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results_data.py
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import numpy as np
frequencies_original = np.array([
# 1.1
[ # 2
[0] * 10 + [0.25] * 0 + [0.5] * 4 + [0.75] * 0 + [1] * 6,
# 4
[0] * 7 + [0.25] * 4 + [0.5] * 0 + [0.75] * 1 + [1] * 8,
# 8
[0] * 11 + [0.25] * 0 + [0.5] * 0 + [0.75] * 0 + [1] * 9,
],
# 2:2
[ # 2
[0] * 8 + [0.25] * 0 + [0.5] * 6 + [0.75] * 0 + [1] * 6,
# 4
[0] * 8 + [0.25] * 5 + [0.5] * 0 + [0.75] * 2 + [1] * 5,
# 8
[0] * 10 + [0.25] * 1 + [0.5] * 0 + [0.75] * 1 + [1] * 8,
],
# 0:1
[ # 2
[0] * 2 + [0.25] * 0 + [0.5] * 1 + [0.75] * 0 + [1] * 17,
# 4
[0] * 5 + [0.25] * 2 + [0.5] * 0 + [0.75] * 5 + [1] * 8,
# 8
[0] * 7 + [0.25] * 0 + [0.5] * 0 + [0.75] * 2 + [1] * 11,
],
# 0:2
[ # 2
[None] * 20, # no data
# 4
[0] * 0 + [0.25] * 2 + [0.5] * 0 + [0.75] * 0 + [1] * 18,
# 8
[0] * 1 + [0.25] * 2 + [0.5] * 0 + [0.75] * 0 + [1] * 17,
],
# 0:3
[ # 2
[None] * 20, # no data,
# 4
[0] * 0 + [0.25] * 2 + [0.5] * 0 + [0.75] * 1 + [1] * 17,
# 8 # here error in graph as it sums in more than 1
[0] * 3 + [0.25] * 1 + [0.5] * 0 + [0.75] * 2 + [1] * 14,
],
# 1:2
[ # 2
[0] * 5 + [0.25] * 0 + [0.5] * 4 + [0.75] * 0 + [1] * 11,
# 4
[0] * 2 + [0.25] * 4 + [0.5] * 3 + [0.75] * 6 + [1] * 5,
# 8
[0] * 2 + [0.25] * 3 + [0.5] * 0 + [0.75] * 3 + [1] * 12,
],
# 1:3
[ # 2
[0] * 1 + [0.25] * 0 + [0.5] * 1 + [0.75] * 0 + [1] * 18,
# 4
[0] * 1 + [0.25] * 0 + [0.5] * 2 + [0.75] * 0 + [1] * 17,
# 8
[0] * 3 + [0.25] * 0 + [0.5] * 3 + [0.75] * 1 + [1] * 13,
],
])
data_example_run = np.array([[[1.0, 1.0, 1.0, 0.0, 0.5, 0.0, 0.0, 0.0, 0.5, 0.5, 0.5, 1.0, 1.0, 0.5, 1.0, 0.0, 0.0, 1.0, 0.5, 0.5, 1.0, 1.0, 0.5, 0.0, 0.5, 0.5, 0.5, 1.0, 1.0, 0.0], [0.25, 0.75, 1.0, 0.75, 0.75, 0.0, 0.0, 0.25, 1.0, 0.5, 0.0, 0.25, 0.25, 1.0, 0.5, 0.5, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.5, 0.5, 0.0, 1.0, 0.5, 1.0, 0.0, 0.75], [1.0, 0.75, 0.375, 0.375, 0.0, 0.25, 1.0, 0.75, 0.875, 0.625, 0.125, 0.0, 0.625, 0.125, 1.0, 0.75, 0.25, 1.0, 0.25, 0.25, 0.5, 0.0, 1.0, 0.875, 0.5, 0.25, 0.5, 0.0, 0.75, 1.0]], [[1.0, 0.0, 0.5, 0.0, 0.0, 0.5, 0.5, 0.0, 0.0, 0.5, 0.5, 0.0, 0.0, 0.0, 0.5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5, 0.0, 0.5, 1.0, 0.5, 0.0, 1.0, 0.0, 1.0, 0.5], [0.0, 0.25, 0.0, 0.5, 0.75, 0.25, 0.75, 1.0, 0.75, 1.0, 0.5, 0.5, 0.0, 1.0, 1.0, 0.75, 0.5, 0.25, 0.0, 1.0, 0.5, 1.0, 0.75, 0.25, 0.75, 0.25, 1.0, 0.75, 0.25, 1.0], [0.375, 0.25, 0.25, 1.0, 0.875, 0.875, 0.5, 0.5, 0.75, 0.625, 1.0, 0.125, 0.5, 0.5, 1.0, 0.125, 0.75, 0.625, 0.25, 0.0, 0.125, 0.625, 0.25, 0.5, 0.75, 0.25, 0.625, 0.375, 0.625, 1.0]], [[1.0, 0.0, 0.5, 0.5, 1.0, 0.5, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.5, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.5, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0], [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.5, 0.75, 0.75, 0.0, 1.0, 1.0, 1.0, 0.0, 0.25, 0.25, 1.0, 0.25, 1.0, 0.0, 0.75, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 0.0, 0.5], [1.0, 0.0, 0.25, 1.0, 1.0, 1.0, 0.625, 0.25, 0.625, 0.375, 0.375, 1.0, 0.125, 0.625, 0.25, 0.625, 0.75, 0.75, 0.75, 1.0, 0.75, 0.0, 1.0, 0.5, 1.0, 0.5, 0.5, 0.25, 0.875, 1.0]], [[0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0, 0.0, 0.5, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.5], [0.75, 1.0, 0.5, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.75, 0.25, 0.5, 1.0, 1.0, 0.0, 1.0, 0.5, 1.0, 0.0, 0.25, 1.0, 1.0, 1.0, 0.25, 0.0, 1.0, 0.0, 0.25, 0.0, 0.75], [0.75, 1.0, 1.0, 1.0, 1.0, 0.75, 1.0, 1.0, 0.875, 1.0, 0.0, 1.0, 0.0, 0.25, 1.0, 1.0, 0.625, 0.0, 0.625, 0.5, 1.0, 0.5, 0.0, 0.75, 0.25, 0.375, 0.25, 1.0, 0.5, 0.875]], [[0.0, 0.0, 1.0, 1.0, 0.5, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 0.0], [1.0, 0.25, 1.0, 1.0, 1.0, 0.75, 0.0, 1.0, 0.75, 0.0, 1.0, 0.0, 0.25, 0.5, 0.75, 1.0, 1.0, 0.5, 0.25, 0.0, 0.25, 1.0, 1.0, 0.25, 1.0, 1.0, 0.25, 0.0, 0.5, 1.0], [0.375, 0.5, 0.0, 0.125, 1.0, 0.75, 0.375, 1.0, 1.0, 0.375, 0.375, 0.75, 0.5, 0.125, 1.0, 0.5, 0.75, 0.375, 0.0, 0.5, 0.375, 1.0, 0.375, 0.5, 0.625, 0.125, 1.0, 1.0, 1.0, 1.0]], [[0.0, 1.0, 1.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 1.0, 0.5, 1.0, 1.0, 0.5, 0.5, 1.0, 0.5, 0.5, 1.0, 0.0, 1.0, 0.5, 0.0, 1.0, 0.0], [0.5, 0.0, 0.0, 0.5, 0.5, 0.5, 0.25, 0.25, 0.5, 1.0, 1.0, 0.0, 0.25, 0.0, 0.0, 0.25, 0.5, 0.0, 0.75, 0.25, 1.0, 0.25, 0.5, 0.75, 1.0, 0.75, 0.5, 0.75, 0.75, 0.5], [0.625, 0.75, 0.0, 0.625, 0.875, 0.875, 0.5, 0.75, 0.625, 0.25, 1.0, 0.5, 0.75, 0.125, 0.0, 0.625, 0.75, 0.375, 0.625, 0.25, 0.625, 0.125, 0.5, 0.75, 1.0, 0.125, 0.375, 0.25, 0.875, 0.5]], [[1.0, 0.5, 1.0, 0.5, 1.0, 0.0, 0.0, 1.0, 0.0, 0.5, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 1.0, 0.5, 0.5, 0.5, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 0.0, 1.0], [0.0, 0.0, 0.25, 0.25, 0.5, 1.0, 1.0, 0.25, 0.25, 1.0, 0.5, 0.75, 0.25, 1.0, 0.75, 1.0, 0.0, 1.0, 0.75, 1.0, 0.0, 0.5, 1.0, 0.5, 1.0, 0.0, 0.25, 1.0, 0.0, 1.0], [0.25, 0.125, 0.0, 0.625, 0.0, 1.0, 0.75, 0.75, 0.25, 0.125, 0.5, 1.0, 0.625, 0.375, 0.25, 0.5, 0.75, 0.5, 0.625, 0.625, 1.0, 0.0, 0.125, 0.5, 0.625, 0.5, 0.0, 1.0, 0.375, 0.625]]])