Merge pull request #362 from ConnectedSystems/develop

Latest dev version

.github/workflows/python-package-conda.yml

@@ -0,0 +1,39 @@
+# Based on: https://github.com/fcakyon/conda-publish-action
+
+name: SALib Python Package using Conda
+
+on: 
+  push:
+    branches: 
+      - master
+    tags:
+      - "*v*"
+
+jobs:
+  build-linux:
+    runs-on: ubuntu-latest
+    strategy:
+      max-parallel: 5
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Set up Python 3.8
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.8
+    - name: Install dependencies
+      run: |
+        # $CONDA is an environment variable pointing to the root of the miniconda directory
+        $CONDA/bin/conda env update --file environment.yml --name base
+    - name: Lint with flake8
+      run: |
+        $CONDA/bin/conda install flake8
+        # stop the build if there are Python syntax errors or undefined names
+        $CONDA/bin/flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        $CONDA/bin/flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Test with pytest
+      run: |
+        conda install pytest
+        $CONDA/bin/pytest

.github/workflows/test-pypi-publish.yml

@@ -0,0 +1,43 @@
+# This workflows will upload a Python Package using Twine when a release is created
+# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
+
+name: Upload SALib Python Package pre-release to PyPI and TestPyPI
+
+on: 
+  push:
+    branches:
+      - "develop"
+    tags:
+      - "*dev*"
+
+jobs:
+  pre-release:
+    name: "Pre Release"
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Publish distribution 📦 to Test PyPI
+      uses: pypa/gh-action-pypi-publish@master
+      with:
+        password: ${{ secrets.test_pypi_password }}
+        repository_url: https://test.pypi.org/legacy/
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.x'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install setuptools wheel twine
+
+    - name: Build and publish
+      env:
+        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+      run: |
+        python setup.py sdist bdist_wheel
+        twine upload dist/*

.github/workflows/update-changelog.yml

@@ -0,0 +1,45 @@
+# This workflow creates a PR with an automatically updated changelog
+# Based on: https://github.com/marketplace/actions/update-changelog
+
+name: Update changelog for release candidates
+
+on: 
+  push:
+    branches:
+      - "release-candidate"
+jobs:
+  comment:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python
+        uses: actions/setup-python@v1
+        with:
+          python-version: "3.8"
+      - name: Update version
+        id: version
+        run: |
+          echo "GITHUB_REF is a tag you set for the release"
+          echo "Your GitHub ref: ${GITHUB_REF}"
+          VERSION=`echo "${GITHUB_REF}" | cut -f 3 -d "/"`
+          echo "Preparing version ${VERSION}"
+          echo "__version__ = \"${VERSION}\"" > __version__.py
+          echo "##[set-output name=version;]$(echo ${VERSION})"
+      - uses: vemel/update-changelog@0.0.1
+        id: changelog
+        with:
+          version: ${{ steps.version.outputs.version }}
+      - name: Create Pull Request
+        uses: peter-evans/create-pull-request@v2
+        with:
+          commit-message: Release ${{ steps.version.outputs.version }}
+          labels: release, bot
+          title: "Release ${{ steps.version.outputs.version }}"
+          body: |
+            # Release ${{ steps.version.outputs.version }}
+
+            Merge this PR to update your version and changelog!
+
+            ## Included Pull Requests
+
+            ${{ steps.changelog.outputs.pulls_list_md }}

AUTHORS.rst

@@ -11,3 +11,4 @@ Developers
 * Fernando Rios
 * Dan Hyams
 * xantares
+* Abdullah Sahin <sahina@uci.edu>

CHANGELOG.md

@@ -0,0 +1,151 @@
+# Changelog
+
+This changelog follows the format defined at:
+https://keepachangelog.com/en/1.0.0/
+
+## [1.3.0]
+
+### Added
+
+- Various minor performance enhancements (PR #253 #264)
+- Added some visualisation methods (PR #259)
+- Tidying up of the Command Line Interfance, and num samples (PR #260 #291)
+- Improved efficiency of summing distances in local optimization (PR #246)
+- Revamped fast method for consistency (PR #239)
+- Updated Sobol-G function to modified G-function (#269)
+
+### Bug Fixes:
+
+- Method of morris didn't adjust with levels above 4 (PR #252)
+- Add missing seed option for morris sampling
+- Handle singular value matrix cases (PR #251)
+- Fixed typo (#205)
+- Updated import of scipy comb function (PR #243)
+
+### Documentation:
+
+- Update documentation for Morris and DSGM methods (#261 #266)
+
+### Development Features:
+
+- Updated PyScaffold to version 3.2.2 (#267)
+- Updated Travis and package config (#285)
+
+## [1.1.0]
+
+### New Features:
+
+- Refactored Method of Morris so the Ruano et al. local approach is default
+
+### Bug Fixes:
+
+- Inputs to morris.analyze are provided as floats
+- Removed calls to standard random library as inconsistent between Python 2 & 3
+- First row in Sobol sequences should be zero, not empty
+
+### Documentation:
+
+- Added a Code of Conduct
+- Added DAETools, BCMD and others to citations - thanks for using SALib!
+- Removed misleading keyword arguments in docs and readme examples
+- Updated documentation for Method of Morris following refactor
+- Improved existing documentation where lacking e.g. for fractional factorial
+  method
+
+### Development Features:
+
+- Implemented automatic deployment to PyPi
+- Fixed a bug preventing automatic deployment to PyPi upon tagging a branch
+- Removed postgres from travis config
+
+## [1.0.0]
+
+Release of our stable version of SALIB to coincide with an submission to JOSS:
+
+- Added a paper for submission to the Journal of Open-source Software
+- Updated back-end for documentation on read-the-docs
+- Updated the back-end for version introspection using PyScaffold, rather than
+  versioneer
+- Updated the Travis-CI scripts
+- Moved the tests out of the SALib package and migrated to using pytest
+
+## [0.7.1]
+
+Improvements to Morris sampling and Sobol groups/distributions
+
+- Adds improved sampling for the Morris method
+  (thanks to @JoerivanEngelen) and group sampling/analysis for the Sobol method
+  (thanks to @calvinwhealton).
+- @calvinwhealton has also added non-uniform distributions to the Sobol
+  sampling.  This will be a baseline for adding this to the other methods in
+  the future.
+- Also includes several minor bug fixes.
+
+## [0.7.0]
+
+New documentation, doc strings and installation requirements
+
+- @dhadka has kindly contributed a wealth of documentation to the project,
+  including doc strings in every module
+- no longer test for numpy <1.8.0 and matplotlib < 1.4.3, and these
+  requirements are implemented in a new setup script.
+
+## [0.6.3]
+
+Parallel option for Sobol method
+
+- New option to run analyze.sobol function in parallel using multiprocessing
+
+## [0.6.2]
+
+This release does not contain any new functionality, but SALib now is citable
+using a Digital Object Identifier (DOI), which can be found in the readme.
+
+Some minor updates are included:
+
+- morris: sigma has been removed from the grouped-morris results and plots,
+  replaced by mu_star_conf - a bootstrapped confidence interval.
+  Mu_star_conf is not equivalent to sigma when used in the non-grouped method of
+  morris, but its all we have when using groups.
+- some minor updates to the tests in the plotting module
+
+## [0.6.0]
+
+- Set up to include and test plotting functions
+- Specific plotting functions for Morris
+- Fractional Factorial SA from Saltelli et al.
+- Repo transferred to SALib organization, update setup and URLs
+- Small bugfixes
+
+## [0.5.0]
+
+- Vectorized bootstrap calculations for Morris and Sobol
+- Optional trajectory optimization with Gurobi, and tests for it
+- Several minor bugfixes
+- Starting with v0.5, SALib is released under the MIT license.
+
+## [0.4.0]
+
+- Better Python API without requiring file read/write to the OS.
+  Consistent functional API to sampling methods so that they return numpy
+  matrices. Analysis methods now accept numpy matrices instead of data file
+  names. This does not change the CLI at all, but makes it much easier to use
+  from native Python.
+- Also expanded tests for regression and the Sobol method.
+
+## [0.3.0]
+
+Improvements to Morris sampling and analysis methods,
+some bugfixes to make consistent with previous versions of the methods.
+
+## [0.2.0]
+
+Improvements to Morris sampling methods (support for group sampling,
+and optimized trajectories). Much better test coverage, and fixed Python 3
+compatibility.
+
+## [0.1.0]
+
+First numbered release. Contains reasonably well-tested versions of the Sobol,
+Morris, and FAST methods. Also contains newer additions of DGSM and delta
+methods which are not as well-tested yet. Contains setup.py for installation.

FAQ.MD

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+# FAQ
+
+## Installation
+
+Q. I get this error when installing SALib 1.3 with Python 2.7
+A. SALib 1.3 onwards does not support Python 2.7
+
+
+## Usage
+
+Q. I've already got results from my Monte Carlo simulation - which technique can I use?
+A. DMIM, RBD-FAST, and HDMR methods are sampling scheme independent.
+
+Q. Can you help me with implementing my sensitivity analysis?
+A. Check out [the examples here](https://github.com/SALib/SALib/tree/master/examples)
+
+Q. The example(s) use the Ishigami function. How do I use it with my own model?
+A.
+
+Q. How do I get my results?
+A. Call the `.to_df()` method if you would like Pandas DataFrames.
+   The numpy array can be obtained via `.analysis`
+
+Q. How can I plot my results?
+A. SALib provides some basic plotting functionality. See [the example here](https://github.com/SALib/SALib/tree/master/examples/plotting).
+
+
+

README-advanced.md

@@ -88,3 +88,59 @@ The output can then be converted to a Pandas DataFrame for further analysis.
 ```python
 total_Si, first_Si, second_Si = Si.to_df()
 ```
+
+
+### Generating alternate distributions
+
+In the [Quick Start](https://github.com/SALib/SALib/tree/master/README.rst) we
+generate a uniform sample of parameter space.
+
+```python
+from SALib.sample import saltelli
+from SALib.analyze import sobol
+from SALib.test_functions import Ishigami
+import numpy as np
+
+problem = {
+     'num_vars': 3, 
+     'names': ['x1', 'x2', 'x3'], 
+     'bounds': [[-3.14159265359, 3.14159265359], 
+               [-3.14159265359, 3.14159265359], 
+               [-3.14159265359, 3.14159265359]]
+}
+
+param_values = saltelli.sample(problem, 1000)
+```
+
+SALib is also capable of generating alternate sampling distributions by 
+specifying a `dist` entry in the `problem` specification.
+
+As implied in the basic example, a uniform distribution is the default.
+
+When an entry for `dist` is not 'unif', the `bounds` entry does not indicate
+parameter bounds but sample-specific metadata.
+
+`bounds` definitions for available distributions:
+
+* unif: uniform distribution
+    e.g. :code:`[-np.pi, np.pi]` defines the lower and upper bounds
+* triang: triangular with width (scale) and location of peak. 
+    Location of peak is in percentage of width.
+    Lower bound assumed to be zero.
+
+    e.g. :code:`[3, 0.5]` assumes 0 to 3, with a peak at 1.5
+* norm: normal distribution with mean and standard deviation
+* lognorm: lognormal with ln-space mean and standard deviation
+
+An example specification is shown below:
+
+```python
+problem = {
+     'names': ['x1', 'x2', 'x3'],
+     'num_vars': 3,
+     'bounds': [[-np.pi, np.pi], [1.0, 0.2], [3, 0.5]],
+     'groups': ['G1', 'G2', 'G1'],
+     'dists': ['unif', 'lognorm', 'triang']
+}
+```
+