Automated code and docstring formatting

.github/workflows/ci_test.yml

@@ -14,20 +14,21 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.8]
+        python-version: [3.11]
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install dependencies
         run: |
           echo "NUMBA_DISABLE_JIT=false" >> $GITHUB_ENV  # disable numba.jit as it causes issues with JAX
           python -m pip install --upgrade pip
           python -m pip install --upgrade pytest
-          python -m pip install flake8 pytest pytest-cov coveralls
+          python -m pip install flake8 pytest pytest-cov
+          python -m pip install codecov
           if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
           if [ -f test_requirements.txt ]; then pip install -r test_requirements.txt; fi
           python -m pip install .
@@ -40,10 +41,36 @@ jobs:
       #    flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
       - name: Test with pytest
         run: |
-          pytest --cov=jaxtronomy
+          pytest --cov=./ --cov-report=xml
+          codecov
 
-      - name: Coveralls
+      - name: Upload coverage reports to Codecov
+        uses: codecov/codecov-action@v3
         env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          coveralls --service=github
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+        with:
+          files: ./coverage.xml
+
+#      - name: Coveralls
+#        env:
+#          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+#        run: |
+#          coveralls --service=github
+
+      # from this source for coveralls: https://github.com/marketplace/actions/coveralls-github-action
+      #- uses: actions/checkout@v1
+
+      #- name: Use Node.js 10.x
+      #  uses: actions/setup-node@v1
+      #  with:
+      #    node-version: 10.x
+
+      #- name: npm install, make test-coverage
+      #  run: |
+      #    npm install
+      #    make test-coverage
+
+      #- name: Coveralls
+      #  uses: coverallsapp/github-action@master
+      #  with:
+      #    github-token: ${{ secrets.GITHUB_TOKEN }}

.gitignore

@@ -128,5 +128,5 @@ dmypy.json
 # Pyre type checker
 .pyre/
 
-# macOS cache files
+.idea/*
 **/.DS_Store

.pre-commit-config.yaml

@@ -0,0 +1,33 @@
+ci:
+    autofix_commit_msg: |
+        [pre-commit.ci] auto fixes from pre-commit.com hooks
+
+        for more information, see https://pre-commit.ci
+    autofix_prs: true
+    autoupdate_branch: ''
+    autoupdate_commit_msg: '[pre-commit.ci] pre-commit autoupdate'
+    autoupdate_schedule: weekly
+    skip: []
+    submodules: false
+
+repos:
+  - repo: https://github.com/psf/black
+    rev: 24.2.0
+    hooks:
+      - id: black
+        # It is recommended to specify the latest version of Python
+        # supported by your project here, or alternatively use
+        # pre-commit's default_language_version, see
+        # https://pre-commit.com/#top_level-default_language_version
+        language_version: python3
+  - repo: https://github.com/psf/black
+    rev: 24.2.0
+    hooks:
+      - id: black-jupyter
+        language_version: python3
+  - repo: https://github.com/PyCQA/docformatter
+    rev: v1.7.5
+    hooks:
+      - id: docformatter
+        additional_dependencies: [tomli]
+        args: [-r, --black, --in-place]

README.rst

@@ -8,6 +8,18 @@ JAXtronomy
 .. image:: https://img.shields.io/badge/License-BSD_3--Clause-blue.svg
     :target: https://github.com/lenstronomy/lenstronomy/blob/main/LICENSE
 
+.. image:: https://codecov.io/gh/lenstronomy/JAXtronomy/graph/badge.svg?token=6EJAX8CF62 
+    :target: https://codecov.io/gh/lenstronomy/JAXtronomy
+
+.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
+    :target: https://github.com/psf/black
+
+.. image:: https://img.shields.io/badge/%20formatter-docformatter-fedcba.svg
+    :target: https://github.com/PyCQA/docformatter
+
+.. image:: https://img.shields.io/badge/%20style-sphinx-0a507a.svg
+    :target: https://www.sphinx-doc.org/en/master/usage/index.html
+
 
 
 **JAX port of lenstronomy, for parallelized, GPU accelerated, and differentiable gravitational lensing and image simulations.**

codecov.yml

@@ -0,0 +1,10 @@
+comment:                  # this is a top-level key
+  layout: " diff, flags, files"
+  behavior: default
+  require_changes: false  # if true: only post the comment if coverage changes
+  require_base: false        # [true :: must have a base report to post]
+  require_head: true       # [true :: must have a head report to post]
+ignore:
+  - "setup.py"
+  - "test/*"
+  - "test/**/*.py"

jaxtronomy/LensModel/Profiles/p_jaffe.py

@@ -354,4 +354,3 @@ def _sort_ra_rs(Ra, Rs):
         Ra = jnp.where(Rs < Ra, Rs, Ra)
         Rs = jnp.where(Rs < Ra, Ra, Rs)
         return Ra, Rs
-

jaxtronomy/__init__.py

@@ -1,2 +1,2 @@
-__author__ = 'lenstronomy developers'
-__version__ = '0.0.1rc1'
+__author__ = "lenstronomy developers"
+__version__ = "0.0.1rc1"

setup.py

@@ -19,7 +19,7 @@
     license="BSD-3",
     install_requires=requires,
     tests_require=tests_require,
-    keywords='lenstronomy',
+    keywords="lenstronomy",
     classifiers=[
         "Development Status :: 1 - Alpha",
         "Intended Audience :: Science/Research",
@@ -29,4 +29,4 @@
         "Programming Language :: Python :: 3.8",
         "Programming Language :: Python :: 3.9",
     ],
-)
+)

test/test_LensModel/test_Profiles/test_p_jaffe.py

@@ -7,7 +7,8 @@
 import numpy.testing as npt
 import pytest
 import jax
-jax.config.update('jax_enable_x64', True)  # 64-bit floats, consistent with numpy
+
+jax.config.update("jax_enable_x64", True)  # 64-bit floats, consistent with numpy
 import jax.numpy as jnp
 
 
@@ -71,7 +72,9 @@ def test_hessian(self):
         sigma0 = 1.0
         Ra, Rs = 0.5, 0.8
         f_xx, f_xy, f_yx, f_yy = self.profile.hessian(x, y, sigma0, Ra, Rs)
-        f_xx_ref, f_xy_ref, f_yx_ref, f_yy_ref = self.profile_ref.hessian(x, y, sigma0, Ra, Rs)
+        f_xx_ref, f_xy_ref, f_yx_ref, f_yy_ref = self.profile_ref.hessian(
+            x, y, sigma0, Ra, Rs
+        )
         npt.assert_almost_equal(f_xx, f_xx_ref, decimal=8)
         npt.assert_almost_equal(f_xy, f_xy_ref, decimal=8)
         npt.assert_almost_equal(f_yy, f_yy_ref, decimal=8)
@@ -80,7 +83,9 @@ def test_hessian(self):
         x = np.array([1, 3, 4])
         y = np.array([2, 1, 1])
         f_xx, f_xy, f_yx, f_yy = self.profile.hessian(x, y, sigma0, Ra, Rs)
-        f_xx_ref, f_xy_ref, f_yx_ref, f_yy_ref = self.profile_ref.hessian(x, y, sigma0, Ra, Rs)
+        f_xx_ref, f_xy_ref, f_yx_ref, f_yy_ref = self.profile_ref.hessian(
+            x, y, sigma0, Ra, Rs
+        )
         npt.assert_array_almost_equal(f_xx, f_xx_ref, decimal=8)
         npt.assert_array_almost_equal(f_xy, f_xy_ref, decimal=8)
         npt.assert_array_almost_equal(f_yy, f_yy_ref, decimal=8)
@@ -143,16 +148,25 @@ def test_jax_jit(self):
         sigma0 = 1.0
         Ra, Rs = 0.5, 0.8
         jitted = jax.jit(self.profile.function)
-        npt.assert_almost_equal(self.profile.function(x, y, sigma0, Ra, Rs), 
-                                jitted(x, y, sigma0, Ra, Rs), decimal=8)
+        npt.assert_almost_equal(
+            self.profile.function(x, y, sigma0, Ra, Rs),
+            jitted(x, y, sigma0, Ra, Rs),
+            decimal=8,
+        )
 
         jitted = jax.jit(self.profile.derivatives)
-        npt.assert_array_almost_equal(self.profile.derivatives(x, y, sigma0, Ra, Rs), 
-                                      jitted(x, y, sigma0, Ra, Rs), decimal=8)
+        npt.assert_array_almost_equal(
+            self.profile.derivatives(x, y, sigma0, Ra, Rs),
+            jitted(x, y, sigma0, Ra, Rs),
+            decimal=8,
+        )
 
         jitted = jax.jit(self.profile.hessian)
-        npt.assert_array_almost_equal(self.profile.hessian(x, y, sigma0, Ra, Rs), 
-                                      jitted(x, y, sigma0, Ra, Rs), decimal=8)
+        npt.assert_array_almost_equal(
+            self.profile.hessian(x, y, sigma0, Ra, Rs),
+            jitted(x, y, sigma0, Ra, Rs),
+            decimal=8,
+        )
 
 
 if __name__ == "__main__":

test/test_LensModel/test_Profiles/test_p_jaffe_ellipse.py

@@ -2,14 +2,17 @@
 
 
 from jaxtronomy.LensModel.Profiles.p_jaffe_ellipse import PJaffe_Ellipse
-from lenstronomy.LensModel.Profiles.p_jaffe_ellipse import PJaffe_Ellipse as PJaffe_Ellipse_ref
+from lenstronomy.LensModel.Profiles.p_jaffe_ellipse import (
+    PJaffe_Ellipse as PJaffe_Ellipse_ref,
+)
 import jaxtronomy.Util.param_util as param_util
 
 import numpy as np
 import numpy.testing as npt
 import pytest
 import jax
-jax.config.update('jax_enable_x64', True)  # 64-bit floats, consistent with numpy
+
+jax.config.update("jax_enable_x64", True)  # 64-bit floats, consistent with numpy
 import jax.numpy as jnp
 
 
@@ -126,7 +129,9 @@ def test_hessian(self):
 
     def test_mass_3d_lens(self):
         mass = self.profile.mass_3d_lens(r=1, sigma0=1, Ra=0.5, Rs=0.8, e1=0, e2=0)
-        mass_ref = self.profile_ref.mass_3d_lens(r=1, sigma0=1, Ra=0.5, Rs=0.8, e1=0, e2=0)
+        mass_ref = self.profile_ref.mass_3d_lens(
+            r=1, sigma0=1, Ra=0.5, Rs=0.8, e1=0, e2=0
+        )
         npt.assert_almost_equal(mass, mass_ref, decimal=8)
 
     def test_jax_jit(self):
@@ -137,16 +142,25 @@ def test_jax_jit(self):
         q, phi_G = 0.8, 0.1
         e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
         jitted = jax.jit(self.profile.function)
-        npt.assert_almost_equal(self.profile.function(x, y, sigma0, Ra, Rs, e1, e2), 
-                                jitted(x, y, sigma0, Ra, Rs, e1, e2), decimal=8)
+        npt.assert_almost_equal(
+            self.profile.function(x, y, sigma0, Ra, Rs, e1, e2),
+            jitted(x, y, sigma0, Ra, Rs, e1, e2),
+            decimal=8,
+        )
 
         jitted = jax.jit(self.profile.derivatives)
-        npt.assert_array_almost_equal(self.profile.derivatives(x, y, sigma0, Ra, Rs, e1, e2), 
-                                      jitted(x, y, sigma0, Ra, Rs, e1, e2), decimal=8)
+        npt.assert_array_almost_equal(
+            self.profile.derivatives(x, y, sigma0, Ra, Rs, e1, e2),
+            jitted(x, y, sigma0, Ra, Rs, e1, e2),
+            decimal=8,
+        )
 
         jitted = jax.jit(self.profile.hessian)
-        npt.assert_array_almost_equal(self.profile.hessian(x, y, sigma0, Ra, Rs, e1, e2), 
-                                      jitted(x, y, sigma0, Ra, Rs, e1, e2), decimal=8)
+        npt.assert_array_almost_equal(
+            self.profile.hessian(x, y, sigma0, Ra, Rs, e1, e2),
+            jitted(x, y, sigma0, Ra, Rs, e1, e2),
+            decimal=8,
+        )
 
 
 if __name__ == "__main__":

test/test_Util/test_param_util.py

@@ -5,7 +5,8 @@
 import jaxtronomy.Util.param_util as param_util
 import lenstronomy.Util.param_util as param_util_ref
 import jax
-jax.config.update('jax_enable_x64', True)  # 64-bit floats, consistent with numpy
+
+jax.config.update("jax_enable_x64", True)  # 64-bit floats, consistent with numpy
 import jax.numpy as jnp
 
 

test/test_lenstronomy_import.py

@@ -0,0 +1,5 @@
+def test_lenstronomy_version():
+    """Tests the import of lenstronomy."""
+    import lenstronomy
+
+    assert lenstronomy.__version__ == "1.11.7"