Add calibrate.py for astrometric solving
Pierros Papadeas
parent
c8d8256d2a
commit
550399a360
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@ -205,7 +205,6 @@ if __name__ == '__main__':
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logging.basicConfig(filename=os.path.join(path, "acquire.log"),
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level=logging.DEBUG)
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# Set location
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loc = EarthLocation(lat=cfg.getfloat('Common', 'observer_lat')*u.deg,
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lon=cfg.getfloat('Common', 'observer_lon')*u.deg,
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@ -218,7 +217,7 @@ if __name__ == '__main__':
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# Get sunrise and sunset times
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state, tset, trise = get_sunset_and_sunrise(tnow, loc, refalt_set, refalt_rise)
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# Start/end logic
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if state == "sun never rises":
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logging.info("The sun never rises. Exiting program.")
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@ -0,0 +1,51 @@
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#!/usr/bin/env python
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from __future__ import print_function
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import os
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import configparser
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import argparse
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import subprocess
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if __name__ == '__main__':
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# Read commandline options
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conf_parser = argparse.ArgumentParser(description='Plate solve FITS file' +
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' and add WCS on header')
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conf_parser.add_argument("-c", "--conf_file",
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help="Specify configuration file. If no file" +
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" is specified 'configuration.ini' is used.",
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metavar="FILE")
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conf_parser.add_argument("-d", "--directory",
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help="Specify directory of observations. If no" +
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" directory is specified parent will be used.",
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metavar='DIR', dest='file_dir', default=".")
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args = conf_parser.parse_args()
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# Process commandline options and parse configuration
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cfg = configparser.ConfigParser(inline_comment_prefixes=('#', ';'))
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if args.conf_file:
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cfg.read([args.conf_file])
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else:
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cfg.read('configuration.ini')
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path = args.file_dir
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extension = 'fits'
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files = sorted((f for f in os.listdir(path) if f.endswith('.' + extension)),
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key=lambda x: os.path.getctime(os.path.join(path, x)))
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if files:
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file_for_astrometry = os.path.join(path, files[0])
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print("Found " + file_for_astrometry + " for astrometric solving.")
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sex_config = cfg.get('Astrometry', 'sex_config')
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# Format command
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command = "solve-field -O -y -u app -L 37 -H 40 --use-sextractor " + \
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"--sextractor-config %s --downsample 2 --x-column X_IMAGE " % sex_config + \
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"--y-column Y_IMAGE --sort-column MAG_AUTO --sort-ascending " + \
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"%s" % file_for_astrometry
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# Run sextractor
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subprocess.run(command, shell=True, stderr=subprocess.STDOUT)
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else:
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print("No fits file found for astrometric solving.")
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@ -24,3 +24,6 @@ device_id = 0
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camera_x = 720 # Camera horizontal pixel count
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camera_y = 576 # Camera vertical pixel count
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camera_frames = 250 # Camera frames for each image (25fps*10sec=250)
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[Astrometry]
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sex_config = /path/to/solve.sex
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51
imgstat.py
51
imgstat.py
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@ -1,6 +1,5 @@
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#!/usr/bin/env python3
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from __future__ import print_function
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import numpy as np
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from astropy.io import ascii
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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@ -14,34 +13,43 @@ import os
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if __name__ == "__main__":
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# Read commandline options
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conf_parser = argparse.ArgumentParser(description='Plot image statistics')
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conf_parser.add_argument("-c", "--conf_file",
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conf_parser.add_argument("-c",
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"--conf_file",
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help="Specify configuration file. If no file" +
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" is specified 'configuration.ini' is used.",
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metavar="FILE")
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conf_parser.add_argument("-i", "--input",
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conf_parser.add_argument("-i",
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"--input",
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help="Specify file to be processed. If no file" +
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" is specified ./imgstat.csv will be used.",
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metavar='FILE', default="./imgstat.csv")
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conf_parser.add_argument("-d", "--directory",
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metavar='FILE',
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default="./imgstat.csv")
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conf_parser.add_argument("-d",
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"--directory",
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help="Specify directory of observations. If no" +
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" directory is specified parent will be used.",
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metavar='DIR', dest='file_dir', default=".")
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conf_parser.add_argument("-o", "--output",
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help="Specify output file. Default is 'imgstat.png'",
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metavar='FILE', default="./imgstat.png")
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metavar='DIR',
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dest='file_dir',
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default=".")
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conf_parser.add_argument(
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"-o",
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"--output",
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help="Specify output file. Default is 'imgstat.png'",
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metavar='FILE',
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default="./imgstat.png")
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args = conf_parser.parse_args()
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# Process commandline options and parse configuration
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cfg = configparser.ConfigParser(inline_comment_prefixes=('#', ';'))
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if args.conf_file:
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cfg.read([args.conf_file])
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else:
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cfg.read('configuration.ini')
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# Move to processing directory
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os.chdir(args.file_dir)
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table = ascii.read(args.input, format="csv")
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t = Time(table['mjd'], format="mjd", scale="utc")
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@ -49,13 +57,16 @@ if __name__ == "__main__":
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pos = SkyCoord(ra=table['ra'], dec=table['de'], frame="icrs", unit="deg")
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# Set location
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loc = EarthLocation(lat=cfg.getfloat('Common', 'observer_lat')*u.deg,
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lon=cfg.getfloat('Common', 'observer_lon')*u.deg,
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height=cfg.getfloat('Common', 'observer_el')*u.m)
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loc = EarthLocation(lat=cfg.getfloat('Common', 'observer_lat') * u.deg,
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lon=cfg.getfloat('Common', 'observer_lon') * u.deg,
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height=cfg.getfloat('Common', 'observer_el') * u.m)
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pa = pos.transform_to(AltAz(obstime=t, location=loc))
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fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, figsize=(20, 10), sharex=True)
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fig, (ax1, ax2, ax3, ax4) = plt.subplots(4,
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1,
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figsize=(20, 10),
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sharex=True)
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date_format = mdates.DateFormatter("%F\n%H:%M:%S")
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fig.autofmt_xdate(rotation=0, ha="center")
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@ -85,8 +96,6 @@ if __name__ == "__main__":
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ax4.set_xlabel("Time (UTC)")
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ax4.set_ylabel("Residuals (arcseconds)")
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ax4.legend()
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plt.tight_layout()
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plt.savefig(args.output)
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31
keogram.py
31
keogram.py
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@ -10,6 +10,7 @@ import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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from astropy.time import Time
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def generate_keogram(path):
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# Get files
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fnames = sorted(glob.glob(os.path.join(path, "processed/2*.fits")))
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@ -17,13 +18,13 @@ def generate_keogram(path):
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# Allocate arrays
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nx = len(fnames)
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ny = cfg.getint('Camera', 'camera_y')
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ixmid = cfg.getint('Camera', 'camera_x')//2
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keogram = np.zeros(nx*ny).reshape(ny, nx)
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ixmid = cfg.getint('Camera', 'camera_x') // 2
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keogram = np.zeros(nx * ny).reshape(ny, nx)
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mjds = np.zeros(nx)
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# Get data
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for i, fname in enumerate(fnames):
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if i%10==0:
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if i % 10 == 0:
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print(i, fname)
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# Read file
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@ -41,15 +42,19 @@ def generate_keogram(path):
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if __name__ == "__main__":
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# Read commandline options
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conf_parser = argparse.ArgumentParser(description='Process captured' +
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' video frames.')
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conf_parser.add_argument("-c", "--conf_file",
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' video frames.')
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conf_parser.add_argument("-c",
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"--conf_file",
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help="Specify configuration file. If no file" +
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" is specified 'configuration.ini' is used.",
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metavar="FILE")
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conf_parser.add_argument("-d", "--directory",
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conf_parser.add_argument("-d",
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"--directory",
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help="Specify directory of observations. If no" +
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" directory is specified parent will be used.",
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metavar='DIR', dest='file_dir', default=".")
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metavar='DIR',
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dest='file_dir',
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default=".")
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args = conf_parser.parse_args()
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@ -71,16 +76,20 @@ if __name__ == "__main__":
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# Time limits
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tmin = mdates.date2num(Time(np.min(mjds), format="mjd").datetime)
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tmax = mdates.date2num(Time(np.max(mjds), format="mjd").datetime)
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# Plot keogram
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fig, ax = plt.subplots(figsize=(15, 5))
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ax.imshow(np.log10(keogram), aspect="auto", origin="lower", cmap="magma", extent=[tmin, tmax, 0, 1])
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ax.imshow(np.log10(keogram),
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aspect="auto",
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origin="lower",
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cmap="magma",
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extent=[tmin, tmax, 0, 1])
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ax.axes.get_yaxis().set_visible(False)
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ax.xaxis_date()
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date_format = mdates.DateFormatter("%F\n%H:%M:%S")
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ax.xaxis.set_major_formatter(date_format)
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fig.autofmt_xdate(rotation=0, ha="center")
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plt.tight_layout()
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plt.savefig(os.path.join(args.file_dir, "keogram.png"))
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54
process.py
54
process.py
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@ -23,15 +23,19 @@ import shutil
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if __name__ == "__main__":
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# Read commandline options
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conf_parser = argparse.ArgumentParser(description='Process captured' +
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' video frames.')
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conf_parser.add_argument("-c", "--conf_file",
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' video frames.')
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conf_parser.add_argument("-c",
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"--conf_file",
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help="Specify configuration file. If no file" +
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" is specified 'configuration.ini' is used.",
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metavar="FILE")
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conf_parser.add_argument("-d", "--directory",
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conf_parser.add_argument("-d",
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"--directory",
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help="Specify directory of observations. If no" +
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" directory is specified parent will be used.",
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metavar='DIR', dest='file_dir', default=".")
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metavar='DIR',
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dest='file_dir',
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default=".")
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args = conf_parser.parse_args()
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@ -47,9 +51,9 @@ if __name__ == "__main__":
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warnings.simplefilter("ignore", AstropyWarning)
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# Set location
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loc = EarthLocation(lat=cfg.getfloat('Common', 'observer_lat')*u.deg,
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lon=cfg.getfloat('Common', 'observer_lon')*u.deg,
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height=cfg.getfloat('Common', 'observer_el')*u.m)
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loc = EarthLocation(lat=cfg.getfloat('Common', 'observer_lat') * u.deg,
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lon=cfg.getfloat('Common', 'observer_lon') * u.deg,
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height=cfg.getfloat('Common', 'observer_el') * u.m)
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# Extract settings
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# Minimum predicted velocity (pixels/s)
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@ -70,7 +74,7 @@ if __name__ == "__main__":
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# Statistics file
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fstat = open("imgstat.csv", "w")
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fstat.write("fname,mjd,ra,de,rmsx,rmsy,mean,std,nstars,nused\n")
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# Create output dirs
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path = args.file_dir
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results_path = os.path.join(cfg.get('Common', 'results_path'),
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@ -88,53 +92,55 @@ if __name__ == "__main__":
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while True:
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# Get files
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fnames = sorted(glob.glob("2*.fits"))
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# Loop over files
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for fname in fnames:
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# Generate star catalog
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pix_catalog = generate_star_catalog(fname)
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# Calibrate astrometry
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calibrate_from_reference(fname, "test.fits",
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pix_catalog)
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calibrate_from_reference(fname, "test.fits", pix_catalog)
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# Generate satellite predictions
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generate_satellite_predictions(fname)
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# Detect lines with 3D Hough transform
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ids = find_hough3d_lines(fname)
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# Extract tracks
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extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, results_path)
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extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin,
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results_path)
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# Stars available and used
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nused = np.sum(pix_catalog.flag == 1)
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nstars = pix_catalog.nstars
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# Get properties
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ff = fourframe(fname)
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# Write output
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output = "%s %10.6f %10.6f %4d/%4d %5.1f %5.1f %6.2f +- %6.2f"%(ff.fname, ff.crval[0], ff.crval[1], nused, nstars, 3600.0*ff.crres[0], 3600.0*ff.crres[1], np.mean(ff.zavg), np.std(ff.zavg))
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output = "%s %10.6f %10.6f %4d/%4d %5.1f %5.1f %6.2f +- %6.2f" % (
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ff.fname, ff.crval[0], ff.crval[1], nused, nstars,
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3600.0 * ff.crres[0], 3600.0 * ff.crres[1], np.mean(
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ff.zavg), np.std(ff.zavg))
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if is_calibrated(ff):
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print(colored(output, "green"))
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else:
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print(colored(output, "red"))
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fstat.write(("%s,%.8lf,%.6f,%.6f,%.3f,%.3f,%.3f," +
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"%.3f,%d,%d\n") % (ff.fname, ff.mjd, ff.crval[0],
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ff.crval[1], 3600*ff.crres[0],
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3600*ff.crres[1], np.mean(ff.zavg),
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np.std(ff.zavg), nstars, nused))
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fstat.write(
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("%s,%.8lf,%.6f,%.6f,%.3f,%.3f,%.3f," + "%.3f,%d,%d\n") %
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(ff.fname, ff.mjd, ff.crval[0], ff.crval[1],
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3600 * ff.crres[0], 3600 * ff.crres[1], np.mean(
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ff.zavg), np.std(ff.zavg), nstars, nused))
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# Move processed files
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shutil.move(fname, "processed")
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shutil.move(fname + ".png", "processed")
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shutil.move(fname + ".id", "processed")
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shutil.move(fname + ".cat", "processed")
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# Sleep
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time.sleep(10)
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# Close files
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fstat.close()
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@ -0,0 +1,4 @@
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[flake8]
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max-complexity = 25
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max-line-length = 99
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ignore = F403, W504, E226, W503
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@ -207,6 +207,7 @@ def calibrate_from_reference(fname, ref, pix_catalog):
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return w, rmsx, rmsy
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def is_calibrated(ff):
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if (3600.0*ff.crres[0] < 1e-3) | \
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(3600.0*ff.crres[1] < 1e-3) | \
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233
stvid/extract.py
233
stvid/extract.py
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@ -1,7 +1,6 @@
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#!/usr/bin/env python
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from __future__ import print_function
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import os
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import glob
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import shutil
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from stvid.stio import fourframe, satid, observation
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from stvid.astrometry import is_calibrated
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@ -11,33 +10,36 @@ from scipy import optimize, ndimage
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from termcolor import colored
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import datetime
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# Gaussian model
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def model(a, nx, ny):
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x, y = np.meshgrid(np.arange(nx), np.arange(ny))
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dx, dy = (x-a[0])/a[2], (y-a[1])/a[2]
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arg = -0.5*(dx**2+dy**2)
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return a[3]*np.exp(arg)+a[4]
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dx, dy = (x - a[0]) / a[2], (y - a[1]) / a[2]
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arg = -0.5 * (dx**2 + dy**2)
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return a[3] * np.exp(arg) + a[4]
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# Residual function
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def residual(a, img):
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ny, nx = img.shape
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mod = model(a, nx, ny)
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return (img-mod).ravel()
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return (img - mod).ravel()
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# Find peak
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def peakfind(img, w=1.0):
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# Find approximate location
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ny, nx = img.shape
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i = np.argmax(img)
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y0 = int(i/nx)
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x0 = i-y0*nx
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y0 = int(i / nx)
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x0 = i - y0 * nx
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# Image properties
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imgavg = np.mean(img)
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imgstd = np.std(img)
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# Estimate
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a = np.array([x0, y0, w, img[y0, x0]-imgavg, imgavg])
|
||||
a = np.array([x0, y0, w, img[y0, x0] - imgavg, imgavg])
|
||||
q, cov_q, infodict, mesg, ier = optimize.leastsq(residual,
|
||||
a,
|
||||
args=(img),
|
||||
|
|
@ -47,82 +49,87 @@ def peakfind(img, w=1.0):
|
|||
xc, yc, w = q[0], q[1], q[2]
|
||||
|
||||
# Significance
|
||||
sigma = (a[3]-imgavg)/(imgstd+1e-9)
|
||||
sigma = (a[3] - imgavg) / (imgstd + 1e-9)
|
||||
|
||||
return xc, yc, w, sigma
|
||||
|
||||
|
||||
# Plot selection
|
||||
def plot_selection(id, x0, y0, dt=2.0, w=10.0):
|
||||
dx, dy = id.x1-id.x0, id.y1-id.y0
|
||||
dx, dy = id.x1 - id.x0, id.y1 - id.y0
|
||||
ang = np.arctan2(dy, dx)
|
||||
r = np.sqrt(dx**2+dy**2)
|
||||
drdt = r/(id.t1-id.t0)
|
||||
r = np.sqrt(dx**2 + dy**2)
|
||||
drdt = r / (id.t1 - id.t0)
|
||||
sa, ca = np.sin(ang), np.cos(ang)
|
||||
|
||||
dx = np.array([-dt, -dt, dt, dt, -dt])*drdt
|
||||
dx = np.array([-dt, -dt, dt, dt, -dt]) * drdt
|
||||
dy = np.array([w, -w, -w, w, w])
|
||||
x = ca*dx-sa*dy+x0
|
||||
y = sa*dx+ca*dy+y0
|
||||
x = ca * dx - sa * dy + x0
|
||||
y = sa * dx + ca * dy + y0
|
||||
|
||||
ppg.pgsci(7)
|
||||
ppg.pgline(x, y)
|
||||
|
||||
return
|
||||
|
||||
|
||||
# Check if point is inside selection
|
||||
def inside_selection(ident, tmid, x0, y0, dt=2.0, w=10.0):
|
||||
dx, dy = ident.x1-ident.x0, ident.y1-ident.y0
|
||||
dx, dy = ident.x1 - ident.x0, ident.y1 - ident.y0
|
||||
ang = -np.arctan2(dy, dx)
|
||||
r = np.sqrt(dx**2+dy**2)
|
||||
drdt = r/(ident.t1-ident.t0)
|
||||
r = np.sqrt(dx**2 + dy**2)
|
||||
drdt = r / (ident.t1 - ident.t0)
|
||||
sa, ca = np.sin(ang), np.cos(ang)
|
||||
|
||||
xmid = ident.x0+ident.dxdt*tmid
|
||||
ymid = ident.y0+ident.dydt*tmid
|
||||
|
||||
dx, dy = x0-xmid, y0-ymid
|
||||
rm = ca*dx-sa*dy
|
||||
wm = sa*dx+ca*dy
|
||||
dtm = rm/drdt
|
||||
xmid = ident.x0 + ident.dxdt * tmid
|
||||
ymid = ident.y0 + ident.dydt * tmid
|
||||
|
||||
dx, dy = x0 - xmid, y0 - ymid
|
||||
rm = ca * dx - sa * dy
|
||||
wm = sa * dx + ca * dy
|
||||
dtm = rm / drdt
|
||||
|
||||
if (abs(wm) < w) & (abs(dtm) < dt):
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
|
||||
# Get COSPAR ID
|
||||
def get_cospar(norad, nfd):
|
||||
f = open(os.path.join(os.getenv("ST_DATADIR"), "data/desig.txt"))
|
||||
lines = f.readlines()
|
||||
f.close()
|
||||
|
||||
|
||||
try:
|
||||
cospar = ([line for line in lines if str(norad) in line])[0].split()[1]
|
||||
except IndexError:
|
||||
t = datetime.datetime.strptime(nfd[:-4], "%Y-%m-%dT%H:%M:%S")
|
||||
doy = int(t.strftime("%y%j"))+500
|
||||
cospar = "%sA"%doy
|
||||
doy = int(t.strftime("%y%j")) + 500
|
||||
cospar = "%sA" % doy
|
||||
|
||||
return "%2s %s" % (cospar[0:2], cospar[2:])
|
||||
|
||||
|
||||
# IOD position format 2: RA/DEC = HHMMmmm+DDMMmm MX (MX in minutes of arc)
|
||||
def format_position(ra, de):
|
||||
ram = 60.0*ra/15.0
|
||||
rah = int(np.floor(ram/60.0))
|
||||
ram -= 60.0*rah
|
||||
ram = 60.0 * ra / 15.0
|
||||
rah = int(np.floor(ram / 60.0))
|
||||
ram -= 60.0 * rah
|
||||
|
||||
des = np.sign(de)
|
||||
dem = 60.0*np.abs(de)
|
||||
ded = int(np.floor(dem/60.0))
|
||||
dem -= 60.0*ded
|
||||
dem = 60.0 * np.abs(de)
|
||||
ded = int(np.floor(dem / 60.0))
|
||||
dem -= 60.0 * ded
|
||||
|
||||
if des == -1:
|
||||
sign = "-"
|
||||
else:
|
||||
sign = "+"
|
||||
|
||||
return ("%02d%06.3f%c%02d%05.2f"
|
||||
% (rah, ram, sign, ded, dem)).replace(".", "")
|
||||
return ("%02d%06.3f%c%02d%05.2f" % (rah, ram, sign, ded, dem)).replace(
|
||||
".", "")
|
||||
|
||||
|
||||
# Format IOD line
|
||||
def format_iod_line(norad, cospar, site_id, t, ra, de):
|
||||
|
|
@ -132,12 +139,10 @@ def format_iod_line(norad, cospar, site_id, t, ra, de):
|
|||
.replace(":", "") \
|
||||
.replace(".", "")
|
||||
|
||||
return "%05d %-9s %04d G %s 17 25 %s 37 S" % (norad,
|
||||
cospar,
|
||||
site_id,
|
||||
tstr,
|
||||
return "%05d %-9s %04d G %s 17 25 %s 37 S" % (norad, cospar, site_id, tstr,
|
||||
pstr)
|
||||
|
||||
|
||||
def store_results(ident, fname, path, iod_line):
|
||||
# Find destination
|
||||
if ident.catalog.find("classfd.tle") > 0:
|
||||
|
|
@ -159,31 +164,32 @@ def store_results(ident, fname, path, iod_line):
|
|||
|
||||
# Print iod line
|
||||
print(colored(iod_line, color))
|
||||
|
||||
|
||||
# Copy files
|
||||
shutil.copy2(fname, dest)
|
||||
shutil.copy2(fname + ".cat", dest)
|
||||
shutil.copy2(fname + ".id", dest)
|
||||
shutil.copy2(fname + ".png", dest)
|
||||
try:
|
||||
shutil.move(fname.replace(".fits", "_%05d.png"%ident.norad), dest)
|
||||
except:
|
||||
shutil.move(fname.replace(".fits", "_%05d.png" % ident.norad), dest)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
# Write iodline
|
||||
fp = open(outfname, "a")
|
||||
fp.write("%s\n" % iod_line)
|
||||
fp.close()
|
||||
|
||||
|
||||
return
|
||||
|
||||
|
||||
def plot_header(fname, ff, iod_line):
|
||||
# ppgplot arrays
|
||||
heat_l = np.array([0.0, 0.2, 0.4, 0.6, 1.0])
|
||||
heat_r = np.array([0.0, 0.5, 1.0, 1.0, 1.0])
|
||||
heat_g = np.array([0.0, 0.0, 0.5, 1.0, 1.0])
|
||||
heat_b = np.array([0.0, 0.0, 0.0, 0.3, 1.0])
|
||||
|
||||
|
||||
# Plot
|
||||
ppg.pgopen(fname)
|
||||
ppg.pgpap(0.0, 1.0)
|
||||
|
|
@ -191,29 +197,21 @@ def plot_header(fname, ff, iod_line):
|
|||
|
||||
ppg.pgsch(0.8)
|
||||
ppg.pgmtxt("T", 6.0, 0.0, 0.0,
|
||||
"UT Date: %.23s COSPAR ID: %04d"
|
||||
% (ff.nfd, ff.site_id))
|
||||
"UT Date: %.23s COSPAR ID: %04d" % (ff.nfd, ff.site_id))
|
||||
if is_calibrated(ff):
|
||||
ppg.pgsci(1)
|
||||
else:
|
||||
ppg.pgsci(2)
|
||||
ppg.pgmtxt("T", 4.8, 0.0, 0.0,
|
||||
"R.A.: %10.5f (%4.1f'') Decl.: %10.5f (%4.1f'')"
|
||||
% (ff.crval[0],
|
||||
3600.0*ff.crres[0],
|
||||
ff.crval[1],
|
||||
3600.0*ff.crres[1]))
|
||||
ppg.pgmtxt(
|
||||
"T", 4.8, 0.0, 0.0, "R.A.: %10.5f (%4.1f'') Decl.: %10.5f (%4.1f'')" %
|
||||
(ff.crval[0], 3600.0 * ff.crres[0], ff.crval[1], 3600.0 * ff.crres[1]))
|
||||
ppg.pgsci(1)
|
||||
ppg.pgmtxt("T", 3.6, 0.0, 0.0,
|
||||
("FoV: %.2f\\(2218)x%.2f\\(2218) "
|
||||
"Scale: %.2f''x%.2f'' pix\\u-1\\d")
|
||||
% (ff.wx, ff.wy, 3600.0*ff.sx, 3600.0*ff.sy))
|
||||
ppg.pgmtxt("T", 2.4, 0.0, 0.0,
|
||||
"Stat: %5.1f+-%.1f (%.1f-%.1f)"
|
||||
% (np.mean(ff.zmax),
|
||||
np.std(ff.zmax),
|
||||
ff.zmaxmin,
|
||||
ff.zmaxmax))
|
||||
ppg.pgmtxt("T", 3.6, 0.0, 0.0, ("FoV: %.2f\\(2218)x%.2f\\(2218) "
|
||||
"Scale: %.2f''x%.2f'' pix\\u-1\\d") %
|
||||
(ff.wx, ff.wy, 3600.0 * ff.sx, 3600.0 * ff.sy))
|
||||
ppg.pgmtxt(
|
||||
"T", 2.4, 0.0, 0.0, "Stat: %5.1f+-%.1f (%.1f-%.1f)" %
|
||||
(np.mean(ff.zmax), np.std(ff.zmax), ff.zmaxmin, ff.zmaxmax))
|
||||
ppg.pgmtxt("T", 0.3, 0.0, 0.0, iod_line)
|
||||
|
||||
ppg.pgsch(1.0)
|
||||
|
|
@ -228,14 +226,14 @@ def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, path):
|
|||
ff = fourframe(fname)
|
||||
|
||||
# Skip saturated frames
|
||||
if np.sum(ff.zavg > 240.0)/float(ff.nx*ff.ny) > 0.95:
|
||||
if np.sum(ff.zavg > 240.0) / float(ff.nx * ff.ny) > 0.95:
|
||||
return
|
||||
|
||||
# Read satelite IDs
|
||||
try:
|
||||
f = open(fname+".id")
|
||||
f = open(fname + ".id")
|
||||
except OSError:
|
||||
print("Cannot open", fname+".id")
|
||||
print("Cannot open", fname + ".id")
|
||||
else:
|
||||
lines = f.readlines()
|
||||
f.close()
|
||||
|
|
@ -244,7 +242,7 @@ def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, path):
|
|||
|
||||
# Parse identifications
|
||||
idents = [satid(line) for line in lines]
|
||||
|
||||
|
||||
# Identify unknowns
|
||||
for ident0 in idents:
|
||||
if ident0.catalog == "unidentified":
|
||||
|
|
@ -264,67 +262,60 @@ def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, path):
|
|||
ident0.state = ident1.state
|
||||
ident1.state = "remove"
|
||||
break
|
||||
|
||||
|
||||
# Loop over identifications
|
||||
for ident in idents:
|
||||
# Skip superseded unknowns
|
||||
if ident.state == "remove":
|
||||
continue
|
||||
|
||||
|
||||
# Skip slow moving objects
|
||||
drdt = np.sqrt(ident.dxdt**2+ident.dydt**2)
|
||||
drdt = np.sqrt(ident.dxdt**2 + ident.dydt**2)
|
||||
if drdt < drdtmin:
|
||||
continue
|
||||
|
||||
# Extract significant pixels along a track
|
||||
x, y, t, sig = ff.significant_pixels_along_track(trksig,
|
||||
ident.x0,
|
||||
ident.y0,
|
||||
ident.dxdt,
|
||||
ident.dydt,
|
||||
trkrmin)
|
||||
x, y, t, sig = ff.significant_pixels_along_track(
|
||||
trksig, ident.x0, ident.y0, ident.dxdt, ident.dydt, trkrmin)
|
||||
|
||||
# Fit tracks
|
||||
if len(t) > ntrkmin:
|
||||
# Get times
|
||||
tmin = np.min(t)
|
||||
tmax = np.max(t)
|
||||
tmid = 0.5*(tmax+tmin)
|
||||
mjd = ff.mjd+tmid/86400.0
|
||||
tmid = 0.5 * (tmax + tmin)
|
||||
mjd = ff.mjd + tmid / 86400.0
|
||||
|
||||
# Skip if no variance in time
|
||||
if np.std(t-tmid) == 0.0:
|
||||
if np.std(t - tmid) == 0.0:
|
||||
continue
|
||||
|
||||
# Very simple polynomial fit; no weighting, no cleaning
|
||||
px = np.polyfit(t-tmid, x, 1)
|
||||
py = np.polyfit(t-tmid, y, 1)
|
||||
px = np.polyfit(t - tmid, x, 1)
|
||||
py = np.polyfit(t - tmid, y, 1)
|
||||
|
||||
# Extract results
|
||||
x0, y0 = px[1], py[1]
|
||||
dxdt, dydt = px[0], py[0]
|
||||
xmin = x0+dxdt*(tmin-tmid)
|
||||
ymin = y0+dydt*(tmin-tmid)
|
||||
xmax = x0+dxdt*(tmax-tmid)
|
||||
ymax = y0+dydt*(tmax-tmid)
|
||||
xmin = x0 + dxdt * (tmin - tmid)
|
||||
ymin = y0 + dydt * (tmin - tmid)
|
||||
xmax = x0 + dxdt * (tmax - tmid)
|
||||
ymax = y0 + dydt * (tmax - tmid)
|
||||
|
||||
cospar = get_cospar(ident.norad, ff.nfd)
|
||||
obs = observation(ff, mjd, x0, y0)
|
||||
iod_line = "%s" % format_iod_line(ident.norad,
|
||||
cospar,
|
||||
ff.site_id,
|
||||
obs.nfd,
|
||||
obs.ra,
|
||||
obs.de)
|
||||
iod_line = "%s" % format_iod_line(ident.norad, cospar, ff.site_id,
|
||||
obs.nfd, obs.ra, obs.de)
|
||||
|
||||
# Create diagnostic plot
|
||||
plot_header(fname.replace(".fits", "_%05d.png/png" % ident.norad), ff, iod_line)
|
||||
plot_header(fname.replace(".fits", "_%05d.png/png" % ident.norad),
|
||||
ff, iod_line)
|
||||
|
||||
ppg.pgimag(ff.zmax, ff.nx, ff.ny, 0, ff.nx-1,
|
||||
0, ff.ny-1, ff.zmaxmax, ff.zmaxmin, tr)
|
||||
ppg.pgimag(ff.zmax, ff.nx, ff.ny, 0, ff.nx - 1, 0, ff.ny - 1,
|
||||
ff.zmaxmax, ff.zmaxmin, tr)
|
||||
ppg.pgbox("BCTSNI", 0., 0, "BCTSNI", 0., 0)
|
||||
ppg.pgstbg(1)
|
||||
|
||||
|
||||
ppg.pgsci(0)
|
||||
if ident.catalog.find("classfd.tle") > 0:
|
||||
ppg.pgsci(4)
|
||||
|
|
@ -338,7 +329,7 @@ def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, path):
|
|||
ppg.pgtext(np.array([x0]), np.array([y0]), " %05d" % ident.norad)
|
||||
ppg.pgsch(1.0)
|
||||
ppg.pgsci(1)
|
||||
|
||||
|
||||
ppg.pgend()
|
||||
|
||||
# Store results
|
||||
|
|
@ -347,7 +338,7 @@ def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, path):
|
|||
elif ident.catalog.find("classfd.tle") > 0:
|
||||
# Track and stack
|
||||
t = np.linspace(0.0, ff.texp)
|
||||
x, y = ident.x0+ident.dxdt*t, ident.y0+ident.dydt*t
|
||||
x, y = ident.x0 + ident.dxdt * t, ident.y0 + ident.dydt * t
|
||||
c = (x > 0) & (x < ff.nx) & (y > 0) & (y < ff.ny)
|
||||
|
||||
# Skip if no points selected
|
||||
|
|
@ -356,27 +347,27 @@ def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, path):
|
|||
|
||||
# Compute track
|
||||
tmid = np.mean(t[c])
|
||||
mjd = ff.mjd+tmid/86400.0
|
||||
xmid = ident.x0+ident.dxdt*tmid
|
||||
ymid = ident.y0+ident.dydt*tmid
|
||||
ztrk = ndimage.gaussian_filter(ff.track(ident.dxdt, ident.dydt, tmid),
|
||||
1.0)
|
||||
vmin = np.mean(ztrk)-2.0*np.std(ztrk)
|
||||
vmax = np.mean(ztrk)+6.0*np.std(ztrk)
|
||||
mjd = ff.mjd + tmid / 86400.0
|
||||
xmid = ident.x0 + ident.dxdt * tmid
|
||||
ymid = ident.y0 + ident.dydt * tmid
|
||||
ztrk = ndimage.gaussian_filter(
|
||||
ff.track(ident.dxdt, ident.dydt, tmid), 1.0)
|
||||
vmin = np.mean(ztrk) - 2.0 * np.std(ztrk)
|
||||
vmax = np.mean(ztrk) + 6.0 * np.std(ztrk)
|
||||
|
||||
# Select region
|
||||
xmin = int(xmid-100)
|
||||
xmax = int(xmid+100)
|
||||
ymin = int(ymid-100)
|
||||
ymax = int(ymid+100)
|
||||
xmin = int(xmid - 100)
|
||||
xmax = int(xmid + 100)
|
||||
ymin = int(ymid - 100)
|
||||
ymax = int(ymid + 100)
|
||||
if xmin < 0:
|
||||
xmin = 0
|
||||
if ymin < 0:
|
||||
ymin = 0
|
||||
if xmax > ff.nx:
|
||||
xmax = ff.nx-1
|
||||
xmax = ff.nx - 1
|
||||
if ymax > ff.ny:
|
||||
ymax = ff.ny-1
|
||||
ymax = ff.ny - 1
|
||||
|
||||
# Find peak
|
||||
x0, y0, w, sigma = peakfind(ztrk[ymin:ymax, xmin:xmax])
|
||||
|
|
@ -394,20 +385,15 @@ def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, path):
|
|||
# Format IOD line
|
||||
cospar = get_cospar(ident.norad, ff.nfd)
|
||||
obs = observation(ff, mjd, x0, y0)
|
||||
iod_line = "%s" % format_iod_line(ident.norad,
|
||||
cospar,
|
||||
ff.site_id,
|
||||
obs.nfd,
|
||||
obs.ra,
|
||||
obs.de)
|
||||
|
||||
iod_line = "%s" % format_iod_line(ident.norad, cospar, ff.site_id,
|
||||
obs.nfd, obs.ra, obs.de)
|
||||
|
||||
# Create diagnostic plot
|
||||
plot_header(fname.replace(".fits", "_%05d.png/png" % ident.norad), ff, iod_line)
|
||||
plot_header(fname.replace(".fits", "_%05d.png/png" % ident.norad),
|
||||
ff, iod_line)
|
||||
|
||||
|
||||
ppg.pgimag(ztrk, ff.nx, ff.ny, 0, ff.nx-1,
|
||||
0, ff.ny-1, vmax, vmin, tr)
|
||||
ppg.pgimag(ztrk, ff.nx, ff.ny, 0, ff.nx - 1, 0, ff.ny - 1, vmax,
|
||||
vmin, tr)
|
||||
ppg.pgbox("BCTSNI", 0., 0, "BCTSNI", 0., 0)
|
||||
ppg.pgstbg(1)
|
||||
|
||||
|
|
@ -423,8 +409,7 @@ def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin, path):
|
|||
ppg.pgdraw(ident.x1, ident.y1)
|
||||
ppg.pgpt(np.array([x0]), np.array([y0]), 4)
|
||||
ppg.pgsch(0.65)
|
||||
ppg.pgtext(np.array([ident.x0]),
|
||||
np.array([ident.y0]),
|
||||
ppg.pgtext(np.array([ident.x0]), np.array([ident.y0]),
|
||||
" %05d" % ident.norad)
|
||||
ppg.pgsch(1.0)
|
||||
ppg.pgsci(1)
|
||||
|
|
|
|||
|
|
@ -1,17 +1,17 @@
|
|||
#!/usr/bin/env python
|
||||
from __future__ import print_function
|
||||
import os
|
||||
import subprocess
|
||||
from stvid.stio import fourframe
|
||||
from stvid.stio import satid
|
||||
from stvid.stio import observation
|
||||
|
||||
|
||||
def generate_satellite_predictions(fname):
|
||||
# Format command
|
||||
command = "satid %s %s.png/png" % (fname, fname)
|
||||
|
||||
# Run command
|
||||
output = subprocess.check_output(command, shell=True,
|
||||
output = subprocess.check_output(command,
|
||||
shell=True,
|
||||
stderr=subprocess.STDOUT)
|
||||
|
||||
return output
|
||||
|
|
@ -28,9 +28,9 @@ def find_hough3d_lines(fname, ntrkmin=20, dr=8):
|
|||
x, y, z, t, sig = ff.selection_mask(5.0, 40.0)
|
||||
|
||||
# Skip if not enough points
|
||||
if len(t)<2:
|
||||
if len(t) < 2:
|
||||
return []
|
||||
|
||||
|
||||
# Save points to temporary file
|
||||
with open("/tmp/hough.dat", "w") as f:
|
||||
for i in range(len(t)):
|
||||
|
|
@ -38,12 +38,13 @@ def find_hough3d_lines(fname, ntrkmin=20, dr=8):
|
|||
f.close()
|
||||
|
||||
# Run 3D Hough line-finding algorithm
|
||||
command = "hough3dlines -dx %d -minvotes %d %s" % (dr, ntrkmin, "/tmp/hough.dat")
|
||||
command = "hough3dlines -dx %d -minvotes %d %s" % (dr, ntrkmin,
|
||||
"/tmp/hough.dat")
|
||||
try:
|
||||
output = subprocess.check_output(command,
|
||||
shell=True,
|
||||
stderr=subprocess.STDOUT)
|
||||
except:
|
||||
except Exception:
|
||||
return []
|
||||
|
||||
# Clean output (a bit cluncky)
|
||||
|
|
@ -56,16 +57,18 @@ def find_hough3d_lines(fname, ntrkmin=20, dr=8):
|
|||
# Generate identifications
|
||||
lines = []
|
||||
s = cleaned_output.split()
|
||||
for i in range(len(s)//7):
|
||||
for i in range(len(s) // 7):
|
||||
# Extract points
|
||||
x0, y0, z0 = float(s[1+7*i]), float(s[2+7*i]), float(s[3+7*i])
|
||||
dx, dy, dz = float(s[4+7*i]), float(s[5+7*i]), float(s[6+7*i])
|
||||
|
||||
x0, y0, z0 = float(s[1 + 7 * i]), float(s[2 + 7 * i]), float(s[3 +
|
||||
7 * i])
|
||||
dx, dy, dz = float(s[4 + 7 * i]), float(s[5 + 7 * i]), float(s[6 +
|
||||
7 * i])
|
||||
|
||||
# Reconstruct start and end points
|
||||
xmin = x0-z0*dx/(dz+1e-9)
|
||||
xmax = x0+(ff.nz-z0)*dx/(dz+1e-9)
|
||||
ymin = y0-z0*dy/(dz+1e-9)
|
||||
ymax = y0+(ff.nz-z0)*dy/(dz+1e-9)
|
||||
xmin = x0 - z0 * dx / (dz + 1e-9)
|
||||
xmax = x0 + (ff.nz - z0) * dx / (dz + 1e-9)
|
||||
ymin = y0 - z0 * dy / (dz + 1e-9)
|
||||
ymax = y0 + (ff.nz - z0) * dy / (dz + 1e-9)
|
||||
|
||||
# Output line
|
||||
line = "%.23s %8.3f %8.3f %8.3f %8.3f %8.5f %s unidentified sunlit\n" %\
|
||||
|
|
@ -77,5 +80,5 @@ def find_hough3d_lines(fname, ntrkmin=20, dr=8):
|
|||
for line in lines:
|
||||
fp.write(line)
|
||||
fp.close()
|
||||
|
||||
|
||||
return [satid(line) for line in lines]
|
||||
|
|
|
|||
117
stvid/stio.py
117
stvid/stio.py
|
|
@ -22,7 +22,9 @@ class observation:
|
|||
self.nfd = Time(self.mjd, format='mjd', scale='utc').isot
|
||||
|
||||
# Correct for rotation
|
||||
tobs = Time(ff.mjd+0.5*ff.texp/86400.0, format='mjd', scale='utc')
|
||||
tobs = Time(ff.mjd + 0.5 * ff.texp / 86400.0,
|
||||
format='mjd',
|
||||
scale='utc')
|
||||
tobs.delta_ut1_utc = 0
|
||||
hobs = tobs.sidereal_time("mean", longitude=0.0).degree
|
||||
tmid = Time(self.mjd, format='mjd', scale='utc')
|
||||
|
|
@ -31,7 +33,7 @@ class observation:
|
|||
|
||||
# Compute ra/dec
|
||||
world = ff.w.wcs_pix2world(np.array([[self.x0, self.y0]]), 1)
|
||||
self.ra = world[0, 0]+hobs-hmid
|
||||
self.ra = world[0, 0] + hobs - hmid
|
||||
self.de = world[0, 1]
|
||||
|
||||
|
||||
|
|
@ -50,15 +52,13 @@ class satid:
|
|||
self.norad = int(s[6])
|
||||
self.catalog = s[7]
|
||||
self.state = s[8]
|
||||
self.dxdt = (self.x1-self.x0)/(self.t1-self.t0)
|
||||
self.dydt = (self.y1-self.y0)/(self.t1-self.t0)
|
||||
self.dxdt = (self.x1 - self.x0) / (self.t1 - self.t0)
|
||||
self.dydt = (self.y1 - self.y0) / (self.t1 - self.t0)
|
||||
|
||||
def __repr__(self):
|
||||
return "%s %f %f %f -> %f %f %f %d %s %s" % (self.nfd, self.x0,
|
||||
self.y0, self.t0,
|
||||
self.x1, self.y1,
|
||||
self.t1, self.norad,
|
||||
self.catalog, self.state)
|
||||
return "%s %f %f %f -> %f %f %f %d %s %s" % (
|
||||
self.nfd, self.x0, self.y0, self.t0, self.x1, self.y1, self.t1,
|
||||
self.norad, self.catalog, self.state)
|
||||
|
||||
|
||||
class fourframe:
|
||||
|
|
@ -95,15 +95,15 @@ class fourframe:
|
|||
self.zavg, self.zstd, self.zmax, self.znum = hdu[0].data
|
||||
|
||||
# Generate sigma frame
|
||||
self.zsig = (self.zmax-self.zavg)/(self.zstd+1e-9)
|
||||
self.zsig = (self.zmax - self.zavg) / (self.zstd + 1e-9)
|
||||
|
||||
# Frame properties
|
||||
self.ny, self.nx = self.zavg.shape
|
||||
self.nz = hdu[0].header['NFRAMES']
|
||||
|
||||
# Read frame time oselfsets
|
||||
self.dt = np.array([hdu[0].header['DT%04d' % i]
|
||||
for i in range(self.nz)])
|
||||
self.dt = np.array(
|
||||
[hdu[0].header['DT%04d' % i] for i in range(self.nz)])
|
||||
|
||||
# Read header
|
||||
self.mjd = hdu[0].header['MJD-OBS']
|
||||
|
|
@ -114,30 +114,29 @@ class fourframe:
|
|||
self.fname = fname
|
||||
|
||||
# Astrometry keywords
|
||||
self.crpix = np.array([hdu[0].header['CRPIX1'],
|
||||
hdu[0].header['CRPIX2']])
|
||||
self.crval = np.array([hdu[0].header['CRVAL1'],
|
||||
hdu[0].header['CRVAL2']])
|
||||
self.cd = np.array([[hdu[0].header['CD1_1'],
|
||||
hdu[0].header['CD1_2']],
|
||||
[hdu[0].header['CD2_1'],
|
||||
hdu[0].header['CD2_2']]])
|
||||
self.crpix = np.array(
|
||||
[hdu[0].header['CRPIX1'], hdu[0].header['CRPIX2']])
|
||||
self.crval = np.array(
|
||||
[hdu[0].header['CRVAL1'], hdu[0].header['CRVAL2']])
|
||||
self.cd = np.array(
|
||||
[[hdu[0].header['CD1_1'], hdu[0].header['CD1_2']],
|
||||
[hdu[0].header['CD2_1'], hdu[0].header['CD2_2']]])
|
||||
self.ctype = [hdu[0].header['CTYPE1'], hdu[0].header['CTYPE2']]
|
||||
self.cunit = [hdu[0].header['CUNIT1'], hdu[0].header['CUNIT2']]
|
||||
self.crres = np.array([hdu[0].header['CRRES1'],
|
||||
hdu[0].header['CRRES2']])
|
||||
self.crres = np.array(
|
||||
[hdu[0].header['CRRES1'], hdu[0].header['CRRES2']])
|
||||
|
||||
hdu.close()
|
||||
|
||||
|
||||
# Compute image properties
|
||||
self.sx = np.sqrt(self.cd[0, 0]**2+self.cd[1, 0]**2)
|
||||
self.sy = np.sqrt(self.cd[0, 1]**2+self.cd[1, 1]**2)
|
||||
self.wx = self.nx*self.sx
|
||||
self.wy = self.ny*self.sy
|
||||
self.zmaxmin = np.mean(self.zmax)-2.0*np.std(self.zmax)
|
||||
self.zmaxmax = np.mean(self.zmax)+6.0*np.std(self.zmax)
|
||||
self.zavgmin = np.mean(self.zavg)-2.0*np.std(self.zavg)
|
||||
self.zavgmax = np.mean(self.zavg)+6.0*np.std(self.zavg)
|
||||
self.sx = np.sqrt(self.cd[0, 0]**2 + self.cd[1, 0]**2)
|
||||
self.sy = np.sqrt(self.cd[0, 1]**2 + self.cd[1, 1]**2)
|
||||
self.wx = self.nx * self.sx
|
||||
self.wy = self.ny * self.sy
|
||||
self.zmaxmin = np.mean(self.zmax) - 2.0 * np.std(self.zmax)
|
||||
self.zmaxmax = np.mean(self.zmax) + 6.0 * np.std(self.zmax)
|
||||
self.zavgmin = np.mean(self.zavg) - 2.0 * np.std(self.zavg)
|
||||
self.zavgmax = np.mean(self.zavg) + 6.0 * np.std(self.zavg)
|
||||
|
||||
# Setup WCS
|
||||
self.w = wcs.WCS(naxis=2)
|
||||
|
|
@ -163,10 +162,10 @@ class fourframe:
|
|||
def selection_mask(self, sigma, zstd):
|
||||
"""Create a selection mask"""
|
||||
c1 = ndimage.uniform_filter(self.znum, 3, mode='constant')
|
||||
c2 = ndimage.uniform_filter(self.znum*self.znum, 3, mode='constant')
|
||||
c2 = ndimage.uniform_filter(self.znum * self.znum, 3, mode='constant')
|
||||
|
||||
# Add epsilon to keep square root positive
|
||||
z = np.sqrt(c2-c1*c1+1e-9)
|
||||
z = np.sqrt(c2 - c1 * c1 + 1e-9)
|
||||
|
||||
# Standard deviation mask
|
||||
c = z < zstd
|
||||
|
|
@ -177,7 +176,7 @@ class fourframe:
|
|||
c = self.zsig < sigma
|
||||
m2 = np.zeros_like(self.zavg)
|
||||
m2[~c] = 1.0
|
||||
self.zsel = m1*m2
|
||||
self.zsel = m1 * m2
|
||||
|
||||
# Generate points
|
||||
c = self.zsel == 1.0
|
||||
|
|
@ -189,12 +188,17 @@ class fourframe:
|
|||
|
||||
return x, y, inum, t, sig
|
||||
|
||||
def significant_pixels_along_track(self, sigma, x0, y0,
|
||||
dxdt, dydt, rmin=10.0):
|
||||
def significant_pixels_along_track(self,
|
||||
sigma,
|
||||
x0,
|
||||
y0,
|
||||
dxdt,
|
||||
dydt,
|
||||
rmin=10.0):
|
||||
"""Extract significant pixels along a track"""
|
||||
|
||||
# Generate sigma frame
|
||||
zsig = (self.zmax-self.zavg)/(self.zstd+1e-9)
|
||||
zsig = (self.zmax - self.zavg) / (self.zstd + 1e-9)
|
||||
|
||||
# Select
|
||||
c = (zsig > sigma)
|
||||
|
|
@ -207,9 +211,9 @@ class fourframe:
|
|||
t = np.array([self.dt[i] for i in inum])
|
||||
|
||||
# Predicted positions
|
||||
xr = x0+dxdt*t
|
||||
yr = y0+dydt*t
|
||||
r = np.sqrt((x-xr)**2+(y-yr)**2)
|
||||
xr = x0 + dxdt * t
|
||||
yr = y0 + dydt * t
|
||||
r = np.sqrt((x - xr)**2 + (y - yr)**2)
|
||||
c = r < rmin
|
||||
|
||||
return x[c], y[c], t[c], sig[c]
|
||||
|
|
@ -218,7 +222,7 @@ class fourframe:
|
|||
"""Extract significant pixels"""
|
||||
|
||||
# Generate sigma frame
|
||||
zsig = (self.zmax-self.zavg)/(self.zstd+1e-9)
|
||||
zsig = (self.zmax - self.zavg) / (self.zstd + 1e-9)
|
||||
|
||||
# Select
|
||||
c = (zsig > sigma)
|
||||
|
|
@ -239,8 +243,8 @@ class fourframe:
|
|||
|
||||
# Loop over frames
|
||||
for i in range(self.nz):
|
||||
dx = int(np.round(dxdt*(self.dt[i]-tref)))
|
||||
dy = int(np.round(dydt*(self.dt[i]-tref)))
|
||||
dx = int(np.round(dxdt * (self.dt[i] - tref)))
|
||||
dy = int(np.round(dydt * (self.dt[i] - tref)))
|
||||
|
||||
# Skip if shift larger than image
|
||||
if np.abs(dx) >= self.nx:
|
||||
|
|
@ -250,28 +254,23 @@ class fourframe:
|
|||
|
||||
# Extract range
|
||||
if dx >= 0:
|
||||
i1min, i1max = dx, self.nx-1
|
||||
i2min, i2max = 0, self.nx-dx-1
|
||||
i1min, i1max = dx, self.nx - 1
|
||||
i2min, i2max = 0, self.nx - dx - 1
|
||||
else:
|
||||
i1min, i1max = 0, self.nx+dx-1
|
||||
i2min, i2max = -dx, self.nx-1
|
||||
i1min, i1max = 0, self.nx + dx - 1
|
||||
i2min, i2max = -dx, self.nx - 1
|
||||
if dy >= 0:
|
||||
j1min, j1max = dy, self.ny-1
|
||||
j2min, j2max = 0, self.ny-dy-1
|
||||
j1min, j1max = dy, self.ny - 1
|
||||
j2min, j2max = 0, self.ny - dy - 1
|
||||
else:
|
||||
j1min, j1max = 0, self.ny+dy-1
|
||||
j2min, j2max = -dy, self.ny-1
|
||||
j1min, j1max = 0, self.ny + dy - 1
|
||||
j2min, j2max = -dy, self.ny - 1
|
||||
zsel = np.where(self.znum == i, self.zmax, 0.0)
|
||||
ztrk[j2min:j2max, i2min:i2max] += zsel[j1min:j1max, i1min:i1max]
|
||||
|
||||
return ztrk
|
||||
|
||||
def __repr__(self):
|
||||
return "%s %dx%dx%d %s %.3f %d %s" % (self.fname,
|
||||
self.nx,
|
||||
self.ny,
|
||||
self.nz,
|
||||
self.nfd,
|
||||
self.texp,
|
||||
self.site_id,
|
||||
self.observer)
|
||||
return "%s %dx%dx%d %s %.3f %d %s" % (self.fname, self.nx, self.ny,
|
||||
self.nz, self.nfd, self.texp,
|
||||
self.site_id, self.observer)
|
||||
|
|
|
|||
|
|
@ -13,8 +13,8 @@ def get_sunset_and_sunrise(tnow, loc, refalt_set, refalt_rise):
|
|||
# Get time
|
||||
nmjd = 64
|
||||
mjd0 = np.floor(tnow.mjd)
|
||||
mnow = tnow.mjd-mjd0
|
||||
mjd = np.linspace(mjd0-1.0, mjd0+3.0, nmjd)
|
||||
mnow = tnow.mjd - mjd0
|
||||
mjd = np.linspace(mjd0 - 1.0, mjd0 + 3.0, nmjd)
|
||||
t = Time(mjd, format='mjd', scale='utc')
|
||||
|
||||
# Get sun position
|
||||
|
|
@ -28,8 +28,10 @@ def get_sunset_and_sunrise(tnow, loc, refalt_set, refalt_rise):
|
|||
|
||||
# Compute altitude extrema
|
||||
de = np.mean(pos.dec)
|
||||
minalt = np.arcsin(np.sin(loc.lat)*np.sin(de)-np.cos(loc.lat)*np.cos(de))
|
||||
maxalt = np.arcsin(np.sin(loc.lat)*np.sin(de)+np.cos(loc.lat)*np.cos(de))
|
||||
minalt = np.arcsin(
|
||||
np.sin(loc.lat) * np.sin(de) - np.cos(loc.lat) * np.cos(de))
|
||||
maxalt = np.arcsin(
|
||||
np.sin(loc.lat) * np.sin(de) + np.cos(loc.lat) * np.cos(de))
|
||||
|
||||
# Never sets, never rises?
|
||||
if minalt > min(refalt_set, refalt_rise):
|
||||
|
|
@ -38,55 +40,48 @@ def get_sunset_and_sunrise(tnow, loc, refalt_set, refalt_rise):
|
|||
return "sun never rises", t[0], t[0]
|
||||
|
||||
# Prevent discontinuities in right ascension
|
||||
dra = pos[-1].ra-pos[0].ra
|
||||
dra = pos[-1].ra - pos[0].ra
|
||||
ra = pos.ra.degree
|
||||
if dra < 0.0:
|
||||
c = pos.ra.degree < 180.0
|
||||
ra[c] = pos[c].ra.degree+360.0
|
||||
ra[c] = pos[c].ra.degree + 360.0
|
||||
|
||||
# Set up interpolating function
|
||||
fra = interpolate.interp1d(t.mjd, ra)
|
||||
fde = interpolate.interp1d(t.mjd, pos.dec.degree)
|
||||
|
||||
# Get GMST
|
||||
gmst0 = Time(mjd0,
|
||||
format='mjd',
|
||||
gmst0 = Time(mjd0, format='mjd',
|
||||
scale='utc').sidereal_time('mean', 'greenwich')
|
||||
|
||||
# Get transit time
|
||||
mtransit = np.mod((fra(mjd0)*u.degree-loc.lon-gmst0)/(360.0*u.degree), 1.0)
|
||||
mtransit = np.mod(
|
||||
(fra(mjd0) * u.degree - loc.lon - gmst0) / (360.0 * u.degree), 1.0)
|
||||
while True:
|
||||
gmst = gmst0+360.985647*u.deg*mtransit
|
||||
ra = fra(mjd0+mtransit)*u.deg
|
||||
ha = gmst+loc.lon-ra
|
||||
mtransit -= ha/(360.0*u.deg)
|
||||
gmst = gmst0 + 360.985647 * u.deg * mtransit
|
||||
ra = fra(mjd0 + mtransit) * u.deg
|
||||
ha = gmst + loc.lon - ra
|
||||
mtransit -= ha / (360.0 * u.deg)
|
||||
if np.abs(ha.degree) < 1e-9:
|
||||
break
|
||||
|
||||
# Hour angle offset
|
||||
ha0 = np.arccos((np.sin(refalt_set)
|
||||
- np.sin(loc.lat)
|
||||
* np.sin(np.mean(pos.dec)))
|
||||
/ (np.cos(loc.lat)
|
||||
* np.cos(np.mean(pos.dec))))
|
||||
|
||||
ha0 = np.arccos(
|
||||
(np.sin(refalt_set) - np.sin(loc.lat) * np.sin(np.mean(pos.dec))) /
|
||||
(np.cos(loc.lat) * np.cos(np.mean(pos.dec))))
|
||||
|
||||
# Get set time
|
||||
mset = mtransit+ha0/(360.0*u.deg)
|
||||
mset = mtransit + ha0 / (360.0 * u.deg)
|
||||
while True:
|
||||
gmst = gmst0+360.985647*u.deg*mset
|
||||
ra = fra(mjd0+mset)*u.deg
|
||||
de = fde(mjd0+mset)*u.deg
|
||||
ha = gmst+loc.lon-ra
|
||||
alt = np.arcsin(np.sin(loc.lat)
|
||||
* np.sin(de)
|
||||
+ np.cos(loc.lat)
|
||||
* np.cos(de)
|
||||
* np.cos(ha))
|
||||
dm = (alt-refalt_set)/(360.0
|
||||
* u.deg
|
||||
* np.cos(de)
|
||||
* np.cos(loc.lat)
|
||||
* np.sin(ha))
|
||||
gmst = gmst0 + 360.985647 * u.deg * mset
|
||||
ra = fra(mjd0 + mset) * u.deg
|
||||
de = fde(mjd0 + mset) * u.deg
|
||||
ha = gmst + loc.lon - ra
|
||||
alt = np.arcsin(
|
||||
np.sin(loc.lat) * np.sin(de) +
|
||||
np.cos(loc.lat) * np.cos(de) * np.cos(ha))
|
||||
dm = (alt - refalt_set) / (360.0 * u.deg * np.cos(de) *
|
||||
np.cos(loc.lat) * np.sin(ha))
|
||||
mset += dm
|
||||
|
||||
# Break loop or find sunset on next day
|
||||
|
|
@ -97,25 +92,20 @@ def get_sunset_and_sunrise(tnow, loc, refalt_set, refalt_rise):
|
|||
mset += 1.0
|
||||
|
||||
# Set set time
|
||||
tset = Time(mjd0+mset.value, format='mjd', scale='utc')
|
||||
tset = Time(mjd0 + mset.value, format='mjd', scale='utc')
|
||||
|
||||
# Get rise time
|
||||
mrise = mtransit-ha0/(360.0*u.deg)
|
||||
mrise = mtransit - ha0 / (360.0 * u.deg)
|
||||
while True:
|
||||
gmst = gmst0+360.985647*u.deg*mrise
|
||||
ra = fra(mjd0+mrise)*u.deg
|
||||
de = fde(mjd0+mrise)*u.deg
|
||||
ha = gmst+loc.lon-ra
|
||||
alt = np.arcsin(np.sin(loc.lat)
|
||||
* np.sin(de)
|
||||
+ np.cos(loc.lat)
|
||||
* np.cos(de)
|
||||
* np.cos(ha))
|
||||
dm = (alt-refalt_rise)/(360.0
|
||||
* u.deg
|
||||
* np.cos(de)
|
||||
* np.cos(loc.lat)
|
||||
* np.sin(ha))
|
||||
gmst = gmst0 + 360.985647 * u.deg * mrise
|
||||
ra = fra(mjd0 + mrise) * u.deg
|
||||
de = fde(mjd0 + mrise) * u.deg
|
||||
ha = gmst + loc.lon - ra
|
||||
alt = np.arcsin(
|
||||
np.sin(loc.lat) * np.sin(de) +
|
||||
np.cos(loc.lat) * np.cos(de) * np.cos(ha))
|
||||
dm = (alt - refalt_rise) / (360.0 * u.deg * np.cos(de) *
|
||||
np.cos(loc.lat) * np.sin(ha))
|
||||
mrise += dm
|
||||
|
||||
# Break loop or find sunrise on next day
|
||||
|
|
@ -126,6 +116,6 @@ def get_sunset_and_sunrise(tnow, loc, refalt_set, refalt_rise):
|
|||
mrise += 1.0
|
||||
|
||||
# Set rise time
|
||||
trise = Time(mjd0+mrise.value, format='mjd', scale='utc')
|
||||
trise = Time(mjd0 + mrise.value, format='mjd', scale='utc')
|
||||
|
||||
return "sun rises and sets", tset, trise
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ from __future__ import print_function
|
|||
import configparser
|
||||
import argparse
|
||||
from spacetrack import SpaceTrackClient
|
||||
import subprocess
|
||||
from shutil import copyfile
|
||||
import datetime
|
||||
from io import BytesIO
|
||||
|
|
|
|||
Loading…
Reference in New Issue