flake8 fixes for utils_findsat_mrt

Author: dvstark

acstools/utils_findsat_mrt.py

@@ -21,7 +21,7 @@
     from skimage.transform._warps import warp
     from skimage._shared.utils import convert_to_float
 except ImportError as e:
-    warnings.warn(f'skimage not installed. MRT calculation will not work: {repr(e)}')
+    warnings.warn(f'skimage not installed. MRT calculation will not work: {repr(e)}')  # noqa
 
 # check for scipy
 try:
@@ -108,8 +108,8 @@ def merge_tables(tbls, theta_sep=10, rho_sep=10):
             drho = np.abs(t['ycentroid'] - s['ycentroid'])
             sel = (dtheta < theta_sep) & (drho < rho_sep)
             keep[sel] = False
-        # Silence MergeConflictWarning for "date" metadata because
-        # the tables were created with different timestamps. The last entry is kept.
+        # Silence MergeConflictWarning for "date" metadata because the tables
+        # were created with different timestamps. The last entry is kept.
         src = vstack([src, t[keep]], metadata_conflicts="silent")
     return src
 
@@ -1203,23 +1203,23 @@ def update_dq(filename, ext, mask, dqval=16384, verbose=True,
     expand_mask: bool, optional
         Allows the mask to be expanded to match the size of the original mask.
         This is relevant for masks that were generated used binned versions of
-        the original image. 
+        the original image.
 
     """
     with fits.open(filename, mode='update') as pf:
         dqarr = pf[ext].data
 
         # check that the old mask and new mask are the same size
         same_size = mask.shape == dqarr.shape
-        mask_larger = np.any([mask.shape[i] > dqarr.shape[i] 
+        mask_larger = np.any([mask.shape[i] > dqarr.shape[i]
                               for i in range(mask.ndim)])
 
         # provide informative error messages depending on mask/dqarr size
         if not same_size:
             LOG.info('Inconsistent mask sizes: \n'
                      'Input mask: {} \n'
                      'DQ array: {}'.format(mask.shape, dqarr.shape))
-            
+
             if mask_larger:
                 LOG.error('Mask is larger than the DQ array in one or more '
                           'dimensions.\nThis routine cannot currently rescale'
@@ -1228,27 +1228,27 @@ def update_dq(filename, ext, mask, dqval=16384, verbose=True,
 
             elif not mask_larger and not expand_mask:
                 LOG.error('Cannot proceed due to size mismatch.\n'
-                            'Set expand_mask=True if the mask was generated '
-                            'with binned data and needs to be enlarged to the '
-                            'original size.')
+                          'Set expand_mask=True if the mask was generated '
+                          'with binned data and needs to be enlarged to the '
+                          'original size.')
                 return
             else:
                 LOG.info('Enlarging mask to original size.')
 
-                # Determine factor by which to scale-up the image. Scales should
+                # Determine factor by which to scale-up image. Scales should
                 # be the same for the x and y dimensions, after we round down
-                # to the nearest integer in case there are extra rows/columns 
-                # that do not divide evenly. These extra rows/columns will be 
+                # to the nearest integer in case there are extra rows/columns
+                # that do not divide evenly. These extra rows/columns will be
                 # added back at the end. This approach is the reverse of
                 # astropy.nddata.block_reduce, which trims extra rows/cols
-                # first. 
+                # first.
 
                 factor_x = np.floor(dqarr.shape[1]/mask.shape[1]).astype(int)
                 factor_y = np.floor(dqarr.shape[0]/mask.shape[0]).astype(int)
                 if factor_x != factor_y:
                     raise ValueError('Mask dimensions require scaling by'
-                                     'different amounts in order to match the DQ'
-                                     'array but this is not allowed.')
+                                     'different amounts in order to match the'
+                                     'DQ array but this is not allowed.')
                 else:
                     factor = factor_x
 
@@ -1267,8 +1267,7 @@ def update_dq(filename, ext, mask, dqval=16384, verbose=True,
                 if extra_cols > 0:
                     LOG.info('Duplicating end columns to match orig size')
                     while mask.shape[1] != dqarr.shape[1]:
-                        mask = np.hstack([mask,
-                                          mask[:, -1].reshape(mask.shape[0],1)])
+                        mask = np.hstack([mask, mask[:, -1].reshape(mask.shape[0], 1)])  # noqa
 
         old_mask = (dqval & dqarr) != 0  # Existing flagged trails
         new_mask = mask & ~old_mask  # Only flag previously unflagged trails