Merge branch 'develop' into staged

.github/workflows/ci_tests.yml

@@ -67,6 +67,44 @@ jobs:
       run: |
         tox -e ${{ matrix.toxenv }}
 
+  centos:
+    # Some PypeIt users have to run under CentOS and have run into unique issues. GitHub Actions does not
+    # provide CentOS as a runtime environment like it does Ubuntu. However, it can be used by running
+    # it as a container within a provided Ubuntu environment.
+    name: CentOS ${{ matrix.centos_ver }} ${{ matrix.toxenv }}
+    runs-on: ubuntu-latest
+
+    strategy:
+      matrix:
+        # Test both CentOS 7 and 8
+        centos_ver: [7, 8]
+        # Test both pip and conda for installing dependencies
+        toxenv: [test-alldeps, conda]
+
+    container:
+      image: "centos:${{ matrix.centos_ver }}"
+
+    steps:
+    - name: Install base CentOS dependencies
+      run: |
+        yum update -y && yum install -y wget git gcc
+    - name: Check out repository
+      uses: actions/checkout@v1
+      with:
+        fetch-depth: 0
+    - name: Install and configure miniconda
+      run: |
+        wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
+        bash ./miniconda.sh -b -p /conda
+        /conda/bin/conda update -y --all
+        /conda/bin/conda init
+    - name: Install base dependencies
+      run: |
+        source ~/.bashrc && python -m pip install --upgrade pip tox && python --version
+    - name: Test with tox
+      run: |
+        source ~/.bashrc && tox -e ${{ matrix.toxenv }}
+
   codestyle:
     runs-on: ubuntu-latest
     steps:

environment.yml

@@ -18,6 +18,6 @@ dependencies:
   - ginga>=3.0
   - qtpy>=1.9
   - pytest>=3.0.7
-  - bottleneck>=1.3
+  - bottleneck
   - pip
   - linetools>=0.3dev2231

pypeit/core/skysub.py

@@ -474,7 +474,7 @@ def optimal_bkpts(bkpts_optimal, bsp_min, piximg, sampmask, samp_frac=0.80,
 def local_skysub_extract(sciimg, sciivar, tilts, waveimg, global_sky, rn2_img,
                          thismask, slit_left, slit_righ, sobjs, ingpm=None,
                          spat_pix=None, adderr=0.01, bsp=0.6, trim_edg=(3,3),
-                         std=False, prof_nsigma=None, niter=4, box_rad=7, sigrej=3.5, bkpts_optimal=True,
+                         std=False, prof_nsigma=None, niter=4, extract_good_frac=0.005, box_rad=7, sigrej=3.5, bkpts_optimal=True,
                          debug_bkpts=False, force_gauss=False, sn_gauss=4.0, model_full_slit=False, model_noise=True, show_profile=False,
                          show_resids=False, use_2dmodel_mask=True, no_local_sky=False):
     """Perform local sky subtraction and  extraction
@@ -535,6 +535,8 @@ def local_skysub_extract(sciimg, sciivar, tilts, waveimg, global_sky, rn2_img,
             exponential at large distances from the trace.
         niter: int, default = 4
             Number of iterations for successive profile fitting and local sky-subtraction
+        extract_good_frac: float, default = 0.005
+            Minimum fraction of pixels along the spectral direction with good optimal extraction
         box_rad: int or float, default = 7
             Boxcar radius in *pixels* used for boxcar extraction.
         sigrej:
@@ -735,7 +737,8 @@ def local_skysub_extract(sciimg, sciivar, tilts, waveimg, global_sky, rn2_img,
                                             last_profile, box_rad, sobjs[iobj])
                     # If the extraction is bad do not update
                     if sobjs[iobj].OPT_MASK is not None:
-                        if sobjs[iobj].OPT_MASK.any():
+                        # if there is only one good pixel `extract.fit_profile` fails
+                        if np.sum(sobjs[iobj].OPT_MASK) > extract_good_frac * nspec:
                             flux = sobjs[iobj].OPT_COUNTS
                             fluxivar = sobjs[iobj].OPT_COUNTS_IVAR*sobjs[iobj].OPT_MASK
                             wave = sobjs[iobj].OPT_WAVE

pypeit/core/wavecal/autoid.py

@@ -1431,8 +1431,9 @@ def __init__(self, spec, par = None, ok_mask=None, islinelist=False,
                 self._line_lists = line_lists_all[np.where(line_lists_all['ion'] != 'UNKNWN')]
                 self._unknwns = line_lists_all[np.where(line_lists_all['ion'] == 'UNKNWN')]
             else:
+                restrict = spectrograph if self._par['use_instr_flag'] else None
                 self._line_lists = waveio.load_line_lists(
-                    self._lines, restrict_on_instr=spectrograph)
+                    self._lines, restrict_on_instr=restrict)
                 self._unknwns = waveio.load_unknown_list(self._lines)
 
         if self._use_unknowns:

pypeit/core/wavecal/waveio.py

@@ -286,7 +286,7 @@ def load_line_lists(lines, unknown=False, skip=False, all=False, NIST=False,
     line_lists = vstack(lists, join_type='exact')
 
     # Restrict on the spectrograph?
-    if restrict_on_instr:
+    if restrict_on_instr is not None:
         instr_dict = defs.instruments()
         gdI = (line_lists['Instr'] & instr_dict[restrict_on_instr]) > 0
         line_lists = line_lists[gdI]

setup.cfg

@@ -44,7 +44,7 @@ install_requires =
     ginga>=3.0
     linetools
     qtpy>=1.9
-    bottleneck>=1.3
+    bottleneck
 scripts =
     bin/pypeit_c_enabled
     bin/pypeit_chk_plugins

tox.ini

@@ -81,6 +81,7 @@ commands = pycodestyle pypeit --count --select=E9
 
 [testenv:conda]
 description = run tests in environment created via conda
-deps = tox-conda
+requires = tox-conda
+conda_deps = numpy,astropy,scipy,bottleneck
 conda_env = {toxinidir}/environment.yml
 commands = pytest --pyargs pypeit {posargs}