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"""
Module of functions that are like ufuncs in acting on arrays and optionally
storing results in an output array.
"""
__all__ = ['fix', 'isneginf', 'isposinf', 'log2']
import numpy.core.numeric as nx
from numpy.core.numeric import asarray, empty, isinf, signbit, asanyarray
import numpy.core.umath as umath
def fix(x, y=None):
""" Round x to nearest integer towards zero.
"""
x = asanyarray(x)
if y is None:
y = nx.floor(x)
else:
nx.floor(x, y)
if x.ndim == 0:
if (x<0):
y += 1
else:
y[x<0] = y[x<0]+1
return y
def isposinf(x, y=None):
"""
Return True where x is +infinity, and False otherwise.
Parameters
----------
x : array_like
The input array.
y : array_like
A boolean array with the same shape as `x` to store the result.
Returns
-------
y : ndarray
A boolean array where y[i] = True only if x[i] = +Inf.
See Also
--------
isneginf, isfinite
Examples
--------
>>> np.isposinf([-np.inf, 0., np.inf])
array([ False, False, True], dtype=bool)
"""
if y is None:
x = asarray(x)
y = empty(x.shape, dtype=nx.bool_)
umath.logical_and(isinf(x), ~signbit(x), y)
return y
def isneginf(x, y=None):
"""
Return True where x is -infinity, and False otherwise.
Parameters
----------
x : array_like
The input array.
y : array_like
A boolean array with the same shape as `x` to store the result.
Returns
-------
y : ndarray
A boolean array where y[i] = True only if x[i] = -Inf.
See Also
--------
isposinf, isfinite
Examples
--------
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False], dtype=bool)
"""
if y is None:
x = asarray(x)
y = empty(x.shape, dtype=nx.bool_)
umath.logical_and(isinf(x), signbit(x), y)
return y
_log2 = umath.log(2)
def log2(x, y=None):
"""
Return the base 2 logarithm.
Parameters
----------
x : array_like
Input array.
y : array_like
Optional output array with the same shape as `x`.
Returns
-------
y : {ndarray, scalar}
The logarithm to the base 2 of `x` elementwise.
NaNs are returned where `x` is negative.
See Also
--------
log, log1p, log10
Examples
--------
>>> np.log2([-1,2,4])
array([ NaN, 1., 2.])
"""
x = asanyarray(x)
if y is None:
y = umath.log(x)
else:
umath.log(x, y)
y /= _log2
return y
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