[Numpy-discussion] help creating a reversed cumulative histogram
Tim Michelsen
timmichelsen@gmx-topmail...
Wed Sep 2 18:15:28 CDT 2009
Hello fellow numy users,
I posted some questions on histograms recently [1, 2] but still couldn't
find a solution.
I am trying to create a inverse cumulative histogram [3] which shall
look like [4] but with the higher values at the left.
The classification shall follow this exemplary rule:
class 1: 0
all values > 0
class 2: 10
all values > 10
class 3: 15
all values > 15
class 4: 20
all values > 20
class 5: 25
all values > 25
[...]
I could get this easily in a spreadsheet by creating a matix with
conditional statements (if VALUES_COL > CLASS_BOUNDARY; VALUES_COL; '-').
With python (numpy or pylab) I was not successful. The plotted histogram
envelope turned out to be just the inverted curve as the one created
with the spreadsheet app.
I have briely visualised the issue here [5]. I hope that this makes it
more understandable.
Later I would like to sum and count all values in each bin as discussed
in [2].
May someone give me pointer or hint on how to improve my code below to
achive the desired histogram?
Thanks a lot in advance,
Timmie
[1]: http://www.nabble.com/np.hist-with-masked-values-to25243905.html
[2]:
http://www.nabble.com/histogram%3A-sum-up-values-in-each-bin-to25171265.html
[3]: http://en.wikipedia.org/wiki/Histogram#Cumulative_histogram
[4]: http://addictedtor.free.fr/graphiques/RGraphGallery.php?graph=126
[5]: http://www.scribd.com/doc/19371606/Distribution-Histogram
##### CODE #####
normed = False
values # loaded data as array
bins = 10
### sum
## taken from
##
http://www.nabble.com/Scipy-and-statistics%3A-probability-density-function-to24683007.html#a24683304
sums = np.histogram(values, weights=values,
normed=normed,
bins=bins)
ecdf_sums = np.hstack([0.0, sums[0].cumsum() ])
ecdf_inv_sums = ecdf_sums[::-1]
pylab.plot(sums[1], ecdf_inv_sums)
pylab.show()
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