def get_test_array(shape, dtype, no_zeros=False, high=None):
if not isinstance(shape, tuple):
shape = (shape,)
dtype = dtypes.normalize_type(dtype)
if dtypes.is_integer(dtype):
low = 1 if no_zeros else 0
if high is None:
high = 100 # will work even with signed chars
get_arr = lambda: numpy.random.randint(low, high, shape).astype(dtype)
else:
low = 0.01 if no_zeros else 0
if high is None:
high = 1.0
get_arr = lambda: numpy.random.uniform(low, high, shape).astype(dtype)
if dtypes.is_complex(dtype):
return get_arr() + 1j * get_arr()
else:
return get_arr()
def get_test_array(shape, dtype, no_zeros=False, high=None):
if not isinstance(shape, tuple):
shape = (shape, )
dtype = dtypes.normalize_type(dtype)
if dtypes.is_integer(dtype):
low = 1 if no_zeros else 0
if high is None:
high = 100 # will work even with signed chars
get_arr = lambda: numpy.random.randint(low, high, shape).astype(dtype)
else:
low = 0.01 if no_zeros else 0
if high is None:
high = 1.0
get_arr = lambda: numpy.random.uniform(low, high, shape).astype(dtype)
if dtypes.is_complex(dtype):
return get_arr() + 1j * get_arr()
else:
return get_arr()
def diff_is_negligible(m, m_ref):
assert m.dtype == m_ref.dtype
if dtypes.is_integer(m.dtype):
return ((m - m_ref) == 0).all()
else:
return float_diff(m, m_ref) < SINGLE_EPS
def diff_is_negligible(m, m_ref):
assert m.dtype == m_ref.dtype
if dtypes.is_integer(m.dtype):
return ((m - m_ref) == 0).all()
else:
return float_diff(m, m_ref) < SINGLE_EPS