sparse.py
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00001 #!/usr/bin/python
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00034 
00035 ##\author Kevin Watts
00036 ##\brief Make CSV files smaller for use in spreadsheet software
00037 
00038 PKG = 'diagnostic_analysis'
00039 import roslib
00040 roslib.load_manifest(PKG)
00041 
00042 import csv, os, sys
00043 
00044 ##\brief Makes sparse CSV by skipping every nth value
00045 ##\param csv_file str : CSV filename
00046 ##\param skip int : Write every nth row to sparse CSV
00047 ##\return Path of output file
00048 def make_sparse_skip(csv_file, skip):
00049     output_file = csv_file[:-4] + '_sparse.csv'
00050 
00051     input_reader = csv.reader(open(csv_file, 'rb'))
00052 
00053     f = open(output_file, 'wb')
00054     output_writer = csv.writer(f)
00055 
00056     skip_count = skip
00057     for row in input_reader:
00058         if skip_count == skip:
00059             output_writer.writerow(row)
00060             skip_count = 0
00061             
00062         skip_count = skip_count + 1
00063 
00064     return output_file
00065 
00066 ##\brief Makes sparse CSV with the given number of rows
00067 ##\param csv_file str : CSV filename
00068 ##\param length int : Desired number of rows in CSV
00069 ##\return Path of output file
00070 def make_sparse_length(csv_file, length):
00071     output_file = csv_file[:-4] + '_sprs_len.csv'
00072 
00073     input_reader = csv.reader(open(csv_file, 'rb'))
00074 
00075     f = open(output_file, 'wb')
00076     output_writer = csv.writer(f)
00077 
00078     # Calculate skip count for file
00079     orig_len = len(open(csv_file, 'r').read().split('\n'))
00080     skip = max(int(orig_len / length), 1)
00081 
00082     skip_count = skip
00083     for row in input_reader:
00084         if skip_count >= skip:
00085             output_writer.writerow(row)
00086             skip_count = 0
00087             
00088         skip_count = skip_count + 1
00089 
00090     return output_file


diagnostic_analysis
Author(s): Kevin Watts, Brice Rebsamen , Eric Berger, Kevin Watts
autogenerated on Fri Aug 28 2015 10:30:05