def process_loop(fname):
"""
Thread to process satobs FourFrame FITS files in a multi-thread compatible manner
"""
# Generate star catalog
if not os.path.exists(fname + ".cat"):
pix_catalog = generate_star_catalog(fname)
else:
pix_catalog = pixel_catalog(fname + ".cat")
# Calibrate from reference
calibrate_from_reference(fname, "test.fits", pix_catalog)
# Store calibration
store_calibration(pix_catalog, fname + ".cal")
# Generate satellite predictions
generate_satellite_predictions(fname)
# Detect lines with 3D Hough transform
ids = find_hough3d_lines(fname, nhoughmin, houghrmin)
# Get properties
ff = fourframe(fname)
# Extract tracks
if is_calibrated(ff):
screenoutput_idents = extract_tracks(fname, trkrmin, drdtmin, drdtmax, trksig, ntrkmin, root_dir, results_dir, tle_dir)
else:
screenoutput_idents = None
# Stars available and used
nused = np.sum(pix_catalog.flag == 1)
nstars = pix_catalog.nstars
# Write output
screenoutput = "%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))
if is_calibrated(ff):
screenoutput = colored(screenoutput, "green")
else:
screenoutput = colored(screenoutput, "red")
imgstat_output = ("%s,%.8lf,%.6f,%.6f,%.3f,%.3f,%.3f," + "%.3f,%d,%d\n") % (
(ff.fname, ff.mjd, ff.crval[0], ff.crval[1],
3600 * ff.crres[0], 3600 * ff.crres[1], np.mean(
ff.zavg), np.std(ff.zavg), nstars, nused))
# Move processed files
shutil.move(fname, os.path.join(processed_dir, fname))
shutil.move(fname + ".png", os.path.join(processed_dir, fname + ".png"))
shutil.move(fname + ".id", os.path.join(processed_dir, fname + ".id"))
shutil.move(fname + ".cat", os.path.join(processed_dir, fname + ".cat"))
shutil.move(fname + ".cal", os.path.join(processed_dir, fname + ".cal"))
return (screenoutput, imgstat_output, screenoutput_idents)
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)
ppg.pgsvp(0.1, 0.95, 0.1, 0.8)
ppg.pgsch(0.8)
ppg.pgmtxt("T", 6.0, 0.0, 0.0,
"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.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", 0.3, 0.0, 0.0, iod_line)
ppg.pgsch(1.0)
ppg.pgwnad(0.0, ff.nx, 0.0, ff.ny)
ppg.pglab("x (pix)", "y (pix)", " ")
ppg.pgctab(heat_l, heat_r, heat_g, heat_b, 5, 1.0, 0.5)
fnames = sorted(glob.glob("2*.fits"))
# Loop over files
for fname in fnames:
# Generate star catalog
pix_catalog = generate_star_catalog(fname)
# Create reference calibration file
if not os.path.exists("test.fits"):
solved = generate_reference_with_anet(fname, "")
# Calibrate astrometry
calibrate_from_reference(fname, "test.fits", pix_catalog)
# Redo refence if astrometry failed
if not is_calibrated(fourframe(fname)) and pix_catalog.nstars > 10:
print(
colored(
"Recomputing astrometric calibration for %s" % fname,
"yellow"))
solved = generate_reference_with_anet(fname, "")
# Calibrate astrometry
calibrate_from_reference(fname, "test.fits", pix_catalog)
# Generate satellite predictions
generate_satellite_predictions(fname)
# Detect lines with 3D Hough transform
ids = find_hough3d_lines(fname)
pix_catalog = generate_star_catalog(fname)
# Calibrate from reference
calibrate_from_reference(fname, "test.fits", pix_catalog)
# Generate satellite predictions
generate_satellite_predictions(fname)
# Detect lines with 3D Hough transform
ids = find_hough3d_lines(fname)
# Get properties
ff = fourframe(fname)
# Extract tracks
if is_calibrated(ff):
extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin,
root_dir, results_dir)
# Stars available and used
nused = np.sum(pix_catalog.flag == 1)
nstars = pix_catalog.nstars
# Write output
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))
if is_calibrated(ff):
print(colored(output, "green"))
else: