1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
|
import numpy as N
import unittest
from numpy.testing import NumpyTestCase, assert_array_almost_equal, assert_almost_equal, assert_equal
import warnings
def segment_axis(a, length, overlap=0, axis=None, end='cut', endvalue=0):
"""Generate a new array that chops the given array along the given axis into overlapping frames.
example:
>>> segment_axis(arange(10), 4, 2)
array([[0, 1, 2, 3],
[2, 3, 4, 5],
[4, 5, 6, 7],
[6, 7, 8, 9]])
arguments:
a The array to segment
length The length of each frame
overlap The number of array elements by which the frames should overlap
axis The axis to operate on; if None, act on the flattened array
end What to do with the last frame, if the array is not evenly
divisible into pieces. Options are:
'cut' Simply discard the extra values
'wrap' Copy values from the beginning of the array
'pad' Pad with a constant value
endvalue The value to use for end='pad'
The array is not copied unless necessary (either because it is
unevenly strided and being flattened or because end is set to
'pad' or 'wrap').
"""
if axis is None:
a = N.ravel(a) # may copy
axis = 0
l = a.shape[axis]
if overlap>=length:
raise ValueError, "frames cannot overlap by more than 100%"
if overlap<0 or length<=0:
raise ValueError, "overlap must be nonnegative and length must be positive"
if l<length or (l-length)%(length-overlap):
if l>length:
roundup = length + (1+(l-length)//(length-overlap))*(length-overlap)
rounddown = length + ((l-length)//(length-overlap))*(length-overlap)
else:
roundup = length
rounddown = 0
assert rounddown<l<roundup
assert roundup==rounddown+(length-overlap) or (roundup==length and rounddown==0)
a = a.swapaxes(-1,axis)
if end=='cut':
a = a[...,:rounddown]
elif end in ['pad','wrap']: # copying will be necessary
s = list(a.shape)
s[-1]=roundup
b = N.empty(s,dtype=a.dtype)
b[...,:l] = a
if end=='pad':
b[...,l:] = endvalue
elif end=='wrap':
b[...,l:] = a[...,:roundup-l]
a = b
a = a.swapaxes(-1,axis)
l = a.shape[axis]
if l==0:
raise ValueError, "Not enough data points to segment array in 'cut' mode; try 'pad' or 'wrap'"
assert l>=length
assert (l-length)%(length-overlap) == 0
n = 1+(l-length)//(length-overlap)
s = a.strides[axis]
newshape = a.shape[:axis]+(n,length)+a.shape[axis+1:]
newstrides = a.strides[:axis]+((length-overlap)*s,s) + a.strides[axis+1:]
try:
return N.ndarray.__new__(N.ndarray,strides=newstrides,shape=newshape,buffer=a,dtype=a.dtype)
except TypeError:
warnings.warn("Problem with ndarray creation forces copy.")
a = a.copy()
# Shape doesn't change but strides does
newstrides = a.strides[:axis]+((length-overlap)*s,s) + a.strides[axis+1:]
return N.ndarray.__new__(N.ndarray,strides=newstrides,shape=newshape,buffer=a,dtype=a.dtype)
|
