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import numpy as np
from numpy.core.defmatrix import matrix, asmatrix
# need * as we're copying the numpy namespace
from numpy import *
__version__ = np.__version__
__all__ = np.__all__[:] # copy numpy namespace
__all__ += ['rand', 'randn', 'repmat']
def empty(shape, dtype=None, order='C'):
"""return an empty matrix of the given shape
"""
return ndarray.__new__(matrix, shape, dtype, order=order)
def ones(shape, dtype=None, order='C'):
"""return a matrix initialized to all ones
"""
a = ndarray.__new__(matrix, shape, dtype, order=order)
a.fill(1)
return a
def zeros(shape, dtype=None, order='C'):
"""return a matrix initialized to all zeros
"""
a = ndarray.__new__(matrix, shape, dtype, order=order)
a.fill(0)
return a
def identity(n,dtype=None):
"""identity(n) returns the identity matrix of shape n x n.
"""
a = array([1]+n*[0],dtype=dtype)
b = empty((n,n),dtype=dtype)
b.flat = a
return b
def eye(n,M=None, k=0, dtype=float):
return asmatrix(np.eye(n,M,k,dtype))
def rand(*args):
if isinstance(args[0], tuple):
args = args[0]
return asmatrix(np.random.rand(*args))
def randn(*args):
if isinstance(args[0], tuple):
args = args[0]
return asmatrix(np.random.randn(*args))
def repmat(a, m, n):
"""Repeat a 0-d to 2-d array mxn times
"""
a = asanyarray(a)
ndim = a.ndim
if ndim == 0:
origrows, origcols = (1,1)
elif ndim == 1:
origrows, origcols = (1, a.shape[0])
else:
origrows, origcols = a.shape
rows = origrows * m
cols = origcols * n
c = a.reshape(1,a.size).repeat(m, 0).reshape(rows, origcols).repeat(n,0)
return c.reshape(rows, cols)
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