snippet.py

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import numpy as np
matrix = np.array([
    [[1.000000, 1.000000, 1.000000], [0.988923, 0.790028, 0.798076], [0.642698, 0.978405, 0.956425], [0.481530, 0.971889, 0.932753], [0.405674, 0.998219, 0.999889]],
    [[0.988923, 0.790028, 0.798076], [1.000000, 1.000000, 1.000000], [0.731341, 0.669663, 0.624631], [0.570362, 0.904616, 0.956425], [0.490243, 0.756950, 0.790028]],
    [[0.642698, 0.978405, 0.956425], [0.731341, 0.669663, 0.624631], [1.000000, 1.000000, 1.000000], [0.964555, 0.904616, 0.798076], [0.922011, 0.988923, 0.960588]],
    [[0.481530, 0.971889, 0.932753], [0.570362, 0.904616, 0.956425], [0.964555, 0.904616, 0.798076], [1.000000, 1.000000, 1.000000], [0.991019, 0.956425, 0.927470]],
    [[0.405674, 0.998219, 0.999889], [0.490243, 0.756950, 0.790028], [0.922011, 0.988923, 0.960588], [0.991019, 0.956425, 0.927470], [1.000000, 1.000000, 1.000000]]
])
 
# Compute product t-norm (elementwise product of 3 values per cell)
product_tnorm = np.round(np.min(matrix, axis=2), 4)
 
print(product_tnorm)