Parse Zetasizer data

gistfile1.py

"""
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