It looks like the only thing missing in your code was that (unlike the leading bins which are half-open) the last bin in the numpy histogram is closed (includes both endpoints), whereas all of your bins were half-open. (Source, see "Notes")
If a bin is defined by it's edges, binmin and binmax, a value x is assigned to that bin if:
For the first n-1 bins: binmin <= x < binmax
For the last bin: binmin <= x <= binmax
Similarly, np.arange()
also expects a half-open interval, so in the code that follows I used np.linspace()
.
Consider the following:
import numpy as np
def histogram_using_numpy(filename, bins=10):
datas = np.loadtxt(filename, delimiter=" ", usecols=(0,))
hist, bin_edges = np.histogram(datas, bins)
return hist, bin_edges
def histogram_using_list(filename, bins=10, take_col=0):
f = open(filename,"r")
data = []
for item in f.readlines():
data.append(float(item.split()[take_col]))
f.close()
mi,ma = min(data), max(data)
def get_count(lis,binmin,binmax,inclusive_endpoint=False):
count = 0
for item in lis:
if item >= binmin and item < binmax:
count += 1
elif inclusive_endpoint and item == binmax:
count += 1
return count
bin_edges = np.linspace(mi, ma, bins+1)
tot = []
binlims = zip(bin_edges[0:-1], bin_edges[1:])
for i,(binmin,binmax) in enumerate(binlims):
inclusive = (i == (len(binlims) - 1))
tot.append(get_count(data, binmin, binmax, inclusive))
return tot, bin_edges
nump_hist, nump_bin_edges = histogram_using_numpy("ex.txt", bins=15)
func_hist, func_bin_edges = histogram_using_list("ex.txt", bins=15)
print "Histogram:"
print " From numpy: %s" % list(nump_hist)
print " From my function %s" % list(func_hist)
print ""
print "Bin Edges:"
print " From numpy: %s" % nump_bin_edges
print " From my function %s" % func_bin_edges
Which, for bins=10, outputs:
Histogram:
From numpy: [10, 19, 20, 28, 15, 16, 14, 11, 5, 12]
From my function [10, 19, 20, 28, 15, 16, 14, 11, 5, 12]
Bin Edges:
From numpy: [ 4.3 4.66 5.02 5.38 5.74 6.1 6.46 6.82 7.18 7.54 7.9 ]
From my function [ 4.3 4.66 5.02 5.38 5.74 6.1 6.46 6.82 7.18 7.54 7.9 ]
And for bins=15, outputs:
Histogram:
From numpy: [7, 4, 18, 19, 5, 24, 8, 10, 13, 6, 13, 6, 5, 1, 11]
From my function [7, 4, 18, 19, 5, 24, 8, 10, 13, 6, 13, 6, 5, 1, 11]
Bin Edges:
From numpy: [ 4.3 4.54 4.78 5.02 5.26 5.5 5.74 5.98 6.22 6.46 6.7 6.94 7.18 7.42 7.66 7.9 ]
From my function [ 4.3 4.54 4.78 5.02 5.26 5.5 5.74 5.98 6.22 6.46 6.7 6.94 7.18 7.42 7.66 7.9 ]