def center_matrix(M, dim=0):
"""
Return the matrix M with each row having zero mean and unit std
if dim=1, center columns rather than rows
"""
# todo: implement this w/o loop. Allow optional arg to specify
# dimension to remove the mean from
if dim==1: M = transpose(M)
M = array(M, Float)
if len(M.shape)==1 or M.shape[0]==1 or M.shape[1]==1:
M = M-mean(M)
sigma = std(M)
if sigma>0:
M = divide(M, sigma)
if dim==1: M=transpose(M)
return M
for i in range(M.shape[0]):
M[i] -= mean(M[i])
sigma = std(M[i])
if sigma>0:
M[i] = divide(M[i], sigma)
if dim==1: M=transpose(M)
return M
def center_matrix(M, dim=0):
"""
Return the matrix M with each row having zero mean and unit std
if dim=1, center columns rather than rows
"""
# todo: implement this w/o loop. Allow optional arg to specify
# dimension to remove the mean from
if dim == 1: M = transpose(M)
M = array(M, Float)
if len(M.shape) == 1 or M.shape[0] == 1 or M.shape[1] == 1:
M = M - mean(M)
sigma = std(M)
if sigma > 0:
M = divide(M, sigma)
if dim == 1: M = transpose(M)
return M
for i in range(M.shape[0]):
M[i] -= mean(M[i])
sigma = std(M[i])
if sigma > 0:
M[i] = divide(M[i], sigma)
if dim == 1: M = transpose(M)
return M