def run_files(filelist):
fig_s = plt.figure('pos_deltas')
ax_pos = fig_s.add_subplot(111)
fig_s.suptitle('delta_lat_lon')
ax_pos.set(ylabel='dlat (deg)')
ax_pos.set(xlabel='dlon (deg)')
ax_pos.grid()
ax_pos.axis('equal')
ax_pos.set_ylim(-5e-5, 5e-5)
ax_pos.set_xlim(-5e-5, 5e-5)
fig_en = plt.figure('enu_scatter')
ax_en = fig_en.add_subplot(111)
fig_en.suptitle('enu_scatter')
ax_en.set(ylabel='dNorth (m)')
ax_en.set(xlabel='dEast (m)')
ax_en.grid()
ax_en.axis('equal')
ax_en.set_ylim(-10, 10)
ax_en.set_xlim(-10, 10)
fig_p = plt.figure('delta_pos_enu')
ax_e = fig_p.add_subplot(311)
fig_p.suptitle('delta_pos_enu')
ax_e.set(ylabel='dE (m)')
ax_e.set(xlabel='Time (s)')
ax_e.grid()
ax_e.set_ylim(-10, 10)
ax_n = fig_p.add_subplot(312)
ax_n.set(ylabel='dN (m)')
ax_n.set(xlabel='Time (s)')
ax_n.grid()
ax_n.set_ylim(-10, 10)
ax_u = fig_p.add_subplot(313)
ax_u.set(ylabel='dU (m)')
ax_u.set(xlabel='Time (s)')
ax_u.grid()
ax_u.set_ylim(-10, 10)
for f in filelist:
print('---- WORKING ' + f + ' ----')
fname = f.split('.')[0]
df = DataFile(f, data_dir='data/hw1/')
df.setup()
lat_mean = np.mean(df.file_df['latitude {deg}']) * u.degree
lon_mean = np.mean(df.file_df['longitude {deg}']) * u.degree
h_mean = np.mean(df.file_df['h_ellipsiod {m}']) * u.meter
sats_mean = np.mean(df.file_df['num_sats'])
dlats = df.file_df['latitude {deg}'] - lat_mean.value
dlons = df.file_df['longitude {deg}'] - lon_mean.value
dhs = df.file_df['h_ellipsiod {m}'] - h_mean.value
dhs_std = np.std(dhs)
lat_std = np.std(df.file_df['latitude {deg}'])
lon_std = np.std(df.file_df['longitude {deg}'])
CEP_latlon = 0.62 * lat_std + 0.56 * lon_std
res = ax_pos.scatter(dlons, dlats, s=10, label=fname)
color = res.get_facecolor()[0]
circle = plt.Circle((0, 0), CEP_latlon, fill=False, color=color)
ax_pos.add_artist(circle)
print('-- Means -- lat = {}, lon = {}, h_mean = {}, num_sats = {}'.
format(lat_mean, lon_mean, h_mean, sats_mean))
# compute ECEF position vector using mean LAT, LON, H
r_ecef_mean = wgs84.geodetic_point_in_ecef(lat_mean, lon_mean, h_mean)
rs_ecef = wgs84.geodetic_point_in_ecef_arr(
df.file_df['latitude {deg}'].to_numpy() * u.degree,
df.file_df['longitude {deg}'].to_numpy() * u.degree,
df.file_df['h_ellipsiod {m}'].to_numpy() * u.meter)
x_ecef_std = np.std(rs_ecef[:, 0])
y_ecef_std = np.std(rs_ecef[:, 1])
z_ecef_std = np.std(rs_ecef[:, 2])
SEP = 0.51 * (x_ecef_std + y_ecef_std + z_ecef_std)
print('-- SEP -- {} {}'.format(SEP, u.meter.to_string()))
print('-- dhs_std -- {} {}'.format(dhs_std, u.meter.to_string()))
print('-- CEP_latlon -- {} {}'.format(CEP_latlon,
u.degree.to_string()))
print('ECEF_from_MEAN_GEO = ', r_ecef_mean)
R_ecef_enu = wgs84.ecef_to_enu(lat_mean, lon_mean)
rs_enu = np.zeros((len(rs_ecef), 3))
for ii in range(len(rs_ecef)):
r_ecef = rs_ecef[ii, :]
r_ecef_row = r_ecef_mean.flatten()
dr_ecef = r_ecef - r_ecef_row.value
dr_enu = np.matmul(R_ecef_enu, dr_ecef)
rs_enu[ii, :] = dr_enu
ax_e.plot(df.time_s,
rs_enu[:, 0],
label='SEP={:.2f} {}'.format(SEP, u.meter.to_string()))
ax_n.plot(df.time_s, rs_enu[:, 1], label=f)
ax_u.plot(df.time_s, rs_enu[:, 2], label=fname)
ax_en.scatter(rs_enu[:, 0], rs_enu[:, 1], s=10, label=fname)
# newline
print("")
ax_pos.legend()
ax_e.legend()
ax_u.legend()
ax_en.legend()
