replace flatfile with use_blaze

pypeit/par/pypeitpar.py

@@ -1949,7 +1949,7 @@ class SensFuncPar(ParSet):
     For a table with the current keywords, defaults, and descriptions,
     see :ref:`parameters`.
     """
-    def __init__(self, flatfile=None, extrap_blu=None, extrap_red=None, samp_fact=None, multi_spec_det=None, algorithm=None, UVIS=None,
+    def __init__(self, use_blaze=None, extrap_blu=None, extrap_red=None, samp_fact=None, multi_spec_det=None, algorithm=None, UVIS=None,
                  IR=None, polyorder=None, star_type=None, star_mag=None, star_ra=None, extr=None,
                  star_dec=None, mask_hydrogen_lines=None, mask_helium_lines=None, hydrogen_mask_wid=None):
         # Grab the parameter names and values from the function arguments
@@ -1962,11 +1962,9 @@ def __init__(self, flatfile=None, extrap_blu=None, extrap_red=None, samp_fact=No
         dtypes = OrderedDict.fromkeys(pars.keys())
         descr = OrderedDict.fromkeys(pars.keys())
 
-        defaults['flatfile'] = None
-        dtypes['flatfile'] = str
-        descr['flatfile'] = 'Flat field file to be used if the sensitivity function model will utilize the blaze ' \
-                            'function computed from a flat field file in the Calibrations directory, e.g.' \
-                            'Calibrations/Flat_A_0_DET01.fits'
+        defaults['use_blaze'] = False
+        dtypes['use_blaze'] = bool
+        descr['use_blaze'] = 'If True, the blaze will be used when computing the sensitivity function.'
 
         defaults['extr'] = 'OPT'
         dtypes['extr'] = str
@@ -2069,7 +2067,7 @@ def from_dict(cls, cfg):
         k = np.array([*cfg.keys()])
 
         # Single element parameters
-        parkeys = ['flatfile', 'extrap_blu', 'extrap_red', 'samp_fact', 'multi_spec_det', 'algorithm',
+        parkeys = ['use_blaze', 'extrap_blu', 'extrap_red', 'samp_fact', 'multi_spec_det', 'algorithm',
                    'polyorder', 'star_type', 'star_mag', 'star_ra', 'star_dec', 'extr',
                    'mask_hydrogen_lines', 'mask_helium_lines', 'hydrogen_mask_wid']
 

pypeit/sensfunc.py

@@ -255,7 +255,8 @@ def __init__(self, spec1dfile, sensfile, par, par_fluxcalib=None, debug=False,
 
         # Unpack standard
         wave, counts, counts_ivar, counts_mask, log10_blaze_function, self.meta_spec, header \
-            = self.sobjs_std.unpack_object(ret_flam=False, log10blaze=True, extract_type=self.extr, remove_missing=True)
+            = self.sobjs_std.unpack_object(ret_flam=False, log10blaze=True, extract_blaze=par['use_blaze'],
+                                           extract_type=self.extr, remove_missing=True)
 
         # Perform any instrument tweaks
         wave_twk, counts_twk, counts_ivar_twk, counts_mask_twk, log10_blaze_function_twk = \

pypeit/specobjs.py

@@ -188,7 +188,8 @@ def nobj(self):
         """
         return len(self.specobjs)
 
-    def unpack_object(self, ret_flam=False, log10blaze=False, min_blaze_value=1e-3, extract_type='OPT', remove_missing=False):
+    def unpack_object(self, ret_flam=False, log10blaze=False, min_blaze_value=1e-3, extract_type='OPT',
+                      extract_blaze=False, remove_missing=False):
         """
         Utility function to unpack the sobjs for one object and
         return various numpy arrays describing the spectrum and meta
@@ -202,9 +203,11 @@ def unpack_object(self, ret_flam=False, log10blaze=False, min_blaze_value=1e-3,
                 If True return the log10 of the blaze function.
             min_blaze_value (:obj:`float`, optional):
                 Minimum value of the blaze function to consider as good.
-           extract_type (:obj:`str`, optional):
+            extract_type (:obj:`str`, optional):
                 Extraction type to use.  Default is 'OPT'.
-           remove_missing (:obj:`bool`, optional):
+            extract_blaze (:obj:`bool`, optional):
+                If True, extract the blaze function.  Default is False.
+            remove_missing (:obj:`bool`, optional):
                 If True, remove any missing data (i.e. where the flux is None).
                 Default is False.
 
@@ -219,7 +222,7 @@ def unpack_object(self, ret_flam=False, log10blaze=False, min_blaze_value=1e-3,
                   Flambda or counts)
                 - flux_gpm (`numpy.ndarray`_): Good pixel mask.
                   True=Good
-                - blaze (`numpy.ndarray`_): Blaze function
+                - blaze (`numpy.ndarray`_, None): Blaze function
                 - meta_spec (dict:) Dictionary containing meta data.
                   The keys are defined by
                   spectrograph.parse_spec_header()
@@ -255,9 +258,8 @@ def unpack_object(self, ret_flam=False, log10blaze=False, min_blaze_value=1e-3,
         flux = np.zeros((nspec, norddet))
         flux_ivar = np.zeros((nspec, norddet))
         flux_gpm = np.zeros((nspec, norddet), dtype=bool)
-        blaze = np.zeros((nspec, norddet), dtype=float)
-        trace_spec = np.zeros((nspec, norddet))
-        trace_spat = np.zeros((nspec, norddet))
+        if extract_blaze:
+            blaze = np.zeros((nspec, norddet), dtype=float)
 
         detector = [None]*norddet
         ech_orders = np.zeros(norddet, dtype=int)
@@ -270,17 +272,19 @@ def unpack_object(self, ret_flam=False, log10blaze=False, min_blaze_value=1e-3,
                 ech_orders[iorddet] = self[iorddet].ECH_ORDER
             flux[:, iorddet] = getattr(self, flux_key)[iorddet]
             flux_ivar[:, iorddet] = getattr(self, flux_key+'_IVAR')[iorddet]
-            blaze[:, iorddet] = getattr(self, blaze_key)[iorddet]
-            trace_spat[:, iorddet] = self[iorddet].TRACE_SPAT
-            trace_spec[:, iorddet] = self[iorddet].trace_spec
+            if extract_blaze:
+                blaze[:, iorddet] = getattr(self, blaze_key)[iorddet]
 
         # Log10 blaze
-        blaze_function = np.copy(blaze)
-        if log10blaze:
-            for iorddet in range(norddet):
-                blaze_function_smooth = utils.fast_running_median(blaze[:, iorddet], 5)
-                blaze_function_norm = blaze_function_smooth / blaze_function_smooth.max()
-                blaze_function[:, iorddet] = np.log10(np.clip(blaze_function_norm, min_blaze_value, None))
+        if extract_blaze:
+            blaze_function = np.copy(blaze)
+            if log10blaze:
+                for iorddet in range(norddet):
+                    blaze_function_smooth = utils.fast_running_median(blaze[:, iorddet], 5)
+                    blaze_function_norm = blaze_function_smooth / blaze_function_smooth.max()
+                    blaze_function[:, iorddet] = np.log10(np.clip(blaze_function_norm, min_blaze_value, None))
+        else:
+            blaze_function = None
 
         # Populate meta data
         spectrograph = load_spectrograph(self.header['PYP_SPEC'])