Merge branch 'develop' into slitless_flats

doc/releases/1.16.1dev.rst

@@ -18,6 +18,11 @@ Dependency Changes
 Functionality/Performance Improvements and Additions
 ----------------------------------------------------
 
+- Added the possibility to decide if the extracted standard star spectrum should be
+  used as a crutch for tracing the object in the science frame (before it was done as default).
+  This is done by setting the parameter ``use_std_trace`` in FindObjPar.
+- Now PypeIt can handle the case where "Standard star trace does not match the number of orders in the echelle data"
+  both in `run_pypeit` and in `pypeit_coadd_1dspec`.
 - Added the functionality to use slitless flats to create pixelflats. Note: new frametype
   `slitless_pixflat` is added to the PypeIt frametype list.
 - The created pixelflats are stored in the reduction directory and in the PypeIt cache directory
@@ -47,15 +52,12 @@ Script Changes
 - The sensitivity function is now generated outside of datacube generation.
 - The `grating_corr` column is now used to select the correct grating
   correction file for each spec2d file when generating the datacube.
+- Added the ``--extr`` parameter in the ``pypeit_sensfunc`` script (also as a SensFuncPar)
+  to allow the user to specify the extraction method to use when computing the sensitivity
+  function (before only optimal extraction was used).
 - Added ``pypeit_show_pixflat`` script to inspect the (slitless) pixel flat
   generated during the reduction and stored in ``data/pixelflats``.
 
-- A new script, called `pypeit_extract_datacube`, allows 1D spectra of point
-  sources to be extracted from datacubes.
-- The sensitivity function is now generated outside of datacube generation.
-- The `grating_corr` column is now used to select the correct grating
-  correction file for each spec2d file when generating the datacube.
-
 Datamodel Changes
 -----------------
 
@@ -77,6 +79,10 @@ Bug Fixes
 - Fix a MAJOR BUT SUBTLE bug in the use of ``numpy.argsort``. When using ``numpy.argsort``
   the parameter kind='stable' should be used to ensure that a sorting algorithm more robust
   than "quicksort" is used.
+- Fix error "ValueError: setting an array element with a sequence. The requested
+  array has an inhomogeneous shape after 1 dimensions..." occurring when unpacking
+  the SpecObj spectrum but having an attribute of the SpecObj object that is None.
+
 
 
 

pypeit/coadd1d.py

@@ -202,7 +202,6 @@ def __init__(self, spec1dfiles, objids, spectrograph=None, par=None, sensfuncfil
         super().__init__(spec1dfiles, objids, spectrograph=spectrograph, par=par, sensfuncfile=sensfuncfile,
                          setup_id=setup_id, debug=debug, show=show, chk_version=chk_version)
 
-
     def load(self):
         """
         Load the arrays we need for performing coadds.
@@ -461,8 +460,7 @@ def coadd(self):
                                      lower=self.par['lower'], upper=self.par['upper'],
                                      maxrej=self.par['maxrej'], sn_clip=self.par['sn_clip'],
                                      debug=self.debug, show=self.show, show_exp=self.show)
-
-
+
         return wave_grid_mid, wave_coadd, flux_coadd, ivar_coadd, gpm_coadd, order_stacks
 
     def load_ech_arrays(self, spec1dfiles, objids, sensfuncfiles):
@@ -474,7 +472,7 @@ def load_ech_arrays(self, spec1dfiles, objids, sensfuncfiles):
                 List of spec1d files for this setup.
             objids (list):
                 List of objids. This is aligned with spec1dfiles
-            sensfuncfile (list):
+            sensfuncfiles (list):
                 List of sensfuncfiles. This is aligned with spec1dfiles and objids
 
         Returns:
@@ -488,14 +486,15 @@ def load_ech_arrays(self, spec1dfiles, objids, sensfuncfiles):
             indx = sobjs.name_indices(objids[iexp])
             if not np.any(indx):
                 msgs.error("No matching objects for {:s}.  Odds are you input the wrong OBJID".format(objids[iexp]))
-            wave_iexp, flux_iexp, ivar_iexp, gpm_iexp, _, _, _, header = \
+            wave_iexp, flux_iexp, ivar_iexp, gpm_iexp, _, _, meta_spec, header = \
                     sobjs[indx].unpack_object(ret_flam=self.par['flux_value'], extract_type=self.par['ex_value'])
             # This np.atleast2d hack deals with the situation where we are wave_iexp is actually Multislit data, i.e. we are treating
             # it like an echelle spectrograph with a single order. This usage case arises when we want to use the
             # echelle coadding code to combine echelle and multislit data
             if wave_iexp.ndim == 1:
                 wave_iexp, flux_iexp, ivar_iexp, gpm_iexp = np.atleast_2d(wave_iexp).T, np.atleast_2d(flux_iexp).T, np.atleast_2d(ivar_iexp).T, np.atleast_2d(gpm_iexp).T
             weights_sens_iexp = sensfunc.SensFunc.sensfunc_weights(sensfuncfiles[iexp], wave_iexp,
+                                                                   ech_order_vec=meta_spec['ECH_ORDERS'],
                                                                    debug=self.debug,
                                                                    chk_version=self.chk_version)
             # Allocate arrays on first iteration
@@ -511,14 +510,18 @@ def load_ech_arrays(self, spec1dfiles, objids, sensfuncfiles):
                     header_out['RA_OBJ']  = sobjs[indx][0]['RA']
                     header_out['DEC_OBJ'] = sobjs[indx][0]['DEC']
 
-            # Store the information
-            waves[...,iexp], fluxes[...,iexp], ivars[..., iexp], gpms[...,iexp], weights_sens[...,iexp] \
-                = wave_iexp, flux_iexp, ivar_iexp, gpm_iexp, weights_sens_iexp
-
+            # TODO :: The error below can be removed if we refactor to use a list of numpy arrays. But, if we do that,
+            #  we need to make several changes to the ech_combspec function.
+            try:
+                # Store the information
+                waves[...,iexp], fluxes[...,iexp], ivars[..., iexp], gpms[...,iexp], weights_sens[...,iexp] \
+                    = wave_iexp, flux_iexp, ivar_iexp, gpm_iexp, weights_sens_iexp
+            except ValueError:
+                msgs.error('The shape (Nspec,Norder) of spectra is not consistent between exposures. '
+                           'These spec1ds cannot be coadded at this time.')
 
         return waves, fluxes, ivars, gpms, weights_sens, header_out
 
-
     def load(self):
         """
         Load the arrays we need for performing echelle coadds.
@@ -563,8 +566,6 @@ def load(self):
             for c, l in zip(combined, loaded):
                 c.append(l)
 
-
-
         return waves, fluxes, ivars, gpms, weights_sens, headers