Mask off-detector slits/orders

pypeit/edgetrace.py

@@ -5723,6 +5723,32 @@ def get_slits(self):
             specmin = specmin[indx]/binspec
             specmax = specmax[indx]/binspec
 
+        if self.par['mask_off_detector']:
+            # check and mask portions of the slits/orders that are more than 50% off the detector
+            _slits = self.edge_fit[:,gpm].reshape(self.nspec, -1, 2)
+            # for each left and right edge
+            for s in range(_slits.shape[1]):
+                # get the median slit length, calculated using also the off-detector edges
+                med_slit_len = np.median(_slits[:,s,1] - _slits[:,s,0])
+                # bool arrays for slits that are off the detector on the left and right side
+                off_det_left = _slits[:, s, 0] < 0
+                off_det_right = _slits[:, s, 1] > self.nspat
+                # now measure the actual slit lengths, i.e., using the detector edges
+                # as the slit edges if they are off the detector
+                slits_actual = _slits.copy()
+                if np.any(off_det_left):
+                    slits_actual[off_det_left, s, 0] = 0
+                if np.any(off_det_right):
+                    slits_actual[off_det_right, s, 1] = self.nspat
+                # actual slit lengths
+                slit_lens_actual = slits_actual[:, s, 1] - slits_actual[:, s, 0]
+                # find where the actual slit length is less than 50% of the median slit length
+                off_det_indx = np.where(np.logical_not((slit_lens_actual < 0.5 * med_slit_len)))[0]
+                # set the specmin and specmax for the off-detector regions
+                if off_det_indx.size > 0:
+                    specmin[s] = np.maximum(specmin[s], off_det_indx[0])
+                    specmax[s] = np.minimum(specmax[s], off_det_indx[-1])
+
         # Define spat_id (in the same way is done in SlitTraceSet) to add it in the astropy table. It
         # is useful to have spat_id in that table.
         center = (left + right) / 2

pypeit/par/pypeitpar.py

@@ -3294,7 +3294,7 @@ def __init__(self, filt_iter=None, sobel_mode=None, edge_thresh=None, sobel_enha
                  order_gap_poly=None, order_fitrej=None, order_outlier=None, order_spat_range=None,
                  overlap=None, max_overlap=None, use_maskdesign=None, maskdesign_maxsep=None,
                  maskdesign_step=None, maskdesign_sigrej=None, pad=None, add_slits=None,
-                 add_predict=None, rm_slits=None, maskdesign_filename=None):
+                 add_predict=None, rm_slits=None, maskdesign_filename=None, mask_off_detector=None):
 
         # Grab the parameter names and values from the function
         # arguments
@@ -3361,6 +3361,11 @@ def __init__(self, filt_iter=None, sobel_mode=None, edge_thresh=None, sobel_enha
                              'Should be two integers, e.g. 100,150 trims 100 pixels from the ' \
                              'short wavelength end and 150 pixels from the long wavelength ' \
                              'end of the spectral axis of the detector.'
+
+        defaults['mask_off_detector'] = False
+        dtypes['mask_off_detector'] = bool
+        descr['mask_off_detector'] = 'Mask off the portions of the slits/orders that are ' \
+                                     'more that 50% off the detector.'
 
         defaults['max_shift_abs'] = 0.5
         dtypes['max_shift_abs'] = [int, float]
@@ -3883,7 +3888,7 @@ def from_dict(cls, cfg):
                    'order_gap_poly', 'order_fitrej', 'order_outlier', 'order_spat_range','overlap',
                    'max_overlap', 'use_maskdesign', 'maskdesign_maxsep', 'maskdesign_step',
                    'maskdesign_sigrej', 'maskdesign_filename', 'pad', 'add_slits', 'add_predict',
-                   'rm_slits']
+                   'rm_slits', 'mask_off_detector']
 
         # Find the list of keywords provded in `cfg` that are *not* valid
         badkeys = np.array([pk not in parkeys for pk in k])

pypeit/spectrographs/keck_hires.py

@@ -114,6 +114,7 @@ def default_pypeit_par(cls):
         par['calibrations']['slitedges']['max_nudge'] = 0.
         par['calibrations']['slitedges']['overlap'] = True
         par['calibrations']['slitedges']['dlength_range'] = 0.25
+        par['calibrations']['slitedges']['mask_off_detector'] = True
 
         par['calibrations']['slitedges']['add_missed_orders'] = True
         par['calibrations']['slitedges']['order_width_poly'] = 2