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# Functions that should behave the same as Numeric
import numpy as N
import numpy.core.multiarray as mu
import numpy.core.numeric as nn
from typeconv import convtypecode
__all__ = ['take', 'repeat', 'sum', 'product', 'sometrue', 'alltrue',
'cumsum', 'cumproduct']
__all__ += ['ones', 'empty', 'identity', 'zeros']
def take(a, indicies, axis=0):
return N.take(a, indicies, axis)
def repeat(a, repeats, axis=0):
return N.repeats(a, repeats, axis)
def sum(x, axis=0):
return N.sum(x, axis)
def product(x, axis=0):
return N.product(x, axis)
def sometrue(x, axis=0):
return N.sometrue(x, axis)
def alltrue(x, axis=0):
return N.alltrue(x, axis)
def cumsum(x, axis=0):
return N.cumsum(x, axis)
def cumproduct(x, axis=0):
return N.cumproduct(x, axis)
def ones(shape, typecode='l', savespace=0, dtype=None):
"""ones(shape, dtype=int) returns an array of the given
dimensions which is initialized to all ones.
"""
dtype = convtypecode(typecode,dtype)
a = mu.empty(shape, dtype)
a.fill(1)
return a
def zeros(shape, typecode='l', savespace=0, dtype=None):
"""zeros(shape, dtype=int) returns an array of the given
dimensions which is initialized to all zeros
"""
dtype = convtypecode(typecode,dtype)
return mu.zeros(shape, dtype)
def identity(n,typecode='l', dtype=None):
"""identity(n) returns the identity 2-d array of shape n x n.
"""
dtype = convtypecode(typecode, dtype)
return nn.identity(n, dtype)
def empty(shape, typecode='l', dtype=None):
dtype = convtypecode(typecode, dtype)
return mu.empty(shape, dtype, order)
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