Releases: sdv-dev/SDV
v0.17.0 - 2022-09-09
This release updates the code to use RDT version 1.2.0 and greater, so that those new features are now available in SDV. This changes the transformers that are available in SDV models to be those that are in RDT version 1.2.0. As a result, some arguments for initializing models have changed.
Additionally, this release fixes bugs related to loading models with custom constraints. It also fixes a bug that added NaNs
to the index of sampled data when using sample_remaining_columns
.
Bugs Fixed
- Incorrect rounding in Custom Constraint example - Issue #941 by @amontanez24
- Can't save the model if use the custom constraint - Issue #928 by @pvk-developer
- User Guide code fixes - Issue #983 by @amontanez24
- Index contains NaNs when using sample_remaining_columns - Issue #985 by @amontanez24
- Cannot sample after loading a model with custom constraints: TypeError - Issue #984 by @pvk-developer
- Set HyperTransformer config manually, based on Metadata if given - Issue #982 by @pvk-developer
New Features
Maintenance
- Update the RDT version to 1.0 - Issue #897 by @pvk-developer
v0.16.0 - 2022-07-21
This release brings user friendly improvements and bug fixes on the SDV
constraints, to help
users generate their synthetic data easily.
Some predefined constraints have been renamed and redefined to be more user friendly & consistent.
The custom constraint API has also been updated for usability. The SDV now automatically determines
the best handling_strategy
to use for each constraint, attempting transform
by default and
falling back to reject_sampling
otherwise. The handling_strategy
parameters are no longer
included in the API.
Finally, this version of SDV
also unifies the parameters for all sampling related methods for
all models (including TabularPreset).
Changes to Constraints
-
GreatherThan
constraint is now separated in two new constraints:Inequality
, which is
intended to be used between two columns, andScalarInequality
, which is intended to be used
between a column and a scalar. -
Between
constraint is now separated in two new constraints:Range
, which is intended to
be used between three columns, andScalarRange
, which is intended to be used between a column
and low and high scalar values. -
FixedIncrements
a new constraint that makes the data increment by a certain value. -
New
create_custom_constraint
function available to create custom constraints.
Removed Constraints
Rounding
Rounding is automatically being handled by therdt.HyperTransformer
.ColumnFormula
thecreate_custom_constraint
takes place over this one and allows more
advanced usage for the end users.
New Features
- Improve error message for invalid constraints - Issue #801 by @fealho
- Numerical Instability in Constrained GaussianCopula - Issue #806 by @fealho
- Unify sampling params for reject sampling - Issue #809 by @amontanez24
- Split
GreaterThan
constraint intoInequality
andScalarInequality
- Issue #814 by @fealho - Split
Between
constraint intoRange
andScalarRange
- Issue #815 @pvk-developer - Change
columns
tocolumn_names
inOneHotEncoding
andUnique
constraints - Issue #816 by @amontanez24 - Update columns parameter in
Positive
andNegative
constraint - Issue #817 by @fealho - Create
FixedIncrements
constraint - Issue #818 by @amontanez24 - Improve datetime handling in
ScalarInequality
andScalarRange
constraints - Issue #819 by @pvk-developer - Support strict boundaries even when transform strategy is used - Issue #820 by @fealho
- Add
create_custom_constraint
factory method - Issue #836 by @fealho
Internal Improvements
- Remove
handling_strategy
parameter - Issue #833 by @amontanez24 - Remove
fit_columns_model
parameter - Issue #834 by @pvk-developer - Remove the
ColumnFormula
constraint - Issue #837 by @amontanez24 - Move
table_data.copy
to base class of constraints - Issue #845 by @fealho
Bugs Fixed
- Numerical Instability in Constrained GaussianCopula - Issue #801 by @tlranda and @fealho
- Fix error message for
FixedIncrements
- Issue #865 by @pvk-developer - Fix constraints with conditional sampling - Issue #866 by @amontanez24
- Fix error message in
ScalarInequality
- Issue #868 by @pvk-developer - Cannot use
max_tries_per_batch
on sample:TypeError: sample() got an unexpected keyword argument 'max_tries_per_batch'
- Issue #885 by @amontanez24 - Conditional sampling + batch size:
ValueError: Length of values (1) does not match length of index (5)
- Issue #886 by @amontanez24 TabularPreset
doesn't support new sampling parameters - Issue #887 by @fealho- Conditional Sampling:
batch_size
is being set toNone
by default? - Issue #889 by @amontanez24 - Conditional sampling using GaussianCopula inefficient when categories are noised - Issue #910 by @amontanez24
Documentation Changes
- Show the
API
forTabularPreset
models - Issue #854 by @katxiao - Update handling constraints doc - Pull Request #856 by @amontanez24
- Update custom costraints documentation - Pull Request #857 by @pvk-developer
v0.15.0 - 2022-05-25
This release improves the speed of the GaussianCopula
model by removing logic that previously searched for the appropriate distribution to use. It also fixes a bug that was happening when conditional sampling was used with the TabularPreset
.
The rest of the release focuses on making changes to improve constraints including changing the UniqueCombinations
constraint to FixedCombinations
, making the Unique
constraint work with missing values and erroring when null values are seen in the OneHotEncoding
constraint.
New Features
- Silence warnings coming from univariate fit in copulas - Issue #769 by @pvk-developer
- Remove parameters related to distribution search and change default - Issue #767 by @fealho
- Update the UniqueCombinations constraint - Issue #793 by @fealho
- Make Unique constraint works with nans - Issue #797 by @fealho
- Error out if nans in OneHotEncoding - Issue #800 by @amontanez24
Bugs Fixed
Documentation Changes
v0.14.1 - 2022-05-03
This release adds a TabularPreset
, available in the sdv.lite
module, which allows users to easily optimize a tabular model for speed.
In this release, we also include bug fixes for sampling with conditions, an unresolved warning, and setting field distributions. Finally,
we include documentation updates for sampling and the new TabularPreset
.
Bugs Fixed
- Sampling with conditions={column: 0.0} for float columns doesn't work - Issue #525 by @shlomihod and @tssbas
- resolved FutureWarning with Pandas replaced append by concat - Issue #759 by @Deathn0t
- Field distributions bug in CopulaGAN - Issue #747 by @katxiao
- Field distributions bug in GaussianCopula - Issue #746 by @katxiao
New Features
- Set default transformer to categorical_fuzzy - Issue #768 by @amontanez24
- Model nulls normally when tabular preset has constraints - Issue #764 by @katxiao
- Don't modify my metadata object - Issue #754 by @amontanez24
- Presets should be able to handle constraints - Issue #753 by @katxiao
- Change preset optimize_for --> name - Issue #749 by @katxiao
- Create a speed optimized Preset - Issue #716 by @katxiao
Documentation Changes
v0.14.0 - 2022-03-21
This release updates the sampling API and splits the existing functionality into three methods - sample
, sample_conditions
,
and sample_remaining_columns
. We also add support for sampling in batches, displaying a progress bar when sampling with more than one batch,
sampling deterministically, and writing the sampled results to an output file. Finally, we include fixes for sampling with conditions
and updates to the documentation.
Bugs Fixed
- Fix write to file in sampling - Issue #732 by @katxiao
- Conditional sampling doesn't work if the model has a CustomConstraint - Issue #696 by @katxiao
New Features
- Updates to GaussianCopula conditional sampling methods - Issue #729 by @katxiao
- Update conditional sampling errors - Issue #730 by @katxiao
- Enable Batch Sampling + Progress Bar - Issue #693 by @katxiao
- Create sample_remaining_columns() method - Issue #692 by @katxiao
- Create sample_conditions() method - Issue #691 by @katxiao
- Improve sample() method - Issue #690 by @katxiao
- Create Condition object - Issue #689 by @katxiao
- Is it possible to generate data with new set of primary keys? - Issue #686 by @katxiao
- No way to fix the random seed? - Issue #157 by @katxiao
- Can you set a random state for the sdv.tabular.ctgan.CTGAN.sample method? - Issue #515 by @katxiao
- generating different synthetic data while training the model multiple times. - Issue #299 by @katxiao
Documentation Changes
v0.13.1 - 2021-12-22
This release adds support for passing tabular constraints to the HMA1 model, and adds more explicit error handling for
metric evaluation. It also includes a fix for using categorical columns in the PAR model and documentation updates
for metadata and HMA1.
Bugs Fixed
New Features
- Support passing tabular constraints to the HMA1 model - Issue #296 by @katxiao
- Metric evaluation error handling metrics - Issue #638 by @katxiao
Documentation Changes
v0.13.0 - 2021-11-22
This release makes multiple improvements to different Constraint
classes. The Unique
constraint can now
handle columns with the name index
and no longer crashes on subsets of the original data. The Between
constraint can now handle columns with nulls properly. The memory of all constraints was also improved.
Various other features and fixes were added. Conditional sampling no longer crashes when the num_rows
argument
is not provided. Multiple localizations can now be used for PII fields. Scaffolding for integration tests was added
and the workflows now run pip check
.
Additionally, this release adds support for Python 3.9!
Bugs Fixed
- Gaussian Copula – Memory Issue in Release 0.10.0 - Issue #459 by @xamm
- Applying Unique Constraint errors when calling model.fit() on a subset of data - Issue #610 by @xamm
- Calling sampling with conditions and without num_rows crashes - Issue #614 by @xamm
- Metadata.visualize with path parameter throws AttributeError - Issue #634 by @xamm
- The Unique constraint crashes when the data contains a column called index - Issue #616 by @xamm
- The Unique constraint cannot handle non-default index - Issue #617 by @xamm
- ConstraintsNotMetError when applying Between constraint on datetime columns containing null values - Issue #632 by @katxiao
New Features
Housekeeping Tasks
- Support latest version of Faker - Issue #621 by @katxiao
- Add scaffolding for Metadata integration tests - Issue #624 by @katxiao
- Add support for Python 3.9 - Issue #631 by @amontanez24
Internal Improvements
- Add pip check to CI workflows - Issue #626 by @pvk-developer
Documentation Changes
Special thanks to @xamm, @katxiao, @pvk-developer and @amontanez24 for all the work that made this release possible!
v0.12.1 - 2021-10-12
This release fixes bugs in constraints, metadata behavior, and SDV documentation. Specifically, we added
proper handling of data containing null values for constraints and timeseries data, and updated the
default metadata detection behavior.
Bugs Fixed
- ValueError: The parameter loc has invalid values - Issue #353 by @fealho
- Gaussian Copula is generating different data with metadata and without metadata - Issue #576 by @katxiao
- Make pomegranate an optional dependency - Issue #567 by @katxiao
- Small wording change for Question Issue Template - Issue #571 by @katxiao
- ConstraintsNotMetError when using GreaterThan constraint with datetime - Issue #590 by @katxiao
- GreaterThan constraint crashing with NaN values - Issue #592 by @katxiao
- Null values in GreaterThan constraint raises error - Issue #589 by @katxiao
- ColumnFormula raises ConstraintsNotMetError when checking NaN values - Issue #593 by @katxiao
- GreaterThan constraint raises TypeError when using datetime - Issue #596 by @katxiao
- Fix repository language - Issue #464 by @fealho
- Update init.py - Issue #578 by @dyuliu
- IndexingError: Unalignable boolean - Issue #446 by @fealho
v0.12.0 - 2021-08-17
This release focuses on improving and expanding upon the existing constraints. More specifically, the users can now
(1) specify multiple columns in Positive
and Negative
constraints, (2) use the new Unique
constraint and
(3) use datetime data with the Between
constraint. Additionaly, error messages have been added and updated
to provide more useful feedback to the user.
Besides the added features, several bugs regarding the UniqueCombinations
and ColumnFormula
constraints have been fixed,
and an error in the metadata.json for the student_placements
dataset was corrected. The release also added documentation
for the fit_columns_model
which affects the majority of the available constraints.
New Features
- Change default fit_columns_model to False - Issue #550 by @katxiao
- Support multi-column specification for positive and negative constraint - Issue #545 by @sarahmish
- Raise error when multiple constraints can't be enforced - Issue #541 by @amontanez24
- Create Unique Constraint - Issue #532 by @amontanez24
- Passing invalid conditions when using constraints produces unreadable errors - Issue #511 by @katxiao
- Improve error message for ColumnFormula constraint when constraint column used in formula - Issue #508 by @katxiao
- Add datetime functionality to Between constraint - Issue #504 by @katxiao
Bugs Fixed
- UniqueCombinations constraint with handling_strategy = 'transform' yields synthetic data with nan values - Issue #521 by @katxiao and @csala
- UniqueCombinations constraint outputting wrong data type - Issue #510 by @katxiao and @csala
- UniqueCombinations constraint on only one column gets stuck in an infinite loop - Issue #509 by @katxiao
- Conditioning on a non-constraint column using the ColumnFormula constraint - Issue #507 by @katxiao
- Conditioning on the constraint column of the ColumnFormula constraint - Issue #506 by @katxiao
- Update metadata.json for duration of student_placements dataset - Issue #503 by @amontanez24
- Unit test for HMA1 when working with a single child row per parent row - Issue #497 by @pvk-developer
- UniqueCombinations constraint for more than 2 columns - Issue #494 by @katxiao and @csala
Documentation Changes
v0.11.0 - 2021-07-12
This release primarily addresses bugs and feature requests related to using constraints for the single-table models. Users can now enforce scalar comparison with the existing GreaterThan
constraint and apply 5 new constraints: OneHotEncoding
, Positive
, Negative
, Between
and Rounding
. Additionally, the SDV will now auto-apply constraints for rounding numerical values, and for keeping the data within the observed bounds. All related user guides are updated with the new functionality.
New Features
- Add OneHotEncoding Constraint - Issue #303 by @fealho
- GreaterThan Constraint should apply to scalars - Issue #410 by @amontanez24
- Improve GreaterThan constraint - Issue #368 by @amontanez24
- Add Non-negative and Positive constraints across multiple columns- Issue #409 by @amontanez24
- Add Between values constraint - Issue #367 by @fealho
- Ensure values fall within the specified range - Issue #423 by @amontanez24
- Add Rounding constraint - Issue #482 by @katxiao
- Add rounding and min/max arguments that are passed down to the NumericalTransformer - Issue #491 by @amontanez24
Bugs Fixed
- GreaterThan constraint between Date columns rasises TypeError - Issue #421 by @amontanez24
- GreaterThan constraint's transform strategy fails on columns that are not float - Issue #448 by @amontanez24
- AttributeError on UniqueCombinations constraint with non-strings - Issue #196 by @katxiao
- Use reject sampling to sample missing columns for constraints - Issue #435 by @amontanez24