Merge pull request #21 from Autostronomy/versionreqs

Refactor for better version control
Autostronomy · Aug 15, 2024 · 82035d3 · 82035d3
2 parents 4e11bbe + 66580fc
commit 82035d3
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diff --git a/.github/workflows/cd.yaml b/.github/workflows/cd.yaml
@@ -0,0 +1,100 @@
+name: CD
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+      - dev
+  release:
+    types:
+      - published
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+env:
+  FORCE_COLOR: 3
+
+jobs:
+  dist:
+    name: Distribution build
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Build sdist and wheel
+        run: pipx run build
+
+      - uses: actions/upload-artifact@v4
+        with:
+          path: dist
+
+      - name: Check products
+        run: pipx run twine check dist/*
+
+  test-built-dist:
+    needs: [dist]
+    name: Test built distribution
+    runs-on: ubuntu-latest
+    environment: deploy-testpypi
+    permissions:
+      id-token: write
+    steps:
+      - uses: actions/setup-python@v5
+        name: Install Python
+        with:
+          python-version: "3.10"
+      - uses: actions/download-artifact@v4
+        with:
+          name: artifact
+          path: dist
+      - name: List contents of built dist
+        run: |
+          ls -ltrh
+          ls -ltrh dist
+      - name: Publish to Test PyPI
+        uses: pypa/gh-action-pypi-publish@v1.9.0
+        with:
+          repository-url: https://test.pypi.org/legacy/
+          verbose: true
+          skip-existing: true
+      - name: Check test pypi packages
+        run: |
+          sleep 3
+          python -m pip install --upgrade pip
+
+          echo "=== Testing wheel file ==="
+          # Install wheel to get dependencies and check import
+          python -m pip install --extra-index-url https://test.pypi.org/simple --upgrade --pre autoprof
+          python -c "import autoprof; print(autoprof.__version__)"
+          echo "=== Done testing wheel file ==="
+
+          echo "=== Testing source tar file ==="
+          # Install tar gz and check import
+          python -m pip uninstall --yes autoprof
+          python -m pip install --extra-index-url https://test.pypi.org/simple --upgrade --pre --no-binary=:all: autoprof
+          python -c "import autoprof; print(autoprof.__version__)"
+          echo "=== Done testing source tar file ==="
+
+  publish:
+    needs: [dist, test-built-dist]
+    name: Publish to PyPI
+    environment: deploy-pypi
+    permissions:
+      id-token: write
+    runs-on: ubuntu-latest
+    if: github.event_name == 'release' && github.event.action == 'published'
+
+    steps:
+      - uses: actions/download-artifact@v4
+        with:
+          name: artifact
+          path: dist
+
+      - uses: pypa/gh-action-pypi-publish@v1.9.0
+        if: startsWith(github.ref, 'refs/tags')
diff --git a/.github/workflows/testing.yaml b/.github/workflows/testing.yaml
@@ -0,0 +1,51 @@
+name: Unit Tests
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+      - dev
+  workflow_dispatch:
+
+jobs:
+  build:
+    runs-on: ${{matrix.os}}
+    strategy:
+      matrix:
+        python-version: ["3.9", "3.10", "3.11"]
+        os: [ubuntu-latest, windows-latest, macOS-latest]
+    steps:
+      - uses: actions/checkout@master
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Record State
+        run: |
+          pwd
+          echo github.ref is: ${{ github.ref }}
+          echo GITHUB_SHA is: $GITHUB_SHA
+          echo github.event_name is: ${{ github.event_name }}
+          pip --version
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install pytest
+          pip install wheel
+          if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+        shell: bash
+      - name: Install AutoProf
+        run: |
+          cd $GITHUB_WORKSPACE/
+          pip install .
+          pip show AutoProf
+        shell: bash
+      - name: Test with pytest
+        run: |
+          cd $GITHUB_WORKSPACE/tests/
+          pwd
+          pytest -s
+        shell: bash
diff --git a/README.md b/README.md
@@ -13,15 +13,25 @@ and [Jean-Charles Cuillandre](https://www.cfht.hawaii.edu/~jcc/).
 pip install autoprof
 ```
 
+Please use python version 3.9 or greater.
+
 # Documentation
 
-See our [documentation](https://autoprof.readthedocs.io/en/latest/) for a full description of AutoProf's capabilities
+See our [documentation](https://autoprof.readthedocs.io) for a full description
+of AutoProf's capabilities
 
 # Citation
 
-Please see the [ADS Bibliographic Record](https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.1870S/abstract) of the AutoProf paper for proper citation.
+Please see the [ADS Bibliographic
+Record](https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.1870S/abstract) of the
+AutoProf paper for proper citation.
 
 # Notice
 
-This is the AutoProf isophotal code, it works great in its domain which is wherever one would use isophotal fitting. Thus it is suitable for mostly isolated, mostly resolved, objects. If you are limited by the PSF, crowding, or want to model multi-band/epoch data you may want to consider "AstroPhot" a full forward modelling code. Just [follow this link](https://github.com/Autostronomy/AstroPhot) to check it out!
+This is the AutoProf isophotal code, it works great in its domain which is
+wherever one would use isophotal fitting. Thus it is suitable for mostly
+isolated, mostly resolved, objects. If you are limited by the PSF, crowding, or
+want to model multi-band/epoch data you may want to consider "AstroPhot" a full
+forward modelling code. Just [follow this
+link](https://github.com/Autostronomy/AstroPhot) to check it out!
 
diff --git a/autoprof/__init__.py b/autoprof/__init__.py
@@ -3,7 +3,16 @@
 
 from . import autoprofutils, Pipeline, pipeline_steps
 
-__version__ = "1.2.1"
+try:
+    from ._version import version as __version__  # noqa
+except ModuleNotFoundError:
+    __version__ = "0.0.0"
+    import warnings
+
+    warnings.warn(
+        "WARNING: AutoProf version number not found. This is likely because you are running Autoprof from a source directory."
+    )
+
 __author__ = "Connor Stone"
 __email__ = "connorstone628@gmail.com"
 
@@ -16,6 +25,9 @@ def run_from_terminal():
 
     config_file = sys.argv[1]
 
+    if config_file.strip().lower() == "--version":
+        print(__version__)
+        return
     try:
         if ".log" == sys.argv[2][-4:]:
             logfile = sys.argv[2]

diff --git a/autoprof/autoprofutils/Diagnostic_Plots.py b/autoprof/autoprofutils/Diagnostic_Plots.py
@@ -1,31 +1,18 @@
 import numpy as np
-from astropy.visualization import SqrtStretch, LogStretch
+from astropy.visualization import LogStretch
 from astropy.visualization.mpl_normalize import ImageNormalize
 import matplotlib.pyplot as plt
 from matplotlib.patches import Ellipse, Wedge
-import matplotlib.cm as cm
 import matplotlib
 from itertools import compress
-import sys
 import os
 
 from .SharedFunctions import (
-    _x_to_pa,
-    _x_to_eps,
-    _inv_x_to_eps,
-    _inv_x_to_pa,
     LSBImage,
     AddScale,
     AddLogo,
-    _average,
-    _scatter,
-    flux_to_sb,
-    flux_to_mag,
-    PA_shift_convention,
     autocolours,
     autocmap,
-    fluxdens_to_fluxsum_errorprop,
-    mag_to_flux,
     parametric_SuperEllipse,
     Rotate_Cartesian,
 )
@@ -647,7 +634,7 @@ def Plot_Radial_Profiles(dat, R, sb, sbE, pa, nwedges, wedgeangles, wedgewidth,
         ],
     ]
 
-    cmap = cm.get_cmap("hsv")
+    cmap = matplotlib.colormaps["hsv"]
     colorind = (np.linspace(0, 1 - 1 / nwedges, nwedges) + 0.1) % 1.0
     for sa_i in range(len(wedgeangles)):
         CHOOSE = np.logical_and(np.array(sb[sa_i]) < 99, np.array(sbE[sa_i]) < 1)
@@ -767,7 +754,6 @@ def Plot_Axial_Profiles(dat, R, sb, sbE, pa, results, options):
     for rd in [1, -1]:
         for ang in [1, -1]:
             key = (rd, ang)
-            # cmap = matplotlib.cm.get_cmap('viridis_r')
             norm = matplotlib.colors.Normalize(vmin=0, vmax=R[-1] * options["ap_pixscale"])
             for pi, pR in enumerate(R):
                 if pi % 3 != 0:
@@ -858,7 +844,7 @@ def Plot_Axial_Profiles(dat, R, sb, sbE, pa, results, options):
     )
     AddScale(plt.gca(), (ranges[0][1] - ranges[0][0]) * options["ap_pixscale"])
     count = 0
-    cmap = matplotlib.cm.get_cmap("hsv")
+    cmap = matplotlib.colormaps["hsv"]
     colorind = (np.linspace(0, 1 - 1 / 4, 4) + 0.1) % 1
     colours = list(cmap(c) for c in colorind)
     for rd in [1, -1]:

diff --git a/docs/getting_started.rst b/docs/getting_started.rst
@@ -136,14 +136,14 @@ Here is the forced photometry file just make sure to save it as a ``.py`` file::
 
     ap_process_mode = "forced image"
     
-    ap_image_file = "test_ESO479-G1_r.fits"
+    ap_image_file = "ESO479-G1_r.fits"
     ap_name = "testforcedimage"
     ap_pixscale = 0.262
     ap_doplot = True
     ap_isoclip = True
     ap_forcing_profile = "testimage.prof"
 
-
+To try out this pipeline, download the `test file <https://github.com/Autostronomy/AutoProf/raw/main/tests/ESO479-G1_r.fits>`_.
 
 Batch Forced Photometry
 -----------------------
@@ -162,7 +162,7 @@ It's possible to incorporate descision trees into the AutoProf pipeline. This is
 
     ap_process_mode = "image"
 
-    ap_image_file = "test_ESO479-G1_r.fits"
+    ap_image_file = "ESO479-G1_r.fits"
     ap_pixscale = 0.262
     ap_name = "testtreeimage"
     ap_doplot = True
@@ -251,3 +251,4 @@ It's possible to incorporate descision trees into the AutoProf pipeline. This is
         ],
     }
 
+To try out this pipeline, download the `test file <https://github.com/Autostronomy/AutoProf/raw/main/tests/ESO479-G1_r.fits>`_.