Merge release/0.8.0 back into develop for release 0.8.0 (mckinsey#82)

* Hotfix/0.4.3 (#7) - Address broken links and grammar

* Fix documentation links in README (#2)

* Fix links in README

* library -> libraries

* Fix github link in docs

* Clean up grammar and consistency in documentation (#4)

* Clean up grammar and consistency in `README` files

* Add esses, mostly

* Reword feature description to not appear automatic

* Update docs/source/05_resources/05_faq.md

Co-Authored-By: Ben Horsburgh <benhorsburgh@outlook.com>

Co-authored-by: Ben Horsburgh <benhorsburgh@outlook.com>

* hotfix/0.4.3: fix broken links

Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com>
Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com>
Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu>

* Release/0.5.0

* Plotting now backed by pygraphviz. This allows:
   * More powerful layout manager
   * Cleaner fully customisable theme
   * Out-the-box styling for different node and edge types
* Can now get subgraphs from StructureModel containing a specific node
* Bugfix to resolve issue when fitting CPDs with some missing states in data
* Minor documentation fixes and improvements

* Release/0.6.0

* Release/0.7.0 (mckinsey#57)

* Added plottting tutorial to the documentation
* Updated `viz.draw` syntax in tutorial notebooks
* Bugfix on notears lasso (`from_numpy_lasso` and `from_pandas_lasso`) where the non-negativity constraint was not being set
* Added DAG-based synthetic data generator for mixed types (binary, categorical, continuous) using a linear SEM approach.
* Unpinned some requirements

* release.md, version bump, docs

Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com>
Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com>
Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com>
Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu>
Co-authored-by: Philip Pilgerstorfer <34248114+qbphilip@users.noreply.github.com>

RELEASE.md

@@ -1,13 +1,15 @@
 # Upcoming release
 
-* Add dynotears (`from_numpy_dynamic`, an algorithm for structure learning on Dynamic Bayesian Networks)
-* Add a count data type to the data generator using a zero-inflated Poisson
-* Set bounds/max class imbalance for binary features for the data generators
-* Add non-linear data generators for multiple data types
-* Added Pytorch implementation for NOTEARS MLP which is much faster (Only supporting linear structure learning for now)
-* Bugfix to resolve issue when applying notears on data containing NaN
-* Added StructureRegressor sklearn interface using the Pytorch NOTEARS implementation.
-* Hotfix for data_gen system. Fixes issues with root node initialization.
+# Release 0.8.0
+
+* Add DYNOTEARS (`from_numpy_dynamic`, an algorithm for structure learning on Dynamic Bayesian Networks).
+* Added Pytorch implementation for NOTEARS MLP (`pytorch.from_numpy`) which is much faster and allows nonlinear modelling.
+* Added `DAGRegressor` sklearn interface using the Pytorch NOTEARS implementation.
+* Add non-linear data generators for multiple data types.
+* Add a count data type to the data generator using a zero-inflated Poisson.
+* Set bounds/max class imbalance for binary features for the data generators.
+* Bugfix to resolve issue when applying NOTEARS on data containing NaN.
+* Bugfix for data_gen system. Fixes issues with root node initialization.
 
 # Release 0.7.0
 
@@ -50,6 +52,6 @@ The initial release of CausalNex.
 
 ## Thanks for supporting contributions
 CausalNex was originally designed by [Paul Beaumont](https://www.linkedin.com/in/pbeaumont/) and [Ben Horsburgh](https://www.linkedin.com/in/benhorsburgh/) to solve challenges they faced in inferencing causality in their project work. This work was later turned into a product thanks to the following contributors:
-[Yetunde Dada](https://github.com/yetudada), [Wesley Leong](https://www.linkedin.com/in/wesleyleong/), [Steve Ler](https://www.linkedin.com/in/song-lim-steve-ler-380366106/), [Viktoriia Oliinyk](https://www.linkedin.com/in/victoria-oleynik/), [Roxana Pamfil](https://www.linkedin.com/in/roxana-pamfil-1192053b/), [Nisara Sriwattanaworachai](https://www.linkedin.com/in/nisara-sriwattanaworachai-795b357/), [Nikolaos Tsaousis](https://www.linkedin.com/in/ntsaousis/), and [Angel Droth](https://www.linkedin.com/in/angeldroth/).
+[Yetunde Dada](https://github.com/yetudada), [Wesley Leong](https://www.linkedin.com/in/wesleyleong/), [Steve Ler](https://www.linkedin.com/in/song-lim-steve-ler-380366106/), [Viktoriia Oliinyk](https://www.linkedin.com/in/victoria-oleynik/), [Roxana Pamfil](https://www.linkedin.com/in/roxana-pamfil-1192053b/), [Nisara Sriwattanaworachai](https://www.linkedin.com/in/nisara-sriwattanaworachai-795b357/), [Nikolaos Tsaousis](https://www.linkedin.com/in/ntsaousis/), [Angel Droth](https://www.linkedin.com/in/angeldroth/), and [Zain Patel](https://www.linkedin.com/in/zain-patel/).
 
 CausalNex would also not be possible without the generous sharing from leading researches in the field of causal inference and we are grateful to everyone who advised and supported us, filed issues or helped resolve them, asked and answered questions or simply be part of inspiring discussions.

causalnex/__init__.py

@@ -30,6 +30,6 @@
 causalnex toolkit for causal reasoning (Bayesian Networks / Inference)
 """
 
-__version__ = "0.7.0"
+__version__ = "0.8.0"
 
 __all__ = ["structure", "discretiser", "evaluation", "inference", "network", "plots"]

docs/source/api_docs/index.rst

@@ -61,6 +61,7 @@ Welcome to CausalNex's API docs and tutorials!
 
    03_tutorial/03_tutorial.md
    03_tutorial/plotting_tutorial.md
+   03_tutorial/regressor_tutorial.md
 
 .. toctree::
    :maxdepth: 2