I have been trying to create a normed histogram using either SciPy or matplotlib (or anything for Python). When I create my histogram with 'normed' option disabled, it looks like below (this example is for 10 bins, but the same happens for a larger number of bins): (The first number represents the start of a bin, the second the bin's height)
-2.83785600931e-17 1182
5.6688145554e-15 1137
1.13660076709e-14 1031
1.70632007864e-14 950
2.27603939019e-14 912
2.84575870174e-14 802
3.41547801329e-14 853
3.98519732484e-14 948
4.55491663639e-14 1315
5.12463594794e-14 870
Which is absolutely fine, and what I was expecting. However, I later need to fit this histogram to another histogram, and for that I prefer to have a normed version of this histogram so that fitting the height of those histograms is easier.
Strangely, when I use the option density=True
(for scipy.histogram
version) or normed=True
(for matplotlib.pyplot.plt
version) my histogram bin heights get very large values, like below:
-1.44880082614e-17 2.00318764844e+13
5.71138595513e-15 1.98921598219e+13
1.14372599185e-14 1.8040914044e+13
1.71631338819e-14 1.52465807942e+13
2.28890078453e-14 1.56133370332e+13
2.86148818087e-14 1.4617855813e+13
3.43407557721e-14 1.50020766348e+13
4.00666297355e-14 1.74296536456e+13
4.57925036989e-14 2.3769297206e+13
5.15183776622e-14 1.50020766348e+13
I hardly know anything about statistics, but I expected "normed" to mean "sums up to one". Am I incorrect in my thinking, or is the output normalized histogram wrong after all?