Feature/add global error to predict multistep

.githooks/pre-commit.sh

@@ -0,0 +1,83 @@
+#!/usr/bin/env bash
+
+# Git pre-commit hook to check staged Python files for formatting issues with
+# yapf.
+#
+# INSTALLING: Copy this script into `.git/hooks/pre-commit`, and mark it as
+# executable.
+#
+# This requires that yapf is installed and runnable in the environment running
+# the pre-commit hook.
+#
+# When running, this first checks for unstaged changes to staged files, and if
+# there are any, it will exit with an error. Files with unstaged changes will be
+# printed.
+#
+# If all staged files have no unstaged changes, it will run yapf against them,
+# leaving the formatting changes unstaged. Changed files will be printed.
+#
+# BUGS: This does not leave staged changes alone when used with the -a flag to
+# git commit, due to the fact that git stages ALL unstaged files when that flag
+# is used.
+
+# Find all staged Python files, and exit early if there aren't any.
+PYTHON_FILES=()
+while IFS=$'\n' read -r line; do PYTHON_FILES+=("$line"); done \
+  < <(git diff --name-only --cached --diff-filter=AM | grep --color=never '.py$')
+if [ ${#PYTHON_FILES[@]} -eq 0 ]; then
+  exit 0
+fi
+
+########## PIP VERSION #############
+# Verify that yapf is installed; if not, warn and exit.
+if ! command -v yapf >/dev/null; then
+  echo 'yapf not on path; can not format. Please install yapf:'
+  echo '    pip install yapf'
+  exit 2
+fi
+######### END PIP VERSION ##########
+
+########## PIPENV VERSION ##########
+# if ! pipenv run yapf --version 2>/dev/null 2>&1; then
+#   echo 'yapf not on path; can not format. Please install yapf:'
+#   echo '    pipenv install yapf'
+#   exit 2
+# fi
+###### END PIPENV VERSION ##########
+
+
+# Check for unstaged changes to files in the index.
+CHANGED_FILES=()
+while IFS=$'\n' read -r line; do CHANGED_FILES+=("$line"); done \
+  < <(git diff --name-only "${PYTHON_FILES[@]}")
+if [ ${#CHANGED_FILES[@]} -gt 0 ]; then
+  echo 'You have unstaged changes to some files in your commit; skipping '
+  echo 'auto-format. Please stage, stash, or revert these changes. You may '
+  echo 'find `git stash -k` helpful here.'
+  echo 'Files with unstaged changes:' "${CHANGED_FILES[@]}"
+  exit 1
+fi
+
+# Format all staged files, then exit with an error code if any have uncommitted
+# changes.
+echo 'Formatting staged Python files . . .'
+
+########## PIP VERSION #############
+yapf -i -r "${PYTHON_FILES[@]}"
+######### END PIP VERSION ##########
+
+########## PIPENV VERSION ##########
+# pipenv run yapf -i -r "${PYTHON_FILES[@]}"
+###### END PIPENV VERSION ##########
+
+
+CHANGED_FILES=()
+while IFS=$'\n' read -r line; do CHANGED_FILES+=("$line"); done \
+  < <(git diff --name-only "${PYTHON_FILES[@]}")
+if [ ${#CHANGED_FILES[@]} -gt 0 ]; then
+  echo 'Reformatted staged files. Please review and stage the changes.'
+  echo 'Files updated: ' "${CHANGED_FILES[@]}"
+  exit 1
+else
+  exit 0
+fi

.github/workflows/check-formatting.yml

@@ -0,0 +1,12 @@
+name: Check formatting
+on: [push]
+jobs:
+  formatting-check:
+    name: Formatting Check
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v2
+    - name: run YAPF to test if python code is correctly formatted
+      uses: AlexanderMelde/yapf-action@master
+      with:
+        args: --verbose

.isort.cfg

@@ -0,0 +1,3 @@
+[isort]
+multi_line_output=3
+include_trailing_comma = true

.mypy.ini

@@ -1,29 +1,4 @@
 [mypy]
 
 # https://mypy.readthedocs.io/en/stable/running_mypy.html#missing-imports
-[mypy-sklearn.*]
-ignore_missing_imports = True
-
-[mypy-abc]
-ignore_missing_imports = True
-
-[mypy-pandas]
-ignore_missing_imports = True
-
-[mypy-scipy]
-ignore_missing_imports = True
-
-[mypy-scipy.*]
-ignore_missing_imports = True
-
-[mypy-joblib]
-ignore_missing_imports = True
-
-[mypy-picos]
-ignore_missing_imports = True
-
-[mypy-optht]
-ignore_missing_imports = True
-
-[mypy-pytest]
 ignore_missing_imports = True

README.rst

@@ -130,6 +130,16 @@ The documentation can be compiled using
     $ cd doc
     $ make html
 
+If you want a hook to check source code formatting before allowing a commit,
+you can use
+
+.. code-block:: sh
+
+   $ cd .git/hooks/
+   $ ln -s ../../.githooks/pre-commit.sh .
+   $ chmod +x ./pre-commit.sh
+
+You will need ``yapf`` installed for this.
 
 Related packages
 ================

constraints.txt

@@ -4,6 +4,7 @@ scikit-learn>=1.0.1
 PICOS>=2.2.52
 pandas>=1.3.1
 optht>=0.2.0
+Deprecated>=1.2.13
 
 pytest
 matplotlib

doc/conf.py

@@ -12,16 +12,15 @@
 #
 import os
 import sys
-sys.path.insert(0, os.path.abspath('../'))
 
+sys.path.insert(0, os.path.abspath('../'))
 
 # -- Project information -----------------------------------------------------
 
 project = 'pykoop'
 copyright = '2021, Steven Dahdah'
 author = 'Steven Dahdah'
 
-
 # -- General configuration ---------------------------------------------------
 
 # Add any Sphinx extension module names here, as strings. They can be
@@ -49,7 +48,6 @@
 # This pattern also affects html_static_path and html_extra_path.
 exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
 
-
 # -- Options for HTML output -------------------------------------------------
 
 # The theme to use for HTML and HTML Help pages.  See the documentation for

doc/index.rst

@@ -136,6 +136,16 @@ The documentation can be compiled using
     $ cd doc
     $ make html
 
+If you want a hook to check source code formatting before allowing a commit,
+you can use
+
+.. code-block:: sh
+
+   $ cd .git/hooks/
+   $ ln -s ../../.githooks/pre-commit.sh .
+   $ chmod +x ./pre-commit.sh
+
+You will need ``yapf`` installed for this.
 
 Related packages
 ================
@@ -182,7 +192,10 @@ References
 .. [bilinear] Daniel Bruder, Xun Fu, and Ram Vasudevan. "Advantages of bilinear
    Koopman realizations for the modeling and control of systems with unknown
    dynamics." arXiv:2010.09961v3 [cs.RO] (2020).
-   https://arxiv.org/abs/2010.09961v3
+.. [local] Giorgos Mamakoukas, Ian Abraham, and Todd D. Murphey. "Learning
+   Stable Models for Prediction and Control." arXiv:2005.04291v2 [cs.RO]
+   (2022). https://arxiv.org/abs/2005.04291v2  https://arxiv.org/abs/2010.09961v3
+.. [scorers] https://scikit-learn.org/stable/modules/model_evaluation.html
 
 Citation
 ========

examples/example_pipeline_vdp.py

@@ -0,0 +1,142 @@
+"""Example of how to use the Koopman pipeline."""
+
+import numpy as np
+from matplotlib import pyplot as plt
+
+import pykoop
+import pykoop.dynamic_models
+
+
+def main() -> None:
+    """Demonstrate how to use the Koopman pipeline."""
+    # Get sample data
+    X_vdp = pykoop.example_data_vdp()
+
+    # Create pipeline
+    kp = pykoop.KoopmanPipeline(
+        lifting_functions=[(
+            'sp',
+            pykoop.SplitPipeline(
+                lifting_functions_state=[
+                    ('pl', pykoop.PolynomialLiftingFn(order=3))
+                ],
+                lifting_functions_input=None,
+            ),
+        )],
+        regressor=pykoop.Edmd(),
+    )
+
+    # Take last episode for validation
+    X_train = X_vdp[X_vdp[:, 0] < 4]
+    X_valid = X_vdp[X_vdp[:, 0] == 4]
+
+    # Fit the pipeline
+    kp.fit(X_train, n_inputs=1, episode_feature=True)
+
+    # Extract initial conditions and input from validation episode
+    x0 = X_valid[[0], 1:3]
+    u = X_valid[:, 3:]
+
+    # Predict with re-lifting between timesteps (default)
+    X_pred_local = kp.predict_state(
+        x0,
+        u,
+        relift_state=True,
+        episode_feature=False,
+    )
+
+    # Predict without re-lifting between timesteps
+    X_pred_global = kp.predict_state(
+        x0,
+        u,
+        relift_state=False,
+        episode_feature=False,
+    )
+
+    # Plot trajectories in phase space
+    fig, ax = plt.subplots(constrained_layout=True)
+    ax.plot(
+        X_valid[:, 1],
+        X_valid[:, 2],
+        label='True trajectory',
+    )
+    ax.plot(
+        X_pred_local[:, 0],
+        X_pred_local[:, 1],
+        '--',
+        label='Local prediction',
+    )
+    ax.plot(
+        X_pred_global[:, 0],
+        X_pred_global[:, 1],
+        '--',
+        label='Global prediction',
+    )
+    ax.set_xlabel('$x_1[k]$')
+    ax.set_ylabel('$x_2[k]$')
+    ax.legend()
+    ax.grid(linestyle='--')
+
+    # Lift validation set
+    Psi_valid = kp.lift(X_valid[:, 1:], episode_feature=False)
+
+    # Predict lifted state with re-lifting between timesteps (default)
+    Psi_pred_local = kp.predict_state(
+        x0,
+        u,
+        relift_state=True,
+        return_lifted=True,
+        return_input=True,
+        episode_feature=False,
+    )
+
+    # Predict lifted state without re-lifting between timesteps
+    Psi_pred_global = kp.predict_state(
+        x0,
+        u,
+        relift_state=False,
+        return_lifted=True,
+        return_input=True,
+        episode_feature=False,
+    )
+
+    fig, ax = plt.subplots(
+        kp.n_states_out_,
+        1,
+        constrained_layout=True,
+        sharex=True,
+        squeeze=False,
+    )
+    for i in range(ax.shape[0]):
+        ax[i, 0].plot(Psi_valid[:, i], label='True trajectory')
+        ax[i, 0].plot(Psi_pred_local[:, i], '--', label='Local prediction')
+        ax[i, 0].plot(Psi_pred_global[:, i], '--', label='Global prediction')
+        ax[i, 0].grid(linestyle='--')
+        ax[i, 0].set_ylabel(rf'$\vartheta_{i + 1}[k]$')
+
+    ax[-1, 0].set_xlabel('$k$')
+    ax[0, 0].legend()
+
+    fig, ax = plt.subplots(
+        kp.n_inputs_out_,
+        1,
+        constrained_layout=True,
+        sharex=True,
+        squeeze=False,
+    )
+    for i in range(ax.shape[0]):
+        j = kp.n_states_out_ + i
+        ax[i, 0].plot(Psi_valid[:, j], label='True trajectory')
+        ax[i, 0].plot(Psi_pred_local[:, j], '--', label='Local prediction')
+        ax[i, 0].plot(Psi_pred_global[:, j], '--', label='Global prediction')
+        ax[i, 0].grid(linestyle='--')
+
+    ax[-1, 0].set_xlabel('$k$')
+    ax[0, 0].legend()
+    ax[0, 0].set_ylabel('$u[k]$')
+
+    plt.show()
+
+
+if __name__ == '__main__':
+    main()

pykoop/__init__.py

@@ -1,13 +1,32 @@
 """Koopman operator identification library in Python."""
 
-from .koopman_pipeline import (EpisodeDependentLiftingFn,
-                               EpisodeIndependentLiftingFn, KoopmanLiftingFn,
-                               KoopmanPipeline, KoopmanRegressor,
-                               SplitPipeline, combine_episodes, shift_episodes,
-                               split_episodes, strip_initial_conditions)
-from .lifting_functions import (BilinearInputLiftingFn, DelayLiftingFn,
-                                PolynomialLiftingFn, SkLearnLiftingFn)
+from .koopman_pipeline import (
+    EpisodeDependentLiftingFn,
+    EpisodeIndependentLiftingFn,
+    KoopmanLiftingFn,
+    KoopmanPipeline,
+    KoopmanRegressor,
+    SplitPipeline,
+    combine_episodes,
+    extract_initial_conditions,
+    extract_input,
+    score_state,
+    shift_episodes,
+    split_episodes,
+    strip_initial_conditions,
+)
+from .lifting_functions import (
+    BilinearInputLiftingFn,
+    DelayLiftingFn,
+    PolynomialLiftingFn,
+    SkLearnLiftingFn,
+)
 from .regressors import Dmd, Dmdc, Edmd
 from .tsvd import Tsvd
-from .util import (AnglePreprocessor, example_data_msd, random_input,
-                   random_state)
+from .util import (
+    AnglePreprocessor,
+    example_data_msd,
+    example_data_vdp,
+    random_input,
+    random_state,
+)