[NumPy-Tickets] [NumPy] #1864: arange using float for step and integer dtype results in an array with all values being the same

[NumPy Trac]

#1864: arange using float for step and integer dtype results in an array with all
values being the same
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 Reporter:  bsouthey    |       Owner:  somebody   
     Type:  defect      |      Status:  new        
 Priority:  normal      |   Milestone:  Unscheduled
Component:  numpy.core  |     Version:  devel      
 Keywords:              |  
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Comment(by bsouthey):

 Replying to [comment:1 derek]:
 > Actually it seems to construct something like np.arange(int(start),
 int(stop), int(step)), although the length remains the same as for the
 float array - compare
 > {{{
 > >>>np.arange(0,5,1.5, dtype=int)
 > array([0, 1, 2, 3])
 > }}}

 Actually that is not the expected output either because it is dropping the
 last element(s) as seen when ignoring the 'dtype' (with numpy 1.6.1rc1):
 {{{
 >>> np.arange(0,5,1.5)
 array([ 0. ,  1.5,  3. ,  4.5])
 >>> np.arange(0,5,1.5).astype(int)
 array([0, 1, 3, 4])
 >>> np.arange(0,20,1.5, dtype=int)
 array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13])
 }}}

 Initially I thought that np.arange(start, stop, step, dtype=int) should be
 the same as np.arange(start, stop, step).astype(int). But really it should
 infer the correct output dtype from all of the inputs and let the user
 recast the dtype as needed.

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/1864#comment:2>
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