Re: [matplotlib-devel] Histogram normalization and overflow bins

[Tomo L. <laz...@gm...>]

Sorry for the spam, but I just wanted to say that I now understand that I
should be using plt.xlim to zoom in on the x-axis rather than changing the
bins. When I zoom in with that, the bin height is indeed constant as
expected.

On Sat, Mar 7, 2015 at 8:00 PM, Tomo Lazovich <laz...@gm...> wrote:

> Thanks for the suggestion...I will see how numpy handles this.
>
> Sorry for not being clearer earlier. Tom is right that by "zooming" I
> meant changing the bins so that they covered a smaller range. Is there a
> better way of "zooming" in on an axis so that I don't have this issue?
>
> Thanks!
>
> Tomo
>
> On Sat, Mar 7, 2015 at 7:39 PM, Thomas Caswell <tca...@gm...> wrote:
>
>> Paul,
>>
>> Note that by zoom the op means they are changing the bins, not actual
>> zooming(by just changing the x axis).
>>
>> I was going to say we deal with normalization by delegating to numpy, but
>> we actually handle it internally (with a note that when we drop np 1.5 to
>> make numpy do it).
>> I think the best course of action here is to do that conversion and
>> forward this feature request to numpy (if it does not already do this).
>>
>> Tom
>>
>> On Sat, Mar 7, 2015, 18:29 Paul Hobson <pmh...@gm...> wrote:
>>
>>> IMO, this seems like a bug. I would expect bars to change height with
>>> zoom/limit levels.
>>> -p
>>>
>>> —
>>> Sent from Mailbox <https://www.dropbox.com/mailbox>
>>>
>>>
>>> On Sat, Mar 7, 2015 at 4:20 PM, Tomo Lazovich <laz...@gm...>
>>> wrote:
>>>
>>>> Hello matplotlib developers,
>>>>
>>>> I'm not sure if this is the right mailing list for this question, so
>>>> please re-direct me if it is not.
>>>>
>>>> I am wondering whether it is possible to have a histogram in pyplot
>>>> normalized to the total length of the list input, rather than just the bins
>>>> showing on the plot (i.e. include those entries in the "overflow" and
>>>> "underflow", off the right and left edges of the plot). As far as I can
>>>> tell, the normed option of pyplot.hist currently makes it so that the area
>>>> under the bins showing is 1. This can lead to a situation like the one
>>>> pasted below, where when I look at the whole histogram the bins have
>>>> certain values but when I try to zoom in to see one part of the plot better
>>>> those values change.
>>>>
>>>> I can think of two ways to solve this as of now:
>>>>
>>>> 1) Use the weights option to scale each entry by 1/len(input) rather
>>>> than using normed=True.
>>>> 2) Somehow add the contents of the overflow to the last bin of the
>>>> plot, which would keep the normalizations constant for earlier bins even if
>>>> you extend the axes.
>>>>
>>>> Is there a better way of doing this? If the option does not currently
>>>> exist, I am also happy to help implement it if the community would find it
>>>> desirable.
>>>>
>>>> Thanks for your help!
>>>>
>>>> Tomo Lazovich
>>>>
>>>> P.S. Here is a toy example of what I mean:
>>>>
>>>>  >> import numpy as np
>>>> >> import matplotlib.pyplot as plt
>>>> >> h1 = [0, 0, 0, 1, 1, 2, 3]
>>>> >> my_bins = np.linspace(-0.5, 4.5, 6)
>>>> >> plt.hist(h1, bins=my_bins, normed=True)
>>>> >> plt.show()
>>>>
>>>> gives
>>>>
>>>>  <image.png>
>>>>
>>>>
>>>> Now, if I change the range on the x axis that I would like plot:
>>>>
>>>>  >> my_bins2 = np.linspace(-0.5, 1.5, 3)
>>>> >> plt.hist(h1, bins=my_bins2, normed=True)
>>>> >> plt.show()
>>>>
>>>>  <image.png>
>>>>
>>>>
>>>> The y values have changed to 0.6 and 0.4 because the normalization does
>>>> not include the values that are cut off to the right of the plot.
>>>>
>>>
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>>
>