Is there a numpy function that allows you to specify start, step, and number?

Question

We're all familiar with np.linspace, which creates an array given a start, stop, and num of elements:

In [1]: import numpy as np  In [2]: np.linspace(0, 10, 9) Out[2]: array([  0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ]) 

Likewise, who could ever forget np.arange, which creates an array given a start, stop, and step:

In [4]: np.arange(0, 10, 1.25) Out[4]: array([ 0.  ,  1.25,  2.5 ,  3.75,  5.  ,  6.25,  7.5 ,  8.75]) 

But is there a function that allows you to specify a start, step, and num of elements, while omitting the stop? There should be.

Answer 1

Thanks for that question. I had the same issue. The (from my perspective) shortest and most elegant way is:

import numpy as np start=0 step=1.25 num=9  result=np.arange(0,num)*step+start  print(result) 

returns

[  0.     1.25   2.5    3.75   5.     6.25   7.5    8.75  10.  ] 

Answer 2

A deleted answer pointed out that linspace takes an endpoint parameter.

With that, 2 examples given in other answers can be written as:

In [955]: np.linspace(0, 0+(0.1*3),3,endpoint=False) Out[955]: array([ 0. ,  0.1,  0.2])  In [956]: np.linspace(0, 0+(5*3),3,endpoint=False) Out[956]: array([  0.,   5.,  10.])  In [957]: np.linspace(0, 0+(1.25*9),9,endpoint=False) Out[957]: array([  0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ]) 

Look at the functions defined in numpy.lib.index_tricks for other ideas on how to generate ranges and/or grids. For example, np.ogrid[0:10:9j] behaves like linspace.

def altspace(start, step, count, endpoint=False, **kwargs):    stop = start+(step*count)    return np.linspace(start, stop, count, endpoint=endpoint, **kwargs)