def test_singular_a(self):
for b in [self.b_1dim, self.b_2dim]:
for dtype in self.dtypes:
a = np.asfortranarray(self.a_singular, dtype=dtype)
b = np.asfortranarray(b, dtype=dtype)
r = _numba_linalg_solve(a, b)
ok_(r != 0)
def _indiff_mixed_action(payoff_matrix, own_supp, opp_supp, A, out):
"""
Parameters
----------
payoff_matrix : ndarray(ndim=2)
The player's payoff matrix, of shape (m, n).
own_supp : ndarray(int, ndim=1)
Array containing the player's action indices, of length k.
opp_supp : ndarray(int, ndim=1)
Array containing the opponent's action indices, of length k.
A : ndarray(float, ndim=2)
Array used in intermediate steps, of shape (k+1, k+1).
out : ndarray(float, ndim=1)
Array of length k+1 to store the k nonzero values of the desired
mixed action in `out[:-1]` (and the payoff value in `out[-1]`).
Returns
-------
bool
`True` if a desired mixed action exists and `False` otherwise.
"""
m = payoff_matrix.shape[0]
k = len(own_supp)
for i in range(k):
for j in range(k):
A[j, i] = payoff_matrix[own_supp[i], opp_supp[j]] # transpose
A[:-1, -1] = 1
A[-1, :-1] = -1
A[-1, -1] = 0
out[:-1] = 0
out[-1] = 1
r = _numba_linalg_solve(A, out)
if r != 0: # A: singular
return False
for i in range(k):
if out[i] <= 0:
return False
val = out[-1]
if k == m:
return True
own_supp_flags = np.zeros(m, np.bool_)
own_supp_flags[own_supp] = True
for i in range(m):
if not own_supp_flags[i]:
payoff = 0
for j in range(k):
payoff += payoff_matrix[i, opp_supp[j]] * out[j]
if payoff > val:
return False
return True
def test_b_2dim(self):
for dtype in self.dtypes:
a = np.asfortranarray(self.a, dtype=dtype)
b = np.asfortranarray(self.b_2dim, dtype=dtype)
sol_orig = numba_linalg_solve_orig(a, b)
r = _numba_linalg_solve(a, b)
eq_(r, 0)
assert_array_equal(b, sol_orig)