Citrine

v0.66.1 contains a significant new feature: the ability to archive AI Engine modules and workflows.

**What’s New**
* Archiving AI Engine modules and workflows: An archived module is still accessible but is hidden from lists by default. (https://github.com/CitrineInformatics/citrine-python/pull/406)
* Incorporates the most recent release of gemd-python, 0.14.1 (https://github.com/CitrineInformatics/gemd-python/releases/tag/v0.14.1)

**Improvements**
* Better documentation of the names of feature generated by the `GeneralizedMeanPropertyPredictor`. (https://github.com/CitrineInformatics/citrine-python/pull/432)
* Better documentation of which information is removed from the test set when performing cross validation (https://github.com/CitrineInformatics/citrine-python/pull/438)
* Many of the list methods will now automatically deduplicate records that show up on multiple pages when records are being concurrently created. (https://github.com/CitrineInformatics/citrine-python/pull/439)

**Fixes**
* The `add_columns` and `add_all_ingredients` helper methods on `TableConfig` will no longer remove identifiers from `TableConfig` that were read from the platform. (https://github.com/CitrineInformatics/citrine-python/pull/433)

**Deprecations**
* The `filter_by_tags` and `filter_by_name` methods on Data Objects and Templates in data_concepts.py have been deprecated due to their poor performance, and will be removed in a future release. Please use the `list_by_tags` and `list_by_name` methods instead. (https://github.com/CitrineInformatics/citrine-python/pull/436)

v0.61.0 is a feature release that makes it easier to use `Descriptor` by reading them from `AttributeTemplate` and provides more control over cross validation.

**What’s New**
* `PlatformVocabulary` makes it easy to use `AttributeTemplates` as `Descriptors`. For documentation and examples, see the new [descriptors guide](link here). (https://github.com/CitrineInformatics/citrine-python/pull/424)
* `CrossValidationAnalysisConfiguration` now includes an optional `responses` parameter that allows for explicit control over which predictions are validated (https://github.com/CitrineInformatics/citrine-python/pull/429)

**Improvements**
* The design space builders will issue a warning if the resulting space is large enough that it could consume all of your memory (https://github.com/CitrineInformatics/citrine-python/pull/428)

**Changes**
* The type of the `categories` member of `CategoricalDescriptor` has been changed from a list to a set

**What’s New**
* Training data are specified using a list of data sources, instead of a single data source. If multiple training data sources are specified, the data from all sources in the list will be used to train the predictor.
* Training data can be specified on a graph predictor. Any data sources specified by the graph predictor will be shared by all predictors in the graph, and shared data sources do not need to be redefined by any sub-predictors that require these data.
* You can now transfer the ownership of a project resource using `project.transfer_resource`.

**Deprecated**
* Specifying training data as a single data source. Please use a list of data sources instead, e.g. update`training_data=data_source` to `training_data=[data_source]`.

This is a small release focused on improving documentation and making the behavior of the Citrine Platform more transparent and explicit.

What's New
* The association between a GEM Table Data Source and the Formulation Descriptor that it provides is now explicit (https://github.com/CitrineInformatics/citrine-python/pull/422)

Improvements
* Improved documentation of when cross validation can be applied (https://github.com/CitrineInformatics/citrine-python/pull/427)
* Improved documentation of how to fetch the output descriptors of simple mixture predictors (https://github.com/CitrineInformatics/citrine-python/pull/347)

What's New
* A core element of machine learning is making sure inputs are all tabular -- sets of homogeneous vectors. GEMD represents real world data with graphs that can vary a lot, so it's essential to be able to bring consistency to material histories to train models. We are proud to announce the official naming of our graph-to-vector technology, GEM Tables, renamed from the working name, Ara.

Improvements
* The version number of a workflow execution is now visible. See [the documentation](https://citrineinformatics.github.io/citrine-python/reference/citrine.resources.workflow_executions.html) for details.
* Error messages, such as trying to train on an unregistered resource, have been improved.

Fixes
* Some objects were not receiving `id`s before being passed to the server. That's been fixed.
* Control over the scope in some variable definitions hadn't been included; that is now available.
* And some additional bug fixes, improvements to code structure and corrections to documentation.

What's New
* This release is largely about exposing [gemd-python v0.12.0](https://github.com/CitrineInformatics/gemd-python/releases/tag/v0.12.0) and modifying the citrine-python method signatures to mimic the changes therein.
* We are migrating Object constructors to require keyword arguments for nearly all parameters (excluding name), as per [our documented codestyle](https://github.com/CitrineInformatics/citrine-python/blob/master/CONTRIBUTING.md#codestyle).
* The name and labels arguments to the IngredientRun constructor have been deprecated for quite some time, and so those arguments have been removed.

Fixes
* Some errors in documentation were corrected along the way.