python - Splitting lists by short numbers -


i'm using numpy find intersections on graph, isclose returns multiple values per intersection

so, i'm going try find averages. first, want isolate similar values. useful skill feel.

i have list of x values intersection called idx looks 

[-8.67735471 -8.63727455 -8.59719439 -5.5511022  -5.51102204 -5.47094188  -5.43086172 -2.4248497  -2.38476954 -2.34468938 -2.30460922  0.74148297   0.78156313  0.82164329  3.86773547  3.90781563  3.94789579  3.98797595   7.03406814  7.0741483   7.11422846]

and want separate out lists each comprised of similar numbers.

this have far:

n = 0 in range(len(idx)):     try:         if (idx[n]-idx[n-1])<0.5:             sdx.append(idx[n-1])         else:             print(sdx)             sdx = []     except:         sdx.append(idx[n-1])     n = n+1

it works part forgets numbers:

[-8.6773547094188377, -8.6372745490981959] [-5.5511022044088181, -5.5110220440881763, -5.4709418837675354] [-2.4248496993987976, -2.3847695390781567, -2.3446893787575149] [0.7414829659318638, 0.78156312625250379] [3.8677354709418825, 3.9078156312625243, 3.9478957915831661]

theres more efficient way this, know of one?

considering have numpy array, can use np.split, splitting difference > .5:

import numpy np x = np.array([-8.67735471, -8.63727455, -8.59719439, -5.5511022, -5.51102204, -5.47094188,      -5.43086172, -2.4248497, -2.38476954, -2.34468938, -2.30460922, 0.74148297,      0.78156313, 0.82164329, 3.86773547, 3.90781563, 3.94789579, 3.98797595,      7.03406814, 7.0741483])   print np.split(x, np.where(np.diff(x) > .5)[0] + 1)  [array([-8.67735471, -8.63727455, -8.59719439]), array([-5.5511022 , -5.51102204, -5.47094188, -5.43086172]), array([-2.4248497 , -2.38476954, -2.34468938, -2.30460922]), array([ 0.74148297,  0.78156313,  0.82164329]), array([ 3.86773547,  3.90781563,  3.94789579,  3.98797595]), array([ 7.03406814,  7.0741483 ])]

np.where(np.diff(x) > .5)[0] returns index following element not meet np.diff(x) > .5) condition:

in [6]: np.where(np.diff(x) > .5)[0] out[6]: array([ 2,  6, 10, 13, 17])

+ 1 adds 1 each index:

in [12]: np.where(np.diff(x) > .5)[0] + 1 out[12]: array([ 3,  7, 11, 14, 18])

then passing [ 3, 7, 11, 14, 18] np.split splits elements subarrays, x[:3], x[3:7],x[7:11] ...


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