Bin - Quick Demo

Interactive calibration-aware 4D-STEM binning with BF/ADF quality checks.

import numpy as np
from quantem.widget import Bin
import quantem.widget
print(f"quantem.widget {quantem.widget.__version__}")

quantem.widget 0.4.0a3

rng = np.random.default_rng(0)
data = rng.random((32, 32, 96, 96), dtype=np.float32)
w = Bin(data, pixel_size=2.39, k_pixel_size=0.46, device='cpu')
w

# Access binned tensor for downstream analysis
binned = w.get_binned_data(copy=False)
print(type(binned), tuple(binned.shape))

<class 'torch.Tensor'> (32, 32, 96, 96)