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