sparse.py

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#!/usr/bin/python3
#
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PKG = 'diagnostic_analysis'
import roslib
roslib.load_manifest(PKG)
 
import csv, os, sys
 
 
def make_sparse_skip(csv_file, skip):
    output_file = csv_file[:-4] + '_sparse.csv'
 
    input_reader = csv.reader(open(csv_file, newline=''), delimiter=',')
 
    f = open(output_file, 'w')
    output_writer = csv.writer(f)
 
    skip_count = skip
    for row in input_reader:
        if skip_count == skip:
            output_writer.writerow(row)
            skip_count = 0
            
        skip_count = skip_count + 1
 
    return output_file
 
 
def make_sparse_length(csv_file, length):
    output_file = csv_file[:-4] + '_sprs_len.csv'
 
    input_reader = csv.reader(open(csv_file, newline=''), delimiter=',')
 
    f = open(output_file, 'w')
    output_writer = csv.writer(f)
 
    # Calculate skip count for file
    orig_len = len(open(csv_file, 'r').read().split('\n'))
    skip = max(int(orig_len / length), 1)
 
    skip_count = skip
    for row in input_reader:
        if skip_count >= skip:
            output_writer.writerow(row)
            skip_count = 0
            
        skip_count = skip_count + 1
 
    return output_file