phercman5-lasagnetta / load_example.py
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import json
import numpy as np
import zarr
meta = json.load(open("PHercMAN5.lasagna.json"))
cos = zarr.open(meta["groups"]["cos"]["zarr"], mode="r") # cos, 2x down from the CT level read
nx = zarr.open(meta["groups"]["nx"]["zarr"], mode="r") # normals, 4x down; stored as v * 127 + 128
ny = zarr.open(meta["groups"]["ny"]["zarr"], mode="r")
z, y, x = 228, 490, 537 # a voxel on the normals' grid that holds data
a, b = (float(nx[z, y, x]) - 128) / 127, (float(ny[z, y, x]) - 128) / 127
c = np.sqrt(max(0.0, 1 - a * a - b * b)) # nz is not stored
patch = cos[2 * z, 2 * y:2 * y + 64, 2 * x:2 * x + 64] # the same place on the cos grid
print("normal", round(a, 3), round(b, 3), round(c, 3), "cos patch mean", float(np.mean(patch)))