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@danielballan
Last active August 29, 2015 14:03
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Parse Zetasizer data
"""
Copyright 2014 Dan Allan
Read the data from a Zetasizer output file and return the intensity as
as a function of frequency in a spreadsheet-like object (pandas DataFrame)
that can exported to any convenient format.
This is only lightly tested.
"""
import pandas as pd
def _columns_subset(df, pattern):
return df[df.columns[df.columns.to_series().str.contains(pattern)]]
def parse_freq(filename):
"""Parse frequency data file from Zetasizer.
Parameters
----------
filename : string
Returns
-------
intensities : DataFrame indexed by size in nm, with a column for each
measurement in the file
"""
df = pd.read_table(filename)
sizes = _columns_subset(df, 'Sizes')
intensities = _columns_subset(df, 'Intensities')
sizes.columns = sizes.columns.to_series().str.\
extract(r'Sizes\[(\d+)\].*').astype('int')
intensities.columns = intensities.columns.to_series().str.\
extract(r'Intensities\[(\d+)\].*').astype('int')
intensities = intensities.T
sizes = sizes.T[0] # Columns are redundant; just take the first one.
intensities.set_index(sizes, inplace=True)
return intensities
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