added detector plane resampling

py4DSTEM/preprocess/preprocess.py

@@ -576,7 +576,9 @@ def resample_data_diffraction(
             resampling_factor = np.array(output_size) / np.array(datacube.shape[-2:])
 
         resampling_factor = np.concatenate(((1, 1), resampling_factor))
-        datacube.data = zoom(datacube.data, resampling_factor, order=1)
+        datacube.data = zoom(
+            datacube.data, resampling_factor, order=1, mode="grid-wrap", grid_mode=True
+        )
         datacube.calibration.set_Q_pixel_size(
             datacube.calibration.get_Q_pixel_size() / resampling_factor[2]
         )

py4DSTEM/process/phase/magnetic_ptychographic_tomography.py

@@ -236,7 +236,8 @@ def preprocess(
         self,
         diffraction_intensities_shape: Tuple[int, int] = None,
         reshaping_method: str = "fourier",
-        probe_roi_shape: Tuple[int, int] = None,
+        padded_diffraction_intensities_shape: Tuple[int, int] = None,
+        region_of_interest_shape: Tuple[int, int] = None,
         dp_mask: np.ndarray = None,
         fit_function: str = "plane",
         plot_probe_overlaps: bool = True,
@@ -265,9 +266,12 @@ def preprocess(
             If None, no resampling of diffraction intenstities is performed
         reshaping_method: str, optional
             Method to use for reshaping, either 'bin, 'bilinear', or 'fourier' (default)
-        probe_roi_shape, (int,int), optional
+        padded_diffraction_intensities_shape: (int,int), optional
             Padded diffraction intensities shape.
             If None, no padding is performed
+        region_of_interest_shape: (int,int), optional
+            If not None, explicitly sets region_of_interest_shape and resamples exit_waves
+            at the diffraction plane to allow comparison with experimental data
         dp_mask: ndarray, optional
             Mask for datacube intensities (Qx,Qy)
         fit_function: str, optional
@@ -308,7 +312,9 @@ def preprocess(
         # set additional metadata
         self._diffraction_intensities_shape = diffraction_intensities_shape
         self._reshaping_method = reshaping_method
-        self._probe_roi_shape = probe_roi_shape
+        self._padded_diffraction_intensities_shape = (
+            padded_diffraction_intensities_shape
+        )
         self._dp_mask = dp_mask
 
         if self._datacube is None:
@@ -350,11 +356,20 @@ def preprocess(
         roi_shape = self._datacube[0].Qshape
         if diffraction_intensities_shape is not None:
             roi_shape = diffraction_intensities_shape
-        if probe_roi_shape is not None:
-            roi_shape = tuple(max(q, s) for q, s in zip(roi_shape, probe_roi_shape))
+        if padded_diffraction_intensities_shape is not None:
+            roi_shape = tuple(
+                max(q, s)
+                for q, s in zip(roi_shape, padded_diffraction_intensities_shape)
+            )
 
         self._amplitudes = xp.empty((self._num_diffraction_patterns,) + roi_shape)
-        self._region_of_interest_shape = np.array(roi_shape)
+
+        if region_of_interest_shape is not None:
+            self._resample_exit_waves = True
+            self._region_of_interest_shape = np.array(region_of_interest_shape)
+        else:
+            self._resample_exit_waves = False
+            self._region_of_interest_shape = np.array(self._amplitudes.shape[-2:])
 
         # TO-DO: generalize this
         if force_com_shifts is None:
@@ -381,7 +396,7 @@ def preprocess(
                     self._datacube[index],
                     diffraction_intensities_shape=self._diffraction_intensities_shape,
                     reshaping_method=self._reshaping_method,
-                    probe_roi_shape=self._probe_roi_shape,
+                    padded_diffraction_intensities_shape=self._padded_diffraction_intensities_shape,
                     vacuum_probe_intensity=self._vacuum_probe_intensity,
                     dp_mask=self._dp_mask,
                     com_shifts=force_com_shifts[index],
@@ -397,7 +412,7 @@ def preprocess(
                     self._datacube[index],
                     diffraction_intensities_shape=self._diffraction_intensities_shape,
                     reshaping_method=self._reshaping_method,
-                    probe_roi_shape=self._probe_roi_shape,
+                    padded_diffraction_intensities_shape=self._padded_diffraction_intensities_shape,
                     vacuum_probe_intensity=None,
                     dp_mask=None,
                     com_shifts=force_com_shifts[index],

py4DSTEM/process/phase/magnetic_ptychography.py

@@ -207,7 +207,8 @@ def preprocess(
         self,
         diffraction_intensities_shape: Tuple[int, int] = None,
         reshaping_method: str = "fourier",
-        probe_roi_shape: Tuple[int, int] = None,
+        padded_diffraction_intensities_shape: Tuple[int, int] = None,
+        region_of_interest_shape: Tuple[int, int] = None,
         dp_mask: np.ndarray = None,
         fit_function: str = "plane",
         plot_rotation: bool = True,
@@ -244,10 +245,13 @@ def preprocess(
             Pixel dimensions (Qx',Qy') of the resampled diffraction intensities
             If None, no resampling of diffraction intenstities is performed
         reshaping_method: str, optional
-            Method to use for reshaping, either 'bin', 'bilinear', or 'fourier' (default)
-        probe_roi_shape, (int,int), optional
+            Method to use for reshaping, either 'bin, 'bilinear', or 'fourier' (default)
+        padded_diffraction_intensities_shape: (int,int), optional
             Padded diffraction intensities shape.
             If None, no padding is performed
+        region_of_interest_shape: (int,int), optional
+            If not None, explicitly sets region_of_interest_shape and resamples exit_waves
+            at the diffraction plane to allow comparison with experimental data
         dp_mask: ndarray, optional
             Mask for datacube intensities (Qx,Qy)
         fit_function: str, optional
@@ -291,7 +295,9 @@ def preprocess(
         # set additional metadata
         self._diffraction_intensities_shape = diffraction_intensities_shape
         self._reshaping_method = reshaping_method
-        self._probe_roi_shape = probe_roi_shape
+        self._padded_diffraction_intensities_shape = (
+            padded_diffraction_intensities_shape
+        )
         self._dp_mask = dp_mask
 
         if self._datacube is None:
@@ -374,11 +380,20 @@ def preprocess(
         roi_shape = self._datacube[0].Qshape
         if diffraction_intensities_shape is not None:
             roi_shape = diffraction_intensities_shape
-        if probe_roi_shape is not None:
-            roi_shape = tuple(max(q, s) for q, s in zip(roi_shape, probe_roi_shape))
+        if padded_diffraction_intensities_shape is not None:
+            roi_shape = tuple(
+                max(q, s)
+                for q, s in zip(roi_shape, padded_diffraction_intensities_shape)
+            )
 
         self._amplitudes = xp.empty((self._num_diffraction_patterns,) + roi_shape)
-        self._region_of_interest_shape = np.array(roi_shape)
+
+        if region_of_interest_shape is not None:
+            self._resample_exit_waves = True
+            self._region_of_interest_shape = np.array(region_of_interest_shape)
+        else:
+            self._resample_exit_waves = False
+            self._region_of_interest_shape = np.array(self._amplitudes.shape[-2:])
 
         # TO-DO: generalize this
         if force_com_shifts is None:
@@ -408,7 +423,7 @@ def preprocess(
                     self._datacube[index],
                     diffraction_intensities_shape=self._diffraction_intensities_shape,
                     reshaping_method=self._reshaping_method,
-                    probe_roi_shape=self._probe_roi_shape,
+                    padded_diffraction_intensities_shape=self._padded_diffraction_intensities_shape,
                     vacuum_probe_intensity=self._vacuum_probe_intensity,
                     dp_mask=self._dp_mask,
                     com_shifts=force_com_shifts[index],
@@ -424,7 +439,7 @@ def preprocess(
                     self._datacube[index],
                     diffraction_intensities_shape=self._diffraction_intensities_shape,
                     reshaping_method=self._reshaping_method,
-                    probe_roi_shape=self._probe_roi_shape,
+                    padded_diffraction_intensities_shape=self._padded_diffraction_intensities_shape,
                     vacuum_probe_intensity=None,
                     dp_mask=None,
                     com_shifts=force_com_shifts[index],

py4DSTEM/process/phase/mixedstate_multislice_ptychography.py

@@ -276,7 +276,8 @@ def preprocess(
         self,
         diffraction_intensities_shape: Tuple[int, int] = None,
         reshaping_method: str = "fourier",
-        probe_roi_shape: Tuple[int, int] = None,
+        padded_diffraction_intensities_shape: Tuple[int, int] = None,
+        region_of_interest_shape: Tuple[int, int] = None,
         dp_mask: np.ndarray = None,
         fit_function: str = "plane",
         plot_center_of_mass: str = "default",
@@ -314,9 +315,12 @@ def preprocess(
             If None, no resampling of diffraction intenstities is performed
         reshaping_method: str, optional
             Method to use for reshaping, either 'bin, 'bilinear', or 'fourier' (default)
-        probe_roi_shape, (int,int), optional
+        padded_diffraction_intensities_shape: (int,int), optional
             Padded diffraction intensities shape.
             If None, no padding is performed
+        region_of_interest_shape: (int,int), optional
+            If not None, explicitly sets region_of_interest_shape and resamples exit_waves
+            at the diffraction plane to allow comparison with experimental data
         dp_mask: ndarray, optional
             Mask for datacube intensities (Qx,Qy)
         fit_function: str, optional
@@ -363,7 +367,9 @@ def preprocess(
         # set additional metadata
         self._diffraction_intensities_shape = diffraction_intensities_shape
         self._reshaping_method = reshaping_method
-        self._probe_roi_shape = probe_roi_shape
+        self._padded_diffraction_intensities_shape = (
+            padded_diffraction_intensities_shape
+        )
         self._dp_mask = dp_mask
 
         if self._datacube is None:
@@ -387,7 +393,7 @@ def preprocess(
             self._datacube,
             diffraction_intensities_shape=self._diffraction_intensities_shape,
             reshaping_method=self._reshaping_method,
-            probe_roi_shape=self._probe_roi_shape,
+            padded_diffraction_intensities_shape=self._padded_diffraction_intensities_shape,
             vacuum_probe_intensity=self._vacuum_probe_intensity,
             dp_mask=self._dp_mask,
             com_shifts=force_com_shifts,
@@ -460,7 +466,13 @@ def preprocess(
 
         # explicitly delete namespace
         self._num_diffraction_patterns = self._amplitudes.shape[0]
-        self._region_of_interest_shape = np.array(self._amplitudes.shape[-2:])
+
+        if region_of_interest_shape is not None:
+            self._resample_exit_waves = True
+            self._region_of_interest_shape = np.array(region_of_interest_shape)
+        else:
+            self._resample_exit_waves = False
+            self._region_of_interest_shape = np.array(self._amplitudes.shape[-2:])
         del self._intensities
 
         # initialize probe positions

py4DSTEM/process/phase/mixedstate_ptychography.py

@@ -217,7 +217,8 @@ def preprocess(
         self,
         diffraction_intensities_shape: Tuple[int, int] = None,
         reshaping_method: str = "fourier",
-        probe_roi_shape: Tuple[int, int] = None,
+        padded_diffraction_intensities_shape: Tuple[int, int] = None,
+        region_of_interest_shape: Tuple[int, int] = None,
         dp_mask: np.ndarray = None,
         fit_function: str = "plane",
         plot_center_of_mass: str = "default",
@@ -304,7 +305,9 @@ def preprocess(
         # set additional metadata
         self._diffraction_intensities_shape = diffraction_intensities_shape
         self._reshaping_method = reshaping_method
-        self._probe_roi_shape = probe_roi_shape
+        self._padded_diffraction_intensities_shape = (
+            padded_diffraction_intensities_shape
+        )
         self._dp_mask = dp_mask
 
         if self._datacube is None:
@@ -328,7 +331,7 @@ def preprocess(
             self._datacube,
             diffraction_intensities_shape=self._diffraction_intensities_shape,
             reshaping_method=self._reshaping_method,
-            probe_roi_shape=self._probe_roi_shape,
+            padded_diffraction_intensities_shape=self._padded_diffraction_intensities_shape,
             vacuum_probe_intensity=self._vacuum_probe_intensity,
             dp_mask=self._dp_mask,
             com_shifts=force_com_shifts,
@@ -401,7 +404,13 @@ def preprocess(
 
         # explicitly delete namespace
         self._num_diffraction_patterns = self._amplitudes.shape[0]
-        self._region_of_interest_shape = np.array(self._amplitudes.shape[-2:])
+
+        if region_of_interest_shape is not None:
+            self._resample_exit_waves = True
+            self._region_of_interest_shape = np.array(region_of_interest_shape)
+        else:
+            self._resample_exit_waves = False
+            self._region_of_interest_shape = np.array(self._amplitudes.shape[-2:])
         del self._intensities
 
         # initialize probe positions

py4DSTEM/process/phase/multislice_ptychography.py

@@ -251,7 +251,8 @@ def preprocess(
         self,
         diffraction_intensities_shape: Tuple[int, int] = None,
         reshaping_method: str = "fourier",
-        probe_roi_shape: Tuple[int, int] = None,
+        padded_diffraction_intensities_shape: Tuple[int, int] = None,
+        region_of_interest_shape: Tuple[int, int] = None,
         dp_mask: np.ndarray = None,
         fit_function: str = "plane",
         plot_center_of_mass: str = "default",
@@ -289,9 +290,12 @@ def preprocess(
             If None, no resampling of diffraction intenstities is performed
         reshaping_method: str, optional
             Method to use for reshaping, either 'bin, 'bilinear', or 'fourier' (default)
-        probe_roi_shape, (int,int), optional
+        padded_diffraction_intensities_shape: (int,int), optional
             Padded diffraction intensities shape.
             If None, no padding is performed
+        region_of_interest_shape: (int,int), optional
+            If not None, explicitly sets region_of_interest_shape and resamples exit_waves
+            at the diffraction plane to allow comparison with experimental data
         dp_mask: ndarray, optional
             Mask for datacube intensities (Qx,Qy)
         fit_function: str, optional
@@ -338,7 +342,9 @@ def preprocess(
         # set additional metadata
         self._diffraction_intensities_shape = diffraction_intensities_shape
         self._reshaping_method = reshaping_method
-        self._probe_roi_shape = probe_roi_shape
+        self._padded_diffraction_intensities_shape = (
+            padded_diffraction_intensities_shape
+        )
         self._dp_mask = dp_mask
 
         if self._datacube is None:
@@ -362,7 +368,7 @@ def preprocess(
             self._datacube,
             diffraction_intensities_shape=self._diffraction_intensities_shape,
             reshaping_method=self._reshaping_method,
-            probe_roi_shape=self._probe_roi_shape,
+            padded_diffraction_intensities_shape=self._padded_diffraction_intensities_shape,
             vacuum_probe_intensity=self._vacuum_probe_intensity,
             dp_mask=self._dp_mask,
             com_shifts=force_com_shifts,
@@ -435,7 +441,13 @@ def preprocess(
 
         # explicitly delete namespace
         self._num_diffraction_patterns = self._amplitudes.shape[0]
-        self._region_of_interest_shape = np.array(self._amplitudes.shape[-2:])
+
+        if region_of_interest_shape is not None:
+            self._resample_exit_waves = True
+            self._region_of_interest_shape = np.array(region_of_interest_shape)
+        else:
+            self._resample_exit_waves = False
+            self._region_of_interest_shape = np.array(self._amplitudes.shape[-2:])
         del self._intensities
 
         # initialize probe positions

py4DSTEM/process/phase/phase_base_class.py

@@ -136,7 +136,7 @@ def _preprocess_datacube_and_vacuum_probe(
         datacube,
         diffraction_intensities_shape=None,
         reshaping_method="fourier",
-        probe_roi_shape=None,
+        padded_diffraction_intensities_shape=None,
         vacuum_probe_intensity=None,
         dp_mask=None,
         com_shifts=None,
@@ -153,13 +153,10 @@ def _preprocess_datacube_and_vacuum_probe(
         Note this does not affect the maximum scattering wavevector (Qx*dkx,Qy*dky) = (Sx*dkx',Sy*dky'),
         and thus the real-space sampling stays fixed.
 
-        The real space sampling, (dx, dy), combined with the resampled diffraction_intensities_shape,
-        sets the real-space probe region of interest (ROI) extent (dx*Sx, dy*Sy).
-        Occasionally, one may also want to specify a larger probe ROI extent, e.g when the probe
-        does not comfortably fit without self-ovelap artifacts, or when the scan step sizes are much
-        smaller than the real-space sampling (dx,dy). This can be achieved by specifying a
-        probe_roi_shape, which is larger than diffraction_intensities_shape, which will result in
-        zero-padding of the diffraction intensities.
+        Additionally, one may wish to zero-pad the diffraction intensity data. Note this does not increase
+        the information or resolution, but might be beneficial in a limited number of cases, e.g. when the
+        scan step sizes are much smaller than the real-space sampling (dx,dy). This can be achieved by specifying
+        a padded_diffraction_intensities_shape which is larger than diffraction_intensities_shape.
 
         Parameters
         ----------
@@ -170,7 +167,7 @@ def _preprocess_datacube_and_vacuum_probe(
             If None, no resamping is performed
         reshaping method: str, optional
             Reshaping method to use, one of 'bin', 'bilinear' or 'fourier' (default)
-        probe_roi_shape, (int,int), optional
+        padded_diffraction_intensities_shape, (int,int), optional
             Padded diffraction intensities shape.
             If None, no padding is performed
         vacuum_probe_intensity, np.ndarray, optional
@@ -284,10 +281,10 @@ def _preprocess_datacube_and_vacuum_probe(
                     )
                 )
 
-        if probe_roi_shape is not None:
+        if padded_diffraction_intensities_shape is not None:
             Qx, Qy = datacube.shape[-2:]
-            Sx, Sy = probe_roi_shape
-            datacube = datacube.pad_Q(output_size=probe_roi_shape)
+            Sx, Sy = padded_diffraction_intensities_shape
+            datacube = datacube.pad_Q(output_size=padded_diffraction_intensities_shape)
 
             if vacuum_probe_intensity is not None or dp_mask is not None:
                 pad_kx = Sx - Qx