def test_abs_frecuenty(self):
M = SparseMatrix(shape=(10, 10, 10))
M[1, 2, 3] = 2
M[3, 2, 1] = 2
M[2, 2, 2] = 2
R = M.abs_frecuency()
assert (R[0, 1] == 997) and (R[1, 1] == 3), 'Error en la frecuencia'
def test_randint(self):
M = SparseMatrix.randint(self.low, self.high, self.sparsity,
self.shape, self.fill_value)
self.assertGreaterEqual(M.min(), self.low)
self.assertLess(M.max(), self.high)
n = float(np.array(self.shape).prod())
self.assertEqual(M.T.shape[0] / n, self.sparsity)
def test_max_axis(self):
M = SparseMatrix.from_numpy(self.A)
print(M.max(axis=1).shape)
def test_add_int(self):
M = SparseMatrix.from_numpy(self.A)
assert np.all((M + 10).to_numpy() == (self.A +
10)), 'Error suma entero'
def test_setitem_all_one(self):
M = SparseMatrix.from_numpy(self.A)
M[:, :, :] = -1000
assert M.mean() == -1000, ''
def test_setitem_one_vs_one(self):
M = SparseMatrix.from_numpy(self.A)
for i in range(100):
self.A[i, i, i] = -1000
M[i, i, i] = -1000
self.assertEqual(self.A[i, i, i], M[i, i, i])
def test_var(self):
M = SparseMatrix.from_numpy(self.A)
self.assertEqual(round(M.var(), 5), round(self.A.var(), 5))
def test_mean(self):
M = SparseMatrix.from_numpy(self.A)
self.assertEqual(round(M.mean(), 5), round(self.A.mean(), 5))
def test_max(self):
M = SparseMatrix.from_numpy(self.A)
self.assertEqual(M.max(), self.A.max())
def test_sum(self):
M = SparseMatrix.from_numpy(self.A)
self.assertEqual(M.sum(), self.A.sum())
def test_to_numpy(self):
M = SparseMatrix.from_numpy(self.A)
M = M.to_numpy()
assert np.all(M == self.A), 'No cumple el máximo'
def test_from_numpy(self):
M = SparseMatrix.from_numpy(self.A)
self.assertEqual(M.shape.prod(), np.array(self.shape).prod())
self.assertEqual(M.sum(), self.A.sum())
self.assertGreaterEqual(M.min(), self.low)
self.assertLess(M.max(), self.high)