continue incorporation of weighting

src/matchmaps/_compute_realspace_diff.py

@@ -50,6 +50,7 @@ def compute_realspace_difference_map(
     eff : str = None,
     keep_temp_files : str = None,
     radius : float = 5,
+    alpha : float = 0,
     no_bss = False
 ):
     """
@@ -98,10 +99,12 @@ def compute_realspace_difference_map(
         If not None, the name of a subdirectory of the output_dir into which intermediate matchmaps files are moved upon program completion.
     radius : float, optional
         Maximum distance away from protein model to include voxels. Only applies to the "unmasked" difference map output.
+    alpha : float, optional
+        Alpha to use in error weighting of F-obs prior to Fourier Transform. Defaults to 0, e.g. no weighting.
     no_bss : bool, optional
         If True, skip bulk solvent scaling feature of phenix.refine
     """
-    
+
     _validate_environment(ccp4=True)
 
     output_dir_contents = list(output_dir.glob("*"))
@@ -206,11 +209,12 @@ def compute_realspace_difference_map(
     # TO-DO: Figure out why phenix outputs are sometimes still split into (+) and (-) columns, even when I specify that anomalous=False
     # As a workaround, even anomalous files have a single 'F-obs-filtered' column, so I can always just use that.
     fg_off = make_floatgrid_from_mtz(
-        mtzoff, spacing, F="F-obs-filtered", Phi="PH2FOFCWT", spacegroup="P1", dmin=dmin
+        mtzoff, spacing, F="F-obs-filtered", SigF="SIGF-obs-filtered", Phi="PH2FOFCWT", spacegroup="P1", dmin=dmin, alpha=alpha,
     )
     fg_on = make_floatgrid_from_mtz(
-        mtzon, spacing, F="F-obs-filtered", Phi="PH2FOFCWT", spacegroup="P1", dmin=dmin
+        mtzon, spacing, F="F-obs-filtered", SigF="SIGF-obs-filtered", Phi="PH2FOFCWT", spacegroup="P1", dmin=dmin, alpha=alpha,
     )
+
 
     if rbr_gemmi is None:
         _realspace_align_and_subtract(
@@ -369,6 +373,18 @@ def parse_arguments():
             "By default, cutoff is the resolution limit of the lower-resolution input MTZ. "
         ),
     )
+
+    parser.add_argument(
+        "--alpha",
+        required=False,
+        type=float,
+        default=0,
+        help=(
+            "Alpha to use for error weighting of F-obs prior to Fourier Transform. "
+            "Weights are computed as: 1 / ((1+(alpha*(SigF^2)) / <SigF>^2). "
+            "Default value is alpha=0, e.g., no weighting is performed. "
+        )
+    )
 
     parser.add_argument(
         "--unmasked-radius",

src/matchmaps/_utils.py

@@ -108,7 +108,7 @@ def _subparser(selection):
 
 
 def make_floatgrid_from_mtz(
-    mtz, spacing, F, SigF, Phi, spacegroup="P1", dmin=None, alpha=0
+    mtz, spacing, F, SigF, Phi, spacegroup="P1", dmin=None, alpha=0.2
 ):
     """
     Make a gemmi.FloatGrid from an rs.DataSet.
@@ -134,6 +134,7 @@ def make_floatgrid_from_mtz(
         Fourier transform of mtz, written out as a gemmi object containing a 3D voxel array
         and various other metadata and methods
     """
+
     # drop NAs in either of the specified columns
     # this has the secondary purpose of not silently modifying the input mtz
     new_mtz = mtz[~mtz[F].isnull()]
@@ -151,17 +152,22 @@ def make_floatgrid_from_mtz(
     ]
 
     # apply weighting
+    # note: if alpha==1, then these numbers all just become 1, e.g. no weighting
     weights = 1 / (
         1
         + (
-            0.05
-            * mtz["SIGF-obs-filtered"] ** 2
-            / np.mean(mtz["SIGF-obs-filtered"] ** 2)
+            alpha
+            * new_mtz[SigF] ** 2
+            / np.mean(new_mtz[SigF] ** 2)
         )
     )
+
+    if 'weighted_Fobs' in new_mtz.columns:
+        raise NotImplementedError('Error: mtz already contains a column named weighted_Fobs; email Dennis bugging him to support this')
+    new_mtz['weighted_Fobs'] = new_mtz[F] * weights
 
     # perform FFT using the desired amplitudes and phases
-    new_mtz["Fcomplex"] = new_mtz.to_structurefactor(F, Phi)
+    new_mtz["Fcomplex"] = new_mtz.to_structurefactor("weighted_Fobs", Phi)
     reciprocal_grid = new_mtz.to_reciprocal_grid("Fcomplex", grid_size=gridsize)
     real_grid = np.real(np.fft.fftn(reciprocal_grid))