Create a workflow which tests gd_bugfix branch of diffsky

.github/workflows/gd_bugfix_rapid_q.yaml

@@ -0,0 +1,84 @@
+name: pytest against diffsky:gd_bugfix
+
+on:
+  workflow_dispatch: null
+  schedule:
+    # Runs "every Monday & Thursday at 3:05am Central"
+    - cron: '5 8 * * 1,4'
+  push:
+    branches:
+      - main
+  pull_request: null
+
+jobs:
+  tests:
+    name: pytest with diffsky@gd_bugfix_rapid_q
+    runs-on: "ubuntu-latest"
+
+    steps:
+      - uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+
+      - uses: conda-incubator/setup-miniconda@v3
+        with:
+          python-version: 3.11
+          channels: conda-forge,defaults
+          channel-priority: strict
+          show-channel-urls: true
+          miniforge-version: latest
+
+      - name: configure conda and install code
+        shell: bash -l {0}
+        run: |
+          conda config --set always_yes yes
+          conda install --quiet \
+            --file=requirements.txt
+          conda install -y -q \
+            flake8 \
+            pytest \
+            pytest-xdist \
+            pytest-cov \
+            pip \
+            setuptools \
+            "setuptools_scm>=7,<8" \
+            scipy \
+            python-build
+          pip uninstall diffsky --yes
+          pip install --no-deps git+https://github.com/ArgonneCPAC/diffsky.git@gd_bugfix_rapid_q
+
+          python -m pip install --no-build-isolation --no-deps -e .
+
+      - name: test
+        shell: bash -l {0}
+        run: |
+          pytest -v diffhtwo --cov --cov-report=xml
+
+      - name: Upload coverage reports to Codecov
+        uses: codecov/codecov-action@v5
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+
+      - name: test versions
+        shell: bash -el {0}
+        run: |
+          pip uninstall diffhtwo --yes
+          [[ $(python setup.py --version) != "0.0.0" ]] || exit 1
+
+          rm -rf dist/*
+          python setup.py sdist
+          pip install --no-deps --no-build-isolation dist/*.tar.gz
+          pushd ..
+          python -c "import diffhtwo; assert diffhtwo.__version__ != '0.0.0'"
+          popd
+          pip uninstall diffhtwo --yes
+
+          rm -rf dist/*
+          python -m build --sdist . --outdir dist
+          pip install --no-deps --no-build-isolation dist/*.tar.gz
+          pushd ..
+          python -c "import diffhtwo; assert diffhtwo.__version__ != '0.0.0'"
+          popd
+          pip uninstall diffhtwo --yes
+
+          python -m pip install -v --no-deps --no-build-isolation -e .

diffhtwo/experimental/conftest.py

@@ -23,6 +23,11 @@
 ZOUT = "feniks_zout_selected_for_testing.ecsv"
 
 
+@pytest.fixture(scope="session")
+def ran_key():
+    return jran.key(0)
+
+
 @pytest.fixture(scope="session")
 def fake_subset_ssp_data():
     ssp_data = retrieve_fake_fsps_data.load_fake_ssp_data()
@@ -33,9 +38,9 @@ def fake_subset_ssp_data():
 
 
 @pytest.fixture(scope="session")
-def feniks(fake_subset_ssp_data):
+def feniks(ran_key, fake_subset_ssp_data):
     ssp_data, emline_wave_aa = fake_subset_ssp_data
-    ran_key = jran.key(0)
+
     feniks = load_feniks.get_feniks_data(
         FENIKS_DRN,
         ran_key,
@@ -47,9 +52,9 @@ def feniks(fake_subset_ssp_data):
 
 
 @pytest.fixture(scope="session")
-def hizels(fake_subset_ssp_data, feniks_tcurves):
+def hizels(ran_key, fake_subset_ssp_data, feniks_tcurves):
     ssp_data, emline_wave_aa = fake_subset_ssp_data
-    ran_key = jran.key(0)
+
     hizels = load_hizels.get_hizels_data(
         HIZELS_DRN,
         ran_key,
@@ -71,14 +76,13 @@ def feniks_tcurves():
 
 
 @pytest.fixture(scope="session")
-def feniks_single_z_data(fake_subset_ssp_data, feniks):
+def feniks_single_z_data(ran_key, fake_subset_ssp_data, feniks):
     ssp_data, emline_wave_aa = fake_subset_ssp_data
 
     z_min = 0.2
     z_max = 1.0
     N_centroids = 100
 
-    ran_key = jran.key(0)
     feniks_meta_data, feniks_fitting_data = lhu.get_single_zbin_lh_lc(
         ran_key,
         feniks,
@@ -91,15 +95,16 @@ def feniks_single_z_data(fake_subset_ssp_data, feniks):
 
 
 @pytest.fixture(scope="session")
-def feniks_multi_z_data(fake_subset_ssp_data, feniks):
+def feniks_multi_z_data(ran_key, fake_subset_ssp_data, feniks):
     ssp_data, emline_wave_aa = fake_subset_ssp_data
 
-    ran_key = jran.key(0)
+    feniks_z_min = [0.2, 1]
+    feniks_z_max = [1, 2]
 
-    z_mins = [0.2, 1.0]
-    z_maxs = [1.0, 2.0]
+    z_mins = feniks_z_min[:2]
+    z_maxs = feniks_z_max[:2]
 
-    N_centroids = 200
+    N_centroids = 100
     num_halos = 100
     feniks_meta_data, feniks_fitting_data = lhu.get_zbins_lh_lc(
         ran_key,
@@ -114,22 +119,20 @@ def feniks_multi_z_data(fake_subset_ssp_data, feniks):
 
 
 @pytest.fixture(scope="session")
-def feniks_lc_data(fake_subset_ssp_data, feniks):
+def feniks_lc_data(ran_key, fake_subset_ssp_data, feniks):
     ssp_data, emline_wave_aa = fake_subset_ssp_data
     tcurves = feniks.filter_info.tcurves
 
-    ran_key = jran.key(0)
-
     z_min = 0.2
-    z_max = 0.5
+    z_max = 1.0
     n_z_phot_table = 15
     z_phot_table = 10 ** jnp.linspace(
         jnp.log10(z_min), jnp.log10(z_max), n_z_phot_table
     )
 
     num_halos = 100
     lgmp_min = 10.0
-    lgmp_max = 15
+    lgmp_max = 15.0
     lc_sky_area_degsq = 100
 
     lc_data = generate_lc_data(