Acquire STEM Rotation Series with temscript

stem_temscript.py

from pprint import pprint
import temscript as ts
from math import pi

dwelltime = 1e-5 # seconds

tem = ts.Microscope()
illumination = tem._tem_illumination
instrument = ts.GetInstrument()
acq = instrument.Acquisition

stem_detectors = [det for det in acq.Detectors]
values = {'dwelltime(s)':dwelltime, 'image_size':'QUARTER'}
tem.set_detector_param(stem_detectors[0].Info.Name, values)

for detector in stem_detectors:
    pprint(detector.Info.Name)
    pprint(tem.get_detector_param(detector.Info.Name))
    acq.AddAcqDevice(detector)

datas = []
for i in range(4):
    illumination.StemRotation = i * pi/2
    illumination.BeamBlanked = False
    images = acq.AcquireImages()
    illumination.BeamBlanked = True
    data = {}
    for img in images:
        data[img.Name] = img.Array
    datas.append(data)
pprint(datas)

### Show images with matplotlib
import matplotlib.pyplot as plt

fig, AX = plt.subplots(ncols=2, nrows=2)
(ax1, ax2, ax3, ax4) = AX.flatten()
d = datas[0]['HAADF']
ax1.imshow(d)
d = datas[1]['HAADF']
ax2.imshow(d)
d = datas[2]['HAADF']
ax3.imshow(d)
d = datas[3]['HAADF']
ax4.imshow(d)

plt.show()

### Save data with Hyperspy
import hyperspy.api as hs

signal_names = [detector.Info.Name for detector in stem_detectors]
signals = []

for name in signal_names:
    signal_data = []
    for rot_data in datas:
        signal_data.append(rot_data[name])
    s = hs.signals.Signal2D(signal_data)
    s.save(name, overwrite=True)
    signals.append(s)
hs.stack(signals).save('stack.hspy', overwrite=True)