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feat(ai): add get_col_transition
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@ -1,9 +1,9 @@
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import numpy as np
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from .peaks import get_peaks_max
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from .peaks import get_peaks, get_peaks_max
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def get_row_transitions(field: np.ndarray) -> int:
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def get_row_transition(field: np.ndarray) -> int:
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highest_peak = get_peaks_max(field)
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rows_to_check = slice(int(field.shape[0] - highest_peak), field.shape[0])
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@ -12,5 +12,17 @@ def get_row_transitions(field: np.ndarray) -> int:
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return int(transitions)
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def get_col_transitions(field: np.ndarray) -> int:
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pass
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def get_col_transition(field: np.ndarray) -> int:
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transitions_sum = 0
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peaks = get_peaks(field)
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for col in range(field.shape[1]):
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if peaks[col] <= 1:
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continue
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col_values = field[int(field.shape[0] - peaks[col]) : field.shape[0], col]
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transitions = np.sum(col_values[:-1] != col_values[1:])
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transitions_sum += transitions
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return transitions_sum
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@ -2,7 +2,11 @@ import unittest
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import numpy as np
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from ai.fitness.peaks import get_peaks_sum
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from ai.fitness.transitions import get_row_transitions
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from ai.fitness.transitions import (
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get_col_transition,
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get_col_transitions2,
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get_row_transition,
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)
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class TestFitness(unittest.TestCase):
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@ -33,4 +37,9 @@ class TestFitness(unittest.TestCase):
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def test_get_row_transistions(self):
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answers = (8, 0, 2)
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for field, answer in zip(self.fields, answers):
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self.assertEqual(get_row_transitions(field), answer)
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self.assertEqual(get_row_transition(field), answer)
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def test_get_col_transistions2(self):
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answers = (5, 0, 1)
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for field, answer in zip(self.fields, answers):
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self.assertEqual(get_col_transition(field), answer)
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