numpy array indexing with negative index

Question

First I have a scalar time series stored in a numpy array:

ts = np.arange(10)

which is

array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

Suppose I want to extract from ts a series of vectors (2,1,0), (3,2,1), (4,3,2), etc., I can think of the following code to do it:

for i in range(len(ts)-2):
    print(ts[2+i:i-1:-1])

However, when i=0, the above code returns an empty array rather than [2,1,0] because the loop body will become

print(ts[2:-1:-1])

where the -1 in the middle creates trouble.

My question is: is there a way to make the indexing work for [2,1,0]?

HYRY · Accepted Answer · 2015-09-16 03:21:13Z

3

You need use None:

ts = np.arange(10)

for i in range(len(ts)-2):
    print(ts[2+i:None if i == 0 else i - 1:-1])

answered Sep 16, 2015 at 3:21

HYRY

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3 Comments

wdg Over a year ago

Nice! didn't know I can put a if...else there

wdg Over a year ago

not directly related to the question, this does not work in Cython

MasterControlProgram Over a year ago

wdg, the if-else-construct is for using it inline

Julien · Accepted Answer · 2015-09-16 03:43:07Z

3

This should work too:

print(ts[i:i+3][::-1])

answered Sep 16, 2015 at 3:43

Julien

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Comments

Nader Hisham · Accepted Answer · 2015-09-16 07:34:48Z

0

another way is to do the following

slices = np.arange(3)

result = np.array([])
while slices[2] < len(ts):
    # print(ts[slices])
    result = np.r_[result , ts[slices]]
    slices += 1

result.reshape((-1 , 3))
Out[165]:
array([[ 0.,  1.,  2.],
       [ 1.,  2.,  3.],
       [ 2.,  3.,  4.],
       [ 3.,  4.,  5.],
       [ 4.,  5.,  6.],
       [ 5.,  6.,  7.],
       [ 6.,  7.,  8.],
       [ 7.,  8.,  9.]])

answered Sep 16, 2015 at 7:34

Nader Hisham

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