switched to tqdmnd

py4DSTEM/process/digitaldarkfield/DDF.py

@@ -5,7 +5,7 @@
 """
 
 import numpy as np
-from alive_progress import alive_bar
+from emdfile import tqdmnd
 
 
 def aperture_array_generator(
@@ -108,32 +108,28 @@ def aperture_array_generator(
 def pointlist_to_array(bplist, idim, jdim):
  # This function turns the py4dstem pointslist object to a simple array that is more
  # convenient for rapid array processing in numpy
- with alive_bar(idim * jdim, force_tty=True) as bar:
- for i in range(idim):
- for j in range(jdim):
- if i == j == 0:
- ps = np.array(
- [
- bplist.cal[i, j].qx,
- bplist.cal[i, j].qy,
- bplist.cal[i, j].I,
- bplist.cal[i, j].qx.shape[0] * [i],
- bplist.cal[i, j].qx.shape[0] * [j],
- ]
- ).T
- bar()
- else:
- nps = np.array(
- [
- bplist.cal[i, j].qx,
- bplist.cal[i, j].qy,
- bplist.cal[i, j].I,
- bplist.cal[i, j].qx.shape[0] * [i],
- bplist.cal[i, j].qx.shape[0] * [j],
- ]
- ).T
- ps = np.vstack((ps, nps))
- bar()
+ for i, j in tqdmnd(idim, jdim):
+ if i == j == 0:
+ ps = np.array(
+ [
+ bplist.cal[i, j].qx,
+ bplist.cal[i, j].qy,
+ bplist.cal[i, j].I,
+ bplist.cal[i, j].qx.shape[0] * [i],
+ bplist.cal[i, j].qx.shape[0] * [j],
+ ]
+ ).T
+ else:
+ nps = np.array(
+ [
+ bplist.cal[i, j].qx,
+ bplist.cal[i, j].qy,
+ bplist.cal[i, j].I,
+ bplist.cal[i, j].qx.shape[0] * [i],
+ bplist.cal[i, j].qx.shape[0] * [j],
+ ]
+ ).T
+ ps = np.vstack((ps, nps))
  return ps # as a numpy array
  # ps will be an 2D numpy array of n points x 5 columns:
  # qx
@@ -162,17 +158,14 @@ def DDFimage(dataset, points, aperturearray, tol=1):
  # tol is the tolerance for a displacement between points and centers (in pixels)
  # this does rely on the pointslist_differences function
  image = np.zeros_like(dataset[:, :, 0, 0])
- with alive_bar(len(aperturearray), force_tty=True) as bar:
- for apertureposition in aperturearray:
- intensities = np.vstack(
- (points[:, 2:].T, pointlist_differences(apertureposition, points))
- ).T
- intensities2 = np.delete(
- intensities, np.where(intensities[:, 3] > tol), axis=0
- )
- for row in range(intensities2[:, 0].shape[0]):
- image[
- intensities2[row, 1].astype(int), intensities2[row, 2].astype(int)
- ] += intensities2[row, 0]
- bar()
+ for aperture_index in tqdmnd(len(aperturearray)):
+ apertureposition = aperturearray[aperture_index]
+ intensities = np.vstack(
+ (points[:, 2:].T, pointlist_differences(apertureposition, points))
+ ).T
+ intensities2 = np.delete(intensities, np.where(intensities[:, 3] > tol), axis=0)
+ for row in range(intensities2[:, 0].shape[0]):
+ image[
+ intensities2[row, 1].astype(int), intensities2[row, 2].astype(int)
+ ] += intensities2[row, 0]
  return image # as a 2D numpy array