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numpy.matlib.asarray

All Samples(26)  |  Call(20)  |  Derive(0)  |  Import(6)

```    assert cols * rows == m.shape[0]
out = m.reshape(cols, rows).T
if intype == 'array': return asarray(out)
else: return out

```
```    return u[:, rk:]

from numpy.matlib import empty, zeros, eye, mat, asarray
from numpy.linalg import lstsq
def getOrthColumns(m):
```
```    Return type is as input type.
'''
if type(m) == type(asarray(m)):
m = mat(m)
output = 'array'
```
```    maxlag rows are deleted (the matrix is shortened)
'''
if type(m) == type(asarray(m)):
m = mat(m)
output = 'array'
```
```    for lag in range(1, maxlag + 1) :
temp = c_[ temp, m[(maxlag-lag):(T-lag) ,:] ]
if output == 'array': return asarray(temp)
else: return temp

```

```    assert cols * rows == m.shape[0]
out = m.reshape(cols, rows).T
if intype == 'array': return asarray(out)
else: return out

```
```    return u[:, rk:]

from numpy.matlib import empty, zeros, eye, mat, asarray
from numpy.linalg import lstsq
def getOrthColumns(m):
```
```    Return type is as input type.
'''
if type(m) == type(asarray(m)):
m = mat(m)
output = 'array'
```
```    maxlag rows are deleted (the matrix is shortened)
'''
if type(m) == type(asarray(m)):
m = mat(m)
output = 'array'
```
```    for lag in range(1, maxlag + 1) :
temp = c_[ temp, m[(maxlag-lag):(T-lag) ,:] ]
if output == 'array': return asarray(temp)
else: return temp

```