import matplotlib
# Allow running headless from the command line
matplotlib.use("agg")
import os
import datetime
import argparse
import sys;
import json;
from pylab import *
import numpy as np
plotSymb = [ "bo", "ro", "co", "go", "ko", "yo", "mo",
"b*", "r*", "c*", "g*", "k*", "y*", "m*"]
# Load the JSON file
with open('receivers.json', 'r') as f:
receivers = json.load(f)
MaxRX = len(receivers['receivers'])
# Cols
# 0 - Year
# 1 - Month
# 2 - Day
# 3 - Len
#
# 4 - mean(E)
# 5 - sig(E)
# 6 - 68% E
# 7 - 95% E
# 8 - 99% E
# 9 - 100% E
#
# 10 - 15 - repeat for N
# 16 - 21 - repeat for U
#
# 22 - 68% 2D
# 23 - 95% 2D
# 24 - 99% 2D
# 25 - 100% 2D
# 2D velocity error
summaryFig = figure()
summaryAx = summaryFig.add_subplot(111)
for j in range(MaxRX):
RXDir = receivers['receivers'][j]['RXDir']
RXStr = receivers['receivers'][j]['RXStr']
filename = RXStr + "/VelocityStats.txt"
if(os.path.isfile(filename)):
#print(filename)
vel = np.loadtxt(RXStr + "/VelocityStats.txt")
#DOY = [print(*x.astype(int)) for x in vel[:,0:3]]
#DOY = np.array([datetime.datetime(*x.astype(int)).timetuple().tm_yday for x in vel[:,0:3]])
DOY = np.array([(datetime.date(*x.astype(int)) - datetime.date(2018,1,1)).days for x in vel[:,0:3]])
# Generate an HTML table of historical results
fid = open(RXStr + '/summary.html' ,'w')
fid.write("")
fid.write("68% Trend")
fid.write("
")
fid.write("95% Trend")
fid.write("\n")
fid.write( ""
+ "| Date | 2D | ENU | "
+ "DOY | "
+ "2D | ENU | "
+ "
"
+ "| 68% | 95% | 100% | "
+ "E μ | N μ | U μ | "
+ "E σ | N σ | U σ | "
+ "E 68% | N 68% | U 68% | "
+ "E 95% | N 95% | U 95% | "
+ "E 100% | N 100% | U 100% | "
+ "
\n")
for i in range(len(DOY)):
fid.write("| %4d-%02d-%02d | " %
( int(vel[i,0]), int(vel[i,1]), int(vel[i,2])))
fid.write("2D | " %
( int(vel[i,0]), int(vel[i,1]), int(vel[i,2])))
fid.write("ENU | " %
( int(vel[i,0]), int(vel[i,1]), int(vel[i,2])))
fid.write("%d | " % (DOY[i]))
fid.write("%.3f | " % (vel[i,22]))
fid.write("%.3f | " % (vel[i,23]))
fid.write("%.3f | " % (vel[i,25]))
fid.write("%.3f | " % (vel[i,4]))
fid.write("%.3f | " % (vel[i,10]))
fid.write("%.3f | " % (vel[i,16]))
fid.write("%.3f | " % (vel[i,5]))
fid.write("%.3f | " % (vel[i,11]))
fid.write("%.3f | " % (vel[i,17]))
fid.write("%.3f | " % (vel[i,6]))
fid.write("%.3f | " % (vel[i,12]))
fid.write("%.3f | " % (vel[i,18]))
fid.write("%.3f | " % (vel[i,7]))
fid.write("%.3f | " % (vel[i,13]))
fid.write("%.3f | " % (vel[i,19]))
fid.write("%.3f | " % (vel[i,9]))
fid.write("%.3f | " % (vel[i,15]))
fid.write("%.3f | " % (vel[i,21]))
fid.write("
\n")
fid.write( ""
+ "| Date | 2D | ENU | "
+ "DOY | "
+ "68% | 95% | 100% | "
+ "E μ | N μ | U μ | "
+ "E σ | N σ | U σ | "
+ "E 68% | N 68% | U 68% | "
+ "E 95% | N 95% | U 95% | "
+ "E 100% | N 100% | U 100% | "
+ "
"
+ "| 2D | ENU | "
+ "
\n")
fid.write("
\n")
fid.close()
North68 = vel[:,6]
East68 = vel[:,12]
Up68 = vel[:,18]
North95 = vel[:,7]
East95 = vel[:,13]
Up95 = vel[:,19]
twoD68 = vel[:,22]
twoD95 = vel[:,23]
fig = figure()
plot( DOY, East95, label='E 95%')
plot( DOY, North95, label='N 95%')
plot( DOY, Up95, label='U 95%')
plot( DOY, twoD95, label='2D 95%')
ylabel('Velocity [m/s]')
grid()
legend()
xlabel('Time [Day of Year]')
title('Velocity 95% Error')
tight_layout()
show()
# Save the data as a PNG file
savefig(RXStr + "/velocityTrend.png",dpi=150)
close()
fig = figure()
plot( DOY, East68, label='East 68%')
plot( DOY, North68, label='North 68%')
plot( DOY, Up68, label='Up 68%')
plot( DOY, twoD68, label='2D 95%')
ylabel('Velocity [m/s]')
grid()
legend()
xlabel('Time [Day of Year]')
title('Velocity 68% Error')
tight_layout()
show()
# Save the data as a PNG file
savefig(RXStr + "/velocityTrend-68.png",dpi=150)
close()
figure(summaryFig.number)
plot( DOY, twoD95,plotSymb[j],label=RXStr)
# Now save the plot with all data plotted together
ylabel('Velocity [m/s]')
grid()
legend()
xlabel('Time [Day of Year]')
title('2D Velocity 95% Error')
show()
tight_layout()
savefig("velocityTrendSummary.png",dpi=150)
close()
