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Fix usage of deprecated np.bool and np.int #46

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Fix usage of deprecated np.bool and np.int #46

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11 changes: 5 additions & 6 deletions neleval/munkres.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,8 +83,8 @@ def __init__(self, cost_matrix):

# At this point, m >= n.
n, m = self.C.shape
self.row_uncovered = np.ones(n, dtype=np.bool)
self.col_uncovered = np.ones(m, dtype=np.bool)
self.row_uncovered = np.ones(n, dtype=bool)
self.col_uncovered = np.ones(m, dtype=bool)
self.Z0_r = 0
self.Z0_c = 0
self.path = np.zeros((n + m, 2), dtype=int)
Expand Down Expand Up @@ -187,9 +187,9 @@ def _step4(state):
left. Save the smallest uncovered value and Go to Step 6.
"""
# We convert to int as numpy operations are faster on int
C = (state.C == 0).astype(np.int)
C = (state.C == 0).astype(int)
covered_C = C * state.row_uncovered[:, np.newaxis]
covered_C *= state.col_uncovered.astype(np.int)
covered_C *= state.col_uncovered.astype(int)
n = state.C.shape[0]
m = state.C.shape[1]
while True:
Expand All @@ -210,8 +210,7 @@ def _step4(state):
col = star_col
state.row_uncovered[row] = False
state.col_uncovered[col] = True
covered_C[:, col] = C[:, col] * (
state.row_uncovered.astype(np.int))
covered_C[:, col] = C[:, col] * (state.row_uncovered.astype(int))
covered_C[row] = 0


Expand Down