Before some yells at me for using bad code for type conversion :),
here's a better code:

import numpy
sum = numpy.sum(inputs[0].RowData["bin_values"])
array = inputs[0].RowData["bin_values"].astype(numpy.float32)
array = 100.0*array/sum
output.RowData.append(array, "bin_values")
output.RowData.append(inputs[0].RowData["bin_extents"], "bin_extents")

On Mon, Jan 12, 2015 at 2:01 PM, Utkarsh Ayachit
<utkarsh.ayac...@kitware.com> wrote:
> You could do this using a Python Programmable Filter.
>
> Here's a script to use:
>
> import numpy
> sum = numpy.sum(inputs[0].RowData["bin_values"])
> array = 1.0 * inputs[0].RowData["bin_values"]
> array = 100.0*array/sum
> output.RowData.append(array, "bin_values")
> output.RowData.append(inputs[0].RowData["bin_extents"], "bin_extents")
>
> Attached is a state file.
>
> Utkarsh
>
> On Wed, Jan 7, 2015 at 1:03 PM, Ethan Hereth <e.a.her...@gmail.com> wrote:
>> Good afternoon and happy new year!
>>
>> I have a colleague who would like to be able to plot the relative frequency
>> of the histogram data instead of absolute bin count. I.e. instead of having
>> the left axis say there are 100 things in bin one, he'd like for it to say
>> that 5% of the things are in bin one.
>>
>> Is this possible?
>>
>> Thank you!
>>
>> --
>> Ethan Alan Hereth
>>
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