Added tool to calculate average from rtklib.pos

#!/usr/bin/env python

import sys

import os

import numpy as np

dir_path = os.path.dirname(os.path.realpath(__file__))

sys.path.append(os.path.join(dir_path, '..'))

def print_usage():

    print('Usage:')

    print('  python rtklib2matlab.py [rover.pos]')

    sys.exit(1)

def parseline(line, names):

    values = line.split()

    converters = [int] + [float]*4 + [int]*2 + [float]*8

    conv_vals = [c(v) for c, v in zip(converters, values) ]

    return dict(zip(names, conv_vals))

def fix_name(name):

    name = name.strip().lower()

    if '(' in name:

        name = name[:name.find('(')]

    name = name.replace('-', '_')

    return name

if __name__ == '__main__':

    import sys

    if len(sys.argv) < 2:

        print('No file specified.')

        print('')

        print_usage()

    if len(sys.argv) == 3:

        min_quality = int(sys.argv[2])

    else:

        min_quality = 1

    infile = sys.argv[1]

    print('Extracting average from %s with Q <= %d' % (infile, min_quality))

    names = ['week', 'tow', 'ecef_x', 'ecef_y', 'ecef_z', 'Q', 'ns', 'sdx', 'sdy',

     'sdz', 'sdxy', 'sdyz', 'sdzx', 'age', 'ratio']

    n_lines = 0

    with open(infile, 'rU') as f:

        for line in f:

            if line.startswith('%'):

                if 'ratio' in line:

                    names = [fix_name(name) for name in line[1:].split()]

                    if 'gpst' in names:

                        names.insert(0, 'week')

                continue

            n_lines += 1

        f.seek(0)

        arr = np.zeros((4, n_lines))

        arr_ix=0

        for line in f:

            if line.startswith('%'):

                continue

            data_line = parseline(line, names)

            for key, val in data_line.items():

                if key in ['x_ecef', 'lat']:

                    arr[0, arr_ix] = val

                elif key in ['y_ecef', 'lon']:

                    arr[1, arr_ix] = val

                elif key in ['z_ecef', 'alt']:

                    arr[2, arr_ix] = val

                elif key == 'q':

                    arr[3, arr_ix] = val

            arr_ix += 1

    print('')

    print('Found %d lines' % arr_ix)

    legal_arr = arr[:, arr[3,:] > 0]

    valid_arr = legal_arr[:, legal_arr[3,:] <= min_quality]

    print('Found %d quality points.' % valid_arr.shape[1])

    print('')

    print('Mean: %s' % np.mean(valid_arr, axis=1)[:3])