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https://github.com/gnss-sdr/gnss-sdr
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Remove build and data folders, move tests and utils to the base of the source tree
This commit is contained in:
Carles Fernandez
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utils/python/lib/plotPosition.py
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208
utils/python/lib/plotPosition.py
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"""
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plotPosition.py
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plot_position(navSolutions)
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Graph Latitude-Longitude and X-Y-X as a function of Transmit Time
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Args:
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navSolutions - A dictionary with the processed information in lists
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plot_oneVStime(navSolutions, name)
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Graph of a variable as a function of transmission time
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Args:
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navSolutions - A dictionary with the processed information in lists
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name - navSolutions variable name that we want to plot
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calcularCEFP(percentil, navSolutions, m_lat, m_long)
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Calculate CEFP radio [m] for n percentil.
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Args:
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percentil - Number of measures that will be inside the circumference
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navSolutions - A dictionary with the processed information in lists
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m_lat - Mean latitude measures [º]
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m_long - Mean longitude measures [º]
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Modifiable in the file:
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fig_path - Path where plots will be save
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fig_path_maps - Path where the maps will be save
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filename_map - Path where map will be save
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filename_map_t - Path where terrain map will be save
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Irene Pérez Riega, 2023. iperrie@inta.es
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-----------------------------------------------------------------------------
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GNSS-SDR is a Global Navigation Satellite System software-defined receiver.
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This file is part of GNSS-SDR.
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Copyright (C) 2022 (see AUTHORS file for a list of contributors)
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SPDX-License-Identifier: GPL-3.0-or-later
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-----------------------------------------------------------------------------
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"""
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import math
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import os.path
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import webbrowser
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import numpy as np
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import matplotlib.pyplot as plt
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import folium
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def plot_position(navSolutions):
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# ---------- CHANGE HERE:
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fig_path = '/home/labnav/Desktop/TEST_IRENE/PLOTS/PlotPosition/'
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fig_path_maps = fig_path + 'maps/'
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filename_map = 'mapPlotPosition.html'
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filename_map_t = 'mapTerrainPotPosition.html'
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if not os.path.exists(fig_path_maps):
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os.mkdir(fig_path_maps)
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# Statics Positions:
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m_lat = sum(navSolutions['latitude']) / len(navSolutions['latitude'])
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m_long = sum(navSolutions['longitude']) / len(navSolutions['longitude'])
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# CEFP_n -> Include the n% of the dots in the circle
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r_CEFP_95 = calcularCEFP(95, navSolutions, m_lat, m_long)
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r_CEFP_50 = calcularCEFP(50, navSolutions, m_lat, m_long)
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# Generate and save html with the positions
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m = folium.Map(location=[navSolutions['latitude'][0],
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navSolutions['longitude'][0]], zoom_start=100)
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c_CEFP95 = folium.Circle(location=[m_lat, m_long],
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radius=r_CEFP_95, color='green', fill=True,
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fill_color='green', fill_opacity=0.5)
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c_CEFP50 = folium.Circle(location=[m_lat, m_long], radius=r_CEFP_50,
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color='red', fill=True, fill_color='red',
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fill_opacity=0.5)
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# POP-UPs
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popup95 = folium.Popup("(Green)CEFP95 diameter: {} "
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"metres".format(2 * r_CEFP_95))
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popup95.add_to(c_CEFP95)
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popup50 = folium.Popup("(Red)CEFP50 diameter: {} "
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"metres".format(2 * r_CEFP_50))
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popup50.add_to(c_CEFP50)
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c_CEFP95.add_to(m)
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c_CEFP50.add_to(m)
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# Optional: Plot each point ->
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"""
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for i in range(len(navSolutions['latitude'])):
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folium.Marker(location=[navSolutions['latitude'][i],
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navSolutions['longitude'][i]],
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icon=folium.Icon(color='red')).add_to(m)
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"""
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m.save(fig_path_maps + filename_map)
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webbrowser.open(fig_path_maps + filename_map)
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# Optional: with terrain ->
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"""
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n = folium.Map(location=[navSolutions['latitude'][0],
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navSolutions['longitude'][0]], zoom_start=100,
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tiles='Stamen Terrain')
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c_CEFP95.add_to(n)
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c_CEFP50.add_to(n)
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n.save(fig_path_maps + filename_map_t)
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webbrowser.open(fig_path_maps + filename_map_t)
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"""
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# Plot ->
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time = []
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for i in range(len(navSolutions['TransmitTime'])):
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time.append(round(navSolutions['TransmitTime'][i] -
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min(navSolutions['TransmitTime']), 3))
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plt.figure(figsize=(1920 / 120, 1080 / 120))
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plt.clf()
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plt.suptitle(f'Plot file PVT process data results')
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# Latitude and Longitude
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plt.subplot(1, 2, 1)
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scatter = plt.scatter(navSolutions['latitude'], navSolutions['longitude'],
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c=time, marker='.')
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plt.grid()
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plt.ticklabel_format(style='plain', axis='both', useOffset=False)
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plt.title('Positions latitud-longitud')
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plt.xlabel('Latitude º')
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plt.ylabel('Longitude º')
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plt.axis('tight')
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# Colors
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cmap = plt.get_cmap('viridis')
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norm = plt.Normalize(vmin=min(time), vmax=max(time))
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scatter.set_cmap(cmap)
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scatter.set_norm(norm)
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colors = plt.colorbar(scatter)
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colors.set_label('TransmitTime [s]')
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# X, Y, Z
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ax = plt.subplot(1, 2, 2, projection='3d')
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plt.ticklabel_format(style='plain', axis='both', useOffset=False)
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ax.scatter(navSolutions['X'], navSolutions['Y'], navSolutions['Z'],
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c=time, marker='.')
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ax.set_xlabel('Eje X [m]')
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ax.set_ylabel('Eje Y [m]')
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ax.set_zlabel('Eje Z [m]')
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ax.set_title('Positions x-y-z')
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plt.tight_layout()
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plt.savefig(os.path.join(fig_path, f'PVT_ProcessDataResults.png'))
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plt.show()
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def plot_oneVStime(navSolutions, name):
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# ---------- CHANGE HERE:
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fig_path = '/home/labnav/Desktop/TEST_IRENE/PLOTS/PlotPosition/'
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if not os.path.exists(fig_path):
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os.mkdir(fig_path)
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time = []
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for i in range(len(navSolutions['TransmitTime'])):
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time.append(round(navSolutions['TransmitTime'][i] -
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min(navSolutions['TransmitTime']), 3))
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plt.clf()
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plt.scatter(time, navSolutions[name], marker='.')
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plt.grid()
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plt.title(f'{name} vs Time')
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plt.xlabel('Time [s]')
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plt.ylabel(name)
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plt.axis('tight')
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plt.ticklabel_format(style='plain', axis='both', useOffset=False)
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plt.tight_layout()
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plt.savefig(os.path.join(fig_path, f'{name}VSTime.png'))
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plt.show()
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def calcularCEFP(percentil, navSolutions, m_lat, m_long):
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r_earth = 6371000
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lat = []
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long = []
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dlat = []
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dlong = []
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dist = []
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m_lat = math.radians(m_lat)
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m_long = math.radians(m_long)
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for i in range(len(navSolutions['latitude'])):
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lat.append(math.radians(navSolutions['latitude'][i]))
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long.append(math.radians(navSolutions['longitude'][i]))
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for i in range(len(lat)):
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dlat.append(m_lat - lat[i])
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dlong.append(m_long - long[i])
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# Haversine:
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a = (math.sin(dlat[i] / 2) ** 2 +
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math.cos(lat[i]) * math.cos(m_lat) * math.sin(dlong[i] / 2) ** 2)
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c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
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dist.append(r_earth * c)
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# Radio CEFP
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radio_CEFP_p = np.percentile(dist, percentil)
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return radio_CEFP_p
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