option creates a DAG by randomly adding edgew with a given edge
+ probability. The graph is then oriented as a DAG by choosing a
+ causal order.
+
Scale Free DAG
This option creates a DAG whose variable’s degrees obey a power
@@ -2580,7 +2578,10 @@
Using the Search Box
the search.
After optionally changing any search parameters, click on "Run
- Search and Generate Graph" which will execute the search
+ Search and Generate Graph" which will execute the search.
+
+ Notably there are some experimental algorithms available in this box.
+ To see these, select File->Settings->Enable Experimental.
Search Algorithms
@@ -2844,46 +2845,46 @@ Parameters
verbose meekVerbose
- The IMaGES Discrete Algorithm (BDeu Score)
+
- Description
+
-
+
- Adjusts the discrete BDeu variable score of FGES so allow for
- multiple datasets as input. The BDeu scores for each data set are
- averaged at each step of the algorithm, producing a model for all
- data sets that assumes they have the same graphical structure across
- dataset. Note that in order to use this algorithm in a nontrivial
- way, one needs to have loaded or simulated multiple dataset.
+
+
+
+
+
+
-
+
- Input Assumptions
+
- A set of discrete datasets with the same variables and sample
- sizes.
+
+
- Output Format
+
- A CPDAG, interpreted as a common model for all datasets.
+
- Parameters
+
- All of the parameters from FGES are available for IMaGES.
- Additionally:
+
+
-
+
+
- The IMaGES Continuous Algorithm (SEM BIC Score)
+ The IMaGES Algorithm
Description
- Adjusts the continuous variable score (SEM BIC) of FGES so
+
Adjusts the selected score for FGES so
allow for multiple datasets as input. The linear, Gaussian BIC scores
for each data set are averaged at each step of the algorithm,
producing a model for all data sets that assumes they have the same
@@ -2893,7 +2894,7 @@
Description
Input Assumptions
- A set of continuous datasets with the same variables and sample
+
A set of datasets consistent with the chosen score with the same variables and sample
sizes.
Output Format
@@ -3030,52 +3031,52 @@ Parameters
href="#completeRuleSetUsed">completeRuleSetUsed
- The RFCI-BSC Algorithm
+
- Description
+
-
+
- RFCI-BSC is a combination of the RFCI [Colombo, 2012]
- algorithm and the Bayesian Scoring of Constraints (BSC) method
- [Jabbari, 2017] that can generate and probabilistically score
- multiple models, outputting the most probable one. This search
- algorithm is a hybrid method that derives a Bayesian probability that
- the set of independence tests associated with a given causal model
- are jointly correct. Using this constraint-based scoring method, we
- are able to score multiple causal models, which possibly contain
- latent variables, and output the most probable one. See [Jabbari,
- 2017].
+
+
+
+
+
+
+
+
+
+
- Currently, this algorithm can only be accessed if experimental
- algorithms are activated. One may do so by going to the
- File menu, selecting Settings, and then making sure the
- 'Experimental' checkbox is checked.
+
+
+
+
-
+
- Input Assumptions
+
- The data are discrete only.
+
- Output Format
+
- A partial ancestral graph (PAG). See Spirtes et al., 2000.
+
- Parameters
+
- All of the parameters from RFCI are available for RFCI-BSC.
- Additionally:
+
+
- numRandomizedSearchModels, thresholdNoRandomDataSearch, cutoffDataSearch, thresholdNoRandomConstrainSearch
- , cutoffConstrainSearch, numBscBootstrapSamples, lowerBound, upperBound,
- outputRBD
+
+
+
+
+
+
+
+
+
The GFCI Algorithm
@@ -3370,13 +3371,13 @@ Parameters
- The MBFS Algorithm
+ The PC-MB Algorithm
Description
-
+
- Markov blanket fan search. Similar to FGES-MB (see FGES,
+
PC-MB. Similar to FGES-MB (see FGES,
2016) but using PC as the basic search instead of FGES. The rules of
the PC search are restricted to just the variables in the Markov
blanket of a target T, including T; the result is a graph that is a
@@ -4353,7 +4354,7 @@
Parameters
Search Parameters
Note: You must specify the "Value Type" of each parameter, and
- the value type must be one of the following: Integer, Double, String,
+ the value type must be one of the following: Integer, Long, Double, String,
Boolean.
@@ -4598,13 +4599,13 @@ coefLow
id="completeRuleSetUsed_short_desc"> Yes if the complete FCI rule set
should be used
Long Description: Yes if the (simpler) final
+ id="completeRuleSetUsed_long_desc"> No if the (simpler) final
orientation rules set due to P. Spirtes, guaranteeing arrow
- completeness, should be used; no if the (fuller) set due to J. Zhang,
+ completeness, should be used; yes if the (fuller) set due to J. Zhang,
should be used guaranteeing additional tail completeness.
Default Value: false
+ id="completeRuleSetUsed_default_value">true
Lower
Bound:
Upper Bound: coefLow
Boolean
+ doDiscriminatingPathRule
+
+ - Short Description: Yes if the discriminating path rule
+ should be done, No if not
+ - Long Description: Yes if the discriminating path
+ FCI rule (part of the final orientation, requiring an additional test)
+ should be done, No if not
+
+ - Default Value: true
+ - Lower
+ Bound:
+ - Upper Bound:
+ - Value Type:
+ Boolean
+
+
+ doDiscriminatingPathColliderRule
+
+ - Short Description: Yes if the discriminating path collider rule
+ should be done, No if not
+ - Long Description: Yes if the discriminating path collider
+ FCI rule (part of the final orientation, requiring an additional test)
+ should be done, No if not
+
+ - Default Value: false
+ - Lower
+ Bound:
+ - Upper Bound:
+ - Value Type:
+ Boolean
+
+
+ doDiscriminatingPathTailRule
+
+ - Short Description: Yes if the discriminating path tail rule
+ should be done, No if not
+ - Long Description: Yes if the discriminating path tail
+ FCI rule (part of the final orientation, requiring an additional test)
+ should be done, No if not
+
+ - Default Value: true
+ - Lower
+ Bound:
+ - Upper Bound:
+ - Value Type:
+ Boolean
+
+
concurrentFAS
cstarQ
targetNames
-
- - Short Description: Target names
+ id="targets">targets
+
+ - Short Description: Target names
(comma separated)
- Long Description: Target names (comma separated).
+ id="targets_long_desc">Target names (comma separated).
- Default Value:
+ id="targets_default_value">
- Lower Bound:
+ id="targets_lower_bound">
- Upper Bound:
+ id="targets_upper_bound">
- Value Type: String
+ id="targets_value_type">String
depth
Boolean
+ mb
+
+ - Short Description: Find Markov blanket(s)
+ - Long Description: Looks for the graph over the Markov blanket(s) and target(s) if true
+
+ - Default Value: false
+ - Lower Bound:
+ - Upper Bound:
+ - Value Type: Boolean
+
+
discretize
- Short Description: fastIcaA
id="generalSemParameterTemplate_value_type">String
+ imagesMetaAlg
+
+ - Short Description: IMaGES "meta" algorithm. 1 = FGES, 2 = BOSS-Tuck
+ - Long
+ Description: Sets the meta algorithm to be optimized using the IMaGES (average BIC) score.
+
+ - Default Value:
+ 1
+ - Lower Bound: 1
+ - Upper Bound: 5
+ - Value Type: Integer
+
+
ia
@@ -6025,24 +6127,16 @@ maxDegree
Integer
- zsMaxIndegree
-
- - Short Description: Maximum indegree of true graph (min =
- 0)
- - Long Description: This is the maximum number of parents
- one expects any node to have in the true model.
- - Default Value: 4
- - Lower Bound: 0
- - Upper Bound: 2147483647
- - Value Type:
- Integer
+ zsMaxIndegree
+
+ - Short Description: Maximum indegree of true graph (min = 0)
+
+ - Long Description: This is the maximum number of parents one expects any node to have in the true model.
+
+ - Default Value: 4
+ - Lower Bound: 0
+ - Upper Bound: 2147483647
+ - Value Type: Integer
numStarts
bossScoreType
+ id="bossAlg">bossAlg
- Short Description: Yes if edge count of the model should
- be minimized, No if BIC should be maximized
+ id="bossAlg_short_desc">Picks the BOSS algorithm type, BOSS1 or BOSS2
- Long
- Description: If Yes, the number
- of edges in the model will be minimized, following Raskutti and Uhler
- 2018. If second, the supplied score of the model (preferably a BIC
- score) will be optimized, a suggestion made in Solus et al. 2017.
+ Description: 1 = BOSS1, 2 = BOSS2, 3 = BOSS3
- Default Value: false
+ id="bossAlg_default_value">1
- Lower Bound:
-
+ 1
- Upper Bound:
-
+ 3
- Value Type:
- Boolean
+ Integer
numStarts
graspUseVermaPearl
+ id="graspUseRaskuttiUhler">graspUseRaskuttiUhler
- Short Description: Yes to use Raskutti and Uhler's
+ id="graspUseRaskuttiUhler_short_desc"> Yes to use Raskutti and Uhler's
DAG-building method (test), No to use Grow-Shrink (score).
- - Long Description:
+
- Long Description:
Raskutti and Uhler's method adds and edge X->Y if Y ~_||_ X |
Prefix(Y, pi) \ {X}. Grow-Shrink adds an edge X->Y if X is in the
Markov blanket of Y where the variable set is restricted to Prefix(Y,
pi).
- Default Value: false
+ id="graspUseRaskuttiUhler_default_value">false
- Lower
- Bound:
+ Bound:
- Upper Bound:
+ id="graspUseRaskuttiUhler_upper_bound">
- Value Type:
- Boolean
+ Boolean
precomputeCovarianc
id="penaltyDiscount_value_type">Double
+ zSRiskBound
+
+ - Short Description: Risk bound
+ - Long Description:
+ This is the probability of getting the true model if a correct model is discovered. Could underfit.
+
+ - Default Value: 0.001
+ - Lower Bound: 0
+ - Upper Bound: 1
+ - Value Type: Double
+
+
ebicGamma
- Short Description: ebicGamma
id="trueErrorVariance_value_type">Double
- zSRiskBound
-
- - Short Description: Risk bound
- - Long
- Description: This is the
- probability of getting the true model if a correct model is
- discovered. Could underfit.
- - Default Value: 0.001
- - Lower Bound:
- 0
- - Upper Bound:
- 1
- - Value Type:
- Double
-
-
correlationThreshold
ebicGamma
class="parameter_description_list">
- Short Description: The percentage of resample size
- (min = 0.1)
+ (min = 10%)
- Long Description: This parameter specifies the
percentage of records in the bootstrap (as a percentage of the total
@@ -7318,9 +7400,9 @@
ebicGamma
id="percentResampleSize_default_value">90
- Lower
Bound: -2147483648
+ id="percentResampleSize_lower_bound">10
- Upper Bound: 2147483647
+ id="percentResampleSize_upper_bound">100
- Value
Type: Integer
@@ -7663,6 +7745,25 @@ sampleSize
Type: Integer
+ seed
+
+ - Short Description: Seed for pseudorandom number generator (min = -1)
+ - Long Description: The seed is the initial value of the
+ internal state of the pseudorandom number generator.
+ - Default Value: -1
+ - Lower Bound:
+ -1
+ - Upper
+ Bound: 9223372036854775807
+ - Value Type: Long
+
+
selfLoopCoef
semGicRule
Type: Double
+ poissonLambda
+
+ - Short Description: Lambda parameter for the Poisson distribution
+ (> 0)
+ - Long Description: Lambda parameter for the Poisson distribution
+ - Default Value: 1
+ - Lower
+ Bound: 1e-10
+ - Upper Bound: Infinity
+ - Value
+ Type: Double
+
+
skipNumRecords
Trek
ga('send', 'pageview')
+
+
+
diff --git a/pom.xml b/pom.xml
index 18d3a66cad..786df39e46 100644
--- a/pom.xml
+++ b/pom.xml
@@ -4,7 +4,7 @@
4.0.0
io.github.cmu-phil
tetrad
- 7.1.2-2
+ 7.1.3-1
pom
Tetrad Project
diff --git a/tetrad-gui/pom.xml b/tetrad-gui/pom.xml
index e0c70ec727..b0c9d6ddff 100644
--- a/tetrad-gui/pom.xml
+++ b/tetrad-gui/pom.xml
@@ -6,7 +6,7 @@
io.github.cmu-phil
tetrad
- 7.1.2-2
+ 7.1.3-1
tetrad-gui
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/app/ContributorsAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/app/ContributorsAction.java
index 56a55fe020..cd0da48795 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/app/ContributorsAction.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/app/ContributorsAction.java
@@ -57,7 +57,11 @@ public void actionPerformed(ActionEvent e) {
"Kong Wongchakprasitti, and Harry Hochheiser. Additional work has been done by Bryan " +
"Andrews, Ruben Sanchez, Fattaneh Jabbari, Ricardo Silva, Dan Malinsky, Erich Kummerfeld, " +
"Biwei Huang, Juan Miguel Ogarrio, David Danks, Kevin Kelly, Eric Strobl, Shyam Visweswaran, " +
- "Shuyan Wang, Madelyn Glymour, Frank Wimberly, Matt Easterday, and Tyler Gibson.";
+ "Shuyan Wang, Madelyn Glymour, Frank Wimberly, Matt Easterday, and Tyler Gibson, and " +
+ "Mike Konrad (Software Engineering Institute, CMU). " +
+ "This material is based, in part, upon work funded and supported by the Department of Defense under " +
+ "Contract No. FA8702-15-D-0002 with Carnegie Mellon University for the operation of the " +
+ "Software Engineering Institute, a federally funded research and development center.";
JTextArea textArea = new JTextArea(msg);
textArea.setFont(new Font("Monospaced", Font.PLAIN, 12));
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/app/TetradLogArea.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/app/TetradLogArea.java
index 8bcf58e98e..4ff9138770 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/app/TetradLogArea.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/app/TetradLogArea.java
@@ -54,6 +54,7 @@ public TetradLogArea(TetradDesktop tetradDesktop) {
// build the text area.
JTextArea textArea = new JTextArea();
+ textArea.setFont(new Font(Font.MONOSPACED, Font.PLAIN, 12));
if (TetradLogger.getInstance().isDisplayLogEnabled()) {
this.stream = new TextAreaOutputStream(textArea);
TetradLogger.getInstance().addOutputStream(this.stream);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/AbstractSearchEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/AbstractSearchEditor.java
index e12a8bc0ee..404eb2dfa9 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/AbstractSearchEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/AbstractSearchEditor.java
@@ -22,8 +22,7 @@
package edu.cmu.tetradapp.editor;
import edu.cmu.tetrad.data.DataModel;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.GraphUtils;
@@ -226,7 +225,7 @@ public void watch() {
Parameters searchParams = getAlgorithmRunner().getParams();
if (searchParams != null) {
- IKnowledge knowledge = (IKnowledge) searchParams.get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) searchParams.get("knowledge", new Knowledge());
if (!knowledge.isEmpty()) {
JOptionPane.showMessageDialog(
JOptionUtils.centeringComp(),
@@ -403,7 +402,7 @@ JMenuBar menuBar() {
JMenuBar menuBar = new JMenuBar();
JMenu file = new JMenu("File");
menuBar.add(file);
- JMenu fileMenu = new GraphFileMenu(this, getWorkbench());
+ JMenu fileMenu = new GraphFileMenu(this, getWorkbench(), false);
file.add(fileMenu);
file.add(new SaveComponentImage(this.workbench, "Save Graph Image..."));
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/AlgorithmParameterPanel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/AlgorithmParameterPanel.java
index 60047ab4da..1c626ec5bd 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/AlgorithmParameterPanel.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/AlgorithmParameterPanel.java
@@ -32,6 +32,7 @@
import edu.cmu.tetradapp.ui.PaddingPanel;
import edu.cmu.tetradapp.util.DoubleTextField;
import edu.cmu.tetradapp.util.IntTextField;
+import edu.cmu.tetradapp.util.LongTextField;
import edu.cmu.tetradapp.util.StringTextField;
import javax.swing.*;
@@ -183,6 +184,10 @@ protected Box createParameterComponent(String parameter, Parameters parameters,
int lowerBoundInt = paramDesc.getLowerBoundInt();
int upperBoundInt = paramDesc.getUpperBoundInt();
component = getIntTextField(parameter, parameters, (Integer) defaultValue, lowerBoundInt, upperBoundInt);
+ } else if (defaultValue instanceof Long) {
+ long lowerBoundLong = paramDesc.getLowerBoundLong();
+ long upperBoundLong = paramDesc.getUpperBoundLong();
+ component = getLongTextField(parameter, parameters, (Long) defaultValue, lowerBoundLong, upperBoundLong);
} else if (defaultValue instanceof Boolean) {
component = getBooleanSelectionBox(parameter, parameters, (Boolean) defaultValue);
} else if (defaultValue instanceof String) {
@@ -282,6 +287,35 @@ protected IntTextField getIntTextField(String parameter, Parameters parameters,
return field;
}
+
+ protected LongTextField getLongTextField(String parameter, Parameters parameters,
+ long defaultValue, long lowerBound, long upperBound) {
+ LongTextField field = new LongTextField(parameters.getLong(parameter, defaultValue), 8);
+
+ field.setFilter((value, oldValue) -> {
+ if (value == field.getValue()) {
+ return oldValue;
+ }
+
+ if (value < lowerBound) {
+ return oldValue;
+ }
+
+ if (value > upperBound) {
+ return oldValue;
+ }
+
+ try {
+ parameters.set(parameter, value);
+ } catch (Exception e) {
+ // Ignore.
+ }
+
+ return value;
+ });
+
+ return field;
+ }
// Zhou's new implementation with yes/no radio buttons
protected Box getBooleanSelectionBox(String parameter, Parameters parameters, boolean defaultValue) {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/CopySubgraphAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/CopySubgraphAction.java
index f9247b2421..464362c4d0 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/CopySubgraphAction.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/CopySubgraphAction.java
@@ -37,7 +37,7 @@
*
* @author Joseph Ramsey jdramsey@andrew.cmu.edu
*/
-class CopySubgraphAction extends AbstractAction implements ClipboardOwner {
+public class CopySubgraphAction extends AbstractAction implements ClipboardOwner {
/**
* The desktop containing the target session editor.
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DagEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DagEditor.java
index b7fdc1760d..f10be7cdc0 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DagEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DagEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.IndTestDSep;
import edu.cmu.tetrad.search.IndependenceTest;
@@ -179,7 +179,7 @@ public void setGraph(Graph graph) {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return null;
}
@@ -383,7 +383,7 @@ private void modelSelectin(DagWrapper dagWrapper) {
private JMenuBar createGraphMenuBar() {
JMenuBar menuBar = new JMenuBar();
- JMenu fileMenu = new GraphFileMenu(this, getWorkbench());
+ JMenu fileMenu = new GraphFileMenu(this, getWorkbench(), false);
// JMenu fileMenu = createFileMenu();
JMenu editMenu = createEditMenu();
JMenu graphMenu = createGraphMenu();
@@ -427,8 +427,15 @@ private JMenu createGraphMenu() {
graph.add(randomGraph);
graph.addSeparator();
- graph.add(new GraphPropertiesAction(getWorkbench()));
- graph.add(new PathsAction(getWorkbench()));
+ graph.add(new GraphPropertiesAction(this.workbench));
+ graph.add(new PathsAction(this.workbench));
+ graph.add(new UnderliningsAction(this.workbench));
+
+ graph.add(new JMenuItem(new SelectDirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectBidirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectUndirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectLatentsAction(this.workbench)));
+// graph.add(new PagTypeSetter(getWorkbench()));
randomGraph.addActionListener(e -> {
@@ -436,7 +443,7 @@ private JMenu createGraphMenu() {
editor.setParams(this.parameters);
EditorWindow editorWindow = new EditorWindow(editor, "Edit Random Graph Parameters",
- "Done", false, this);
+ "Done", true, this);
DesktopController.getInstance().addEditorWindow(editorWindow, JLayeredPane.PALETTE_LAYER);
editorWindow.pack();
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DagGraphToolbar.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DagGraphToolbar.java
index 7935e15007..e52a918718 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DagGraphToolbar.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DagGraphToolbar.java
@@ -177,6 +177,7 @@ private void addButton(JToggleButton button, String name) {
button.setIcon(
new ImageIcon(ImageUtils.getImage(this, name + "3.gif")));
button.setMaximumSize(new Dimension(80, 40));
+ button.setMaximumSize(new Dimension(80, 40));
button.setPreferredSize(new Dimension(80, 40));
this.buttonsPanel.add(button);
this.buttonsPanel.add(Box.createVerticalStrut(5));
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DataEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DataEditor.java
index 65eeccecc0..b986da1a49 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DataEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/DataEditor.java
@@ -361,11 +361,11 @@ public DataWrapper getDataWrapper() {
return this.dataWrapper;
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.dataWrapper.getKnowledge();
}
- public void setKnowledge(IKnowledge knowledge) {
+ public void setKnowledge(Knowledge knowledge) {
this.dataWrapper.setKnowledge(knowledge);
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/EdgeTypeTable.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/EdgeTypeTable.java
index 28f9095517..b0bc23aa6c 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/EdgeTypeTable.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/EdgeTypeTable.java
@@ -18,13 +18,29 @@
*/
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.graph.*;
-
-import javax.swing.*;
-import javax.swing.table.*;
-import java.awt.*;
+import edu.cmu.tetrad.graph.Edge;
+import edu.cmu.tetrad.graph.EdgeTypeProbability;
+import edu.cmu.tetrad.graph.Edges;
+import edu.cmu.tetrad.graph.Endpoint;
+import edu.cmu.tetrad.graph.Graph;
+import java.awt.BorderLayout;
+import java.awt.Color;
+import java.awt.Component;
+import java.awt.Font;
import java.util.ArrayList;
import java.util.List;
+import javax.swing.JLabel;
+import javax.swing.JPanel;
+import javax.swing.JScrollPane;
+import javax.swing.JTable;
+import javax.swing.SwingConstants;
+import javax.swing.table.DefaultTableCellRenderer;
+import javax.swing.table.DefaultTableModel;
+import javax.swing.table.JTableHeader;
+import javax.swing.table.TableCellRenderer;
+import javax.swing.table.TableColumn;
+import javax.swing.table.TableModel;
+import javax.swing.table.TableRowSorter;
/**
* Apr 30, 2019 2:30:18 PM
@@ -36,28 +52,31 @@ public class EdgeTypeTable extends JPanel {
private static final long serialVersionUID = -9104061917163909746L;
private static final String[] EDGES = {
- "Node 1",
- "Interaction",
- "Node 2"
+ "",
+ "Node 1",
+ "Interaction",
+ "Node 2"
};
private static final String[] EDGES_AND_EDGE_TYPES = {
- "Node 1",
- "Interaction",
- "Node 2",
- "Ensemble",
- "No edge",
- "\u2192",
- "\u2190",
- "\u2192", // -G> pd nl
- "\u2190", // dd nl
- "\u2190", // ",
- "<-o",
- "o-o",
- "<->",
- "---"
+ "",
+ "Node 1",
+ "Interaction",
+ "Node 2",
+ "Ensemble",
+ "Edge",
+ "No edge",
+ "\u2192",
+ "\u2190",
+ "---",
+ "\u2192", // -G> pd nl
+ "\u2190", // dd nl
+ "\u2190", // ",
+ "<-o",
+ "o-o",
+ "<->"
};
private final JLabel title = new JLabel();
@@ -77,34 +96,32 @@ private void initComponents() {
}
public void update(Graph graph) {
- DefaultTableModel tableModel = (DefaultTableModel) this.table.getModel();
+ List edges = new ArrayList<>(graph.getEdges());
+ Edges.sortEdges(edges);
+ DefaultTableModel tableModel = (DefaultTableModel) this.table.getModel();
tableModel.setRowCount(0);
if (hasEdgeProbabilities(graph)) {
this.title.setText("Edges and Edge Type Frequencies");
-
this.table.setAutoResizeMode(JTable.AUTO_RESIZE_OFF);
+ tableModel.setColumnIdentifiers(EdgeTypeTable.EDGES_AND_EDGE_TYPES);
JTableHeader header = this.table.getTableHeader();
Font boldFont = new Font(header.getFont().getFontName(), Font.BOLD, 18);
TableCellRenderer headerRenderer = header.getDefaultRenderer();
header.setDefaultRenderer((tbl, value, isSelected, hasFocus, row, column) -> {
Component comp = headerRenderer.getTableCellRendererComponent(tbl, value, isSelected, hasFocus, row, column);
- if (column > 6 && column < 11) {
- comp.setForeground(Color.GREEN);
+ if (column >= 9 && column <= 12) {
+ comp.setForeground(Color.BLUE);
}
- if (column > 8 && column < 11) {
+ if (column >= 11 && column <= 12) {
comp.setFont(boldFont);
}
return comp;
});
- tableModel.setColumnIdentifiers(EdgeTypeTable.EDGES_AND_EDGE_TYPES);
-
- List edges = new ArrayList<>(graph.getEdges());
- Edges.sortEdges(edges);
edges.forEach(edge -> {
String[] rowData = new String[EdgeTypeTable.EDGES_AND_EDGE_TYPES.length];
addEdgeData(edge, rowData);
@@ -114,102 +131,102 @@ public void update(Graph graph) {
});
} else {
this.title.setText("Edges");
-
this.table.setAutoResizeMode(JTable.AUTO_RESIZE_ALL_COLUMNS);
-
tableModel.setColumnIdentifiers(EdgeTypeTable.EDGES);
- List edges = new ArrayList<>(graph.getEdges());
- Edges.sortEdges(edges);
edges.forEach(edge -> {
String[] rowData = new String[EdgeTypeTable.EDGES.length];
addEdgeData(edge, rowData);
tableModel.addRow(rowData);
});
+
}
tableModel.fireTableDataChanged();
}
private void addEdgeProbabilityData(Edge edge, String[] rowData) {
- edge.getEdgeTypeProbabilities().forEach(edgeTypeProb -> {
- String probValue = String.format("%.4f", edgeTypeProb.getProbability());
- boolean nl, pd, dd;
- switch (edgeTypeProb.getEdgeType()) {
- case nil:
- rowData[4] = probValue;
- break;
- case ta:
- nl = false;
- pd = false;
- dd = false;
- for (Edge.Property p : edgeTypeProb.getProperties()) {
- if (p == Edge.Property.dd) {
- dd = true;
- }
- if (p == Edge.Property.nl) {
- nl = true;
- }
- if (p == Edge.Property.pd) {
- pd = true;
- }
- }
- if (nl && dd) {
- rowData[9] = probValue;
- } else if (nl && pd) {
- rowData[7] = probValue;
- } else {
- rowData[5] = probValue;
- }
- break;
- case at:
- nl = false;
- pd = false;
- dd = false;
- for (Edge.Property p : edgeTypeProb.getProperties()) {
- if (p == Edge.Property.dd) {
- dd = true;
- }
- if (p == Edge.Property.nl) {
- nl = true;
- }
- if (p == Edge.Property.pd) {
- pd = true;
- }
+ edge.getEdgeTypeProbabilities().stream()
+ .filter(edgeTypeProb -> edgeTypeProb.getProbability() > 0)
+ .forEach(edgeTypeProb -> {
+ String probValue = String.format("%.4f", edgeTypeProb.getProbability());
+ boolean nl, pd, dd;
+ switch (edgeTypeProb.getEdgeType()) {
+ case nil:
+ rowData[6] = probValue;
+ break;
+ case ta:
+ nl = false;
+ pd = false;
+ dd = false;
+ for (Edge.Property p : edgeTypeProb.getProperties()) {
+ if (p == Edge.Property.dd) {
+ dd = true;
+ }
+ if (p == Edge.Property.nl) {
+ nl = true;
+ }
+ if (p == Edge.Property.pd) {
+ pd = true;
+ }
+ }
+ if (nl && dd) {
+ rowData[12] = probValue;
+ } else if (nl && pd) {
+ rowData[10] = probValue;
+ } else {
+ rowData[7] = probValue;
+ }
+ break;
+ case at:
+ nl = false;
+ pd = false;
+ dd = false;
+ for (Edge.Property p : edgeTypeProb.getProperties()) {
+ if (p == Edge.Property.dd) {
+ dd = true;
+ }
+ if (p == Edge.Property.nl) {
+ nl = true;
+ }
+ if (p == Edge.Property.pd) {
+ pd = true;
+ }
+ }
+ if (nl && dd) {
+ rowData[13] = probValue;
+ } else if (nl && pd) {
+ rowData[11] = probValue;
+ } else {
+ rowData[8] = probValue;
+ }
+ break;
+ case tt:
+ rowData[9] = probValue;
+ break;
+ case ca:
+ rowData[14] = probValue;
+ break;
+ case ac:
+ rowData[15] = probValue;
+ break;
+ case cc:
+ rowData[16] = probValue;
+ break;
+ case aa:
+ rowData[17] = probValue;
+ break;
}
- if (nl && dd) {
- rowData[10] = probValue;
- } else if (nl && pd) {
- rowData[8] = probValue;
- } else {
- rowData[6] = probValue;
- }
- break;
- case ca:
- rowData[11] = probValue;
- break;
- case ac:
- rowData[12] = probValue;
- break;
- case cc:
- rowData[13] = probValue;
- break;
- case aa:
- rowData[14] = probValue;
- break;
- case tt:
- rowData[15] = probValue;
- break;
- }
- });
+ });
double maxEdgeProbability = edge.getEdgeTypeProbabilities().stream()
.filter(e -> e.getEdgeType() != EdgeTypeProbability.EdgeType.nil)
.mapToDouble(EdgeTypeProbability::getProbability)
.max()
.orElse(0);
- rowData[3] = String.format("%.4f", maxEdgeProbability);
+ rowData[4] = String.format("%.4f", maxEdgeProbability);
+ rowData[5] = String.format("%.4f", edge.getProbability());
}
private void addEdgeData(Edge edge, String[] rowData) {
@@ -220,7 +237,6 @@ private void addEdgeData(Edge edge, String[] rowData) {
Endpoint endpoint2 = edge.getEndpoint2();
// These should not be flipped.
-
String endpoint1Str = "";
if (endpoint1 == Endpoint.TAIL) {
endpoint1Str = "-";
@@ -241,9 +257,9 @@ private void addEdgeData(Edge edge, String[] rowData) {
String edgeType = endpoint1Str + "-" + endpoint2Str;
- rowData[0] = node1Name;
- rowData[1] = edgeType;
- rowData[2] = node2Name;
+ rowData[1] = node1Name;
+ rowData[2] = edgeType;
+ rowData[3] = node2Name;
}
private boolean hasEdgeProbabilities(Graph graph) {
@@ -254,7 +270,7 @@ private boolean hasEdgeProbabilities(Graph graph) {
return false;
}
- private static class EdgeInfoTable extends JTable {
+ class EdgeInfoTable extends JTable {
private static final long serialVersionUID = -4052775309418269033L;
@@ -271,7 +287,7 @@ private void initComponents() {
setRowSorter(new TableRowSorter(getModel()) {
@Override
public boolean isSortable(int column) {
- return !(column == 1 || column == 12);
+ return !(column == 0);
}
});
}
@@ -306,13 +322,19 @@ private void initComponents() {
@Override
public Component getTableCellRendererComponent(JTable table, Object value, boolean isSelected, boolean hasFocus, int row, int column) {
- JComponent component = (JComponent) super.getTableCellRendererComponent(table, value, isSelected, hasFocus, row, column);
+ JLabel label = (JLabel) super.getTableCellRendererComponent(table, value, isSelected, hasFocus, row, column);
if (!isSelected) {
- component.setBackground((row % 2 == 0) ? this.NON_STRIPE : this.STRIPE);
+ label.setBackground((row % 2 == 0) ? this.NON_STRIPE : this.STRIPE);
}
- return component;
+ if (column == 0) {
+ setText(Integer.toString(row + 1));
+ label.setHorizontalAlignment(SwingConstants.CENTER);
+ label.setFont(new Font("SansSerif", Font.BOLD, 12));
+ }
+
+ return label;
}
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/EdgewiseComparisonEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/EdgewiseComparisonEditor.java
index 7d656da993..a9afb09724 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/EdgewiseComparisonEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/EdgewiseComparisonEditor.java
@@ -21,12 +21,14 @@
package edu.cmu.tetradapp.editor;
import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetradapp.model.EdgewiseComparisonModel;
-import edu.cmu.tetradapp.model.GraphWrapper;
+import org.jetbrains.annotations.NotNull;
import javax.swing.*;
import java.awt.*;
-import java.util.List;
+
+import static edu.cmu.tetrad.graph.GraphUtils.getComparisonGraph;
/**
* Provides a little display/editor for notes in the session workbench. This may
@@ -42,12 +44,15 @@ public class EdgewiseComparisonEditor extends JPanel {
* The model for the note.
*/
private final EdgewiseComparisonModel comparison;
+ private JTextArea area;
+ private final Parameters params;
/**
* Constructs the editor given the model
*/
public EdgewiseComparisonEditor(EdgewiseComparisonModel comparison) {
this.comparison = comparison;
+ this.params = comparison.getParams();
setup();
}
@@ -55,44 +60,105 @@ public EdgewiseComparisonEditor(EdgewiseComparisonModel comparison) {
private void setup() {
setLayout(new BorderLayout());
- List referenceGraphs = this.comparison.getReferenceGraphs();
- JTabbedPane pane = new JTabbedPane(SwingConstants.LEFT);
+ JPanel pane = new JPanel();
- for (int i = 0; i < referenceGraphs.size(); i++) {
- JTabbedPane pane2 = new JTabbedPane(SwingConstants.TOP);
- String compareString = this.comparison.getComparisonString(i);
+ Font font = new Font("Monospaced", Font.PLAIN, 14);
+ area = new JTextArea();
+ area.setText(tableTextWithHeader());
- Font font = new Font("Monospaced", Font.PLAIN, 14);
- JTextArea textPane = new JTextArea();
- textPane.setText(compareString);
+ area.setFont(font);
- textPane.setFont(font);
+ JScrollPane scrollTextPane = new JScrollPane(area);
+ scrollTextPane.setPreferredSize(new Dimension(500, 600));
- JScrollPane scrollTextPane = new JScrollPane(textPane);
- scrollTextPane.setPreferredSize(new Dimension(400, 400));
+ pane.add(scrollTextPane, new BorderLayout());
- pane2.add("Comparison", scrollTextPane);
+ add(pane);
- GraphEditor graphEditor = new GraphEditor(new GraphWrapper(this.comparison.getTargetGraphs().get(i)));
- graphEditor.enableEditing(false);
+ add(menubar(), BorderLayout.NORTH);
+ }
- JScrollPane scrollTargetGraph = new JScrollPane(graphEditor.getWorkbench());
- scrollTargetGraph.setPreferredSize(new Dimension(400, 400));
+ @NotNull
+ private JMenuBar menubar() {
+ JMenuBar menubar = new JMenuBar();
+ JMenu menu = new JMenu("Compare To...");
+ JMenuItem graph = new JCheckBoxMenuItem("DAG");
+ graph.setBackground(Color.WHITE);
+ JMenuItem cpdag = new JCheckBoxMenuItem("CPDAG");
+ cpdag.setBackground(Color.YELLOW);
+ JMenuItem pag = new JCheckBoxMenuItem("PAG");
+ pag.setBackground(Color.GREEN.brighter().brighter());
+
+ ButtonGroup group = new ButtonGroup();
+ group.add(graph);
+ group.add(cpdag);
+ group.add(pag);
+
+ menu.add(graph);
+ menu.add(cpdag);
+ menu.add(pag);
+
+ menubar.add(menu);
+
+ switch (this.params.getString("graphComparisonType")) {
+ case "CPDAG":
+ menu.setText("Compare to CPDAG...");
+ cpdag.setSelected(true);
+ break;
+ case "PAG":
+ menu.setText("Compare to PAG...");
+ pag.setSelected(true);
+ break;
+ default:
+ menu.setText("Compare to DAG...");
+ graph.setSelected(true);
+ break;
+ }
- pane2.add("Target Graph", scrollTargetGraph);
+ graph.addActionListener(e -> {
+ this.params.set("graphComparisonType", "DAG");
+ menu.setText("Compare to DAG...");
+ menu.setBackground(Color.WHITE);
- graphEditor = new GraphEditor(new GraphWrapper(this.comparison.getReferenceGraphs().get(i)));
- graphEditor.enableEditing(false);
+ this.area.setText(comparison.getComparisonString());
+ this.area.moveCaretPosition(0);
+ this.area.setSelectionStart(0);
+ this.area.setSelectionEnd(0);
- JScrollPane scrollTrueGraph = new JScrollPane(graphEditor.getWorkbench());
- scrollTrueGraph.setPreferredSize(new Dimension(400, 400));
+ this.area.repaint();
- pane2.add("True Graph", scrollTrueGraph);
+ });
- pane.add("" + (i + 1), pane2);
- }
+ cpdag.addActionListener(e -> {
+ this.params.set("graphComparisonType", "CPDAG");
+ menu.setText("Compare to CPDAG...");
+ menu.setBackground(Color.YELLOW);
- add(pane);
+ this.area.setText(comparison.getComparisonString());
+ this.area.moveCaretPosition(0);
+ this.area.setSelectionStart(0);
+ this.area.setSelectionEnd(0);
+
+ this.area.repaint();
+
+ });
+
+ pag.addActionListener(e -> {
+ this.params.set("graphComparisonType", "PAG");
+ menu.setText("Compare to PAG...");
+ menu.setBackground(Color.GREEN.brighter().brighter());
+
+ this.area.setText(comparison.getComparisonString());
+ this.area.moveCaretPosition(0);
+ this.area.setSelectionStart(0);
+ this.area.setSelectionEnd(0);
+ this.area.repaint();
+ });
+
+ return menubar;
}
+ private String tableTextWithHeader() {
+ return this.comparison.getComparisonString();
+ }
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemEstimatorEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemEstimatorEditor.java
index dbbecd01e7..e259d9774a 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemEstimatorEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemEstimatorEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.SemGraph;
import edu.cmu.tetrad.sem.GeneralizedSemIm;
@@ -224,7 +224,7 @@ public Map getModelNodesToDisplay() {
return graphicalEditor().getWorkbench().getModelNodesToDisplay();
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return graphicalEditor().getWorkbench().getKnowledge();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemImEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemImEditor.java
index 20f0200366..26b22fedfb 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemImEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemImEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.SemGraph;
import edu.cmu.tetrad.sem.GeneralizedSemIm;
@@ -355,7 +355,7 @@ public Map getModelNodesToDisplay() {
return graphicalEditor().getWorkbench().getModelNodesToDisplay();
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return graphicalEditor().getWorkbench().getKnowledge();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemPmEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemPmEditor.java
index f6957fb9b4..7a3a59e2f2 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemPmEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GeneralizedSemPmEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetrad.graph.SemGraph;
@@ -342,7 +342,7 @@ public Map getModelNodesToDisplay() {
return graphicalEditor().getWorkbench().getModelNodesToDisplay();
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return graphicalEditor().getWorkbench().getKnowledge();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphEditor.java
index 1dc7a37490..b89680ed2f 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.IndTestDSep;
import edu.cmu.tetrad.search.IndependenceTest;
@@ -183,7 +183,7 @@ public Map getModelNodesToDisplay() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return null;
}
@@ -234,7 +234,7 @@ private void initUI(GraphWrapper graphWrapper) {
JMenuBar menuBar = createGraphMenuBar();
// Add the model selection to top if multiple models
- modelSelectin(graphWrapper);
+ modelSelection(graphWrapper);
// topBox Left side toolbar
GraphToolbar graphToolbar = new GraphToolbar(getWorkbench());
@@ -344,7 +344,7 @@ private void updateBootstrapTable(Graph graph) {
* Creates the UI component for choosing from multiple graph models
*
*/
- private void modelSelectin(GraphWrapper graphWrapper) {
+ private void modelSelection(GraphWrapper graphWrapper) {
int numModels = graphWrapper.getNumModels();
if (numModels > 1) {
@@ -396,7 +396,7 @@ public void enableEditing(boolean enableEditing) {
private JMenuBar createGraphMenuBar() {
JMenuBar menuBar = new JMenuBar();
- JMenu fileMenu = new GraphFileMenu(this, getWorkbench());
+ JMenu fileMenu = new GraphFileMenu(this, getWorkbench(), false);
JMenu editMenu = createEditMenu();
JMenu graphMenu = createGraphMenu();
@@ -408,6 +408,31 @@ private JMenuBar createGraphMenuBar() {
return menuBar;
}
+ JMenuBar createGraphMenuBarNoEditing() {
+ JMenuBar menuBar = new JMenuBar();
+ JMenu file = new JMenu("File");
+ file.add(new SaveComponentImage(this.workbench, "Save Graph Image..."));
+
+ menuBar.add(file);
+
+ JMenu graph = new JMenu("Graph");
+
+ graph.add(new GraphPropertiesAction(this.workbench));
+ graph.add(new PathsAction(this.workbench));
+ graph.add(new UnderliningsAction(this.workbench));
+
+ graph.add(new JMenuItem(new SelectDirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectBidirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectUndirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectLatentsAction(this.workbench)));
+ graph.add(new PagTypeSetter(getWorkbench()));
+
+ menuBar.add(graph);
+
+ return menuBar;
+ }
+
+
/**
* Creates the "file" menu, which allows the user to load, save, and post
* workbench models.
@@ -469,7 +494,7 @@ private JMenu createGraphMenu() {
editor.setParams(this.parameters);
EditorWindow editorWindow = new EditorWindow(editor, "Edit Random Graph Parameters",
- "Done", false, this);
+ "Done", true, this);
DesktopController.getInstance().addEditorWindow(editorWindow, JLayeredPane.PALETTE_LAYER);
editorWindow.pack();
@@ -500,9 +525,11 @@ public void internalFrameClosed(InternalFrameEvent e1) {
});
});
+ graph.add(new JMenuItem(new SelectDirectedAction(getWorkbench())));
graph.add(new JMenuItem(new SelectBidirectedAction(getWorkbench())));
graph.add(new JMenuItem(new SelectUndirectedAction(getWorkbench())));
graph.add(new JMenuItem(new SelectLatentsAction(getWorkbench())));
+ graph.add(new PagTypeSetter(getWorkbench()));
// Only show these menu options for graph that has interventional nodes - Zhou
if (isHasInterventional()) {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphFileMenu.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphFileMenu.java
index 09d579211a..20db235b52 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphFileMenu.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphFileMenu.java
@@ -31,19 +31,22 @@
* @author Aaron Powers
* @author Joseph Ramsey
*/
-final class GraphFileMenu extends JMenu {
+public final class GraphFileMenu extends JMenu {
private static final long serialVersionUID = 8003709852565658589L;
- public GraphFileMenu(GraphEditable editable, JComponent comp) {
+ public GraphFileMenu(GraphEditable editable, JComponent comp, boolean saveOnly) {
super("File");
- JMenu load = new JMenu("Load...");
- add(load);
+ if (!saveOnly) {
+ JMenu load = new JMenu("Load...");
+ add(load);
- load.add(new LoadGraph(editable, "XML..."));
- load.add(new LoadGraphTxt(editable, "Text..."));
- load.add(new LoadGraphJson(editable, "Json..."));
+ load.add(new LoadGraph(editable, "XML..."));
+ load.add(new LoadGraphTxt(editable, "Text..."));
+ load.add(new LoadGraphJson(editable, "Json..."));
+ load.add(new LoadGraphPcalg(editable, "PCALG..."));
+ }
JMenu save = new JMenu("Save...");
add(save);
@@ -53,6 +56,7 @@ public GraphFileMenu(GraphEditable editable, JComponent comp) {
save.add(new SaveGraph(editable, "Json...", SaveGraph.Type.json));
save.add(new SaveGraph(editable, "R...", SaveGraph.Type.r));
save.add(new SaveGraph(editable, "Dot...", SaveGraph.Type.dot));
+ save.add(new SaveGraph(editable, "PCALG...", SaveGraph.Type.pcalg));
addSeparator();
add(new SaveComponentImage(comp, "Save Graph Image..."));
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphPropertiesAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphPropertiesAction.java
index 9017543878..9ba0b331e1 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphPropertiesAction.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/GraphPropertiesAction.java
@@ -39,7 +39,7 @@
*
* @author Joseph Ramsey jdramsey@andrew.cmu.edu
*/
-class GraphPropertiesAction extends AbstractAction implements ClipboardOwner {
+public class GraphPropertiesAction extends AbstractAction implements ClipboardOwner {
private GraphWorkbench workbench;
/**
@@ -83,35 +83,88 @@ public void actionPerformed(ActionEvent e) {
}
}
+ java.util.List nodes = getGraph().getNodes();
+
+ int numTwoCycles = 0;
int numDirectedEdges = 0;
int numBidirectedEdges = 0;
int numUndirectedEdges = 0;
- for (Edge edge : getGraph().getEdges()) {
- if (Edges.isDirectedEdge(edge)) numDirectedEdges++;
- else if (Edges.isBidirectedEdge(edge)) numBidirectedEdges++;
- else if (Edges.isUndirectedEdge(edge)) numUndirectedEdges++;
+ for (int i = 0; i < nodes.size(); i++) {
+ for (int j = i; j < nodes.size(); j++) {
+ Node n1 = nodes.get(i);
+ Node n2 = nodes.get(j);
+
+ if (getGraph().getDirectedEdge(n1, n2) != null && getGraph().getDirectedEdge(n2, n1) != null) {
+ numTwoCycles++;
+ } else if (getGraph().getEdges(n1, n2).size() == 1) {
+ if (getGraph().getEdge(n1, n2).isDirected()) {
+ numDirectedEdges++;
+ } else if (Edges.isBidirectedEdge(getGraph().getEdge(n1, n2))) {
+ numBidirectedEdges++;
+ } else if (Edges.isUndirectedEdge(getGraph().getEdge(n1, n2))) {
+ numUndirectedEdges++;
+ }
+ }
+ }
}
+// for (Edge edge : getGraph().getEdges()) {
+// if (Edges.isDirectedEdge(edge)) {
+// if (getGraph().containsEdge(edge) && getGraph().containsEdge(edge.reverse())) {
+// numTwoCycles++;
+// } else {
+// numDirectedEdges++;
+// }
+// }
+// else if (Edges.isBidirectedEdge(edge)) numBidirectedEdges++;
+// else if (Edges.isUndirectedEdge(edge)) numUndirectedEdges++;
+// }
+
boolean cyclic = getGraph().existsDirectedCycle();
+ int numAdjacencies = 0;
+
+ for (
+ int i = 0; i < nodes.size(); i++) {
+ for (int j = i; j < nodes.size(); j++) {
+ if (getGraph().isAdjacentTo(nodes.get(i), nodes.get(j))) {
+ numAdjacencies++;
+ }
+ }
+ }
+
+ int numEdges = 0;
+
+ for (int i = 0; i < nodes.size(); i++) {
+ for (int j = i; j < nodes.size(); j++) {
+ numEdges += getGraph().getEdges(nodes.get(i), nodes.get(j)).size();
+ }
+ }
+
JTextArea textArea = new JTextArea();
JScrollPane scroll = new JScrollPane(textArea);
- scroll.setPreferredSize(new Dimension(300, 300));
+ scroll.setPreferredSize(new Dimension(400, 300));
- textArea.append("\nNumber of nodes: " + getGraph().getNumNodes());
+ textArea.append("\nNumber of nodes: " + getGraph(). getNumNodes());
textArea.append("\nNumber of latents: " + numLatents);
- textArea.append("\nNumber of edges: " + getGraph().getNumEdges());
- textArea.append("\nNumber of directed edges: " + numDirectedEdges);
+ textArea.append("\nNumber of edges: " + numEdges);
+ textArea.append("\nNumber of adjacencies: " + numAdjacencies);
+ textArea.append("\nNumber of two-cycles: " + numTwoCycles);
+ textArea.append("\nNumber of directed edges not in two cycles: " + numDirectedEdges);
textArea.append("\nNumber of bidirected edges: " + numBidirectedEdges);
textArea.append("\nNumber of undirected edges: " + numUndirectedEdges);
- textArea.append("\nMax degree: " + getGraph().getConnectivity());
+ textArea.append("\nMax degree: " +
+
+ getGraph().
+
+ getConnectivity());
textArea.append("\nMax indegree: " + maxIndegree);
textArea.append("\nMax outdegree: " + maxOutdegree);
- int numEdges = getGraph().getNumEdges();
+ // int numEdges = getGraph().getNumEdges();
int numVars = getGraph().getNumNodes();
- double avgDegree = 2 * numEdges / ((double) (numVars));
+ double avgDegree = 2 * numAdjacencies / ((double) (numVars));
double density = avgDegree / (numVars - 1);
textArea.append("\nAverage degree: " + NumberFormat.getInstance().format(avgDegree));
@@ -129,6 +182,12 @@ public void actionPerformed(ActionEvent e) {
panel.setLayout(new BorderLayout());
panel.add(b);
+// Node x = getGraph().getNode("X5");
+
+ for (Node x : getGraph().getNodes()) {
+ System.out.println("district(" + x + ") = " + GraphUtils.district(x, getGraph()));
+ }
+
EditorWindow window = new EditorWindow(panel,
"Graph Properties", "Close", false, workbench);
DesktopController.getInstance().addEditorWindow(window, JLayeredPane.PALETTE_LAYER);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/IndependenceFactsEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/IndependenceFactsEditor.java
index b5be25b80f..7853bcebb1 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/IndependenceFactsEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/IndependenceFactsEditor.java
@@ -26,7 +26,7 @@
import edu.cmu.tetrad.search.IndependenceResult;
import edu.cmu.tetrad.search.IndependenceTest;
import edu.cmu.tetrad.util.ChoiceGenerator;
-import edu.cmu.tetrad.util.DepthChoiceGenerator;
+import edu.cmu.tetrad.util.SublistGenerator;
import edu.cmu.tetradapp.model.IndTestModel;
import edu.cmu.tetradapp.model.IndTestProducer;
import edu.cmu.tetradapp.model.IndependenceResultIndFacts;
@@ -596,7 +596,7 @@ private void generateResults() {
List vars3 = new ArrayList<>(vars2);
vars3.removeAll(s3);
- DepthChoiceGenerator gen3 = new DepthChoiceGenerator(vars3.size(), plusIndices.length);
+ SublistGenerator gen3 = new SublistGenerator(vars3.size(), plusIndices.length);
int[] choice3;
while ((choice3 = gen3.next()) != null) {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/LoadGraphPcalg.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/LoadGraphPcalg.java
new file mode 100644
index 0000000000..62d2a20148
--- /dev/null
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/LoadGraphPcalg.java
@@ -0,0 +1,87 @@
+///////////////////////////////////////////////////////////////////////////////
+// For information as to what this class does, see the Javadoc, below. //
+// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, //
+// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard //
+// Scheines, Joseph Ramsey, and Clark Glymour. //
+// //
+// This program is free software; you can redistribute it and/or modify //
+// it under the terms of the GNU General Public License as published by //
+// the Free Software Foundation; either version 2 of the License, or //
+// (at your option) any later version. //
+// //
+// This program is distributed in the hope that it will be useful, //
+// but WITHOUT ANY WARRANTY; without even the implied warranty of //
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the //
+// GNU General Public License for more details. //
+// //
+// You should have received a copy of the GNU General Public License //
+// along with this program; if not, write to the Free Software //
+// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA //
+///////////////////////////////////////////////////////////////////////////////
+
+package edu.cmu.tetradapp.editor;
+
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.graph.GraphUtils;
+
+import javax.swing.*;
+import java.awt.*;
+import java.awt.event.ActionEvent;
+import java.io.File;
+import java.util.prefs.Preferences;
+
+/**
+ * @author Joseph Ramsey jdramsey@andrew.cmu.edu
+ */
+class LoadGraphPcalg extends AbstractAction {
+
+ /**
+ * The component whose image is to be saved.
+ */
+ private final GraphEditable graphEditable;
+
+ public LoadGraphPcalg(GraphEditable graphEditable, String title) {
+ super(title);
+
+ if (graphEditable == null) {
+ throw new NullPointerException("Component must not be null.");
+ }
+
+ this.graphEditable = graphEditable;
+ }
+
+ /**
+ * Performs the action of loading a session from a file.
+ */
+ public void actionPerformed(ActionEvent e) {
+ JFileChooser chooser = LoadGraphPcalg.getJFileChooser();
+ chooser.setFileSelectionMode(JFileChooser.FILES_AND_DIRECTORIES);
+ chooser.showOpenDialog((Component) this.graphEditable);
+
+ File file = chooser.getSelectedFile();
+
+ if (file == null) {
+ System.out.println("File was null.");
+ return;
+ }
+
+ Preferences.userRoot().put("fileSaveLocation", file.getParent());
+
+ Graph graph = GraphUtils.loadGraphPcalg(file);
+ GraphUtils.circleLayout(graph, 200, 200, 150);
+ this.graphEditable.setGraph(graph);
+ }
+
+ private static JFileChooser getJFileChooser() {
+ JFileChooser chooser = new JFileChooser();
+ String sessionSaveLocation =
+ Preferences.userRoot().get("fileSaveLocation", "");
+ chooser.setCurrentDirectory(new File(sessionSaveLocation));
+ chooser.resetChoosableFileFilters();
+ chooser.setFileSelectionMode(JFileChooser.FILES_AND_DIRECTORIES);
+ return chooser;
+ }
+}
+
+
+
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MarkovBlanketSearchEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MarkovBlanketSearchEditor.java
index d669b3fcb2..7464216418 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MarkovBlanketSearchEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MarkovBlanketSearchEditor.java
@@ -23,8 +23,7 @@
import edu.cmu.tetrad.data.DataModel;
import edu.cmu.tetrad.data.DataSet;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.search.IndTestType;
@@ -143,7 +142,7 @@ public void watch() {
setErrorMessage(null);
if (!MarkovBlanketSearchEditor.this.knowledgeMessageShown) {
- IKnowledge knowledge = (IKnowledge) getAlgorithmRunner().getParams().get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) getAlgorithmRunner().getParams().get("knowledge", new Knowledge());
if (!knowledge.isEmpty()) {
JOptionPane.showMessageDialog(
JOptionUtils.centeringComp(),
@@ -338,7 +337,7 @@ private JMenuBar menuBar() {
JMenuBar menuBar = new JMenuBar();
JMenu file = new JMenu("File");
file.add(new JMenuItem(new SaveDataAction(this)));
- file.add(new GraphFileMenu(this, getWorkbench()));
+ file.add(new GraphFileMenu(this, getWorkbench(), false));
// file.add(new SaveGraph(this, "Save Graph..."));
JMenu edit = new JMenu("Edit");
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MarkovCheckEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MarkovCheckEditor.java
index a0af38e90e..7b8166579a 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MarkovCheckEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MarkovCheckEditor.java
@@ -45,8 +45,10 @@
import java.awt.event.MouseAdapter;
import java.awt.event.MouseEvent;
import java.text.NumberFormat;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.Comparator;
import java.util.List;
-import java.util.*;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ForkJoinPool;
@@ -63,14 +65,17 @@
public class MarkovCheckEditor extends JPanel {
private Graph dag;
private final MarkovCheckIndTestModel model;
- private AbstractTableModel tableModel;
+ private AbstractTableModel tableModelIndep;
+ private AbstractTableModel tableModelDep;
private int sortDir;
private int lastSortCol;
private final NumberFormat nf = NumberFormatUtil.getInstance().getNumberFormat();
private boolean parallelized = true;
private final IndependenceTest test;
- private double fractionDependent = Double.NaN;
- private JLabel fractionDepLabel;
+ private double fractionDependentIndep = Double.NaN;
+ private double fractionDependentDep = Double.NaN;
+ private JLabel fractionDepLabelIndep;
+ private JLabel fractionDepLabelDep;
public MarkovCheckEditor(MarkovCheckIndTestModel model) {
if (model == null) {
@@ -124,7 +129,13 @@ public MarkovCheckEditor(MarkovCheckIndTestModel model) {
this.dag = sourceGraph;
model.setVars(dag.getNodeNames());
- buildGui();
+ JPanel indep = buildGuiIndep();
+ JPanel dep = buildGuiDep();
+
+ JTabbedPane pane = new JTabbedPane();
+ pane.addTab("Should be Independent", indep);
+ pane.addTab("Should be Dependent", dep);
+ add(pane);
}
//========================PUBLIC METHODS==========================//
@@ -132,16 +143,16 @@ public MarkovCheckEditor(MarkovCheckIndTestModel model) {
/**
* Performs the action of opening a session from a file.
*/
- private void buildGui() {
+ private JPanel buildGuiDep() {
JButton list = new JButton("CHECK");
list.setFont(new Font("Dialog", Font.BOLD, 14));
- list.addActionListener(e -> generateResults());
+ list.addActionListener(e -> generateResults(false));
JButton clear = new JButton("Clear");
clear.setFont(new Font("Dialog", Font.PLAIN, 14));
clear.addActionListener(e -> {
- model.getResults().clear();
+ model.getResults(false).clear();
revalidate();
repaint();
});
@@ -149,14 +160,19 @@ private void buildGui() {
Box b1 = Box.createVerticalBox();
Box b2 = Box.createHorizontalBox();
- b2.add(new JLabel("Checks whether X _||_ Y | parents(x) for y not in (desc(x) U parentx(x)), for "));
- b2.add(new JLabel(getIndependenceTest().toString()));
+ b2.add(new JLabel("Checks whether X ~_||_ Y | parents(X) for Y in desc(X)"));
b2.add(Box.createHorizontalGlue());
b1.add(b2);
+ Box b2a = Box.createHorizontalBox();
+ b2a.add(new JLabel("Test: "));
+ b2a.add(new JLabel(getIndependenceTest().toString()));
+ b2a.add(Box.createHorizontalGlue());
+ b1.add(b2a);
+
b1.add(Box.createVerticalStrut(5));
- this.tableModel = new AbstractTableModel() {
+ this.tableModelDep = new AbstractTableModel() {
public String getColumnName(int column) {
if (column == 0) {
return "Index";
@@ -176,20 +192,20 @@ public int getColumnCount() {
}
public int getRowCount() {
- return model.getResults().size();
+ return model.getResults(false).size();
}
public Object getValueAt(int rowIndex, int columnIndex) {
- if (rowIndex > model.getResults().size()) return null;
+ if (rowIndex > model.getResults(false).size()) return null;
if (columnIndex == 0) {
return rowIndex + 1;
}
if (columnIndex == 1) {
- return model.getResults().get(rowIndex).getFact();
+ return model.getResults(false).get(rowIndex).getFact();
}
- IndependenceResult result = model.getResults().get(rowIndex);
+ IndependenceResult result = model.getResults(false).get(rowIndex);
if (columnIndex == 2) {
if (getIndependenceTest() instanceof IndTestDSep) {
@@ -226,7 +242,7 @@ public Class getColumnClass(int columnIndex) {
}
};
- JTable table = new JTable(tableModel);
+ JTable table = new JTable(tableModelDep);
table.getColumnModel().getColumn(0).setMinWidth(40);
table.getColumnModel().getColumn(0).setMaxWidth(40);
@@ -250,7 +266,7 @@ public void mouseClicked(MouseEvent e) {
int col = header.columnAtPoint(point);
int sortCol = header.getTable().convertColumnIndexToModel(col);
- MarkovCheckEditor.this.sortByColumn(sortCol);
+ MarkovCheckEditor.this.sortByColumn(sortCol, false);
}
});
@@ -267,7 +283,7 @@ public void mouseClicked(MouseEvent e) {
showHistogram.addMouseListener(new MouseAdapter() {
@Override
public void mouseClicked(MouseEvent e) {
- JPanel component = createHistogramPanel();
+ JPanel component = createHistogramPanel(false);
EditorWindow editorWindow = new EditorWindow(component, "Histogram", "Close", false, MarkovCheckEditor.this);
DesktopController.getInstance().addEditorWindow(editorWindow, JLayeredPane.PALETTE_LAYER);
editorWindow.pack();
@@ -288,28 +304,211 @@ public void mouseClicked(MouseEvent e) {
int dependent = 0;
- for (IndependenceResult result : model.getResults()) {
+ for (IndependenceResult result : model.getResults(false)) {
if (result.dependent() && !Double.isNaN(result.getPValue())) dependent++;
}
- fractionDependent = dependent / (double) model.getResults().size();
+ fractionDependentDep = dependent / (double) model.getResults(false).size();
- fractionDepLabel = new JLabel("% dependent = "
- + ((Double.isNaN(fractionDependent)
- ? "-" : NumberFormatUtil.getInstance().getNumberFormat().format(fractionDependent))));
+ fractionDepLabelDep = new JLabel("% dependent = "
+ + ((Double.isNaN(fractionDependentDep)
+ ? "-" : NumberFormatUtil.getInstance().getNumberFormat().format(fractionDependentDep))));
- b5.add(fractionDepLabel);
+ b5.add(fractionDepLabelDep);
b1.add(b5);
- JPanel panel = this;
+ JPanel panel = new JPanel();
panel.setLayout(new BorderLayout());
panel.add(b1, BorderLayout.CENTER);
panel.setBorder(new EmptyBorder(10, 10, 10, 10));
+ return panel;
+ }
+
+ private JPanel buildGuiIndep() {
+ JButton list = new JButton("CHECK");
+ list.setFont(new Font("Dialog", Font.BOLD, 14));
+
+ list.addActionListener(e -> generateResults(true));
+
+ JButton clear = new JButton("Clear");
+ clear.setFont(new Font("Dialog", Font.PLAIN, 14));
+ clear.addActionListener(e -> {
+ model.getResults(true).clear();
+ revalidate();
+ repaint();
+ });
+
+ Box b1 = Box.createVerticalBox();
+
+ Box b2 = Box.createHorizontalBox();
+ b2.add(new JLabel("Checks whether X _||_ Y | parents(X) for Y not in (desc(X) U parentx(X))"));
+ b2.add(Box.createHorizontalGlue());
+ b1.add(b2);
+
+ Box b2a = Box.createHorizontalBox();
+ b2a.add(new JLabel("Test: "));
+ b2a.add(new JLabel(getIndependenceTest().toString()));
+ b2a.add(Box.createHorizontalGlue());
+ b1.add(b2a);
+
+
+ b1.add(Box.createVerticalStrut(5));
+
+ this.tableModelIndep = new AbstractTableModel() {
+ public String getColumnName(int column) {
+ if (column == 0) {
+ return "Index";
+ } else if (column == 1) {
+ return "Fact";
+ } else if (column == 2) {
+ return "Result";
+ } else if (column == 3) {
+ return "P-value";
+ }
+
+ return null;
+ }
+
+ public int getColumnCount() {
+ return 4;//2 + MarkovFactsEditor.this.indTestProducers.size();
+ }
+
+ public int getRowCount() {
+ return model.getResults(true).size();
+ }
+
+ public Object getValueAt(int rowIndex, int columnIndex) {
+ if (rowIndex > model.getResults(true).size()) return null;
+
+ if (columnIndex == 0) {
+ return rowIndex + 1;
+ }
+ if (columnIndex == 1) {
+ return model.getResults(true).get(rowIndex).getFact();
+ }
+
+ IndependenceResult result = model.getResults(true).get(rowIndex);
+
+ if (columnIndex == 2) {
+ if (getIndependenceTest() instanceof IndTestDSep) {
+ if (result.independent()) {
+ return "D-SEPARATED";
+ } else {
+ return "d-connected";
+ }
+ } else {
+ if (result.independent()) {
+ return "INDEPENDENT";
+ } else {
+ return "dependent";
+ }
+ }
+ }
+
+ if (columnIndex == 3) {
+ return nf.format(result.getPValue());
+ }
+
+ return null;
+ }
+
+ public Class getColumnClass(int columnIndex) {
+ if (columnIndex == 0) {
+ return Number.class;
+ }
+ if (columnIndex == 1) {
+ return String.class;
+ } else {
+ return Number.class;
+ }
+ }
+ };
+
+ JTable table = new JTable(tableModelIndep);
+
+ table.getColumnModel().getColumn(0).setMinWidth(40);
+ table.getColumnModel().getColumn(0).setMaxWidth(40);
+ table.getColumnModel().getColumn(1).setMinWidth(200);
+ table.getColumnModel().getColumn(1).setCellRenderer(new Renderer());
+ table.getColumnModel().getColumn(2).setMinWidth(100);
+ table.getColumnModel().getColumn(2).setMaxWidth(100);
+ table.getColumnModel().getColumn(3).setMinWidth(100);
+ table.getColumnModel().getColumn(3).setMaxWidth(100);
+
+ table.getColumnModel().getColumn(2).setCellRenderer(new Renderer());
+ table.getColumnModel().getColumn(3).setCellRenderer(new Renderer());
+
+
+ JTableHeader header = table.getTableHeader();
+
+ header.addMouseListener(new MouseAdapter() {
+ public void mouseClicked(MouseEvent e) {
+ JTableHeader header = (JTableHeader) e.getSource();
+ Point point = e.getPoint();
+ int col = header.columnAtPoint(point);
+ int sortCol = header.getTable().convertColumnIndexToModel(col);
+
+ MarkovCheckEditor.this.sortByColumn(sortCol, true);
+ }
+ });
+
+ JScrollPane scroll = new JScrollPane(table);
+ scroll.setPreferredSize(new Dimension(400, 400));
+ b1.add(scroll);
+
+ Box b4 = Box.createHorizontalBox();
+ b4.add(Box.createGlue());
+ b4.add(Box.createHorizontalStrut(10));
+
+ JButton showHistogram = new JButton("Show P-Value Histogram");
+ showHistogram.setFont(new Font("Dialog", Font.PLAIN, 14));
+ showHistogram.addMouseListener(new MouseAdapter() {
+ @Override
+ public void mouseClicked(MouseEvent e) {
+ JPanel component = createHistogramPanel(true);
+ EditorWindow editorWindow = new EditorWindow(component, "Histogram", "Close", false, MarkovCheckEditor.this);
+ DesktopController.getInstance().addEditorWindow(editorWindow, JLayeredPane.PALETTE_LAYER);
+ editorWindow.pack();
+ editorWindow.setVisible(true);
+ }
+ });
+
+ b4.add(Box.createHorizontalGlue());
+ b4.add(clear);
+ b4.add(list);
+ b4.add(showHistogram);
+
+ b1.add(b4);
+ b1.add(Box.createVerticalStrut(10));
+
+ Box b5 = Box.createHorizontalBox();
+ b5.add(Box.createGlue());
+
+ int dependent = 0;
+
+ for (IndependenceResult result : model.getResults(true)) {
+ if (result.dependent() && !Double.isNaN(result.getPValue())) dependent++;
+ }
+
+ fractionDependentIndep = dependent / (double) model.getResults(true).size();
+
+ fractionDepLabelIndep = new JLabel("% dependent = "
+ + ((Double.isNaN(fractionDependentIndep)
+ ? "-" : NumberFormatUtil.getInstance().getNumberFormat().format(fractionDependentIndep))));
+
+ b5.add(fractionDepLabelIndep);
+ b1.add(b5);
+
+ JPanel panel = new JPanel();
+ panel.setLayout(new BorderLayout());
+ panel.add(b1, BorderLayout.CENTER);
+ panel.setBorder(new EmptyBorder(10, 10, 10, 10));
+ return panel;
}
//=============================PRIVATE METHODS=======================//
- private void sortByColumn(int sortCol) {
+ private void sortByColumn(int sortCol, boolean indep) {
if (sortCol == this.getLastSortCol()) {
this.setSortDir(-1 * this.getSortDir());
} else {
@@ -317,10 +516,14 @@ private void sortByColumn(int sortCol) {
}
this.setLastSortCol(sortCol);
- model.getResults().sort(Comparator.comparing(
+ model.getResults(indep).sort(Comparator.comparing(
IndependenceResult::getFact));
- tableModel.fireTableDataChanged();
+ if (indep) {
+ tableModelIndep.fireTableDataChanged();
+ } else {
+ tableModelDep.fireTableDataChanged();
+ }
}
static class Renderer extends DefaultTableCellRenderer {
@@ -350,14 +553,18 @@ public Component getTableCellRendererComponent(JTable table, Object value, boole
}
}
- private void generateResults() {
+ private void generateResults(boolean indep) {
Window owner = (Window) JOptionUtils.centeringComp().getTopLevelAncestor();
new WatchedProcess(owner) {
public void watch() {
if (model.getVars().size() < 2) {
- tableModel.fireTableDataChanged();
+ if (indep) {
+ tableModelIndep.fireTableDataChanged();
+ } else {
+ tableModelDep.fireTableDataChanged();
+ }
return;
}
@@ -376,8 +583,14 @@ public void watch() {
System.out.println("Node " + x + " parents = " + z
+ " non-descendants = " + nondesc);
- for (Node y : nondesc) {
- facts.add(new IndependenceFact(x, y, z));
+ if (indep) {
+ for (Node y : nondesc) {
+ facts.add(new IndependenceFact(x, y, z));
+ }
+ } else {
+ for (Node y : desc) {
+ facts.add(new IndependenceFact(x, y, z));
+ }
}
}
@@ -412,6 +625,12 @@ public List call() {
test.setVerbose(verbose);
results.add(new IndependenceResult(fact, indep, pValue));
+
+ if (indep) {
+ tableModelIndep.fireTableDataChanged();
+ } else {
+ tableModelDep.fireTableDataChanged();
+ }
}
return results;
@@ -428,7 +647,7 @@ public List call() {
if (!parallelized) {
List _results = task.call();
- model.getResults().addAll(_results);
+ model.getResults(indep).addAll(_results);
} else {
tasks.add(task);
}
@@ -439,7 +658,7 @@ public List call() {
for (Future> future : theseResults) {
try {
- model.getResults().addAll(future.get());
+ model.getResults(indep).addAll(future.get());
} catch (InterruptedException | ExecutionException e) {
throw new RuntimeException(e);
}
@@ -448,17 +667,31 @@ public List call() {
int dependent = 0;
- for (IndependenceResult result : model.getResults()) {
+ for (IndependenceResult result : model.getResults(indep)) {
if (result.dependent() && !Double.isNaN(result.getPValue())) dependent++;
}
- fractionDependent = dependent / (double) model.getResults().size();
+ if (indep) {
+ fractionDependentIndep = dependent / (double) model.getResults(indep).size();
+ } else {
+ fractionDependentDep = dependent / (double) model.getResults(indep).size();
+ }
- fractionDepLabel.setText("% dependent = "
- + ((Double.isNaN(fractionDependent)
- ? "-" : NumberFormatUtil.getInstance().getNumberFormat().format(fractionDependent))));
+ if (indep) {
+ fractionDepLabelIndep.setText("% dependent = "
+ + ((Double.isNaN(fractionDependentIndep)
+ ? "-" : NumberFormatUtil.getInstance().getNumberFormat().format(fractionDependentIndep))));
+ } else {
+ fractionDepLabelDep.setText("% dependent = "
+ + ((Double.isNaN(fractionDependentDep)
+ ? "-" : NumberFormatUtil.getInstance().getNumberFormat().format(fractionDependentDep))));
+ }
- tableModel.fireTableDataChanged();
+ if (indep) {
+ tableModelIndep.fireTableDataChanged();
+ } else {
+ tableModelDep.fireTableDataChanged();
+ }
}
};
}
@@ -497,12 +730,12 @@ private void setSortDir(int sortDir) {
this.sortDir = sortDir;
}
- private JPanel createHistogramPanel() {
- DataSet dataSet = new BoxDataSet(new VerticalDoubleDataBox(model.getResults().size(), 1),
+ private JPanel createHistogramPanel(boolean indep) {
+ DataSet dataSet = new BoxDataSet(new VerticalDoubleDataBox(model.getResults(indep).size(), 1),
Collections.singletonList(new ContinuousVariable("P-Values")));
- for (int i = 0; i < model.getResults().size(); i++) {
- dataSet.setDouble(i, 0, model.getResults().get(i).getPValue());
+ for (int i = 0; i < model.getResults(indep).size(); i++) {
+ dataSet.setDouble(i, 0, model.getResults(indep).get(i).getPValue());
}
Histogram histogram = new Histogram(dataSet);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MisclassificationsEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MisclassificationsEditor.java
index a7dd91023d..eafcb10c38 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MisclassificationsEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/MisclassificationsEditor.java
@@ -21,12 +21,15 @@
package edu.cmu.tetradapp.editor;
import edu.cmu.tetrad.graph.Graph;
-import edu.cmu.tetradapp.model.GraphWrapper;
+import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetradapp.model.Misclassifications;
+import org.jetbrains.annotations.NotNull;
import javax.swing.*;
import java.awt.*;
+import static edu.cmu.tetrad.graph.GraphUtils.getComparisonGraph;
+
/**
* Provides a little display/editor for notes in the session workbench. This may
* be elaborated in the future to allow marked up text.
@@ -41,62 +44,121 @@ public class MisclassificationsEditor extends JPanel {
* The model for the note.
*/
private final Misclassifications comparison;
+ private JTextArea area;
+
+ private final Parameters params;
/**
* Constructs the editor given the model
*/
public MisclassificationsEditor(Misclassifications comparison) {
this.comparison = comparison;
+ this.params = comparison.getParams();
setup();
}
private void setup() {
- java.util.List referenceGraphs = this.comparison.getReferenceGraphs();
- JTabbedPane pane = new JTabbedPane(SwingConstants.LEFT);
+ setLayout(new BorderLayout());
- for (int i = 0; i < referenceGraphs.size(); i++) {
- JTabbedPane pane2 = new JTabbedPane(SwingConstants.TOP);
- String compareString = this.comparison.getComparisonString(i);
+ JPanel pane = new JPanel();
- JPanel panel = new JPanel();
+ Font font = new Font("Monospaced", Font.PLAIN, 14);
+ area = new JTextArea();
+ area.setText(this.comparison.getComparisonString());
- Font font = new Font("Monospaced", Font.PLAIN, 14);
- JTextArea textPane = new JTextArea();
- textPane.setText(compareString);
+ area.setFont(font);
- textPane.setFont(font);
+ JScrollPane scrollTextPane = new JScrollPane(area);
+ scrollTextPane.setPreferredSize(new Dimension(500, 600));
- JScrollPane scroll = new JScrollPane(textPane);
- scroll.setPreferredSize(new Dimension(400, 400));
+ pane.add(scrollTextPane, new BorderLayout());
- panel.add(Box.createVerticalStrut(10));
+ add(pane);
- Box box = Box.createHorizontalBox();
- panel.add(box);
- panel.add(Box.createVerticalStrut(10));
+ add(menubar(), BorderLayout.NORTH);
+ }
- Box box1 = Box.createHorizontalBox();
- box1.add(new JLabel("Graph Comparison: "));
- box1.add(Box.createHorizontalGlue());
- add(box1);
- setLayout(new BorderLayout());
+ @NotNull
+ private JMenuBar menubar() {
+ JMenuBar menubar = new JMenuBar();
+ JMenu menu = new JMenu("Compare To...");
+ JMenuItem graph = new JCheckBoxMenuItem("DAG");
+ graph.setBackground(Color.WHITE);
+ JMenuItem cpdag = new JCheckBoxMenuItem("CPDAG");
+ cpdag.setBackground(Color.YELLOW);
+ JMenuItem pag = new JCheckBoxMenuItem("PAG");
+ pag.setBackground(Color.GREEN.brighter().brighter());
+
+ ButtonGroup group = new ButtonGroup();
+ group.add(graph);
+ group.add(cpdag);
+ group.add(pag);
+
+ menu.add(graph);
+ menu.add(cpdag);
+ menu.add(pag);
+
+ menubar.add(menu);
+
+ switch (this.params.getString("graphComparisonType")) {
+ case "CPDAG":
+ menu.setText("Compare to CPDAG...");
+ cpdag.setSelected(true);
+ break;
+ case "PAG":
+ menu.setText("Compare to PAG...");
+ pag.setSelected(true);
+ break;
+ default:
+ menu.setText("Compare to DAG...");
+ graph.setSelected(true);
+ break;
+ }
- pane2.add("Comparison", scroll);
+ graph.addActionListener(e -> {
+ this.params.set("graphComparisonType", "DAG");
+ menu.setText("Compare to DAG...");
+ menu.setBackground(Color.WHITE);
+ Graph referenceGraph = getComparisonGraph(this.comparison.getReferenceGraph(), this.params);
- GraphEditor graphEditor = new GraphEditor(new GraphWrapper(this.comparison.getTargetGraphs().get(i)));
- graphEditor.enableEditing(false);
- pane2.add("Target Graph", graphEditor.getWorkbench());
+ this.area.setText(comparison.getComparisonString());
+ this.area.moveCaretPosition(0);
+ this.area.setSelectionStart(0);
+ this.area.setSelectionEnd(0);
- graphEditor = new GraphEditor(new GraphWrapper(this.comparison.getReferenceGraphs().get(i)));
- graphEditor.enableEditing(false);
- pane2.add("True Graph", graphEditor.getWorkbench());
+ this.area.repaint();
- pane.add("" + (i + 1), pane2);
+ });
- }
+ cpdag.addActionListener(e -> {
+ this.params.set("graphComparisonType", "CPDAG");
+ menu.setText("Compare to CPDAG...");
+ menu.setBackground(Color.YELLOW);
- add(pane);
+ this.area.setText(comparison.getComparisonString());
+ this.area.moveCaretPosition(0);
+ this.area.setSelectionStart(0);
+ this.area.setSelectionEnd(0);
+
+ this.area.repaint();
+
+ });
+
+ pag.addActionListener(e -> {
+ this.params.set("graphComparisonType", "PAG");
+ menu.setText("Compare to PAG...");
+ menu.setBackground(Color.GREEN.brighter().brighter());
+
+ this.area.setText(comparison.getComparisonString());
+ this.area.moveCaretPosition(0);
+ this.area.setSelectionStart(0);
+ this.area.setSelectionEnd(0);
+ this.area.repaint();
+ });
+
+ return menubar;
}
+
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/PagTypeSetter.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/PagTypeSetter.java
new file mode 100644
index 0000000000..f609f8c392
--- /dev/null
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/PagTypeSetter.java
@@ -0,0 +1,55 @@
+///////////////////////////////////////////////////////////////////////////////
+// For information as to what this class does, see the Javadoc, below. //
+// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, //
+// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard //
+// Scheines, Joseph Ramsey, and Clark Glymour. //
+// //
+// This program is free software; you can redistribute it and/or modify //
+// it under the terms of the GNU General Public License as published by //
+// the Free Software Foundation; either version 2 of the License, or //
+// (at your option) any later version. //
+// //
+// This program is distributed in the hope that it will be useful, //
+// but WITHOUT ANY WARRANTY; without even the implied warranty of //
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the //
+// GNU General Public License for more details. //
+// //
+// You should have received a copy of the GNU General Public License //
+// along with this program; if not, write to the Free Software //
+// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA //
+///////////////////////////////////////////////////////////////////////////////
+
+package edu.cmu.tetradapp.editor;
+
+import edu.cmu.tetrad.graph.*;
+import edu.cmu.tetradapp.workbench.GraphWorkbench;
+
+import javax.swing.*;
+import java.awt.event.ItemEvent;
+
+/**
+ * Applies PAG coloring to the graph in the workbench.
+ *
+ * @author Joseph Ramsey jdramsey@andrew.cmu.edu
+ */
+public class PagTypeSetter extends JCheckBoxMenuItem {
+
+ /**
+ * Creates a new copy subsession action for the given desktop and
+ * clipboard.
+ */
+ public PagTypeSetter(GraphWorkbench workbench) {
+ super("Set type to PAG");
+
+ if (workbench == null) {
+ throw new NullPointerException("Desktop must not be null.");
+ }
+
+ final GraphWorkbench _workbench = workbench;
+ setSelected(workbench.getGraph().getGraphType() == EdgeListGraph.GraphType.PAG);
+ addItemListener(e -> _workbench.setPag(e.getStateChange() == ItemEvent.SELECTED));
+ }
+}
+
+
+
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/PathsAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/PathsAction.java
index 571e498dce..065b862498 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/PathsAction.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/PathsAction.java
@@ -21,11 +21,12 @@
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.graph.*;
-import edu.cmu.tetrad.util.JOptionUtils;
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.graph.GraphNode;
+import edu.cmu.tetrad.graph.GraphUtils;
+import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetradapp.util.DesktopController;
import edu.cmu.tetradapp.util.IntTextField;
-import edu.cmu.tetradapp.util.WatchedProcess;
import edu.cmu.tetradapp.workbench.GraphWorkbench;
import javax.swing.*;
@@ -45,7 +46,7 @@
*
* @author Joseph Ramsey jdramsey@andrew.cmu.edu
*/
-class PathsAction extends AbstractAction implements ClipboardOwner {
+public class PathsAction extends AbstractAction implements ClipboardOwner {
private final GraphWorkbench workbench;
private List nodes1, nodes2;
private JTextArea textArea;
@@ -91,8 +92,6 @@ public void actionPerformed(ActionEvent e) {
}
Preferences.userRoot().put("pathFrom", node.getName());
-
-// update(graph, textArea, nodes1, nodes2, method);
});
node1Box.setSelectedItem(this.nodes1.get(0));
@@ -119,8 +118,6 @@ public void actionPerformed(ActionEvent e) {
}
Preferences.userRoot().put("pathTo", node.getName());
-
-// update(graph, textArea, nodes1, nodes2, method);
});
node2Box.setSelectedItem(this.nodes2.get(0));
@@ -143,7 +140,6 @@ public void actionPerformed(ActionEvent e) {
maxField.setFilter((value, oldValue) -> {
try {
setMaxLength(value);
-// update(graph, textArea, nodes1, nodes2, method);
return value;
} catch (Exception e14) {
return oldValue;
@@ -155,8 +151,6 @@ public void actionPerformed(ActionEvent e) {
updateButton.addActionListener(e15 -> update(graph, PathsAction.this.textArea,
PathsAction.this.nodes1, PathsAction.this.nodes2, PathsAction.this.method));
- allDirectedPaths(graph, this.textArea, this.nodes1, this.nodes2);
-
Box b = Box.createVerticalBox();
Box b1 = Box.createHorizontalBox();
@@ -190,27 +184,19 @@ public void actionPerformed(ActionEvent e) {
}
private void update(Graph graph, JTextArea textArea, List nodes1, List nodes2, String method) {
- Window owner = (Window) JOptionUtils.centeringComp().getTopLevelAncestor();
-
- WatchedProcess process = new WatchedProcess(owner) {
- public void watch() {
- if ("Directed Paths".equals(method)) {
- textArea.setText("");
- allDirectedPaths(graph, textArea, nodes1, nodes2);
- } else if ("Semidirected Paths".equals(method)) {
- textArea.setText("");
- allSemidirectedPaths(graph, textArea, nodes1, nodes2);
- } else if ("Treks".equals(method)) {
- textArea.setText("");
- allTreks(graph, textArea, nodes1, nodes2);
- } else if ("Adjacents".equals(method)) {
- textArea.setText("");
- adjacentNodes(graph, textArea, nodes1, nodes2);
- }
- }
- };
-
- process.watch();
+ if ("Directed Paths".equals(method)) {
+ textArea.setText("");
+ allDirectedPaths(graph, textArea, nodes1, nodes2);
+ } else if ("Semidirected Paths".equals(method)) {
+ textArea.setText("");
+ allSemidirectedPaths(graph, textArea, nodes1, nodes2);
+ } else if ("Treks".equals(method)) {
+ textArea.setText("");
+ allTreks(graph, textArea, nodes1, nodes2);
+ } else if ("Adjacents".equals(method)) {
+ textArea.setText("");
+ adjacentNodes(graph, textArea, nodes1, nodes2);
+ }
}
private void allDirectedPaths(Graph graph, JTextArea textArea, List nodes1, List nodes2) {
@@ -218,65 +204,19 @@ private void allDirectedPaths(Graph graph, JTextArea textArea, List nodes1
for (Node node1 : nodes1) {
for (Node node2 : nodes2) {
- List> directedPaths = GraphUtils.directedPathsFromTo(graph, node1, node2,
+ List> paths = GraphUtils.directedPathsFromTo(graph, node1, node2,
Preferences.userRoot().getInt("pathMaxLength", 3));
- if (!directedPaths.isEmpty()) {
- textArea.append("\n\nFrom " + node1 + " to " + node2 + ":");
-
- for (List directedPath : directedPaths) {
- textArea.append("\n ");
-
- textArea.append(directedPath.get(0).toString());
-
- for (int m = 1; m < directedPath.size(); m++) {
- Node n0 = directedPath.get(m - 1);
- Node n1 = directedPath.get(m);
-
- Edge edge = graph.getEdge(n0, n1);
-
- Endpoint endpoint0 = edge.getProximalEndpoint(n0);
- Endpoint endpoint1 = edge.getProximalEndpoint(n1);
-
- textArea.append(endpoint0 == Endpoint.ARROW ? "<" : "-");
- textArea.append("-");
- textArea.append(endpoint1 == Endpoint.ARROW ? ">" : "-");
-
- textArea.append(n1.toString());
- }
- }
-
+ if (paths.isEmpty()) {
+ continue;
+ } else {
pathListed = true;
}
- directedPaths = GraphUtils.directedPathsFromTo(graph, node2, node1, Preferences.userRoot().getInt("pathMaxLength", 3));
-
- if (!directedPaths.isEmpty()) {
- textArea.append("\n\nFrom " + node2 + " to " + node1 + ":");
-
- for (List directedPath : directedPaths) {
- textArea.append("\n ");
-
- textArea.append(directedPath.get(0).toString());
-
- for (int m = 1; m < directedPath.size(); m++) {
- Node n0 = directedPath.get(m - 1);
- Node n1 = directedPath.get(m);
-
- Edge edge = graph.getEdge(n0, n1);
-
- Endpoint endpoint0 = edge.getProximalEndpoint(n0);
- Endpoint endpoint1 = edge.getProximalEndpoint(n1);
-
- textArea.append(endpoint0 == Endpoint.ARROW ? "<" : "-");
- textArea.append("-");
- textArea.append(endpoint1 == Endpoint.ARROW ? ">" : "-");
-
- textArea.append(n1.toString());
- }
- }
+ textArea.append("\n\nBetween " + node1 + " and " + node2 + ":");
- pathListed = true;
+ for (List path : paths) {
+ textArea.append("\n " + GraphUtils.pathString(graph, path));
}
}
}
@@ -291,43 +231,25 @@ private void allSemidirectedPaths(Graph graph, JTextArea textArea, List no
for (Node node1 : nodes1) {
for (Node node2 : nodes2) {
- List> directedPaths = GraphUtils.semidirectedPathsFromTo(graph, node1, node2,
+ List> paths = GraphUtils.semidirectedPathsFromTo(graph, node1, node2,
Preferences.userRoot().getInt("pathMaxLength", 3));
- if (directedPaths.isEmpty()) {
+ if (paths.isEmpty()) {
continue;
} else {
pathListed = true;
}
- textArea.append("\n\nFrom " + node1 + " to " + node2 + ":");
-
- for (List directedPath : directedPaths) {
- textArea.append("\n ");
-
- textArea.append(directedPath.get(0).toString());
-
- for (int m = 1; m < directedPath.size(); m++) {
- Node n0 = directedPath.get(m - 1);
- Node n1 = directedPath.get(m);
-
- Edge edge = graph.getEdge(n0, n1);
-
- Endpoint endpoint0 = edge.getProximalEndpoint(n0);
- Endpoint endpoint1 = edge.getProximalEndpoint(n1);
-
- textArea.append(endpoint0 == Endpoint.ARROW ? "<" : "-");
- textArea.append("-");
- textArea.append(endpoint1 == Endpoint.ARROW ? ">" : "-");
+ textArea.append("\n\nBetween " + node1 + " and " + node2 + ":");
- textArea.append(n1.toString());
- }
+ for (List path : paths) {
+ textArea.append("\n " + GraphUtils.pathString(graph, path));
}
}
}
if (!pathListed) {
- textArea.append("No undirectedPaths listed.");
+ textArea.append("No semidirected paths listed.");
}
}
@@ -347,13 +269,13 @@ private void allTreks(Graph graph, JTextArea textArea, List nodes1, List trek : treks) {
- textArea.append("\n " + GraphUtils.pathString(trek, graph));
+ textArea.append("\n " + GraphUtils.pathString(graph, trek));
}
}
}
if (!pathListed) {
- textArea.append("No undirectedPaths listed.");
+ textArea.append("No treks listed.");
}
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SaveGraph.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SaveGraph.java
index 61f6fe6e9c..7af83451eb 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SaveGraph.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SaveGraph.java
@@ -57,7 +57,7 @@ public class SaveGraph extends AbstractAction {
*/
private final Type type;
- public enum Type {text, xml, json, r, dot}
+ public enum Type {text, xml, json, r, dot, pcalg}
public SaveGraph(GraphEditable graphEditable, String title, Type type) {
super(title);
@@ -130,6 +130,23 @@ public void actionPerformed(ActionEvent e) {
try {
String text = GraphUtils.graphToDot(graph);
+ PrintWriter out = new PrintWriter(file);
+ out.println(text);
+ Preferences.userRoot().put("fileSaveLocation", file.getParent());
+ out.close();
+ } catch (FileNotFoundException e1) {
+ e1.printStackTrace();
+ throw new RuntimeException("Not a directed graph.", e1);
+ } catch (IllegalArgumentException e1) {
+
+ // Probably not a directed graph.
+ JOptionPane.showMessageDialog(getGraphEditable().getWorkbench(), e1.getMessage());
+ }
+ }else if (this.type == Type.pcalg) {
+ File file = EditorUtils.getSaveFile("graph", "pcalg.csv", parent, false, this.title);
+ try {
+ String text = GraphUtils.graphToPcalg(graph);
+
PrintWriter out = new PrintWriter(file);
out.println(text);
Preferences.userRoot().put("fileSaveLocation", file.getParent());
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectBidirectedAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectBidirectedAction.java
index 15609ea1df..8896f412bd 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectBidirectedAction.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectBidirectedAction.java
@@ -39,7 +39,7 @@
*
* @author Joseph Ramsey jdramsey@andrew.cmu.edu
*/
-class SelectBidirectedAction extends AbstractAction implements ClipboardOwner {
+public class SelectBidirectedAction extends AbstractAction implements ClipboardOwner {
/**
* The desktop containing the target session editor.
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectDirectedAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectDirectedAction.java
new file mode 100644
index 0000000000..7ebf7ae29e
--- /dev/null
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectDirectedAction.java
@@ -0,0 +1,88 @@
+///////////////////////////////////////////////////////////////////////////////
+// For information as to what this class does, see the Javadoc, below. //
+// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, //
+// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard //
+// Scheines, Joseph Ramsey, and Clark Glymour. //
+// //
+// This program is free software; you can redistribute it and/or modify //
+// it under the terms of the GNU General Public License as published by //
+// the Free Software Foundation; either version 2 of the License, or //
+// (at your option) any later version. //
+// //
+// This program is distributed in the hope that it will be useful, //
+// but WITHOUT ANY WARRANTY; without even the implied warranty of //
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the //
+// GNU General Public License for more details. //
+// //
+// You should have received a copy of the GNU General Public License //
+// along with this program; if not, write to the Free Software //
+// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA //
+///////////////////////////////////////////////////////////////////////////////
+
+package edu.cmu.tetradapp.editor;
+
+import edu.cmu.tetrad.graph.Edge;
+import edu.cmu.tetrad.graph.Edges;
+import edu.cmu.tetradapp.workbench.DisplayEdge;
+import edu.cmu.tetradapp.workbench.GraphWorkbench;
+
+import javax.swing.*;
+import java.awt.*;
+import java.awt.datatransfer.Clipboard;
+import java.awt.datatransfer.ClipboardOwner;
+import java.awt.datatransfer.Transferable;
+import java.awt.event.ActionEvent;
+
+/**
+ * Copies a selection of session nodes in the frontmost session editor, to the
+ * clipboard.
+ *
+ * @author Joseph Ramsey jdramsey@andrew.cmu.edu
+ */
+public class SelectDirectedAction extends AbstractAction implements ClipboardOwner {
+
+ /**
+ * The desktop containing the target session editor.
+ */
+ private final GraphWorkbench workbench;
+
+ /**
+ * Creates a new copy subsession action for the given desktop and
+ * clipboard.
+ */
+ public SelectDirectedAction(GraphWorkbench workbench) {
+ super("Highlight Directed Edges");
+
+ if (workbench == null) {
+ throw new NullPointerException("Desktop must not be null.");
+ }
+
+ this.workbench = workbench;
+ }
+
+ /**
+ * Copies a parentally closed selection of session nodes in the frontmost
+ * session editor to the clipboard.
+ */
+ public void actionPerformed(ActionEvent e) {
+ this.workbench.deselectAll();
+
+ for (Component comp : this.workbench.getComponents()) {
+ if (comp instanceof DisplayEdge) {
+ Edge edge = ((DisplayEdge) comp).getModelEdge();
+ if (Edges.isDirectedEdge(edge)) {
+ this.workbench.selectEdge(edge);
+ }
+ }
+ }
+ }
+
+ /**
+ * Required by the AbstractAction interface; does nothing.
+ */
+ public void lostOwnership(Clipboard clipboard, Transferable contents) {
+ }
+}
+
+
+
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectLatentsAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectLatentsAction.java
index 0c0826ab24..b44f28fcbc 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectLatentsAction.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectLatentsAction.java
@@ -41,7 +41,7 @@
*
* @author Joseph Ramsey jdramsey@andrew.cmu.edu
*/
-class SelectLatentsAction extends AbstractAction implements ClipboardOwner {
+public class SelectLatentsAction extends AbstractAction implements ClipboardOwner {
/**
* The desktop containing the target session editor.
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectUndirectedAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectUndirectedAction.java
index c4e21f7fe3..02df6f40ba 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectUndirectedAction.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SelectUndirectedAction.java
@@ -39,7 +39,7 @@
*
* @author Joseph Ramsey jdramsey@andrew.cmu.edu
*/
-class SelectUndirectedAction extends AbstractAction implements ClipboardOwner {
+public class SelectUndirectedAction extends AbstractAction implements ClipboardOwner {
/**
* The desktop containing the target session editor.
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemEstimatorEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemEstimatorEditor.java
index 33fdc67d5d..ca8db2a5bf 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemEstimatorEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemEstimatorEditor.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.editor;
import edu.cmu.tetrad.data.DataSet;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.sem.*;
import edu.cmu.tetrad.util.*;
@@ -566,7 +566,7 @@ public Map getModelNodesToDisplay() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.semImGraphicalEditor.getWorkbench().getKnowledge();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemGraphEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemGraphEditor.java
index 101ea582cf..03f96d8c56 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemGraphEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemGraphEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.IndTestDSep;
import edu.cmu.tetrad.search.IndependenceTest;
@@ -182,7 +182,7 @@ public void setGraph(Graph graph) {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return null;
}
@@ -385,7 +385,7 @@ private void modelSelectin(SemGraphWrapper semGraphWrapper) {
private JMenuBar createGraphMenuBar() {
JMenuBar menuBar = new JMenuBar();
- JMenu fileMenu = new GraphFileMenu(this, getWorkbench());
+ JMenu fileMenu = new GraphFileMenu(this, getWorkbench(), false);
JMenu editMenu = createEditMenu();
JMenu graphMenu = createGraphMenu();
@@ -479,7 +479,7 @@ private JMenu createGraphMenu() {
editor.setParams(this.parameters);
EditorWindow editorWindow = new EditorWindow(editor, "Edit Random Graph Parameters",
- "Done", false, this);
+ "Done", true, this);
DesktopController.getInstance().addEditorWindow(editorWindow, JLayeredPane.PALETTE_LAYER);
editorWindow.pack();
@@ -510,7 +510,11 @@ public void internalFrameClosed(InternalFrameEvent e1) {
});
});
- graph.add(new JMenuItem(new SelectBidirectedAction(getWorkbench())));
+ graph.add(new JMenuItem(new SelectDirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectBidirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectUndirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectLatentsAction(this.workbench)));
+ graph.add(new PagTypeSetter(getWorkbench()));
return graph;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemImEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemImEditor.java
index 17e1bcd2e4..967355b1cc 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemImEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemImEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.sem.*;
import edu.cmu.tetrad.util.Matrix;
@@ -155,7 +155,7 @@ public Map getModelNodesToDisplay() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.oneEditorPanel.getKnowledge();
}
@@ -410,7 +410,7 @@ public Map getModelNodesToDisplay() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.semImGraphicalEditor.getWorkbench().getKnowledge();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemPmEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemPmEditor.java
index e9ff099cf7..9ad28638b5 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemPmEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SemPmEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.sem.ParamType;
import edu.cmu.tetrad.sem.Parameter;
@@ -216,7 +216,7 @@ public Map getModelNodesToDisplay() {
return graphicalEditor().getWorkbench().getModelNodesToDisplay();
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return graphicalEditor().getWorkbench().getKnowledge();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SimulationEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SimulationEditor.java
index 46492092d0..96d70d3ede 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SimulationEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/SimulationEditor.java
@@ -22,7 +22,7 @@
import edu.cmu.tetrad.algcomparison.Comparison;
import edu.cmu.tetrad.data.DataModelList;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.util.JOptionUtils;
import edu.cmu.tetrad.util.Parameters;
@@ -201,12 +201,12 @@ public void propertyChange(PropertyChangeEvent evt) {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return null;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
+ public void setKnowledge(Knowledge knowledge) {
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/StandardizedSemImEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/StandardizedSemImEditor.java
index 3d7eb906e7..e334599487 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/StandardizedSemImEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/StandardizedSemImEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.SemGraph;
import edu.cmu.tetrad.sem.StandardizedSemIm;
@@ -141,7 +141,7 @@ public Map getModelNodesToDisplay() {
* @return the knowledge currently stored in the workbench. Required for and
* interface.
*/
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.standardizedSemImGraphicalEditor.getWorkbench().getKnowledge();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/StatsListEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/StatsListEditor.java
index 2c3ee095a5..89cef29b53 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/StatsListEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/StatsListEditor.java
@@ -34,7 +34,7 @@ public StatsListEditor(TabularComparison comparison) {
this.comparison = comparison;
this.params = comparison.getParams();
this.targetGraph = comparison.getTargetGraph();
- this.referenceGraph = getComparisonGraph(comparison.getReferenceGraph(), this.params);
+ this.referenceGraph = comparison.getReferenceGraph();
this.dataModel = comparison.getDataModel();
setup();
}
@@ -62,7 +62,7 @@ private JComponent getTableDisplay() {
this.area.setBorder(new EmptyBorder(5, 5, 5, 5));
this.area.setFont(new Font(Font.MONOSPACED, Font.BOLD, 14));
- this.area.setPreferredSize(new Dimension(700, 1200));
+// this.area.setPreferredSize(new Dimension(1200, 1800));
JScrollPane pane = new JScrollPane(this.area);
pane.setPreferredSize(new Dimension(700, 700));
@@ -76,7 +76,7 @@ private JComponent getTableDisplay() {
@NotNull
private String tableTextWithHeader() {
TextTable table = tableText();
- return "Comparing target " + this.comparison.getTargetName() + " to reference " + this.comparison.getReferenceName()
+ return "True graph from " + this.comparison.getReferenceName() + "\nTarget graph from " + this.comparison.getTargetName()
+ "\n\n" + table;
}
@@ -108,12 +108,13 @@ private TextTable tableText() {
for (int i = 0; i < abbr.size(); i++) {
double value = vals.get(i);
- table.setToken(i, 2, Double.isNaN(value) ? "-" : "" + nf.format(value));
+ table.setToken(i, 1, Double.isNaN(value) ? "-" : "" + nf.format(value));
table.setToken(i, 0, abbr.get(i));
- table.setToken(i, 1, desc.get(i));
+ table.setToken(i, 2, desc.get(i));
}
table.setJustification(TextTable.LEFT_JUSTIFIED);
+
return table;
}
@@ -121,9 +122,7 @@ private TextTable tableText() {
private List statistics() {
List statistics = new ArrayList<>();
- statistics.add(new BicTrue());
- statistics.add(new BicEst());
- statistics.add(new BicDiff());
+ // Others
statistics.add(new AdjacencyPrecision());
statistics.add(new AdjacencyRecall());
statistics.add(new ArrowheadPrecision());
@@ -144,12 +143,10 @@ private List statistics() {
statistics.add(new F1Arrow());
statistics.add(new MathewsCorrAdj());
statistics.add(new MathewsCorrArrow());
- statistics.add(new SHD());
- statistics.add(new NumAmbiguousTriples());
- statistics.add(new PercentAmbiguous());
- statistics.add(new PercentBidirectedEdges());
statistics.add(new NumberOfEdgesEst());
statistics.add(new NumberOfEdgesTrue());
+ statistics.add(new NumCorrectVisibleAncestors());
+ statistics.add(new PercentBidirectedEdges());
statistics.add(new TailPrecision());
statistics.add(new TailRecall());
statistics.add(new TwoCyclePrecision());
@@ -161,6 +158,30 @@ private List statistics() {
statistics.add(new AverageDegreeTrue());
statistics.add(new DensityEst());
statistics.add(new DensityTrue());
+
+
+ // Joe table.
+ statistics.add(new NumDirectedEdges());
+ statistics.add(new NumUndirectedEdges());
+ statistics.add(new NumPartiallyOrientedEdges());
+ statistics.add(new NumNondirectedEdges());
+ statistics.add(new NumBidirectedEdgesEst());
+ statistics.add(new TrueDagPrecisionTails());
+ statistics.add(new TrueDagPrecisionArrow());
+ statistics.add(new BidirectedLatentPrecision());
+
+
+ // Greg table
+ statistics.add(new AncestorPrecision());
+ statistics.add(new AncestorRecall());
+ statistics.add(new AncestorF1());
+ statistics.add(new SemidirectedPrecision());
+ statistics.add(new SemidirectedRecall());
+ statistics.add(new SemidirectedPathF1());
+ statistics.add(new NoSemidirectedPrecision());
+ statistics.add(new NoSemidirectedRecall());
+ statistics.add(new NoSemidirectedF1());
+
return statistics;
}
@@ -186,6 +207,8 @@ private JMenuBar menubar() {
menubar.add(menu);
+ this.referenceGraph = getComparisonGraph(this.comparison.getReferenceGraph(), this.params);
+
switch (this.params.getString("graphComparisonType")) {
case "CPDAG":
menu.setText("Compare to CPDAG...");
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TabularComparisonEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TabularComparisonEditor.java
index 8969c472e7..542cd114c5 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TabularComparisonEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TabularComparisonEditor.java
@@ -93,7 +93,7 @@ private Box getTableDisplay() {
private TextTable getTextTable(DataSet dataSet, NumberFormat nf) {
TextTable table = new TextTable(dataSet.getNumRows() + 2, dataSet.getNumColumns() + 1);
- table.setTabDelimited(true);
+ table.setDelimiter(TextTable.Delimiter.TAB);
table.setToken(0, 0, "Run");
for (int j = 0; j < dataSet.getNumColumns(); j++) {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TemporalTierEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TemporalTierEditor.java
index 7e4cb53679..c55654fc22 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TemporalTierEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TemporalTierEditor.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import javax.swing.*;
import java.awt.*;
@@ -40,7 +40,7 @@ class TemporalTierEditor extends JPanel
implements PropertyChangeListener, ActionListener {
- private final IKnowledge knowledge;
+ private final Knowledge knowledge;
//private JButton nameTiers;
private final JButton clear;
@@ -49,7 +49,7 @@ class TemporalTierEditor extends JPanel
*/
private final TierList tierList;
- public TemporalTierEditor(IKnowledge knowledge, List varNames,
+ public TemporalTierEditor(Knowledge knowledge, List varNames,
String sessionName) {
//nameTiers = new JButton("VariableNameImpliedTiers");
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/Tier.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/Tier.java
index 4d436ffb77..df0d126260 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/Tier.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/Tier.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import javax.swing.*;
import java.awt.*;
@@ -41,7 +41,7 @@ class Tier extends JPanel {
private final String[] tierNames;
private final JPanel view = new JPanel();
private final JScrollPane jsp;
- private static IKnowledge know;
+ private static Knowledge know;
/**
* A panel with a tier name, and all vars in that tier.
@@ -61,7 +61,7 @@ public Tier(TierList kn, int thisTier, String[] tierNames) {
this.jsp.setViewportView(this.view);
}
- public static void setKnowledge(IKnowledge k) {
+ public static void setKnowledge(Knowledge k) {
Tier.know = k;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TierList.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TierList.java
index b6cac2c75b..5936f417a6 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TierList.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TierList.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import javax.swing.*;
import java.util.List;
@@ -32,7 +32,7 @@
* @author Shane Harwood
*/
class TierList extends JScrollPane {
- private final IKnowledge knowledge;
+ private final Knowledge knowledge;
/**
* Field TierListEditor
@@ -43,7 +43,7 @@ class TierList extends JScrollPane {
private final Tier[] tiers;
- public TierList(IKnowledge know, List varNames,
+ public TierList(Knowledge know, List varNames,
TemporalTierEditor tierListEditor) {
super(ScrollPaneConstants.VERTICAL_SCROLLBAR_AS_NEEDED,
@@ -135,7 +135,7 @@ public void refreshInfo() {
/**
* @return modified knowledge allowing saving.
*/
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TimeLagGraphEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TimeLagGraphEditor.java
index 8797706bc2..7a35aacf9a 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TimeLagGraphEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/TimeLagGraphEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.IndTestDSep;
import edu.cmu.tetrad.search.IndependenceTest;
@@ -161,7 +161,7 @@ public void setGraph(Graph graph) {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return null;
}
@@ -304,7 +304,7 @@ private void updateBootstrapTable(Graph graph) {
private JMenuBar createGraphMenuBar() {
JMenuBar menuBar = new JMenuBar();
- JMenu fileMenu = new GraphFileMenu(this, getWorkbench());
+ JMenu fileMenu = new GraphFileMenu(this, getWorkbench(), false);
JMenu editMenu = createNumLagsMenu();
// JMenu graphMenu = createGraphMenu();
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/UnderliningsAction.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/UnderliningsAction.java
index ce812559ce..8bd18a35c7 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/UnderliningsAction.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/UnderliningsAction.java
@@ -45,7 +45,7 @@
*
* @author Joseph Ramsey jdramsey@andrew.cmu.edu
*/
-class UnderliningsAction extends AbstractAction implements ClipboardOwner {
+public class UnderliningsAction extends AbstractAction implements ClipboardOwner {
private final GraphWorkbench workbench;
/**
@@ -150,7 +150,7 @@ private String niceList(List triples) {
private String pathFor(Triple triple, Graph graph) {
List path = asList(triple);
- return GraphUtils.pathString(path, graph);
+ return GraphUtils.pathString(graph, path);
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/search/AlgorithmCard.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/search/AlgorithmCard.java
index 0b262382a0..3bab65d94b 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/search/AlgorithmCard.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/search/AlgorithmCard.java
@@ -484,7 +484,7 @@ private void validateAlgorithmOption() {
|| cmd.equalsIgnoreCase("ts-gfci")
|| cmd.equalsIgnoreCase("ts-imgs")) {
DataModel dataModel = this.algorithmRunner.getDataModel();
- IKnowledge knowledge = this.algorithmRunner.getKnowledge();
+ Knowledge knowledge = this.algorithmRunner.getKnowledge();
if ((knowledge == null || knowledge.isEmpty())
&& (dataModel.getKnowledge() == null || dataModel.getKnowledge().isEmpty())) {
firePropertyChange("algoFwdBtn", null, false);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/search/GraphCard.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/search/GraphCard.java
index ffff69ec8f..c62a8e6d8b 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/search/GraphCard.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/search/GraphCard.java
@@ -19,7 +19,7 @@
package edu.cmu.tetradapp.editor.search;
import edu.cmu.tetrad.graph.Graph;
-import edu.cmu.tetradapp.editor.EdgeTypeTable;
+import edu.cmu.tetradapp.editor.*;
import edu.cmu.tetradapp.model.GeneralAlgorithmRunner;
import edu.cmu.tetradapp.ui.PaddingPanel;
import edu.cmu.tetradapp.util.ImageUtils;
@@ -33,6 +33,8 @@
import java.awt.*;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;
+import java.awt.event.InputEvent;
+import java.awt.event.KeyEvent;
import java.net.URL;
/**
@@ -45,6 +47,7 @@ public class GraphCard extends JPanel {
private static final long serialVersionUID = -7654484444146823298L;
private final GeneralAlgorithmRunner algorithmRunner;
+ private GraphWorkbench workbench;
public GraphCard(GeneralAlgorithmRunner algorithmRunner) {
this.algorithmRunner = algorithmRunner;
@@ -69,10 +72,36 @@ public void refresh() {
tabbedPane.addTab("Edges", createEdgeTypeTable(graph));
add(tabbedPane, BorderLayout.CENTER);
+ add(menuBar(), BorderLayout.NORTH);
+
revalidate();
repaint();
}
+ JMenuBar menuBar() {
+ JMenuBar menuBar = new JMenuBar();
+ JMenu file = new JMenu("File");
+ file.add(new SaveComponentImage(this.workbench, "Save Graph Image..."));
+
+ menuBar.add(file);
+
+ JMenu graph = new JMenu("Graph");
+
+ graph.add(new GraphPropertiesAction(this.workbench));
+ graph.add(new PathsAction(this.workbench));
+ graph.add(new UnderliningsAction(this.workbench));
+
+ graph.add(new JMenuItem(new SelectDirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectBidirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectUndirectedAction(this.workbench)));
+ graph.add(new JMenuItem(new SelectLatentsAction(this.workbench)));
+ graph.add(new PagTypeSetter(this.workbench));
+
+ menuBar.add(graph);
+
+ return menuBar;
+ }
+
private EdgeTypeTable createEdgeTypeTable(Graph graph) {
EdgeTypeTable edgeTypeTable = new EdgeTypeTable();
edgeTypeTable.setPreferredSize(new Dimension(825, 100));
@@ -85,6 +114,8 @@ private JPanel createGraphPanel(Graph graph) {
GraphWorkbench graphWorkbench = new GraphWorkbench(graph);
graphWorkbench.enableEditing(false);
+ this.workbench = graphWorkbench;
+
JPanel mainPanel = new JPanel(new BorderLayout());
mainPanel.setPreferredSize(new Dimension(825, 406));
mainPanel.add(new JScrollPane(graphWorkbench), BorderLayout.CENTER);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/simulation/ParameterTab.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/simulation/ParameterTab.java
index f2dfa56d0d..c7263a7786 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/simulation/ParameterTab.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/editor/simulation/ParameterTab.java
@@ -22,6 +22,7 @@
import edu.cmu.tetrad.algcomparison.simulation.*;
import edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs;
import edu.cmu.tetrad.graph.EdgeListGraph;
+import edu.cmu.tetrad.sem.LargeScaleSimulation;
import edu.cmu.tetradapp.model.Simulation;
import edu.cmu.tetradapp.ui.PaddingPanel;
import edu.cmu.tetradapp.util.ParameterComponents;
@@ -55,7 +56,7 @@ public class ParameterTab extends JPanel {
private static final String[] SOURCE_GRAPH_ITEMS = {
SimulationTypes.BAYS_NET,
SimulationTypes.STRUCTURAL_EQUATION_MODEL,
-// SimulationTypes.LINEAR_FISHER_MODEL,
+ SimulationTypes.LINEAR_FISHER_MODEL,
SimulationTypes.LEE_AND_HASTIE,
SimulationTypes.CONDITIONAL_GAUSSIAN,
SimulationTypes.TIME_SERIES
@@ -163,6 +164,9 @@ private void newSimulation(RandomGraph randomGraph) {
case SimulationTypes.STRUCTURAL_EQUATION_MODEL:
this.simulation.setSimulation(new SemSimulation(randomGraph), this.simulation.getParams());
break;
+ case SimulationTypes.LINEAR_FISHER_MODEL:
+ this.simulation.setSimulation(new LinearFisherModel(randomGraph), this.simulation.getParams());
+ break;
case SimulationTypes.GENERAL_STRUCTURAL_EQUATION_MODEL:
this.simulation.setSimulation(new GeneralSemSimulationSpecial1(randomGraph), this.simulation.getParams());
break;
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeBoxEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeBoxEditor.java
index 130413922d..ea5f3ab6c7 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeBoxEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeBoxEditor.java
@@ -28,6 +28,7 @@
import edu.cmu.tetrad.util.TetradLogger;
import edu.cmu.tetradapp.model.ForbiddenGraphModel;
import edu.cmu.tetradapp.model.KnowledgeBoxModel;
+import edu.cmu.tetradapp.model.RemoveNonSkeletonEdgesModel;
import javax.swing.*;
import javax.swing.border.*;
@@ -63,7 +64,7 @@ public class KnowledgeBoxEditor extends JPanel {
private final List firstTierVars = new LinkedList<>();
private final List secondTierVars = new LinkedList<>();
private final KnowledgeBoxModel knowledgeBoxModel;
- private IKnowledge knowledge;
+ private Knowledge knowledge;
private KnowledgeWorkbench edgeWorkbench;
private JPanel tiersPanel;
private boolean showForbiddenExplicitly;
@@ -78,6 +79,10 @@ public KnowledgeBoxEditor(ForbiddenGraphModel knowledgeBoxModel) {
this((KnowledgeBoxModel) knowledgeBoxModel);
}
+ public KnowledgeBoxEditor(RemoveNonSkeletonEdgesModel knowledgeBoxModel) {
+ this((KnowledgeBoxModel) knowledgeBoxModel);
+ }
+
/**
* Constructs a Knowledge editor for the given knowledge, variable names
* (that is, the list of all variable names to be considered, which may vary
@@ -159,7 +164,7 @@ private JMenuBar menuBar() {
Preferences.userRoot().put("fileSaveLocation", selectedFile.getParent());
try {
- IKnowledge knowledge = DataUtils.loadKnowledge(selectedFile, DelimiterType.WHITESPACE, "//");
+ Knowledge knowledge = DataUtils.loadKnowledge(selectedFile, DelimiterType.WHITESPACE, "//");
setKnowledge(knowledge);
resetTabbedPane();
} catch (Exception e1) {
@@ -531,7 +536,7 @@ private JPanel edgeDisplay() {
}
private void resetEdgeDisplay(JCheckBox checkBox) {
- IKnowledge knowledge = getKnowledge();
+ Knowledge knowledge = getKnowledge();
KnowledgeGraph graph = new KnowledgeGraph(getKnowledge());
getVarNames().forEach(e -> {
knowledge.addVariable(e);
@@ -696,11 +701,11 @@ private void notifyKnowledge() {
firePropertyChange("modelChanged", null, null);
}
- private IKnowledge getKnowledge() {
+ private Knowledge getKnowledge() {
return this.knowledge;
}
- public void setKnowledge(IKnowledge knowledge) {
+ public void setKnowledge(Knowledge knowledge) {
if (knowledge == null) {
throw new NullPointerException();
}
@@ -797,7 +802,7 @@ public boolean importData(TransferSupport info) {
JList source = (JList) info.getComponent();
DefaultListModel listModel = (DefaultListModel) source.getModel();
- IKnowledge knowledge = getKnowledge();
+ Knowledge knowledge = getKnowledge();
Transferable transferable = info.getTransferable();
try {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeDisplayEdge.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeDisplayEdge.java
index 5dc959b84f..c6dafa78da 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeDisplayEdge.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeDisplayEdge.java
@@ -204,7 +204,8 @@ public class KnowledgeDisplayEdge extends JComponent implements IDisplayEdge {
*/
private final PropertyChangeHandler propertyChangeHandler =
new PropertyChangeHandler();
- private boolean bold;
+ private boolean solid = true;
+ private boolean thick = false;
//==========================CONSTRUCTORS============================//
@@ -970,12 +971,17 @@ public void setLineColor(Color lineColor) {
// throw new UnsupportedOperationException();
}
- public boolean getBold() {
- return this.bold;
+ public boolean getSolid() {
+ return this.solid;
}
- public void setBold(boolean bold) {
- this.bold = bold;
+ public void setSolid(boolean solid) {
+ this.solid = solid;
+ }
+
+ @Override
+ public void setThick(boolean thick) {
+ this.thick = thick;
}
/**
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeEditorToolbar.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeEditorToolbar.java
index a15c31fbf7..5e024a648d 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeEditorToolbar.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeEditorToolbar.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.knowledge_editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.GraphUtils;
import edu.cmu.tetrad.search.SearchGraphUtils;
@@ -232,7 +232,7 @@ private void setWorkbenchMode(JToggleButton button) {
this.workbench.setGraph(graph);
} else if ("Knowledge Layout".equals(nodeType)) {
KnowledgeGraph graph = (KnowledgeGraph) this.workbench.getGraph();
- IKnowledge knowledge = graph.getKnowledge();
+ Knowledge knowledge = graph.getKnowledge();
try {
SearchGraphUtils.arrangeByKnowledgeTiers(graph, knowledge);
this.workbench.setGraph(graph);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeGraph.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeGraph.java
index 8c06487425..e1a46be374 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeGraph.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/KnowledgeGraph.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.knowledge_editor;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.util.TetradSerializableExcluded;
import edu.cmu.tetrad.util.TetradSerializableUtils;
@@ -50,18 +49,19 @@ public class KnowledgeGraph implements Graph, TetradSerializableExcluded {
/**
* @serial
*/
- private final IKnowledge knowledge;
+ private final Knowledge knowledge;
private boolean pag;
private boolean CPDAG;
private final Map attributes = new HashMap<>();
+ private EdgeListGraph.GraphType graphType = EdgeListGraph.GraphType.DAG;
//============================CONSTRUCTORS=============================//
/**
* Constructs a new directed acyclic graph (DAG).
*/
- public KnowledgeGraph(IKnowledge knowledge) {
+ public KnowledgeGraph(Knowledge knowledge) {
if (knowledge == null) {
throw new NullPointerException();
}
@@ -75,7 +75,7 @@ public KnowledgeGraph(IKnowledge knowledge) {
* @see TetradSerializableUtils
*/
public static KnowledgeGraph serializableInstance() {
- return new KnowledgeGraph(Knowledge2.serializableInstance());
+ return new KnowledgeGraph(Knowledge.serializableInstance());
}
//=============================PUBLIC METHODS==========================//
@@ -558,7 +558,7 @@ public String toString() {
return getGraph().toString();
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@@ -576,24 +576,12 @@ public List> getTriplesLists(Node node) {
return null;
}
- @Override
- public boolean isPag() {
- return this.pag;
- }
-
- @Override
- public void setPag(boolean pag) {
- this.pag = pag;
+ public void setGraphType(EdgeListGraph.GraphType graphType) {
+ this.graphType = graphType;
}
- @Override
- public boolean isCPDAG() {
- return this.CPDAG;
- }
-
- @Override
- public void setCPDAG(boolean CPDAG) {
- this.CPDAG = CPDAG;
+ public EdgeListGraph.GraphType getGraphType() {
+ return this.graphType;
}
@Override
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/OtherGroupsEditor.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/OtherGroupsEditor.java
index 69d7207709..1d2ed920c4 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/OtherGroupsEditor.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/knowledge_editor/OtherGroupsEditor.java
@@ -20,7 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.knowledge_editor;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.data.KnowledgeGroup;
import edu.cmu.tetradapp.workbench.LayoutUtils;
@@ -46,14 +46,14 @@ class OtherGroupsEditor extends JPanel {
/**
* The knowledge that is being edited.
*/
- private final IKnowledge knowledge;
+ private final Knowledge knowledge;
/**
* The variables in the graph.
*/
private final List variables;
- public OtherGroupsEditor(IKnowledge knowledge, List vars) {
+ public OtherGroupsEditor(Knowledge knowledge, List vars) {
if (knowledge == null) {
throw new NullPointerException("The given knowledge must not be null");
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/DataWrapper.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/DataWrapper.java
index a3cb6ea9f6..c6c0dab49b 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/DataWrapper.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/DataWrapper.java
@@ -332,11 +332,11 @@ public void setDataModel(DataModel dataModel) {
}
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return getSelectedDataModel().getKnowledge();
}
- public void setKnowledge(IKnowledge knowledge) {
+ public void setKnowledge(Knowledge knowledge) {
getSelectedDataModel().setKnowledge(knowledge);
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/EdgewiseComparisonModel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/EdgewiseComparisonModel.java
index eec6525799..64ea9f5ecf 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/EdgewiseComparisonModel.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/EdgewiseComparisonModel.java
@@ -21,10 +21,9 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
import edu.cmu.tetrad.data.DataSet;
+import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
-import edu.cmu.tetrad.graph.GraphUtils;
import edu.cmu.tetrad.search.SearchGraphUtils;
import edu.cmu.tetrad.session.DoNotAddOldModel;
import edu.cmu.tetrad.session.SessionModel;
@@ -33,9 +32,8 @@
import java.io.IOException;
import java.io.ObjectInputStream;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.List;
+
+import static edu.cmu.tetrad.search.SearchGraphUtils.dagToPag;
/**
@@ -47,13 +45,14 @@
*/
public final class EdgewiseComparisonModel implements SessionModel, DoNotAddOldModel {
static final long serialVersionUID = 23L;
- private Algorithm algorithm;
- private String name;
+ public enum ComparisonType {DAG, CPDAG, PAG}
+
+ private final Graph targetGraph;
+ private final Graph referenceGraph;
private final Parameters params;
- private List targetGraphs;
- private List referenceGraphs;
-// private Graph trueGraph;
+ private String name;
+
//=============================CONSTRUCTORS==========================//
@@ -62,122 +61,35 @@ public final class EdgewiseComparisonModel implements SessionModel, DoNotAddOldM
* of omission and commission. The counts can be retrieved using the methods
* countOmissionErrors and countCommissionErrors.
*/
-
- public EdgewiseComparisonModel(MultipleGraphSource model1, MultipleGraphSource model2,
- Parameters params) {
+ public EdgewiseComparisonModel(GraphSource model1, GraphSource model2, Parameters params) {
if (params == null) {
throw new NullPointerException("Parameters must not be null");
}
- // Need to be able to construct this object even if the models are
- // null. Otherwise the interface is annoying.
-
- if (model1 instanceof GeneralAlgorithmRunner && model2 instanceof GeneralAlgorithmRunner) {
- throw new IllegalArgumentException("Both parents can't be general algorithm runners.");
- }
-
- if (model1 instanceof GeneralAlgorithmRunner) {
- GeneralAlgorithmRunner generalAlgorithmRunner = (GeneralAlgorithmRunner) model1;
- this.algorithm = generalAlgorithmRunner.getAlgorithm();
- } else if (model2 instanceof GeneralAlgorithmRunner) {
- GeneralAlgorithmRunner generalAlgorithmRunner = (GeneralAlgorithmRunner) model2;
- this.algorithm = generalAlgorithmRunner.getAlgorithm();
+ if (model1 == null || model2 == null) {
+ throw new NullPointerException("Null graph source>");
}
this.params = params;
- String referenceName = this.params.getString("referenceGraphName", null);
-
- if (referenceName.equals(model1.getName())) {
- if (model1 instanceof Simulation && model2 instanceof GeneralAlgorithmRunner) {
- this.referenceGraphs = ((GeneralAlgorithmRunner) model2).getCompareGraphs(model1.getGraphs());
- } else if (model1 instanceof MultipleGraphSource) {
- this.referenceGraphs = model1.getGraphs();
- }
-
- if (model2 instanceof MultipleGraphSource) {
- this.targetGraphs = model2.getGraphs();
- }
-
- if (this.referenceGraphs.size() == 1 && this.targetGraphs.size() > 1) {
- Graph graph = this.referenceGraphs.get(0);
- this.referenceGraphs = new ArrayList<>();
- this.referenceGraphs.addAll(this.targetGraphs);
- }
-
- if (this.targetGraphs.size() == 1 && this.referenceGraphs.size() > 1) {
- Graph graph = this.targetGraphs.get(0);
- this.targetGraphs = new ArrayList<>();
- for (Graph _graph : this.referenceGraphs) {
- this.targetGraphs.add(graph);
- }
- }
-
- if (this.referenceGraphs == null) {
- this.referenceGraphs = Collections.singletonList(((GraphSource) model1).getGraph());
- }
-
- if (this.targetGraphs == null) {
- this.targetGraphs = Collections.singletonList(((GraphSource) model2).getGraph());
- }
- } else if (referenceName.equals(model2.getName())) {
- if (model2 instanceof Simulation && model1 instanceof GeneralAlgorithmRunner) {
- this.referenceGraphs = ((GeneralAlgorithmRunner) model1).getCompareGraphs(model2.getGraphs());
- } else if (model1 instanceof MultipleGraphSource) {
- this.referenceGraphs = model2.getGraphs();
- }
-
- if (model1 instanceof MultipleGraphSource) {
- this.targetGraphs = model1.getGraphs();
- }
-
- if (this.referenceGraphs.size() == 1 && this.targetGraphs.size() > 1) {
- Graph graph = this.referenceGraphs.get(0);
- this.referenceGraphs = new ArrayList<>();
- this.referenceGraphs.addAll(this.targetGraphs);
- }
-
- if (this.targetGraphs.size() == 1 && this.referenceGraphs.size() > 1) {
- Graph graph = this.targetGraphs.get(0);
- this.targetGraphs = new ArrayList<>();
- for (Graph _graph : this.referenceGraphs) {
- this.targetGraphs.add(graph);
- }
- }
-
- if (this.referenceGraphs == null) {
- this.referenceGraphs = Collections.singletonList(((GraphSource) model2).getGraph());
- }
-
- if (this.targetGraphs == null) {
- this.targetGraphs = Collections.singletonList(((GraphSource) model1).getGraph());
- }
- } else {
- throw new IllegalArgumentException(
- "Neither of the supplied session models is named '" +
- referenceName + "'.");
- }
-
- for (int i = 0; i < this.targetGraphs.size(); i++) {
- this.targetGraphs.set(i, GraphUtils.replaceNodes(this.targetGraphs.get(i), this.referenceGraphs.get(i).getNodes()));
- }
+ String referenceName = params.getString("referenceGraphName", null);
- if (this.algorithm != null) {
- for (int i = 0; i < this.referenceGraphs.size(); i++) {
- this.referenceGraphs.set(i, this.algorithm.getComparisonGraph(this.referenceGraphs.get(i)));
- }
- }
+ String model1Name = model1.getName();
+ String model2Name = model2.getName();
- if (this.referenceGraphs.size() != this.targetGraphs.size()) {
- throw new IllegalArgumentException("I was expecting the same number of graphs in each parent.");
+ if (referenceName.equals(model1Name)) {
+ this.referenceGraph = model1.getGraph();
+ this.targetGraph = model2.getGraph();
+ } else if (referenceName.equals(model2Name)) {
+ this.referenceGraph = model2.getGraph();
+ this.targetGraph = model1.getGraph();
+ } else {
+ this.referenceGraph = model1.getGraph();
+ this.targetGraph = model2.getGraph();
}
TetradLogger.getInstance().log("info", "Graph Comparison");
- for (int i = 0; i < this.referenceGraphs.size(); i++) {
- TetradLogger.getInstance().log("comparison", "\nModel " + (i + 1));
- TetradLogger.getInstance().log("comparison", getComparisonString(i));
- }
}
//==============================PUBLIC METHODS========================//
@@ -194,11 +106,14 @@ public void setName(String name) {
this.name = name;
}
- public String getComparisonString(int i) {
+ public String getComparisonString() {
String refName = getParams().getString("referenceGraphName", null);
String targetName = getParams().getString("targetGraphName", null);
- return SearchGraphUtils.graphComparisonString(targetName, this.targetGraphs.get(i),
- refName, this.referenceGraphs.get(i), false);
+
+ Graph comparisonGraph = getComparisonGraph(referenceGraph, params);
+
+ return SearchGraphUtils.graphComparisonString(refName, comparisonGraph,
+ targetName, this.targetGraph, false);
}
/**
@@ -216,20 +131,26 @@ private void readObject(ObjectInputStream s)
s.defaultReadObject();
}
- private Parameters getParams() {
+ public Parameters getParams() {
return this.params;
}
- public List getTargetGraphs() {
- return this.targetGraphs;
- }
-
- public List getReferenceGraphs() {
- return this.referenceGraphs;
- }
-
- public void setReferenceGraphs(List referenceGraphs) {
- this.referenceGraphs = referenceGraphs;
+ public static Graph getComparisonGraph(Graph graph, Parameters params) {
+ String type = params.getString("graphComparisonType");
+
+ if ("DAG".equals(type)) {
+ params.set("graphComparisonType", "DAG");
+ return new EdgeListGraph(graph);
+ } else if ("CPDAG".equals(type)) {
+ params.set("graphComparisonType", "CPDAG");
+ return SearchGraphUtils.cpdagForDag(graph);
+ } else if ("PAG".equals(type)) {
+ params.set("graphComparisonType", "PAG");
+ return dagToPag(graph);
+ } else {
+ params.set("graphComparisonType", "DAG");
+ return new EdgeListGraph(graph);
+ }
}
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FasRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FasRunner.java
index 69bc7f6125..b2bd47e8dc 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FasRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FasRunner.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.*;
import edu.cmu.tetrad.util.Parameters;
@@ -116,7 +115,7 @@ public static FasRunner serializableInstance() {
public ImpliedOrientation getMeekRules() {
MeekRules rules = new MeekRules();
rules.setAggressivelyPreventCycles(this.isAggressivelyPreventCycles());
- rules.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ rules.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
return rules;
}
@@ -128,7 +127,7 @@ public String getAlgorithmName() {
//===================PUBLIC METHODS OVERRIDING ABSTRACT================//
public void execute() {
- IKnowledge knowledge = (IKnowledge) getParams().get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) getParams().get("knowledge", new Knowledge());
int depth = getParams().getInt("depth", -1);
Graph graph = new EdgeListGraph(getIndependenceTest().getVariables());
@@ -193,7 +192,7 @@ public boolean supportsKnowledge() {
private boolean isAggressivelyPreventCycles() {
Parameters params = getParams();
if (params != null) {
- return params.getBoolean("aggressivelyPreventCycles", false);
+ return params.getBoolean("aggressivelyPreventCycles", true);
}
return false;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FciRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FciRunner.java
index 2205ca1af9..89fdde84bb 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FciRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FciRunner.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.*;
import edu.cmu.tetrad.util.Parameters;
@@ -105,7 +104,7 @@ public static FciRunner serializableInstance() {
* implemented in the extending class.
*/
public void execute() {
- IKnowledge knowledge = (IKnowledge) getParams().get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) getParams().get("knowledge", new Knowledge());
Graph graph;
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FgesRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FgesRunner.java
index 535472877f..963b0dcf19 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FgesRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/FgesRunner.java
@@ -122,7 +122,7 @@ public void execute() {
if (model instanceof Graph) {
GraphScore gesScore = new GraphScore((Graph) model);
this.fges = new Fges(gesScore);
- this.fges.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ this.fges.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
this.fges.setVerbose(true);
} else {
double penaltyDiscount = params.getDouble("penaltyDiscount", 4);
@@ -201,15 +201,15 @@ public void execute() {
}
this.fges.setExternalGraph(this.externalGraph);
- this.fges.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ this.fges.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
this.fges.setVerbose(true);
this.fges.setFaithfulnessAssumed(params.getBoolean("faithfulnessAssumed", true));
Graph graph = this.fges.search();
if (getSourceGraph() != null) {
GraphUtils.arrangeBySourceGraph(graph, getSourceGraph());
- } else if (((IKnowledge) getParams().get("knowledge", new Knowledge2())).isDefaultToKnowledgeLayout()) {
- SearchGraphUtils.arrangeByKnowledgeTiers(graph, (IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ } else if (((Knowledge) getParams().get("knowledge", new Knowledge())).isDefaultToKnowledgeLayout()) {
+ SearchGraphUtils.arrangeByKnowledgeTiers(graph, (Knowledge) getParams().get("knowledge", new Knowledge()));
} else {
GraphUtils.circleLayout(graph, 200, 200, 150);
}
@@ -344,7 +344,7 @@ public boolean supportsKnowledge() {
public ImpliedOrientation getMeekRules() {
MeekRules rules = new MeekRules();
- rules.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ rules.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
return rules;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/ForbiddenGraphModel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/ForbiddenGraphModel.java
index dad624dc35..6d77b7265b 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/ForbiddenGraphModel.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/ForbiddenGraphModel.java
@@ -20,10 +20,8 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.data.KnowledgeBoxInput;
-import edu.cmu.tetrad.graph.Edge;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
@@ -36,6 +34,8 @@
import java.util.SortedSet;
import java.util.TreeSet;
+import static edu.cmu.tetrad.graph.GraphUtils.addForbiddenReverseEdgesForDirectedEdges;
+
/**
* @author kaalpurush
*/
@@ -137,7 +137,7 @@ public ForbiddenGraphModel(Parameters params, KnowledgeBoxInput input) {
/*
* @serial @deprecated
*/
- IKnowledge knowledge = new Knowledge2();
+ Knowledge knowledge = new Knowledge();
for (Node v : input.getVariables()) {
knowledge.addVariable(v.getName());
@@ -151,41 +151,44 @@ public ForbiddenGraphModel(Parameters params, KnowledgeBoxInput input) {
// simulation or not. If in a simulation, I should print the knowledge.
// If not, I should wait for resetParams to be called. For now I'm
// printing the knowledge if it's not empty.
- if (!((IKnowledge) params.get("knowledge", new Knowledge2())).isEmpty()) {
- TetradLogger.getInstance().log("knowledge", params.get("knowledge", new Knowledge2()).toString());
+ if (!((Knowledge) params.get("knowledge", new Knowledge())).isEmpty()) {
+ TetradLogger.getInstance().log("knowledge", params.get("knowledge", new Knowledge()).toString());
}
}
private void createKnowledge(Parameters params) {
- IKnowledge knwl = getKnowledge();
- if (knwl == null) {
+ Knowledge knowledge = getKnowledge();
+ if (knowledge == null) {
return;
}
- knwl.clear();
+ knowledge.clear();
if (this.resultGraph == null) {
throw new NullPointerException("I couldn't find a parent graph.");
}
- List nodes = this.resultGraph.getNodes();
-
- int numOfNodes = nodes.size();
- for (int i = 0; i < numOfNodes; i++) {
- for (int j = i + 1; j < numOfNodes; j++) {
- Node n1 = nodes.get(i);
- Node n2 = nodes.get(j);
-
- if (n1.getName().startsWith("E_") || n2.getName().startsWith("E_")) {
- continue;
- }
-
- Edge edge = this.resultGraph.getEdge(n1, n2);
- if (edge != null && edge.isDirected()) {
- knwl.setForbidden(edge.getNode2().getName(), edge.getNode1().getName());
- }
- }
- }
+ addForbiddenReverseEdgesForDirectedEdges(resultGraph, knowledge);
+
+
+// List nodes = this.resultGraph.getNodes();
+//
+// int numOfNodes = nodes.size();
+// for (int i = 0; i < numOfNodes; i++) {
+// for (int j = i + 1; j < numOfNodes; j++) {
+// Node n1 = nodes.get(i);
+// Node n2 = nodes.get(j);
+//
+// if (n1.getName().startsWith("E_") || n2.getName().startsWith("E_")) {
+// continue;
+// }
+//
+// Edge edge = this.resultGraph.getEdge(n1, n2);
+// if (edge != null && edge.isDirected()) {
+// knowledge.setForbidden(edge.getNode2().getName(), edge.getNode1().getName());
+// }
+// }
+// }
}
/**
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/GeneralAlgorithmRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/GeneralAlgorithmRunner.java
index bf7076b31a..74f7fe0a9e 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/GeneralAlgorithmRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/GeneralAlgorithmRunner.java
@@ -64,7 +64,7 @@ public class GeneralAlgorithmRunner implements AlgorithmRunner, ParamsResettable
private Graph sourceGraph;
private Graph externalGraph;
private List graphList = new ArrayList<>();
- private IKnowledge knowledge;
+ private Knowledge knowledge;
private final Map userAlgoSelections = new HashMap<>();
private transient List independenceTests;
@@ -89,7 +89,7 @@ public GeneralAlgorithmRunner(DataWrapper dataWrapper, Parameters parameters) {
* containing either a DataSet or a DataSet as its selected model.
*/
public GeneralAlgorithmRunner(DataWrapper dataWrapper, Parameters parameters,
- KnowledgeBoxModel knowledgeBoxModel) {
+ KnowledgeBoxModel knowledgeBoxModel) {
this(dataWrapper, null, parameters, knowledgeBoxModel, null);
}
@@ -98,8 +98,8 @@ public GeneralAlgorithmRunner(DataWrapper dataWrapper, GraphSource graphSource,
}
public GeneralAlgorithmRunner(DataWrapper dataWrapper, GraphSource graphSource,
- KnowledgeBoxModel knowledgeBoxModel,
- Parameters parameters) {
+ KnowledgeBoxModel knowledgeBoxModel,
+ Parameters parameters) {
this(dataWrapper, graphSource, parameters, knowledgeBoxModel, null);
}
@@ -109,7 +109,7 @@ public GeneralAlgorithmRunner(DataWrapper dataWrapper, GraphSource graphSource,
* containing either a DataSet or a DataSet as its selected model.
*/
public GeneralAlgorithmRunner(DataWrapper dataWrapper, Parameters parameters,
- KnowledgeBoxModel knowledgeBoxModel, IndependenceFactsModel facts) {
+ KnowledgeBoxModel knowledgeBoxModel, IndependenceFactsModel facts) {
this(dataWrapper, null, parameters, knowledgeBoxModel, facts);
}
@@ -126,7 +126,7 @@ public GeneralAlgorithmRunner(DataWrapper dataWrapper, GeneralAlgorithmRunner ru
* containing either a DataSet or a DataSet as its selected model.
*/
public GeneralAlgorithmRunner(DataWrapper dataWrapper, GeneralAlgorithmRunner runner, Parameters parameters,
- KnowledgeBoxModel knowledgeBoxModel) {
+ KnowledgeBoxModel knowledgeBoxModel) {
this(dataWrapper, null, parameters, knowledgeBoxModel, null);
this.algorithm = runner.algorithm;
@@ -134,7 +134,7 @@ public GeneralAlgorithmRunner(DataWrapper dataWrapper, GeneralAlgorithmRunner ru
}
public GeneralAlgorithmRunner(DataWrapper dataWrapper, GraphSource graphSource, GeneralAlgorithmRunner runner,
- Parameters parameters) {
+ Parameters parameters) {
this(dataWrapper, graphSource, parameters, null, null);
this.algorithm = runner.algorithm;
@@ -147,8 +147,8 @@ public GeneralAlgorithmRunner(DataWrapper dataWrapper, GraphSource graphSource,
* containing either a DataSet or a DataSet as its selected model.
*/
public GeneralAlgorithmRunner(DataWrapper dataWrapper, GraphSource graphSource, GeneralAlgorithmRunner runner,
- Parameters parameters,
- KnowledgeBoxModel knowledgeBoxModel) {
+ Parameters parameters,
+ KnowledgeBoxModel knowledgeBoxModel) {
this(dataWrapper, graphSource, parameters, knowledgeBoxModel, null);
this.algorithm = runner.algorithm;
@@ -166,12 +166,12 @@ public GeneralAlgorithmRunner(GraphSource graphSource, GeneralAlgorithmRunner ru
}
public GeneralAlgorithmRunner(GraphSource graphSource, Parameters parameters,
- KnowledgeBoxModel knowledgeBoxModel) {
+ KnowledgeBoxModel knowledgeBoxModel) {
this(null, graphSource, parameters, knowledgeBoxModel, null);
}
public GeneralAlgorithmRunner(IndependenceFactsModel model,
- Parameters parameters, KnowledgeBoxModel knowledgeBoxModel) {
+ Parameters parameters, KnowledgeBoxModel knowledgeBoxModel) {
this(null, null, parameters, knowledgeBoxModel, model);
}
@@ -188,7 +188,7 @@ public GeneralAlgorithmRunner(GraphSource graphSource, Parameters parameters) {
* containing either a DataSet or a DataSet as its selected model.
*/
public GeneralAlgorithmRunner(DataWrapper dataWrapper, GraphSource graphSource, Parameters parameters,
- KnowledgeBoxModel knowledgeBoxModel, IndependenceFactsModel facts) {
+ KnowledgeBoxModel knowledgeBoxModel, IndependenceFactsModel facts) {
if (parameters == null) {
throw new NullPointerException();
}
@@ -223,7 +223,7 @@ public GeneralAlgorithmRunner(DataWrapper dataWrapper, GraphSource graphSource,
if (knowledgeBoxModel != null) {
this.knowledge = knowledgeBoxModel.getKnowledge();
} else {
- this.knowledge = new Knowledge2();
+ this.knowledge = new Knowledge();
}
if (facts != null) {
@@ -267,7 +267,7 @@ public void execute() {
}
if (this.algorithm instanceof HasKnowledge) {
- IKnowledge knowledge1 = TimeSeriesUtils.getKnowledge(getSourceGraph());
+ Knowledge knowledge1 = TimeSeriesUtils.getKnowledge(getSourceGraph());
if (this.knowledge.isEmpty() && !knowledge1.isEmpty()) {
((HasKnowledge) algo).setKnowledge(knowledge1);
@@ -276,11 +276,15 @@ public void execute() {
}
}
- graphList.add(algo.search(null, this.parameters));
+ Graph graph = algo.search(null, this.parameters);
+
+ GraphUtils.circleLayout(graph, 200, 200, 150);
+
+ graphList.add(graph);
} else {
if (getAlgorithm() instanceof MultiDataSetAlgorithm) {
for (int k = 0; k < this.parameters.getInt("numRuns"); k++) {
- IKnowledge knowledge1 = getDataModelList().get(0).getKnowledge();
+ Knowledge knowledge1 = getDataModelList().get(0).getKnowledge();
List dataSets = getDataModelList().stream()
.map(e -> (DataSet) e)
.collect(Collectors.toCollection(ArrayList::new));
@@ -324,7 +328,11 @@ public void execute() {
((HasKnowledge) this.algorithm).setKnowledge(this.knowledge.copy());
}
- graphList.add(this.algorithm.search(dataSet, this.parameters));
+ Graph graph = this.algorithm.search(dataSet, this.parameters);
+
+ GraphUtils.circleLayout(graph, 200, 200, 150);
+
+ graphList.add(graph);
} else if (dataModel instanceof DataSet) {
DataSet dataSet = (DataSet) dataModel;
@@ -340,7 +348,10 @@ public void execute() {
((HasKnowledge) this.algorithm).setKnowledge(this.knowledge.copy());
}
- graphList.add(this.algorithm.search(dataSet, this.parameters));
+ Graph graph = this.algorithm.search(dataSet, this.parameters);
+ GraphUtils.circleLayout(graph, 200, 200, 150);
+
+ graphList.add(graph);
}
});
}
@@ -351,7 +362,7 @@ public void execute() {
if (algo != null) {
getDataModelList().forEach(data -> {
- IKnowledge knowledgeFromData = data.getKnowledge();
+ Knowledge knowledgeFromData = data.getKnowledge();
if (!(knowledgeFromData == null || knowledgeFromData.getVariables().isEmpty())) {
this.knowledge = knowledgeFromData;
}
@@ -367,11 +378,17 @@ public void execute() {
}
if (data.isContinuous() && (algDataType == DataType.Continuous || algDataType == DataType.Mixed)) {
- graphList.add(algo.search(data, this.parameters));
+ Graph graph = algo.search(data, this.parameters);
+ GraphUtils.circleLayout(graph, 200, 200, 150);
+ graphList.add(graph);
} else if (data.isDiscrete() && (algDataType == DataType.Discrete || algDataType == DataType.Mixed)) {
- graphList.add(algo.search(data, this.parameters));
+ Graph graph = algo.search(data, this.parameters);
+ GraphUtils.circleLayout(graph, 200, 200, 150);
+ graphList.add(graph);
} else if (data.isMixed() && algDataType == DataType.Mixed) {
- graphList.add(algo.search(data, this.parameters));
+ Graph graph = algo.search(data, this.parameters);
+ GraphUtils.circleLayout(graph, 200, 200, 150);
+ graphList.add(graph);
} else {
throw new IllegalArgumentException("The algorithm was not expecting that type of data.");
}
@@ -383,7 +400,7 @@ public void execute() {
if (algo instanceof HasKnowledge && ((HasKnowledge) algo).getKnowledge().getNumTiers() > 0) {
// && ((HasKnowledge) algo).getKnowledge().getVariablesNotInTiers().size()
// < ((HasKnowledge) algo).getKnowledge().getVariables().size()) {
- IKnowledge _knowledge = ((HasKnowledge) algo).getKnowledge();
+ Knowledge _knowledge = ((HasKnowledge) algo).getKnowledge();
if (_knowledge.getVariablesNotInTiers().size()
< _knowledge.getVariables().size()) {
for (Graph graph : graphList) {
@@ -635,7 +652,9 @@ public Graph getGraph() {
if (this.graphList == null || this.graphList.isEmpty()) {
return null;
} else {
- return this.graphList.get(0);
+ Graph graph = this.graphList.get(0);
+ GraphUtils.circleLayout( graph,225, 225, 180);
+ return graph;
}
}
@@ -644,7 +663,7 @@ public List getGraphs() {
return this.graphList;
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IndTestModel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IndTestModel.java
index 6153da7073..6e83c0a8e4 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IndTestModel.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IndTestModel.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.session.SessionModel;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.TetradSerializableUtils;
@@ -50,8 +49,8 @@ public class IndTestModel implements SessionModel {
*
* @see TetradSerializableUtils
*/
- public static IKnowledge serializableInstance() {
- return new Knowledge2();
+ public static Knowledge serializableInstance() {
+ return new Knowledge();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IndependenceFactsModel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IndependenceFactsModel.java
index c0c1608748..d0f01df30f 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IndependenceFactsModel.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IndependenceFactsModel.java
@@ -21,9 +21,8 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
import edu.cmu.tetrad.data.IndependenceFacts;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.data.KnowledgeBoxInput;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.GraphNode;
@@ -53,8 +52,8 @@ public IndependenceFactsModel() {
/**
* Generates a simple exemplar of this class to test serialization.
*/
- public static IKnowledge serializableInstance() {
- return new Knowledge2();
+ public static Knowledge serializableInstance() {
+ return new Knowledge();
}
public void add(IndependenceFact fact) {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IonRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IonRunner.java
index 66c553d35f..da41666ff7 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IonRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/IonRunner.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
@@ -202,7 +201,7 @@ public void execute() {
ion.setAdjacencySearch(getParams().getBoolean("pruneByAdjacencies", true));
ion.setPathLengthSearch(getParams().getBoolean("pruneByPathLength", true));
- ion.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ ion.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
List graphs = ion.search();
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/KnowledgeBoxModel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/KnowledgeBoxModel.java
index bdd64ac747..9d4f0b761f 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/KnowledgeBoxModel.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/KnowledgeBoxModel.java
@@ -20,8 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.data.KnowledgeBoxInput;
import edu.cmu.tetrad.data.KnowledgeTransferable;
import edu.cmu.tetrad.graph.EdgeListGraph;
@@ -45,13 +44,13 @@ public class KnowledgeBoxModel implements SessionModel, ParamsResettable, Knowle
private final Graph sourceGraph = new EdgeListGraph();
private String name;
private Parameters params;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
private List variables = new ArrayList<>();
private List variableNames = new ArrayList<>();
private int numTiers = 3;
public KnowledgeBoxModel(Parameters params) {
- this.knowledge = new Knowledge2();
+ this.knowledge = new Knowledge();
this.numTiers = 3;
this.variables = new ArrayList<>();
this.params = params;
@@ -102,12 +101,12 @@ public KnowledgeBoxModel(KnowledgeBoxInput[] inputs, Parameters params) {
this.params = params;
Object myKnowledge = params.get("__myKnowledge");
- if (myKnowledge instanceof IKnowledge
- && new HashSet<>(((IKnowledge) myKnowledge).getVariables())
+ if (myKnowledge instanceof Knowledge
+ && new HashSet<>(((Knowledge) myKnowledge).getVariables())
.equals(new HashSet<>(variableNames))) {
- this.knowledge = (IKnowledge) myKnowledge;
+ this.knowledge = (Knowledge) myKnowledge;
} else {
- this.knowledge = new Knowledge2();
+ this.knowledge = new Knowledge();
for (String var : variableNames) {
this.knowledge.addVariable(var);
@@ -140,7 +139,7 @@ private void freshenKnowledgeIfEmpty(List varNames) {
}
}
- private void createKnowledge(IKnowledge knowledge) {
+ private void createKnowledge(Knowledge knowledge) {
knowledge.clear();
this.variableNames.clear();
for (String varName : knowledge.getVariables()) {
@@ -174,12 +173,12 @@ public List getVarNames() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
+ public void setKnowledge(Knowledge knowledge) {
if (knowledge == null) {
throw new NullPointerException();
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/KnowledgeEditable.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/KnowledgeEditable.java
index 2f88a57c59..4263637d75 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/KnowledgeEditable.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/KnowledgeEditable.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import java.util.List;
@@ -37,12 +37,12 @@ public interface KnowledgeEditable {
/**
* @return a copy of the knowledge for this class.
*/
- IKnowledge getKnowledge();
+ Knowledge getKnowledge();
/**
* Sets knowledge to a copy of the given object.
*/
- void setKnowledge(IKnowledge knowledge);
+ void setKnowledge(Knowledge knowledge);
/**
* @return the source graph. This will be used to arrange the graph in the
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MarkovCheckIndTestModel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MarkovCheckIndTestModel.java
index bee3164407..61058a962f 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MarkovCheckIndTestModel.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MarkovCheckIndTestModel.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.search.IndependenceResult;
import edu.cmu.tetrad.session.SessionModel;
@@ -43,7 +42,8 @@ public class MarkovCheckIndTestModel implements SessionModel, GraphSource {
private final IndTestProducer indTestProducer;
private String name = "";
private List vars = new LinkedList<>();
- private List results = new ArrayList<>();
+ private List resultsIndep = new ArrayList<>();
+ private List resultsDep = new ArrayList<>();
private final Graph graph;
/**
@@ -51,8 +51,8 @@ public class MarkovCheckIndTestModel implements SessionModel, GraphSource {
*
* @see TetradSerializableUtils
*/
- public static IKnowledge serializableInstance() {
- return new Knowledge2();
+ public static Knowledge serializableInstance() {
+ return new Knowledge();
}
@@ -88,12 +88,20 @@ public List getVars() {
return this.vars;
}
- public List getResults() {
- return this.results;
+ public List getResults(boolean indep) {
+ if (indep) {
+ return this.resultsIndep;
+ } else {
+ return this.resultsDep;
+ }
}
- public void setResults(List results) {
- this.results = results;
+ public void setResults(List results, boolean indep) {
+ if (indep) {
+ this.resultsIndep = results;
+ } else {
+ this.resultsDep = results;
+ }
}
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MimBuildRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MimBuildRunner.java
index 3da0c15cfb..a36ed479d7 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MimBuildRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MimBuildRunner.java
@@ -103,7 +103,7 @@ public void execute() throws Exception {
Mimbuild mimbuild = new Mimbuild();
mimbuild.setPenaltyDiscount(getParams().getDouble(Params.PENALTY_DISCOUNT));
- mimbuild.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ mimbuild.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
if (getParams().getBoolean("includeThreeClusters", true)) {
mimbuild.setMinClusterSize(3);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MimBuildTrekRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MimBuildTrekRunner.java
index d5ec06340e..dd3843f4d9 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MimBuildTrekRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/MimBuildTrekRunner.java
@@ -127,7 +127,7 @@ public void execute() throws Exception {
MimbuildTrek mimbuild = new MimbuildTrek();
mimbuild.setAlpha(getParams().getDouble("alpha", 0.001));
- mimbuild.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ mimbuild.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
if (getParams().getBoolean("includeThreeClusters", true)) {
mimbuild.setMinClusterSize(3);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/Misclassifications.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/Misclassifications.java
index 9e03f22553..0ad14464ce 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/Misclassifications.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/Misclassifications.java
@@ -21,61 +21,37 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
-import edu.cmu.tetrad.graph.*;
+import edu.cmu.tetrad.data.DataSet;
+import edu.cmu.tetrad.graph.EdgeListGraph;
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.graph.MisclassificationUtils;
+import edu.cmu.tetrad.search.SearchGraphUtils;
import edu.cmu.tetrad.session.DoNotAddOldModel;
import edu.cmu.tetrad.session.SessionModel;
-import edu.cmu.tetrad.util.*;
+import edu.cmu.tetrad.util.Parameters;
+import edu.cmu.tetrad.util.TetradLogger;
import java.io.IOException;
import java.io.ObjectInputStream;
-import java.text.NumberFormat;
-import java.util.*;
+
+import static edu.cmu.tetrad.search.SearchGraphUtils.dagToPag;
/**
- * Compares a target workbench with a reference workbench using an edge type
- * misclassification matrix and an endpoint misclassification matrix.
+ * Compares a target workbench with a reference workbench by counting errors of
+ * omission and commission. (for edge presence only, not orientation).
*
* @author Joseph Ramsey
+ * @author Erin Korber (added remove latents functionality July 2004)
*/
public final class Misclassifications implements SessionModel, DoNotAddOldModel {
static final long serialVersionUID = 23L;
- private Algorithm algorithm;
- private boolean useVcpcOutputs;
- private boolean useCpcOutputs;
- private boolean usePcOutputs;
- private boolean useSvcpcOutputs;
- private boolean useScpcOutputs;
- private boolean useSFcpcOutputs;
- private boolean useFcpcOutputs;
-
- private Set vcpcAdjacent;
- private Set vcpcApparent;
- private Set vcpcDefinite;
- private List vcpcNodes;
-
- private Set fvcpcAdjacent;
- private List fvcpcNodes;
-
- private Set sfVcpcAdjacent;
- private List sfVcpcNodes;
-
- private Set sVcpcAdjacent;
- private Set sVcpcApparent;
- private Set sVcpcDefinite;
- private List sVcpcNodes;
-
- private Set pcAdjacent;
- private Set pcNonadjacent;
- private List pcNodes;
- private String name;
+ private final Graph targetGraph;
+ private final Graph referenceGraph;
private final Parameters params;
- private List targetGraphs = new ArrayList<>();
- private List referenceGraphs = new ArrayList<>();
+ private String name;
- private NumberFormat nf;
//=============================CONSTRUCTORS==========================//
@@ -84,191 +60,43 @@ public final class Misclassifications implements SessionModel, DoNotAddOldModel
* of omission and commission. The counts can be retrieved using the methods
* countOmissionErrors and countCommissionErrors.
*/
- public Misclassifications(MultipleGraphSource model1, MultipleGraphSource model2,
- Parameters params) {
+ public Misclassifications(GraphSource model1, GraphSource model2, Parameters params) {
if (params == null) {
throw new NullPointerException("Parameters must not be null");
}
- if (model1 instanceof VcpcRunner && model2 instanceof PcRunner) {
- this.usePcOutputs = true;
- setVcpcFields((VcpcRunner) model1);
- setPcFields((PcRunner) model2);
- }
-
- if ((model2 instanceof VcpcRunner && model1 instanceof PcRunner)) {
- this.usePcOutputs = true;
- setVcpcFields((VcpcRunner) model2);
- setPcFields((PcRunner) model1);
- }
-
- if (model1 instanceof VcpcRunner && model2 instanceof SampleVcpcRunner) {
- this.useSvcpcOutputs = true;
- setVcpcFields((VcpcRunner) model1);
- setSvcpcFields((SampleVcpcRunner) model2);
- }
-
- if ((model2 instanceof VcpcRunner && model1 instanceof SampleVcpcRunner)) {
- this.useSvcpcOutputs = true;
- setVcpcFields((VcpcRunner) model2);
- setSvcpcFields((SampleVcpcRunner) model1);
-
+ if (model1 == null || model2 == null) {
+ throw new NullPointerException("Null graph source>");
}
this.params = params;
String referenceName = params.getString("referenceGraphName", null);
- if (referenceName == null) {
- throw new IllegalArgumentException("Must specify a reference graph.");
- }
+ String model1Name = model1.getName();
+ String model2Name = model2.getName();
- if (referenceName.equals(model1.getName())) {
- if (model1 instanceof Simulation && model2 instanceof GeneralAlgorithmRunner) {
- this.referenceGraphs = ((GeneralAlgorithmRunner) model2).getCompareGraphs(model1.getGraphs());
- } else if (model1 instanceof MultipleGraphSource) {
- this.referenceGraphs = model1.getGraphs();
- }
-
- if (model2 instanceof MultipleGraphSource) {
- this.targetGraphs = model2.getGraphs();
- }
-
- if (this.referenceGraphs.size() == 1 && this.targetGraphs.size() > 1) {
- Graph graph = this.referenceGraphs.get(0);
- this.referenceGraphs = new ArrayList<>();
- this.referenceGraphs.addAll(this.targetGraphs);
- }
-
- if (this.targetGraphs.size() == 1 && this.referenceGraphs.size() > 1) {
- Graph graph = this.targetGraphs.get(0);
- this.targetGraphs = new ArrayList<>();
- for (Graph _graph : this.referenceGraphs) {
- this.targetGraphs.add(graph);
- }
- }
-
- if (this.referenceGraphs == null) {
- this.referenceGraphs = Collections.singletonList(((GraphSource) model1).getGraph());
- }
-
- if (this.targetGraphs == null) {
- this.targetGraphs = Collections.singletonList(((GraphSource) model2).getGraph());
- }
- } else if (referenceName.equals(model2.getName())) {
- if (model2 instanceof Simulation && model1 instanceof GeneralAlgorithmRunner) {
- this.referenceGraphs = ((GeneralAlgorithmRunner) model1).getCompareGraphs(model2.getGraphs());
- } else if (model1 instanceof MultipleGraphSource) {
- this.referenceGraphs = model2.getGraphs();
- }
-
- if (model1 instanceof MultipleGraphSource) {
- this.targetGraphs = model1.getGraphs();
- }
-
- if (this.referenceGraphs.size() == 1 && this.targetGraphs.size() > 1) {
- Graph graph = this.referenceGraphs.get(0);
- this.referenceGraphs = new ArrayList<>();
- this.referenceGraphs.addAll(this.targetGraphs);
- }
-
- if (this.targetGraphs.size() == 1 && this.referenceGraphs.size() > 1) {
- Graph graph = this.targetGraphs.get(0);
- this.targetGraphs = new ArrayList<>();
- for (Graph _graph : this.referenceGraphs) {
- this.targetGraphs.add(graph);
- }
- }
-
- if (this.referenceGraphs == null) {
- this.referenceGraphs = Collections.singletonList(((GraphSource) model2).getGraph());
- }
-
- if (this.targetGraphs == null) {
- this.targetGraphs = Collections.singletonList(((GraphSource) model1).getGraph());
- }
+ if (referenceName.equals(model1Name)) {
+ this.referenceGraph = model1.getGraph();
+ this.targetGraph = model2.getGraph();
+ } else if (referenceName.equals(model2Name)) {
+ this.referenceGraph = model2.getGraph();
+ this.targetGraph = model1.getGraph();
} else {
- throw new IllegalArgumentException(
- "Neither of the supplied session models is named '" +
- referenceName + "'.");
+ this.referenceGraph = model1.getGraph();
+ this.targetGraph = model2.getGraph();
}
- for (int i = 0; i < this.targetGraphs.size(); i++) {
- this.targetGraphs.set(i, GraphUtils.replaceNodes(this.targetGraphs.get(i), this.referenceGraphs.get(i).getNodes()));
- }
-
- if (this.algorithm != null) {
- for (int i = 0; i < this.referenceGraphs.size(); i++) {
- this.referenceGraphs.set(i, this.algorithm.getComparisonGraph(this.referenceGraphs.get(i)));
- }
- }
-
- if (this.referenceGraphs.size() != this.targetGraphs.size()) {
- throw new IllegalArgumentException("I was expecting the same number of graphs in each parent.");
- }
-
- TetradLogger.getInstance().
-
- log("info", "Graph Comparison");
-
- for (
- int i = 0;
- i < this.referenceGraphs.size(); i++) {
- TetradLogger.getInstance().log("comparison", "\nModel " + (i + 1));
- TetradLogger.getInstance().log("comparison", getComparisonString(i));
- }
-
- this.nf = NumberFormatUtil.getInstance().
-
- getNumberFormat();
-
- }
-
- private void setVcpcFields(VcpcRunner vcpc) {
- this.vcpcAdjacent = vcpc.getAdj();
- this.vcpcApparent = vcpc.getAppNon();
- this.vcpcDefinite = vcpc.getDefNon();
- this.vcpcNodes = vcpc.getGraph().getNodes();
- }
-
- private void setSvcpcFields(SampleVcpcRunner svcpc) {
- this.sVcpcAdjacent = svcpc.getAdj();
- this.sVcpcApparent = svcpc.getAppNon();
- this.sVcpcDefinite = svcpc.getDefNon();
- this.sVcpcNodes = svcpc.getGraph().getNodes();
- }
-
- private void setVcpcFastFields(VcpcFastRunner fvcpc) {
- this.fvcpcAdjacent = fvcpc.getAdj();
- Set fvcpcApparent = fvcpc.getAppNon();
- Set fvcpcDefinite = fvcpc.getDefNon();
- this.fvcpcNodes = fvcpc.getGraph().getNodes();
- }
+ TetradLogger.getInstance().log("info", "Graph Comparison");
- private void setSfvcpcFields(SampleVcpcFastRunner sfvcpc) {
- this.sfVcpcAdjacent = sfvcpc.getAdj();
- Set sfVcpcApparent = sfvcpc.getAppNon();
- Set sfVcpcDefinite = sfvcpc.getDefNon();
- this.sfVcpcNodes = sfvcpc.getGraph().getNodes();
}
- private void setPcFields(PcRunner pc) {
- this.pcAdjacent = pc.getAdj();
- this.pcNonadjacent = pc.getNonAdj();
- this.pcNodes = pc.getGraph().getNodes();
- }
+ //==============================PUBLIC METHODS========================//
- /**
- * Generates a simple exemplar of this class to test serialization.
- *
- * @see TetradSerializableUtils
- */
- public static Node serializableInstance() {
- return new GraphNode("X");
+ public DataSet getDataSet() {
+ return (DataSet) this.params.get("dataSet", null);
}
- //==============================PUBLIC METHODS========================//
-
public String getName() {
return this.name;
}
@@ -277,536 +105,24 @@ public void setName(String name) {
this.name = name;
}
- public String getComparisonString(int i) {
+ public String getComparisonString() {
+ String refName = getParams().getString("referenceGraphName", null);
+ String targetName = getParams().getString("targetGraphName", null);
- if (this.useVcpcOutputs) {
- return (this.params.get("referenceGraphName", null) + " down the left; " +
- this.params.get("targetGraphName", null) + " across the top.") +
- "\n\nAdjacency Misclassification:\n" + adjacencyMisclassificationsOne() +
- "\nEdge Misclassifications:\n" +
- MisclassificationUtils.edgeMisclassifications(this.targetGraphs.get(i), this.referenceGraphs.get(i));
- }
- if (this.useCpcOutputs) {
- return (this.params.get("referenceGraphName", null) + " down the left; " +
- this.params.get("targetGraphName", null) + " across the top.") +
- "\n\nAdjacency Misclassification:\n" + adjacencyMisclassificationsTwo() +
- "\nEdge Misclassifications:\n" +
- MisclassificationUtils.edgeMisclassifications(this.targetGraphs.get(i), this.referenceGraphs.get(i));
- }
- if (this.usePcOutputs) {
- return (this.params.get("referenceGraphName", null) + " down the left; " +
- this.params.get("targetGraphName", null) + " across the top.") +
- "\n\nAdjacency Misclassification:\n" + adjacencyMisclassificationsThree() +
- "\nEdge Misclassifications:\n" +
- MisclassificationUtils.edgeMisclassifications(this.targetGraphs.get(i), this.referenceGraphs.get(i));
- }
+ Graph comparisonGraph = getComparisonGraph(referenceGraph, params);
- if (this.useSvcpcOutputs) {
- return (this.params.get("targetGraphName", null) + " down the left; " +
- this.params.get("referenceGraphName", null) + " across the top.") +
- "\n\nAdjacency Misclassification:\n" + adjacencyMisclassificationsFour() +
- "\nEdge Misclassifications:\n" +
- MisclassificationUtils.edgeMisclassifications(this.targetGraphs.get(i), this.referenceGraphs.get(i));
- }
- if (this.useScpcOutputs) {
- return (this.params.get("referenceGraphName", null) + " down the left; " +
- this.params.get("targetGraphName", null) + " across the top.") +
- "\n\nAdjacency Misclassification:\n" + adjacencyMisclassificationsFive() +
- "\nEdge Misclassifications:\n" +
- MisclassificationUtils.edgeMisclassifications(this.targetGraphs.get(i), this.referenceGraphs.get(i));
- }
-
- if (this.useSFcpcOutputs) {
- return (this.params.get("referenceGraphName", null) + " down the left; " +
- this.params.get("targetGraphName", null) + " across the top.") +
- "\n\nAdjacency Misclassification:\n" + adjacencyMisclassificationsSix() +
- "\nEdge Misclassifications:\n" +
- MisclassificationUtils.edgeMisclassifications(this.targetGraphs.get(i), this.referenceGraphs.get(i));
- }
-
- if (this.useFcpcOutputs) {
- return (this.params.get("referenceGraphName", null) + " down the left; " +
- this.params.get("targetGraphName", null) + " across the top.") +
- "\n\nAdjacency Misclassification:\n" + adjacencyMisclassificationsSeven() +
- "\n\nEndpoint Misclassification:\n" + "\nEdge Misclassifications:\n" +
- MisclassificationUtils.edgeMisclassifications(this.targetGraphs.get(i), this.referenceGraphs.get(i));
- } else {
- return (this.params.get("referenceGraphName", null) + " down the left; " +
- this.params.get("targetGraphName", null) + " across the top.") +
- "\n\nEdge Misclassification:\n" +
- MisclassificationUtils.edgeMisclassifications(this.targetGraphs.get(i), this.referenceGraphs.get(i)) +
- "\nEndpoint Misclassification:\n" +
- MisclassificationUtils.endpointMisclassification(this.targetGraphs.get(i), this.referenceGraphs.get(i));
- }
+ return "True graph from " + refName + "\nTarget graph from " + targetName +
+ "\n\n\n" +
+ "Edge Misclassification Table" +
+ "\n" +
+ MisclassificationUtils.edgeMisclassifications(targetGraph, comparisonGraph) +
+ "\n\n" +
+ "Endpoint Misclassification Table:" +
+ "\n\n" +
+ MisclassificationUtils.endpointMisclassification(targetGraph, comparisonGraph);
}
- private String adjacencyMisclassificationsFour() {
-
- if (this.sVcpcNodes == null) {
- throw new NullPointerException("Please run SVCPC first, jerk");
- }
- if (this.vcpcNodes == null) {
- throw new NullPointerException("Please run VCPC first, or see Nich");
- }
-
- this.nf = NumberFormatUtil.getInstance().getNumberFormat();
-
- Set adjAppNonAdj = new HashSet<>();
- Set adjDefNonAdj = new HashSet<>();
- Set nonAdjAppNonAdj = new HashSet<>();
- Set nonAdjDefNonAdj = new HashSet<>();
-
- Set sVcpcAdj = MisclassificationUtils.convertNodes(this.sVcpcAdjacent, this.vcpcNodes);
- Set sVcpcAppNonadj = MisclassificationUtils.convertNodes(this.sVcpcApparent, this.vcpcNodes);
- Set sVcpcDefNonadj = MisclassificationUtils.convertNodes(this.sVcpcDefinite, this.vcpcNodes);
-
- Set vcpcAdj = new HashSet<>(this.vcpcAdjacent);
-
-
- for (Edge edge : sVcpcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
- for (Edge edge : vcpcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
-
- int[][] tableAdj = new int[3][3];
-
- for (Edge edge : sVcpcAppNonadj) {
-
- if (this.vcpcApparent.contains(edge)) {
- tableAdj[0][0]++;
- tableAdj[0][2]++;
- tableAdj[2][0]++;
- adjAppNonAdj.add(edge);
- }
- if (this.vcpcDefinite.contains(edge)) {
- tableAdj[1][0]++;
- tableAdj[1][2]++;
- tableAdj[2][0]++;
- adjDefNonAdj.add(edge);
- }
-
- }
-
- TetradLogger.getInstance().log("adjacenciesApp", "\n Apparent non-Adjacencies marked Apparent Non-adjacent" + adjAppNonAdj);
- TetradLogger.getInstance().log("adjacenciesDef", "\n Apparent non-Adjacencies marked Definite Non-adjacent" + adjDefNonAdj);
-
- for (Edge edge : sVcpcDefNonadj) {
- if (this.vcpcApparent.contains(edge)) {
- tableAdj[0][1]++;
- tableAdj[0][2]++;
- tableAdj[2][1]++;
- nonAdjAppNonAdj.add(edge);
- }
- if (this.vcpcDefinite.contains(edge)) {
- tableAdj[1][1]++;
- tableAdj[1][2]++;
- tableAdj[2][1]++;
- nonAdjDefNonAdj.add(edge);
- }
- }
-
-
- TetradLogger.getInstance().log("nonadjacenciesApp", "\n Definite Non-Adjacencies marked Apparent Non-adjacent" + nonAdjAppNonAdj);
- TetradLogger.getInstance().log("nonadjacenciesDef", "\n Definite Non-Adjacencies marked Definite Non-adjacent" + nonAdjDefNonAdj);
-
- StringBuilder builder = new StringBuilder();
-
- TextTable table9 = new TextTable(4, 4);
-
-
- table9.setToken(1, 0, "Apparently Nonadjacent");
- table9.setToken(2, 0, "Definitely Nonadjacent");
- table9.setToken(3, 0, "Total");
-
- table9.setToken(0, 1, "Apparently Nonadjacent");
- table9.setToken(0, 2, "Definitely Nonadjacent");
- table9.setToken(0, 3, "Total");
-
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 3; j++) {
- table9.setToken(i + 1, j + 1, this.nf.format(tableAdj[i][j]));
-
- }
- }
- builder.append("\n").append(table9);
- return builder.toString();
- }
-
- private String adjacencyMisclassificationsFive() {
-
- if (this.sVcpcNodes == null) {
- throw new NullPointerException("Please run sVCPC first, jerk");
- }
-
- this.nf = NumberFormatUtil.getInstance().getNumberFormat();
-
- Set adjAppNonAdj = new HashSet<>();
- Set adjDefNonAdj = new HashSet<>();
- Set nonAdjAppNonAdj = new HashSet<>();
- Set nonAdjDefNonAdj = new HashSet<>();
-
-
- Set svcpcAdj = new HashSet<>(this.sVcpcAdjacent);
-
- for (Edge edge : svcpcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
-
- int[][] tableAdj = new int[4][3];
-
- TetradLogger.getInstance().log("adjacenciesApp", "\n Adjacencies marked Apparent Non-adjacent" + adjAppNonAdj);
- TetradLogger.getInstance().log("adjacenciesDef", "\n Adjacencies marked Definite Non-adjacent" + adjDefNonAdj);
-
- TetradLogger.getInstance().log("nonadjacenciesApp", "\n Non-Adjacencies marked Apparent Non-adjacent" + nonAdjAppNonAdj);
- TetradLogger.getInstance().log("nonadjacenciesDef", "\n Non-Adjacencies marked Definite Non-adjacent" + nonAdjDefNonAdj);
-
- StringBuilder builder = new StringBuilder();
-
- TextTable table9 = new TextTable(5, 4);
-
- table9.setToken(1, 0, "Adjacent");
- table9.setToken(2, 0, "Apparently Nonadjacent");
- table9.setToken(3, 0, "Definitely Nonadjacent");
- table9.setToken(4, 0, "Total");
-
- table9.setToken(0, 1, "Adjacent");
- table9.setToken(0, 2, "Nonadjacent");
- table9.setToken(0, 3, "Total");
-
- for (int i = 0; i < 4; i++) {
- for (int j = 0; j < 3; j++) {
- table9.setToken(i + 1, j + 1, this.nf.format(tableAdj[i][j]));
-
- }
- }
- builder.append("\n").append(table9);
- System.out.println("Sample CM: " + table9);
- return builder.toString();
- }
-
-
- private String adjacencyMisclassificationsSix() {
-
- if (this.sfVcpcNodes == null) {
- throw new NullPointerException("Please run sfVCPC first, jerk");
- }
-
- this.nf = NumberFormatUtil.getInstance().getNumberFormat();
-
- Set adjAppNonAdj = new HashSet<>();
- Set adjDefNonAdj = new HashSet<>();
- Set nonAdjAppNonAdj = new HashSet<>();
- Set nonAdjDefNonAdj = new HashSet<>();
-
-
- Set sfvcpcAdj = new HashSet<>(this.sfVcpcAdjacent);
-
- for (Edge edge : sfvcpcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
-
- int[][] tableAdj = new int[4][3];
-
- TetradLogger.getInstance().log("adjacenciesApp", "\n Adjacencies marked Apparent Non-adjacent" + adjAppNonAdj);
- TetradLogger.getInstance().log("adjacenciesDef", "\n Adjacencies marked Definite Non-adjacent" + adjDefNonAdj);
-
- TetradLogger.getInstance().log("nonadjacenciesApp", "\n Non-Adjacencies marked Apparent Non-adjacent" + nonAdjAppNonAdj);
- TetradLogger.getInstance().log("nonadjacenciesDef", "\n Non-Adjacencies marked Definite Non-adjacent" + nonAdjDefNonAdj);
-
- StringBuilder builder = new StringBuilder();
-
- TextTable table9 = new TextTable(5, 4);
-
- table9.setToken(1, 0, "Adjacent");
- table9.setToken(2, 0, "Apparently Nonadjacent");
- table9.setToken(3, 0, "Definitely Nonadjacent");
- table9.setToken(4, 0, "Total");
-
- table9.setToken(0, 1, "Adjacent");
- table9.setToken(0, 2, "Nonadjacent");
- table9.setToken(0, 3, "Total");
-
- for (int i = 0; i < 4; i++) {
- for (int j = 0; j < 3; j++) {
- table9.setToken(i + 1, j + 1, this.nf.format(tableAdj[i][j]));
-
- }
- }
- builder.append("\n").append(table9);
- System.out.println("Sample Fast CM: " + table9);
- return builder.toString();
- }
-
- private String adjacencyMisclassificationsSeven() {
-
- if (this.fvcpcNodes == null) {
- throw new NullPointerException("Please run fVCPC first, jerk");
- }
-
- this.nf = NumberFormatUtil.getInstance().getNumberFormat();
-
- Set adjAppNonAdj = new HashSet<>();
- Set adjDefNonAdj = new HashSet<>();
- Set nonAdjAppNonAdj = new HashSet<>();
- Set nonAdjDefNonAdj = new HashSet<>();
-
-
- Set fvcpcAdj = new HashSet<>(this.fvcpcAdjacent);
-
- for (Edge edge : fvcpcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
-
- int[][] tableAdj = new int[4][3];
-
- TetradLogger.getInstance().log("adjacenciesApp", "\n Adjacencies marked Apparent Non-adjacent" + adjAppNonAdj);
- TetradLogger.getInstance().log("adjacenciesDef", "\n Adjacencies marked Definite Non-adjacent" + adjDefNonAdj);
-
- TetradLogger.getInstance().log("nonadjacenciesApp", "\n Non-Adjacencies marked Apparent Non-adjacent" + nonAdjAppNonAdj);
- TetradLogger.getInstance().log("nonadjacenciesDef", "\n Non-Adjacencies marked Definite Non-adjacent" + nonAdjDefNonAdj);
-
- StringBuilder builder = new StringBuilder();
-
- TextTable table9 = new TextTable(5, 4);
-
- table9.setToken(1, 0, "Adjacent");
- table9.setToken(2, 0, "Apparently Nonadjacent");
- table9.setToken(3, 0, "Definitely Nonadjacent");
- table9.setToken(4, 0, "Total");
-
- table9.setToken(0, 1, "Adjacent");
- table9.setToken(0, 2, "Nonadjacent");
- table9.setToken(0, 3, "Total");
-
- for (int i = 0; i < 4; i++) {
- for (int j = 0; j < 3; j++) {
- table9.setToken(i + 1, j + 1, this.nf.format(tableAdj[i][j]));
-
- }
- }
- builder.append("\n").append(table9);
- System.out.println("Sample CM: " + table9);
- return builder.toString();
- }
-
-
- private String adjacencyMisclassificationsOne() {
-
- if (this.vcpcNodes == null) {
- throw new NullPointerException("Please run VCPC first, or see Nich");
- }
-
- this.nf = NumberFormatUtil.getInstance().getNumberFormat();
-
- Set adjAppNonAdj = new HashSet<>();
- Set adjDefNonAdj = new HashSet<>();
- Set nonAdjAppNonAdj = new HashSet<>();
- Set nonAdjDefNonAdj = new HashSet<>();
-
-
- Set vcpcAdj = new HashSet<>(this.vcpcAdjacent);
-
- for (Edge edge : vcpcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
-
- int[][] tableAdj = new int[4][3];
-
- TetradLogger.getInstance().log("adjacenciesApp", "\n Adjacencies marked Apparent Non-adjacent" + adjAppNonAdj);
- TetradLogger.getInstance().log("adjacenciesDef", "\n Adjacencies marked Definite Non-adjacent" + adjDefNonAdj);
-
- TetradLogger.getInstance().log("nonadjacenciesApp", "\n Non-Adjacencies marked Apparent Non-adjacent" + nonAdjAppNonAdj);
- TetradLogger.getInstance().log("nonadjacenciesDef", "\n Non-Adjacencies marked Definite Non-adjacent" + nonAdjDefNonAdj);
-
- StringBuilder builder = new StringBuilder();
-
- TextTable table9 = new TextTable(5, 4);
-
- table9.setToken(1, 0, "Adjacent");
- table9.setToken(2, 0, "Apparently Nonadjacent");
- table9.setToken(3, 0, "Definitely Nonadjacent");
- System.out.println(table9);
- table9.setToken(4, 0, "Total");
-
- table9.setToken(0, 1, "Adjacent");
- table9.setToken(0, 2, "Nonadjacent");
- table9.setToken(0, 3, "Total");
-
- for (int i = 0; i < 4; i++) {
- for (int j = 0; j < 3; j++) {
- table9.setToken(i + 1, j + 1, this.nf.format(tableAdj[i][j]));
-
- }
- }
- builder.append("\n").append(table9);
- System.out.println("VCPC CM: " + table9);
- return builder.toString();
- }
-
- private String adjacencyMisclassificationsTwo() {
-
- if (this.pcNodes == null) {
- throw new NullPointerException("Please run PC first, or see Nich");
- }
-
- this.nf = NumberFormatUtil.getInstance().getNumberFormat();
-
- Set pcAdj = new HashSet<>(this.pcAdjacent);
-
- for (Edge edge : pcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
- int[][] tableAdj = new int[3][3];
-
- StringBuilder builder = new StringBuilder();
-
- TextTable table9 = new TextTable(4, 4);
-
- table9.setToken(1, 0, "Adjacent");
- table9.setToken(2, 0, "Nonadjacent");
- table9.setToken(3, 0, "Total");
-
- table9.setToken(0, 1, "Adjacent");
- table9.setToken(0, 2, "Nonadjacent");
- table9.setToken(0, 3, "Total");
-
- for (int i = 0; i < 3; i++) {
- for (int j = 0; j < 3; j++) {
- table9.setToken(i + 1, j + 1, this.nf.format(tableAdj[i][j]));
-
- }
- }
- builder.append("\n").append(table9);
- System.out.println("PC CM: " + table9);
- return builder.toString();
- }
-
- private String adjacencyMisclassificationsThree() {
-
- if (this.pcNodes == null) {
- throw new NullPointerException("Please run CPC first, jerk");
- }
- if (this.vcpcNodes == null) {
- throw new NullPointerException("Please run VCPC first, or see Nich");
- }
-
- this.nf = NumberFormatUtil.getInstance().getNumberFormat();
-
- Set adjAppNonAdj = new HashSet<>();
- Set adjDefNonAdj = new HashSet<>();
- Set nonAdjAppNonAdj = new HashSet<>();
- Set nonAdjDefNonAdj = new HashSet<>();
-
-
- Set pcAdj = MisclassificationUtils.convertNodes(this.pcAdjacent, this.vcpcNodes);
- Set pcNonadj = MisclassificationUtils.convertNodes(this.pcNonadjacent, this.vcpcNodes);
-
-
- Set vcpcAdj = new HashSet<>(this.vcpcAdjacent);
-
- for (Edge edge : pcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
- for (Edge edge : vcpcAdj) {
- edge.setEndpoint1(Endpoint.TAIL);
- edge.setEndpoint2(Endpoint.TAIL);
- }
-
- int[][] tableAdj = new int[4][3];
-
- for (Edge edge : pcAdj) {
-
- if (vcpcAdj.contains(edge)) {
- tableAdj[0][0]++;
- tableAdj[0][2]++;
- tableAdj[3][0]++;
- }
- if (this.vcpcApparent.contains(edge)) {
- tableAdj[1][0]++;
- tableAdj[1][2]++;
- tableAdj[3][0]++;
- adjAppNonAdj.add(edge);
- }
- if (this.vcpcDefinite.contains(edge)) {
- tableAdj[2][0]++;
- tableAdj[2][2]++;
- tableAdj[3][0]++;
- adjDefNonAdj.add(edge);
- }
- }
-
- TetradLogger.getInstance().log("adjacenciesApp", "\n Adjacencies marked Apparent Non-adjacent" + adjAppNonAdj);
- TetradLogger.getInstance().log("adjacenciesDef", "\n Adjacencies marked Definite Non-adjacent" + adjDefNonAdj);
-
- for (Edge edge : pcNonadj) {
- if (vcpcAdj.contains(edge)) {
- tableAdj[0][1]++;
- tableAdj[0][2]++;
- tableAdj[3][1]++;
- }
- if (this.vcpcApparent.contains(edge)) {
- tableAdj[1][1]++;
- tableAdj[1][2]++;
- tableAdj[3][1]++;
- nonAdjAppNonAdj.add(edge);
- }
- if (this.vcpcDefinite.contains(edge)) {
- tableAdj[2][1]++;
- tableAdj[2][2]++;
- tableAdj[3][1]++;
- nonAdjDefNonAdj.add(edge);
- }
- }
-
- TetradLogger.getInstance().log("nonadjacenciesApp", "\n Non-Adjacencies marked Apparent Non-adjacent" + nonAdjAppNonAdj);
- TetradLogger.getInstance().log("nonadjacenciesDef", "\n Non-Adjacencies marked Definite Non-adjacent" + nonAdjDefNonAdj);
-
-
- StringBuilder builder = new StringBuilder();
-
- TextTable table9 = new TextTable(5, 4);
-
- table9.setToken(1, 0, "Adjacent");
- table9.setToken(2, 0, "Apparently Nonadjacent");
- table9.setToken(3, 0, "Definitely Nonadjacent");
- table9.setToken(4, 0, "Total");
-
- table9.setToken(0, 1, "Adjacent");
- table9.setToken(0, 2, "Nonadjacent");
- table9.setToken(0, 3, "Total");
-
- for (int i = 0; i < 4; i++) {
- for (int j = 0; j < 3; j++) {
- table9.setToken(i + 1, j + 1, this.nf.format(tableAdj[i][j]));
-
- }
- }
- builder.append("\n").append(table9);
- return builder.toString();
- }
-
-
- //============================PRIVATE METHODS=========================//
-
/**
* Adds semantic checks to the default deserialization method. This method
* must have the standard signature for a readObject method, and the body of
@@ -826,12 +142,26 @@ public Parameters getParams() {
return this.params;
}
- public List getReferenceGraphs() {
- return this.referenceGraphs;
+ public static Graph getComparisonGraph(Graph graph, Parameters params) {
+ String type = params.getString("graphComparisonType");
+
+ if ("DAG".equals(type)) {
+ params.set("graphComparisonType", "DAG");
+ return new EdgeListGraph(graph);
+ } else if ("CPDAG".equals(type)) {
+ params.set("graphComparisonType", "CPDAG");
+ return SearchGraphUtils.cpdagForDag(graph);
+ } else if ("PAG".equals(type)) {
+ params.set("graphComparisonType", "PAG");
+ return dagToPag(graph);
+ } else {
+ params.set("graphComparisonType", "DAG");
+ return new EdgeListGraph(graph);
+ }
}
- public List getTargetGraphs() {
- return this.targetGraphs;
+ public Graph getReferenceGraph() {
+ return this.referenceGraph;
}
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PValueImproverWrapper.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PValueImproverWrapper.java
index 8c4f1e1821..a76de7aeed 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PValueImproverWrapper.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PValueImproverWrapper.java
@@ -202,7 +202,7 @@ public boolean isShuffleMoves() {
public void execute() {
DataModel dataModel = getDataModel();
- IKnowledge knowledge = (IKnowledge) this.params2.get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) this.params2.get("knowledge", new Knowledge());
if (this.externalGraph == null) {
this.externalGraph = new EdgeListGraph(dataModel.getVariables());
@@ -268,7 +268,7 @@ public boolean supportsKnowledge() {
public ImpliedOrientation getMeekRules() {
MeekRules rules = new MeekRules();
- rules.setKnowledge((IKnowledge) this.params.get("knowledge", new Knowledge2()));
+ rules.setKnowledge((Knowledge) this.params.get("knowledge", new Knowledge()));
return rules;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PagFromDagGraphWrapper.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PagFromDagGraphWrapper.java
index c6416d0324..8b6687b584 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PagFromDagGraphWrapper.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PagFromDagGraphWrapper.java
@@ -42,17 +42,17 @@ public PagFromDagGraphWrapper(GraphSource source, Parameters parameters) {
public PagFromDagGraphWrapper(Graph graph) {
- super(new EdgeListGraph());
+ super(graph);
- // make sure the given graph is a dag.
- try {
- new Dag(graph);
- } catch (Exception e) {
+ if (graph.existsDirectedCycle()) {
throw new IllegalArgumentException("The source graph is not a DAG.");
}
DagToPag p = new DagToPag(graph);
+ p.setCompleteRuleSetUsed(true);
+ p.setMaxPathLength(-1);
Graph pag = p.convert();
+ pag.setGraphType(EdgeListGraph.GraphType.PAG);
setGraph(pag);
TetradLogger.getInstance().log("info", "\nGenerating allow_latent_common_causes from DAG.");
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PcRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PcRunner.java
index 2e4cc8aaa9..c977c72325 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PcRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/PcRunner.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.*;
import edu.cmu.tetrad.util.Parameters;
@@ -117,7 +116,7 @@ public static PcRunner serializableInstance() {
public ImpliedOrientation getMeekRules() {
MeekRules rules = new MeekRules();
rules.setAggressivelyPreventCycles(this.isAggressivelyPreventCycles());
- rules.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ rules.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
return rules;
}
@@ -129,7 +128,7 @@ public String getAlgorithmName() {
//===================PUBLIC METHODS OVERRIDING ABSTRACT================//
public void execute() {
- IKnowledge knowledge = (IKnowledge) getParams().get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) getParams().get("knowledge", new Knowledge());
int depth = getParams().getInt("depth", -1);
Graph graph;
Pc pc = new Pc(getIndependenceTest());
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/RemoveNonSkeletonEdgesModel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/RemoveNonSkeletonEdgesModel.java
new file mode 100644
index 0000000000..519b1136d1
--- /dev/null
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/RemoveNonSkeletonEdgesModel.java
@@ -0,0 +1,179 @@
+///////////////////////////////////////////////////////////////////////////////
+// For information as to what this class does, see the Javadoc, below. //
+// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, //
+// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard //
+// Scheines, Joseph Ramsey, and Clark Glymour. //
+// //
+// This program is free software; you can redistribute it and/or modify //
+// it under the terms of the GNU General Public License as published by //
+// the Free Software Foundation; either version 2 of the License, or //
+// (at your option) any later version. //
+// //
+// This program is distributed in the hope that it will be useful, //
+// but WITHOUT ANY WARRANTY; without even the implied warranty of //
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the //
+// GNU General Public License for more details. //
+// //
+// You should have received a copy of the GNU General Public License //
+// along with this program; if not, write to the Free Software //
+// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA //
+///////////////////////////////////////////////////////////////////////////////
+package edu.cmu.tetradapp.model;
+
+import edu.cmu.tetrad.data.Knowledge;
+import edu.cmu.tetrad.data.KnowledgeBoxInput;
+import edu.cmu.tetrad.graph.EdgeListGraph;
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.graph.Node;
+import edu.cmu.tetrad.util.Parameters;
+import edu.cmu.tetrad.util.TetradLogger;
+import edu.cmu.tetrad.util.TetradSerializableUtils;
+
+import java.util.SortedSet;
+import java.util.TreeSet;
+
+import static edu.cmu.tetrad.graph.GraphUtils.removeNonSkeletonEdges;
+
+/**
+ * @author kaalpurush
+ */
+public class RemoveNonSkeletonEdgesModel extends KnowledgeBoxModel {
+
+ static final long serialVersionUID = 23L;
+
+ private Graph resultGraph = new EdgeListGraph();
+
+ public RemoveNonSkeletonEdgesModel(BayesPmWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(GraphWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(StandardizedSemImWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(SemImWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(SemPmWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(DataWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(TimeLagGraphWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(GeneralizedSemImWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(BayesImWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(SemGraphWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(GeneralizedSemPmWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(DagWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(DirichletBayesImWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(BuildPureClustersRunner wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(PurifyRunner wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(MeasurementModelWrapper wrapper, Parameters params) {
+ this((KnowledgeBoxInput) wrapper, params);
+ }
+
+ public RemoveNonSkeletonEdgesModel(KnowledgeBoxInput input, Parameters params) {
+ this(params, input);
+ }
+
+ /**
+ * Constructor from dataWrapper edge
+ */
+ public RemoveNonSkeletonEdgesModel(Parameters params, KnowledgeBoxInput input) {
+ super(new KnowledgeBoxInput[]{input}, params);
+
+ if (input == null) {
+ throw new NullPointerException();
+ }
+
+ SortedSet variableNodes = new TreeSet<>(input.getVariables());
+ SortedSet variableNames = new TreeSet<>(input.getVariableNames());
+
+ this.resultGraph = input.getResultGraph();
+
+ /*
+ * @serial @deprecated
+ */
+ Knowledge knowledge = new Knowledge();
+
+ for (Node v : input.getVariables()) {
+ knowledge.addVariable(v.getName());
+ }
+
+ createKnowledge(params);
+
+ TetradLogger.getInstance().log("info", "Knowledge");
+
+ // This is a conundrum. At this point I dont know whether I am in a
+ // simulation or not. If in a simulation, I should print the knowledge.
+ // If not, I should wait for resetParams to be called. For now I'm
+ // printing the knowledge if it's not empty.
+ if (!((Knowledge) params.get("knowledge", new Knowledge())).isEmpty()) {
+ TetradLogger.getInstance().log("knowledge", params.get("knowledge", new Knowledge()).toString());
+ }
+ }
+
+ private void createKnowledge(Parameters params) {
+ Knowledge knowledge = getKnowledge();
+ if (knowledge == null) {
+ return;
+ }
+
+ knowledge.clear();
+
+ if (this.resultGraph == null) {
+ throw new NullPointerException("I couldn't find a parent graph.");
+ }
+
+ removeNonSkeletonEdges(resultGraph, knowledge);
+ }
+
+ /**
+ * Generates a simple exemplar of this class to test serialization.
+ *
+ * @see TetradSerializableUtils
+ */
+ public static RemoveNonSkeletonEdgesModel serializableInstance() {
+ return new RemoveNonSkeletonEdgesModel(new Parameters(), GraphWrapper.serializableInstance());
+ }
+
+ public Graph getResultGraph() {
+ return this.resultGraph;
+ }
+
+}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/RequiredGraphModel.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/RequiredGraphModel.java
index 2084edce2d..bddf3ef278 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/RequiredGraphModel.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/RequiredGraphModel.java
@@ -20,8 +20,7 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.data.KnowledgeBoxInput;
import edu.cmu.tetrad.graph.Edge;
import edu.cmu.tetrad.graph.Edges;
@@ -130,13 +129,13 @@ public RequiredGraphModel(Parameters params, KnowledgeBoxInput input) {
// simulation or not. If in a simulation, I should print the knowledge.
// If not, I should wait for resetParams to be called. For now I'm
// printing the knowledge if it's not empty.
- if (!((IKnowledge) params.get("knowledge", new Knowledge2())).isEmpty()) {
- TetradLogger.getInstance().log("knowledge", params.get("knowledge", new Knowledge2()).toString());
+ if (!((Knowledge) params.get("knowledge", new Knowledge())).isEmpty()) {
+ TetradLogger.getInstance().log("knowledge", params.get("knowledge", new Knowledge()).toString());
}
}
private void createKnowledge() {
- IKnowledge knwl = getKnowledge();
+ Knowledge knwl = getKnowledge();
if (knwl == null) {
return;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SampleVcpcFastRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SampleVcpcFastRunner.java
index 20786949f6..a6933238a1 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SampleVcpcFastRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SampleVcpcFastRunner.java
@@ -21,13 +21,11 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.*;
import edu.cmu.tetrad.sem.SemIm;
import edu.cmu.tetrad.util.Parameters;
-import edu.cmu.tetrad.util.TetradSerializableUtils;
import java.util.ArrayList;
import java.util.HashSet;
@@ -145,7 +143,7 @@ public static SampleVcpcFastRunner serializableInstance() {
//===================PUBLIC METHODS OVERRIDING ABSTRACT================//
public void execute() {
- IKnowledge knowledge = (IKnowledge) getParams().get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) getParams().get("knowledge", new Knowledge());
Parameters params = getParams();
SampleVcpcFast sfvcpc = new SampleVcpcFast(getIndependenceTest());
@@ -223,7 +221,7 @@ public boolean supportsKnowledge() {
public ImpliedOrientation getMeekRules() {
MeekRules meekRules = new MeekRules();
meekRules.setAggressivelyPreventCycles(this.isAggressivelyPreventCycles());
- meekRules.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ meekRules.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
return meekRules;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SampleVcpcRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SampleVcpcRunner.java
index cdee56794c..a11dca24ff 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SampleVcpcRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SampleVcpcRunner.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.*;
import edu.cmu.tetrad.sem.SemIm;
@@ -169,7 +168,7 @@ public static SampleVcpcRunner serializableInstance() {
//===================PUBLIC METHODS OVERRIDING ABSTRACT================//
public void execute() {
- IKnowledge knowledge = (IKnowledge) getParams().get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) getParams().get("knowledge", new Knowledge());
SampleVcpc svcpc = new SampleVcpc(getIndependenceTest());
@@ -256,7 +255,7 @@ public boolean supportsKnowledge() {
public ImpliedOrientation getMeekRules() {
MeekRules meekRules = new MeekRules();
meekRules.setAggressivelyPreventCycles(this.isAggressivelyPreventCycles());
- meekRules.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ meekRules.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
return meekRules;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SessionWrapper.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SessionWrapper.java
index 4086607d16..60b2793e5b 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SessionWrapper.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/SessionWrapper.java
@@ -84,6 +84,7 @@ public class SessionWrapper extends EdgeListGraph implements SessionWrapperIndir
private final boolean highlighted = false;
private boolean pag;
private boolean CPDAG;
+ private GraphType graphType;
//==========================CONSTRUCTORS=======================//
@@ -743,24 +744,12 @@ public List> getTriplesLists(Node node) {
return null;
}
- @Override
- public boolean isPag() {
- return this.pag;
- }
-
- @Override
- public void setPag(boolean pag) {
- this.pag = pag;
+ public void setGraphType(GraphType graphType) {
+ this.graphType = graphType;
}
- @Override
- public boolean isCPDAG() {
- return this.CPDAG;
- }
-
- @Override
- public void setCPDAG(boolean CPDAG) {
- this.CPDAG = CPDAG;
+ public GraphType getGraphType() {
+ return this.graphType;
}
/**
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/Simulation.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/Simulation.java
index 4942b3e346..90bc8a49a2 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/Simulation.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/Simulation.java
@@ -26,16 +26,12 @@
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.data.DataModel;
import edu.cmu.tetrad.data.DataModelList;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.TetradSerializableUtils;
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
+import java.util.*;
/**
* Wraps a Simulation object for the Tetrad interface. A Simulation object
@@ -309,11 +305,11 @@ public void setFixedGraph(boolean fixedGraph) {
this.fixedGraph = fixedGraph;
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
if (this.simulation instanceof HasKnowledge) {
return ((HasKnowledge) this.simulation).getKnowledge();
} else {
- return new Knowledge2();
+ return new Knowledge();
}
}
@@ -327,10 +323,11 @@ public List getInputDataModelList() {
@Override
public Graph getGraph() {
- if (getGraphs().size() == 1) {
- return getGraphs().get(0);
+ Set graphs = new HashSet<>(getGraphs());
+ if (graphs.size() == 1) {
+ return graphs.iterator().next();
+ } else {
+ throw new IllegalArgumentException("Expecting one graph.");
}
-
- throw new IllegalArgumentException("Expecting one graph.");
}
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/TabularComparison.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/TabularComparison.java
index c4b2666c8d..6d47d3db2a 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/TabularComparison.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/TabularComparison.java
@@ -22,6 +22,7 @@
import edu.cmu.tetrad.algcomparison.statistic.*;
import edu.cmu.tetrad.data.*;
+import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetrad.session.DoNotAddOldModel;
@@ -99,14 +100,9 @@ public TabularComparison(GraphSource model1, GraphSource model2,
this.targetGraph = model2.getGraph();
}
- if (this.targetGraph.isPag() || this.referenceGraph.isPag()) {
- this.targetGraph.setPag(true);
- this.referenceGraph.setPag(true);
- }
-
newExecution();
- addRecord();
+// addRecord();
TetradLogger.getInstance().log("info", "Graph Comparison");
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/TimeLagGraphWrapper.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/TimeLagGraphWrapper.java
index 7f619b671e..a1c5e9ac76 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/TimeLagGraphWrapper.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/TimeLagGraphWrapper.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.data.KnowledgeBoxInput;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.util.Parameters;
@@ -108,7 +107,7 @@ public TimeLagGraphWrapper(GraphWrapper graphWrapper) {
int numLags = 1; // need to fix this!
List variables = graph.getNodes();
List laglist = new ArrayList<>();
- IKnowledge knowledge1 = new Knowledge2();
+ Knowledge knowledge1 = new Knowledge();
int lag;
for (Node node : variables) {
String varName = node.getName();
@@ -212,11 +211,11 @@ public void setGraph(TimeLagGraph graph) {
this.graph = graph;
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
int numLags = 1; // need to fix this!
List variables = this.graph.getNodes();
List laglist = new ArrayList<>();
- IKnowledge knowledge1 = new Knowledge2();
+ Knowledge knowledge1 = new Knowledge();
int lag;
for (Node node : variables) {
String varName = node.getName();
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/VcpcFastRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/VcpcFastRunner.java
index 738df803ab..927a58ab91 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/VcpcFastRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/VcpcFastRunner.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.*;
import edu.cmu.tetrad.util.Parameters;
@@ -169,7 +168,7 @@ public static VcpcFastRunner serializableInstance() {
//===================PUBLIC METHODS OVERRIDING ABSTRACT================//
public void execute() {
- IKnowledge knowledge = (IKnowledge) getParams().get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) getParams().get("knowledge", new Knowledge());
VcpcFast fvcpc = new VcpcFast(getIndependenceTest());
@@ -254,7 +253,7 @@ public boolean supportsKnowledge() {
public ImpliedOrientation getMeekRules() {
MeekRules meekRules = new MeekRules();
meekRules.setAggressivelyPreventCycles(this.isAggressivelyPreventCycles());
- meekRules.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ meekRules.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
return meekRules;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/VcpcRunner.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/VcpcRunner.java
index d10df8076b..e5b96d0d8d 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/VcpcRunner.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/VcpcRunner.java
@@ -21,8 +21,7 @@
package edu.cmu.tetradapp.model;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.*;
import edu.cmu.tetrad.util.Parameters;
@@ -169,7 +168,7 @@ public static VcpcRunner serializableInstance() {
//===================PUBLIC METHODS OVERRIDING ABSTRACT================//
public void execute() {
- IKnowledge knowledge = (IKnowledge) getParams().get("knowledge", new Knowledge2());
+ Knowledge knowledge = (Knowledge) getParams().get("knowledge", new Knowledge());
Vcpc vcpc = new Vcpc(getIndependenceTest());
@@ -254,7 +253,7 @@ public boolean supportsKnowledge() {
public ImpliedOrientation getMeekRules() {
MeekRules meekRules = new MeekRules();
meekRules.setAggressivelyPreventCycles(this.isAggressivelyPreventCycles());
- meekRules.setKnowledge((IKnowledge) getParams().get("knowledge", new Knowledge2()));
+ meekRules.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
return meekRules;
}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/YeastPcCcdSearchWrapper.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/YeastPcCcdSearchWrapper.java
index 035e3d628f..3280e131e0 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/YeastPcCcdSearchWrapper.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/YeastPcCcdSearchWrapper.java
@@ -25,8 +25,7 @@
import edu.cmu.tetrad.data.DataSet;
import edu.cmu.tetrad.data.DataUtils;
-import edu.cmu.tetrad.data.IKnowledge;
-import edu.cmu.tetrad.data.Knowledge2;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetrad.search.Ccd;
@@ -115,7 +114,7 @@ public static void main(String[] args) {
// read in variable name and set up DataSet.
int ngenes = Integer.parseInt(args[2]);
- IKnowledge bk = new Knowledge2();
+ Knowledge bk = new Knowledge();
bk.addToTiersByVarNames(listOfNames);
//if(verbose) {
@@ -288,7 +287,7 @@ private static int[] CcdAccuracy(double alpha, int ngenes,
}
private static int[] PCAccuracy(double alpha, int ngenes,
- DataSet cds, IKnowledge bk, int[][] yeastReg, List names,
+ DataSet cds, Knowledge bk, int[][] yeastReg, List names,
DataOutputStream d) {
int[] falsePosNeg = new int[2];
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/datamanip/TimeSeriesWrapper.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/datamanip/TimeSeriesWrapper.java
index f2f3c2f5ca..d355fc56ed 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/datamanip/TimeSeriesWrapper.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/model/datamanip/TimeSeriesWrapper.java
@@ -35,7 +35,7 @@ public class TimeSeriesWrapper extends DataWrapper implements KnowledgeTransfera
static final long serialVersionUID = 23L;
@SuppressWarnings("FieldCanBeLocal")
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
/**
* Constructs a new time series dataset.
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/LayoutEditable.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/LayoutEditable.java
index e701e4d31e..85a3d4f899 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/LayoutEditable.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/LayoutEditable.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.util;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.Edge;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
@@ -52,7 +52,7 @@ public interface LayoutEditable {
/**
* @return the getModel knowledge.
*/
- IKnowledge getKnowledge();
+ Knowledge getKnowledge();
/**
* @return the source graph.
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/LongTextField.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/LongTextField.java
new file mode 100644
index 0000000000..eff045fd51
--- /dev/null
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/LongTextField.java
@@ -0,0 +1,208 @@
+///////////////////////////////////////////////////////////////////////////////
+// For information as to what this class does, see the Javadoc, below. //
+// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, //
+// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard //
+// Scheines, Joseph Ramsey, and Clark Glymour. //
+// //
+// This program is free software; you can redistribute it and/or modify //
+// it under the terms of the GNU General Public License as published by //
+// the Free Software Foundation; either version 2 of the License, or //
+// (at your option) any later version. //
+// //
+// This program is distributed in the hope that it will be useful, //
+// but WITHOUT ANY WARRANTY; without even the implied warranty of //
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the //
+// GNU General Public License for more details. //
+// //
+// You should have received a copy of the GNU General Public License //
+// along with this program; if not, write to the Free Software //
+// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA //
+///////////////////////////////////////////////////////////////////////////////
+package edu.cmu.tetradapp.util;
+
+import javax.swing.*;
+import java.awt.*;
+import java.awt.event.ActionEvent;
+import java.awt.event.ActionListener;
+import java.awt.event.FocusAdapter;
+import java.awt.event.FocusEvent;
+
+/**
+ * A text field which is specialized for displaying longs. Handles otherwise
+ * annoying GUI-related functions like keeping the textbox the right size and
+ * listening to itself. A filter may be specified as a way of, e.g., forcing
+ * variables to be within a certain range; see the setFilter
+ * method.
+ *
+ * @author Kevin Bui
+ */
+public final class LongTextField extends JTextField {
+
+ /**
+ * The getModel value of the text field.
+ */
+ private long value;
+
+ /**
+ * If set, checks whether the given value should be accepted; otherwise, the
+ * old value will be reinstated. May be null.
+ */
+ private Filter filter;
+
+ //==========================CONSTRUCTORS=============================//
+ /**
+ * Constructs a new long text field displaying the given default value,
+ * restricting the value to [lowerBound, upperBound].
+ *
+ * @param value The initial value. Must be between lowerBound and
+ * upperBound.
+ * @param size the number of columns in the textfield.
+ */
+ public LongTextField(long value, int size) {
+ super(size);
+
+ setValue(value);
+ setText(Long.toString(value));
+
+ setHorizontalAlignment(SwingConstants.RIGHT);
+ addActionListener(new ActionListener() {
+
+ /**
+ * Reacts to somebody pressing the return key in this field by
+ * attempting to set the value displayed. If the value displayed
+ * cannot be set, the set value is reinstated.
+ */
+ public void actionPerformed(ActionEvent e) {
+ try {
+ long n = Long.parseLong(e.getActionCommand());
+ setValue(n);
+ } catch (NumberFormatException e1) {
+ setText(Long.toString(getValue()));
+ }
+ }
+ });
+
+ addFocusListener(new FocusAdapter() {
+ /**
+ * Nothing need be done when focus is gained, but this method is
+ * required by the FocusListener interface.
+ *
+ * @param e the event.
+ */
+ public void focusGained(FocusEvent e) {
+ LongTextField source = (LongTextField) e.getSource();
+ source.selectAll();
+ }
+
+ /**
+ * If focus is lost, attempt to store the text value being displayed
+ * as long; if this cannot be done, restore the previous value.
+ */
+ public void focusLost(FocusEvent e) {
+ try {
+ long n = Long.parseLong(getText());
+ setValue(n);
+ } catch (NumberFormatException e1) {
+ setText(Long.toString(getValue()));
+ }
+ }
+ });
+ }
+
+ //=============================PUBLIC METHODS=======================//
+ public void setUnfilteredValue(long value) {
+ setText(String.valueOf(value));
+ }
+
+ /**
+ * Sets the value of the text field to the given long value.
+ */
+ public void setValue(long value) {
+ if (value == this.value) {
+ return;
+ }
+
+ long newValue = filter(value, this.value);
+
+ if (newValue == this.value) {
+ setText(Long.toString(this.value));
+ } else {
+ this.value = newValue;
+ setText(Long.toString(this.value));
+ firePropertyChange("newValue", null, this.value);
+ }
+ }
+
+ /**
+ * @return the long value currently displayed.
+ */
+ public long getValue() {
+ return this.value;
+ }
+
+ /**
+ * Sets whether the given value should be accepted.
+ */
+ public void setFilter(Filter filter) {
+ this.filter = filter;
+ }
+
+ /**
+ * Convinces the text field to stay the right size in layouts that are
+ * trying to expand it like a balloon by returning the preferred size.
+ *
+ * @return the maximum size.
+ */
+ public Dimension getMaximumSize() {
+ return getPreferredSize();
+ }
+
+ /**
+ * Convinces the text field to stay the right size in layouts that are
+ * trying to shrink it.
+ *
+ * @return the maximum size.
+ */
+ public Dimension getMinimumSize() {
+ return getPreferredSize();
+ }
+
+ //==============================PRIVATE METHODS======================//
+ /**
+ * Determines whether the given value is a legal value for this text field.
+ * The default behavior is to constrain the value to be within a certain
+ * range--in other words, in the range [lower bound, upper bound]. For any
+ * other behavior, this method should be overridden. This method is called
+ * by default by the setLabel() method; it may become irrelevant if
+ * setLabel() is overridden in a way that doesn't make a call to
+ * checkValue().
+ */
+ private long filter(long value, long oldValue) {
+ if (this.filter == null) {
+ return value;
+ }
+
+ return this.filter.filter(value, oldValue);
+ }
+
+ //==============================Interfaces============================//
+ /**
+ * Filters the given value, returning the value that should actually be
+ * displayed. Typical use is to return either the value or the old value,
+ * depending on whether the value is in range, though more complicated uses
+ * are permitted. Side effects (such as storing the value in the process of
+ * filtering it) are permitted.
+ */
+ public interface Filter {
+
+ /**
+ * Filters the given value, returning the new value that should be
+ * displayed.
+ *
+ * @param value The value entered by the user.
+ * @param oldValue The value previously displayed, in case it needs to
+ * be reverted to.
+ */
+ long filter(long value, long oldValue);
+ }
+}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/ParameterComponents.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/ParameterComponents.java
index 3e1e0992ca..cdeb362e3d 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/ParameterComponents.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/ParameterComponents.java
@@ -129,6 +129,35 @@ public static IntTextField getIntTextField(String parameter, Parameters paramete
return field;
}
+ public static LongTextField getLongTextField(String parameter, Parameters parameters,
+ long defaultValue, double lowerBound, double upperBound) {
+ LongTextField field = new LongTextField(parameters.getLong(parameter, defaultValue), 10);
+
+ field.setFilter((value, oldValue) -> {
+ if (value == field.getValue()) {
+ return oldValue;
+ }
+
+ if (value < lowerBound) {
+ return oldValue;
+ }
+
+ if (value > upperBound) {
+ return oldValue;
+ }
+
+ try {
+ parameters.set(parameter, value);
+ } catch (Exception e) {
+ // Ignore.
+ }
+
+ return value;
+ });
+
+ return field;
+ }
+
public static Box getBooleanSelectionBox(String parameter, Parameters parameters, boolean defaultValue) {
Box selectionBox = Box.createHorizontalBox();
@@ -203,6 +232,10 @@ private static Box createParameterComponent(String parameter, Parameters paramet
int lowerBoundInt = paramDesc.getLowerBoundInt();
int upperBoundInt = paramDesc.getUpperBoundInt();
component = ParameterComponents.getIntTextField(parameter, parameters, (Integer) defaultValue, lowerBoundInt, upperBoundInt);
+ } else if (defaultValue instanceof Long) {
+ int lowerBoundInt = paramDesc.getLowerBoundInt();
+ int upperBoundInt = paramDesc.getUpperBoundInt();
+ component = ParameterComponents.getLongTextField(parameter, parameters, (Long) defaultValue, lowerBoundInt, upperBoundInt);
} else if (defaultValue instanceof Boolean) {
component = ParameterComponents.getBooleanSelectionBox(parameter, parameters, (Boolean) defaultValue);
} else if (defaultValue instanceof String) {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/AbstractWorkbench.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/AbstractWorkbench.java
index eae2901f82..f9c0ca83d3 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/AbstractWorkbench.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/AbstractWorkbench.java
@@ -20,11 +20,10 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.workbench;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.util.JOptionUtils;
import edu.cmu.tetradapp.model.SessionWrapper;
-import edu.cmu.tetradapp.util.CopyLayoutAction;
import edu.cmu.tetradapp.util.LayoutEditable;
import edu.cmu.tetradapp.util.PasteLayoutAction;
@@ -523,7 +522,6 @@ public final void setEdgeLabel(Edge modelEdge, JComponent label) {
/**
* Node tooltip to show the node attributes - Added by Kong
- *
*/
public final void setNodeToolTip(Node modelNode, String toolTipText) {
if (modelNode == null) {
@@ -539,7 +537,6 @@ public final void setNodeToolTip(Node modelNode, String toolTipText) {
/**
* Edge tooltip to show the edge type and probabilities - Added by Zhou
- *
*/
public final void setEdgeToolTip(Edge modelEdge, String toolTipText) {
if (modelEdge == null) {
@@ -841,7 +838,7 @@ public void layoutByGraph(Graph layoutGraph) {
// setGraphWithoutNotify(graph);
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return null;
}
@@ -930,7 +927,7 @@ private void setGraphWithoutNotify(Graph graph) {
} else {
this.graph = graph;
- if (graph.isPag()) {
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
GraphUtils.addPagColoring(new EdgeListGraph(graph));
}
}
@@ -1178,7 +1175,9 @@ private void addEdge(Edge modelEdge) {
}
if (!getGraph().containsEdge(modelEdge)) {
- throw new IllegalArgumentException("Attempt to add edge not in model.");
+ System.out.println("Attempt to add edge not in model: " + modelEdge);
+ return;
+// throw new IllegalArgumentException("Attempt to add edge not in model.");
}
// construct a display edge for the model edge
@@ -1201,13 +1200,23 @@ private void addEdge(Edge modelEdge) {
displayEdge.setHighlighted(true);
}
- boolean bold = modelEdge.getProperties().contains(Edge.Property.dd) || modelEdge.isBold();
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
- Color lineColor = modelEdge.getProperties().contains(Edge.Property.nl) ? Color.green
- : this.graph.isHighlighted(modelEdge) ? displayEdge.getHighlightedColor() : modelEdge.getLineColor();
+ // visible edges.
+ boolean solid = modelEdge.getProperties().contains(Edge.Property.nl);
- displayEdge.setLineColor(lineColor);
- displayEdge.setBold(bold);
+ // definitely direct edges.
+ boolean thick = modelEdge.getProperties().contains(Edge.Property.dd);
+
+ // definitely direct edges.
+// Color green = Color.green.darker();
+// Color lineColor = modelEdge.getProperties().contains(Edge.Property.nl) ? green
+// : this.graph.isHighlighted(modelEdge) ? displayEdge.getHighlightedColor() : modelEdge.getLineColor();
+
+// displayEdge.setLineColor(lineColor);
+ displayEdge.setSolid(solid);
+ displayEdge.setThick(thick);
+ }
// Link the display edge to the model edge.
getModelEdgesToDisplay().put(modelEdge, displayEdge);
@@ -1783,6 +1792,10 @@ private void edgeClicked(Object source, MouseEvent e) {
graphEdge.setSelected(true);
}
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void nodeClicked(Object source, MouseEvent e) {
@@ -1805,6 +1818,10 @@ private void nodeClicked(Object source, MouseEvent e) {
selectConnectingEdges();
fireNodeSelection();
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void reorientEdge(Object source, MouseEvent e) {
@@ -1819,7 +1836,7 @@ private void reorientEdge(Object source, MouseEvent e) {
if (e.isShiftDown()) {
if (AbstractWorkbench.distance(point, pointA) < endpointRadius) {
toggleEndpoint(graphEdge, 1);
- firePropertyChange("modelChanged", null, null);
+ fireModelChanged();
} else if (AbstractWorkbench.distance(point, pointB) < endpointRadius) {
toggleEndpoint(graphEdge, 2);
firePropertyChange("modelChanged", null, null);
@@ -1833,6 +1850,14 @@ private void reorientEdge(Object source, MouseEvent e) {
firePropertyChange("modelChanged", null, null);
}
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
+ }
+
+ private void fireModelChanged() {
+ firePropertyChange("modelChanged", null, null);
}
private void handleMousePressed(MouseEvent e) {
@@ -1885,6 +1910,10 @@ private void handleMousePressed(MouseEvent e) {
break;
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void launchPopup(MouseEvent e) {
@@ -1926,6 +1955,10 @@ private void handleMouseReleased(MouseEvent e) {
finishEdge();
break;
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void handleMouseDragged(MouseEvent e) {
@@ -1951,6 +1984,10 @@ private void handleMouseDragged(MouseEvent e) {
dragNewEdge(source, newPoint);
break;
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void handleMouseEntered(MouseEvent e) {
@@ -1969,13 +2006,13 @@ private void handleMouseEntered(MouseEvent e) {
endpoint1 = "-";
break;
case "Arrow":
- endpoint1 = "<";
+ endpoint1 = "<";
break;
case "Circle":
endpoint1 = "o";
break;
case "Star":
- endpoint1 = "*";
+ endpoint1 = "*";
break;
case "Null":
endpoint1 = "Null";
@@ -1988,13 +2025,13 @@ private void handleMouseEntered(MouseEvent e) {
endpoint2 = "-";
break;
case "Arrow":
- endpoint2 = ">";
+ endpoint2 = ">";
break;
case "Circle":
endpoint2 = "o";
break;
case "Star":
- endpoint2 = "*";
+ endpoint2 = "*";
break;
case "Null":
endpoint2 = "Null";
@@ -2026,19 +2063,19 @@ private void handleMouseEntered(MouseEvent e) {
_type = "no edge";
break;
case ta:
- _type = "-->";
+ _type = "--?";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case at:
- _type = "<--";
+ _type = "<--";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case ca:
- _type = "o->";
+ _type = "o->";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case ac:
- _type = "<-o";
+ _type = "<-o";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case cc:
@@ -2046,7 +2083,7 @@ private void handleMouseEntered(MouseEvent e) {
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case aa:
- _type = "<->";
+ _type = "<->";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case tt:
@@ -2236,17 +2273,28 @@ private void directEdge(IDisplayEdge graphEdge, int endpoint) {
try {
boolean added = getGraph().addEdge(newEdge);
+
if (!added) {
getGraph().addEdge(edge);
JOptionPane.showMessageDialog(JOptionUtils.centeringComp(),
"Reorienting that edge would violate graph constraints.");
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
} catch (IllegalArgumentException e) {
getGraph().addEdge(edge);
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
+
JOptionPane.showMessageDialog(JOptionUtils.centeringComp(),
"Reorienting that edge would violate graph constraints.");
}
+ revalidate();
repaint();
}
@@ -2290,6 +2338,11 @@ private void toggleEndpoint(IDisplayEdge graphEdge, int endpointNumber) {
boolean added = getGraph().addEdge(newEdge);
if (!added) {
getGraph().addEdge(edge);
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
+
return;
}
} catch (IllegalArgumentException e) {
@@ -2297,6 +2350,11 @@ private void toggleEndpoint(IDisplayEdge graphEdge, int endpointNumber) {
return;
}
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
+
+ revalidate();
repaint();
}
@@ -2350,6 +2408,15 @@ public void enableEditing(boolean enableEditing) {
setEnabled(enableEditing);
}
+ public void setPag(boolean pagColoring) {
+ if (pagColoring) {
+ this.graph.setGraphType(EdgeListGraph.GraphType.PAG);
+ } else {
+ this.graph.setGraphType(EdgeListGraph.GraphType.UNLABELED);
+ }
+ setGraph(graph);
+ }
+
/**
* This inner class is a simple wrapper for JComponents which are to serve
* as edge labels in the workbench. Its sole function is to make sure the
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/DisplayEdge.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/DisplayEdge.java
index 61b3b90b07..befe2b3a47 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/DisplayEdge.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/DisplayEdge.java
@@ -181,7 +181,7 @@ public class DisplayEdge extends JComponent implements IDisplayEdge {
/**
* The width of the stroke.
*/
- private float strokeWidth = 1f;
+ private float strokeWidth = 1.2f;
/**
* True iff this edge is highlighted.
@@ -198,7 +198,8 @@ public class DisplayEdge extends JComponent implements IDisplayEdge {
*/
private final PropertyChangeHandler propertyChangeHandler =
new PropertyChangeHandler();
- private boolean bold;
+ private boolean solid = true;
+ private boolean thick = false;
//==========================CONSTRUCTORS============================//
@@ -425,12 +426,16 @@ private void drawEdge(Graphics g) {
// width <= 1.0 seems to cause the problem, so we pick a stroke
// width slightly greater than 1.0. jdramsey 4/16/2005
// g2d.setStroke(new BasicStroke(1.000001f));
- BasicStroke s;
+ Stroke s;
+ float width = thick ? 2.5f : 1.1f;
- if (this.bold) {
- s = new BasicStroke(3.0f);
+ Stroke solid = new BasicStroke(width);
+ Stroke dashed = new BasicStroke(width, BasicStroke.CAP_BUTT, BasicStroke.JOIN_BEVEL, 0, new float[]{9}, 0);
+
+ if (this.solid) {
+ s = solid;
} else {
- s = new BasicStroke(getStrokeWidth() + 0.000001f);
+ s = dashed;
}
g2d.setStroke(s);
@@ -1029,12 +1034,17 @@ public void setLineColor(Color lineColor) {
}
}
- public boolean getBold() {
- return this.bold;
+ public boolean getSolid() {
+ return this.solid;
+ }
+
+ public void setSolid(boolean solid) {
+ this.solid = solid;
}
- public void setBold(boolean bold) {
- this.bold = bold;
+ @Override
+ public void setThick(boolean thick) {
+ this.thick = thick;
}
public Color getSelectedColor() {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/GraphWorkbench.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/GraphWorkbench.java
index bf9cff7d04..e86540d10d 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/GraphWorkbench.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/GraphWorkbench.java
@@ -62,7 +62,7 @@ public GraphWorkbench() {
}
/**
- * Constructs a new workbench workbench for the given workbench model.
+ * Constructs a new workbench for the given graph model.
*/
public GraphWorkbench(Graph graph) {
super(graph);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/IDisplayEdge.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/IDisplayEdge.java
index 478140fff5..6bcbff85c2 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/IDisplayEdge.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/IDisplayEdge.java
@@ -65,9 +65,11 @@ public interface IDisplayEdge {
void setLineColor(Color lineColor);
- boolean getBold();
+ boolean getSolid();
- void setBold(boolean bold);
+ void setSolid(boolean solid);
+
+ void setThick(boolean thick);
Color getSelectedColor();
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/LayoutUtils.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/LayoutUtils.java
index a88e9f3161..7546d24b8f 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/LayoutUtils.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/LayoutUtils.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.workbench;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.SearchGraphUtils;
import edu.cmu.tetrad.util.JOptionUtils;
@@ -485,7 +485,7 @@ public static void knowledgeLayout(LayoutEditable layoutEditable) {
}
}
- IKnowledge knowledge = layoutEditable.getKnowledge();
+ Knowledge knowledge = layoutEditable.getKnowledge();
SearchGraphUtils.arrangeByKnowledgeTiers(graph, knowledge);
layoutEditable.layoutByGraph(graph);
} catch (Exception e1) {
diff --git a/tetrad-gui/src/main/resources/config/devConfig.xml b/tetrad-gui/src/main/resources/config/devConfig.xml
index e28f884017..19b66b4e89 100644
--- a/tetrad-gui/src/main/resources/config/devConfig.xml
+++ b/tetrad-gui/src/main/resources/config/devConfig.xml
@@ -943,17 +943,17 @@
edu.cmu.tetradapp.editor.BayesUpdaterEditor
-
-
-
- edu.cmu.tetradapp.model.CptInvariantUpdaterWrapper
-
- edu.cmu.tetradapp.editor.BayesUpdaterEditor
-
-
+
+
+
+
+
+
+
+
+
+
+
edu.cmu.tetradapp.model.SemUpdaterWrapper
@@ -1190,6 +1190,14 @@
edu.cmu.tetradapp.model.RequiredGraphModel
edu.cmu.tetradapp.knowledge_editor.KnowledgeBoxEditor
+
+
+
+ edu.cmu.tetradapp.model.RemoveNonSkeletonEdgesModel
+ edu.cmu.tetradapp.knowledge_editor.KnowledgeBoxEditor
+
diff --git a/tetrad-gui/src/main/resources/config/prodConfig.xml b/tetrad-gui/src/main/resources/config/prodConfig.xml
index 6b96cf0b1c..f97d4c42e0 100644
--- a/tetrad-gui/src/main/resources/config/prodConfig.xml
+++ b/tetrad-gui/src/main/resources/config/prodConfig.xml
@@ -903,17 +903,17 @@
edu.cmu.tetradapp.editor.BayesUpdaterEditor
-
-
-
- edu.cmu.tetradapp.model.CptInvariantUpdaterWrapper
-
- edu.cmu.tetradapp.editor.BayesUpdaterEditor
-
-
+
+
+
+
+
+
+
+
+
+
+
edu.cmu.tetradapp.model.SemUpdaterWrapper
@@ -1160,6 +1160,14 @@
edu.cmu.tetradapp.model.RequiredGraphModel
edu.cmu.tetradapp.knowledge_editor.KnowledgeBoxEditor
+
+
+
+ edu.cmu.tetradapp.model.RemoveNonSkeletonEdgesModel
+ edu.cmu.tetradapp.knowledge_editor.KnowledgeBoxEditor
+
diff --git a/tetrad-gui/src/main/resources/resources/javahelp/Map.jhm b/tetrad-gui/src/main/resources/resources/javahelp/Map.jhm
index b5a8177d05..136ac97764 100644
--- a/tetrad-gui/src/main/resources/resources/javahelp/Map.jhm
+++ b/tetrad-gui/src/main/resources/resources/javahelp/Map.jhm
@@ -97,7 +97,7 @@
- Search Algorithms: MBFS
Search Algorithms: PC-MB
-The MBFS search (Markov blanket fan Search) is designed to search for Markov blanket DAGs of
+The PC-MB search is designed to search for Markov blanket DAGs of
target variables in datasets, under the assumptions of the PC algorithm--i.e., that the true causal graph over the
variables in the dataset does not contain any cycles, that there are no hidden common causes between variables in
the dataset, and that no relationship between variables in the dataset is deterministic. The Markov blanket of a
diff --git a/tetrad-gui/src/main/resources/resources/javahelp/manual/boxes/search/types_of_algorithms.html b/tetrad-gui/src/main/resources/resources/javahelp/manual/boxes/search/types_of_algorithms.html
index 39c19bf020..326d3a2327 100644
--- a/tetrad-gui/src/main/resources/resources/javahelp/manual/boxes/search/types_of_algorithms.html
+++ b/tetrad-gui/src/main/resources/resources/javahelp/manual/boxes/search/types_of_algorithms.html
@@ -32,7 +32,7 @@ Types of Algorithms
or the algorithm uses only conditional independence information as data.
For CPDAG algorithms, it is assumed that there are no latent common causes
in the model--that is, there can be latents, but there cannot be structures of
- the following form: X<-L->Y, where X and Y are measured and L is not.
+ the following form: X<~~L~~>Y, where X and Y are measured and L is not.
- PAG (Partial Ancestral Graph) algorithm. This is the class of equivalence
classes of graphs one obtains if one assumes latent common causes (as above)
diff --git a/tetrad-gui/src/main/resources/resources/javahelp/manual/graph_edge_types.html b/tetrad-gui/src/main/resources/resources/javahelp/manual/graph_edge_types.html
index 321f753c76..f797bf4995 100644
--- a/tetrad-gui/src/main/resources/resources/javahelp/manual/graph_edge_types.html
+++ b/tetrad-gui/src/main/resources/resources/javahelp/manual/graph_edge_types.html
@@ -68,12 +68,12 @@
Graph Edge Types
- If an edge is green that means there is no latent
- confounder. Otherwise, there is possibly latent confounder.
+ If an edge is solid, that means there is no latent
+ confounder (i.e., is visible). If dashed, there is possibly latent confounder.
- If an edge is bold (thickened) that means it is
+ If an edge is thickened that means it is
definitely direct. Otherwise, it is possibly direct.
diff --git a/tetrad-lib/pom.xml b/tetrad-lib/pom.xml
index 2b1f634b8a..8677159f35 100644
--- a/tetrad-lib/pom.xml
+++ b/tetrad-lib/pom.xml
@@ -6,7 +6,7 @@
io.github.cmu-phil
tetrad
- 7.1.2-2
+ 7.1.3-1
tetrad-lib
@@ -115,7 +115,7 @@
org.json
json
- 20220320
+ 20220924
@@ -130,7 +130,7 @@
org.jsoup
jsoup
- 1.14.3
+ 1.15.3
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/Comparison.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/Comparison.java
index e068adc62a..173d899ade 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/Comparison.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/Comparison.java
@@ -41,7 +41,6 @@
import edu.cmu.tetrad.data.*;
import edu.cmu.tetrad.data.simulation.LoadDataAndGraphs;
import edu.cmu.tetrad.graph.*;
-import edu.cmu.tetrad.search.DagToPag;
import edu.cmu.tetrad.search.SearchGraphUtils;
import edu.cmu.tetrad.util.*;
import org.reflections.Reflections;
@@ -51,7 +50,11 @@
import java.text.DecimalFormat;
import java.text.NumberFormat;
import java.util.*;
-import java.util.concurrent.RecursiveTask;
+import java.util.concurrent.Callable;
+import java.util.concurrent.Executors;
+import java.util.concurrent.ForkJoinPool;
+
+import static edu.cmu.tetrad.search.SearchGraphUtils.dagToPag;
/**
* Script to do a comparison of a list of algorithms using a list of statistics
@@ -62,6 +65,12 @@
*/
public class Comparison {
+ private boolean parallelized = false;
+
+ public void setParallelized(boolean parallelized) {
+ this.parallelized = parallelized;
+ }
+
public enum ComparisonGraph {
true_DAG, CPDAG_of_the_true_DAG, PAG_of_the_true_DAG
}
@@ -296,16 +305,6 @@ public void compareFromSimulations(String resultsPath, Simulations simulations,
double[][][][] allStats = calcStats(algorithmSimulationWrappers, algorithmWrappers, simulationWrappers,
statistics, numRuns, stdout);
- // Print out the preliminary information for statistics types, etc.
- this.out.println();
- this.out.println("Statistics:");
- this.out.println();
-
- for (Statistic stat : statistics.getStatistics()) {
- this.out.println(stat.getAbbreviation() + " = " + stat.getDescription());
- }
-
- this.out.println();
{
int numTables = allStats.length;
@@ -333,6 +332,7 @@ public void compareFromSimulations(String resultsPath, Simulations simulations,
}
}
+ this.out.println();
this.out.println("Simulations:");
this.out.println();
@@ -362,6 +362,18 @@ public void compareFromSimulations(String resultsPath, Simulations simulations,
}
}
+
+ // Print out the preliminary information for statistics types, etc.
+ this.out.println();
+ this.out.println("Statistics:");
+ this.out.println();
+
+ for (Statistic stat : statistics.getStatistics()) {
+ this.out.println(stat.getAbbreviation() + " = " + stat.getDescription());
+ }
+
+ this.out.println();
+
if (isSortByUtility()) {
this.out.println();
this.out.println("Sorting by utility, high to low.");
@@ -389,11 +401,14 @@ public void compareFromSimulations(String resultsPath, Simulations simulations,
this.out.println("interval [0, 1], with higher being better.");
}
- this.out.println();
this.out.println("Graphs are being compared to the " + this.comparisonGraph.toString().replace("_", " ") + ".");
+ this.out.println("All statistics are individually summarized over " + numRuns + " runs using the indicated statistic.");
this.out.println();
+ statTables = calcStatTables(allStats, Mode.Average, numTables,
+ algorithmSimulationWrappers, numStats, statistics);
+
// Add utilities to table as the last column.
for (int u = 0; u < numTables; u++) {
for (int t = 0; t < algorithmSimulationWrappers.size(); t++) {
@@ -401,10 +416,11 @@ public void compareFromSimulations(String resultsPath, Simulations simulations,
}
}
- // Print all of the tables.
+ // Print all the tables.
printStats(statTables, statistics, Mode.Average, newOrder, algorithmSimulationWrappers,
algorithmWrappers, simulationWrappers, utilities, parameters);
+
statTables = calcStatTables(allStats, Mode.StandardDeviation, numTables,
algorithmSimulationWrappers, numStats, statistics);
@@ -417,7 +433,7 @@ public void compareFromSimulations(String resultsPath, Simulations simulations,
printStats(statTables, statistics, Mode.StandardDeviation, newOrder, algorithmSimulationWrappers, algorithmWrappers,
simulationWrappers, utilities, parameters);
- statTables = calcStatTables(allStats, Mode.WorstCase, numTables, algorithmSimulationWrappers,
+ statTables = calcStatTables(allStats, Mode.MinValue, numTables, algorithmSimulationWrappers,
numStats, statistics);
for (int u = 0; u < numTables; u++) {
@@ -426,10 +442,10 @@ public void compareFromSimulations(String resultsPath, Simulations simulations,
}
}
- printStats(statTables, statistics, Mode.WorstCase, newOrder, algorithmSimulationWrappers, algorithmWrappers,
+ printStats(statTables, statistics, Mode.MinValue, newOrder, algorithmSimulationWrappers, algorithmWrappers,
simulationWrappers, utilities, parameters);
- statTables = calcStatTables(allStats, Mode.MedianCase, numTables, algorithmSimulationWrappers,
+ statTables = calcStatTables(allStats, Mode.MaxValue, numTables, algorithmSimulationWrappers,
numStats, statistics);
for (int u = 0; u < numTables; u++) {
@@ -438,15 +454,27 @@ public void compareFromSimulations(String resultsPath, Simulations simulations,
}
}
- printStats(statTables, statistics, Mode.MedianCase, newOrder, algorithmSimulationWrappers, algorithmWrappers,
+ printStats(statTables, statistics, Mode.MaxValue, newOrder, algorithmSimulationWrappers, algorithmWrappers,
simulationWrappers, utilities, parameters);
- // Add utilities to table as the last column.
+ statTables = calcStatTables(allStats, Mode.MedianValue, numTables, algorithmSimulationWrappers,
+ numStats, statistics);
+
for (int u = 0; u < numTables; u++) {
for (int t = 0; t < algorithmSimulationWrappers.size(); t++) {
statTables[u][t][numStats] = utilities[t];
}
}
+
+ printStats(statTables, statistics, Mode.MedianValue, newOrder, algorithmSimulationWrappers, algorithmWrappers,
+ simulationWrappers, utilities, parameters);
+
+// // Add utilities to table as the last column.
+// for (int u = 0; u < numTables; u++) {
+// for (int t = 0; t < algorithmSimulationWrappers.size(); t++) {
+// statTables[u][t][numStats] = utilities[t];
+// }
+// }
}
for (int i = 0; i < simulations.getSimulations().size(); i++) {
@@ -483,7 +511,9 @@ public void saveToFiles(String dataPath, Simulation simulation, Parameters param
parameters.set(param, simulationWrapper.getValue(param));
}
- simulationWrapper.createData(simulationWrapper.getSimulationSpecificParameters(), false);
+ if (simulation.getNumDataModels() == 0) {
+ simulationWrapper.createData(simulationWrapper.getSimulationSpecificParameters(), true);
+ }
File subdir = dir;
if (simulationWrappers.size() > 1) {
@@ -534,9 +564,8 @@ public void saveToFiles(String dataPath, Simulation simulation, Parameters param
if (isSavePags()) {
File file4 = new File(dir4, "pag." + (j + 1) + ".txt");
- GraphUtils.saveGraph(new DagToPag(graph).convert(), file4, false);
+ GraphUtils.saveGraph(dagToPag(graph), file4, false);
}
-
}
PrintStream out = new PrintStream(new FileOutputStream(new File(subdir, "parameters.txt")));
@@ -621,7 +650,7 @@ public void saveToFilesSingleSimulation(String dataPath, Simulation simulation,
if (isSavePags()) {
File file4 = new File(dir4, "pag." + (j + 1) + ".txt");
- GraphUtils.saveGraph(new DagToPag(graph).convert(), file4, false);
+ GraphUtils.saveGraph(dagToPag(graph), file4, false);
}
}
} catch (IOException e) {
@@ -888,8 +917,15 @@ private double[][][][] calcStats(List algorithmSimul
}
}
- for (AlgorithmTask task : tasks) {
- task.compute();
+ if (parallelized) {
+ int parallelism = ForkJoinPool.getCommonPoolParallelism() + 10;
+ ForkJoinPool pool = (ForkJoinPool) Executors.newWorkStealingPool(parallelism);
+ pool.invokeAll(tasks);
+ pool.shutdown();
+ } else {
+ for (AlgorithmTask task : tasks) {
+ task.call();
+ }
}
return allStats;
@@ -1024,7 +1060,7 @@ public void setComparisonGraph(ComparisonGraph comparisonGraph) {
this.comparisonGraph = comparisonGraph;
}
- private class AlgorithmTask extends RecursiveTask {
+ private class AlgorithmTask implements Callable {
private final List algorithmSimulationWrappers;
private final List algorithmWrappers;
@@ -1049,7 +1085,7 @@ public AlgorithmTask(List algorithmSimulationWrapper
}
@Override
- protected Boolean compute() {
+ public Boolean call() {
doRun(this.algorithmSimulationWrappers, this.algorithmWrappers,
this.simulationWrappers, this.statistics, this.numGraphTypes, this.allStats, this.run, this.stdout);
return true;
@@ -1198,7 +1234,7 @@ private void doRun(List algorithmSimulationWrappers,
} else if (this.comparisonGraph == ComparisonGraph.CPDAG_of_the_true_DAG) {
comparisonGraph = SearchGraphUtils.cpdagForDag(new EdgeListGraph(trueGraph));
} else if (this.comparisonGraph == ComparisonGraph.PAG_of_the_true_DAG) {
- comparisonGraph = new DagToPag(new EdgeListGraph(trueGraph)).convert();
+ comparisonGraph = dagToPag(new EdgeListGraph(trueGraph));
} else {
throw new IllegalArgumentException("Unrecognized graph type.");
}
@@ -1296,7 +1332,7 @@ private void saveGraph(String resultsPath, Graph graph, int i, int simIndex,
}
private enum Mode {
- Average, StandardDeviation, WorstCase, MedianCase
+ Average, StandardDeviation, MinValue, MaxValue, MedianValue
}
private String getHeader(int u) {
@@ -1375,11 +1411,13 @@ private double[][][] calcStatTables(double[][][][] allStats, Mode mode, int numT
} else if (mode == Mode.Average) {
double mean = StatUtils.mean(allStats[u][i][j]);
statTables[u][i][j] = mean;
- } else if (mode == Mode.WorstCase) {
+ } else if (mode == Mode.MinValue) {
statTables[u][i][j] = StatUtils.min(allStats[u][i][j]);
+ } else if (mode == Mode.MaxValue) {
+ statTables[u][i][j] = StatUtils.max(allStats[u][i][j]);
} else if (mode == Mode.StandardDeviation) {
statTables[u][i][j] = StatUtils.sd(allStats[u][i][j]);
- } else if (mode == Mode.MedianCase) {
+ } else if (mode == Mode.MedianValue) {
statTables[u][i][j] = StatUtils.median(allStats[u][i][j]);
} else {
throw new IllegalStateException();
@@ -1398,13 +1436,15 @@ private void printStats(double[][][] statTables, Statistics statistics, Mode mod
Parameters parameters) {
if (mode == Mode.Average) {
- this.out.println("AVERAGE STATISTICS");
+ this.out.println("AVERAGE VALUE");
} else if (mode == Mode.StandardDeviation) {
- this.out.println("STANDARD DEVIATIONS");
- } else if (mode == Mode.WorstCase) {
- this.out.println("WORST CASE");
- } else if (mode == Mode.MedianCase) {
- this.out.println("MEDIAN CASE");
+ this.out.println("STANDARD DEVIATION");
+ } else if (mode == Mode.MinValue) {
+ this.out.println("MIN VALUE");
+ } else if (mode == Mode.MaxValue) {
+ this.out.println("MAX VALUE");
+ } else if (mode == Mode.MedianValue) {
+ this.out.println("MEDIAN VALUE");
} else {
throw new IllegalStateException();
}
@@ -1427,7 +1467,7 @@ private void printStats(double[][][] statTables, Statistics statistics, Mode mod
+ (isShowUtilities() ? 1 : 0);
TextTable table = new TextTable(rows, cols);
- table.setTabDelimited(isTabDelimitedTables());
+ table.setDelimiter(isTabDelimitedTables() ? TextTable.Delimiter.TAB : TextTable.Delimiter.JUSTIFIED);
int initialColumn = 0;
@@ -1763,12 +1803,14 @@ public SimulationWrapper(Simulation simulation, Parameters parameters) {
@Override
public void createData(Parameters parameters, boolean newModel) {
- this.simulation.createData(parameters, newModel);
- this.graphs = new ArrayList<>();
- this.dataModels = new ArrayList<>();
- for (int i = 0; i < this.simulation.getNumDataModels(); i++) {
- this.graphs.add(this.simulation.getTrueGraph(i));
- this.dataModels.add(this.simulation.getDataModel(i));
+ if (newModel) {
+ this.simulation.createData(parameters, newModel);
+ this.graphs = new ArrayList<>();
+ this.dataModels = new ArrayList<>();
+ for (int i = 0; i < this.simulation.getNumDataModels(); i++) {
+ this.graphs.add(this.simulation.getTrueGraph(i));
+ this.dataModels.add(this.simulation.getDataModel(i));
+ }
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/TimeoutComparison.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/TimeoutComparison.java
index 009c7665ba..63704b1131 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/TimeoutComparison.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/TimeoutComparison.java
@@ -53,6 +53,8 @@
import java.util.*;
import java.util.concurrent.*;
+import static edu.cmu.tetrad.search.SearchGraphUtils.dagToPag;
+
/**
* Nov 14, 2017 12:00:31 PM
*
@@ -511,7 +513,7 @@ public void saveToFiles(String dataPath, Simulation simulation, Parameters param
if (isSavePags()) {
File file4 = new File(dir4, "pag." + (j + 1) + ".txt");
- GraphUtils.saveGraph(new DagToPag(graph).convert(), file4, false);
+ GraphUtils.saveGraph(dagToPag(graph), file4, false);
}
}
@@ -1147,7 +1149,7 @@ private void doRun(List algorithmSimulationWrappers,
} else if (this.comparisonGraph == ComparisonGraph.CPDAG_of_the_true_DAG) {
comparisonGraph = SearchGraphUtils.cpdagForDag(new EdgeListGraph(trueGraph));
} else if (this.comparisonGraph == ComparisonGraph.PAG_of_the_true_DAG) {
- comparisonGraph = new DagToPag(new EdgeListGraph(trueGraph)).convert();
+ comparisonGraph = dagToPag(new EdgeListGraph(trueGraph));
} else {
throw new IllegalArgumentException("Unrecognized graph type.");
}
@@ -1368,7 +1370,7 @@ private void printStats(double[][][] statTables, Statistics statistics, Mode mod
+ (isShowUtilities() ? 1 : 0);
TextTable table = new TextTable(rows, cols);
- table.setTabDelimited(isTabDelimitedTables());
+ table.setDelimiter(isTabDelimitedTables() ? TextTable.Delimiter.TAB : TextTable.Delimiter.JUSTIFIED);
int initialColumn = 0;
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/MultiDataSetAlgorithm.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/MultiDataSetAlgorithm.java
index ee058b01b9..0716945d70 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/MultiDataSetAlgorithm.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/MultiDataSetAlgorithm.java
@@ -1,5 +1,6 @@
package edu.cmu.tetrad.algcomparison.algorithm;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
import edu.cmu.tetrad.data.DataModel;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.util.Parameters;
@@ -16,9 +17,11 @@ public interface MultiDataSetAlgorithm extends Algorithm {
/**
* Runs the search.
*
- * @param dataSet The data set to run to the search on.
+ * @param dataSets The data set to run to the search on.
* @param parameters The paramters of the search.
* @return The result graph.
*/
- Graph search(List dataSet, Parameters parameters);
+ Graph search(List dataSets, Parameters parameters);
+
+ void setScoreWrapper(ScoreWrapper score);
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Bpc.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Bpc.java
index 92f73d482c..d4d1bdc84d 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Bpc.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Bpc.java
@@ -32,7 +32,7 @@
public class Bpc implements Algorithm, HasKnowledge, ClusterAlgorithm {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public Bpc() {
}
@@ -65,7 +65,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
Mimbuild mimbuild = new Mimbuild();
mimbuild.setPenaltyDiscount(parameters.getDouble(Params.PENALTY_DISCOUNT));
- mimbuild.setKnowledge((IKnowledge) parameters.get("knowledge", new Knowledge2()));
+ mimbuild.setKnowledge((Knowledge) parameters.get("knowledge", new Knowledge()));
if (parameters.getBoolean("includeThreeClusters", true)) {
mimbuild.setMinClusterSize(3);
@@ -136,12 +136,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Fofc.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Fofc.java
index 1d20751fd3..88abccf437 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Fofc.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Fofc.java
@@ -5,7 +5,6 @@
import edu.cmu.tetrad.annotation.AlgType;
import edu.cmu.tetrad.annotation.Bootstrapping;
import edu.cmu.tetrad.data.*;
-import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.GraphUtils;
import edu.cmu.tetrad.graph.Node;
@@ -33,7 +32,7 @@
public class Fofc implements Algorithm, HasKnowledge, ClusterAlgorithm {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public Fofc() {
}
@@ -76,7 +75,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
Mimbuild mimbuild = new Mimbuild();
mimbuild.setPenaltyDiscount(parameters.getDouble(Params.PENALTY_DISCOUNT));
- mimbuild.setKnowledge((IKnowledge) parameters.get("knowledge", new Knowledge2()));
+ mimbuild.setKnowledge((Knowledge) parameters.get("knowledge", new Knowledge()));
if (parameters.getBoolean("includeThreeClusters", true)) {
mimbuild.setMinClusterSize(3);
@@ -148,12 +147,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Ftfc.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Ftfc.java
index c556f72c8d..409bc4ede1 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Ftfc.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Ftfc.java
@@ -31,7 +31,7 @@
public class Ftfc implements Algorithm, HasKnowledge, ClusterAlgorithm {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public Ftfc() {
}
@@ -105,13 +105,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/CcdMaxConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/CcdMaxConcatenated.java
index f7bf3dc59f..22bb2f6faa 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/CcdMaxConcatenated.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/CcdMaxConcatenated.java
@@ -2,6 +2,7 @@
import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm;
import edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.annotation.Bootstrapping;
import edu.cmu.tetrad.data.*;
@@ -26,7 +27,7 @@
@Bootstrapping
public class CcdMaxConcatenated implements MultiDataSetAlgorithm, HasKnowledge {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
private final IndependenceWrapper test;
public CcdMaxConcatenated(IndependenceWrapper test) {
@@ -69,6 +70,7 @@ public Graph search(List dataModels, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -76,6 +78,11 @@ public Graph search(List dataModels, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
@@ -90,6 +97,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -132,12 +140,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FASK.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FASK.java
index 638f63125e..190f786fd7 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FASK.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FASK.java
@@ -41,7 +41,7 @@ public class FASK implements Algorithm, HasKnowledge, UsesScoreWrapper, TakesInd
private IndependenceWrapper test;
private ScoreWrapper score;
private Graph externalGraph;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
private Algorithm algorithm;
// Don't delete.
@@ -178,13 +178,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofs.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofs.java
index dda72be1eb..4ce5ce8048 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofs.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofs.java
@@ -24,7 +24,7 @@
public class FasLofs implements Algorithm, HasKnowledge {
static final long serialVersionUID = 23L;
private final Lofs2.Rule rule;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public FasLofs(Lofs2.Rule rule) {
this.rule = rule;
@@ -83,12 +83,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofsConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofsConcatenated.java
index 2c8a892e2c..38c17dd0d1 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofsConcatenated.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofsConcatenated.java
@@ -1,6 +1,7 @@
package edu.cmu.tetrad.algcomparison.algorithm.multi;
import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.annotation.Bootstrapping;
import edu.cmu.tetrad.data.*;
@@ -29,7 +30,7 @@
public class FasLofsConcatenated implements MultiDataSetAlgorithm, HasKnowledge {
static final long serialVersionUID = 23L;
private final Lofs2.Rule rule;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public FasLofsConcatenated(Lofs2.Rule rule) {
this.rule = rule;
@@ -66,6 +67,7 @@ public Graph search(List dataModels, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -73,6 +75,11 @@ public Graph search(List dataModels, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
private Graph getGraph(FasLofs search) {
return search.search();
}
@@ -91,6 +98,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -128,12 +136,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskConcatenated.java
index 92a1962373..bb9b4ba034 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskConcatenated.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskConcatenated.java
@@ -39,7 +39,7 @@ public class FaskConcatenated implements MultiDataSetAlgorithm, HasKnowledge, Ta
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
private ScoreWrapper score;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public FaskConcatenated() {
@@ -86,6 +86,7 @@ public Graph search(List dataSets, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(score);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -93,6 +94,11 @@ public Graph search(List dataSets, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
@@ -107,6 +113,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(score);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -145,13 +152,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskVote.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskVote.java
index ca5c02e4a7..07331aa24c 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskVote.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskVote.java
@@ -41,7 +41,7 @@
public class FaskVote implements MultiDataSetAlgorithm, HasKnowledge, UsesScoreWrapper, TakesExternalGraph, TakesIndependenceWrapper {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
private Graph externalGraph;
private ScoreWrapper score;
private IndependenceWrapper test;
@@ -87,6 +87,7 @@ public Graph search(List dataSets, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(score);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -109,6 +110,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(score);
search.setParameters(parameters);
@@ -141,13 +143,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FgesConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FgesConcatenated.java
index 4d78f2db6c..4b6e8ab932 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FgesConcatenated.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FgesConcatenated.java
@@ -29,7 +29,7 @@
public class FgesConcatenated implements MultiDataSetAlgorithm, HasKnowledge {
static final long serialVersionUID = 23L;
private final ScoreWrapper score;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
private Algorithm externalGraph;
private boolean compareToTrue;
@@ -95,6 +95,7 @@ public Graph search(List dataModels, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(score);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -102,6 +103,11 @@ public Graph search(List dataModels, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
@@ -117,6 +123,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(score);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -158,13 +165,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
/**
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/Images.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/Images.java
new file mode 100644
index 0000000000..102b4b4f78
--- /dev/null
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/Images.java
@@ -0,0 +1,232 @@
+package edu.cmu.tetrad.algcomparison.algorithm.multi;
+
+import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm;
+import edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
+import edu.cmu.tetrad.algcomparison.score.SemBicScore;
+import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
+import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper;
+import edu.cmu.tetrad.annotation.AlgType;
+import edu.cmu.tetrad.annotation.Bootstrapping;
+import edu.cmu.tetrad.data.*;
+import edu.cmu.tetrad.graph.EdgeListGraph;
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.search.*;
+import edu.cmu.tetrad.util.Parameters;
+import edu.cmu.tetrad.util.Params;
+import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
+
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.LinkedList;
+import java.util.List;
+
+/**
+ * Wraps the IMaGES algorithm for continuous variables.
+ *
+ * Requires that the parameter 'randomSelectionSize' be set to indicate how many
+ * datasets should be taken at a time (randomly). This cannot given multiple
+ * values.
+ *
+ * @author jdramsey
+ */
+@edu.cmu.tetrad.annotation.Algorithm(
+ name = "IMaGES",
+ command = "images",
+ algoType = AlgType.forbid_latent_common_causes,
+ dataType = DataType.All
+)
+@Bootstrapping
+public class Images implements MultiDataSetAlgorithm, HasKnowledge, UsesScoreWrapper {
+
+ static final long serialVersionUID = 23L;
+ private Knowledge knowledge = new Knowledge();
+
+ private ScoreWrapper score;
+
+ public Images() {
+ }
+
+ @Override
+ public Graph search(List dataSets, Parameters parameters) {
+ this.knowledge = dataSets.get(0).getKnowledge();
+ int meta = parameters.getInt(Params.IMAGES_META_ALG);
+
+ if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
+ List _dataSets = new ArrayList<>();
+
+ if (parameters.getInt(Params.TIME_LAG) > 0) {
+ for (DataModel dataSet : dataSets) {
+ DataSet timeSeries = TimeSeriesUtils.createLagData((DataSet) dataSet, parameters.getInt(Params.TIME_LAG));
+ if (dataSet.getName() != null) {
+ timeSeries.setName(dataSet.getName());
+ }
+ _dataSets.add(timeSeries);
+ }
+
+ dataSets = _dataSets;
+ this.knowledge = _dataSets.get(0).getKnowledge();
+ }
+
+ List scores = new ArrayList<>();
+
+ for (DataModel dataModel : dataSets) {
+ Score s = score.getScore(dataModel, parameters);
+ scores.add(s);
+ }
+
+ ImagesScore score = new ImagesScore(scores);
+
+ if (meta == 1) {
+ edu.cmu.tetrad.search.Fges search = new edu.cmu.tetrad.search.Fges(score);
+ search.setKnowledge(new Knowledge((Knowledge) knowledge));
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ return search.search();
+ }
+// else if (meta == 2) {
+// Grasp search = new edu.cmu.tetrad.search.Grasp(score);
+// search.setKnowledge(this.knowledge);
+// search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+// search.bestOrder(score.getVariables());
+// search.setDepth(6);
+// search.setSingularDepth(1);
+// search.setNonSingularDepth(1);
+// return search.getGraph(true);
+// }
+ else if (meta == 2) {
+ Boss search = new Boss(score);
+ search.setAlgType(Boss.AlgType.BOSS1);
+ search.setKnowledge(new Knowledge((Knowledge) knowledge));
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ search.bestOrder(score.getVariables());
+ return search.getGraph(true);
+ }
+// else if (meta == 4) {
+// Boss search = new edu.cmu.tetrad.search.Boss(score);
+// search.setKnowledge(this.knowledge);
+// search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+// search.bestOrder(score.getVariables());
+// return search.getGraph();
+// }
+ else if (meta == 3) {
+ BridgesOld search = new edu.cmu.tetrad.search.BridgesOld(score);
+ search.setKnowledge(this.knowledge);
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ return search.search();
+ }
+ else {
+ throw new IllegalArgumentException("Unrecognized meta option: " + meta);
+ }
+ } else {
+ Images imagesSemBic = new Images();
+
+ List dataSets2 = new ArrayList<>();
+
+ for (DataModel dataModel : dataSets) {
+ dataSets2.add((DataSet) dataModel);
+ }
+
+ List _dataSets = new ArrayList<>();
+
+ if (parameters.getInt(Params.TIME_LAG) > 0) {
+ for (DataSet dataSet : dataSets2) {
+ DataSet timeSeries = TimeSeriesUtils.createLagData(dataSet, parameters.getInt(Params.TIME_LAG));
+ if (dataSet.getName() != null) {
+ timeSeries.setName(dataSet.getName());
+ }
+ _dataSets.add(timeSeries);
+ }
+
+ dataSets2 = _dataSets;
+ }
+
+ GeneralResamplingTest search = new GeneralResamplingTest(
+ dataSets2,
+ imagesSemBic,
+ parameters.getInt(Params.NUMBER_RESAMPLING),
+ parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
+ parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
+ search.setParameters(parameters);
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ search.setKnowledge(dataSets.get(0).getKnowledge());
+ search.setScoreWrapper(score);
+ return search.search();
+ }
+ }
+
+ @Override
+ public Graph search(DataModel dataSet, Parameters parameters) {
+ if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
+ return search(Collections.singletonList(DataUtils.getMixedDataSet(dataSet)), parameters);
+ } else {
+ Images images = new Images();
+
+ List dataSets = Collections.singletonList(DataUtils.getMixedDataSet(dataSet));
+ GeneralResamplingTest search = new GeneralResamplingTest(dataSets,
+ images,
+ parameters.getInt(Params.NUMBER_RESAMPLING),
+ parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
+ parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
+// search.setKnowledge(this.knowledge);
+
+ if (score == null) {
+ System.out.println();
+ }
+
+ search.setParameters(parameters);
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ search.setScoreWrapper(score);
+ return search.search();
+ }
+ }
+
+ @Override
+ public Graph getComparisonGraph(Graph graph) {
+ return new EdgeListGraph(graph);
+ }
+
+ @Override
+ public String getDescription() {
+ return "IMaGES";
+ }
+
+ @Override
+ public DataType getDataType() {
+ return DataType.All;
+ }
+
+ @Override
+ public List getParameters() {
+ List parameters = new LinkedList<>();
+ parameters.addAll(new SemBicScore().getParameters());
+
+ parameters.addAll((new Fges()).getParameters());
+ parameters.add(Params.RANDOM_SELECTION_SIZE);
+ parameters.add(Params.TIME_LAG);
+ parameters.add(Params.IMAGES_META_ALG);
+
+ parameters.add(Params.VERBOSE);
+
+ return parameters;
+ }
+
+ @Override
+ public Knowledge getKnowledge() {
+ return this.knowledge;
+ }
+
+ @Override
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
+ }
+
+ @Override
+ public ScoreWrapper getScoreWrapper() {
+ return this.score;
+ }
+
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+ this.score = score;
+ }
+}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesBDeu.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesBDeu.java
index 83ef36efdc..c08e0c9b68 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesBDeu.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesBDeu.java
@@ -3,9 +3,10 @@
import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm;
import edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges;
import edu.cmu.tetrad.algcomparison.score.BdeuScore;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
-import edu.cmu.tetrad.annotation.AlgType;
import edu.cmu.tetrad.annotation.Bootstrapping;
+import edu.cmu.tetrad.annotation.Experimental;
import edu.cmu.tetrad.data.*;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
@@ -29,17 +30,18 @@
*
* @author jdramsey
*/
-@edu.cmu.tetrad.annotation.Algorithm(
- name = "IMaGES Discrete",
- command = "imgs_disc",
- algoType = AlgType.forbid_latent_common_causes,
- dataType = DataType.Discrete
-)
+//@edu.cmu.tetrad.annotation.Algorithm(
+// name = "IMaGES Discrete",
+// command = "imgs_disc",
+// algoType = AlgType.forbid_latent_common_causes,
+// dataType = DataType.Discrete
+//)
@Bootstrapping
+@Experimental
public class ImagesBDeu implements MultiDataSetAlgorithm, HasKnowledge {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public ImagesBDeu() {
}
@@ -71,6 +73,7 @@ public Graph search(List dataSets, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -78,6 +81,11 @@ public Graph search(List dataSets, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
@@ -92,6 +100,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -127,12 +136,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesPcStableMax.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesPcStableMax.java
index bd00d4ad8d..d9b0a32d4e 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesPcStableMax.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesPcStableMax.java
@@ -1,6 +1,7 @@
package edu.cmu.tetrad.algcomparison.algorithm.multi;
import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.annotation.Bootstrapping;
import edu.cmu.tetrad.data.*;
@@ -29,7 +30,7 @@
@Bootstrapping
public class ImagesPcStableMax implements MultiDataSetAlgorithm, HasKnowledge {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public ImagesPcStableMax() {
}
@@ -67,6 +68,7 @@ public Graph search(List dataModels, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -74,6 +76,11 @@ public Graph search(List dataModels, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
@@ -88,6 +95,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -131,12 +139,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesSemBic.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesSemBic.java
index 2eb1f3c1bf..80f5d5bb81 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesSemBic.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesSemBic.java
@@ -2,10 +2,11 @@
import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm;
import edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
import edu.cmu.tetrad.algcomparison.score.SemBicScore;
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
-import edu.cmu.tetrad.annotation.AlgType;
import edu.cmu.tetrad.annotation.Bootstrapping;
+import edu.cmu.tetrad.annotation.Experimental;
import edu.cmu.tetrad.data.*;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
@@ -29,17 +30,18 @@
*
* @author jdramsey
*/
-@edu.cmu.tetrad.annotation.Algorithm(
- name = "IMaGES Continuous",
- command = "imgs_cont",
- algoType = AlgType.forbid_latent_common_causes,
- dataType = DataType.Continuous
-)
+//@edu.cmu.tetrad.annotation.Algorithm(
+// name = "IMaGES Continuous",
+// command = "imgs_cont",
+// algoType = AlgType.forbid_latent_common_causes,
+// dataType = DataType.Continuous
+//)
@Bootstrapping
+@Experimental
public class ImagesSemBic implements MultiDataSetAlgorithm, HasKnowledge {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public ImagesSemBic() {
}
@@ -51,7 +53,7 @@ public Graph search(List dataSets, Parameters parameters) {
if (parameters.getInt(Params.TIME_LAG) > 0) {
for (DataModel dataSet : dataSets) {
- DataSet timeSeries = TimeSeriesUtils.createLagData((DataSet) dataSet, parameters.getInt(Params.TIME_LAG));
+ DataSet timeSeries = TimeSeriesUtils.createLagData((DataSet) dataSet, parameters.getInt(Params.TIME_LAG));
if (dataSet.getName() != null) {
timeSeries.setName(dataSet.getName());
}
@@ -71,22 +73,35 @@ public Graph search(List dataSets, Parameters parameters) {
} else {
ImagesSemBic imagesSemBic = new ImagesSemBic();
- List datasets = new ArrayList<>();
+ List dataSets2 = new ArrayList<>();
+ for (DataModel dataModel : dataSets) {
+ dataSets2.add((DataSet) dataModel);
+ }
+ List _dataSets = new ArrayList<>();
- for (DataModel dataModel : dataSets) {
- dataModel.setKnowledge(knowledge);
- datasets.add((DataSet) dataModel);
+ if (parameters.getInt(Params.TIME_LAG) > 0) {
+ for (DataModel dataSet : dataSets2) {
+ DataSet timeSeries = TimeSeriesUtils.createLagData((DataSet) dataSet, parameters.getInt(Params.TIME_LAG));
+ if (dataSet.getName() != null) {
+ timeSeries.setName(dataSet.getName());
+ }
+ _dataSets.add(timeSeries);
+ }
+
+ dataSets2 = _dataSets;
+ this.knowledge = _dataSets.get(0).getKnowledge();
}
GeneralResamplingTest search = new GeneralResamplingTest(
- datasets,
+ dataSets2,
imagesSemBic,
parameters.getInt(Params.NUMBER_RESAMPLING),
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -95,6 +110,11 @@ public Graph search(List dataSets, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
@@ -109,6 +129,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -147,12 +168,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/MultiFaskV1.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/MultiFaskV1.java
index 4400e486b9..f4e541e1c7 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/MultiFaskV1.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/MultiFaskV1.java
@@ -2,6 +2,7 @@
import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm;
import edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
import edu.cmu.tetrad.algcomparison.score.SemBicScore;
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.annotation.Bootstrapping;
@@ -39,7 +40,7 @@
public class MultiFaskV1 implements MultiDataSetAlgorithm, HasKnowledge {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public MultiFaskV1() {
@@ -84,6 +85,7 @@ public Graph search(List dataSets, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -91,6 +93,11 @@ public Graph search(List dataSets, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
@@ -105,6 +112,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -142,12 +150,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/PcStableMaxConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/PcStableMaxConcatenated.java
index d17e17e19c..0b231bc764 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/PcStableMaxConcatenated.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/PcStableMaxConcatenated.java
@@ -3,6 +3,7 @@
import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm;
import edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.annotation.Bootstrapping;
import edu.cmu.tetrad.data.*;
@@ -33,7 +34,7 @@ public class PcStableMaxConcatenated implements MultiDataSetAlgorithm, HasKnowle
private boolean compareToTrue;
private final IndependenceWrapper test;
private final Algorithm externalGraph = null;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public PcStableMaxConcatenated(IndependenceWrapper test, boolean compareToTrue) {
this.test = test;
@@ -77,6 +78,7 @@ public Graph search(List dataModels, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -84,6 +86,11 @@ public Graph search(List dataModels, Parameters parameters) {
}
}
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+
+ }
+
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
@@ -98,6 +105,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
+ search.setScoreWrapper(null);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
@@ -144,13 +152,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS.java
index aeedad2943..703bc275cb 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS.java
@@ -9,10 +9,18 @@
import edu.cmu.tetrad.annotation.AlgType;
import edu.cmu.tetrad.annotation.Bootstrapping;
import edu.cmu.tetrad.annotation.Experimental;
-import edu.cmu.tetrad.data.*;
+import edu.cmu.tetrad.data.DataModel;
+import edu.cmu.tetrad.data.DataSet;
+import edu.cmu.tetrad.data.DataType;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
-import edu.cmu.tetrad.search.*;
+import edu.cmu.tetrad.graph.Node;
+import edu.cmu.tetrad.graph.NodeType;
+import edu.cmu.tetrad.search.Boss;
+import edu.cmu.tetrad.search.IndependenceTest;
+import edu.cmu.tetrad.search.Score;
+import edu.cmu.tetrad.search.TimeSeriesUtils;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.Params;
import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
@@ -21,7 +29,7 @@
import java.util.List;
/**
- * GRaSP (Greedy Relaxations of Sparsest Permutation)
+ * BOSS (Best Order Score Search)
*
* @author bryanandrews
* @author josephramsey
@@ -37,15 +45,19 @@ public class BOSS implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapp
static final long serialVersionUID = 23L;
private ScoreWrapper score;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public BOSS() {
// Used in reflection; do not delete.
}
- public BOSS(ScoreWrapper score, IndependenceWrapper test) {
- this.score = score;
+// public BOSS(ScoreWrapper score) {
+// this.score = score;
+// }
+
+ public BOSS(IndependenceWrapper test, ScoreWrapper score) {
this.test = test;
+ this.score = score;
}
@Override
@@ -64,28 +76,44 @@ public Graph search(DataModel dataModel, Parameters parameters) {
Score score = this.score.getScore(dataModel, parameters);
IndependenceTest test = this.test.getTest(dataModel, parameters);
- test.setVerbose(parameters.getBoolean(Params.VERBOSE));
Boss boss = new Boss(test, score);
- boss.setDepth(parameters.getInt(Params.GRASP_DEPTH));
- boss.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE));
- boss.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL));
+ if (parameters.getInt(Params.BOSS_ALG) == 1) {
+ boss.setAlgType(Boss.AlgType.BOSS1);
+ } else if (parameters.getInt(Params.BOSS_ALG) == 2) {
+ boss.setAlgType(Boss.AlgType.BOSS2);
+ } else if (parameters.getInt(Params.BOSS_ALG) == 3) {
+ boss.setAlgType(Boss.AlgType.BOSS3);
+ } else {
+ throw new IllegalArgumentException("Unrecognized boss algorithm type.");
+ }
+
+ boss.setDepth(parameters.getInt(Params.DEPTH));
boss.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER));
+ boss.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE));
+ boss.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_RASKUTTI_UHLER));
boss.setVerbose(parameters.getBoolean(Params.VERBOSE));
- boss.setCacheScores(parameters.getBoolean(Params.CACHE_SCORES));
-
boss.setNumStarts(parameters.getInt(Params.NUM_STARTS));
+ boss.setCaching(parameters.getBoolean(Params.CACHE_SCORES));
+
boss.setKnowledge(this.knowledge);
- boss.bestOrder(score.getVariables());
- return boss.getGraph(parameters.getBoolean(Params.OUTPUT_CPDAG));
+
+ boss.bestOrder(new ArrayList(score.getVariables()));
+ return boss.getGraph(true);
} else {
- BOSS algorithm = new BOSS(this.score, this.test);
+ BOSS algorithm = new BOSS(this.test, this.score);
DataSet data = (DataSet) dataModel;
- GeneralResamplingTest search = new GeneralResamplingTest(data, algorithm, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
+ GeneralResamplingTest search = new GeneralResamplingTest(
+ data,
+ algorithm,
+ parameters.getInt(Params.NUMBER_RESAMPLING),
+ parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
+ parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT),
+ parameters.getInt(Params.RESAMPLING_ENSEMBLE),
+ parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
search.setKnowledge(this.knowledge);
-
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean(Params.VERBOSE));
return search.search();
@@ -99,8 +127,7 @@ public Graph getComparisonGraph(Graph graph) {
@Override
public String getDescription() {
- return "BOSS (Better Order Score Search) using " + this.test.getDescription()
- + " or " + this.score.getDescription();
+ return "BOSS (Best Order Score Search) using " + this.score.getDescription();
}
@Override
@@ -113,15 +140,19 @@ public List getParameters() {
ArrayList params = new ArrayList<>();
// Flags
- params.add(Params.GRASP_DEPTH);
+ params.add(Params.BOSS_ALG);
+ params.add(Params.DEPTH);
params.add(Params.GRASP_USE_SCORE);
- params.add(Params.GRASP_USE_VERMA_PEARL);
+ params.add(Params.GRASP_USE_RASKUTTI_UHLER);
params.add(Params.GRASP_USE_DATA_ORDER);
+ params.add(Params.TIME_LAG);
+ params.add(Params.CACHE_SCORES);
params.add(Params.VERBOSE);
// Parameters
params.add(Params.NUM_STARTS);
+
return params;
}
@@ -136,22 +167,22 @@ public void setScoreWrapper(ScoreWrapper score) {
}
@Override
- public IndependenceWrapper getIndependenceWrapper() {
- return this.test;
+ public Knowledge getKnowledge() {
+ return this.knowledge.copy();
}
@Override
- public void setIndependenceWrapper(IndependenceWrapper independenceWrapper) {
- this.test = independenceWrapper;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
- public IKnowledge getKnowledge() {
- return this.knowledge.copy();
+ public void setIndependenceWrapper(IndependenceWrapper test) {
+ this.test = test;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge.copy();
+ public IndependenceWrapper getIndependenceWrapper() {
+ return this.test;
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB.java
new file mode 100644
index 0000000000..cb6a7eb93e
--- /dev/null
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB.java
@@ -0,0 +1,144 @@
+package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag;
+
+import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
+import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
+import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper;
+import edu.cmu.tetrad.annotation.AlgType;
+import edu.cmu.tetrad.annotation.Bootstrapping;
+import edu.cmu.tetrad.annotation.Experimental;
+import edu.cmu.tetrad.data.*;
+import edu.cmu.tetrad.graph.EdgeListGraph;
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.graph.GraphUtils;
+import edu.cmu.tetrad.graph.Node;
+import edu.cmu.tetrad.search.BossMB;
+import edu.cmu.tetrad.search.Score;
+import edu.cmu.tetrad.util.Parameters;
+import edu.cmu.tetrad.util.Params;
+import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * BOSS-MB.
+ *
+ * @author jdramsey
+ */
+@edu.cmu.tetrad.annotation.Algorithm(
+ name = "BOSS-MB",
+ command = "boss-mb",
+ algoType = AlgType.search_for_Markov_blankets
+)
+@Bootstrapping
+@Experimental
+public class BOSS_MB implements Algorithm, HasKnowledge, UsesScoreWrapper {
+
+ static final long serialVersionUID = 23L;
+ private ScoreWrapper score;
+ private Knowledge knowledge = new Knowledge();
+ private String targets;
+
+ public BOSS_MB() {
+ }
+
+ public BOSS_MB(ScoreWrapper score) {
+ this.score = score;
+ }
+
+ @Override
+ public Graph search(DataModel dataSet, Parameters parameters) {
+ if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
+ this.targets = parameters.getString(Params.TARGETS);
+
+ String[] tokens = this.targets.split(",");
+ List targets = new ArrayList<>();
+
+ Score score = this.score.getScore(dataSet, parameters);
+
+ for (String t : tokens) {
+ String name = t.trim();
+ targets.add(score.getVariable(name));
+ }
+
+
+ BossMB boss = new BossMB(score);
+
+ boss.setDepth(parameters.getInt(Params.GRASP_DEPTH));
+ boss.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER));
+ boss.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ boss.setFindMb(parameters.getBoolean(Params.MB));
+
+ boss.setNumStarts(parameters.getInt(Params.NUM_STARTS));
+ boss.setKnowledge(this.knowledge);
+
+ boss.bestOrder(score.getVariables(), targets);
+ return boss.getGraph();
+ } else {
+ BOSS_MB fgesMb = new BOSS_MB(this.score);
+
+ DataSet data = (DataSet) dataSet;
+ GeneralResamplingTest search = new GeneralResamplingTest(data, fgesMb, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
+ search.setKnowledge(this.knowledge);
+ search.setParameters(parameters);
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ return search.search();
+ }
+ }
+
+ @Override
+ public Graph getComparisonGraph(Graph graph) {
+ Node target = graph.getNode(this.targets);
+ return GraphUtils.markovBlanketDag(target, new EdgeListGraph(graph));
+ }
+
+ @Override
+ public String getDescription() {
+ return "BOSS-MB using " + this.score.getDescription();
+ }
+
+ @Override
+ public DataType getDataType() {
+ return this.score.getDataType();
+ }
+
+ @Override
+ public List getParameters() {
+ List params = new ArrayList<>();
+ params.add(Params.TARGETS);
+ params.add(Params.MB);
+
+ // Flags
+ params.add(Params.GRASP_DEPTH);
+ params.add(Params.GRASP_USE_DATA_ORDER);
+ params.add(Params.CACHE_SCORES);
+ params.add(Params.VERBOSE);
+
+ // Parameters
+ params.add(Params.NUM_STARTS);
+
+ return params;
+ }
+
+ @Override
+ public Knowledge getKnowledge() {
+ return this.knowledge;
+ }
+
+ @Override
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
+ }
+
+ @Override
+ public ScoreWrapper getScoreWrapper() {
+ return this.score;
+ }
+
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+ this.score = score;
+ }
+
+}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB2.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB2.java
new file mode 100644
index 0000000000..63a4595c03
--- /dev/null
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB2.java
@@ -0,0 +1,117 @@
+package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag;
+
+import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
+import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
+import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper;
+import edu.cmu.tetrad.data.*;
+import edu.cmu.tetrad.graph.EdgeListGraph;
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.search.BossMB2;
+import edu.cmu.tetrad.search.Score;
+import edu.cmu.tetrad.util.Parameters;
+import edu.cmu.tetrad.util.Params;
+import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
+
+import java.util.ArrayList;
+import java.util.List;
+
+///**
+// * BOSS-MB.
+// *
+// * @author jdramsey
+// */
+//@edu.cmu.tetrad.annotation.Algorithm(
+// name = "BOSS-MB2",
+// command = "boss-mb2",
+// algoType = AlgType.search_for_Markov_blankets
+//)
+//@Bootstrapping
+//@Experimental
+public class BOSS_MB2 implements Algorithm, HasKnowledge, UsesScoreWrapper {
+
+ static final long serialVersionUID = 23L;
+ private ScoreWrapper score;
+ private Knowledge knowledge = new Knowledge();
+
+ public BOSS_MB2() {
+ }
+
+ public BOSS_MB2(ScoreWrapper score) {
+ this.score = score;
+ }
+
+ @Override
+ public Graph search(DataModel dataSet, Parameters parameters) {
+ if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
+ Score score = this.score.getScore(dataSet, parameters);
+
+ BossMB2 boss = new BossMB2(score);
+
+ boss.setDepth(parameters.getInt(Params.DEPTH));
+ boss.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ boss.setFindMb(parameters.getBoolean(Params.MB));
+ boss.setKnowledge(this.knowledge);
+
+ return boss.search(score.getVariables());
+ } else {
+ BOSS_MB2 fgesMb = new BOSS_MB2(this.score);
+
+ DataSet data = (DataSet) dataSet;
+ GeneralResamplingTest search = new GeneralResamplingTest(data, fgesMb, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
+ search.setKnowledge(this.knowledge);
+ search.setParameters(parameters);
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ return search.search();
+ }
+ }
+
+ @Override
+ public Graph getComparisonGraph(Graph graph) {
+ return new EdgeListGraph(graph);
+ }
+
+ @Override
+ public String getDescription() {
+ return "BOSS-MB2 using " + this.score.getDescription();
+ }
+
+ @Override
+ public DataType getDataType() {
+ return this.score.getDataType();
+ }
+
+ @Override
+ public List getParameters() {
+ List params = new ArrayList<>();
+ params.add(Params.MB);
+
+ // Flags
+ params.add(Params.DEPTH);
+ params.add(Params.CACHE_SCORES);
+ params.add(Params.VERBOSE);
+
+ return params;
+ }
+
+ @Override
+ public Knowledge getKnowledge() {
+ return this.knowledge;
+ }
+
+ @Override
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
+ }
+
+ @Override
+ public ScoreWrapper getScoreWrapper() {
+ return this.score;
+ }
+
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+ this.score = score;
+ }
+
+}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES.java
new file mode 100644
index 0000000000..aa32db3379
--- /dev/null
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES.java
@@ -0,0 +1,152 @@
+package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag;
+
+import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
+import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
+import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper;
+import edu.cmu.tetrad.annotation.AlgType;
+import edu.cmu.tetrad.annotation.Bootstrapping;
+import edu.cmu.tetrad.annotation.Experimental;
+import edu.cmu.tetrad.data.*;
+import edu.cmu.tetrad.graph.EdgeListGraph;
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.search.Bridges;
+import edu.cmu.tetrad.search.Score;
+import edu.cmu.tetrad.search.TimeSeriesUtils;
+import edu.cmu.tetrad.util.Parameters;
+import edu.cmu.tetrad.util.Params;
+import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
+
+import java.io.PrintStream;
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * FGES (the heuristic version).
+ *
+ * @author jdramsey
+ */
+//@edu.cmu.tetrad.annotation.Algorithm(
+// name = "BRIDGES",
+// command = "bridges",
+// algoType = AlgType.forbid_latent_common_causes
+//)
+//@Bootstrapping
+//@Experimental
+public class BRIDGES implements Algorithm, HasKnowledge, UsesScoreWrapper {
+
+ static final long serialVersionUID = 23L;
+
+ private ScoreWrapper score;
+ private Knowledge knowledge = new Knowledge();
+
+ public BRIDGES() {
+
+ }
+
+ public BRIDGES(ScoreWrapper score) {
+ this.score = score;
+ }
+
+ @Override
+ public Graph search(DataModel dataModel, Parameters parameters) {
+ if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
+ if (parameters.getInt(Params.TIME_LAG) > 0) {
+ DataSet dataSet = (DataSet) dataModel;
+ DataSet timeSeries = TimeSeriesUtils.createLagData(dataSet, parameters.getInt(Params.TIME_LAG));
+ if (dataSet.getName() != null) {
+ timeSeries.setName(dataSet.getName());
+ }
+ dataModel = timeSeries;
+ knowledge = timeSeries.getKnowledge();
+ }
+
+ Score score = this.score.getScore(dataModel, parameters);
+ Graph graph;
+
+ Bridges search
+ = new Bridges(score);
+ search.setKnowledge(this.knowledge);
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ search.setMeekVerbose(parameters.getBoolean(Params.MEEK_VERBOSE));
+ search.setMaxDegree(parameters.getInt(Params.MAX_DEGREE));
+ search.setSymmetricFirstStep(parameters.getBoolean(Params.SYMMETRIC_FIRST_STEP));
+ search.setFaithfulnessAssumed(parameters.getBoolean(Params.FAITHFULNESS_ASSUMED));
+ search.setParallelized(parameters.getBoolean(Params.PARALLELIZED));
+ search.setDepth(parameters.getInt(Params.DEPTH));
+
+ Object obj = parameters.get(Params.PRINT_STREAM);
+ if (obj instanceof PrintStream) {
+ search.setOut((PrintStream) obj);
+ }
+
+ graph = search.search();
+
+ return graph;
+ } else {
+ BRIDGES fges = new BRIDGES(this.score);
+
+ DataSet data = (DataSet) dataModel;
+ GeneralResamplingTest search = new GeneralResamplingTest(
+ data, fges, parameters.getInt(Params.NUMBER_RESAMPLING),
+ parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
+ parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
+ search.setKnowledge(this.knowledge);
+ search.setParameters(parameters);
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ return search.search();
+ }
+ }
+
+ @Override
+ public Graph getComparisonGraph(Graph graph) {
+ return new EdgeListGraph(graph);
+ }
+
+ @Override
+ public String getDescription() {
+ return "BRIDGES using " + this.score.getDescription();
+ }
+
+ @Override
+ public DataType getDataType() {
+ return this.score.getDataType();
+ }
+
+ @Override
+ public List getParameters() {
+ List parameters = new ArrayList<>();
+ parameters.add(Params.SYMMETRIC_FIRST_STEP);
+ parameters.add(Params.MAX_DEGREE);
+ parameters.add(Params.PARALLELIZED);
+ parameters.add(Params.FAITHFULNESS_ASSUMED);
+ parameters.add(Params.TIME_LAG);
+ parameters.add(Params.DEPTH);
+
+ parameters.add(Params.VERBOSE);
+ parameters.add(Params.MEEK_VERBOSE);
+
+ return parameters;
+ }
+
+ @Override
+ public Knowledge getKnowledge() {
+ return this.knowledge;
+ }
+
+ @Override
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
+ }
+
+ @Override
+ public ScoreWrapper getScoreWrapper() {
+ return this.score;
+ }
+
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+ this.score = score;
+ }
+
+}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES2.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES2.java
new file mode 100644
index 0000000000..5ea5bb1e8c
--- /dev/null
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES2.java
@@ -0,0 +1,145 @@
+package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag;
+
+import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
+import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
+import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
+import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper;
+import edu.cmu.tetrad.annotation.AlgType;
+import edu.cmu.tetrad.annotation.Bootstrapping;
+import edu.cmu.tetrad.annotation.Experimental;
+import edu.cmu.tetrad.data.*;
+import edu.cmu.tetrad.graph.EdgeListGraph;
+import edu.cmu.tetrad.graph.Graph;
+import edu.cmu.tetrad.search.Bridges2;
+import edu.cmu.tetrad.search.Score;
+import edu.cmu.tetrad.search.TimeSeriesUtils;
+import edu.cmu.tetrad.util.Parameters;
+import edu.cmu.tetrad.util.Params;
+import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
+
+import java.io.PrintStream;
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * FGES (the heuristic version).
+ *
+ * @author jdramsey
+ */
+//@edu.cmu.tetrad.annotation.Algorithm(
+// name = "BRIDGES2",
+// command = "bridges2",
+// algoType = AlgType.forbid_latent_common_causes
+//)
+//@Bootstrapping
+//@Experimental
+public class BRIDGES2 implements Algorithm, HasKnowledge, UsesScoreWrapper {
+
+ static final long serialVersionUID = 23L;
+
+ private ScoreWrapper score;
+ private Knowledge knowledge = new Knowledge();
+
+ public BRIDGES2() {
+
+ }
+
+ public BRIDGES2(ScoreWrapper score) {
+ this.score = score;
+ }
+
+ @Override
+ public Graph search(DataModel dataModel, Parameters parameters) {
+ if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
+ if (parameters.getInt(Params.TIME_LAG) > 0) {
+ DataSet dataSet = (DataSet) dataModel;
+ DataSet timeSeries = TimeSeriesUtils.createLagData(dataSet, parameters.getInt(Params.TIME_LAG));
+ if (dataSet.getName() != null) {
+ timeSeries.setName(dataSet.getName());
+ }
+ dataModel = timeSeries;
+ knowledge = timeSeries.getKnowledge();
+ }
+
+ Score score = this.score.getScore(dataModel, parameters);
+ Graph graph;
+
+ Bridges2 search = new Bridges2(score);
+ search.setKnowledge(this.knowledge);
+ search.setMaxDegree(parameters.getInt(Params.MAX_DEGREE));
+
+ Object obj = parameters.get(Params.PRINT_STREAM);
+ if (obj instanceof PrintStream) {
+ search.setOut((PrintStream) obj);
+ }
+
+ graph = search.search();
+
+ return graph;
+ } else {
+ BRIDGES2 fges = new BRIDGES2(this.score);
+
+ DataSet data = (DataSet) dataModel;
+ GeneralResamplingTest search = new GeneralResamplingTest(
+ data, fges, parameters.getInt(Params.NUMBER_RESAMPLING),
+ parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE),
+ parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
+ search.setKnowledge(this.knowledge);
+ search.setParameters(parameters);
+ search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ return search.search();
+ }
+ }
+
+ @Override
+ public Graph getComparisonGraph(Graph graph) {
+ return new EdgeListGraph(graph);
+ }
+
+ @Override
+ public String getDescription() {
+ return "BRIDGES using " + this.score.getDescription();
+ }
+
+ @Override
+ public DataType getDataType() {
+ return this.score.getDataType();
+ }
+
+ @Override
+ public List getParameters() {
+ List parameters = new ArrayList<>();
+ parameters.add(Params.SYMMETRIC_FIRST_STEP);
+ parameters.add(Params.MAX_DEGREE);
+ parameters.add(Params.PARALLELIZED);
+ parameters.add(Params.FAITHFULNESS_ASSUMED);
+ parameters.add(Params.TIME_LAG);
+ parameters.add(Params.DEPTH);
+
+ parameters.add(Params.VERBOSE);
+ parameters.add(Params.MEEK_VERBOSE);
+
+ return parameters;
+ }
+
+ @Override
+ public Knowledge getKnowledge() {
+ return this.knowledge;
+ }
+
+ @Override
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
+ }
+
+ @Override
+ public ScoreWrapper getScoreWrapper() {
+ return this.score;
+ }
+
+ @Override
+ public void setScoreWrapper(ScoreWrapper score) {
+ this.score = score;
+ }
+
+}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/rGES.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES_OLD.java
similarity index 68%
rename from tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/rGES.java
rename to tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES_OLD.java
index cdca1f0503..d6e980b477 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/rGES.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES_OLD.java
@@ -2,15 +2,17 @@
import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
+import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper;
import edu.cmu.tetrad.annotation.AlgType;
import edu.cmu.tetrad.annotation.Bootstrapping;
import edu.cmu.tetrad.annotation.Experimental;
import edu.cmu.tetrad.data.DataModel;
import edu.cmu.tetrad.data.DataType;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
-import edu.cmu.tetrad.search.Rges;
+import edu.cmu.tetrad.search.BridgesOld;
import edu.cmu.tetrad.search.Score;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.Params;
@@ -20,26 +22,29 @@
import java.util.List;
/**
- * rGES (experimental algorithm).
+ * BRIDGES (experimental algorithm).
*
* @author bryanandrews
*/
-@edu.cmu.tetrad.annotation.Algorithm(
- name = "rGES",
- command = "rges",
- algoType = AlgType.forbid_latent_common_causes
-)
-@Bootstrapping
-@Experimental
-public class rGES implements Algorithm, UsesScoreWrapper {
+//@edu.cmu.tetrad.annotation.Algorithm(
+// name = "BRIDGES_OLD",
+// command = "bridges-old",
+// algoType = AlgType.forbid_latent_common_causes
+//)
+//@Bootstrapping
+//@Experimental
+public class BRIDGES_OLD implements Algorithm, HasKnowledge, UsesScoreWrapper {
static final long serialVersionUID = 23L;
private ScoreWrapper score;
- public rGES() {}
+ private Knowledge knowledge = new Knowledge();
- public rGES(ScoreWrapper score) {
+
+ public BRIDGES_OLD() {}
+
+ public BRIDGES_OLD(ScoreWrapper score) {
this.score = score;
}
@@ -49,8 +54,10 @@ public Graph search(DataModel dataModel, Parameters parameters) {
Score score = this.score.getScore(dataModel, parameters);
Graph graph;
- Rges search = new Rges(score);
- search.setVerbose(parameters.getBoolean(Params.VERBOSE));
+ BridgesOld search = new BridgesOld(score);
+// search.setKnowledge(knowledge);
+ search.setVerbose(false);
+// search.setVerbose(parameters.getBoolean(Params.VERBOSE));
search.setMaxDegree(parameters.getInt(Params.MAX_DEGREE));
search.setSymmetricFirstStep(parameters.getBoolean(Params.SYMMETRIC_FIRST_STEP));
search.setFaithfulnessAssumed(parameters.getBoolean(Params.FAITHFULNESS_ASSUMED));
@@ -74,7 +81,7 @@ public Graph getComparisonGraph(Graph graph) {
@Override
public String getDescription() {
- return "rGES (r Greedy Equivalence Search) using " + this.score.getDescription();
+ return "BRIDGES_OLD (BRIDGES is not Restricted to Imaps During Greedy Equivalent Search) using " + this.score.getDescription();
}
@Override
@@ -104,4 +111,15 @@ public void setScoreWrapper(ScoreWrapper score) {
this.score = score;
}
+ @Override
+ public Knowledge getKnowledge() {
+ return this.knowledge;
+ }
+
+ @Override
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
+ }
+
+
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CPC.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CPC.java
index a2cf005949..6fd3bfb93f 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CPC.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CPC.java
@@ -34,7 +34,7 @@ public class CPC implements Algorithm, HasKnowledge, TakesIndependenceWrapper {
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public CPC() {
}
@@ -145,13 +145,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CpcStable.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CpcStable.java
index 87b9f68414..af3a64c634 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CpcStable.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CpcStable.java
@@ -28,7 +28,7 @@ public class CpcStable implements Algorithm, HasKnowledge, TakesIndependenceWrap
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
private Algorithm algorithm;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public CpcStable() {
}
@@ -93,13 +93,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FAS.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FAS.java
index bcedfd0d40..241beb50d1 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FAS.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FAS.java
@@ -34,7 +34,7 @@ public class FAS implements Algorithm, HasKnowledge, TakesIndependenceWrapper {
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public FAS() {
}
@@ -98,13 +98,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Fges.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Fges.java
index 9eac885510..bac789e847 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Fges.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Fges.java
@@ -35,7 +35,7 @@ public class Fges implements Algorithm, HasKnowledge, UsesScoreWrapper {
static final long serialVersionUID = 23L;
private ScoreWrapper score;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public Fges() {
@@ -125,13 +125,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
@@ -144,4 +144,4 @@ public void setScoreWrapper(ScoreWrapper score) {
this.score = score;
}
-}
+}
\ No newline at end of file
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMb.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMb.java
index 2994e8c1f7..1ea423191a 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMb.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMb.java
@@ -36,7 +36,7 @@ public class FgesMb implements Algorithm, HasKnowledge, UsesScoreWrapper {
static final long serialVersionUID = 23L;
private ScoreWrapper score;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
private String targetName;
public FgesMb() {
@@ -105,13 +105,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMeasurement.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMeasurement.java
index e199684593..7f3c5b0c96 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMeasurement.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMeasurement.java
@@ -28,7 +28,7 @@ public class FgesMeasurement implements Algorithm, HasKnowledge {
static final long serialVersionUID = 23L;
private final ScoreWrapper score;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public FgesMeasurement(ScoreWrapper score) {
this.score = score;
@@ -104,13 +104,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSP.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSP.java
index b68dac29d7..1fa2a94dfe 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSP.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSP.java
@@ -38,7 +38,7 @@ public class GRaSP implements Algorithm, UsesScoreWrapper, TakesIndependenceWrap
static final long serialVersionUID = 23L;
private ScoreWrapper score;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public GRaSP() {
// Used in reflection; do not delete.
@@ -73,7 +73,7 @@ public Graph search(DataModel dataModel, Parameters parameters) {
grasp.setNonSingularDepth(parameters.getInt(Params.GRASP_NONSINGULAR_DEPTH));
grasp.setOrdered(parameters.getBoolean(Params.GRASP_ORDERED_ALG));
grasp.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE));
- grasp.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL));
+ grasp.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_RASKUTTI_UHLER));
grasp.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER));
grasp.setVerbose(parameters.getBoolean(Params.VERBOSE));
grasp.setCacheScores(parameters.getBoolean(Params.CACHE_SCORES));
@@ -121,7 +121,7 @@ public List getParameters() {
params.add(Params.GRASP_SINGULAR_DEPTH);
params.add(Params.GRASP_NONSINGULAR_DEPTH);
params.add(Params.GRASP_ORDERED_ALG);
- params.add(Params.GRASP_USE_VERMA_PEARL);
+ params.add(Params.GRASP_USE_RASKUTTI_UHLER);
params.add(Params.GRASP_USE_DATA_ORDER);
params.add(Params.CACHE_SCORES);
params.add(Params.TIME_LAG);
@@ -154,12 +154,12 @@ public void setIndependenceWrapper(IndependenceWrapper independenceWrapper) {
}
@Override
- public IKnowledge getKnowledge() {
- return this.knowledge.copy();
+ public Knowledge getKnowledge() {
+ return new Knowledge((Knowledge) knowledge);
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge.copy();
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSPTol.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSPTol.java
index 98e5a26ddd..76af4772a3 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSPTol.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSPTol.java
@@ -37,7 +37,7 @@ public class GRaSPTol implements Algorithm, UsesScoreWrapper, TakesIndependenceW
static final long serialVersionUID = 23L;
private ScoreWrapper score;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public GRaSPTol() {
// Used in reflection; do not delete.
@@ -72,7 +72,7 @@ public Graph search(DataModel dataModel, Parameters parameters) {
grasp.setNonSingularDepth(parameters.getInt(Params.GRASP_NONSINGULAR_DEPTH));
grasp.setOrdered(parameters.getBoolean(Params.GRASP_ORDERED_ALG));
grasp.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE));
- grasp.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL));
+ grasp.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_RASKUTTI_UHLER));
grasp.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER));
grasp.setToleranceDepth(parameters.getInt(Params.GRASP_TOLERANCE_DEPTH));
grasp.setAllowRandomnessInsideAlgorithm(parameters.getBoolean(Params.GRASP_ALLOW_RANDOMNESS_INSIDE_ALGORITHM));
@@ -104,7 +104,7 @@ public Graph getComparisonGraph(Graph graph) {
@Override
public String getDescription() {
- return "GRaSP (Greedy Relaxed Sparsest Permutation) using " + this.test.getDescription()
+ return "GRaSPTol (Greedy Relaxed Sparsest Permutation Tolerance) using " + this.test.getDescription()
+ " or " + this.score.getDescription();
}
@@ -124,7 +124,7 @@ public List getParameters() {
params.add(Params.GRASP_TOLERANCE_DEPTH);
params.add(Params.GRASP_ORDERED_ALG);
// params.add(Params.GRASP_USE_SCORE);
- params.add(Params.GRASP_USE_VERMA_PEARL);
+ params.add(Params.GRASP_USE_RASKUTTI_UHLER);
params.add(Params.GRASP_USE_DATA_ORDER);
params.add(Params.GRASP_ALLOW_RANDOMNESS_INSIDE_ALGORITHM);
params.add(Params.CACHE_SCORES);
@@ -158,12 +158,12 @@ public void setIndependenceWrapper(IndependenceWrapper independenceWrapper) {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge.copy();
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge.copy();
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GesMe.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GesMe.java
index 396f879f5c..71ba828462 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GesMe.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GesMe.java
@@ -117,7 +117,7 @@ public Graph search(DataModel dataSet, Parameters parameters) {
leaves.add(nodes.get(indices.get(i)));
}
- IKnowledge knowledge2 = new Knowledge2();
+ Knowledge knowledge2 = new Knowledge();
for (Node v : nodes) {
if (leaves.contains(v)) {
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC.java
index 5223d21f71..8785942255 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC.java
@@ -34,7 +34,7 @@ public class PC implements Algorithm, HasKnowledge, TakesIndependenceWrapper {
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public PC() {
}
@@ -146,13 +146,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PCMAX.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PCMAX.java
index a9025143e6..b22dae777c 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PCMAX.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PCMAX.java
@@ -34,7 +34,7 @@ public class PCMAX implements Algorithm, HasKnowledge, TakesIndependenceWrapper
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public PCMAX() {
}
@@ -147,13 +147,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/MBFS.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC_MB.java
similarity index 65%
rename from tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/MBFS.java
rename to tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC_MB.java
index ae246fb7e4..c10bffc161 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/MBFS.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC_MB.java
@@ -12,9 +12,11 @@
import edu.cmu.tetrad.graph.GraphUtils;
import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetrad.search.IndependenceTest;
+import edu.cmu.tetrad.search.PcMb;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.Params;
import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
+import org.jetbrains.annotations.NotNull;
import java.util.ArrayList;
import java.util.List;
@@ -25,22 +27,22 @@
* @author jdramsey
*/
@edu.cmu.tetrad.annotation.Algorithm(
- name = "MBFS",
- command = "mbfs",
+ name = "PC-MB",
+ command = "pc-mb",
algoType = AlgType.search_for_Markov_blankets
)
@Bootstrapping
-public class MBFS implements Algorithm, HasKnowledge, TakesIndependenceWrapper {
+public class PC_MB implements Algorithm, HasKnowledge, TakesIndependenceWrapper {
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
- private String targetName;
+ private Knowledge knowledge = new Knowledge();
+ private List targets;
- public MBFS() {
+ public PC_MB() {
}
- public MBFS(IndependenceWrapper type) {
+ public PC_MB(IndependenceWrapper type) {
this.test = type;
}
@@ -48,24 +50,15 @@ public MBFS(IndependenceWrapper type) {
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) {
IndependenceTest test = this.test.getTest(dataSet, parameters);
- edu.cmu.tetrad.search.Mbfs search = new edu.cmu.tetrad.search.Mbfs(test, parameters.getInt(Params.DEPTH));
-
+ PcMb search = new PcMb(test, parameters.getInt(Params.DEPTH));
+ List targets = targets(test, parameters.getString(Params.TARGETS));
+ this.targets = targets;
search.setDepth(parameters.getInt(Params.DEPTH));
search.setKnowledge(this.knowledge);
-
- this.targetName = parameters.getString(Params.TARGET_NAME);
- if (this.targetName.isEmpty()) {
- throw new IllegalArgumentException("Target variable name needs to be provided.");
- }
-
- if (test.getVariable(this.targetName) == null) {
- throw new IllegalArgumentException("Target variable name '" + this.targetName + "' not found in dataset.");
- }
-
- Node target = test.getVariable(this.targetName);
- return search.search(target.getName());
+ search.setFindMb(parameters.getBoolean(Params.MB));
+ return search.search(targets);
} else {
- MBFS algorithm = new MBFS(this.test);
+ PC_MB algorithm = new PC_MB(this.test);
DataSet data = (DataSet) dataSet;
GeneralResamplingTest search = new GeneralResamplingTest(data, algorithm, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
@@ -77,15 +70,26 @@ public Graph search(DataModel dataSet, Parameters parameters) {
}
}
+ @NotNull
+ private List targets(IndependenceTest test, String targetString) {
+ String[] tokens = targetString.split(",");
+ List targets = new ArrayList<>();
+
+ for (String t : tokens) {
+ String name = t.trim();
+ targets.add(test.getVariable(name));
+ }
+ return targets;
+ }
+
@Override
public Graph getComparisonGraph(Graph graph) {
- Node target = graph.getNode(this.targetName);
- return GraphUtils.markovBlanketDag(target, new EdgeListGraph(graph));
+ return GraphUtils.markovBlanketDag(targets.get(0), new EdgeListGraph(graph));
}
@Override
public String getDescription() {
- return "MBFS (Markov Blanket Fan Search) using " + this.test.getDescription();
+ return "PC-MB (Markov blanket search using PC) using " + this.test.getDescription();
}
@Override
@@ -96,21 +100,22 @@ public DataType getDataType() {
@Override
public List getParameters() {
List parameters = new ArrayList<>();
+ parameters.add(Params.TARGETS);
+ parameters.add(Params.MB);
parameters.add(Params.DEPTH);
- parameters.add(Params.TARGET_NAME);
parameters.add(Params.VERBOSE);
return parameters;
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcAll.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcAll.java
index 67e77955fe..122593ac79 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcAll.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcAll.java
@@ -34,7 +34,7 @@ public class PcAll implements Algorithm, HasKnowledge, TakesIndependenceWrapper
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public PcAll() {
}
@@ -147,13 +147,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcStable.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcStable.java
index 0e779cc049..be8c1ec2f9 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcStable.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcStable.java
@@ -27,7 +27,7 @@ public class PcStable implements Algorithm, HasKnowledge, TakesIndependenceWrapp
static final long serialVersionUID = 23L;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public PcStable() {
}
@@ -87,13 +87,13 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
@Override
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Pcd.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Pcd.java
index 6ac4bbf536..8abc4cd458 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Pcd.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Pcd.java
@@ -23,7 +23,7 @@
@Bootstrapping
public class Pcd implements Algorithm, HasKnowledge {
static final long serialVersionUID = 23L;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
public Pcd() {
}
@@ -93,12 +93,12 @@ public List getParameters() {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge;
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge;
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSSTuck.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SIMPLE_DEMO_GA.java
similarity index 69%
rename from tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSSTuck.java
rename to tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SIMPLE_DEMO_GA.java
index 79763214bc..d6a1cda905 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSSTuck.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SIMPLE_DEMO_GA.java
@@ -6,9 +6,6 @@
import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.algcomparison.utils.TakesIndependenceWrapper;
import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper;
-import edu.cmu.tetrad.annotation.AlgType;
-import edu.cmu.tetrad.annotation.Bootstrapping;
-import edu.cmu.tetrad.annotation.Experimental;
import edu.cmu.tetrad.data.*;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
@@ -26,24 +23,24 @@
* @author bryanandrews
* @author josephramsey
*/
-@edu.cmu.tetrad.annotation.Algorithm(
- name = "BOSSTuck",
- command = "boss-tuck",
- algoType = AlgType.forbid_latent_common_causes
-)
-@Bootstrapping
-@Experimental
-public class BOSSTuck implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapper, HasKnowledge {
+//@edu.cmu.tetrad.annotation.Algorithm(
+// name = "SIMPLE_DEMO_GA",
+// command = "simple-demo-ga",
+// algoType = AlgType.forbid_latent_common_causes
+//)
+//@Bootstrapping
+//@Experimental
+public class SIMPLE_DEMO_GA implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapper, HasKnowledge {
static final long serialVersionUID = 23L;
private ScoreWrapper score;
private IndependenceWrapper test;
- private IKnowledge knowledge = new Knowledge2();
+ private Knowledge knowledge = new Knowledge();
- public BOSSTuck() {
+ public SIMPLE_DEMO_GA() {
// Used in reflection; do not delete.
}
- public BOSSTuck(ScoreWrapper score, IndependenceWrapper test) {
+ public SIMPLE_DEMO_GA(ScoreWrapper score, IndependenceWrapper test) {
this.score = score;
this.test = test;
}
@@ -65,21 +62,10 @@ public Graph search(DataModel dataModel, Parameters parameters) {
IndependenceTest test = this.test.getTest(dataModel, parameters);
test.setVerbose(parameters.getBoolean(Params.VERBOSE));
- BossTuck boss = new BossTuck(test, score);
-
- boss.setDepth(parameters.getInt(Params.GRASP_DEPTH));
- boss.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE));
- boss.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL));
- boss.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER));
- boss.setVerbose(parameters.getBoolean(Params.VERBOSE));
- boss.setCacheScores(parameters.getBoolean(Params.CACHE_SCORES));
-
- boss.setNumStarts(parameters.getInt(Params.NUM_STARTS));
- boss.setKnowledge(this.knowledge);
- boss.bestOrder(score.getVariables());
- return boss.getGraph(parameters.getBoolean(Params.OUTPUT_CPDAG));
+ SimpleDemoGA boss = new SimpleDemoGA(score, 10);
+ return boss.search();
} else {
- BOSSTuck algorithm = new BOSSTuck(this.score, this.test);
+ SIMPLE_DEMO_GA algorithm = new SIMPLE_DEMO_GA(this.score, this.test);
DataSet data = (DataSet) dataModel;
GeneralResamplingTest search = new GeneralResamplingTest(data, algorithm, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
@@ -99,7 +85,7 @@ public Graph getComparisonGraph(Graph graph) {
@Override
public String getDescription() {
- return "BOSS-tuck (Better Order Score Search) using " + this.test.getDescription()
+ return "SIMPLE_DEMO_GA using " + this.test.getDescription()
+ " or " + this.score.getDescription();
}
@@ -115,8 +101,9 @@ public List getParameters() {
// Flags
params.add(Params.GRASP_DEPTH);
params.add(Params.GRASP_USE_SCORE);
- params.add(Params.GRASP_USE_VERMA_PEARL);
+ params.add(Params.GRASP_USE_RASKUTTI_UHLER);
params.add(Params.GRASP_USE_DATA_ORDER);
+ params.add(Params.CACHE_SCORES);
params.add(Params.VERBOSE);
// Parameters
@@ -146,12 +133,12 @@ public void setIndependenceWrapper(IndependenceWrapper independenceWrapper) {
}
@Override
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return this.knowledge.copy();
}
@Override
- public void setKnowledge(IKnowledge knowledge) {
- this.knowledge = knowledge.copy();
+ public void setKnowledge(Knowledge knowledge) {
+ this.knowledge = new Knowledge((Knowledge) knowledge);
}
}
diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SP.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SP.java
index 39c9997343..9d9ec7dd70 100644
--- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SP.java
+++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SP.java
@@ -3,6 +3,7 @@
import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
import edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper;
import edu.cmu.tetrad.algcomparison.score.ScoreWrapper;
+import edu.cmu.tetrad.algcomparison.utils.HasKnowledge;
import edu.cmu.tetrad.algcomparison.utils.TakesIndependenceWrapper;
import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper;
import edu.cmu.tetrad.annotation.AlgType;
@@ -10,12 +11,12 @@
import edu.cmu.tetrad.data.DataModel;
import edu.cmu.tetrad.data.DataSet;
import edu.cmu.tetrad.data.DataType;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.EdgeListGraph;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.search.IndependenceTest;
import edu.cmu.tetrad.search.OtherPermAlgs;
import edu.cmu.tetrad.search.Score;
-import edu.cmu.tetrad.sem.Parameter;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.Params;
import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest;
@@ -34,18 +35,20 @@
algoType = AlgType.forbid_latent_common_causes
)
@Bootstrapping
-public class SP implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapper {
+public class SP implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapper, HasKnowledge {
static final long serialVersionUID = 23L;
private ScoreWrapper score = null;
private IndependenceWrapper test;
+ private Knowledge knowledge = new Knowledge();
+
public SP() {
// Used in reflection; do not delete.
}
- public SP(ScoreWrapper score, IndependenceWrapper test) {
- this.score = score;
+ public SP(IndependenceWrapper test, ScoreWrapper score) {
this.test = test;
+ this.score = score;
}
@Override
@@ -57,20 +60,12 @@ public Graph search(DataModel dataModel, Parameters parameters) {
test.setVerbose(parameters.getBoolean(Params.VERBOSE));
- OtherPermAlgs otherPermAlgs;
-
- otherPermAlgs = new OtherPermAlgs(test, score);
-
- OtherPermAlgs.Method method = OtherPermAlgs.Method.SP;
-
- otherPermAlgs.setMethod(method);
- otherPermAlgs.setUsePearl(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL));
- otherPermAlgs.setVerbose(parameters.getBoolean(Params.VERBOSE));
-
- otherPermAlgs.bestOrder(score.getVariables());
- return otherPermAlgs.getGraph(true);
+ edu.cmu.tetrad.search.SP sp = new edu.cmu.tetrad.search.SP(test, score);
+ sp.setKnowledge(knowledge);
+ sp.bestOrder(score.getVariables());
+ return sp.getGraph(true);
} else {
- GRaSP algorithm = new GRaSP(this.score, this.test);
+ SP algorithm = new SP(this.test, this.score);
DataSet data = (DataSet) dataModel;
GeneralResamplingTest search = new GeneralResamplingTest(data, algorithm, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET));
@@ -99,7 +94,7 @@ public DataType getDataType() {
@Override
public List
Adjusts the discrete BDeu variable score of FGES so allow for - multiple datasets as input. The BDeu scores for each data set are - averaged at each step of the algorithm, producing a model for all - data sets that assumes they have the same graphical structure across - dataset. Note that in order to use this algorithm in a nontrivial - way, one needs to have loaded or simulated multiple dataset.
+ + + + + + -Adjusts the continuous variable score (SEM BIC) of FGES so +
Adjusts the selected score for FGES so allow for multiple datasets as input. The linear, Gaussian BIC scores for each data set are averaged at each step of the algorithm, producing a model for all data sets that assumes they have the same @@ -2893,7 +2894,7 @@
Description
Input Assumptions
-A set of continuous datasets with the same variables and sample +
A set of datasets consistent with the chosen score with the same variables and sample sizes.
Output Format
@@ -3030,52 +3031,52 @@Parameters
href="#completeRuleSetUsed">completeRuleSetUsed -The RFCI-BSC Algorithm
+ -Description
+ -RFCI-BSC is a combination of the RFCI [Colombo, 2012] - algorithm and the Bayesian Scoring of Constraints (BSC) method - [Jabbari, 2017] that can generate and probabilistically score - multiple models, outputting the most probable one. This search - algorithm is a hybrid method that derives a Bayesian probability that - the set of independence tests associated with a given causal model - are jointly correct. Using this constraint-based scoring method, we - are able to score multiple causal models, which possibly contain - latent variables, and output the most probable one. See [Jabbari, - 2017].
+ + + + + + + + + + -Currently, this algorithm can only be accessed if experimental - algorithms are activated. One may do so by going to the - File menu, selecting Settings, and then making sure the - 'Experimental' checkbox is checked.
+ + + + -Input Assumptions
+ -The data are discrete only.
+ -Output Format
+ -A partial ancestral graph (PAG). See Spirtes et al., 2000.
+ -Parameters
+ -All of the parameters from RFCI are available for RFCI-BSC. - Additionally:
+ + -numRandomizedSearchModels, thresholdNoRandomDataSearch, cutoffDataSearch, thresholdNoRandomConstrainSearch - , cutoffConstrainSearch, numBscBootstrapSamples, lowerBound, upperBound, - outputRBD
+ + + + + + + + +The GFCI Algorithm
@@ -3370,13 +3371,13 @@Parameters
-The MBFS Algorithm
+The PC-MB Algorithm
Description
-Markov blanket fan search. Similar to FGES-MB (see FGES, +
PC-MB. Similar to FGES-MB (see FGES, 2016) but using PC as the basic search instead of FGES. The rules of the PC search are restricted to just the variables in the Markov blanket of a target T, including T; the result is a graph that is a @@ -4353,7 +4354,7 @@
Parameters
Search Parameters
Note: You must specify the "Value Type" of each parameter, and - the value type must be one of the following: Integer, Double, String, + the value type must be one of the following: Integer, Long, Double, String, Boolean.
@@ -4598,13 +4599,13 @@coefLow
id="completeRuleSetUsed_short_desc"> Yes if the complete FCI rule set should be useddoDiscriminatingPathRule
+-
+
- Short Description: Yes if the discriminating path rule + should be done, No if not +
- Long Description: Yes if the discriminating path + FCI rule (part of the final orientation, requiring an additional test) + should be done, No if not + +
- Default Value: true +
- Lower + Bound: +
- Upper Bound: +
- Value Type: + Boolean +
doDiscriminatingPathColliderRule
+-
+
- Short Description: Yes if the discriminating path collider rule + should be done, No if not +
- Long Description: Yes if the discriminating path collider + FCI rule (part of the final orientation, requiring an additional test) + should be done, No if not + +
- Default Value: false +
- Lower + Bound: +
- Upper Bound: +
- Value Type: + Boolean +
doDiscriminatingPathTailRule
+-
+
- Short Description: Yes if the discriminating path tail rule + should be done, No if not +
- Long Description: Yes if the discriminating path tail + FCI rule (part of the final orientation, requiring an additional test) + should be done, No if not + +
- Default Value: true +
- Lower + Bound: +
- Upper Bound: +
- Value Type: + Boolean +
concurrentFAS
- cstarQ
targetNames
--
-
- Short Description: Target names
+ id="targets">targets
+
-
+
- Short Description: Target names (comma separated)
- Long Description: Target names (comma separated). + id="targets_long_desc">Target names (comma separated).
- Default Value: + id="targets_default_value">
- Lower Bound: + id="targets_lower_bound">
- Upper Bound: + id="targets_upper_bound">
- Value Type: String + id="targets_value_type">String
depth
Boolean +mb
+-
+
- Short Description: Find Markov blanket(s) +
- Long Description: Looks for the graph over the Markov blanket(s) and target(s) if true + +
- Default Value: false +
- Lower Bound: +
- Upper Bound: +
- Value Type: Boolean +
discretize
- Short Description: fastIcaA id="generalSemParameterTemplate_value_type">String
imagesMetaAlg
+-
+
- Short Description: IMaGES "meta" algorithm. 1 = FGES, 2 = BOSS-Tuck +
- Long + Description: Sets the meta algorithm to be optimized using the IMaGES (average BIC) score. + +
- Default Value: + 1 +
- Lower Bound: 1 +
- Upper Bound: 5 +
- Value Type: Integer +
ia
-
@@ -6025,24 +6127,16 @@
maxDegree
IntegerzsMaxIndegree
--
-
- Short Description: Maximum indegree of true graph (min = - 0) -
- Long Description: This is the maximum number of parents - one expects any node to have in the true model. -
- Default Value: 4 -
- Lower Bound: 0 -
- Upper Bound: 2147483647 -
- Value Type: - Integer +
- Short Description: Maximum indegree of true graph (min = 0) + +
- Long Description: This is the maximum number of parents one expects any node to have in the true model. + +
- Default Value: 4 +
- Lower Bound: 0 +
- Upper Bound: 2147483647 +
- Value Type: Integer
zsMaxIndegree
+-
+
numStarts
bossScoreType
+ id="bossAlg">bossAlg- Short Description: Yes if edge count of the model should - be minimized, No if BIC should be maximized + id="bossAlg_short_desc">Picks the BOSS algorithm type, BOSS1 or BOSS2
- Long - Description: If Yes, the number - of edges in the model will be minimized, following Raskutti and Uhler - 2018. If second, the supplied score of the model (preferably a BIC - score) will be optimized, a suggestion made in Solus et al. 2017. + Description: 1 = BOSS1, 2 = BOSS2, 3 = BOSS3
- Default Value: false + id="bossAlg_default_value">1
- Lower Bound: - + 1
- Upper Bound: - + 3
- Value Type: - Boolean + Integer
numStarts
graspUseVermaPearl
+ id="graspUseRaskuttiUhler">graspUseRaskuttiUhler- Short Description: Yes to use Raskutti and Uhler's + id="graspUseRaskuttiUhler_short_desc"> Yes to use Raskutti and Uhler's DAG-building method (test), No to use Grow-Shrink (score). -
- Long Description:
+
- Long Description: Raskutti and Uhler's method adds and edge X->Y if Y ~_||_ X | Prefix(Y, pi) \ {X}. Grow-Shrink adds an edge X->Y if X is in the Markov blanket of Y where the variable set is restricted to Prefix(Y, pi).
- Default Value: false
+ id="graspUseRaskuttiUhler_default_value">false - Lower - Bound: + Bound:
- Upper Bound: + id="graspUseRaskuttiUhler_upper_bound">
- Value Type: - Boolean + Boolean
precomputeCovarianc
id="penaltyDiscount_value_type">Double
+ zSRiskBound
+
+ - Short Description: Risk bound
+ - Long Description:
+ This is the probability of getting the true model if a correct model is discovered. Could underfit.
+
+ - Default Value: 0.001
+ - Lower Bound: 0
+ - Upper Bound: 1
+ - Value Type: Double
+
+
ebicGamma
- Short Description: ebicGamma
id="trueErrorVariance_value_type">Double
- zSRiskBound
--
-
- Short Description: Risk bound -
- Long - Description: This is the - probability of getting the true model if a correct model is - discovered. Could underfit. -
- Default Value: 0.001 -
- Lower Bound: - 0 -
- Upper Bound: - 1 -
- Value Type: - Double -
correlationThreshold
- ebicGamma
class="parameter_description_list">
- Short Description: The percentage of resample size - (min = 0.1) + (min = 10%)
- Long Description: This parameter specifies the
percentage of records in the bootstrap (as a percentage of the total
@@ -7318,9 +7400,9 @@
ebicGamma
id="percentResampleSize_default_value">90 - Lower Bound: -2147483648 + id="percentResampleSize_lower_bound">10
- Upper Bound: 2147483647 + id="percentResampleSize_upper_bound">100
- Value Type: Integer
sampleSize
Type: Integer +seed
+-
+
- Short Description: Seed for pseudorandom number generator (min = -1) +
- Long Description: The seed is the initial value of the + internal state of the pseudorandom number generator. +
- Default Value: -1 +
- Lower Bound: + -1 +
- Upper + Bound: 9223372036854775807 +
- Value Type: Long +
selfLoopCoef
- semGicRule
Type: Double
poissonLambda
+-
+
- Short Description: Lambda parameter for the Poisson distribution + (> 0) +
- Long Description: Lambda parameter for the Poisson distribution +
- Default Value: 1 +
- Lower + Bound: 1e-10 +
- Upper Bound: Infinity +
- Value + Type: Double +
skipNumRecords
- Trek
ga('send', 'pageview')
+
+
+
diff --git a/pom.xml b/pom.xml
index 18d3a66cad..786df39e46 100644
--- a/pom.xml
+++ b/pom.xml
@@ -4,7 +4,7 @@
- PAG (Partial Ancestral Graph) algorithm. This is the class of equivalence
classes of graphs one obtains if one assumes latent common causes (as above)
diff --git a/tetrad-gui/src/main/resources/resources/javahelp/manual/graph_edge_types.html b/tetrad-gui/src/main/resources/resources/javahelp/manual/graph_edge_types.html
index 321f753c76..f797bf4995 100644
--- a/tetrad-gui/src/main/resources/resources/javahelp/manual/graph_edge_types.html
+++ b/tetrad-gui/src/main/resources/resources/javahelp/manual/graph_edge_types.html
@@ -68,12 +68,12 @@
Graph Edge Types
- If an edge is green that means there is no latent - confounder. Otherwise, there is possibly latent confounder. + If an edge is solid, that means there is no latent + confounder (i.e., is visible). If dashed, there is possibly latent confounder. - diff --git a/tetrad-lib/pom.xml b/tetrad-lib/pom.xml index 2b1f634b8a..8677159f35 100644 --- a/tetrad-lib/pom.xml +++ b/tetrad-lib/pom.xml @@ -6,7 +6,7 @@If an edge is bold (thickened) that means it is + If an edge is thickened that means it is definitely direct. Otherwise, it is possibly direct. io.github.cmu-phil tetrad -7.1.2-2 +7.1.3-1 tetrad-lib @@ -115,7 +115,7 @@org.json json -20220320 +20220924 org.jsoup jsoup -1.14.3 +1.15.3 algorithmSimul } } - for (AlgorithmTask task : tasks) { - task.compute(); + if (parallelized) { + int parallelism = ForkJoinPool.getCommonPoolParallelism() + 10; + ForkJoinPool pool = (ForkJoinPool) Executors.newWorkStealingPool(parallelism); + pool.invokeAll(tasks); + pool.shutdown(); + } else { + for (AlgorithmTask task : tasks) { + task.call(); + } } return allStats; @@ -1024,7 +1060,7 @@ public void setComparisonGraph(ComparisonGraph comparisonGraph) { this.comparisonGraph = comparisonGraph; } - private class AlgorithmTask extends RecursiveTask { + private class AlgorithmTask implements Callable { private final List algorithmSimulationWrappers; private final List algorithmWrappers; @@ -1049,7 +1085,7 @@ public AlgorithmTask(List algorithmSimulationWrapper } @Override - protected Boolean compute() { + public Boolean call() { doRun(this.algorithmSimulationWrappers, this.algorithmWrappers, this.simulationWrappers, this.statistics, this.numGraphTypes, this.allStats, this.run, this.stdout); return true; @@ -1198,7 +1234,7 @@ private void doRun(List algorithmSimulationWrappers, } else if (this.comparisonGraph == ComparisonGraph.CPDAG_of_the_true_DAG) { comparisonGraph = SearchGraphUtils.cpdagForDag(new EdgeListGraph(trueGraph)); } else if (this.comparisonGraph == ComparisonGraph.PAG_of_the_true_DAG) { - comparisonGraph = new DagToPag(new EdgeListGraph(trueGraph)).convert(); + comparisonGraph = dagToPag(new EdgeListGraph(trueGraph)); } else { throw new IllegalArgumentException("Unrecognized graph type."); } @@ -1296,7 +1332,7 @@ private void saveGraph(String resultsPath, Graph graph, int i, int simIndex, } private enum Mode { - Average, StandardDeviation, WorstCase, MedianCase + Average, StandardDeviation, MinValue, MaxValue, MedianValue } private String getHeader(int u) { @@ -1375,11 +1411,13 @@ private double[][][] calcStatTables(double[][][][] allStats, Mode mode, int numT } else if (mode == Mode.Average) { double mean = StatUtils.mean(allStats[u][i][j]); statTables[u][i][j] = mean; - } else if (mode == Mode.WorstCase) { + } else if (mode == Mode.MinValue) { statTables[u][i][j] = StatUtils.min(allStats[u][i][j]); + } else if (mode == Mode.MaxValue) { + statTables[u][i][j] = StatUtils.max(allStats[u][i][j]); } else if (mode == Mode.StandardDeviation) { statTables[u][i][j] = StatUtils.sd(allStats[u][i][j]); - } else if (mode == Mode.MedianCase) { + } else if (mode == Mode.MedianValue) { statTables[u][i][j] = StatUtils.median(allStats[u][i][j]); } else { throw new IllegalStateException(); @@ -1398,13 +1436,15 @@ private void printStats(double[][][] statTables, Statistics statistics, Mode mod Parameters parameters) { if (mode == Mode.Average) { - this.out.println("AVERAGE STATISTICS"); + this.out.println("AVERAGE VALUE"); } else if (mode == Mode.StandardDeviation) { - this.out.println("STANDARD DEVIATIONS"); - } else if (mode == Mode.WorstCase) { - this.out.println("WORST CASE"); - } else if (mode == Mode.MedianCase) { - this.out.println("MEDIAN CASE"); + this.out.println("STANDARD DEVIATION"); + } else if (mode == Mode.MinValue) { + this.out.println("MIN VALUE"); + } else if (mode == Mode.MaxValue) { + this.out.println("MAX VALUE"); + } else if (mode == Mode.MedianValue) { + this.out.println("MEDIAN VALUE"); } else { throw new IllegalStateException(); } @@ -1427,7 +1467,7 @@ private void printStats(double[][][] statTables, Statistics statistics, Mode mod + (isShowUtilities() ? 1 : 0); TextTable table = new TextTable(rows, cols); - table.setTabDelimited(isTabDelimitedTables()); + table.setDelimiter(isTabDelimitedTables() ? TextTable.Delimiter.TAB : TextTable.Delimiter.JUSTIFIED); int initialColumn = 0; @@ -1763,12 +1803,14 @@ public SimulationWrapper(Simulation simulation, Parameters parameters) { @Override public void createData(Parameters parameters, boolean newModel) { - this.simulation.createData(parameters, newModel); - this.graphs = new ArrayList<>(); - this.dataModels = new ArrayList<>(); - for (int i = 0; i < this.simulation.getNumDataModels(); i++) { - this.graphs.add(this.simulation.getTrueGraph(i)); - this.dataModels.add(this.simulation.getDataModel(i)); + if (newModel) { + this.simulation.createData(parameters, newModel); + this.graphs = new ArrayList<>(); + this.dataModels = new ArrayList<>(); + for (int i = 0; i < this.simulation.getNumDataModels(); i++) { + this.graphs.add(this.simulation.getTrueGraph(i)); + this.dataModels.add(this.simulation.getDataModel(i)); + } } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/TimeoutComparison.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/TimeoutComparison.java index 009c7665ba..63704b1131 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/TimeoutComparison.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/TimeoutComparison.java @@ -53,6 +53,8 @@ import java.util.*; import java.util.concurrent.*; +import static edu.cmu.tetrad.search.SearchGraphUtils.dagToPag; + /** * Nov 14, 2017 12:00:31 PM * @@ -511,7 +513,7 @@ public void saveToFiles(String dataPath, Simulation simulation, Parameters param if (isSavePags()) { File file4 = new File(dir4, "pag." + (j + 1) + ".txt"); - GraphUtils.saveGraph(new DagToPag(graph).convert(), file4, false); + GraphUtils.saveGraph(dagToPag(graph), file4, false); } } @@ -1147,7 +1149,7 @@ private void doRun(List algorithmSimulationWrappers, } else if (this.comparisonGraph == ComparisonGraph.CPDAG_of_the_true_DAG) { comparisonGraph = SearchGraphUtils.cpdagForDag(new EdgeListGraph(trueGraph)); } else if (this.comparisonGraph == ComparisonGraph.PAG_of_the_true_DAG) { - comparisonGraph = new DagToPag(new EdgeListGraph(trueGraph)).convert(); + comparisonGraph = dagToPag(new EdgeListGraph(trueGraph)); } else { throw new IllegalArgumentException("Unrecognized graph type."); } @@ -1368,7 +1370,7 @@ private void printStats(double[][][] statTables, Statistics statistics, Mode mod + (isShowUtilities() ? 1 : 0); TextTable table = new TextTable(rows, cols); - table.setTabDelimited(isTabDelimitedTables()); + table.setDelimiter(isTabDelimitedTables() ? TextTable.Delimiter.TAB : TextTable.Delimiter.JUSTIFIED); int initialColumn = 0; diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/MultiDataSetAlgorithm.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/MultiDataSetAlgorithm.java index ee058b01b9..0716945d70 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/MultiDataSetAlgorithm.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/MultiDataSetAlgorithm.java @@ -1,5 +1,6 @@ package edu.cmu.tetrad.algcomparison.algorithm; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; import edu.cmu.tetrad.data.DataModel; import edu.cmu.tetrad.graph.Graph; import edu.cmu.tetrad.util.Parameters; @@ -16,9 +17,11 @@ public interface MultiDataSetAlgorithm extends Algorithm { /** * Runs the search. * - * @param dataSet The data set to run to the search on. + * @param dataSets The data set to run to the search on. * @param parameters The paramters of the search. * @return The result graph. */ - Graph search(List dataSet, Parameters parameters); + Graph search(List dataSets, Parameters parameters); + + void setScoreWrapper(ScoreWrapper score); } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Bpc.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Bpc.java index 92f73d482c..d4d1bdc84d 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Bpc.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Bpc.java @@ -32,7 +32,7 @@ public class Bpc implements Algorithm, HasKnowledge, ClusterAlgorithm { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public Bpc() { } @@ -65,7 +65,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { Mimbuild mimbuild = new Mimbuild(); mimbuild.setPenaltyDiscount(parameters.getDouble(Params.PENALTY_DISCOUNT)); - mimbuild.setKnowledge((IKnowledge) parameters.get("knowledge", new Knowledge2())); + mimbuild.setKnowledge((Knowledge) parameters.get("knowledge", new Knowledge())); if (parameters.getBoolean("includeThreeClusters", true)) { mimbuild.setMinClusterSize(3); @@ -136,12 +136,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Fofc.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Fofc.java index 1d20751fd3..88abccf437 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Fofc.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Fofc.java @@ -5,7 +5,6 @@ import edu.cmu.tetrad.annotation.AlgType; import edu.cmu.tetrad.annotation.Bootstrapping; import edu.cmu.tetrad.data.*; -import edu.cmu.tetrad.graph.EdgeListGraph; import edu.cmu.tetrad.graph.Graph; import edu.cmu.tetrad.graph.GraphUtils; import edu.cmu.tetrad.graph.Node; @@ -33,7 +32,7 @@ public class Fofc implements Algorithm, HasKnowledge, ClusterAlgorithm { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public Fofc() { } @@ -76,7 +75,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { Mimbuild mimbuild = new Mimbuild(); mimbuild.setPenaltyDiscount(parameters.getDouble(Params.PENALTY_DISCOUNT)); - mimbuild.setKnowledge((IKnowledge) parameters.get("knowledge", new Knowledge2())); + mimbuild.setKnowledge((Knowledge) parameters.get("knowledge", new Knowledge())); if (parameters.getBoolean("includeThreeClusters", true)) { mimbuild.setMinClusterSize(3); @@ -148,12 +147,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Ftfc.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Ftfc.java index c556f72c8d..409bc4ede1 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Ftfc.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/cluster/Ftfc.java @@ -31,7 +31,7 @@ public class Ftfc implements Algorithm, HasKnowledge, ClusterAlgorithm { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public Ftfc() { } @@ -105,13 +105,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/CcdMaxConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/CcdMaxConcatenated.java index f7bf3dc59f..22bb2f6faa 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/CcdMaxConcatenated.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/CcdMaxConcatenated.java @@ -2,6 +2,7 @@ import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm; import edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; import edu.cmu.tetrad.annotation.Bootstrapping; import edu.cmu.tetrad.data.*; @@ -26,7 +27,7 @@ @Bootstrapping public class CcdMaxConcatenated implements MultiDataSetAlgorithm, HasKnowledge { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); private final IndependenceWrapper test; public CcdMaxConcatenated(IndependenceWrapper test) { @@ -69,6 +70,7 @@ public Graph search(List dataModels, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -76,6 +78,11 @@ public Graph search(List dataModels, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + @Override public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { @@ -90,6 +97,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -132,12 +140,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FASK.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FASK.java index 638f63125e..190f786fd7 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FASK.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FASK.java @@ -41,7 +41,7 @@ public class FASK implements Algorithm, HasKnowledge, UsesScoreWrapper, TakesInd private IndependenceWrapper test; private ScoreWrapper score; private Graph externalGraph; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); private Algorithm algorithm; // Don't delete. @@ -178,13 +178,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofs.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofs.java index dda72be1eb..4ce5ce8048 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofs.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofs.java @@ -24,7 +24,7 @@ public class FasLofs implements Algorithm, HasKnowledge { static final long serialVersionUID = 23L; private final Lofs2.Rule rule; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public FasLofs(Lofs2.Rule rule) { this.rule = rule; @@ -83,12 +83,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofsConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofsConcatenated.java index 2c8a892e2c..38c17dd0d1 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofsConcatenated.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FasLofsConcatenated.java @@ -1,6 +1,7 @@ package edu.cmu.tetrad.algcomparison.algorithm.multi; import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; import edu.cmu.tetrad.annotation.Bootstrapping; import edu.cmu.tetrad.data.*; @@ -29,7 +30,7 @@ public class FasLofsConcatenated implements MultiDataSetAlgorithm, HasKnowledge { static final long serialVersionUID = 23L; private final Lofs2.Rule rule; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public FasLofsConcatenated(Lofs2.Rule rule) { this.rule = rule; @@ -66,6 +67,7 @@ public Graph search(List dataModels, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -73,6 +75,11 @@ public Graph search(List dataModels, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + private Graph getGraph(FasLofs search) { return search.search(); } @@ -91,6 +98,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -128,12 +136,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskConcatenated.java index 92a1962373..bb9b4ba034 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskConcatenated.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskConcatenated.java @@ -39,7 +39,7 @@ public class FaskConcatenated implements MultiDataSetAlgorithm, HasKnowledge, Ta static final long serialVersionUID = 23L; private IndependenceWrapper test; private ScoreWrapper score; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public FaskConcatenated() { @@ -86,6 +86,7 @@ public Graph search(List dataSets, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(score); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -93,6 +94,11 @@ public Graph search(List dataSets, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + @Override public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { @@ -107,6 +113,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(score); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -145,13 +152,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskVote.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskVote.java index ca5c02e4a7..07331aa24c 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskVote.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FaskVote.java @@ -41,7 +41,7 @@ public class FaskVote implements MultiDataSetAlgorithm, HasKnowledge, UsesScoreWrapper, TakesExternalGraph, TakesIndependenceWrapper { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); private Graph externalGraph; private ScoreWrapper score; private IndependenceWrapper test; @@ -87,6 +87,7 @@ public Graph search(List dataSets, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(score); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -109,6 +110,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(score); search.setParameters(parameters); @@ -141,13 +143,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FgesConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FgesConcatenated.java index 4d78f2db6c..4b6e8ab932 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FgesConcatenated.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/FgesConcatenated.java @@ -29,7 +29,7 @@ public class FgesConcatenated implements MultiDataSetAlgorithm, HasKnowledge { static final long serialVersionUID = 23L; private final ScoreWrapper score; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); private Algorithm externalGraph; private boolean compareToTrue; @@ -95,6 +95,7 @@ public Graph search(List dataModels, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(score); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -102,6 +103,11 @@ public Graph search(List dataModels, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + @Override public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { @@ -117,6 +123,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(score); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -158,13 +165,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } /** diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/Images.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/Images.java new file mode 100644 index 0000000000..102b4b4f78 --- /dev/null +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/Images.java @@ -0,0 +1,232 @@ +package edu.cmu.tetrad.algcomparison.algorithm.multi; + +import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm; +import edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; +import edu.cmu.tetrad.algcomparison.score.SemBicScore; +import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; +import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper; +import edu.cmu.tetrad.annotation.AlgType; +import edu.cmu.tetrad.annotation.Bootstrapping; +import edu.cmu.tetrad.data.*; +import edu.cmu.tetrad.graph.EdgeListGraph; +import edu.cmu.tetrad.graph.Graph; +import edu.cmu.tetrad.search.*; +import edu.cmu.tetrad.util.Parameters; +import edu.cmu.tetrad.util.Params; +import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest; + +import java.util.ArrayList; +import java.util.Collections; +import java.util.LinkedList; +import java.util.List; + +/** + * Wraps the IMaGES algorithm for continuous variables. + * + * Requires that the parameter 'randomSelectionSize' be set to indicate how many + * datasets should be taken at a time (randomly). This cannot given multiple + * values. + * + * @author jdramsey + */ +@edu.cmu.tetrad.annotation.Algorithm( + name = "IMaGES", + command = "images", + algoType = AlgType.forbid_latent_common_causes, + dataType = DataType.All +) +@Bootstrapping +public class Images implements MultiDataSetAlgorithm, HasKnowledge, UsesScoreWrapper { + + static final long serialVersionUID = 23L; + private Knowledge knowledge = new Knowledge(); + + private ScoreWrapper score; + + public Images() { + } + + @Override + public Graph search(List
dataSets, Parameters parameters) { + this.knowledge = dataSets.get(0).getKnowledge(); + int meta = parameters.getInt(Params.IMAGES_META_ALG); + + if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { + List _dataSets = new ArrayList<>(); + + if (parameters.getInt(Params.TIME_LAG) > 0) { + for (DataModel dataSet : dataSets) { + DataSet timeSeries = TimeSeriesUtils.createLagData((DataSet) dataSet, parameters.getInt(Params.TIME_LAG)); + if (dataSet.getName() != null) { + timeSeries.setName(dataSet.getName()); + } + _dataSets.add(timeSeries); + } + + dataSets = _dataSets; + this.knowledge = _dataSets.get(0).getKnowledge(); + } + + List scores = new ArrayList<>(); + + for (DataModel dataModel : dataSets) { + Score s = score.getScore(dataModel, parameters); + scores.add(s); + } + + ImagesScore score = new ImagesScore(scores); + + if (meta == 1) { + edu.cmu.tetrad.search.Fges search = new edu.cmu.tetrad.search.Fges(score); + search.setKnowledge(new Knowledge((Knowledge) knowledge)); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + return search.search(); + } +// else if (meta == 2) { +// Grasp search = new edu.cmu.tetrad.search.Grasp(score); +// search.setKnowledge(this.knowledge); +// search.setVerbose(parameters.getBoolean(Params.VERBOSE)); +// search.bestOrder(score.getVariables()); +// search.setDepth(6); +// search.setSingularDepth(1); +// search.setNonSingularDepth(1); +// return search.getGraph(true); +// } + else if (meta == 2) { + Boss search = new Boss(score); + search.setAlgType(Boss.AlgType.BOSS1); + search.setKnowledge(new Knowledge((Knowledge) knowledge)); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + search.bestOrder(score.getVariables()); + return search.getGraph(true); + } +// else if (meta == 4) { +// Boss search = new edu.cmu.tetrad.search.Boss(score); +// search.setKnowledge(this.knowledge); +// search.setVerbose(parameters.getBoolean(Params.VERBOSE)); +// search.bestOrder(score.getVariables()); +// return search.getGraph(); +// } + else if (meta == 3) { + BridgesOld search = new edu.cmu.tetrad.search.BridgesOld(score); + search.setKnowledge(this.knowledge); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + return search.search(); + } + else { + throw new IllegalArgumentException("Unrecognized meta option: " + meta); + } + } else { + Images imagesSemBic = new Images(); + + List dataSets2 = new ArrayList<>(); + + for (DataModel dataModel : dataSets) { + dataSets2.add((DataSet) dataModel); + } + + List _dataSets = new ArrayList<>(); + + if (parameters.getInt(Params.TIME_LAG) > 0) { + for (DataSet dataSet : dataSets2) { + DataSet timeSeries = TimeSeriesUtils.createLagData(dataSet, parameters.getInt(Params.TIME_LAG)); + if (dataSet.getName() != null) { + timeSeries.setName(dataSet.getName()); + } + _dataSets.add(timeSeries); + } + + dataSets2 = _dataSets; + } + + GeneralResamplingTest search = new GeneralResamplingTest( + dataSets2, + imagesSemBic, + parameters.getInt(Params.NUMBER_RESAMPLING), + parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), + parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); + search.setParameters(parameters); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + search.setKnowledge(dataSets.get(0).getKnowledge()); + search.setScoreWrapper(score); + return search.search(); + } + } + + @Override + public Graph search(DataModel dataSet, Parameters parameters) { + if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { + return search(Collections.singletonList(DataUtils.getMixedDataSet(dataSet)), parameters); + } else { + Images images = new Images(); + + List dataSets = Collections.singletonList(DataUtils.getMixedDataSet(dataSet)); + GeneralResamplingTest search = new GeneralResamplingTest(dataSets, + images, + parameters.getInt(Params.NUMBER_RESAMPLING), + parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), + parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); +// search.setKnowledge(this.knowledge); + + if (score == null) { + System.out.println(); + } + + search.setParameters(parameters); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + search.setScoreWrapper(score); + return search.search(); + } + } + + @Override + public Graph getComparisonGraph(Graph graph) { + return new EdgeListGraph(graph); + } + + @Override + public String getDescription() { + return "IMaGES"; + } + + @Override + public DataType getDataType() { + return DataType.All; + } + + @Override + public List getParameters() { + List parameters = new LinkedList<>(); + parameters.addAll(new SemBicScore().getParameters()); + + parameters.addAll((new Fges()).getParameters()); + parameters.add(Params.RANDOM_SELECTION_SIZE); + parameters.add(Params.TIME_LAG); + parameters.add(Params.IMAGES_META_ALG); + + parameters.add(Params.VERBOSE); + + return parameters; + } + + @Override + public Knowledge getKnowledge() { + return this.knowledge; + } + + @Override + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); + } + + @Override + public ScoreWrapper getScoreWrapper() { + return this.score; + } + + @Override + public void setScoreWrapper(ScoreWrapper score) { + this.score = score; + } +} diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesBDeu.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesBDeu.java index 83ef36efdc..c08e0c9b68 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesBDeu.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesBDeu.java @@ -3,9 +3,10 @@ import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm; import edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges; import edu.cmu.tetrad.algcomparison.score.BdeuScore; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; -import edu.cmu.tetrad.annotation.AlgType; import edu.cmu.tetrad.annotation.Bootstrapping; +import edu.cmu.tetrad.annotation.Experimental; import edu.cmu.tetrad.data.*; import edu.cmu.tetrad.graph.EdgeListGraph; import edu.cmu.tetrad.graph.Graph; @@ -29,17 +30,18 @@ * * @author jdramsey */ -@edu.cmu.tetrad.annotation.Algorithm( - name = "IMaGES Discrete", - command = "imgs_disc", - algoType = AlgType.forbid_latent_common_causes, - dataType = DataType.Discrete -) +//@edu.cmu.tetrad.annotation.Algorithm( +// name = "IMaGES Discrete", +// command = "imgs_disc", +// algoType = AlgType.forbid_latent_common_causes, +// dataType = DataType.Discrete +//) @Bootstrapping +@Experimental public class ImagesBDeu implements MultiDataSetAlgorithm, HasKnowledge { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public ImagesBDeu() { } @@ -71,6 +73,7 @@ public Graph search(List dataSets, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -78,6 +81,11 @@ public Graph search(List dataSets, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + @Override public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { @@ -92,6 +100,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -127,12 +136,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesPcStableMax.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesPcStableMax.java index bd00d4ad8d..d9b0a32d4e 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesPcStableMax.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesPcStableMax.java @@ -1,6 +1,7 @@ package edu.cmu.tetrad.algcomparison.algorithm.multi; import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; import edu.cmu.tetrad.annotation.Bootstrapping; import edu.cmu.tetrad.data.*; @@ -29,7 +30,7 @@ @Bootstrapping public class ImagesPcStableMax implements MultiDataSetAlgorithm, HasKnowledge { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public ImagesPcStableMax() { } @@ -67,6 +68,7 @@ public Graph search(List dataModels, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -74,6 +76,11 @@ public Graph search(List dataModels, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + @Override public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { @@ -88,6 +95,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -131,12 +139,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesSemBic.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesSemBic.java index 2eb1f3c1bf..80f5d5bb81 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesSemBic.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/ImagesSemBic.java @@ -2,10 +2,11 @@ import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm; import edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; import edu.cmu.tetrad.algcomparison.score.SemBicScore; import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; -import edu.cmu.tetrad.annotation.AlgType; import edu.cmu.tetrad.annotation.Bootstrapping; +import edu.cmu.tetrad.annotation.Experimental; import edu.cmu.tetrad.data.*; import edu.cmu.tetrad.graph.EdgeListGraph; import edu.cmu.tetrad.graph.Graph; @@ -29,17 +30,18 @@ * * @author jdramsey */ -@edu.cmu.tetrad.annotation.Algorithm( - name = "IMaGES Continuous", - command = "imgs_cont", - algoType = AlgType.forbid_latent_common_causes, - dataType = DataType.Continuous -) +//@edu.cmu.tetrad.annotation.Algorithm( +// name = "IMaGES Continuous", +// command = "imgs_cont", +// algoType = AlgType.forbid_latent_common_causes, +// dataType = DataType.Continuous +//) @Bootstrapping +@Experimental public class ImagesSemBic implements MultiDataSetAlgorithm, HasKnowledge { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public ImagesSemBic() { } @@ -51,7 +53,7 @@ public Graph search(List dataSets, Parameters parameters) { if (parameters.getInt(Params.TIME_LAG) > 0) { for (DataModel dataSet : dataSets) { - DataSet timeSeries = TimeSeriesUtils.createLagData((DataSet) dataSet, parameters.getInt(Params.TIME_LAG)); + DataSet timeSeries = TimeSeriesUtils.createLagData((DataSet) dataSet, parameters.getInt(Params.TIME_LAG)); if (dataSet.getName() != null) { timeSeries.setName(dataSet.getName()); } @@ -71,22 +73,35 @@ public Graph search(List dataSets, Parameters parameters) { } else { ImagesSemBic imagesSemBic = new ImagesSemBic(); - List datasets = new ArrayList<>(); + List dataSets2 = new ArrayList<>(); + for (DataModel dataModel : dataSets) { + dataSets2.add((DataSet) dataModel); + } + List _dataSets = new ArrayList<>(); - for (DataModel dataModel : dataSets) { - dataModel.setKnowledge(knowledge); - datasets.add((DataSet) dataModel); + if (parameters.getInt(Params.TIME_LAG) > 0) { + for (DataModel dataSet : dataSets2) { + DataSet timeSeries = TimeSeriesUtils.createLagData((DataSet) dataSet, parameters.getInt(Params.TIME_LAG)); + if (dataSet.getName() != null) { + timeSeries.setName(dataSet.getName()); + } + _dataSets.add(timeSeries); + } + + dataSets2 = _dataSets; + this.knowledge = _dataSets.get(0).getKnowledge(); } GeneralResamplingTest search = new GeneralResamplingTest( - datasets, + dataSets2, imagesSemBic, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -95,6 +110,11 @@ public Graph search(List dataSets, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + @Override public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { @@ -109,6 +129,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -147,12 +168,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/MultiFaskV1.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/MultiFaskV1.java index 4400e486b9..f4e541e1c7 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/MultiFaskV1.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/MultiFaskV1.java @@ -2,6 +2,7 @@ import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm; import edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; import edu.cmu.tetrad.algcomparison.score.SemBicScore; import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; import edu.cmu.tetrad.annotation.Bootstrapping; @@ -39,7 +40,7 @@ public class MultiFaskV1 implements MultiDataSetAlgorithm, HasKnowledge { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public MultiFaskV1() { @@ -84,6 +85,7 @@ public Graph search(List dataSets, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -91,6 +93,11 @@ public Graph search(List dataSets, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + @Override public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { @@ -105,6 +112,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -142,12 +150,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/PcStableMaxConcatenated.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/PcStableMaxConcatenated.java index d17e17e19c..0b231bc764 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/PcStableMaxConcatenated.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/multi/PcStableMaxConcatenated.java @@ -3,6 +3,7 @@ import edu.cmu.tetrad.algcomparison.algorithm.Algorithm; import edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm; import edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; import edu.cmu.tetrad.annotation.Bootstrapping; import edu.cmu.tetrad.data.*; @@ -33,7 +34,7 @@ public class PcStableMaxConcatenated implements MultiDataSetAlgorithm, HasKnowle private boolean compareToTrue; private final IndependenceWrapper test; private final Algorithm externalGraph = null; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public PcStableMaxConcatenated(IndependenceWrapper test, boolean compareToTrue) { this.test = test; @@ -77,6 +78,7 @@ public Graph search(List dataModels, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -84,6 +86,11 @@ public Graph search(List dataModels, Parameters parameters) { } } + @Override + public void setScoreWrapper(ScoreWrapper score) { + + } + @Override public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { @@ -98,6 +105,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); + search.setScoreWrapper(null); search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); @@ -144,13 +152,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS.java index aeedad2943..703bc275cb 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS.java @@ -9,10 +9,18 @@ import edu.cmu.tetrad.annotation.AlgType; import edu.cmu.tetrad.annotation.Bootstrapping; import edu.cmu.tetrad.annotation.Experimental; -import edu.cmu.tetrad.data.*; +import edu.cmu.tetrad.data.DataModel; +import edu.cmu.tetrad.data.DataSet; +import edu.cmu.tetrad.data.DataType; +import edu.cmu.tetrad.data.Knowledge; import edu.cmu.tetrad.graph.EdgeListGraph; import edu.cmu.tetrad.graph.Graph; -import edu.cmu.tetrad.search.*; +import edu.cmu.tetrad.graph.Node; +import edu.cmu.tetrad.graph.NodeType; +import edu.cmu.tetrad.search.Boss; +import edu.cmu.tetrad.search.IndependenceTest; +import edu.cmu.tetrad.search.Score; +import edu.cmu.tetrad.search.TimeSeriesUtils; import edu.cmu.tetrad.util.Parameters; import edu.cmu.tetrad.util.Params; import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest; @@ -21,7 +29,7 @@ import java.util.List; /** - * GRaSP (Greedy Relaxations of Sparsest Permutation) + * BOSS (Best Order Score Search) * * @author bryanandrews * @author josephramsey @@ -37,15 +45,19 @@ public class BOSS implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapp static final long serialVersionUID = 23L; private ScoreWrapper score; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public BOSS() { // Used in reflection; do not delete. } - public BOSS(ScoreWrapper score, IndependenceWrapper test) { - this.score = score; +// public BOSS(ScoreWrapper score) { +// this.score = score; +// } + + public BOSS(IndependenceWrapper test, ScoreWrapper score) { this.test = test; + this.score = score; } @Override @@ -64,28 +76,44 @@ public Graph search(DataModel dataModel, Parameters parameters) { Score score = this.score.getScore(dataModel, parameters); IndependenceTest test = this.test.getTest(dataModel, parameters); - test.setVerbose(parameters.getBoolean(Params.VERBOSE)); Boss boss = new Boss(test, score); - boss.setDepth(parameters.getInt(Params.GRASP_DEPTH)); - boss.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE)); - boss.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL)); + if (parameters.getInt(Params.BOSS_ALG) == 1) { + boss.setAlgType(Boss.AlgType.BOSS1); + } else if (parameters.getInt(Params.BOSS_ALG) == 2) { + boss.setAlgType(Boss.AlgType.BOSS2); + } else if (parameters.getInt(Params.BOSS_ALG) == 3) { + boss.setAlgType(Boss.AlgType.BOSS3); + } else { + throw new IllegalArgumentException("Unrecognized boss algorithm type."); + } + + boss.setDepth(parameters.getInt(Params.DEPTH)); boss.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER)); + boss.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE)); + boss.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_RASKUTTI_UHLER)); boss.setVerbose(parameters.getBoolean(Params.VERBOSE)); - boss.setCacheScores(parameters.getBoolean(Params.CACHE_SCORES)); - boss.setNumStarts(parameters.getInt(Params.NUM_STARTS)); + boss.setCaching(parameters.getBoolean(Params.CACHE_SCORES)); + boss.setKnowledge(this.knowledge); - boss.bestOrder(score.getVariables()); - return boss.getGraph(parameters.getBoolean(Params.OUTPUT_CPDAG)); + + boss.bestOrder(new ArrayList (score.getVariables())); + return boss.getGraph(true); } else { - BOSS algorithm = new BOSS(this.score, this.test); + BOSS algorithm = new BOSS(this.test, this.score); DataSet data = (DataSet) dataModel; - GeneralResamplingTest search = new GeneralResamplingTest(data, algorithm, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); + GeneralResamplingTest search = new GeneralResamplingTest( + data, + algorithm, + parameters.getInt(Params.NUMBER_RESAMPLING), + parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), + parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), + parameters.getInt(Params.RESAMPLING_ENSEMBLE), + parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); search.setKnowledge(this.knowledge); - search.setParameters(parameters); search.setVerbose(parameters.getBoolean(Params.VERBOSE)); return search.search(); @@ -99,8 +127,7 @@ public Graph getComparisonGraph(Graph graph) { @Override public String getDescription() { - return "BOSS (Better Order Score Search) using " + this.test.getDescription() - + " or " + this.score.getDescription(); + return "BOSS (Best Order Score Search) using " + this.score.getDescription(); } @Override @@ -113,15 +140,19 @@ public List getParameters() { ArrayList params = new ArrayList<>(); // Flags - params.add(Params.GRASP_DEPTH); + params.add(Params.BOSS_ALG); + params.add(Params.DEPTH); params.add(Params.GRASP_USE_SCORE); - params.add(Params.GRASP_USE_VERMA_PEARL); + params.add(Params.GRASP_USE_RASKUTTI_UHLER); params.add(Params.GRASP_USE_DATA_ORDER); + params.add(Params.TIME_LAG); + params.add(Params.CACHE_SCORES); params.add(Params.VERBOSE); // Parameters params.add(Params.NUM_STARTS); + return params; } @@ -136,22 +167,22 @@ public void setScoreWrapper(ScoreWrapper score) { } @Override - public IndependenceWrapper getIndependenceWrapper() { - return this.test; + public Knowledge getKnowledge() { + return this.knowledge.copy(); } @Override - public void setIndependenceWrapper(IndependenceWrapper independenceWrapper) { - this.test = independenceWrapper; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override - public IKnowledge getKnowledge() { - return this.knowledge.copy(); + public void setIndependenceWrapper(IndependenceWrapper test) { + this.test = test; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge.copy(); + public IndependenceWrapper getIndependenceWrapper() { + return this.test; } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB.java new file mode 100644 index 0000000000..cb6a7eb93e --- /dev/null +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB.java @@ -0,0 +1,144 @@ +package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag; + +import edu.cmu.tetrad.algcomparison.algorithm.Algorithm; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; +import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; +import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper; +import edu.cmu.tetrad.annotation.AlgType; +import edu.cmu.tetrad.annotation.Bootstrapping; +import edu.cmu.tetrad.annotation.Experimental; +import edu.cmu.tetrad.data.*; +import edu.cmu.tetrad.graph.EdgeListGraph; +import edu.cmu.tetrad.graph.Graph; +import edu.cmu.tetrad.graph.GraphUtils; +import edu.cmu.tetrad.graph.Node; +import edu.cmu.tetrad.search.BossMB; +import edu.cmu.tetrad.search.Score; +import edu.cmu.tetrad.util.Parameters; +import edu.cmu.tetrad.util.Params; +import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest; + +import java.util.ArrayList; +import java.util.List; + +/** + * BOSS-MB. + * + * @author jdramsey + */ +@edu.cmu.tetrad.annotation.Algorithm( + name = "BOSS-MB", + command = "boss-mb", + algoType = AlgType.search_for_Markov_blankets +) +@Bootstrapping +@Experimental +public class BOSS_MB implements Algorithm, HasKnowledge, UsesScoreWrapper { + + static final long serialVersionUID = 23L; + private ScoreWrapper score; + private Knowledge knowledge = new Knowledge(); + private String targets; + + public BOSS_MB() { + } + + public BOSS_MB(ScoreWrapper score) { + this.score = score; + } + + @Override + public Graph search(DataModel dataSet, Parameters parameters) { + if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { + this.targets = parameters.getString(Params.TARGETS); + + String[] tokens = this.targets.split(","); + List targets = new ArrayList<>(); + + Score score = this.score.getScore(dataSet, parameters); + + for (String t : tokens) { + String name = t.trim(); + targets.add(score.getVariable(name)); + } + + + BossMB boss = new BossMB(score); + + boss.setDepth(parameters.getInt(Params.GRASP_DEPTH)); + boss.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER)); + boss.setVerbose(parameters.getBoolean(Params.VERBOSE)); + boss.setFindMb(parameters.getBoolean(Params.MB)); + + boss.setNumStarts(parameters.getInt(Params.NUM_STARTS)); + boss.setKnowledge(this.knowledge); + + boss.bestOrder(score.getVariables(), targets); + return boss.getGraph(); + } else { + BOSS_MB fgesMb = new BOSS_MB(this.score); + + DataSet data = (DataSet) dataSet; + GeneralResamplingTest search = new GeneralResamplingTest(data, fgesMb, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); + search.setKnowledge(this.knowledge); + search.setParameters(parameters); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + return search.search(); + } + } + + @Override + public Graph getComparisonGraph(Graph graph) { + Node target = graph.getNode(this.targets); + return GraphUtils.markovBlanketDag(target, new EdgeListGraph(graph)); + } + + @Override + public String getDescription() { + return "BOSS-MB using " + this.score.getDescription(); + } + + @Override + public DataType getDataType() { + return this.score.getDataType(); + } + + @Override + public List getParameters() { + List params = new ArrayList<>(); + params.add(Params.TARGETS); + params.add(Params.MB); + + // Flags + params.add(Params.GRASP_DEPTH); + params.add(Params.GRASP_USE_DATA_ORDER); + params.add(Params.CACHE_SCORES); + params.add(Params.VERBOSE); + + // Parameters + params.add(Params.NUM_STARTS); + + return params; + } + + @Override + public Knowledge getKnowledge() { + return this.knowledge; + } + + @Override + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); + } + + @Override + public ScoreWrapper getScoreWrapper() { + return this.score; + } + + @Override + public void setScoreWrapper(ScoreWrapper score) { + this.score = score; + } + +} diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB2.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB2.java new file mode 100644 index 0000000000..63a4595c03 --- /dev/null +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSS_MB2.java @@ -0,0 +1,117 @@ +package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag; + +import edu.cmu.tetrad.algcomparison.algorithm.Algorithm; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; +import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; +import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper; +import edu.cmu.tetrad.data.*; +import edu.cmu.tetrad.graph.EdgeListGraph; +import edu.cmu.tetrad.graph.Graph; +import edu.cmu.tetrad.search.BossMB2; +import edu.cmu.tetrad.search.Score; +import edu.cmu.tetrad.util.Parameters; +import edu.cmu.tetrad.util.Params; +import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest; + +import java.util.ArrayList; +import java.util.List; + +///** +// * BOSS-MB. +// * +// * @author jdramsey +// */ +//@edu.cmu.tetrad.annotation.Algorithm( +// name = "BOSS-MB2", +// command = "boss-mb2", +// algoType = AlgType.search_for_Markov_blankets +//) +//@Bootstrapping +//@Experimental +public class BOSS_MB2 implements Algorithm, HasKnowledge, UsesScoreWrapper { + + static final long serialVersionUID = 23L; + private ScoreWrapper score; + private Knowledge knowledge = new Knowledge(); + + public BOSS_MB2() { + } + + public BOSS_MB2(ScoreWrapper score) { + this.score = score; + } + + @Override + public Graph search(DataModel dataSet, Parameters parameters) { + if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { + Score score = this.score.getScore(dataSet, parameters); + + BossMB2 boss = new BossMB2(score); + + boss.setDepth(parameters.getInt(Params.DEPTH)); + boss.setVerbose(parameters.getBoolean(Params.VERBOSE)); + boss.setFindMb(parameters.getBoolean(Params.MB)); + boss.setKnowledge(this.knowledge); + + return boss.search(score.getVariables()); + } else { + BOSS_MB2 fgesMb = new BOSS_MB2(this.score); + + DataSet data = (DataSet) dataSet; + GeneralResamplingTest search = new GeneralResamplingTest(data, fgesMb, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); + search.setKnowledge(this.knowledge); + search.setParameters(parameters); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + return search.search(); + } + } + + @Override + public Graph getComparisonGraph(Graph graph) { + return new EdgeListGraph(graph); + } + + @Override + public String getDescription() { + return "BOSS-MB2 using " + this.score.getDescription(); + } + + @Override + public DataType getDataType() { + return this.score.getDataType(); + } + + @Override + public List getParameters() { + List params = new ArrayList<>(); + params.add(Params.MB); + + // Flags + params.add(Params.DEPTH); + params.add(Params.CACHE_SCORES); + params.add(Params.VERBOSE); + + return params; + } + + @Override + public Knowledge getKnowledge() { + return this.knowledge; + } + + @Override + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); + } + + @Override + public ScoreWrapper getScoreWrapper() { + return this.score; + } + + @Override + public void setScoreWrapper(ScoreWrapper score) { + this.score = score; + } + +} diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES.java new file mode 100644 index 0000000000..aa32db3379 --- /dev/null +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES.java @@ -0,0 +1,152 @@ +package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag; + +import edu.cmu.tetrad.algcomparison.algorithm.Algorithm; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; +import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; +import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper; +import edu.cmu.tetrad.annotation.AlgType; +import edu.cmu.tetrad.annotation.Bootstrapping; +import edu.cmu.tetrad.annotation.Experimental; +import edu.cmu.tetrad.data.*; +import edu.cmu.tetrad.graph.EdgeListGraph; +import edu.cmu.tetrad.graph.Graph; +import edu.cmu.tetrad.search.Bridges; +import edu.cmu.tetrad.search.Score; +import edu.cmu.tetrad.search.TimeSeriesUtils; +import edu.cmu.tetrad.util.Parameters; +import edu.cmu.tetrad.util.Params; +import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest; + +import java.io.PrintStream; +import java.util.ArrayList; +import java.util.List; + +/** + * FGES (the heuristic version). + * + * @author jdramsey + */ +//@edu.cmu.tetrad.annotation.Algorithm( +// name = "BRIDGES", +// command = "bridges", +// algoType = AlgType.forbid_latent_common_causes +//) +//@Bootstrapping +//@Experimental +public class BRIDGES implements Algorithm, HasKnowledge, UsesScoreWrapper { + + static final long serialVersionUID = 23L; + + private ScoreWrapper score; + private Knowledge knowledge = new Knowledge(); + + public BRIDGES() { + + } + + public BRIDGES(ScoreWrapper score) { + this.score = score; + } + + @Override + public Graph search(DataModel dataModel, Parameters parameters) { + if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { + if (parameters.getInt(Params.TIME_LAG) > 0) { + DataSet dataSet = (DataSet) dataModel; + DataSet timeSeries = TimeSeriesUtils.createLagData(dataSet, parameters.getInt(Params.TIME_LAG)); + if (dataSet.getName() != null) { + timeSeries.setName(dataSet.getName()); + } + dataModel = timeSeries; + knowledge = timeSeries.getKnowledge(); + } + + Score score = this.score.getScore(dataModel, parameters); + Graph graph; + + Bridges search + = new Bridges(score); + search.setKnowledge(this.knowledge); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + search.setMeekVerbose(parameters.getBoolean(Params.MEEK_VERBOSE)); + search.setMaxDegree(parameters.getInt(Params.MAX_DEGREE)); + search.setSymmetricFirstStep(parameters.getBoolean(Params.SYMMETRIC_FIRST_STEP)); + search.setFaithfulnessAssumed(parameters.getBoolean(Params.FAITHFULNESS_ASSUMED)); + search.setParallelized(parameters.getBoolean(Params.PARALLELIZED)); + search.setDepth(parameters.getInt(Params.DEPTH)); + + Object obj = parameters.get(Params.PRINT_STREAM); + if (obj instanceof PrintStream) { + search.setOut((PrintStream) obj); + } + + graph = search.search(); + + return graph; + } else { + BRIDGES fges = new BRIDGES(this.score); + + DataSet data = (DataSet) dataModel; + GeneralResamplingTest search = new GeneralResamplingTest( + data, fges, parameters.getInt(Params.NUMBER_RESAMPLING), + parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), + parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); + search.setKnowledge(this.knowledge); + search.setParameters(parameters); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + return search.search(); + } + } + + @Override + public Graph getComparisonGraph(Graph graph) { + return new EdgeListGraph(graph); + } + + @Override + public String getDescription() { + return "BRIDGES using " + this.score.getDescription(); + } + + @Override + public DataType getDataType() { + return this.score.getDataType(); + } + + @Override + public List getParameters() { + List parameters = new ArrayList<>(); + parameters.add(Params.SYMMETRIC_FIRST_STEP); + parameters.add(Params.MAX_DEGREE); + parameters.add(Params.PARALLELIZED); + parameters.add(Params.FAITHFULNESS_ASSUMED); + parameters.add(Params.TIME_LAG); + parameters.add(Params.DEPTH); + + parameters.add(Params.VERBOSE); + parameters.add(Params.MEEK_VERBOSE); + + return parameters; + } + + @Override + public Knowledge getKnowledge() { + return this.knowledge; + } + + @Override + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); + } + + @Override + public ScoreWrapper getScoreWrapper() { + return this.score; + } + + @Override + public void setScoreWrapper(ScoreWrapper score) { + this.score = score; + } + +} diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES2.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES2.java new file mode 100644 index 0000000000..5ea5bb1e8c --- /dev/null +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES2.java @@ -0,0 +1,145 @@ +package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag; + +import edu.cmu.tetrad.algcomparison.algorithm.Algorithm; +import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; +import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; +import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper; +import edu.cmu.tetrad.annotation.AlgType; +import edu.cmu.tetrad.annotation.Bootstrapping; +import edu.cmu.tetrad.annotation.Experimental; +import edu.cmu.tetrad.data.*; +import edu.cmu.tetrad.graph.EdgeListGraph; +import edu.cmu.tetrad.graph.Graph; +import edu.cmu.tetrad.search.Bridges2; +import edu.cmu.tetrad.search.Score; +import edu.cmu.tetrad.search.TimeSeriesUtils; +import edu.cmu.tetrad.util.Parameters; +import edu.cmu.tetrad.util.Params; +import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest; + +import java.io.PrintStream; +import java.util.ArrayList; +import java.util.List; + +/** + * FGES (the heuristic version). + * + * @author jdramsey + */ +//@edu.cmu.tetrad.annotation.Algorithm( +// name = "BRIDGES2", +// command = "bridges2", +// algoType = AlgType.forbid_latent_common_causes +//) +//@Bootstrapping +//@Experimental +public class BRIDGES2 implements Algorithm, HasKnowledge, UsesScoreWrapper { + + static final long serialVersionUID = 23L; + + private ScoreWrapper score; + private Knowledge knowledge = new Knowledge(); + + public BRIDGES2() { + + } + + public BRIDGES2(ScoreWrapper score) { + this.score = score; + } + + @Override + public Graph search(DataModel dataModel, Parameters parameters) { + if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { + if (parameters.getInt(Params.TIME_LAG) > 0) { + DataSet dataSet = (DataSet) dataModel; + DataSet timeSeries = TimeSeriesUtils.createLagData(dataSet, parameters.getInt(Params.TIME_LAG)); + if (dataSet.getName() != null) { + timeSeries.setName(dataSet.getName()); + } + dataModel = timeSeries; + knowledge = timeSeries.getKnowledge(); + } + + Score score = this.score.getScore(dataModel, parameters); + Graph graph; + + Bridges2 search = new Bridges2(score); + search.setKnowledge(this.knowledge); + search.setMaxDegree(parameters.getInt(Params.MAX_DEGREE)); + + Object obj = parameters.get(Params.PRINT_STREAM); + if (obj instanceof PrintStream) { + search.setOut((PrintStream) obj); + } + + graph = search.search(); + + return graph; + } else { + BRIDGES2 fges = new BRIDGES2(this.score); + + DataSet data = (DataSet) dataModel; + GeneralResamplingTest search = new GeneralResamplingTest( + data, fges, parameters.getInt(Params.NUMBER_RESAMPLING), + parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), + parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); + search.setKnowledge(this.knowledge); + search.setParameters(parameters); + search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + return search.search(); + } + } + + @Override + public Graph getComparisonGraph(Graph graph) { + return new EdgeListGraph(graph); + } + + @Override + public String getDescription() { + return "BRIDGES using " + this.score.getDescription(); + } + + @Override + public DataType getDataType() { + return this.score.getDataType(); + } + + @Override + public List getParameters() { + List parameters = new ArrayList<>(); + parameters.add(Params.SYMMETRIC_FIRST_STEP); + parameters.add(Params.MAX_DEGREE); + parameters.add(Params.PARALLELIZED); + parameters.add(Params.FAITHFULNESS_ASSUMED); + parameters.add(Params.TIME_LAG); + parameters.add(Params.DEPTH); + + parameters.add(Params.VERBOSE); + parameters.add(Params.MEEK_VERBOSE); + + return parameters; + } + + @Override + public Knowledge getKnowledge() { + return this.knowledge; + } + + @Override + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); + } + + @Override + public ScoreWrapper getScoreWrapper() { + return this.score; + } + + @Override + public void setScoreWrapper(ScoreWrapper score) { + this.score = score; + } + +} diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/rGES.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES_OLD.java similarity index 68% rename from tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/rGES.java rename to tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES_OLD.java index cdca1f0503..d6e980b477 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/rGES.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BRIDGES_OLD.java @@ -2,15 +2,17 @@ import edu.cmu.tetrad.algcomparison.algorithm.Algorithm; import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; +import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper; import edu.cmu.tetrad.annotation.AlgType; import edu.cmu.tetrad.annotation.Bootstrapping; import edu.cmu.tetrad.annotation.Experimental; import edu.cmu.tetrad.data.DataModel; import edu.cmu.tetrad.data.DataType; +import edu.cmu.tetrad.data.Knowledge; import edu.cmu.tetrad.graph.EdgeListGraph; import edu.cmu.tetrad.graph.Graph; -import edu.cmu.tetrad.search.Rges; +import edu.cmu.tetrad.search.BridgesOld; import edu.cmu.tetrad.search.Score; import edu.cmu.tetrad.util.Parameters; import edu.cmu.tetrad.util.Params; @@ -20,26 +22,29 @@ import java.util.List; /** - * rGES (experimental algorithm). + * BRIDGES (experimental algorithm). * * @author bryanandrews */ -@edu.cmu.tetrad.annotation.Algorithm( - name = "rGES", - command = "rges", - algoType = AlgType.forbid_latent_common_causes -) -@Bootstrapping -@Experimental -public class rGES implements Algorithm, UsesScoreWrapper { +//@edu.cmu.tetrad.annotation.Algorithm( +// name = "BRIDGES_OLD", +// command = "bridges-old", +// algoType = AlgType.forbid_latent_common_causes +//) +//@Bootstrapping +//@Experimental +public class BRIDGES_OLD implements Algorithm, HasKnowledge, UsesScoreWrapper { static final long serialVersionUID = 23L; private ScoreWrapper score; - public rGES() {} + private Knowledge knowledge = new Knowledge(); - public rGES(ScoreWrapper score) { + + public BRIDGES_OLD() {} + + public BRIDGES_OLD(ScoreWrapper score) { this.score = score; } @@ -49,8 +54,10 @@ public Graph search(DataModel dataModel, Parameters parameters) { Score score = this.score.getScore(dataModel, parameters); Graph graph; - Rges search = new Rges(score); - search.setVerbose(parameters.getBoolean(Params.VERBOSE)); + BridgesOld search = new BridgesOld(score); +// search.setKnowledge(knowledge); + search.setVerbose(false); +// search.setVerbose(parameters.getBoolean(Params.VERBOSE)); search.setMaxDegree(parameters.getInt(Params.MAX_DEGREE)); search.setSymmetricFirstStep(parameters.getBoolean(Params.SYMMETRIC_FIRST_STEP)); search.setFaithfulnessAssumed(parameters.getBoolean(Params.FAITHFULNESS_ASSUMED)); @@ -74,7 +81,7 @@ public Graph getComparisonGraph(Graph graph) { @Override public String getDescription() { - return "rGES (r Greedy Equivalence Search) using " + this.score.getDescription(); + return "BRIDGES_OLD (BRIDGES is not Restricted to Imaps During Greedy Equivalent Search) using " + this.score.getDescription(); } @Override @@ -104,4 +111,15 @@ public void setScoreWrapper(ScoreWrapper score) { this.score = score; } + @Override + public Knowledge getKnowledge() { + return this.knowledge; + } + + @Override + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); + } + + } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CPC.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CPC.java index a2cf005949..6fd3bfb93f 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CPC.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CPC.java @@ -34,7 +34,7 @@ public class CPC implements Algorithm, HasKnowledge, TakesIndependenceWrapper { static final long serialVersionUID = 23L; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public CPC() { } @@ -145,13 +145,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CpcStable.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CpcStable.java index 87b9f68414..af3a64c634 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CpcStable.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/CpcStable.java @@ -28,7 +28,7 @@ public class CpcStable implements Algorithm, HasKnowledge, TakesIndependenceWrap static final long serialVersionUID = 23L; private IndependenceWrapper test; private Algorithm algorithm; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public CpcStable() { } @@ -93,13 +93,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FAS.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FAS.java index bcedfd0d40..241beb50d1 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FAS.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FAS.java @@ -34,7 +34,7 @@ public class FAS implements Algorithm, HasKnowledge, TakesIndependenceWrapper { static final long serialVersionUID = 23L; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public FAS() { } @@ -98,13 +98,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Fges.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Fges.java index 9eac885510..bac789e847 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Fges.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Fges.java @@ -35,7 +35,7 @@ public class Fges implements Algorithm, HasKnowledge, UsesScoreWrapper { static final long serialVersionUID = 23L; private ScoreWrapper score; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public Fges() { @@ -125,13 +125,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override @@ -144,4 +144,4 @@ public void setScoreWrapper(ScoreWrapper score) { this.score = score; } -} +} \ No newline at end of file diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMb.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMb.java index 2994e8c1f7..1ea423191a 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMb.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMb.java @@ -36,7 +36,7 @@ public class FgesMb implements Algorithm, HasKnowledge, UsesScoreWrapper { static final long serialVersionUID = 23L; private ScoreWrapper score; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); private String targetName; public FgesMb() { @@ -105,13 +105,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMeasurement.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMeasurement.java index e199684593..7f3c5b0c96 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMeasurement.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/FgesMeasurement.java @@ -28,7 +28,7 @@ public class FgesMeasurement implements Algorithm, HasKnowledge { static final long serialVersionUID = 23L; private final ScoreWrapper score; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public FgesMeasurement(ScoreWrapper score) { this.score = score; @@ -104,13 +104,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSP.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSP.java index b68dac29d7..1fa2a94dfe 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSP.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSP.java @@ -38,7 +38,7 @@ public class GRaSP implements Algorithm, UsesScoreWrapper, TakesIndependenceWrap static final long serialVersionUID = 23L; private ScoreWrapper score; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public GRaSP() { // Used in reflection; do not delete. @@ -73,7 +73,7 @@ public Graph search(DataModel dataModel, Parameters parameters) { grasp.setNonSingularDepth(parameters.getInt(Params.GRASP_NONSINGULAR_DEPTH)); grasp.setOrdered(parameters.getBoolean(Params.GRASP_ORDERED_ALG)); grasp.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE)); - grasp.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL)); + grasp.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_RASKUTTI_UHLER)); grasp.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER)); grasp.setVerbose(parameters.getBoolean(Params.VERBOSE)); grasp.setCacheScores(parameters.getBoolean(Params.CACHE_SCORES)); @@ -121,7 +121,7 @@ public List getParameters() { params.add(Params.GRASP_SINGULAR_DEPTH); params.add(Params.GRASP_NONSINGULAR_DEPTH); params.add(Params.GRASP_ORDERED_ALG); - params.add(Params.GRASP_USE_VERMA_PEARL); + params.add(Params.GRASP_USE_RASKUTTI_UHLER); params.add(Params.GRASP_USE_DATA_ORDER); params.add(Params.CACHE_SCORES); params.add(Params.TIME_LAG); @@ -154,12 +154,12 @@ public void setIndependenceWrapper(IndependenceWrapper independenceWrapper) { } @Override - public IKnowledge getKnowledge() { - return this.knowledge.copy(); + public Knowledge getKnowledge() { + return new Knowledge((Knowledge) knowledge); } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge.copy(); + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSPTol.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSPTol.java index 98e5a26ddd..76af4772a3 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSPTol.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GRaSPTol.java @@ -37,7 +37,7 @@ public class GRaSPTol implements Algorithm, UsesScoreWrapper, TakesIndependenceW static final long serialVersionUID = 23L; private ScoreWrapper score; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public GRaSPTol() { // Used in reflection; do not delete. @@ -72,7 +72,7 @@ public Graph search(DataModel dataModel, Parameters parameters) { grasp.setNonSingularDepth(parameters.getInt(Params.GRASP_NONSINGULAR_DEPTH)); grasp.setOrdered(parameters.getBoolean(Params.GRASP_ORDERED_ALG)); grasp.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE)); - grasp.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL)); + grasp.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_RASKUTTI_UHLER)); grasp.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER)); grasp.setToleranceDepth(parameters.getInt(Params.GRASP_TOLERANCE_DEPTH)); grasp.setAllowRandomnessInsideAlgorithm(parameters.getBoolean(Params.GRASP_ALLOW_RANDOMNESS_INSIDE_ALGORITHM)); @@ -104,7 +104,7 @@ public Graph getComparisonGraph(Graph graph) { @Override public String getDescription() { - return "GRaSP (Greedy Relaxed Sparsest Permutation) using " + this.test.getDescription() + return "GRaSPTol (Greedy Relaxed Sparsest Permutation Tolerance) using " + this.test.getDescription() + " or " + this.score.getDescription(); } @@ -124,7 +124,7 @@ public List getParameters() { params.add(Params.GRASP_TOLERANCE_DEPTH); params.add(Params.GRASP_ORDERED_ALG); // params.add(Params.GRASP_USE_SCORE); - params.add(Params.GRASP_USE_VERMA_PEARL); + params.add(Params.GRASP_USE_RASKUTTI_UHLER); params.add(Params.GRASP_USE_DATA_ORDER); params.add(Params.GRASP_ALLOW_RANDOMNESS_INSIDE_ALGORITHM); params.add(Params.CACHE_SCORES); @@ -158,12 +158,12 @@ public void setIndependenceWrapper(IndependenceWrapper independenceWrapper) { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge.copy(); } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge.copy(); + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GesMe.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GesMe.java index 396f879f5c..71ba828462 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GesMe.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/GesMe.java @@ -117,7 +117,7 @@ public Graph search(DataModel dataSet, Parameters parameters) { leaves.add(nodes.get(indices.get(i))); } - IKnowledge knowledge2 = new Knowledge2(); + Knowledge knowledge2 = new Knowledge(); for (Node v : nodes) { if (leaves.contains(v)) { diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC.java index 5223d21f71..8785942255 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC.java @@ -34,7 +34,7 @@ public class PC implements Algorithm, HasKnowledge, TakesIndependenceWrapper { static final long serialVersionUID = 23L; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public PC() { } @@ -146,13 +146,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PCMAX.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PCMAX.java index a9025143e6..b22dae777c 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PCMAX.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PCMAX.java @@ -34,7 +34,7 @@ public class PCMAX implements Algorithm, HasKnowledge, TakesIndependenceWrapper static final long serialVersionUID = 23L; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public PCMAX() { } @@ -147,13 +147,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/MBFS.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC_MB.java similarity index 65% rename from tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/MBFS.java rename to tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC_MB.java index ae246fb7e4..c10bffc161 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/MBFS.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PC_MB.java @@ -12,9 +12,11 @@ import edu.cmu.tetrad.graph.GraphUtils; import edu.cmu.tetrad.graph.Node; import edu.cmu.tetrad.search.IndependenceTest; +import edu.cmu.tetrad.search.PcMb; import edu.cmu.tetrad.util.Parameters; import edu.cmu.tetrad.util.Params; import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest; +import org.jetbrains.annotations.NotNull; import java.util.ArrayList; import java.util.List; @@ -25,22 +27,22 @@ * @author jdramsey */ @edu.cmu.tetrad.annotation.Algorithm( - name = "MBFS", - command = "mbfs", + name = "PC-MB", + command = "pc-mb", algoType = AlgType.search_for_Markov_blankets ) @Bootstrapping -public class MBFS implements Algorithm, HasKnowledge, TakesIndependenceWrapper { +public class PC_MB implements Algorithm, HasKnowledge, TakesIndependenceWrapper { static final long serialVersionUID = 23L; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); - private String targetName; + private Knowledge knowledge = new Knowledge(); + private List targets; - public MBFS() { + public PC_MB() { } - public MBFS(IndependenceWrapper type) { + public PC_MB(IndependenceWrapper type) { this.test = type; } @@ -48,24 +50,15 @@ public MBFS(IndependenceWrapper type) { public Graph search(DataModel dataSet, Parameters parameters) { if (parameters.getInt(Params.NUMBER_RESAMPLING) < 1) { IndependenceTest test = this.test.getTest(dataSet, parameters); - edu.cmu.tetrad.search.Mbfs search = new edu.cmu.tetrad.search.Mbfs(test, parameters.getInt(Params.DEPTH)); - + PcMb search = new PcMb(test, parameters.getInt(Params.DEPTH)); + List targets = targets(test, parameters.getString(Params.TARGETS)); + this.targets = targets; search.setDepth(parameters.getInt(Params.DEPTH)); search.setKnowledge(this.knowledge); - - this.targetName = parameters.getString(Params.TARGET_NAME); - if (this.targetName.isEmpty()) { - throw new IllegalArgumentException("Target variable name needs to be provided."); - } - - if (test.getVariable(this.targetName) == null) { - throw new IllegalArgumentException("Target variable name '" + this.targetName + "' not found in dataset."); - } - - Node target = test.getVariable(this.targetName); - return search.search(target.getName()); + search.setFindMb(parameters.getBoolean(Params.MB)); + return search.search(targets); } else { - MBFS algorithm = new MBFS(this.test); + PC_MB algorithm = new PC_MB(this.test); DataSet data = (DataSet) dataSet; GeneralResamplingTest search = new GeneralResamplingTest(data, algorithm, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); @@ -77,15 +70,26 @@ public Graph search(DataModel dataSet, Parameters parameters) { } } + @NotNull + private List targets(IndependenceTest test, String targetString) { + String[] tokens = targetString.split(","); + List targets = new ArrayList<>(); + + for (String t : tokens) { + String name = t.trim(); + targets.add(test.getVariable(name)); + } + return targets; + } + @Override public Graph getComparisonGraph(Graph graph) { - Node target = graph.getNode(this.targetName); - return GraphUtils.markovBlanketDag(target, new EdgeListGraph(graph)); + return GraphUtils.markovBlanketDag(targets.get(0), new EdgeListGraph(graph)); } @Override public String getDescription() { - return "MBFS (Markov Blanket Fan Search) using " + this.test.getDescription(); + return "PC-MB (Markov blanket search using PC) using " + this.test.getDescription(); } @Override @@ -96,21 +100,22 @@ public DataType getDataType() { @Override public List getParameters() { List parameters = new ArrayList<>(); + parameters.add(Params.TARGETS); + parameters.add(Params.MB); parameters.add(Params.DEPTH); - parameters.add(Params.TARGET_NAME); parameters.add(Params.VERBOSE); return parameters; } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcAll.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcAll.java index 67e77955fe..122593ac79 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcAll.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcAll.java @@ -34,7 +34,7 @@ public class PcAll implements Algorithm, HasKnowledge, TakesIndependenceWrapper static final long serialVersionUID = 23L; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public PcAll() { } @@ -147,13 +147,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcStable.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcStable.java index 0e779cc049..be8c1ec2f9 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcStable.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/PcStable.java @@ -27,7 +27,7 @@ public class PcStable implements Algorithm, HasKnowledge, TakesIndependenceWrapp static final long serialVersionUID = 23L; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public PcStable() { } @@ -87,13 +87,13 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } @Override diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Pcd.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Pcd.java index 6ac4bbf536..8abc4cd458 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Pcd.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/Pcd.java @@ -23,7 +23,7 @@ @Bootstrapping public class Pcd implements Algorithm, HasKnowledge { static final long serialVersionUID = 23L; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); public Pcd() { } @@ -93,12 +93,12 @@ public List getParameters() { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge; } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge; + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSSTuck.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SIMPLE_DEMO_GA.java similarity index 69% rename from tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSSTuck.java rename to tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SIMPLE_DEMO_GA.java index 79763214bc..d6a1cda905 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/BOSSTuck.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SIMPLE_DEMO_GA.java @@ -6,9 +6,6 @@ import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; import edu.cmu.tetrad.algcomparison.utils.TakesIndependenceWrapper; import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper; -import edu.cmu.tetrad.annotation.AlgType; -import edu.cmu.tetrad.annotation.Bootstrapping; -import edu.cmu.tetrad.annotation.Experimental; import edu.cmu.tetrad.data.*; import edu.cmu.tetrad.graph.EdgeListGraph; import edu.cmu.tetrad.graph.Graph; @@ -26,24 +23,24 @@ * @author bryanandrews * @author josephramsey */ -@edu.cmu.tetrad.annotation.Algorithm( - name = "BOSSTuck", - command = "boss-tuck", - algoType = AlgType.forbid_latent_common_causes -) -@Bootstrapping -@Experimental -public class BOSSTuck implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapper, HasKnowledge { +//@edu.cmu.tetrad.annotation.Algorithm( +// name = "SIMPLE_DEMO_GA", +// command = "simple-demo-ga", +// algoType = AlgType.forbid_latent_common_causes +//) +//@Bootstrapping +//@Experimental +public class SIMPLE_DEMO_GA implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapper, HasKnowledge { static final long serialVersionUID = 23L; private ScoreWrapper score; private IndependenceWrapper test; - private IKnowledge knowledge = new Knowledge2(); + private Knowledge knowledge = new Knowledge(); - public BOSSTuck() { + public SIMPLE_DEMO_GA() { // Used in reflection; do not delete. } - public BOSSTuck(ScoreWrapper score, IndependenceWrapper test) { + public SIMPLE_DEMO_GA(ScoreWrapper score, IndependenceWrapper test) { this.score = score; this.test = test; } @@ -65,21 +62,10 @@ public Graph search(DataModel dataModel, Parameters parameters) { IndependenceTest test = this.test.getTest(dataModel, parameters); test.setVerbose(parameters.getBoolean(Params.VERBOSE)); - BossTuck boss = new BossTuck(test, score); - - boss.setDepth(parameters.getInt(Params.GRASP_DEPTH)); - boss.setUseScore(parameters.getBoolean(Params.GRASP_USE_SCORE)); - boss.setUseRaskuttiUhler(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL)); - boss.setUseDataOrder(parameters.getBoolean(Params.GRASP_USE_DATA_ORDER)); - boss.setVerbose(parameters.getBoolean(Params.VERBOSE)); - boss.setCacheScores(parameters.getBoolean(Params.CACHE_SCORES)); - - boss.setNumStarts(parameters.getInt(Params.NUM_STARTS)); - boss.setKnowledge(this.knowledge); - boss.bestOrder(score.getVariables()); - return boss.getGraph(parameters.getBoolean(Params.OUTPUT_CPDAG)); + SimpleDemoGA boss = new SimpleDemoGA(score, 10); + return boss.search(); } else { - BOSSTuck algorithm = new BOSSTuck(this.score, this.test); + SIMPLE_DEMO_GA algorithm = new SIMPLE_DEMO_GA(this.score, this.test); DataSet data = (DataSet) dataModel; GeneralResamplingTest search = new GeneralResamplingTest(data, algorithm, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); @@ -99,7 +85,7 @@ public Graph getComparisonGraph(Graph graph) { @Override public String getDescription() { - return "BOSS-tuck (Better Order Score Search) using " + this.test.getDescription() + return "SIMPLE_DEMO_GA using " + this.test.getDescription() + " or " + this.score.getDescription(); } @@ -115,8 +101,9 @@ public List getParameters() { // Flags params.add(Params.GRASP_DEPTH); params.add(Params.GRASP_USE_SCORE); - params.add(Params.GRASP_USE_VERMA_PEARL); + params.add(Params.GRASP_USE_RASKUTTI_UHLER); params.add(Params.GRASP_USE_DATA_ORDER); + params.add(Params.CACHE_SCORES); params.add(Params.VERBOSE); // Parameters @@ -146,12 +133,12 @@ public void setIndependenceWrapper(IndependenceWrapper independenceWrapper) { } @Override - public IKnowledge getKnowledge() { + public Knowledge getKnowledge() { return this.knowledge.copy(); } @Override - public void setKnowledge(IKnowledge knowledge) { - this.knowledge = knowledge.copy(); + public void setKnowledge(Knowledge knowledge) { + this.knowledge = new Knowledge((Knowledge) knowledge); } } diff --git a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SP.java b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SP.java index 39c9997343..9d9ec7dd70 100644 --- a/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SP.java +++ b/tetrad-lib/src/main/java/edu/cmu/tetrad/algcomparison/algorithm/oracle/cpdag/SP.java @@ -3,6 +3,7 @@ import edu.cmu.tetrad.algcomparison.algorithm.Algorithm; import edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper; import edu.cmu.tetrad.algcomparison.score.ScoreWrapper; +import edu.cmu.tetrad.algcomparison.utils.HasKnowledge; import edu.cmu.tetrad.algcomparison.utils.TakesIndependenceWrapper; import edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper; import edu.cmu.tetrad.annotation.AlgType; @@ -10,12 +11,12 @@ import edu.cmu.tetrad.data.DataModel; import edu.cmu.tetrad.data.DataSet; import edu.cmu.tetrad.data.DataType; +import edu.cmu.tetrad.data.Knowledge; import edu.cmu.tetrad.graph.EdgeListGraph; import edu.cmu.tetrad.graph.Graph; import edu.cmu.tetrad.search.IndependenceTest; import edu.cmu.tetrad.search.OtherPermAlgs; import edu.cmu.tetrad.search.Score; -import edu.cmu.tetrad.sem.Parameter; import edu.cmu.tetrad.util.Parameters; import edu.cmu.tetrad.util.Params; import edu.pitt.dbmi.algo.resampling.GeneralResamplingTest; @@ -34,18 +35,20 @@ algoType = AlgType.forbid_latent_common_causes ) @Bootstrapping -public class SP implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapper { +public class SP implements Algorithm, UsesScoreWrapper, TakesIndependenceWrapper, HasKnowledge { static final long serialVersionUID = 23L; private ScoreWrapper score = null; private IndependenceWrapper test; + private Knowledge knowledge = new Knowledge(); + public SP() { // Used in reflection; do not delete. } - public SP(ScoreWrapper score, IndependenceWrapper test) { - this.score = score; + public SP(IndependenceWrapper test, ScoreWrapper score) { this.test = test; + this.score = score; } @Override @@ -57,20 +60,12 @@ public Graph search(DataModel dataModel, Parameters parameters) { test.setVerbose(parameters.getBoolean(Params.VERBOSE)); - OtherPermAlgs otherPermAlgs; - - otherPermAlgs = new OtherPermAlgs(test, score); - - OtherPermAlgs.Method method = OtherPermAlgs.Method.SP; - - otherPermAlgs.setMethod(method); - otherPermAlgs.setUsePearl(parameters.getBoolean(Params.GRASP_USE_VERMA_PEARL)); - otherPermAlgs.setVerbose(parameters.getBoolean(Params.VERBOSE)); - - otherPermAlgs.bestOrder(score.getVariables()); - return otherPermAlgs.getGraph(true); + edu.cmu.tetrad.search.SP sp = new edu.cmu.tetrad.search.SP(test, score); + sp.setKnowledge(knowledge); + sp.bestOrder(score.getVariables()); + return sp.getGraph(true); } else { - GRaSP algorithm = new GRaSP(this.score, this.test); + SP algorithm = new SP(this.test, this.score); DataSet data = (DataSet) dataModel; GeneralResamplingTest search = new GeneralResamplingTest(data, algorithm, parameters.getInt(Params.NUMBER_RESAMPLING), parameters.getDouble(Params.PERCENT_RESAMPLE_SIZE), parameters.getBoolean(Params.RESAMPLING_WITH_REPLACEMENT), parameters.getInt(Params.RESAMPLING_ENSEMBLE), parameters.getBoolean(Params.ADD_ORIGINAL_DATASET)); @@ -99,7 +94,7 @@ public DataType getDataType() { @Override public List
countOmissionErrors and countCommissionErrors.
*/
-
- public EdgewiseComparisonModel(MultipleGraphSource model1, MultipleGraphSource model2,
- Parameters params) {
+ public EdgewiseComparisonModel(GraphSource model1, GraphSource model2, Parameters params) {
if (params == null) {
throw new NullPointerException("Parameters must not be null");
}
- // Need to be able to construct this object even if the models are
- // null. Otherwise the interface is annoying.
-
- if (model1 instanceof GeneralAlgorithmRunner && model2 instanceof GeneralAlgorithmRunner) {
- throw new IllegalArgumentException("Both parents can't be general algorithm runners.");
- }
-
- if (model1 instanceof GeneralAlgorithmRunner) {
- GeneralAlgorithmRunner generalAlgorithmRunner = (GeneralAlgorithmRunner) model1;
- this.algorithm = generalAlgorithmRunner.getAlgorithm();
- } else if (model2 instanceof GeneralAlgorithmRunner) {
- GeneralAlgorithmRunner generalAlgorithmRunner = (GeneralAlgorithmRunner) model2;
- this.algorithm = generalAlgorithmRunner.getAlgorithm();
+ if (model1 == null || model2 == null) {
+ throw new NullPointerException("Null graph source>");
}
this.params = params;
- String referenceName = this.params.getString("referenceGraphName", null);
-
- if (referenceName.equals(model1.getName())) {
- if (model1 instanceof Simulation && model2 instanceof GeneralAlgorithmRunner) {
- this.referenceGraphs = ((GeneralAlgorithmRunner) model2).getCompareGraphs(model1.getGraphs());
- } else if (model1 instanceof MultipleGraphSource) {
- this.referenceGraphs = model1.getGraphs();
- }
-
- if (model2 instanceof MultipleGraphSource) {
- this.targetGraphs = model2.getGraphs();
- }
-
- if (this.referenceGraphs.size() == 1 && this.targetGraphs.size() > 1) {
- Graph graph = this.referenceGraphs.get(0);
- this.referenceGraphs = new ArrayList<>();
- this.referenceGraphs.addAll(this.targetGraphs);
- }
-
- if (this.targetGraphs.size() == 1 && this.referenceGraphs.size() > 1) {
- Graph graph = this.targetGraphs.get(0);
- this.targetGraphs = new ArrayList<>();
- for (Graph _graph : this.referenceGraphs) {
- this.targetGraphs.add(graph);
- }
- }
-
- if (this.referenceGraphs == null) {
- this.referenceGraphs = Collections.singletonList(((GraphSource) model1).getGraph());
- }
-
- if (this.targetGraphs == null) {
- this.targetGraphs = Collections.singletonList(((GraphSource) model2).getGraph());
- }
- } else if (referenceName.equals(model2.getName())) {
- if (model2 instanceof Simulation && model1 instanceof GeneralAlgorithmRunner) {
- this.referenceGraphs = ((GeneralAlgorithmRunner) model1).getCompareGraphs(model2.getGraphs());
- } else if (model1 instanceof MultipleGraphSource) {
- this.referenceGraphs = model2.getGraphs();
- }
-
- if (model1 instanceof MultipleGraphSource) {
- this.targetGraphs = model1.getGraphs();
- }
-
- if (this.referenceGraphs.size() == 1 && this.targetGraphs.size() > 1) {
- Graph graph = this.referenceGraphs.get(0);
- this.referenceGraphs = new ArrayList<>();
- this.referenceGraphs.addAll(this.targetGraphs);
- }
-
- if (this.targetGraphs.size() == 1 && this.referenceGraphs.size() > 1) {
- Graph graph = this.targetGraphs.get(0);
- this.targetGraphs = new ArrayList<>();
- for (Graph _graph : this.referenceGraphs) {
- this.targetGraphs.add(graph);
- }
- }
-
- if (this.referenceGraphs == null) {
- this.referenceGraphs = Collections.singletonList(((GraphSource) model2).getGraph());
- }
-
- if (this.targetGraphs == null) {
- this.targetGraphs = Collections.singletonList(((GraphSource) model1).getGraph());
- }
- } else {
- throw new IllegalArgumentException(
- "Neither of the supplied session models is named '" +
- referenceName + "'.");
- }
-
- for (int i = 0; i < this.targetGraphs.size(); i++) {
- this.targetGraphs.set(i, GraphUtils.replaceNodes(this.targetGraphs.get(i), this.referenceGraphs.get(i).getNodes()));
- }
+ String referenceName = params.getString("referenceGraphName", null);
- if (this.algorithm != null) {
- for (int i = 0; i < this.referenceGraphs.size(); i++) {
- this.referenceGraphs.set(i, this.algorithm.getComparisonGraph(this.referenceGraphs.get(i)));
- }
- }
+ String model1Name = model1.getName();
+ String model2Name = model2.getName();
- if (this.referenceGraphs.size() != this.targetGraphs.size()) {
- throw new IllegalArgumentException("I was expecting the same number of graphs in each parent.");
+ if (referenceName.equals(model1Name)) {
+ this.referenceGraph = model1.getGraph();
+ this.targetGraph = model2.getGraph();
+ } else if (referenceName.equals(model2Name)) {
+ this.referenceGraph = model2.getGraph();
+ this.targetGraph = model1.getGraph();
+ } else {
+ this.referenceGraph = model1.getGraph();
+ this.targetGraph = model2.getGraph();
}
TetradLogger.getInstance().log("info", "Graph Comparison");
- for (int i = 0; i < this.referenceGraphs.size(); i++) {
- TetradLogger.getInstance().log("comparison", "\nModel " + (i + 1));
- TetradLogger.getInstance().log("comparison", getComparisonString(i));
- }
}
//==============================PUBLIC METHODS========================//
@@ -194,11 +106,14 @@ public void setName(String name) {
this.name = name;
}
- public String getComparisonString(int i) {
+ public String getComparisonString() {
String refName = getParams().getString("referenceGraphName", null);
String targetName = getParams().getString("targetGraphName", null);
- return SearchGraphUtils.graphComparisonString(targetName, this.targetGraphs.get(i),
- refName, this.referenceGraphs.get(i), false);
+
+ Graph comparisonGraph = getComparisonGraph(referenceGraph, params);
+
+ return SearchGraphUtils.graphComparisonString(refName, comparisonGraph,
+ targetName, this.targetGraph, false);
}
/**
@@ -216,20 +131,26 @@ private void readObject(ObjectInputStream s)
s.defaultReadObject();
}
- private Parameters getParams() {
+ public Parameters getParams() {
return this.params;
}
- public ListcountOmissionErrors and countCommissionErrors.
*/
- public Misclassifications(MultipleGraphSource model1, MultipleGraphSource model2,
- Parameters params) {
+ public Misclassifications(GraphSource model1, GraphSource model2, Parameters params) {
if (params == null) {
throw new NullPointerException("Parameters must not be null");
}
- if (model1 instanceof VcpcRunner && model2 instanceof PcRunner) {
- this.usePcOutputs = true;
- setVcpcFields((VcpcRunner) model1);
- setPcFields((PcRunner) model2);
- }
-
- if ((model2 instanceof VcpcRunner && model1 instanceof PcRunner)) {
- this.usePcOutputs = true;
- setVcpcFields((VcpcRunner) model2);
- setPcFields((PcRunner) model1);
- }
-
- if (model1 instanceof VcpcRunner && model2 instanceof SampleVcpcRunner) {
- this.useSvcpcOutputs = true;
- setVcpcFields((VcpcRunner) model1);
- setSvcpcFields((SampleVcpcRunner) model2);
- }
-
- if ((model2 instanceof VcpcRunner && model1 instanceof SampleVcpcRunner)) {
- this.useSvcpcOutputs = true;
- setVcpcFields((VcpcRunner) model2);
- setSvcpcFields((SampleVcpcRunner) model1);
-
+ if (model1 == null || model2 == null) {
+ throw new NullPointerException("Null graph source>");
}
this.params = params;
String referenceName = params.getString("referenceGraphName", null);
- if (referenceName == null) {
- throw new IllegalArgumentException("Must specify a reference graph.");
- }
+ String model1Name = model1.getName();
+ String model2Name = model2.getName();
- if (referenceName.equals(model1.getName())) {
- if (model1 instanceof Simulation && model2 instanceof GeneralAlgorithmRunner) {
- this.referenceGraphs = ((GeneralAlgorithmRunner) model2).getCompareGraphs(model1.getGraphs());
- } else if (model1 instanceof MultipleGraphSource) {
- this.referenceGraphs = model1.getGraphs();
- }
-
- if (model2 instanceof MultipleGraphSource) {
- this.targetGraphs = model2.getGraphs();
- }
-
- if (this.referenceGraphs.size() == 1 && this.targetGraphs.size() > 1) {
- Graph graph = this.referenceGraphs.get(0);
- this.referenceGraphs = new ArrayList<>();
- this.referenceGraphs.addAll(this.targetGraphs);
- }
-
- if (this.targetGraphs.size() == 1 && this.referenceGraphs.size() > 1) {
- Graph graph = this.targetGraphs.get(0);
- this.targetGraphs = new ArrayList<>();
- for (Graph _graph : this.referenceGraphs) {
- this.targetGraphs.add(graph);
- }
- }
-
- if (this.referenceGraphs == null) {
- this.referenceGraphs = Collections.singletonList(((GraphSource) model1).getGraph());
- }
-
- if (this.targetGraphs == null) {
- this.targetGraphs = Collections.singletonList(((GraphSource) model2).getGraph());
- }
- } else if (referenceName.equals(model2.getName())) {
- if (model2 instanceof Simulation && model1 instanceof GeneralAlgorithmRunner) {
- this.referenceGraphs = ((GeneralAlgorithmRunner) model1).getCompareGraphs(model2.getGraphs());
- } else if (model1 instanceof MultipleGraphSource) {
- this.referenceGraphs = model2.getGraphs();
- }
-
- if (model1 instanceof MultipleGraphSource) {
- this.targetGraphs = model1.getGraphs();
- }
-
- if (this.referenceGraphs.size() == 1 && this.targetGraphs.size() > 1) {
- Graph graph = this.referenceGraphs.get(0);
- this.referenceGraphs = new ArrayList<>();
- this.referenceGraphs.addAll(this.targetGraphs);
- }
-
- if (this.targetGraphs.size() == 1 && this.referenceGraphs.size() > 1) {
- Graph graph = this.targetGraphs.get(0);
- this.targetGraphs = new ArrayList<>();
- for (Graph _graph : this.referenceGraphs) {
- this.targetGraphs.add(graph);
- }
- }
-
- if (this.referenceGraphs == null) {
- this.referenceGraphs = Collections.singletonList(((GraphSource) model2).getGraph());
- }
-
- if (this.targetGraphs == null) {
- this.targetGraphs = Collections.singletonList(((GraphSource) model1).getGraph());
- }
+ if (referenceName.equals(model1Name)) {
+ this.referenceGraph = model1.getGraph();
+ this.targetGraph = model2.getGraph();
+ } else if (referenceName.equals(model2Name)) {
+ this.referenceGraph = model2.getGraph();
+ this.targetGraph = model1.getGraph();
} else {
- throw new IllegalArgumentException(
- "Neither of the supplied session models is named '" +
- referenceName + "'.");
+ this.referenceGraph = model1.getGraph();
+ this.targetGraph = model2.getGraph();
}
- for (int i = 0; i < this.targetGraphs.size(); i++) {
- this.targetGraphs.set(i, GraphUtils.replaceNodes(this.targetGraphs.get(i), this.referenceGraphs.get(i).getNodes()));
- }
-
- if (this.algorithm != null) {
- for (int i = 0; i < this.referenceGraphs.size(); i++) {
- this.referenceGraphs.set(i, this.algorithm.getComparisonGraph(this.referenceGraphs.get(i)));
- }
- }
-
- if (this.referenceGraphs.size() != this.targetGraphs.size()) {
- throw new IllegalArgumentException("I was expecting the same number of graphs in each parent.");
- }
-
- TetradLogger.getInstance().
-
- log("info", "Graph Comparison");
-
- for (
- int i = 0;
- i < this.referenceGraphs.size(); i++) {
- TetradLogger.getInstance().log("comparison", "\nModel " + (i + 1));
- TetradLogger.getInstance().log("comparison", getComparisonString(i));
- }
-
- this.nf = NumberFormatUtil.getInstance().
-
- getNumberFormat();
-
- }
-
- private void setVcpcFields(VcpcRunner vcpc) {
- this.vcpcAdjacent = vcpc.getAdj();
- this.vcpcApparent = vcpc.getAppNon();
- this.vcpcDefinite = vcpc.getDefNon();
- this.vcpcNodes = vcpc.getGraph().getNodes();
- }
-
- private void setSvcpcFields(SampleVcpcRunner svcpc) {
- this.sVcpcAdjacent = svcpc.getAdj();
- this.sVcpcApparent = svcpc.getAppNon();
- this.sVcpcDefinite = svcpc.getDefNon();
- this.sVcpcNodes = svcpc.getGraph().getNodes();
- }
-
- private void setVcpcFastFields(VcpcFastRunner fvcpc) {
- this.fvcpcAdjacent = fvcpc.getAdj();
- SetsetFilter
+ * method.
+ *
+ * @author Kevin Bui
+ */
+public final class LongTextField extends JTextField {
+
+ /**
+ * The getModel value of the text field.
+ */
+ private long value;
+
+ /**
+ * If set, checks whether the given value should be accepted; otherwise, the
+ * old value will be reinstated. May be null.
+ */
+ private Filter filter;
+
+ //==========================CONSTRUCTORS=============================//
+ /**
+ * Constructs a new long text field displaying the given default value,
+ * restricting the value to [lowerBound, upperBound].
+ *
+ * @param value The initial value. Must be between lowerBound and
+ * upperBound.
+ * @param size the number of columns in the textfield.
+ */
+ public LongTextField(long value, int size) {
+ super(size);
+
+ setValue(value);
+ setText(Long.toString(value));
+
+ setHorizontalAlignment(SwingConstants.RIGHT);
+ addActionListener(new ActionListener() {
+
+ /**
+ * Reacts to somebody pressing the return key in this field by
+ * attempting to set the value displayed. If the value displayed
+ * cannot be set, the set value is reinstated.
+ */
+ public void actionPerformed(ActionEvent e) {
+ try {
+ long n = Long.parseLong(e.getActionCommand());
+ setValue(n);
+ } catch (NumberFormatException e1) {
+ setText(Long.toString(getValue()));
+ }
+ }
+ });
+
+ addFocusListener(new FocusAdapter() {
+ /**
+ * Nothing need be done when focus is gained, but this method is
+ * required by the FocusListener interface.
+ *
+ * @param e the event.
+ */
+ public void focusGained(FocusEvent e) {
+ LongTextField source = (LongTextField) e.getSource();
+ source.selectAll();
+ }
+
+ /**
+ * If focus is lost, attempt to store the text value being displayed
+ * as long; if this cannot be done, restore the previous value.
+ */
+ public void focusLost(FocusEvent e) {
+ try {
+ long n = Long.parseLong(getText());
+ setValue(n);
+ } catch (NumberFormatException e1) {
+ setText(Long.toString(getValue()));
+ }
+ }
+ });
+ }
+
+ //=============================PUBLIC METHODS=======================//
+ public void setUnfilteredValue(long value) {
+ setText(String.valueOf(value));
+ }
+
+ /**
+ * Sets the value of the text field to the given long value.
+ */
+ public void setValue(long value) {
+ if (value == this.value) {
+ return;
+ }
+
+ long newValue = filter(value, this.value);
+
+ if (newValue == this.value) {
+ setText(Long.toString(this.value));
+ } else {
+ this.value = newValue;
+ setText(Long.toString(this.value));
+ firePropertyChange("newValue", null, this.value);
+ }
+ }
+
+ /**
+ * @return the long value currently displayed.
+ */
+ public long getValue() {
+ return this.value;
+ }
+
+ /**
+ * Sets whether the given value should be accepted.
+ */
+ public void setFilter(Filter filter) {
+ this.filter = filter;
+ }
+
+ /**
+ * Convinces the text field to stay the right size in layouts that are
+ * trying to expand it like a balloon by returning the preferred size.
+ *
+ * @return the maximum size.
+ */
+ public Dimension getMaximumSize() {
+ return getPreferredSize();
+ }
+
+ /**
+ * Convinces the text field to stay the right size in layouts that are
+ * trying to shrink it.
+ *
+ * @return the maximum size.
+ */
+ public Dimension getMinimumSize() {
+ return getPreferredSize();
+ }
+
+ //==============================PRIVATE METHODS======================//
+ /**
+ * Determines whether the given value is a legal value for this text field.
+ * The default behavior is to constrain the value to be within a certain
+ * range--in other words, in the range [lower bound, upper bound]. For any
+ * other behavior, this method should be overridden. This method is called
+ * by default by the setLabel() method; it may become irrelevant if
+ * setLabel() is overridden in a way that doesn't make a call to
+ * checkValue().
+ */
+ private long filter(long value, long oldValue) {
+ if (this.filter == null) {
+ return value;
+ }
+
+ return this.filter.filter(value, oldValue);
+ }
+
+ //==============================Interfaces============================//
+ /**
+ * Filters the given value, returning the value that should actually be
+ * displayed. Typical use is to return either the value or the old value,
+ * depending on whether the value is in range, though more complicated uses
+ * are permitted. Side effects (such as storing the value in the process of
+ * filtering it) are permitted.
+ */
+ public interface Filter {
+
+ /**
+ * Filters the given value, returning the new value that should be
+ * displayed.
+ *
+ * @param value The value entered by the user.
+ * @param oldValue The value previously displayed, in case it needs to
+ * be reverted to.
+ */
+ long filter(long value, long oldValue);
+ }
+}
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/ParameterComponents.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/ParameterComponents.java
index 3e1e0992ca..cdeb362e3d 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/ParameterComponents.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/util/ParameterComponents.java
@@ -129,6 +129,35 @@ public static IntTextField getIntTextField(String parameter, Parameters paramete
return field;
}
+ public static LongTextField getLongTextField(String parameter, Parameters parameters,
+ long defaultValue, double lowerBound, double upperBound) {
+ LongTextField field = new LongTextField(parameters.getLong(parameter, defaultValue), 10);
+
+ field.setFilter((value, oldValue) -> {
+ if (value == field.getValue()) {
+ return oldValue;
+ }
+
+ if (value < lowerBound) {
+ return oldValue;
+ }
+
+ if (value > upperBound) {
+ return oldValue;
+ }
+
+ try {
+ parameters.set(parameter, value);
+ } catch (Exception e) {
+ // Ignore.
+ }
+
+ return value;
+ });
+
+ return field;
+ }
+
public static Box getBooleanSelectionBox(String parameter, Parameters parameters, boolean defaultValue) {
Box selectionBox = Box.createHorizontalBox();
@@ -203,6 +232,10 @@ private static Box createParameterComponent(String parameter, Parameters paramet
int lowerBoundInt = paramDesc.getLowerBoundInt();
int upperBoundInt = paramDesc.getUpperBoundInt();
component = ParameterComponents.getIntTextField(parameter, parameters, (Integer) defaultValue, lowerBoundInt, upperBoundInt);
+ } else if (defaultValue instanceof Long) {
+ int lowerBoundInt = paramDesc.getLowerBoundInt();
+ int upperBoundInt = paramDesc.getUpperBoundInt();
+ component = ParameterComponents.getLongTextField(parameter, parameters, (Long) defaultValue, lowerBoundInt, upperBoundInt);
} else if (defaultValue instanceof Boolean) {
component = ParameterComponents.getBooleanSelectionBox(parameter, parameters, (Boolean) defaultValue);
} else if (defaultValue instanceof String) {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/AbstractWorkbench.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/AbstractWorkbench.java
index eae2901f82..f9c0ca83d3 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/AbstractWorkbench.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/AbstractWorkbench.java
@@ -20,11 +20,10 @@
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.workbench;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.util.JOptionUtils;
import edu.cmu.tetradapp.model.SessionWrapper;
-import edu.cmu.tetradapp.util.CopyLayoutAction;
import edu.cmu.tetradapp.util.LayoutEditable;
import edu.cmu.tetradapp.util.PasteLayoutAction;
@@ -523,7 +522,6 @@ public final void setEdgeLabel(Edge modelEdge, JComponent label) {
/**
* Node tooltip to show the node attributes - Added by Kong
- *
*/
public final void setNodeToolTip(Node modelNode, String toolTipText) {
if (modelNode == null) {
@@ -539,7 +537,6 @@ public final void setNodeToolTip(Node modelNode, String toolTipText) {
/**
* Edge tooltip to show the edge type and probabilities - Added by Zhou
- *
*/
public final void setEdgeToolTip(Edge modelEdge, String toolTipText) {
if (modelEdge == null) {
@@ -841,7 +838,7 @@ public void layoutByGraph(Graph layoutGraph) {
// setGraphWithoutNotify(graph);
}
- public IKnowledge getKnowledge() {
+ public Knowledge getKnowledge() {
return null;
}
@@ -930,7 +927,7 @@ private void setGraphWithoutNotify(Graph graph) {
} else {
this.graph = graph;
- if (graph.isPag()) {
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
GraphUtils.addPagColoring(new EdgeListGraph(graph));
}
}
@@ -1178,7 +1175,9 @@ private void addEdge(Edge modelEdge) {
}
if (!getGraph().containsEdge(modelEdge)) {
- throw new IllegalArgumentException("Attempt to add edge not in model.");
+ System.out.println("Attempt to add edge not in model: " + modelEdge);
+ return;
+// throw new IllegalArgumentException("Attempt to add edge not in model.");
}
// construct a display edge for the model edge
@@ -1201,13 +1200,23 @@ private void addEdge(Edge modelEdge) {
displayEdge.setHighlighted(true);
}
- boolean bold = modelEdge.getProperties().contains(Edge.Property.dd) || modelEdge.isBold();
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
- Color lineColor = modelEdge.getProperties().contains(Edge.Property.nl) ? Color.green
- : this.graph.isHighlighted(modelEdge) ? displayEdge.getHighlightedColor() : modelEdge.getLineColor();
+ // visible edges.
+ boolean solid = modelEdge.getProperties().contains(Edge.Property.nl);
- displayEdge.setLineColor(lineColor);
- displayEdge.setBold(bold);
+ // definitely direct edges.
+ boolean thick = modelEdge.getProperties().contains(Edge.Property.dd);
+
+ // definitely direct edges.
+// Color green = Color.green.darker();
+// Color lineColor = modelEdge.getProperties().contains(Edge.Property.nl) ? green
+// : this.graph.isHighlighted(modelEdge) ? displayEdge.getHighlightedColor() : modelEdge.getLineColor();
+
+// displayEdge.setLineColor(lineColor);
+ displayEdge.setSolid(solid);
+ displayEdge.setThick(thick);
+ }
// Link the display edge to the model edge.
getModelEdgesToDisplay().put(modelEdge, displayEdge);
@@ -1783,6 +1792,10 @@ private void edgeClicked(Object source, MouseEvent e) {
graphEdge.setSelected(true);
}
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void nodeClicked(Object source, MouseEvent e) {
@@ -1805,6 +1818,10 @@ private void nodeClicked(Object source, MouseEvent e) {
selectConnectingEdges();
fireNodeSelection();
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void reorientEdge(Object source, MouseEvent e) {
@@ -1819,7 +1836,7 @@ private void reorientEdge(Object source, MouseEvent e) {
if (e.isShiftDown()) {
if (AbstractWorkbench.distance(point, pointA) < endpointRadius) {
toggleEndpoint(graphEdge, 1);
- firePropertyChange("modelChanged", null, null);
+ fireModelChanged();
} else if (AbstractWorkbench.distance(point, pointB) < endpointRadius) {
toggleEndpoint(graphEdge, 2);
firePropertyChange("modelChanged", null, null);
@@ -1833,6 +1850,14 @@ private void reorientEdge(Object source, MouseEvent e) {
firePropertyChange("modelChanged", null, null);
}
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
+ }
+
+ private void fireModelChanged() {
+ firePropertyChange("modelChanged", null, null);
}
private void handleMousePressed(MouseEvent e) {
@@ -1885,6 +1910,10 @@ private void handleMousePressed(MouseEvent e) {
break;
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void launchPopup(MouseEvent e) {
@@ -1926,6 +1955,10 @@ private void handleMouseReleased(MouseEvent e) {
finishEdge();
break;
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void handleMouseDragged(MouseEvent e) {
@@ -1951,6 +1984,10 @@ private void handleMouseDragged(MouseEvent e) {
dragNewEdge(source, newPoint);
break;
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
}
private void handleMouseEntered(MouseEvent e) {
@@ -1969,13 +2006,13 @@ private void handleMouseEntered(MouseEvent e) {
endpoint1 = "-";
break;
case "Arrow":
- endpoint1 = "<";
+ endpoint1 = "<";
break;
case "Circle":
endpoint1 = "o";
break;
case "Star":
- endpoint1 = "*";
+ endpoint1 = "*";
break;
case "Null":
endpoint1 = "Null";
@@ -1988,13 +2025,13 @@ private void handleMouseEntered(MouseEvent e) {
endpoint2 = "-";
break;
case "Arrow":
- endpoint2 = ">";
+ endpoint2 = ">";
break;
case "Circle":
endpoint2 = "o";
break;
case "Star":
- endpoint2 = "*";
+ endpoint2 = "*";
break;
case "Null":
endpoint2 = "Null";
@@ -2026,19 +2063,19 @@ private void handleMouseEntered(MouseEvent e) {
_type = "no edge";
break;
case ta:
- _type = "-->";
+ _type = "--?";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case at:
- _type = "<--";
+ _type = "<--";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case ca:
- _type = "o->";
+ _type = "o->";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case ac:
- _type = "<-o";
+ _type = "<-o";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case cc:
@@ -2046,7 +2083,7 @@ private void handleMouseEntered(MouseEvent e) {
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case aa:
- _type = "<->";
+ _type = "<->";
_type = nodes.get(0) + " " + _type + " " + nodes.get(1);
break;
case tt:
@@ -2236,17 +2273,28 @@ private void directEdge(IDisplayEdge graphEdge, int endpoint) {
try {
boolean added = getGraph().addEdge(newEdge);
+
if (!added) {
getGraph().addEdge(edge);
JOptionPane.showMessageDialog(JOptionUtils.centeringComp(),
"Reorienting that edge would violate graph constraints.");
}
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
} catch (IllegalArgumentException e) {
getGraph().addEdge(edge);
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
+
JOptionPane.showMessageDialog(JOptionUtils.centeringComp(),
"Reorienting that edge would violate graph constraints.");
}
+ revalidate();
repaint();
}
@@ -2290,6 +2338,11 @@ private void toggleEndpoint(IDisplayEdge graphEdge, int endpointNumber) {
boolean added = getGraph().addEdge(newEdge);
if (!added) {
getGraph().addEdge(edge);
+
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
+
return;
}
} catch (IllegalArgumentException e) {
@@ -2297,6 +2350,11 @@ private void toggleEndpoint(IDisplayEdge graphEdge, int endpointNumber) {
return;
}
+ if (graph.getGraphType() == EdgeListGraph.GraphType.PAG) {
+ GraphUtils.addPagColoring(new EdgeListGraph(graph));
+ }
+
+ revalidate();
repaint();
}
@@ -2350,6 +2408,15 @@ public void enableEditing(boolean enableEditing) {
setEnabled(enableEditing);
}
+ public void setPag(boolean pagColoring) {
+ if (pagColoring) {
+ this.graph.setGraphType(EdgeListGraph.GraphType.PAG);
+ } else {
+ this.graph.setGraphType(EdgeListGraph.GraphType.UNLABELED);
+ }
+ setGraph(graph);
+ }
+
/**
* This inner class is a simple wrapper for JComponents which are to serve
* as edge labels in the workbench. Its sole function is to make sure the
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/DisplayEdge.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/DisplayEdge.java
index 61b3b90b07..befe2b3a47 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/DisplayEdge.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/DisplayEdge.java
@@ -181,7 +181,7 @@ public class DisplayEdge extends JComponent implements IDisplayEdge {
/**
* The width of the stroke.
*/
- private float strokeWidth = 1f;
+ private float strokeWidth = 1.2f;
/**
* True iff this edge is highlighted.
@@ -198,7 +198,8 @@ public class DisplayEdge extends JComponent implements IDisplayEdge {
*/
private final PropertyChangeHandler propertyChangeHandler =
new PropertyChangeHandler();
- private boolean bold;
+ private boolean solid = true;
+ private boolean thick = false;
//==========================CONSTRUCTORS============================//
@@ -425,12 +426,16 @@ private void drawEdge(Graphics g) {
// width <= 1.0 seems to cause the problem, so we pick a stroke
// width slightly greater than 1.0. jdramsey 4/16/2005
// g2d.setStroke(new BasicStroke(1.000001f));
- BasicStroke s;
+ Stroke s;
+ float width = thick ? 2.5f : 1.1f;
- if (this.bold) {
- s = new BasicStroke(3.0f);
+ Stroke solid = new BasicStroke(width);
+ Stroke dashed = new BasicStroke(width, BasicStroke.CAP_BUTT, BasicStroke.JOIN_BEVEL, 0, new float[]{9}, 0);
+
+ if (this.solid) {
+ s = solid;
} else {
- s = new BasicStroke(getStrokeWidth() + 0.000001f);
+ s = dashed;
}
g2d.setStroke(s);
@@ -1029,12 +1034,17 @@ public void setLineColor(Color lineColor) {
}
}
- public boolean getBold() {
- return this.bold;
+ public boolean getSolid() {
+ return this.solid;
+ }
+
+ public void setSolid(boolean solid) {
+ this.solid = solid;
}
- public void setBold(boolean bold) {
- this.bold = bold;
+ @Override
+ public void setThick(boolean thick) {
+ this.thick = thick;
}
public Color getSelectedColor() {
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/GraphWorkbench.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/GraphWorkbench.java
index bf9cff7d04..e86540d10d 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/GraphWorkbench.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/GraphWorkbench.java
@@ -62,7 +62,7 @@ public GraphWorkbench() {
}
/**
- * Constructs a new workbench workbench for the given workbench model.
+ * Constructs a new workbench for the given graph model.
*/
public GraphWorkbench(Graph graph) {
super(graph);
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/IDisplayEdge.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/IDisplayEdge.java
index 478140fff5..6bcbff85c2 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/IDisplayEdge.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/IDisplayEdge.java
@@ -65,9 +65,11 @@ public interface IDisplayEdge {
void setLineColor(Color lineColor);
- boolean getBold();
+ boolean getSolid();
- void setBold(boolean bold);
+ void setSolid(boolean solid);
+
+ void setThick(boolean thick);
Color getSelectedColor();
diff --git a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/LayoutUtils.java b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/LayoutUtils.java
index a88e9f3161..7546d24b8f 100644
--- a/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/LayoutUtils.java
+++ b/tetrad-gui/src/main/java/edu/cmu/tetradapp/workbench/LayoutUtils.java
@@ -21,7 +21,7 @@
package edu.cmu.tetradapp.workbench;
-import edu.cmu.tetrad.data.IKnowledge;
+import edu.cmu.tetrad.data.Knowledge;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.SearchGraphUtils;
import edu.cmu.tetrad.util.JOptionUtils;
@@ -485,7 +485,7 @@ public static void knowledgeLayout(LayoutEditable layoutEditable) {
}
}
- IKnowledge knowledge = layoutEditable.getKnowledge();
+ Knowledge knowledge = layoutEditable.getKnowledge();
SearchGraphUtils.arrangeByKnowledgeTiers(graph, knowledge);
layoutEditable.layoutByGraph(graph);
} catch (Exception e1) {
diff --git a/tetrad-gui/src/main/resources/config/devConfig.xml b/tetrad-gui/src/main/resources/config/devConfig.xml
index e28f884017..19b66b4e89 100644
--- a/tetrad-gui/src/main/resources/config/devConfig.xml
+++ b/tetrad-gui/src/main/resources/config/devConfig.xml
@@ -943,17 +943,17 @@
Search Algorithms: MBFS |
+ Search Algorithms: PC-MB |
The MBFS search (Markov blanket fan Search) is designed to search for Markov blanket DAGs of
+ The PC-MB search is designed to search for Markov blanket DAGs of
target variables in datasets, under the assumptions of the PC algorithm--i.e., that the true causal graph over the
variables in the dataset does not contain any cycles, that there are no hidden common causes between variables in
the dataset, and that no relationship between variables in the dataset is deterministic. The Markov blanket of a
diff --git a/tetrad-gui/src/main/resources/resources/javahelp/manual/boxes/search/types_of_algorithms.html b/tetrad-gui/src/main/resources/resources/javahelp/manual/boxes/search/types_of_algorithms.html
index 39c19bf020..326d3a2327 100644
--- a/tetrad-gui/src/main/resources/resources/javahelp/manual/boxes/search/types_of_algorithms.html
+++ b/tetrad-gui/src/main/resources/resources/javahelp/manual/boxes/search/types_of_algorithms.html
@@ -32,7 +32,7 @@ Types of Algorithms
or the algorithm uses only conditional independence information as data.
For CPDAG algorithms, it is assumed that there are no latent common causes
in the model--that is, there can be latents, but there cannot be structures of
- the following form: X<-L->Y, where X and Y are measured and L is not.
+ the following form: X<~~L~~>Y, where X and Y are measured and L is not.