def _get_outer_edges(a, range):
"""
Determine the outer bin edges to use, from either the data or the range
argument
"""
if range is not None:
first_edge, last_edge = range
if first_edge > last_edge:
raise ValueError('max must be larger than min in range parameter.')
if not (np.isfinite(first_edge) and np.isfinite(last_edge)):
raise ValueError("supplied range of [{}, {}] is not finite".format(
first_edge, last_edge))
elif a.size == 0:
# handle empty arrays. Can't determine range, so use 0-1.
first_edge, last_edge = 0, 1
else:
first_edge, last_edge = a.min(), a.max()
if not (np.isfinite(first_edge) and np.isfinite(last_edge)):
raise ValueError(
"autodetected range of [{}, {}] is not finite".format(
first_edge, last_edge))
# expand empty range to avoid divide by zero
if first_edge == last_edge:
first_edge = first_edge - 0.5
last_edge = last_edge + 0.5
return first_edge, last_edge
def test_nans_infs(self):
with np.errstate(all='ignore'):
# Check some of the ufuncs
assert_equal(np.isnan(self.all_f16), np.isnan(self.all_f32))
assert_equal(np.isinf(self.all_f16), np.isinf(self.all_f32))
assert_equal(np.isfinite(self.all_f16), np.isfinite(self.all_f32))
assert_equal(np.signbit(self.all_f16), np.signbit(self.all_f32))
assert_equal(np.spacing(float16(65504)), np.inf)
# Check comparisons of all values with NaN
nan = float16(np.nan)
assert_(not (self.all_f16 == nan).any())
assert_(not (nan == self.all_f16).any())
assert_((self.all_f16 != nan).all())
assert_((nan != self.all_f16).all())
assert_(not (self.all_f16 < nan).any())
assert_(not (nan < self.all_f16).any())
assert_(not (self.all_f16 <= nan).any())
assert_(not (nan <= self.all_f16).any())
assert_(not (self.all_f16 > nan).any())
assert_(not (nan > self.all_f16).any())
assert_(not (self.all_f16 >= nan).any())
assert_(not (nan >= self.all_f16).any())
def test_complex_bad2(self):
with np.errstate(divide='ignore', invalid='ignore'):
v = 1 + 1j
v += np.array(-1 + 1.j) / 0.
vals = nan_to_num(v)
assert_all(np.isfinite(vals))
assert_equal(type(vals), np.complex_)
def test_complex_bad(self):
with np.errstate(divide='ignore', invalid='ignore'):
v = 1 + 1j
v += np.array(0 + 1.j) / 0.
vals = nan_to_num(v)
# !! This is actually (unexpectedly) zero
assert_all(np.isfinite(vals))
assert_equal(type(vals), np.complex_)
def test_generic(self):
with np.errstate(divide='ignore', invalid='ignore'):
vals = nan_to_num(np.array((-1., 0, 1)) / 0.)
assert_all(vals[0] < -1e10) and assert_all(np.isfinite(vals[0]))
assert_(vals[1] == 0)
assert_all(vals[2] > 1e10) and assert_all(np.isfinite(vals[2]))
assert_equal(type(vals), np.ndarray)
# perform the same test but in-place
with np.errstate(divide='ignore', invalid='ignore'):
vals = np.array((-1., 0, 1)) / 0.
result = nan_to_num(vals, copy=False)
assert_(result is vals)
assert_all(vals[0] < -1e10) and assert_all(np.isfinite(vals[0]))
assert_(vals[1] == 0)
assert_all(vals[2] > 1e10) and assert_all(np.isfinite(vals[2]))
assert_equal(type(vals), np.ndarray)
def test_half_ufuncs(self):
"""Test the various ufuncs"""
a = np.array([0, 1, 2, 4, 2], dtype=float16)
b = np.array([-2, 5, 1, 4, 3], dtype=float16)
c = np.array([0, -1, -np.inf, np.nan, 6], dtype=float16)
assert_equal(np.add(a, b), [-2, 6, 3, 8, 5])
assert_equal(np.subtract(a, b), [2, -4, 1, 0, -1])
assert_equal(np.multiply(a, b), [0, 5, 2, 16, 6])
assert_equal(np.divide(a, b), [0, 0.199951171875, 2, 1, 0.66650390625])
assert_equal(np.equal(a, b), [False, False, False, True, False])
assert_equal(np.not_equal(a, b), [True, True, True, False, True])
assert_equal(np.less(a, b), [False, True, False, False, True])
assert_equal(np.less_equal(a, b), [False, True, False, True, True])
assert_equal(np.greater(a, b), [True, False, True, False, False])
assert_equal(np.greater_equal(a, b), [True, False, True, True, False])
assert_equal(np.logical_and(a, b), [False, True, True, True, True])
assert_equal(np.logical_or(a, b), [True, True, True, True, True])
assert_equal(np.logical_xor(a, b), [True, False, False, False, False])
assert_equal(np.logical_not(a), [True, False, False, False, False])
assert_equal(np.isnan(c), [False, False, False, True, False])
assert_equal(np.isinf(c), [False, False, True, False, False])
assert_equal(np.isfinite(c), [True, True, False, False, True])
assert_equal(np.signbit(b), [True, False, False, False, False])
assert_equal(np.copysign(b, a), [2, 5, 1, 4, 3])
assert_equal(np.maximum(a, b), [0, 5, 2, 4, 3])
x = np.maximum(b, c)
assert_(np.isnan(x[3]))
x[3] = 0
assert_equal(x, [0, 5, 1, 0, 6])
assert_equal(np.minimum(a, b), [-2, 1, 1, 4, 2])
x = np.minimum(b, c)
assert_(np.isnan(x[3]))
x[3] = 0
assert_equal(x, [-2, -1, -np.inf, 0, 3])
assert_equal(np.fmax(a, b), [0, 5, 2, 4, 3])
assert_equal(np.fmax(b, c), [0, 5, 1, 4, 6])
assert_equal(np.fmin(a, b), [-2, 1, 1, 4, 2])
assert_equal(np.fmin(b, c), [-2, -1, -np.inf, 4, 3])
assert_equal(np.floor_divide(a, b), [0, 0, 2, 1, 0])
assert_equal(np.remainder(a, b), [0, 1, 0, 0, 2])
assert_equal(np.divmod(a, b), ([0, 0, 2, 1, 0], [0, 1, 0, 0, 2]))
assert_equal(np.square(b), [4, 25, 1, 16, 9])
assert_equal(np.reciprocal(b),
[-0.5, 0.199951171875, 1, 0.25, 0.333251953125])
assert_equal(np.ones_like(b), [1, 1, 1, 1, 1])
assert_equal(np.conjugate(b), b)
assert_equal(np.absolute(b), [2, 5, 1, 4, 3])
assert_equal(np.negative(b), [2, -5, -1, -4, -3])
assert_equal(np.positive(b), b)
assert_equal(np.sign(b), [-1, 1, 1, 1, 1])
assert_equal(np.modf(b), ([0, 0, 0, 0, 0], b))
assert_equal(np.frexp(b),
([-0.5, 0.625, 0.5, 0.5, 0.75], [2, 3, 1, 3, 2]))
assert_equal(np.ldexp(b, [0, 1, 2, 4, 2]), [-2, 10, 4, 64, 12])
def test_complex1(self):
with np.errstate(divide='ignore', invalid='ignore'):
assert_all(np.isfinite(np.array(1 + 1j) / 0.) == 0)
def test_complex(self):
assert_all(np.isfinite(1 + 1j) == 1)
def test_integer(self):
assert_all(np.isfinite(1) == 1)
def test_ind(self):
with np.errstate(divide='ignore', invalid='ignore'):
assert_all(np.isfinite(np.array((0., )) / 0.) == 0)
def test_goodvalues(self):
z = np.array((-1., 0., 1.))
res = np.isfinite(z) == 1
assert_all(np.all(res, axis=0))