Merge branch 'develop' into rmcodecov

.github/workflows/ci_cron.yml

@@ -15,7 +15,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python: ['3.10', '3.11', '3.12']
+        python: ['3.11', '3.12']
         toxenv: [test-alldeps, test-numpydev, test-linetoolsdev, test-gingadev, test-astropydev]
     steps:
     - name: Check out repository

.github/workflows/ci_tests.yml

@@ -17,8 +17,8 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python: ['3.10', '3.11', '3.12']
-        toxenv: [test, test-alldeps-cov, test-linetoolsdev, test-gingadev, test-astropydev]
+        python: ['3.11', '3.12']
+        toxenv: [test, test-alldeps-cov, test-numpydev, test-linetoolsdev, test-gingadev, test-astropydev]
     steps:
     - name: Check out repository
       uses: actions/checkout@v3
@@ -48,7 +48,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [windows-latest, macos-latest]
-        python: ['3.10', '3.11', '3.12']
+        python: ['3.11', '3.12']
         toxenv: [test-alldeps]
     steps:
     - name: Check out repository
@@ -71,7 +71,7 @@ jobs:
     - name: Conda environment check
       uses: actions/setup-python@v4
       with:
-        python-version: '3.11'
+        python-version: '3.12'
     - name: Install base dependencies
       run: |
         python -m pip install --upgrade pip tox
@@ -86,7 +86,7 @@ jobs:
     - name: Python codestyle check
       uses: actions/setup-python@v4
       with:
-        python-version: '3.11'
+        python-version: '3.12'
     - name: Install base dependencies
       run: |
         python -m pip install --upgrade pip

bin/pypeit_c_enabled

@@ -13,11 +13,25 @@ else:
     print('Successfully imported bspline C utilities.')
 
 try:
-    from pypeit.bspline.setup_package import extra_compile_args
+
+    # Check for whether OpenMP support is enabled, by seeing if the bspline
+    # extension was compiled with it.
+    #
+    # The extension_helpers code that is run to figure out OMP support runs
+    # multiple tests to determine compiler version, some of which output to stderr.
+    # To make the output pretty we redirect those to /dev/null (or equivalent)
+    import os
+    import sys
+    devnull_fd = os.open(os.devnull,os.O_WRONLY)
+    os.dup2(devnull_fd,sys.stderr.fileno())
+
+    from pypeit.bspline.setup_package import get_extensions
+    bspline_extension = get_extensions()[0]
 except:
     print("Can't check status of OpenMP support")
 else:
-    if '-fopenmp' in extra_compile_args:
+    # Windows uses -openmp, other environments use -fopenmp
+    if any(['openmp' in arg for arg in bspline_extension.extra_compile_args]):
         print('OpenMP compiler support detected.')
     else:
         print('OpenMP compiler support not detected. Bspline utilities single-threaded.')

deprecated/arc_old.py

@@ -855,3 +855,53 @@ def saturation_mask(a, satlevel):
 
     return mask.astype(int)
 
+def mask_around_peaks(spec, inbpm):
+    """
+    Find peaks in the input spectrum and mask pixels around them.
+
+    All pixels to the left and right of a peak is masked until
+    a pixel has a lower value than the adjacent pixel. At this
+    point, we assume that spec has reached the noise level.
+
+    Parameters
+    ----------
+    spec: `numpy.ndarray`_
+        Spectrum (1D array) in counts
+    inbpm: `numpy.ndarray`_
+        Input bad pixel mask
+
+    Returns
+    -------
+    outbpm: `numpy.ndarray`_
+        Bad pixel mask with pixels around peaks masked
+    """
+    # Find the peak locations
+    pks = detect_peaks(spec)
+
+    # Initialise some useful variables and the output bpm
+    xarray = np.arange(spec.size)
+    specdiff = np.append(np.diff(spec), 0.0)
+    outbpm = inbpm.copy()
+
+    # Loop over the peaks and mask pixels around them
+    for i in range(len(pks)):
+        # Find all pixels to the left of the peak that are above the noise level
+        wl = np.where((xarray <= pks[i]) & (specdiff > 0.0))[0]
+        ww = (pks[i]-wl)[::-1]
+        # Find the first pixel to the left of the peak that is below the noise level
+        nmask = np.where(np.diff(ww) > 1)[0]
+        if nmask.size != 0 and nmask[0] > 5:
+            # Mask all pixels to the left of the peak
+            mini = max(0,wl.size-nmask[0]-1)
+            outbpm[wl[mini]:pks[i]] = True
+        # Find all pixels to the right of the peak that are above the noise level
+        ww = np.where((xarray >= pks[i]) & (specdiff < 0.0))[0]
+        # Find the first pixel to the right of the peak that is below the noise level
+        nmask = np.where(np.diff(ww) > 1)[0]
+        if nmask.size != 0 and nmask[0] > 5:
+            # Mask all pixels to the right of the peak
+            maxi = min(nmask[0], ww.size)
+            outbpm[pks[i]:ww[maxi]+2] = True
+    # Return the output bpm
+    return outbpm
+

deprecated/datacube.py

@@ -443,3 +443,71 @@ def make_whitelight_frompixels(all_ra, all_dec, all_wave, all_sci, all_wghts, al
             whitelight_ivar[:, :, ff] = ivar_img.copy()
     return whitelight_Imgs, whitelight_ivar, whitelightWCS
 
+
+def make_sensfunc(ss_file, senspar, blaze_wave=None, blaze_spline=None, grating_corr=False):
+    """
+    Generate the sensitivity function from a standard star DataCube.
+
+    Args:
+        ss_file (:obj:`str`):
+            The relative path and filename of the standard star datacube. It
+            should be fits format, and for full functionality, should ideally of
+            the form :class:`~pypeit.coadd3d.DataCube`.
+        senspar (:class:`~pypeit.par.pypeitpar.SensFuncPar`):
+            The parameters required for the sensitivity function computation.
+        blaze_wave (`numpy.ndarray`_, optional):
+            Wavelength array used to construct blaze_spline
+        blaze_spline (`scipy.interpolate.interp1d`_, optional):
+            Spline representation of the reference blaze function (based on the illumflat).
+        grating_corr (:obj:`bool`, optional):
+            If a grating correction should be performed, set this variable to True.
+
+    Returns:
+        `numpy.ndarray`_: A mask of the good sky pixels (True = good)
+    """
+    # TODO :: This routine has not been updated to the new spec1d plan of passing in a sensfunc object
+    #      :: Probably, this routine should be removed and the functionality moved to the sensfunc object
+    msgs.error("coding error - make_sensfunc is not currently supported.  Please contact the developers")
+    # Check if the standard star datacube exists
+    if not os.path.exists(ss_file):
+        msgs.error("Standard cube does not exist:" + msgs.newline() + ss_file)
+    msgs.info(f"Loading standard star cube: {ss_file:s}")
+    # Load the standard star cube and retrieve its RA + DEC
+    stdcube = fits.open(ss_file)
+    star_ra, star_dec = stdcube[1].header['CRVAL1'], stdcube[1].header['CRVAL2']
+
+    # Extract a spectrum of the standard star
+    wave, Nlam_star, Nlam_ivar_star, gpm_star = extract_standard_spec(stdcube)
+
+    # Extract the information about the blaze
+    if grating_corr:
+        blaze_wave_curr, blaze_spec_curr = stdcube['BLAZE_WAVE'].data, stdcube['BLAZE_SPEC'].data
+        blaze_spline_curr = interp1d(blaze_wave_curr, blaze_spec_curr,
+                                     kind='linear', bounds_error=False, fill_value="extrapolate")
+        # Perform a grating correction
+        grat_corr = correct_grating_shift(wave, blaze_wave_curr, blaze_spline_curr, blaze_wave, blaze_spline)
+        # Apply the grating correction to the standard star spectrum
+        Nlam_star /= grat_corr
+        Nlam_ivar_star *= grat_corr ** 2
+
+    # Read in some information above the standard star
+    std_dict = flux_calib.get_standard_spectrum(star_type=senspar['star_type'],
+                                                star_mag=senspar['star_mag'],
+                                                ra=star_ra, dec=star_dec)
+    # Calculate the sensitivity curve
+    # TODO :: This needs to be addressed... unify flux calibration into the main PypeIt routines.
+    msgs.warn("Datacubes are currently flux-calibrated using the UVIS algorithm... this will be deprecated soon")
+    zeropoint_data, zeropoint_data_gpm, zeropoint_fit, zeropoint_fit_gpm = \
+        flux_calib.fit_zeropoint(wave, Nlam_star, Nlam_ivar_star, gpm_star, std_dict,
+                                 mask_hydrogen_lines=senspar['mask_hydrogen_lines'],
+                                 mask_helium_lines=senspar['mask_helium_lines'],
+                                 hydrogen_mask_wid=senspar['hydrogen_mask_wid'],
+                                 nresln=senspar['UVIS']['nresln'],
+                                 resolution=senspar['UVIS']['resolution'],
+                                 trans_thresh=senspar['UVIS']['trans_thresh'],
+                                 polyorder=senspar['polyorder'],
+                                 polycorrect=senspar['UVIS']['polycorrect'],
+                                 polyfunc=senspar['UVIS']['polyfunc'])
+    wgd = np.where(zeropoint_fit_gpm)
+    sens = np.power(10.0, -0.4 * (zeropoint_fit[wgd] - flux_calib.ZP_UNIT_CONST)) / np.square(wave[wgd])
+    return interp1d(wave[wgd], sens, kind='linear', bounds_error=False, fill_value="extrapolate")