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I'm working on a code that takes a list of points from a text file and an input m, to create a frequency distribution of points where m is the number of bins.

discret =  open('testingdisc.txt','w+')
x = []
y = []

m = int(input("Input number of bins:"))

for line in open('xypoints.txt','r'):
    lines = line.split(",")
    x.append(float(lines[0]))
    y.append(float(lines[1]))

H = np.histogram2d(x, y, bins= m)

list = re.sub('( \[|\[|\])', '', str(H[0].astype(int)))

print(list , file = discret)

The code gives me the output I'm looking for when m < 30:

1 0 0 1 0 0 0 0 0 1
0 1 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
1 0 0 1 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
1 0 1 0 0 0 0 0 0 0
0 0 0 1 0 0 0 0 0 0

However, the number of bins that I'm after is going to be more than 40 which gives me the following output:

1 0 0 ... 0 0 1
0 0 0 ... 0 0 0
0 0 0 ... 0 0 0
 ...
0 0 0 ... 0 0 0
0 0 0 ... 0 0 0
0 0 0 ... 0 0 0

Is there a limit to the number of bins that could be used?

Tuna
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1 Answers1

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Python's default is not print all entries when you try to print out a very large array. The main reason behind it is probably that it helps no one when you accidentally out an array with millions of entries. You change that behaviour by changing the print options:

import sys
import numpy
numpy.set_printoptions(threshold=sys.maxsize)
partypeter
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