Sdv

This release introduces a few changes in the HMA1 relational algorithm to decrease modeling
and sampling times, while also ensuring that correlations are properly kept across tables
and also adding support for some relational schemas that were not supported before.

A few changes in constraints and tabular models also ensure that situations that produced
errors before now work without errors.

Issues resolved

* Fix unique key generation - Issue [306](https://github.com/sdv-dev/SDV/issues/306) by fealho
* Ensure tables that contain nothing but ids can be modeled - Issue [302](https://github.com/sdv-dev/SDV/issues/302) by csala
* Metadata visualization improvements - Issue [301](https://github.com/sdv-dev/SDV/issues/301) by csala
* Multi-parent re-model and re-sample issue - Issue [298](https://github.com/sdv-dev/SDV/issues/298) by csala
* Support datetimes in GreaterThan constraint - Issue [266](https://github.com/sdv-dev/SDV/issues/266) by rollervan
* Support for multiple foreign keys in one table - Issue [185](https://github.com/sdv-dev/SDV/issues/185) by csala

SDMetrics version is updated to include the new Time Series metrics, which have also
been added to the API Reference and User Guides documentation. Additionally,
a few code has been refactored to reduce external dependencies and a few minor bugs
related to single table constraints have been fixed

Issues resolved

* Add timeseries metrics and user guides - [Issue 289](https://github.com/sdv-dev/SDV/issues/289) by csala
* Add functions to generate regex ids - [Issue 288](https://github.com/sdv-dev/SDV/issues/288) by csala
* Saving a fitted tabular model with UniqueCombinations constraint raises PicklingError -
[Issue 286](https://github.com/sdv-dev/SDV/issues/288) by csala
* Constraints: `handling_strategy='reject_sampling'` causes `'ZeroDivisionError: division by zero'` -
[Issue 285](https://github.com/sdv-dev/SDV/issues/285) by csala

This release updates to the latest CTGAN, RDT and SDMetrics libraries to introduce a
new TVAE model, multiple new metrics for single table and multi table, and fixes
issues in the re-creation of tabular models from a metadata dict.

Issues resolved

* Upgrade to SDMetrics v0.1.0 and add `sdv.metrics` module - [Issue 281](https://github.com/sdv-dev/SDV/issues/281) by csala
* Upgrade to CTGAN 0.3.0 and add TVAE model - [Issue 278](https://github.com/sdv-dev/SDV/issues/278) by fealho
* Add `dtype_transformers` to `Table.from_dict` - [Issue 276](https://github.com/sdv-dev/SDV/issues/276) by csala
* Fix Metadata `from_dict` behavior - [Issue 275](https://github.com/sdv-dev/SDV/issues/275) by csala

This version updates the dependencies and makes a few internal changes in order
to ensure that SDV works properly on Windows Systems, making this the first
release to be officially supported on Windows.

Apart from this, some more internal changes have been made to solve a few minor
issues from the older versions while also improving the processing speed when
processing relational datasets with the default parameters.

API breaking changes

* The `distribution` argument of the `GaussianCopula` has been renamed to `field_distributions`.
* The `HMA1` and `SDV` classes now use the `categorical_fuzzy` transformer by default instead of
the `one_hot_encoding` one.

Issues resolved

* GaussianCopula: rename `distribution` argument to `field_distributions` - [Issue 237](https://github.com/sdv-dev/SDV/issues/237) by csala
* GaussianCopula: Improve error message if an invalid distribution name is passed - [Issue 220](https://github.com/sdv-dev/SDV/issues/220) by csala
* Import urllib.request explicitly - [Issue 227](https://github.com/sdv-dev/SDV/issues/227) by csala
* TypeError: cannot astype a datetimelike from [datetime64[ns]] to [int32] - [Issue 218](https://github.com/sdv-dev/SDV/issues/218) by csala
* Change default categorical transformer to `categorical_fuzzy` in HMA1 - [Issue 214](https://github.com/sdv-dev/SDV/issues/214) by csala
* Integer categoricals being sampled as strings instead of integer values - [Issue 194](https://github.com/sdv-dev/SDV/issues/194) by csala

In this version a new family of models for Synthetic Time Series Generation is introduced
under the `sdv.timeseries` sub-package. The new family of models now includes a new class
called `PAR`, which implements a *Probabilistic AutoRegressive* model.

This version also adds support for composite primary keys and regex based generation of id
fields in tabular models and drops Python 3.5 support.

Issues resolved

* Drop python 3.5 support - [Issue 204](https://github.com/sdv-dev/SDV/issues/204) by csala
* Support composite primary keys in tabular models - [Issue 207](https://github.com/sdv-dev/SDV/issues/207) by csala
* Add the option to generate string `id` fields based on regex on tabular models - [Issue 208](https://github.com/sdv-dev/SDV/issues/208) by csala
* Synthetic Time Series - [Issue 142](https://github.com/sdv-dev/SDV/issues/142) by csala

This version adds a new tabular model based on combining the CTGAN model with the reversible
transformation applied in the GaussianCopula model that converts random variables with
arbitrary distributions to new random variables with standard normal distribution.

The reversible transformation is handled by the GaussianCopulaTransformer recently added to RDT.

Issues resolved

* Add CopulaGAN Model - [Issue 202](https://github.com/sdv-dev/SDV/issues/202) by csala