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Returns
-------
equilibria: A generator.
"""
if np.min(A) < 0:
A = A + abs(np.min(A))
if np.min(B) < 0:
B = B + abs(np.min(B))
number_of_row_strategies, row_dimension = A.shape
max_label = number_of_row_strategies + row_dimension
full_labels = set(range(max_label))
row_halfspaces = build_halfspaces(B.transpose())
col_halfspaces = build_halfspaces(A)
for row_v, row_l in non_trivial_vertices(row_halfspaces):
adjusted_row_l = set((label + number_of_row_strategies) % (max_label)
for label in row_l)
for col_v, col_l in non_trivial_vertices(col_halfspaces):
if adjusted_row_l.union(col_l) == full_labels:
yield row_v / sum(row_v), col_v / sum(col_v)
-------
equilibria: A generator.
"""
if np.min(A) < 0:
A = A + abs(np.min(A))
if np.min(B) < 0:
B = B + abs(np.min(B))
number_of_row_strategies, row_dimension = A.shape
max_label = number_of_row_strategies + row_dimension
full_labels = set(range(max_label))
row_halfspaces = build_halfspaces(B.transpose())
col_halfspaces = build_halfspaces(A)
for row_v, row_l in non_trivial_vertices(row_halfspaces):
adjusted_row_l = set((label + number_of_row_strategies) % (max_label)
for label in row_l)
for col_v, col_l in non_trivial_vertices(col_halfspaces):
if adjusted_row_l.union(col_l) == full_labels:
yield row_v / sum(row_v), col_v / sum(col_v)