

In [1]:

    
from __future__ import print_function
import pytest
import os, sys
import numpy as np

sys.path.insert(0, os.path.abspath('../../..'))
import hublib.rappture as rappture
from hublib import ureg, Q_

Histogram Example

This code loads in the output of a run from the Rappture zoo of examples.

https://nanohub.org/infrastructure/rappture/browser/trunk/examples/zoo/histogram



In [2]:

    
io = rappture.RapXML('hist_run.xml')



In [3]:

    
io









    Out[3]:




INPUTS
Path Label Description
input.integer(points) Number of points Determines the number of data points in 
OUTPUTS
Path Label Description
output.histogram(example) Single dataset This is an example of a single histogram
output.histogram(single) Single histogram This is an example of a single histogram
output.histogram(multi1.8) Factor a=1.8 This is an example of a multiple histogr
output.histogram(multi2) Factor a=2 This is an example of a multiple histogr
output.histogram(namevalue) Name value histogram This is an example of a name value histo
output.histogram(width) Variable-Width histogram This is an example of an  histogram



In [4]:

    
%matplotlib notebook
io['output.histogram(example)'].plot()

Here is what Rappture outputs:



In [5]:

    
io['output.histogram(example)'].xml()









    Out[5]:





<histogram id="example">
            <about>
                <label>Single dataset</label>
                <description>This is an example of a single histogram.</description>
            </about>
            <xaxis>
                <label>Time</label>
                <description>Time during the experiment.</description>
                <units>s</units>
                <marker>
                    <at>5</at>
                    <label>Look here</label>
                    <style>-foreground red -linewidth 2</style>
                </marker>
            </xaxis>
            <yaxis>
                <label>Voltage v(11)</label>
                <description>Output from the amplifier.</description>
                <units>V</units>
            </yaxis>
            <component>
                <xy>1 0.99
       2 0.34
       4 0.57
       6 0.22
       7 0.11</xy>
            </component>
        </histogram>



In [6]:

    
io['output.histogram(single)'].plot()

Here is Rappture's output for the same data:

Just like Curves, Histograms can have a group id, so they can be plotted together. Here they are seperated



In [7]:

    
import matplotlib.pyplot as plt
fig, axs = plt.subplots(1,2)
io['output.histogram(multi1.8)'].plot(single=True, ax=axs[0])
io['output.histogram(multi2)'].plot(single=True, ax=axs[1])

Plot them both together like this:



In [8]:

    
io['output.histogram(multi2)'].plot()

If you prefer them stacked...



In [9]:

    
io['output.histogram(multi2)'].plot(stacked=True)

Here is what Rappture does, which seems VERY wrong. It looks like a stacked barchart, but the heights do not add up. Its behavior for multiple histograms is actually not documented, so maybe it is a feature. This example is from the zoo examples.



In [10]:

    
io['output.histogram(namevalue)'].plot(horizontal=True)



In [11]:

    
io['output.histogram(width)'].plot()

Path	Label	Description
output.histogram(example)	Single dataset	This is an example of a single histogram
output.histogram(single)	Single histogram	This is an example of a single histogram
output.histogram(multi1.8)	Factor a=1.8	This is an example of a multiple histogr
output.histogram(multi2)	Factor a=2	This is an example of a multiple histogr
output.histogram(namevalue)	Name value histogram	This is an example of a name value histo
output.histogram(width)	Variable-Width histogram	This is an example of an histogram