def compare(x, y):
from numpy.core import number, float_, result_type, array
from numpy.core.numerictypes import issubdtype
from numpy.core.fromnumeric import any as npany
try:
if npany(gisinf(x)) or npany(gisinf(y)):
xinfid = gisinf(x)
yinfid = gisinf(y)
if not (xinfid == yinfid).all():
return False
# if one item, x and y is +- inf
if x.size == y.size == 1:
return x == y
x = x[~xinfid]
y = y[~yinfid]
except (TypeError, NotImplementedError):
pass
# make sure y is an inexact type to avoid abs(MIN_INT); will cause
# casting of x later.
dtype = result_type(y, 1.)
y = array(y, dtype=dtype, copy=False, subok=True)
z = abs(x - y)
if not issubdtype(z.dtype, number):
z = z.astype(float_) # handle object arrays
return z < 1.5 * 10.0**(-decimal)
def compare(x, y):
try:
if npany(gisinf(x)) or npany( gisinf(y)):
xinfid = gisinf(x)
yinfid = gisinf(y)
if not xinfid == yinfid:
return False
# if one item, x and y is +- inf
if x.size == y.size == 1:
return x == y
x = x[~xinfid]
y = y[~yinfid]
except (TypeError, NotImplementedError):
pass
z = abs(x-y)
if not issubdtype(z.dtype, number):
z = z.astype(float_) # handle object arrays
return around(z, decimal) <= 10.0**(-decimal)
def compare(x, y):
try:
if npany(gisinf(x)) or npany( gisinf(y)):
xinfid = gisinf(x)
yinfid = gisinf(y)
if not xinfid == yinfid:
return False
# if one item, x and y is +- inf
if x.size == y.size == 1:
return x == y
x = x[~xinfid]
y = y[~yinfid]
except TypeError:
pass
z = abs(x-y)
if not issubdtype(z.dtype, number):
z = z.astype(float_) # handle object arrays
return around(z, decimal) <= 10.0**(-decimal)