Merge remote-tracking branch 'origin/dev' into phase_contrast

py4DSTEM/braggvectors/diskdetection_aiml_cuda.py

@@ -496,7 +496,7 @@ def get_maxima_2D_cp(
         if minSpacing > 0:
             deletemask = np.zeros(len(maxima), dtype=bool)
             for i in range(len(maxima)):
-                if deletemask[i] is False:
+                if deletemask[i] == False:  # noqa: E712
                     tooClose = (
                         (maxima["x"] - maxima["x"][i]) ** 2
                         + (maxima["y"] - maxima["y"][i]) ** 2

py4DSTEM/braggvectors/diskdetection_cuda.py

@@ -482,7 +482,7 @@ def get_maxima_2D(
         if minSpacing > 0:
             deletemask = np.zeros(len(maxima), dtype=bool)
             for i in range(len(maxima)):
-                if deletemask[i] is False:
+                if deletemask[i] == False:  # noqa: E712
                     tooClose = (
                         (maxima["x"] - maxima["x"][i]) ** 2
                         + (maxima["y"] - maxima["y"][i]) ** 2

py4DSTEM/braggvectors/threshold.py

@@ -1,7 +1,6 @@
 # Bragg peaks thresholding fns
 
 import numpy as np
-
 from emdfile import tqdmnd, PointListArray
 
 
@@ -52,7 +51,7 @@ def threshold_Braggpeaks(
             r2 = minPeakSpacing**2
             deletemask = np.zeros(pointlist.length, dtype=bool)
             for i in range(pointlist.length):
-                if deletemask[i] is False:
+                if deletemask[i] == False:  # noqa: E712
                     tooClose = (
                         (pointlist.data["qx"] - pointlist.data["qx"][i]) ** 2
                         + (pointlist.data["qy"] - pointlist.data["qy"][i]) ** 2
@@ -160,7 +159,7 @@ def universal_threshold(
             r2 = minPeakSpacing**2
             deletemask = np.zeros(pointlist.length, dtype=bool)
             for i in range(pointlist.length):
-                if deletemask[i] is False:
+                if deletemask[i] == False:  # noqa: E712
                     tooClose = (
                         (pointlist.data["qx"] - pointlist.data["qx"][i]) ** 2
                         + (pointlist.data["qy"] - pointlist.data["qy"][i]) ** 2

py4DSTEM/io/filereaders/read_K2.py

@@ -336,9 +336,9 @@ def _find_offsets(self):
             for i in range(8):
                 sync = False
                 frame = 0
-                while sync is False:
+                while sync == False:  # noqa: E712
                     sync = self._bin_files[i][frame]["block"] == block_id
-                    if sync is False:
+                    if sync == False:  # noqa: E712
                         frame += 1
                 self._shutter_offsets[i] += frame
             print("Offsets are currently ", self._shutter_offsets)
@@ -358,20 +358,20 @@ def _find_offsets(self):
                     sync = False
                     next_frame = stripe[j]["frame"]
 
-        if sync is False:
+        if sync == False:  # noqa: E712
             # the first frame is incomplete, so we need to seek the next one
             print(
                 f"First frame ({first_frame}) incomplete, seeking frame {next_frame}..."
             )
             for i in range(8):
                 sync = False
                 frame = 0
-                while sync is False:
+                while sync == False:  # noqa: E712
                     sync = (
                         self._bin_files[i][self._shutter_offsets[i] + frame]["frame"]
                         == next_frame
                     )
-                    if sync is False:
+                    if sync == False:  # noqa: E712
                         frame += 1
                 self._shutter_offsets[i] += frame
             print("Offsets are now ", self._shutter_offsets)
@@ -387,7 +387,7 @@ def _find_offsets(self):
                 ]
                 if np.any(stripe[:]["frame"] != first_frame):
                     sync = False
-            if sync is True:
+            if sync == True:  # noqa: E712
                 print("New frame is complete!")
             else:
                 print("Next frame also incomplete!!!! Data may be corrupt?")
@@ -397,7 +397,7 @@ def _find_offsets(self):
         for i in range(8):
             shutter = False
             frame = 0
-            while shutter is False:
+            while shutter == False:  # noqa: E712
                 offset = self._shutter_offsets[i] + (frame * 32)
                 stripe = self._bin_files[i][offset : offset + 32]
                 shutter = stripe[0]["shutter"]

py4DSTEM/preprocess/radialbkgrd.py

@@ -80,7 +80,7 @@ def get_1D_polar_background(
     # Crop polar data to maximum distance which contains information from original image
     if (polarData.mask.sum(axis=(0)) == polarData.shape[0]).any():
         ii = polarData.data.shape[1] - 1
-        while polarData.mask[:, ii].all() is True:
+        while polarData.mask[:, ii].all() == True:  # noqa: E712
             ii = ii - 1
         maximalDistance = ii
         polarData = polarData[:, 0:maximalDistance]

py4DSTEM/preprocess/utils.py

@@ -293,7 +293,7 @@ def filter_2D_maxima(
     if minSpacing > 0:
         deletemask = np.zeros(len(maxima), dtype=bool)
         for i in range(len(maxima)):
-            if deletemask[i] is False:
+            if deletemask[i] == False:  # noqa: E712
                 tooClose = (
                     (maxima["x"] - maxima["x"][i]) ** 2
                     + (maxima["y"] - maxima["y"][i]) ** 2

py4DSTEM/process/calibration/ellipse.py

@@ -63,7 +63,7 @@ def fit_ellipse_1D(ar, center=None, fitradii=None, mask=None):
     rr = np.sqrt((xx - x0) ** 2 + (yy - y0) ** 2)
     _mask = (rr > ri) * (rr <= ro)
     if mask is not None:
-        _mask *= mask is False
+        _mask *= mask == False  # noqa: E712
     xs, ys = np.nonzero(_mask)
     vals = ar[_mask]
 

py4DSTEM/process/calibration/qpixelsize.py

@@ -60,6 +60,6 @@ def get_dq_from_indexed_peaks(qs, hkl, a):
     # Get pixel size
     dq = 1 / (c * a)
     qs_fit = d_inv[mask] / a
-    hkl_fit = [hkl[i] for i in range(len(hkl)) if mask[i] is True]
+    hkl_fit = [hkl[i] for i in range(len(hkl)) if mask[i] == True]  # noqa: E712
 
     return dq, qs_fit, hkl_fit

py4DSTEM/process/classification/braggvectorclassification.py

@@ -594,8 +594,8 @@ def merge_iterative(self, threshBPs=0.1, threshScanPosition=0.1):
             W_merge = W_merge[:, 1:]
             H_merge = H_merge[1:, :]
 
-            W_ = np.hstack((W_[:, merged is False], W_merge))
-            H_ = np.vstack((H_[merged is False, :], H_merge))
+            W_ = np.hstack((W_[:, merged == False], W_merge))  # noqa: E712
+            H_ = np.vstack((H_[merged == False, :], H_merge))  # noqa: E712
             Nc_ = W_.shape[1]
 
             if len(merge_candidates) == 0:

py4DSTEM/process/classification/featurization.py

@@ -182,7 +182,7 @@ def from_braggvectors(
                                     (pointlist.data["qy"] / q_pixel_size) + Q_Ny / 2
                                 ).astype(int),
                             ]
-                            is False
+                            == False  # noqa: E712
                         ),
                         True,
                         False,

py4DSTEM/process/diffraction/crystal_phase.py

@@ -276,7 +276,7 @@ def quantify_phase_pointlist(
         if len(pointlist["qx"]) > 0:
             if mask_peaks is not None:
                 for i in range(len(mask_peaks)):
-                    if mask_peaks[i] is None:
+                    if mask_peaks[i] == None:  # noqa: E711
                         continue
                     inds_mask = np.where(
                         pointlist_peak_intensity_matches[:, mask_peaks[i]] != 0

py4DSTEM/process/polar/polar_analysis.py

@@ -218,6 +218,7 @@ def calculate_pair_dist_function(
     r_max=20.0,
     r_step=0.02,
     damp_origin_fluctuations=True,
+    enforce_positivity=True,
     density=None,
     plot_background_fits=False,
     plot_sf_estimate=False,
@@ -281,6 +282,8 @@ def calculate_pair_dist_function(
         The value of the PDF approaching the origin should be zero, however numerical
         instability may result in non-physical finite values there. This flag toggles
         damping the value of the PDF to zero near the origin.
+    enforce_positivity:
+        Force all pdf values to be >0.
     density : number or None
         The density of the sample, if known.  If this is not provided, only the
         reduced PDF is calculated.  If this value is provided, the PDF is also
@@ -411,13 +414,13 @@ def calculate_pair_dist_function(
     if density is not None:
         pdf = pdf_reduced.copy()
         pdf[1:] /= 4 * np.pi * density * r[1:] * (r[1] - r[0])
-        pdf *= 2 / np.pi
         pdf += 1
 
         # damp and clip values below zero
         if damp_origin_fluctuations:
             pdf *= r_mask
-        pdf = np.maximum(pdf, 0.0)
+        if enforce_positivity:
+            pdf = np.maximum(pdf, 0.0)
 
         # store results
         self.pdf = pdf

py4DSTEM/process/polar/polar_datacube.py

@@ -292,16 +292,36 @@ def transform(self):
             these values directly. Length 2 list of ints uses the calibrated
             origin value at this scan position. None uses the calibrated mean
             origin.
+        ellipse : tuple or None
+            Variable behavior depending on the arg type. Length 3 tuples uses
+            these values directly (a,b,theta). None uses the calibrated value.
         mask : boolean array or None
             A mask applied to the data before transformation.  The value of
-            masked pixels (0's) in the output is determined by `returnval`. Note
-            that this mask is applied in combination with any mask at
-            PolarData.mask.
-        returnval : 'masked' or 'nan' or None
-            Controls the returned data. 'masked' returns a numpy masked array.
-            'nan' returns a normal numpy array with masked pixels set to np.nan.
-            None returns a 2-tuple of numpy arrays - the transformed data with
-            masked pixels set to 0, and the transformed mask.
+            masked pixels in the output is determined by `returnval`. Note that
+            this mask is applied in combination with any mask at PolarData.mask.
+        mask_thresh : number
+            Pixels in the transformed mask with values below this number are
+            considered masked, and will be populated by the values specified
+            by `returnval`.
+        returnval : 'masked' or 'nan' or 'all' or 'zeros' or 'all_zeros'
+            Controls the returned data, including how un-sampled points
+            are handled.
+              - 'masked' returns a numpy masked array.
+              - 'nan' returns a normal numpy array with unsampled pixels set to
+                np.nan.
+              - 'all' returns a 4-tuple of numpy arrays - the transformed data
+                with unsampled pixels set to 'nan', the normalization array, the
+                normalization array scaled to account for the q-dependent
+                sampling density, and the polar boolean mask
+              - 'zeros' returns a normal numpy with unsampled pixels set to 0
+              - 'all_zeros' returns the same 4-tuple as 'all', but with unsampled
+                pixels in the transformed data array set to zeros.
+
+         Returns
+        --------
+        variable
+            see `returnval`, above. Default is a masked array representing
+            the polar transformed data.
         """
         return self._polar_data_getter._transform
 

py4DSTEM/process/wholepatternfit/wp_models.py

@@ -1117,7 +1117,7 @@ def __init__(
         name="Complex Overlapped Disk Lattice",
         verbose=False,
     ):
-        return NotImplementedError(
+        raise NotImplementedError(
             "This model type has not been updated for use with the new architecture."
         )