make release-tag: Merge branch 'master' into stable

Author: csala

.gitignore

@@ -112,3 +112,4 @@ ENV/
 
 notebooks/
 dask-worker-space/
+tutorials/sunglasses

HISTORY.md

@@ -1,6 +1,11 @@
 # History
 
-## 0.1.3 (2020-10-16)
+## 0.1.4 - 2020-10-16
+
+Minor maintenance version to update dependencies and documentation, and
+also make the demo data loading function parse dates properly.
+
+## 0.1.3 - 2020-10-16
 
 This version includes several minor improvements to the PAR model and the
 way the sequences are generated:
@@ -11,11 +16,11 @@ way the sequences are generated:
 * NaN values are generated for numerical columns only if there were NaNs in the input data.
 * Constant columns can now be modeled.
 
-## 0.1.2 (2020-09-15)
+## 0.1.2 - 2020-09-15
 
 Add BasicGAN Model and additional benchmarking results.
 
-## 0.1.1 (2020-08-15)
+## 0.1.1 - 2020-08-15
 
 This release includes a few new features to make DeepEcho work on more types of datasets
 as well as to making it easier to add new datasets to the benchmarking framework.
@@ -27,7 +32,7 @@ as well as to making it easier to add new datasets to the benchmarking framework
 * Add function `make_dataset` to create a dataset from a dataframe and just a few column names.
 * Add notebook tutorial to show how to create a datasets and use them.
 
-## 0.1.0 (2020-08-11)
+## 0.1.0 - 2020-08-11
 
 First release.
 

INSTALL.md

@@ -0,0 +1,60 @@
+# Installing DeepEcho
+
+## Requirements
+
+**DeepEcho** has been developed and tested on [Python 3.6, 3.7 and 3.8](https://www.python.org/downloads/)
+
+Also, although it is not strictly required, the usage of a [virtualenv](
+https://virtualenv.pypa.io/en/latest/) is highly recommended in order to avoid
+interfering with other software installed in the system where **DeepEcho** is run.
+
+## Install with pip
+
+The easiest and recommended way to install **DeepEcho** is using [pip](
+https://pip.pypa.io/en/stable/):
+
+```bash
+pip install deepecho
+```
+
+This will pull and install the latest stable release from [PyPi](https://pypi.org/).
+
+## Install with conda
+
+**DeepEcho** can also be installed using [conda](https://docs.conda.io/en/latest/):
+
+```bash
+conda install -c sdv-dev -c pytorch -c conda-forge deepecho
+```
+
+This will pull and install the latest stable release from [Anaconda](https://anaconda.org/).
+
+## Install from source
+
+If you want to install **DeepEcho** from source you need to first clone the repository
+and then execute the `make install` command inside the `stable` branch. Note that this
+command works only on Unix based systems like GNU/Linux and macOS:
+
+```bash
+git clone https://github.com/sdv-dev/DeepEcho
+cd DeepEcho
+git checkout stable
+make install
+```
+
+## Install for development
+
+If you intend to modify the source code or contribute to the project you will need to
+install it from the source using the `make install-develop` command. In this case, we
+recommend you to branch from `master` first:
+
+```bash
+git clone [email protected]:sdv-dev/DeepEcho
+cd DeepEcho
+git checkout master
+git checkout -b <your-branch-name>
+make install-develp
+```
+
+For more details about how to contribute to the project please visit the [Contributing Guide](
+CONTRIBUTING.rst).

Makefile

@@ -37,9 +37,6 @@ clean-build: ## remove build artifacts
 	rm -fr build/
 	rm -fr dist/
 	rm -fr .eggs/
-	rm -fr benchmark/build/
-	rm -fr benchmark/dist/
-	rm -fr benchmark/.eggs/
 	find . -name '*.egg-info' -exec rm -fr {} +
 	find . -name '*.egg' -exec rm -f {} +
 
@@ -77,17 +74,13 @@ clean: clean-build clean-pyc clean-test clean-coverage clean-docs ## remove all
 install: clean-build clean-pyc ## install the package to the active Python's site-packages
 	pip install .
 
-.PHONY: install-benchmark
-install-benchmark: clean-build clean-pyc ## install the package and test dependencies
-	pip install ./benchmark
-
 .PHONY: install-test
 install-test: clean-build clean-pyc ## install the package and test dependencies
-	pip install .[test] ./benchmark
+	pip install .[test]
 
 .PHONY: install-develop
 install-develop: clean-build clean-pyc ## install the package in editable mode and dependencies for development
-	pip install -e .[dev] -e ./benchmark[dev]
+	pip install -e .[dev]
 
 
 # LINT TARGETS
@@ -98,25 +91,19 @@ lint-deepecho: ## check style with flake8 and isort
 	isort -c --recursive deepecho
 	pylint deepecho --rcfile=setup.cfg
 
-.PHONY: lint-benchmark
-lint-benchmark: ## check style with flake8 and isort
-	flake8 benchmark/deepecho
-	isort -c --recursive benchmark/deepecho
-	pylint benchmark/deepecho --rcfile=setup.cfg
-
 .PHONY: lint-tests
 lint-tests: ## check style with flake8 and isort
-	flake8 --ignore=D tests benchmark/tests
-	isort -c --recursive tests benchmark/tests
+	flake8 --ignore=D tests
+	isort -c --recursive tests
 
 .PHONY: lint
-lint:lint-deepecho lint-benchmark lint-tests  ## Run all code style checks
+lint:lint-deepecho lint-tests  ## Run all code style checks
 
 .PHONY: fix-lint
 fix-lint: ## fix lint issues using autoflake, autopep8, and isort
-	find deepecho benchmark/deepecho tests -name '*.py' | xargs autoflake --in-place --remove-all-unused-imports --remove-unused-variables
-	autopep8 --in-place --recursive --aggressive deepecho benchmark/deepecho tests
-	isort --apply --atomic --recursive deepecho benchmark/deepecho tests
+	find deepecho tests -name '*.py' | xargs autoflake --in-place --remove-all-unused-imports --remove-unused-variables
+	autopep8 --in-place --recursive --aggressive deepecho tests
+	isort --apply --atomic --recursive deepecho tests
 
 
 # TEST TARGETS
@@ -163,7 +150,6 @@ coverage: ## check code coverage quickly with the default Python
 docs: clean-docs ## generate Sphinx HTML documentation, including API docs
 	cp -r tutorials docs/tutorials
 	sphinx-apidoc --separate --no-toc -M -o docs/api/ deepecho
-	sphinx-apidoc --separate --no-toc -M -o docs/api/ benchmark/deepecho
 	$(MAKE) -C docs html
 
 .PHONY: view-docs
@@ -181,9 +167,6 @@ serve-docs: view-docs ## compile the docs watching for changes
 dist: clean ## builds source and wheel package
 	python setup.py sdist
 	python setup.py bdist_wheel
-	# cd benchmark && python setup.py sdist
-	# cd benchmark && python setup.py bdist_wheel
-	# mv benchmark/dist/* dist && rmdir benchmark/dist
 	ls -l dist
 
 .PHONY: publish-confirm
@@ -241,6 +224,7 @@ bumpversion-revert: ## Undo a previous bumpversion-release
 
 CLEAN_DIR := $(shell git status --short | grep -v ??)
 CURRENT_BRANCH := $(shell git rev-parse --abbrev-ref HEAD 2>/dev/null)
+CURRENT_VERSION := $(shell grep "^current_version" setup.cfg | grep -o "dev[0-9]*")
 CHANGELOG_LINES := $(shell git diff HEAD..origin/stable HISTORY.md 2>&1 | wc -l)
 
 .PHONY: check-clean
@@ -255,14 +239,20 @@ ifneq ($(CURRENT_BRANCH),master)
 	$(error Please make the release from master branch\n)
 endif
 
+.PHONY: check-candidate
+check-candidate: ## Check if a release candidate has been made
+ifeq ($(CURRENT_VERSION),dev0)
+	$(error Please make a release candidate and test it before atempting a release)
+endif
+
 .PHONY: check-history
 check-history: ## Check if HISTORY.md has been modified
 ifeq ($(CHANGELOG_LINES),0)
 	$(error Please insert the release notes in HISTORY.md before releasing)
 endif
 
 .PHONY: check-release
-check-release: check-clean check-master check-history ## Check if the release can be made
+check-release: check-clean check-candidate check-master check-history ## Check if the release can be made
 	@echo "A new release can be made"
 
 .PHONY: release
@@ -276,29 +266,3 @@ release-candidate: check-master publish bumpversion-candidate
 
 .PHONY: release-candidate-test
 release-candidate-test: check-clean check-master publish-test
-
-.PHONY: release-minor
-release-minor: check-release bumpversion-minor release
-
-.PHONY: release-major
-release-major: check-release bumpversion-major release
-
-
-# DOCKER TARGETS
-
-.PHONY: docker-login
-docker-login:
-	docker login docker.io
-
-.PHONY: docker-build
-docker-build:
-	docker build -t deepecho -f benchmark/Dockerfile .
-
-.PHONY: docker-push
-docker-push: docker-login
-	@$(eval VERSION := $(shell python -c 'import deepecho; print(deepecho.__version__)'))
-	docker tag deepecho sdvproject/deepecho:$(VERSION)
-	docker push sdvproject/deepecho:$(VERSION)
-
-.PHONY: docker-publish
-docker-publish: docker-login docker-build docker-push

README.md

@@ -1,25 +1,25 @@
 <p align="left">
-<img width=20% src="https://dai.lids.mit.edu/wp-content/uploads/2018/06/Logo_DAI_highres.png" alt=“sdv-dev” />
-<i>An open source project from Data to AI Lab at MIT.</i>
-</p>
-
-<p>
-  <img width=65% src="docs/images/DeepEcho-Logo.png">
+  <a href="https://dai.lids.mit.edu">
+    <img width=15% src="https://dai.lids.mit.edu/wp-content/uploads/2018/06/Logo_DAI_highres.png" alt="DAI-Lab" />
+  </a>
+  <i>An Open Source Project from the <a href="https://dai.lids.mit.edu">Data to AI Lab, at MIT</a></i>
 </p>
 
 [![Development Status](https://img.shields.io/badge/Development%20Status-2%20--%20Pre--Alpha-yellow)](https://pypi.org/search/?c=Development+Status+%3A%3A+2+-+Pre-Alpha)
 [![PyPi Shield](https://img.shields.io/pypi/v/deepecho.svg)](https://pypi.python.org/pypi/deepecho)
-[![Travis CI Shield](https://travis-ci.org/sdv-dev/DeepEcho.svg?branch=master)](https://travis-ci.org/sdv-dev/DeepEcho)
-[![Coverage Status](https://codecov.io/gh/sdv-dev/DeepEcho/branch/master/graph/badge.svg)](https://codecov.io/gh/sdv-dev/DeepEcho)
+[![Tests](https://github.com/sdv-dev/DeepEcho/workflows/Run%20Tests/badge.svg)](https://github.com/sdv-dev/DeepEcho/actions?query=workflow%3A%22Run+Tests%22+branch%3Amaster)
 [![Downloads](https://pepy.tech/badge/deepecho)](https://pepy.tech/project/deepecho)
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/sdv-dev/DeepEcho/master?filepath=tutorials)
+[![Coverage Status](https://codecov.io/gh/sdv-dev/DeepEcho/branch/master/graph/badge.svg)](https://codecov.io/gh/sdv-dev/DeepEcho)
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/sdv-dev/DeepEcho/master?filepath=tutorials/timeseries_data)
 [![Slack](https://img.shields.io/badge/Slack%20Workspace-Join%20now!-36C5F0?logo=slack)](https://join.slack.com/t/sdv-space/shared_invite/zt-gdsfcb5w-0QQpFMVoyB2Yd6SRiMplcw)
 
-# DeepEcho
+<img align="center" width=60% src="docs/images/DeepEcho-Logo.png">
 
+* Website: https://sdv.dev
+* Documentation: https://sdv.dev/SDV
+* Repository: https://github.com/sdv-dev/DeepEcho
 * License: [MIT](https://github.com/sdv-dev/DeepEcho/blob/master/LICENSE)
 * Development Status: [Pre-Alpha](https://pypi.org/search/?c=Development+Status+%3A%3A+2+-+Pre-Alpha)
-* Homepage: https://github.com/sdv-dev/DeepEcho
 
 # Overview
 
@@ -28,16 +28,17 @@ time series**. It provides:
 
 1. Multiple models based both on **classical statistical modeling** of time series and the latest
    in **Deep Learning** techniques.
-2. A robust [benchmarking framework](benchmark) for evaluating these methods on multiple datasets
-   and with multiple metrics.
+2. A robust [benchmarking framework](https://github.com/sdv-dev/SDGym) for evaluating these methods
+   on multiple datasets and with multiple metrics.
 3. Ability for **Machine Learning researchers** to submit new methods following our `model` and
    `sample` API and get evaluated.
 
 ## Try it out now!
 
 If you want to quickly discover **DeepEcho**, simply click the button below and follow the tutorials!
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/sdv-dev/DeepEcho/master?filepath=tutorials)
+[![Binder](https://mybinder.org/badge_logo.svg)](
+https://mybinder.org/v2/gh/sdv-dev/DeepEcho/master?filepath=tutorials/timeseries_data)
 
 ## Join our Slack Workspace
 
@@ -49,30 +50,39 @@ our Slack Workspace!
 
 # Install
 
-## Requirements
+**DeepEcho** is part of the **SDV** project and is automatically installed alongside it. For
+details about this process please visit the [SDV Installation Guide](
+https://sdv.dev/SDV/getting_started/install.html)
 
-**DeepEcho** has been developed and tested on [Python 3.6, 3.7 and 3.8](https://www.python.org/downloads/)
+Optionally, **DeepEcho** can also be installed as a standalone library using the following commands:
 
-Also, although it is not strictly required, the usage of a [virtualenv](https://virtualenv.pypa.io/en/latest/)
-is highly recommended in order to avoid interfering with other software installed in the system where **DeepEcho**
-is run.
-
-## Install with pip
-
-The easiest and recommended way to install **DeepEcho** is using [pip](https://pip.pypa.io/en/stable/):
+**Using `pip`:**
 
 ```bash
 pip install deepecho
 ```
 
-This will pull and install the latest stable release from [PyPi](https://pypi.org/).
+**Using `conda`:**
 
-If you want to install from source or contribute to the project please read the
-[Contributing Guide](CONTRIBUTING.rst).
+```bash
+conda install -c sdv-dev -c pytorch -c conda-forge deepecho
+```
 
+For more installation options please visit the [DeepEcho installation Guide](INSTALL.md)
 
 # Quickstart
 
+**DeepEcho** is included as part of [SDV](https://sdv.dev/SDV) to model and sample synthetic
+time series. In most cases, usage through SDV is recommeded, since it provides additional
+functionalities which are not available here. For more details about how to use DeepEcho
+whithin SDV, please visit the corresponding User Guide:
+
+* [SDV TimeSeries User Guide](https://sdv.dev/SDV/user_guides/timeseries/par.html)
+
+## Standalone usage
+
+**DeepEcho** can also be used as a standalone library.
+
 In this short quickstart, we show how to learn a mixed-type multivariate time series
 dataset and then generate synthetic data that resembles it.
 
@@ -133,24 +143,19 @@ For more details about **DeepEcho** and all its possibilities and features, plea
 run the [tutorials](tutorials).
 
 If you want to see how we evaluate the performance and quality of our models, please have a
-look at the [DeepEcho Benchmarking framework](benchmark) or [Explore the obtained results](
-https://docs.google.com/spreadsheets/d/1Fbwj5ZjuYjvPmgUbXQR1HiXs5UZ1K3VulItbqrzH8rA/)
+look at the [SDGym Benchmarking framework](https://github.com/sdv-dev/SDGym).
 
 Also, please feel welcome to visit [our contributing guide](CONTRIBUTING.rst) in order to help
 us developing new features or cool ideas!
 
-# Related Projects
+# The Synthetic Data Vault
 
-## SDV
-
-[SDV](https://github.com/HDI-Project/SDV), for Synthetic Data Vault, is the end-user library for
-synthesizing data in development under the [HDI Project](https://hdi-dai.lids.mit.edu/).
-SDV allows you to easily model and sample relational datasets using DeepEcho thought a simple API.
-Other features include anonymization of Personal Identifiable Information (PII) and preserving
-relational integrity on sampled records.
-
-## CTGAN
+<p>
+  <a href="https://sdv.dev">
+    <img width=30% src="https://github.com/sdv-dev/SDV/blob/master/docs/images/SDV-Logo-Color-Tagline.png?raw=true">
+  </a>
+  <p><i>This repository is part of <a href="https://sdv.dev">The Synthetic Data Vault Project</a></i></p>
+</p>
 
-[CTGAN](https://github.com/sdv-dev/CTGAN) is a GAN based model for synthesizing tabular data.
-It's also developed by the [MIT's Data to AI Lab](https://sdv-dev.github.io/) and is under
-active development.
+* Website: https://sdv.dev
+* Documentation: https://sdv.dev/SDV