real space mask for positions to ignore

py4DSTEM/process/phase/iterative_base_class.py

@@ -1535,7 +1535,9 @@ def _set_polar_parameters(self, parameters: dict):
             else:
                 raise ValueError("{} not a recognized parameter".format(symbol))
 
-    def _calculate_scan_positions_in_pixels(self, positions: np.ndarray):
+    def _calculate_scan_positions_in_pixels(
+        self, positions: np.ndarray, positions_mask
+    ):
         """
         Method to compute the initial guess of scan positions in pixels.
 
@@ -1544,6 +1546,8 @@ def _calculate_scan_positions_in_pixels(self, positions: np.ndarray):
         positions: (J,2) np.ndarray or None
             Input probe positions in Å.
             If None, a raster scan using experimental parameters is constructed.
+        positions_mask: np.ndarray, optional
+            Boolean real space mask to select positions in datacube to skip for reconstruction
 
         Returns
         -------
@@ -1592,6 +1596,15 @@ def _calculate_scan_positions_in_pixels(self, positions: np.ndarray):
             positions = np.array([x.ravel(), y.ravel()]).T
         positions -= np.min(positions, axis=0)
 
+        if positions_mask is not None:
+            if positions_mask.dtype != "bool":
+                warnings.warn(
+                    ("`positions_mask` converged to `bool` array"),
+                    UserWarning,
+                )
+                positions_mask = np.asarray(positions_mask, dtype="bool")
+            positions = positions[positions_mask.ravel()]
+
         if self._object_padding_px is None:
             float_padding = self._region_of_interest_shape / 2
             self._object_padding_px = (float_padding, float_padding)

py4DSTEM/process/phase/iterative_mixedstate_multislice_ptychography.py

@@ -85,6 +85,8 @@ class MixedstateMultislicePtychographicReconstruction(PtychographicReconstructio
     object_type: str, optional
         The object can be reconstructed as a real potential ('potential') or a complex
         object ('complex')
+    positions_mask: np.ndarray, optional
+        Boolean real space mask to select positions in datacube to skip for reconstruction
     verbose: bool, optional
         If True, class methods will inherit this and print additional information
     device: str, optional
@@ -115,6 +117,7 @@ def __init__(
         initial_probe_guess: np.ndarray = None,
         initial_scan_positions: np.ndarray = None,
         object_type: str = "complex",
+        positions_mask: np.ndarray = None,
         verbose: bool = True,
         device: str = "cpu",
         name: str = "multi-slice_ptychographic_reconstruction",
@@ -201,6 +204,7 @@ def __init__(
         self._semiangle_cutoff_pixels = semiangle_cutoff_pixels
         self._rolloff = rolloff
         self._object_type = object_type
+        self._positions_mask = positions_mask
         self._object_padding_px = object_padding_px
         self._verbose = verbose
         self._device = device
@@ -454,7 +458,7 @@ def preprocess(
         del self._intensities
 
         self._positions_px = self._calculate_scan_positions_in_pixels(
-            self._scan_positions
+            self._scan_positions, self._positions_mask
         )
 
         # handle semiangle specified in pixels

py4DSTEM/process/phase/iterative_mixedstate_ptychography.py

@@ -74,6 +74,8 @@ class MixedstatePtychographicReconstruction(PtychographicReconstruction):
     initial_scan_positions: np.ndarray, optional
         Probe positions in Å for each diffraction intensity
         If None, initialized to a grid scan
+    positions_mask: np.ndarray, optional
+        Boolean real space mask to select positions in datacube to skip for reconstruction
     verbose: bool, optional
         If True, class methods will inherit this and print additional information
     device: str, optional
@@ -102,6 +104,7 @@ def __init__(
         initial_probe_guess: np.ndarray = None,
         initial_scan_positions: np.ndarray = None,
         object_type: str = "complex",
+        positions_mask: np.ndarray = None,
         verbose: bool = True,
         device: str = "cpu",
         name: str = "mixed-state_ptychographic_reconstruction",
@@ -178,6 +181,7 @@ def __init__(
         self._rolloff = rolloff
         self._object_type = object_type
         self._object_padding_px = object_padding_px
+        self._positions_mask = positions_mask
         self._verbose = verbose
         self._device = device
         self._preprocessed = False
@@ -358,7 +362,7 @@ def preprocess(
         del self._intensities
 
         self._positions_px = self._calculate_scan_positions_in_pixels(
-            self._scan_positions
+            self._scan_positions, self._positions_mask
         )
 
         # handle semiangle specified in pixels

py4DSTEM/process/phase/iterative_multislice_ptychography.py

@@ -89,6 +89,8 @@ class MultislicePtychographicReconstruction(PtychographicReconstruction):
     object_type: str, optional
         The object can be reconstructed as a real potential ('potential') or a complex
         object ('complex')
+    positions_mask: np.ndarray, optional
+        Boolean real space mask to select positions in datacube to skip for reconstruction
     verbose: bool, optional
         If True, class methods will inherit this and print additional information
     device: str, optional
@@ -121,6 +123,7 @@ def __init__(
         theta_y: float = 0,
         middle_focus: bool = False,
         object_type: str = "complex",
+        positions_mask: np.ndarray = None,
         verbose: bool = True,
         device: str = "cpu",
         name: str = "multi-slice_ptychographic_reconstruction",
@@ -211,6 +214,7 @@ def __init__(
         self._semiangle_cutoff_pixels = semiangle_cutoff_pixels
         self._rolloff = rolloff
         self._object_type = object_type
+        self._positions_mask = positions_mask
         self._object_padding_px = object_padding_px
         self._verbose = verbose
         self._device = device
@@ -481,7 +485,7 @@ def preprocess(
         del self._intensities
 
         self._positions_px = self._calculate_scan_positions_in_pixels(
-            self._scan_positions
+            self._scan_positions, self._positions_mask
         )
 
         # handle semiangle specified in pixels

py4DSTEM/process/phase/iterative_overlap_magnetic_tomography.py

@@ -93,6 +93,8 @@ class OverlapMagneticTomographicReconstruction(PtychographicReconstruction):
     object_type: str, optional
         The object can be reconstructed as a real potential ('potential') or a complex
         object ('complex')
+    positions_mask: np.ndarray, optional
+        Boolean real space mask to select positions in datacube to skip for reconstruction
     name: str, optional
         Class name
     kwargs:
@@ -115,6 +117,7 @@ def __init__(
         polar_parameters: Mapping[str, float] = None,
         object_padding_px: Tuple[int, int] = None,
         object_type: str = "potential",
+        positions_mask: np.ndarray = None,
         initial_object_guess: np.ndarray = None,
         initial_probe_guess: np.ndarray = None,
         initial_scan_positions: Sequence[np.ndarray] = None,
@@ -179,6 +182,7 @@ def __init__(
         self._rolloff = rolloff
         self._object_type = object_type
         self._object_padding_px = object_padding_px
+        self._positions_mask = positions_mask
         self._verbose = verbose
         self._device = device
         self._preprocessed = False
@@ -615,7 +619,7 @@ def preprocess(
                     tilt_index + 1
                 ]
             ] = self._calculate_scan_positions_in_pixels(
-                self._scan_positions[tilt_index]
+                self._scan_positions[tilt_index], self._positions_mask[tilt_index]
             )
 
         # handle semiangle specified in pixels

py4DSTEM/process/phase/iterative_overlap_tomography.py

@@ -88,6 +88,8 @@ class OverlapTomographicReconstruction(PtychographicReconstruction):
     object_type: str, optional
         The object can be reconstructed as a real potential ('potential') or a complex
         object ('complex')
+    positions_mask: np.ndarray, optional
+        Boolean real space mask to select positions to ignore in reconstruction
     name: str, optional
         Class name
     kwargs:
@@ -111,6 +113,7 @@ def __init__(
         polar_parameters: Mapping[str, float] = None,
         object_padding_px: Tuple[int, int] = None,
         object_type: str = "potential",
+        positions_mask: np.ndarray = None,
         initial_object_guess: np.ndarray = None,
         initial_probe_guess: np.ndarray = None,
         initial_scan_positions: Sequence[np.ndarray] = None,
@@ -188,6 +191,7 @@ def __init__(
         self._rolloff = rolloff
         self._object_type = object_type
         self._object_padding_px = object_padding_px
+        self._positions_mask = positions_mask
         self._verbose = verbose
         self._device = device
         self._preprocessed = False
@@ -555,7 +559,7 @@ def preprocess(
                     tilt_index + 1
                 ]
             ] = self._calculate_scan_positions_in_pixels(
-                self._scan_positions[tilt_index]
+                self._scan_positions[tilt_index], self._positions_mask[tilt_index]
             )
 
         # handle semiangle specified in pixels

py4DSTEM/process/phase/iterative_simultaneous_ptychography.py

@@ -66,6 +66,8 @@ class SimultaneousPtychographicReconstruction(PtychographicReconstruction):
     object_padding_px: Tuple[int,int], optional
         Pixel dimensions to pad objects with
         If None, the padding is set to half the probe ROI dimensions
+    positions_mask: np.ndarray, optional
+        Boolean real space mask to select positions in datacube to skip for reconstruction
     initial_object_guess: np.ndarray, optional
         Initial guess for complex-valued object of dimensions (Px,Py)
         If None, initialized to 1.0j
@@ -102,6 +104,7 @@ def __init__(
         vacuum_probe_intensity: np.ndarray = None,
         polar_parameters: Mapping[str, float] = None,
         object_padding_px: Tuple[int, int] = None,
+        positions_mask: np.ndarray = None,
         initial_object_guess: np.ndarray = None,
         initial_probe_guess: np.ndarray = None,
         initial_scan_positions: np.ndarray = None,
@@ -167,6 +170,7 @@ def __init__(
         self._rolloff = rolloff
         self._object_type = object_type
         self._object_padding_px = object_padding_px
+        self._positions_mask = positions_mask
         self._verbose = verbose
         self._device = device
         self._preprocessed = False
@@ -607,7 +611,7 @@ def preprocess(
         self._region_of_interest_shape = np.array(self._amplitudes[0].shape[-2:])
 
         self._positions_px = self._calculate_scan_positions_in_pixels(
-            self._scan_positions
+            self._scan_positions, self._positions_mask
         )
 
         # handle semiangle specified in pixels

py4DSTEM/process/phase/iterative_singleslice_ptychography.py

@@ -79,6 +79,8 @@ class SingleslicePtychographicReconstruction(PtychographicReconstruction):
     object_type: str, optional
         The object can be reconstructed as a real potential ('potential') or a complex
         object ('complex')
+    positions_mask: np.ndarray, optional
+        Boolean real space mask to select positions in datacube to skip for reconstruction
     name: str, optional
         Class name
     kwargs:
@@ -102,6 +104,7 @@ def __init__(
         initial_scan_positions: np.ndarray = None,
         object_padding_px: Tuple[int, int] = None,
         object_type: str = "complex",
+        positions_mask: np.ndarray = None,
         verbose: bool = True,
         device: str = "cpu",
         name: str = "ptychographic_reconstruction",
@@ -163,6 +166,7 @@ def __init__(
         self._rolloff = rolloff
         self._object_type = object_type
         self._object_padding_px = object_padding_px
+        self._positions_mask = positions_mask
         self._verbose = verbose
         self._device = device
         self._preprocessed = False
@@ -342,7 +346,7 @@ def preprocess(
         del self._intensities
 
         self._positions_px = self._calculate_scan_positions_in_pixels(
-            self._scan_positions
+            self._scan_positions, self._positions_mask
         )
 
         # handle semiangle specified in pixels