switch to centered alignment bins by default

py4dstem · Jul 18, 2024 · 7c2eb04 · 7c2eb04
1 parent d995f66
commit 7c2eb04
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Showing 2 changed files with 13 additions and 8 deletions.
diff --git a/py4DSTEM/process/phase/parallax.py b/py4DSTEM/process/phase/parallax.py
@@ -743,6 +743,7 @@ def reconstruct(
         min_alignment_bin: int = 1,
         num_iter_at_min_bin: int = 2,
         alignment_bin_values: list = None,
+        centered_alignment_bins: bool = True,
         cross_correlation_upsample_factor: int = 8,
         regularizer_matrix_size: Tuple[int, int] = (1, 1),
         regularize_shifts: bool = False,
@@ -879,6 +880,8 @@ def reconstruct(
                     (bin_vals, np.repeat(bin_vals[-1], num_iter_at_min_bin - 1))
                 )
 
+        bin_shift = 0 if centered_alignment_bins else 0.5
+
         if plot_aligned_bf:
             num_plots = bin_vals.shape[0]
             nrows = int(np.sqrt(num_plots))
@@ -913,7 +916,7 @@ def reconstruct(
             G_ref = xp.fft.fft2(self._recon_BF)
 
             # Segment the virtual images with current binning values
-            xy_inds = xp.round(xy_center / bin_vals[a0] + 0.5).astype("int")
+            xy_inds = xp.round(xy_center / bin_vals[a0] + bin_shift).astype("int")
             xy_vals = np.unique(
                 asnumpy(xy_inds), axis=0
             )  # axis is not yet supported in cupy

diff --git a/py4DSTEM/process/phase/parameter_optimize.py b/py4DSTEM/process/phase/parameter_optimize.py
@@ -458,13 +458,15 @@ def _split_static_and_optimization_vars(self, argdict):
         return static_args, optimization_args
 
     def _get_scan_positions(self, affine_transform, dataset):
-        R_pixel_size = dataset.calibration.get_R_pixel_size()
-        x, y = (
-            np.arange(dataset.R_Nx) * R_pixel_size,
-            np.arange(dataset.R_Ny) * R_pixel_size,
-        )
-        x, y = np.meshgrid(x, y, indexing="ij")
-        scan_positions = np.stack((x.ravel(), y.ravel()), axis=1)
+        scan_positions = self._init_static_args.pop("initial_scan_positions",None)
+        if scan_positions is None:
+            R_pixel_size = dataset.calibration.get_R_pixel_size()
+            x, y = (
+                np.arange(dataset.R_Nx) * R_pixel_size,
+                np.arange(dataset.R_Ny) * R_pixel_size,
+            )
+            x, y = np.meshgrid(x, y, indexing="ij")
+            scan_positions = np.stack((x.ravel(), y.ravel()), axis=1)
         scan_positions = scan_positions @ affine_transform.asarray()
         return scan_positions