def almostEqual(self, A, B, precision=15):
if FLOATING_PRECISION == 32:
precision = 7
elif FLOATING_PRECISION == 64:
precision = 16
else:
print "FLOATING_PRECISION has invalid value (neither 32 nor 64)."
exit()
# Unwrap the array object one dimension at a time:
def dissembleAndTest(A,B):
for i in range(A.shape[0]):
if A.shape.__len__() > 1:
dissembleAndTest(A[i],B[i])
else:
self.assertAlmostEqual(A[i], B[i], precision,
"expected %f+%fj, was %f+%fj (diff %e+%ej)"\
%(A[i].real,A[i].imag,B[i].real,B[i].imag,A[i].real-B[i].real, A[i].imag-B[i].imag))
if is_np_type(A.__class__):
if is_np_type(B.__class__) and A.shape == B.shape:
dissembleAndTest(A,B)
else:
self.fail("variables are not of the same type and/or shape")
else:
self.assertEqual(A, B,
"expected %f+%fj, was %f+%fj (diff %e+%ej)"\
%(A.real,A.imag,B.real,B.imag,A.real-B.real, A.imag-B.imag))
def almostEqual(self, A, B, precision=15):
if FLOATING_PRECISION == 32:
precision = 7
elif FLOATING_PRECISION == 64:
precision = 16
else:
print "FLOATING_PRECISION has invalid value (neither 32 nor 64)."
exit()
# Unwrap the array object one dimension at a time:
def dissembleAndTest(A, B):
for i in range(A.shape[0]):
if A.shape.__len__() > 1:
dissembleAndTest(A[i], B[i])
else:
self.assertAlmostEqual(A[i], B[i], precision,
"expected %f+%fj, was %f+%fj (diff %e+%ej)"\
%(A[i].real,A[i].imag,B[i].real,B[i].imag,A[i].real-B[i].real, A[i].imag-B[i].imag))
if is_np_type(A.__class__):
if is_np_type(B.__class__) and A.shape == B.shape:
dissembleAndTest(A, B)
else:
self.fail("variables are not of the same type and/or shape")
else:
self.assertEqual(A, B,
"expected %f+%fj, was %f+%fj (diff %e+%ej)"\
%(A.real,A.imag,B.real,B.imag,A.real-B.real, A.imag-B.imag))
def equal(self, A, B):
# Unwrap the array object one dimension at a time:
def dissembleAndTest(A,B):
for i in range(A.shape[0]):
if A.shape.__len__() > 1:
dissembleAndTest(A[i],B[i])
else:
self.assertEqual(A[i], B[i],
"expected %f+%fj, was %f+%fj (diff %e+%ej)"\
%(A[i].real,A[i].imag,B[i].real,B[i].imag,A[i].real-B[i].real, A[i].imag-B[i].imag))
if is_np_type(A.__class__):
if is_np_type(B.__class__) and A.shape == B.shape:
dissembleAndTest(A,B)
else:
self.fail("variables are not of the same type and/or shape")
else:
self.assertEqual(A, B,
"expected %f+%fj, was %f+%fj (diff %e+%ej)"\
%(A.real,A.imag,B.real,B.imag,A.real-B.real, A.imag-B.imag))
def equal(self, A, B):
# Unwrap the array object one dimension at a time:
def dissembleAndTest(A, B):
for i in range(A.shape[0]):
if A.shape.__len__() > 1:
dissembleAndTest(A[i], B[i])
else:
self.assertEqual(A[i], B[i],
"expected %f+%fj, was %f+%fj (diff %e+%ej)"\
%(A[i].real,A[i].imag,B[i].real,B[i].imag,A[i].real-B[i].real, A[i].imag-B[i].imag))
if is_np_type(A.__class__):
if is_np_type(B.__class__) and A.shape == B.shape:
dissembleAndTest(A, B)
else:
self.fail("variables are not of the same type and/or shape")
else:
self.assertEqual(A, B,
"expected %f+%fj, was %f+%fj (diff %e+%ej)"\
%(A.real,A.imag,B.real,B.imag,A.real-B.real, A.imag-B.imag))
