time_diffs = numpy.ma.array(time_diffs, mask = mask).compressed()
clock_drifts_deriv = differences / time_diffs
logging.info("Plotting")
error_histogram = plt.figure().add_subplot(1, 1, 1)
mu, sigma, outliers = matplotlib_settings.plot_hist(error_histogram,
all_errors,
arguments.outlier_threshold)
print("Mean: {}".format(mu))
print("Sigma: {}".format(sigma))
print("Outlier probability: {}".format(outliers))
error_histogram.set_title('Measurement errors')
error_histogram.set_xlabel(r'Error/\si{\meter}')
error_histogram.set_ylabel(r'Count')
matplotlib_settings.maybe_save_plot(error_histogram,
arguments.save_pseudorange_histogram)
fig2 = plt.figure()
velocity_error_histogram = fig2.add_subplot(1, 1, 1)
mu, sigma, outliers = matplotlib_settings.plot_hist(velocity_error_histogram,
all_velocity_errors,
arguments.velocity_outlier_threshold)
print("Velocity mean: {}".format(mu))
print("Velocity sigma: {}".format(sigma))
print("Outlier probability: {}".format(outliers))
velocity_error_histogram.set_title('Velocity errors')
velocity_error_histogram.set_xlabel(r'Error/\si{\meter\per\second}')
velocity_error_histogram.set_ylabel(r'Count')
matplotlib_settings.maybe_save_plot(velocity_error_histogram,
arguments.save_velocity_histogram)
logging.info("Plotting")
error_plot = plt.figure().add_subplot(1, 1, 1)
error_plot.scatter(
times[:: arguments.plot_thinning],
errors[:: arguments.plot_thinning],
marker=".",
s=40,
alpha=0.7,
edgecolors="none",
rasterized=True,
)
error_plot.set_title("Measurement errors for SV {}".format(sv_id))
error_plot.set_xlabel(r"Time/\si{\second}")
error_plot.set_ylabel(r"Error/\si{\meter}")
matplotlib_settings.maybe_save_plot(error_plot, arguments.save_pseudorange_errors)
error_histogram = plt.figure().add_subplot(1, 1, 1)
mu, sigma, offsets = matplotlib_settings.plot_hist(error_histogram, errors, arguments.outlier_threshold)
print("Mean: {}".format(mu))
print("Sigma: {}".format(sigma))
error_histogram.set_title("Measurement errors for SV {}".format(sv_id))
error_histogram.set_xlabel(r"Error/\si{\meter}")
error_histogram.set_ylabel(r"Count")
drifts_plot = plt.figure().add_subplot(1, 1, 1)
drifts_plot.plot(times[:: arguments.plot_thinning], clock_drifts[:: arguments.plot_thinning], "-", alpha=0.7)
drifts_plot.set_title("Receiver clock drifts for SV {}".format(sv_id))
drifts_plot.set_xlabel(r"Time/\si{\second}")
drifts_plot.set_ylabel(r"Drift/\si{\meter\per\second}")
matplotlib_settings.common_plot_settings(drifts_plot, set_limits=False)
errors = data['errors'][::arguments.plot_thinning]
clock_offsets = data['clock_offsets'][::arguments.plot_thinning]
clock_drifts = data['clock_drifts'][::arguments.plot_thinning]
errors -= clock_offsets
velocity_errors = data['velocity_errors'][::arguments.plot_thinning]
velocity_errors -= clock_drifts
logging.info("Plotting")
error_plot = plt.figure().add_subplot(1, 1, 1)
error_plot.scatter(times, errors, c=sv_ids, marker='.', s=40, alpha=0.7,
edgecolors='none', rasterized=True)
error_plot.set_title('Measurement errors')
error_plot.set_xlabel(r'Time/\si{\second}')
error_plot.set_ylabel(r'Error/\si{\meter}')
matplotlib_settings.maybe_save_plot(error_plot, arguments.save_pseudorange_errors)
error_histogram = plt.figure().add_subplot(1, 1, 1)
mu, sigma, outliers = matplotlib_settings.plot_hist(error_histogram,
errors,
arguments.outlier_threshold)
print("Mean: {}".format(mu))
print("Sigma: {}".format(sigma))
error_histogram.set_title('Measurement errors')
error_histogram.set_xlabel(r'Error/\si{\meter}')
error_histogram.set_ylabel(r'Count')
matplotlib_settings.maybe_save_plot(error_histogram, arguments.save_pseudorange_histogram)
drifts_plot = plt.figure().add_subplot(1, 1, 1)
drifts_plot.plot(times, clock_drifts,
'-', alpha=0.7)
logging.basicConfig(
format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s",
level = logging.INFO
)
arg_parser = argparse.ArgumentParser(
description="Plot clock offsets from the preprocessed data.")
arg_parser.add_argument('fixes', help="Data obtained from clock_offsets_to_numpy.py")
arg_parser.add_argument('--no-show', action='store_true',
help="Don't show the plots, only save them.")
arg_parser.add_argument('--save-plot', default=None,
help="Filename, optionally followed by comma separated (x0, y0, x1, y1) coordinates.")
arguments = arg_parser.parse_args()
logging.info("Retreiving fixes")
data = numpy.load(arguments.fixes)
logging.info("Plotting")
plot = plt.figure().add_subplot(1, 1, 1)
plot.plot(data['times'], data['clock_offsets'] / gps.measurement_error.C, alpha=0.7, rasterized=True)
plot.set_title('Clock offsets')
plot.set_xlabel(r'Time/\si{\second}')
plot.set_ylabel(r'Clock offset/\si{\second}')
matplotlib_settings.maybe_save_plot(plot, arguments.save_plot)
if not arguments.no_show:
plt.show()
