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mdbarnesUCSDmdbarnesUCSD
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Merge pull request #194 from SigProfilerSuite/ci-switch
Ci switch
2 parents 26a966c + caa3bbb commit d7deef0

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-184
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‎.github/workflows/ci.yml‎

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name: CI
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on:
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push:
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branches:
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- main
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pull_request:
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branches:
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- main
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permissions:
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contents: read
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packages: write
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jobs:
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test:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ['3.9', '3.12']
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install system dependencies
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run: |
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sudo apt-get update
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sudo apt-get install -y poppler-utils
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- name: Upgrade pip, setuptools, and packaging
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run: |
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python -m pip install --upgrade pip setuptools packaging
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- name: Cache src directory
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uses: actions/cache@v4
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with:
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path: ./src/
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key: ${{ runner.os }}-src-grch37
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restore-keys: |
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${{ runner.os }}-src-
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- name: Download GRCh37.tar.gz if not present
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run: |
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if [ ! -f ./src/GRCh37.tar.gz ]; then
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wget --connect-timeout=10 --tries=20 ftp://alexandrovlab-ftp.ucsd.edu/pub/tools/SigProfilerMatrixGenerator/GRCh37.tar.gz -P ./src/
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fi
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- name: Install package with tests
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run: |
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pip install .[tests]
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- name: Install genome
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run: |
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python install_genome.py ${{ github.workspace }}/src/
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- name: Run unit tests
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run: |
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pytest tests
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- name: Run integration test
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run: |
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python3 test.py
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- name: Build and push Docker image
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if: github.ref == 'refs/heads/main' && github.event_name == 'push' && matrix.python-version == '3.12'
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run: |
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echo "Starting Docker deployment to GHCR for sigprofilersuite..."
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VERSION_TAG=$(grep "VERSION = " setup.py | cut -d'"' -f2)
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# Get the repository name and convert it to lowercase
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REPO_NAME=$(basename ${{ github.repository }} | tr '[:upper:]' '[:lower:]')
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IMAGE_NAME="ghcr.io/sigprofilersuite/$REPO_NAME"
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echo "Building version: $VERSION_TAG for image: $IMAGE_NAME"
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echo "${{ secrets.GITHUB_TOKEN }}" | docker login ghcr.io \
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--username "${{ github.actor }}" \
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--password-stdin
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docker build \
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--build-arg COMMIT_SHA=${{ github.sha }} \
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-t $IMAGE_NAME:$VERSION_TAG \
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-t $IMAGE_NAME:latest .
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docker push $IMAGE_NAME:$VERSION_TAG
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docker push $IMAGE_NAME:latest
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echo "Docker deployment to GHCR successful"

‎.travis.yml‎

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This file was deleted.

‎CHANGELOG.md‎

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## [Unreleased]
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## [1.1.2] - 2026-01-23
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### Fixed
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- Fixed Python 3.12 compatibility issues with pandas DataFrame/Series indexing and method calls:
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- Updated `to_csv()` calls to use keyword arguments (`sep="\t"`) instead of positional arguments
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- Changed DataFrame/Series index access from `[0]` to `.iloc[0]` throughout the codebase
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- Fixed dtype assignment when converting columns to strings with "%" suffix
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### Changed
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- Switched CI/CD from Travis CI to GitHub Actions. Updated README badge to reflect the new CI/CD platform.
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## [1.1.1] - 2026-01-06
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### Added
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- Added missing COSMIC v3.5 signature files: exome versions for all supported genome builds, mm39 genome build signatures, and rn7 genome build signatures.

‎README.md‎

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[![Docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://osf.io/mz79v/wiki/home/)
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[![License](https://img.shields.io/badge/License-BSD\%202--Clause-orange.svg)](https://opensource.org/licenses/BSD-2-Clause)
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[![Build Status](https://api.travis-ci.com/AlexandrovLab/SigProfilerAssignment.svg?branch=main)](https://app.travis-ci.com/AlexandrovLab/SigProfilerAssignment)
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[![CI](https://github.com/SigProfilerSuite/SigProfilerAssignment/actions/workflows/ci.yml/badge.svg)](https://github.com/SigProfilerSuite/SigProfilerAssignment/actions/workflows/ci.yml)
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<img src="SigProfilerAssignment/figures/SigProfilerAssignment.png" alt="drawing" width="1000"/>
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‎SigProfilerAssignment/DecompositionPlots/PlotDecomposition_CNV48.py‎

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# c_draw - (Canvas) The canvas to draw the graph decomposition on.
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# statistics - (Pandas Dataframe) Dataframe w/ calculations
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def draw_statistics(c_draw, statistics, sig_version, custom_text):
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cos_sim = statistics["Cosine Similarity"][0]
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cor_coeff = statistics["Correlation Coefficient"][0]
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l1_norm_percent = statistics["L1 Norm %"][0]
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l2_norm_percent = statistics["L2 Norm %"][0]
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kl_divergence = statistics["KL Divergence"][0]
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cos_sim = statistics["Cosine Similarity"].iloc[0]
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cor_coeff = statistics["Correlation Coefficient"].iloc[0]
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l1_norm_percent = statistics["L1 Norm %"].iloc[0]
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l2_norm_percent = statistics["L2 Norm %"].iloc[0]
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kl_divergence = statistics["KL Divergence"].iloc[0]
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c_draw.drawString(
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WIDTH_GAP + 15,

‎SigProfilerAssignment/DecompositionPlots/PlotDecomposition_DBS78.py‎

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# c_draw - (Canvas) The canvas to draw the graph decomposition on.
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# statistics - (Pandas Dataframe) Dataframe w/ calculations
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def draw_statistics(c_draw, statistics, sig_version, custom_text):
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cos_sim = statistics["Cosine Similarity"][0]
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cor_coeff = statistics["Correlation Coefficient"][0]
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l1_norm_percent = statistics["L1 Norm %"][0]
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l2_norm_percent = statistics["L2 Norm %"][0]
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kl_divergence = statistics["KL Divergence"][0]
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cos_sim = statistics["Cosine Similarity"].iloc[0]
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cor_coeff = statistics["Correlation Coefficient"].iloc[0]
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l1_norm_percent = statistics["L1 Norm %"].iloc[0]
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l2_norm_percent = statistics["L2 Norm %"].iloc[0]
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kl_divergence = statistics["KL Divergence"].iloc[0]
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c_draw.drawString(
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WIDTH_GAP + 15,

‎SigProfilerAssignment/DecompositionPlots/PlotDecomposition_ID83.py‎

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# c_draw - (Canvas) The canvas to draw the graph decomposition on.
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# statistics - (Pandas Dataframe) Dataframe w/ calculations
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def draw_statistics(c_draw, statistics, sig_version, custom_text):
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cos_sim = statistics["Cosine Similarity"][0]
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cos_dist = statistics["Cosine Distance"][0]
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cor_dist = statistics["Correlation Distance"][0]
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cor_coeff = statistics["Correlation Coefficient"][0]
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l1_norm_percent = statistics["L1 Norm %"][0]
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l2_norm_percent = statistics["L2 Norm %"][0]
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kl_divergence = statistics["KL Divergence"][0]
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cos_sim = statistics["Cosine Similarity"].iloc[0]
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cos_dist = statistics["Cosine Distance"].iloc[0]
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cor_dist = statistics["Correlation Distance"].iloc[0]
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cor_coeff = statistics["Correlation Coefficient"].iloc[0]
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l1_norm_percent = statistics["L1 Norm %"].iloc[0]
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l2_norm_percent = statistics["L2 Norm %"].iloc[0]
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kl_divergence = statistics["KL Divergence"].iloc[0]
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c_draw.drawString(
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WIDTH_GAP + 15,

‎SigProfilerAssignment/DecompositionPlots/PlotDecomposition_SBS1536.py‎

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# c_draw - (Canvas) The canvas to draw the graph decomposition on.
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# statistics - (Pandas Dataframe) Dataframe w/ calculations
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def draw_statistics(c_draw, statistics, sig_version, custom_text):
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cos_sim = statistics["Cosine Similarity"][0]
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cor_coeff = statistics["Correlation Coefficient"][0]
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l1_norm_percent = statistics["L1 Norm %"][0]
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l2_norm_percent = statistics["L2 Norm %"][0]
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kl_divergence = statistics["KL Divergence"][0]
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cos_sim = statistics["Cosine Similarity"].iloc[0]
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cor_coeff = statistics["Correlation Coefficient"].iloc[0]
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l1_norm_percent = statistics["L1 Norm %"].iloc[0]
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l2_norm_percent = statistics["L2 Norm %"].iloc[0]
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kl_divergence = statistics["KL Divergence"].iloc[0]
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c_draw.drawString(
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WIDTH_GAP + 15,

‎SigProfilerAssignment/DecompositionPlots/PlotDecomposition_SBS288.py‎

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# c_draw - (Canvas) The canvas to draw the graph decomposition on.
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# statistics - (Pandas Dataframe) Dataframe w/ calculations
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def draw_statistics(c_draw, statistics, sig_version, custom_text):
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cos_sim = statistics["Cosine Similarity"][0]
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cor_coeff = statistics["Correlation Coefficient"][0]
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l1_norm_percent = statistics["L1 Norm %"][0]
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l2_norm_percent = statistics["L2 Norm %"][0]
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kl_divergence = statistics["KL Divergence"][0]
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cos_sim = statistics["Cosine Similarity"].iloc[0]
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cor_coeff = statistics["Correlation Coefficient"].iloc[0]
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l1_norm_percent = statistics["L1 Norm %"].iloc[0]
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l2_norm_percent = statistics["L2 Norm %"].iloc[0]
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kl_divergence = statistics["KL Divergence"].iloc[0]
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c_draw.drawString(
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‎SigProfilerAssignment/DecompositionPlots/PlotDecomposition_SBS96.py‎

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# c_draw - (Canvas) The canvas to draw the graph decomposition on.
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# statistics - (Pandas Dataframe) Dataframe w/ calculations
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def draw_statistics(c_draw, statistics, sig_version, custom_text):
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cos_sim = statistics["Cosine Similarity"][0]
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cor_coeff = statistics["Correlation Coefficient"][0]
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l1_norm_percent = statistics["L1 Norm %"][0]
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l2_norm_percent = statistics["L2 Norm %"][0]
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kl_divergence = statistics["KL Divergence"][0]
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cos_sim = statistics["Cosine Similarity"].iloc[0]
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cor_coeff = statistics["Correlation Coefficient"].iloc[0]
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l1_norm_percent = statistics["L1 Norm %"].iloc[0]
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l2_norm_percent = statistics["L2 Norm %"].iloc[0]
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kl_divergence = statistics["KL Divergence"].iloc[0]
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c_draw.drawString(
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WIDTH_GAP + 15,

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