neurodata · david-z-shi · Sep 18, 2020 · Sep 22, 2020 · Sep 22, 2020 · Sep 22, 2020
diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -0,0 +1,133 @@
+version: 2.1
+
+orbs:
+  codecov: codecov/codecov@1.0.2
+
+jobs:
+  build:
+    parameters:
+      version:
+        type: string
+    docker:
+      - image: cimg/python:<< parameters.version >>
+    steps:
+      - checkout
+      - restore_cache:
+          key: v1-<< parameters.version >>-min-dependency-cache-{{ checksum "dev-requirements.txt" }}
+      - run:
+          name: install python dependencies
+          command: |
+            python3 -m venv venv
+            . venv/bin/activate
+            pip install --upgrade pip
+            pip install -r dev-requirements.txt
+      - save_cache:
+          key: v1-<< parameters.version >>-min-dependency-cache-{{ checksum "dev-requirements.txt" }}
+          paths:
+            - "venv"
+      - run:
+          name: test if package installs
+          command: |
+            . venv/bin/activate
+            python3 setup.py install
+  test-module:
+    parameters:
+      module:
+        type: string
+    docker:
+      - image: cimg/python:3.8
+    steps:
+      - checkout
+      - restore_cache:
+          key: v1-3.8-dependency-cache-{{ checksum "dev-requirements.txt" }}
+      - run:
+          name: install python dependencies
+          command: |
+            python3 -m venv venv
+            . venv/bin/activate
+            pip install -r dev-requirements.txt
+            pip install -e .
+      - save_cache:
+          key: v1-3.8-dependency-cache-{{ checksum "dev-requirements.txt" }}
+          paths:
+            - "venv"
+      - run:
+          name: run code linting
+          command: |
+            . venv/bin/activate
+            black --check --diff ./<< parameters.module >>
+      - run:
+          name: run tests and coverage
+          command: |
+            . venv/bin/activate
+            pytest --junitxml=test-reports/junit.xml --cov-report=xml --cov=./<< parameters.module >> ./<< parameters.module >>
+      - store_test_results:
+          path: test-reports
+      - store_artifacts:
+          path: test-reports
+      - codecov/upload:
+          file: "coverage.xml"
+  deploy:
+    docker:
+      - image: cimg/python:3.8
+    steps:
+      - checkout
+      - restore_cache:
+          key: v1-3.8-dependency-cache-{{ checksum "dev-requirements.txt" }}
+      - run:
+          name: install python dependencies
+          command: |
+            python3 -m venv venv
+            . venv/bin/activate
+            pip install -r dev-requirements.txt
+            pip install -e .
+      - save_cache:
+          key: v1-3.8-dependency-cache-{{ checksum "dev-requirements.txt" }}
+          paths:
+            - "venv"
+      - run:
+          name: verify git tag vs. version
+          command: |
+            python3 -m venv venv
+            . venv/bin/activate
+            python setup.py verify
+      - run:
+          name: init .pypirc
+          command: |
+            echo -e "[pypi]" >> ~/.pypirc
+            echo -e "username = $PYPI_USERNAME" >> ~/.pypirc
+            echo -e "password = $PYPI_PASSWORD" >> ~/.pypirc
+      - run:
+          name: create packages
+          command: |
+            python setup.py sdist
+      - run:
+          name: upload to pypi
+          command: |
+            . venv/bin/activate
+            twine upload dist/*
+workflows:
+  build-test-deploy:
+    jobs:
+      - build:
+          name: "v3.6"
+          version: "3.6"
+      - build:
+          name: "v3.7"
+          version: "3.7"
+      - build:
+          name: "v3.8"
+          version: "3.8"
+      - test-module:
+          name: "proglearn"
+          module: "proglearn"
+          requires:
+            - "v3.8"
+      - deploy:
+          requires:
+            - "proglearn"
+          filters:
+            tags:
+              only: /[0-9]+(\.[0-9]+)*/
+            branches:
+              ignore: /.*/
diff --git a/.travis.yml b/.travis.yml
diff --git a/README.md b/README.md
@@ -1,7 +1,7 @@
 # ProgLearn
 
-[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4276573.svg)](https://doi.org/10.5281/zenodo.4276573)
-[![Build Status](https://travis-ci.org/neurodata/ProgLearn.svg?branch=main)](https://travis-ci.org/neurodata/ProgLearn)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4060264.svg)](https://doi.org/10.5281/zenodo.4060264)
+[![Build Status](https://circleci.com/gh/neurodata/ProgLearn/tree/main.svg?style=shield&circle-token=:circle-token)](https://app.circleci.com/pipelines/github/neurodata/ProgLearn)
 [![Codecov](https://codecov.io/gh/neurodata/ProgLearn/branches/main/graph/badge.svg)](https://codecov.io/gh/neurodata/ProgLearn)
 [![PyPI version](https://img.shields.io/pypi/v/proglearn.svg)](https://pypi.org/project/proglearn/)
 [![arXiv](https://img.shields.io/badge/arXiv-2004.12908-red.svg?style=flat)](https://arxiv.org/abs/2004.12908)

diff --git a/benchmarks/uf_posterior_visualization/uncertaintyforest_conditionalentropyestimates.ipynb b/benchmarks/uf_posterior_visualization/uncertaintyforest_conditionalentropyestimates.ipynb
diff --git a/benchmarks/uf_posterior_visualization/uncertaintyforest_mutualinformationestimates.ipynb b/benchmarks/uf_posterior_visualization/uncertaintyforest_mutualinformationestimates.ipynb
diff --git a/benchmarks/uf_posterior_visualization/uncertaintyforest_posteriorestimates.ipynb b/benchmarks/uf_posterior_visualization/uncertaintyforest_posteriorestimates.ipynb
diff --git a/dev-requirements.txt b/dev-requirements.txt
@@ -0,0 +1,6 @@
+-r requirements.txt
+pytest
+coverage
+pytest-cov
+codecov
+black
diff --git a/docs/index.rst b/docs/index.rst
@@ -2,15 +2,15 @@
 
 .. _contents:
 
-Overview of ProgLearn_
+ProgLearn_
 ======================
 
 .. _proglearn: https://proglearn.neurodata.io/
 
-.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4276573.svg
-   :target: https://doi.org/10.5281/zenodo.4276573
-.. image:: https://travis-ci.org/neurodata/ProgLearn.svg?branch=main
-   :target: https://travis-ci.org/neurodata/ProgLearn
+.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4060264.svg
+   :target: https://doi.org/10.5281/zenodo.4060264
+.. image:: https://circleci.com/gh/neurodata/ProgLearn/tree/main.svg?style=shield&circle-token=:circle-token
+   :target: https://app.circleci.com/pipelines/github/neurodata/ProgLearn
 .. image:: https://codecov.io/gh/neurodata/ProgLearn/branches/main/graph/badge.svg
    :target: https://codecov.io/gh/neurodata/ProgLearn
 .. image:: https://img.shields.io/pypi/v/proglearn.svg
@@ -62,6 +62,7 @@ Documentation
    :maxdepth: 1
    :caption: Using ProgLearn
 
+   overview
    install
    tutorials/
    reference/index

diff --git a/docs/install.rst b/docs/install.rst
@@ -53,8 +53,8 @@ Python package dependencies
 - tensorflow>=1.19.0
 - scikit-learn>=0.22.0
 - scipy==1.4.1
-- numpy<1.19
 - joblib>=0.14.1
+- numpy==1.19.2
 
 Hardware requirements
 ---------------------
@@ -65,7 +65,7 @@ tensorflow's backend.
 OS Requirements
 ---------------
 This package is supported for all major operating systems. The following
-versions of operating systems was tested on Travis CI:
+versions of operating systems was tested on CircleCI:
 
 - **Linux**: Ubuntu 16.04
 - **macOS**: Mojave (10.14.1)

diff --git a/docs/overview.rst b/docs/overview.rst
@@ -0,0 +1,53 @@
+..  -*- coding: utf-8 -*-
+
+.. _contents:
+
+Overview
+========
+
+``ProgLearn`` provides classes and functions for biological machine learning. Notably, it improves in performance on all tasks (including past and future) with any new data. This sets it apart from classical machine learning algorithms and many other recent approaches to biological learning.
+
+The Library
+-----------
+
+All classes and functions are available through the ``ProgLearn`` package and can also be imported separately.
+
+.. code:: python
+
+    import proglearn as PL
+    from proglearn.forest import UncertaintyForest
+
+The Learners
+------------
+
+There are three main parts to the ``ProgLearn`` package: Lifelong Classification Network, Lifelong Classification Forest, and the Uncertainty Forest. All three have very similar syntax and usage. A general overview is provided below with more specific and complete examples in the tutorial section. This overview example will use ``proglearn.forest.UncertaintyForest`` but is generalizable to the Lifelong Classification Network and Lifelong Classification Forest.
+
+First, we'll create our forest:
+
+.. code:: python
+
+    UF = UncertaintyForest(n_estimators = n_estimators)
+
+Then, we fit to data:
+
+.. code:: python
+
+    UF.fit(X_train, y_train)
+
+Finally we can predict the classes of the data:
+
+.. code:: python
+
+    predictions = UF.predict(X_test)
+
+Another advantage of the ``ProgLearn`` package is the ``predict_proba(X)`` function. It can be used to estimate the class posteriors for each example in the input data, X.
+
+.. code:: python
+
+  predicted_posteriors = UF.predict_proba(X_test)
+
+
+Wrap Up
+-------
+
+This overview covers the basics of using ``ProgLearn``. Most use cases will utilize the functions presented above. Further examples are available in the tutorials section (see menu).
diff --git a/docs/reference/forest.rst b/docs/reference/forest.rst
@@ -8,4 +8,7 @@ Lifelong Classification Forest
 
 .. autoclass:: LifelongClassificationForest
 
+Uncertainty Forest
+------------------------------
+
 .. autoclass:: UncertaintyForest
diff --git a/docs/tutorials.rst b/docs/tutorials.rst
@@ -9,6 +9,7 @@ The following tutorials highlight what one can do with the ``ProgLearn`` package
 
     tutorials/installation_guide
     tutorials/fte_bte_food101
+    tutorials/fte_bte_mnist
     tutorials/label_shuffle_exp
     tutorials/random_class_exp
     tutorials/rotation_cifar
@@ -20,4 +21,4 @@ The following tutorials highlight what one can do with the ``ProgLearn`` package
     tutorials/xor_nxor_exp
     tutorials/xor_rxor_exp
     tutorials/xor_rxor_with_cpd
-    tutorials/xor_rxor_with_icp
+    tutorials/xor_rxor_with_icp