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Cap Featuretools at < 1.15.0#3775

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cap_ft_1_15
Oct 25, 2022
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Cap Featuretools at < 1.15.0#3775
chukarsten merged 4 commits into
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cap_ft_1_15

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@jeremyliweishih jeremyliweishih commented Oct 24, 2022

Cap featuretools at < 1.15.0 until we can address the failures in #3774 due do dependency incompatibility.

@jeremyliweishih jeremyliweishih marked this pull request as ready for review October 24, 2022 22:01
@jeremyliweishih jeremyliweishih enabled auto-merge (squash) October 24, 2022 22:11
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codecov Bot commented Oct 24, 2022

Codecov Report

Merging #3775 (ccb0429) into main (5c4e5c0) will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff          @@
##            main   #3775   +/-   ##
=====================================
  Coverage   99.7%   99.7%           
=====================================
  Files        341     341           
  Lines      35287   35287           
=====================================
  Hits       35155   35155           
  Misses       132     132           

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@chukarsten chukarsten disabled auto-merge October 25, 2022 03:58
@chukarsten chukarsten merged commit f3e2a19 into main Oct 25, 2022
@chukarsten chukarsten deleted the cap_ft_1_15 branch October 25, 2022 03:59
chukarsten pushed a commit that referenced this pull request Oct 25, 2022
* cap featuretools

* RL

* Cap nlp primitives as well

* Fix conda
chukarsten added a commit that referenced this pull request Oct 25, 2022
* fit and transform are working.  inverse_transform in sample works.

* Got inverse_transform tests working.

* Changed the inverse_transform() variables to match each other in the different classes.  Moved the test to project the seasonal signal up to the parent Decomposer class.  Moved the testing for the seasonal projection to the decomposer test module.

* Added basic get_trend_df() to STLDecomposer.  Moved testing up into Decomposer.

* Moved the .set_period() tests up to the parent class.

* Moved .determine_periodicity() tests and functionality up to the base class.

* Changed the way we detect whether Decomposer has been fit.  Still need to move that up to the base Decomposer class.

* Transform out of sample should work.

* Transform handles partially in and out of sample data

* Stl decomposer kc (#3747)

* Updated get_trend_df() to work out of sample.

* Fixed transform() to work with in sample, but not spanning the sample.

* Fixed inverse_transform to work with smaller than sample, in sample data.

* Updated STL get_trend_dataframe() tests to work on less than full sample.  Also updated test for transform to return same if y is None and moved that to parent class.

* Refactored Decomposer tests to all iterate across the two decomposers.

* I forget

* Removed unused test parameterization.

* Moved plot function up to parent class.

* Updated base_meta to handle the new get_trend_df() function to check for fit.

* Docstring for init, release notes, test for  auto changing of seasonal_period.

* Changed Decomposer's _build_seasonal_signal to _project_seasonal to better reflect what's going on.  Docstring changes.

* Refactored the checking for y to be None into the base class.

* Moved .fit_transform() up to parent class.

* Adjusted the PolynomialDecomposer to also save the seasonality and the seasonal sample to match the STLDecomposer.

* Backed out the check_target changes.

* Docstring adjustments for inverse_transform.

* Removed commented code.

* Boiler plate tests for test_components and test_utils.

* Added the type annotations import to decomposer.py

* Lint and swapped seasonal&seasonality.

* Code cov.

* Removed unused code.

* Removed some untested code and added more annotations.

* Added type annotations to Decomposer.py

* Removed flaky CI test case for STLDecomposer.

* Update evalml/pipelines/components/transformers/preprocessing/stl_decomposer.py

Co-authored-by: Becca McBrayer <becca.mcbrayer@alteryx.com>

* Lint.

* Added some testing for out of sample target data partially in the past.

* Added some testing for out of sample target data partially in the past.

* Addressed Jeremy's comments and fixed comment about wholly in-sample data.

* Removed traces of polynomial.

* Cleaned up import.

* Empty-Commit

* Added a quick test to trigger errors in the underlying statsmodels STL decomposer.

* Addressed Parthiv's comments.

* Karsten - test.

* Updated the STL Decomposer to run with integer indices.

* Lint

* Removed raise e

* Made inverse_transform of STLDecomposer work with integer indices.

* Made inverse_transform test run with integer index and fixed probable bug in forecasting the trend

* Removed automl local test again.

* Test coverage

* Comments and removed unnecessary TODO.

* Addressed Becca's comments.

* Fixed index test that somehow got broken.

* Typos.

* Update stl seasonal period after fitting

* Update index finding in _project_seasonal

* Updated becca's change to transform_first_ind to be general for the periodicity.

* Addressed Parthiv's comment to add in the original index into the PolynomialDecomposer.

* Save last seasonal period instead of first

* Becca's comments addressed.

* Cap Featuretools at < 1.15.0 (#3775)

* cap featuretools

* RL

* Cap nlp primitives as well

* Fix conda

* Docstring for init, release notes, test for  auto changing of seasonal_period.

* Empty-Commit

* Removed additional test.

Co-authored-by: Becca McBrayer <becca.mcbrayer@alteryx.com>
Co-authored-by: Jeremy Shih <jeremyliweishih@gmail.com>
@chukarsten chukarsten mentioned this pull request Oct 26, 2022
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2 participants