Added tool to calculate average from rtklib.pos

converters/rtklib2avg.py

+#!/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])