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radiosonde_auto_rx/auto_rx/utils/plot_sonde_log.py

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Python
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#!/usr/bin/env python
#
# Radiosonde Log Plotter
#
# Copyright (C) 2019 Mark Jessop <vk5qi@rfhead.net>
# Released under GNU GPL v3 or later
#
# Note: This script is very much a first pass, and doesn't have any error checking of data.
#
# Usage: plot_sonde_log.py [-h] [--metric] [--alt-limit ALT_LIMIT]
# [--temp-limit TEMP_LIMIT] [--decimation DECIMATION]
# filename
#
# positional arguments:
# filename Log File name.
#
# optional arguments:
# -h, --help show this help message and exit
# --metric Use metric altitudes. (Default is to use Feet)
# --alt-limit ALT_LIMIT
# Limit plot to supplied altitude (feet or metres,
# depending on user selection)
# --temp-limit TEMP_LIMIT
# Limit plot to a lower temperature in degrees. (Default
# is no limit, plot will autoscale)
# --decimation DECIMATION
# Decimate input data by X times. (Default = 10)
#
import argparse
import os.path
import sys
import numpy as np
import matplotlib.pyplot as plt
from dateutil.parser import parse
from math import radians, degrees, sin, cos, atan2, sqrt, pi
# Earthmaths code by Daniel Richman (thanks!)
# Copyright 2012 (C) Daniel Richman; GNU GPL 3
def position_info(listener, balloon):
"""
Calculate and return information from 2 (lat, lon, alt) tuples
Returns a dict with:
- angle at centre
- great circle distance
- distance in a straight line
- bearing (azimuth or initial course)
- elevation (altitude)
Input and output latitudes, longitudes, angles, bearings and elevations are
in degrees, and input altitudes and output distances are in meters.
"""
# Earth:
radius = 6371000.0
(lat1, lon1, alt1) = listener
(lat2, lon2, alt2) = balloon
lat1 = radians(lat1)
lat2 = radians(lat2)
lon1 = radians(lon1)
lon2 = radians(lon2)
# Calculate the bearing, the angle at the centre, and the great circle
# distance using Vincenty's_formulae with f = 0 (a sphere). See
# http://en.wikipedia.org/wiki/Great_circle_distance#Formulas and
# http://en.wikipedia.org/wiki/Great-circle_navigation and
# http://en.wikipedia.org/wiki/Vincenty%27s_formulae
d_lon = lon2 - lon1
sa = cos(lat2) * sin(d_lon)
sb = (cos(lat1) * sin(lat2)) - (sin(lat1) * cos(lat2) * cos(d_lon))
bearing = atan2(sa, sb)
aa = sqrt((sa ** 2) + (sb ** 2))
ab = (sin(lat1) * sin(lat2)) + (cos(lat1) * cos(lat2) * cos(d_lon))
angle_at_centre = atan2(aa, ab)
great_circle_distance = angle_at_centre * radius
# Armed with the angle at the centre, calculating the remaining items
# is a simple 2D triangley circley problem:
# Use the triangle with sides (r + alt1), (r + alt2), distance in a
# straight line. The angle between (r + alt1) and (r + alt2) is the
# angle at the centre. The angle between distance in a straight line and
# (r + alt1) is the elevation plus pi/2.
# Use sum of angle in a triangle to express the third angle in terms
# of the other two. Use sine rule on sides (r + alt1) and (r + alt2),
# expand with compound angle formulae and solve for tan elevation by
# dividing both sides by cos elevation
ta = radius + alt1
tb = radius + alt2
ea = (cos(angle_at_centre) * tb) - ta
eb = sin(angle_at_centre) * tb
elevation = atan2(ea, eb)
# Use cosine rule to find unknown side.
distance = sqrt((ta ** 2) + (tb ** 2) - 2 * tb * ta * cos(angle_at_centre))
# Give a bearing in range 0 <= b < 2pi
if bearing < 0:
bearing += 2 * pi
return {
"listener": listener, "balloon": balloon,
"listener_radians": (lat1, lon1, alt1),
"balloon_radians": (lat2, lon2, alt2),
"angle_at_centre": degrees(angle_at_centre),
"angle_at_centre_radians": angle_at_centre,
"bearing": degrees(bearing),
"bearing_radians": bearing,
"great_circle_distance": great_circle_distance,
"straight_distance": distance,
"elevation": degrees(elevation),
"elevation_radians": elevation
}
if __name__ == "__main__":
# Data format:
# 2019-04-17T00:40:40.000Z,P4740856,7611,-35.38981,139.47062,12908.1,-67.9,25.0,RS41,402.500,SATS 9,BATT -1.0
parser = argparse.ArgumentParser()
parser.add_argument("filename", type=str, help="Log File name.")
parser.add_argument("--metric", action="store_true", default=False, help="Use metric altitudes. (Default is to use Feet)")
parser.add_argument("--alt-limit", default=20000, type=int, help="Limit plot to supplied altitude (feet or metres, depending on user selection)")
parser.add_argument("--temp-limit", default=None, type=float, help="Limit plot to a lower temperature in degrees. (Default is no limit, plot will autoscale)")
parser.add_argument("--decimation", default=10, type=int, help="Decimate input data by X times. (Default = 10)")
args = parser.parse_args()
# Load in the file.
data = np.genfromtxt(args.filename,delimiter=',', dtype=None)
decimation = args.decimation
# Extract fields.
times = data['f0']
latitude = data['f3']
longitude = data['f4']
altitude = data['f5']
temperature = data['f6']
humidity = data['f7']
_output = [] # Altitude, Wind Speed, Wind Direction, Temperature, Dew Point
# First entry, We assume all the values are unknown for now.
_output.append([altitude[0], np.NaN, np.NaN, np.NaN, np.NaN])
i = decimation
while i < len(times):
# Check if we are descending. If so, break.
if altitude[i] < _output[-1][0]:
break
# If we have valid PTU data, calculate the dew point.
if temperature[i] != -273:
T = temperature[i]
RH = humidity[i]
DP = 243.04*(np.log(RH/100)+((17.625*T)/(243.04+T)))/(17.625-np.log(RH/100)-((17.625*T)/(243.04+T)))
else:
# Otherwise we insert NaNs, so data isn't plotted.
T = np.NaN
DP = np.NaN
# Calculate time delta between telemetry frames.
_time = parse(times[i])
_time_old = parse(times[i-decimation])
_delta_seconds = (_time - _time_old).total_seconds()
# Calculate the movement direction and distance, and then calculate the movement speed.
_movement = position_info((latitude[i], longitude[i], altitude[i]), (latitude[i-decimation], longitude[i-decimation], altitude[i-decimation]))
_heading = _movement['bearing']
_speed = (_movement['great_circle_distance']/_delta_seconds)*1.94384 # Convert to knots
_output.append([altitude[i], _speed, _heading, T, DP])
i += decimation
# Convert our output data into something we can process easier.
data_np = np.array(_output)
if args.metric:
_alt = data_np[:,0]
else:
_alt = data_np[:,0]*3.28084 # Convert to feet.
_speed = data_np[:,1]
_direction = data_np[:,2]/10.0
_temp = data_np[:,3]
_dp = data_np[:,4]
# Produce a boolean array to limit the plotted data.
_data_limit = _alt < args.alt_limit
# Plot the data...
plt.figure()
plt.plot(_speed[_data_limit], _alt[_data_limit], label='Speed (kt)', color='g')
plt.plot(_direction[_data_limit], _alt[_data_limit], label='Direction (deg/10)', color='m')
plt.plot(_temp[_data_limit], _alt[_data_limit], label='Temp (deg C)', color='b')
plt.plot(_dp[_data_limit], _alt[_data_limit], label='DP (deg C)', color='r')
if args.metric:
plt.ylabel("Altitude (metres)")
else:
plt.ylabel("Altitude (feet)")
# Determine and set plot axis limits
_axes = plt.gca()
# Y limit is either a default value, or a user specified altitude.
_axes.set_ylim(top=args.alt_limit, bottom=0)
# X limits are based on a combination of data.
# The upper limit is based on the maximum speed within our altitude window
if args.temp_limit == None:
_temp_in_range= _temp[_data_limit]
_dp_in_range= _dp[_data_limit]
_min_temp = np.min(_temp_in_range[~np.isnan(_temp_in_range)])
_min_dp = np.min(_dp_in_range[~np.isnan(_dp_in_range)])
_axes.set_xlim(left=min(_min_temp, _min_dp))
else:
_axes.set_xlim(left=args.temp_limit)
plt.title("Sounding File: %s" % os.path.basename(args.filename))
plt.grid(which='both')
plt.legend(loc='upper right')
plt.show()
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