Citrine

This release includes new functionality around pulling ingredient labels into models and generating features from chemical formulas.

What's New
* Including ingredient labels in a table is now easier. With IngredientLabelsSetByProcessAndName and IngredientLabelsSetInOutput, users can now include all labels from an ingredient (using the ConcatColumn) in one cell rather than a series of Booleans to describe their presence of absence. (576, 580)

Improvements
* `build_mean_feature_property_predictors()`, a builder method that makes it easier for a graphical model calculate the mean of featurized properties, now accepts a `ChemicalFormulaFeaturizer` in addition to a `MolecularStructureFeaturizer` (578).

Deprecated
* We've removed support for using pipenv for running tests. Users should be conscientious about additionally installing the test_requirements.txt file when trying to test code. (579)

Coming Soon
* Even more ways of mapping your GEMD data into tables, feeding your materials design processes.
* Most formulations-related predictors promoted to Beta.

This is a minor bugfix release to correct an oversight in [v0.117.0](https://github.com/CitrineInformatics/citrine-python/releases/tag/v0.117.0).

Bugfixes
* Fixed support for deserialization of `ChemicalFormulaFeaturizer` (https://github.com/CitrineInformatics/citrine-python/pull/577)

This release includes significant new functionality around featurization of molecular structures, chemical formulas, and formulation ingredients.

What's new
* The `MolecularStructureFeaturizer` is out of alpha! (https://github.com/CitrineInformatics/citrine-python/pull/573)
* A new `ChemicalFormulaFeaturizer` that can be used in `GraphPredictors` (https://github.com/CitrineInformatics/citrine-python/pull/575)
* A new builder method to make it easier to use molecular structure and chemical formula properties as ingredient properties in formulations problems (https://github.com/CitrineInformatics/citrine-python/pull/575)

Improvements
* The `training_data_count` field is now available in the predictor report's `ModelSummary` (https://github.com/CitrineInformatics/citrine-python/pull/574)

This release includes significant new functionality around deleting GEMD objects, particularly Attribute Templates. It also contains considerable quality of life improvements, both for developers and for users.

What's new
* Support for deleting Attribute Templates (https://github.com/CitrineInformatics/citrine-python/pull/561)
* Support for deleting the entire contents of a dataset (https://github.com/CitrineInformatics/citrine-python/pull/567)

Improvements
* Default resolution for formulation design space reduced to `0.0001` (https://github.com/CitrineInformatics/citrine-python/pull/564)
* Made the GEMD batch delete async, increasing its flexibility (https://github.com/CitrineInformatics/citrine-python/pull/561)
* Predictor reports are now fetched only when needed, avoiding a rare race condition (https://github.com/CitrineInformatics/citrine-python/pull/571)
* Many small quality of life improvements for developers and users (https://github.com/CitrineInformatics/citrine-python/pull/568)

Fixes
* Response parsing in error cases is more flexible (https://github.com/CitrineInformatics/citrine-python/pull/565/files)

What's new
* This version introduces the `MeanPropertyPredictor`. This predictor computes mean ingredient properties and is meant to replace the `GeneralizedMeanPropertyPredictor`. The behavior of the `MeanPropertyPredictor` is identical to that of the `GeneralizedMeanPropertyPredictor`, but the `MeanPropertyPredictor` requires that `properties` are specified as a list of `RealDescriptor` instead of a list of descriptor keys.

Deprecated
* The `GeneralizedMeanPropertyPredictor` has been replaced by the `MeanPropertyPredictor`.

This release makes a backwards incompatible update to Alpha functionality of AutoMLPredictors, updates documentation, and clarifies some argument types.

Improvements
* In an `IngredientsToSimpleMixturePredictor`, the type of `labels` has been updated from `Mapping[str, List[str]]` to a `Mapping[str, Set[str]]`. In the `LabelFractionsPredictor`, `labels` has been updated from a `List[str]` to a `Set[str]`. (https://github.com/CitrineInformatics/citrine-python/pull/558)
* A pre-validation of `IngredientQuantityDimension` has been added to prevent the subsequent type check for the units string from failing because of a type inconsistency. (https://github.com/CitrineInformatics/citrine-python/pull/559)

Fixes
* Documentation for the `GeneralizedMeanPropertyPredictor` has been updated to reflect that `p` must be an `int`. Deprecation warnings were added in case of `float` values. (https://github.com/CitrineInformatics/citrine-python/pull/556 and https://github.com/CitrineInformatics/citrine-python/pull/560)

Deprecated
* The `AutoMLPredictor` interface has been updated from accepting `responses` as a `List[Descriptor]` to accepting `output` as a single `Descriptor`. (https://github.com/CitrineInformatics/citrine-python/pull/553)