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)
def startPlotter(self):
if self.plotDeviceIsOpened:
raise ValueError("You already started a plot!")
devId = pgplot.pgopen(self.deviceName)
self.plotDeviceIsOpened = True
if not self.widthInches is None:
pgplot.pgpap(self.widthInches, self.yOnXRatio)
# For devices /xs, /xw, /png etc, should make the paper white and the ink black. Only for /ps does pgplot default to that.
#
deviceWithoutFile = self.deviceName.split('/')[-1]
if deviceWithoutFile == 'xs' or deviceWithoutFile == 'xw' or deviceWithoutFile == 'png':
pgplot.pgscr(0, 1.0, 1.0, 1.0)
pgplot.pgscr(1, 0.0, 0.0, 0.0)
pgplot.pgsvp(self._vXLo, self._vXHi, self._vYLo, self._vYHi)
if self.fixAspect:
pgplot.pgwnad(self.worldXLo, self.worldXHi, self.worldYLo,
self.worldYHi)
else:
pgplot.pgswin(self.worldXLo, self.worldXHi, self.worldYLo,
self.worldYHi)
pgplot.pgsfs(2)
pgplot.pgslw(1)
pgplot.pgsch(self._charHeight)
self._setColourRepresentations()
# Set up things so calling pgplot.pggray() won't overwrite the CR of any of the colours in self.colours.
#
(minCI, maxCI) = pgplot.pgqcir()
if minCI <= self.maxCI:
pgplot.pgscir(self.maxCI + 1, maxCI)
(xLoPixels, xHiPixels, yLoPixels, yHiPixels) = pgplot.pgqvsz(3)
(xLoInches, xHiInches, yLoInches, yHiInches) = pgplot.pgqvsz(1)
self.xPixelWorld = (xHiInches - xLoInches) / (xHiPixels - xLoPixels)
self.yPixelWorld = (yHiInches - yLoInches) / (yHiPixels - yLoPixels)
ppgplot.pgslw(2)
ppgplot.pgpap(0.0, 0.75)
# For ever loop
redraw = True
while True:
# Redraw
if redraw == True:
# Update
m.update()
# Initialize window
ppgplot.pgscr(0, 0., 0., 0.)
ppgplot.pgeras()
ppgplot.pgsvp(0.01, 0.99, 0.01, 0.99)
ppgplot.pgwnad(-1.5 * m.w, 1.5 * m.w, -m.w, m.w)
# Set background depending on solar altitude
if m.sunalt > 0.0:
ppgplot.pgscr(0, 0.0, 0.0, 0.4)
elif m.sunalt > -6.0:
ppgplot.pgscr(0, 0.0, 0.0, 0.3)
elif m.sunalt > -12.0:
ppgplot.pgscr(0, 0.0, 0.0, 0.2)
elif m.sunalt > -18.0:
ppgplot.pgscr(0, 0.0, 0.0, 0.1)
else:
ppgplot.pgscr(0, 0.0, 0.0, 0.0)
ppgplot.pgsci(0)
# Plot box
def plot(self, vlo=2., vhi=98., nc=-1, method='p', mpl=False, cmap=CMDEF, \
close=True, x1=None, x2=None, y1=None, y2=None, sepmin=1.):
"""
Plots an MCCD using pgplot or matplotlib if preferred.
:Parameters:
vlo : float
number specifying the lowest level to plot (default as a percentile)
vhi : float
number specifying the lowest level to plot (default as a percentile)
nc : int
CCD number (starting from 0, -1 for all)
method : string
how vlo and vhi are to be interpreted. 'p' = percentile, 'a' = automatic (min to max,
vlo and vhi are irrelevant), 'd' = direct, i.e. just take the values given.
mpl : bool
True to prefer matplotlib over pgplot (which may not even be an option)
cmap : matplotlib.cm.binary
colour map if using matplotlib
close : bool
close (pgplot) or 'show' (matplotlib) the plot at the end (or not, to allow
you to plot something else, use a cursor etc). In the case of pgplot, this also
implies opening the plot at the start, i.e. a self-contained quick plot.
x1 : float
left-hand plot limit. Defaults to 0.5
x2 : float
right-hand plot limit. Defaults to nxmax+0.5
y1 : float
lower plot limit. Defaults to 0.5
y2 : float
upper plot limit. Defaults to nymax+0.5
sepmin : float
minimum separation between intensity limits (> 0 to stop PGPLOT complaining)
:Returns:
range(s) : tuple or list
the plot range(s) used either as a single 2-element tuple, or
a list of them, one per CCD plotted.
"""
if nc == -1:
nc1 = 0
nc2 = len(self)
else:
nc1 = nc
nc2 = nc+1
if not mpl:
if close: pg.pgopen('/xs')
if nc2-nc1 > 1: pg.pgsubp(nc2-nc1,1)
prange = []
for nc, ccd in enumerate(self._data[nc1:nc2]):
# Determine intensity range to display
if method == 'p':
vmin, vmax = ccd.centile((vlo,vhi))
elif method == 'a':
vmin, vmax = ccd.min(), ccd.max()
elif method == 'd':
vmin, vmax = vlo, vhi
else:
raise UltracamError('MCCD.plot: method must be one of p, a or d.')
if vmin == vmax:
vmin -= sepmin/2.
vmax += sepmin/2.
prange.append((vmin, vmax))
# start
nxmax, nymax = ccd.nxmax, ccd.nymax
x1 = 0.5 if x1 is None else x1
x2 = nxmax+0.5 if x2 is None else x2
y1 = 0.5 if y1 is None else y1
y2 = nymax+0.5 if y2 is None else y2
if mpl:
if nc2-nc1 > 1:
plt.subplot(1,nc2-nc1,nc+1)
plt.axis('equal')
else:
if nc2-nc1 > 1: pg.pgpanl(nc-nc1+1,1)
pg.pgwnad(x1,x2,y1,y2)
# plot CCD
ccd.plot(vmin,vmax,mpl,cmap)
# per-frame finishing-off
if mpl:
plt.xlim(x1,x2)
plt.ylim(y1,y2)
else:
pg.pgbox('bcnst',0,0,'bcnst',0,0)
pg.pglab('X','Y','')
if close:
if mpl:
plt.show()
else:
pg.pgclos()
# return intensity range(s) used
if len(prange) == 1:
return prange[0]
else:
return tuple(prange)
def plot(self, vlo=2., vhi=98., nc=-1, method='p', mpl=False, cmap=CMDEF, \
close=True, x1=None, x2=None, y1=None, y2=None, sepmin=1.):
"""
Plots an MCCD using pgplot or matplotlib if preferred.
:Parameters:
vlo : float
number specifying the lowest level to plot (default as a percentile)
vhi : float
number specifying the lowest level to plot (default as a percentile)
nc : int
CCD number (starting from 0, -1 for all)
method : string
how vlo and vhi are to be interpreted. 'p' = percentile, 'a' = automatic (min to max,
vlo and vhi are irrelevant), 'd' = direct, i.e. just take the values given.
mpl : bool
True to prefer matplotlib over pgplot (which may not even be an option)
cmap : matplotlib.cm.binary
colour map if using matplotlib
close : bool
close (pgplot) or 'show' (matplotlib) the plot at the end (or not, to allow
you to plot something else, use a cursor etc). In the case of pgplot, this also
implies opening the plot at the start, i.e. a self-contained quick plot.
x1 : float
left-hand plot limit. Defaults to 0.5
x2 : float
right-hand plot limit. Defaults to nxmax+0.5
y1 : float
lower plot limit. Defaults to 0.5
y2 : float
upper plot limit. Defaults to nymax+0.5
sepmin : float
minimum separation between intensity limits (> 0 to stop PGPLOT complaining)
:Returns:
range(s) : tuple or list
the plot range(s) used either as a single 2-element tuple, or
a list of them, one per CCD plotted.
"""
if nc == -1:
nc1 = 0
nc2 = len(self)
else:
nc1 = nc
nc2 = nc + 1
if not mpl:
if close: pg.pgopen('/xs')
if nc2 - nc1 > 1: pg.pgsubp(nc2 - nc1, 1)
prange = []
for nc, ccd in enumerate(self._data[nc1:nc2]):
# Determine intensity range to display
if method == 'p':
vmin, vmax = ccd.centile((vlo, vhi))
elif method == 'a':
vmin, vmax = ccd.min(), ccd.max()
elif method == 'd':
vmin, vmax = vlo, vhi
else:
raise UltracamError(
'MCCD.plot: method must be one of p, a or d.')
if vmin == vmax:
vmin -= sepmin / 2.
vmax += sepmin / 2.
prange.append((vmin, vmax))
# start
nxmax, nymax = ccd.nxmax, ccd.nymax
x1 = 0.5 if x1 is None else x1
x2 = nxmax + 0.5 if x2 is None else x2
y1 = 0.5 if y1 is None else y1
y2 = nymax + 0.5 if y2 is None else y2
if mpl:
if nc2 - nc1 > 1:
plt.subplot(1, nc2 - nc1, nc + 1)
plt.axis('equal')
else:
if nc2 - nc1 > 1: pg.pgpanl(nc - nc1 + 1, 1)
pg.pgwnad(x1, x2, y1, y2)
# plot CCD
ccd.plot(vmin, vmax, mpl, cmap)
# per-frame finishing-off
if mpl:
plt.xlim(x1, x2)
plt.ylim(y1, y2)
else:
pg.pgbox('bcnst', 0, 0, 'bcnst', 0, 0)
pg.pglab('X', 'Y', '')
if close:
if mpl:
plt.show()
else:
pg.pgclos()
# return intensity range(s) used
if len(prange) == 1:
return prange[0]
else:
return tuple(prange)
def extract_tracks(fname, trkrmin, drdtmin, trksig, ntrkmin):
# Read four frame
ff = fourframe(fname)
# Skip saturated frames
if np.sum(ff.zavg > 240.0) / float(ff.nx * ff.ny) > 0.95:
return
# Read satelite IDs
try:
f = open(fname + ".id")
except OSError:
print("Cannot open", fname + ".id")
else:
lines = f.readlines()
f.close()
# ppgplot arrays
tr = np.array([-0.5, 1.0, 0.0, -0.5, 0.0, 1.0])
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])
# Loop over identifications
for line in lines:
# Decode
id = satid(line)
# Skip slow moving objects
drdt = np.sqrt(id.dxdt**2 + id.dydt**2)
if drdt < drdtmin:
continue
# Extract significant pixels
x, y, t, sig = ff.significant(trksig, id.x0, id.y0, id.dxdt, id.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
# Skip if no variance in time
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)
# 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)
cospar = get_cospar(id.norad)
obs = observation(ff, mjd, x0, y0)
iod_line = "%s" % format_iod_line(id.norad, cospar, ff.site_id,
obs.nfd, obs.ra, obs.de)
print(iod_line)
if id.catalog.find("classfd.tle") > 0:
outfname = "classfd.dat"
elif id.catalog.find("inttles.tle") > 0:
outfname = "inttles.dat"
else:
outfname = "catalog.dat"
f = open(outfname, "a")
f.write("%s\n" % iod_line)
f.close()
# Plot
ppgplot.pgopen(
fname.replace(".fits", "") + "_%05d.png/png" % id.norad)
#ppgplot.pgopen("/xs")
ppgplot.pgpap(0.0, 1.0)
ppgplot.pgsvp(0.1, 0.95, 0.1, 0.8)
ppgplot.pgsch(0.8)
ppgplot.pgmtxt(
"T", 6.0, 0.0, 0.0,
"UT Date: %.23s COSPAR ID: %04d" % (ff.nfd, ff.site_id))
if (3600.0 * ff.crres[0] < 1e-3
) | (3600.0 * ff.crres[1] < 1e-3) | (
ff.crres[0] / ff.sx > 2.0) | (ff.crres[1] / ff.sy > 2.0):
ppgplot.pgsci(2)
else:
ppgplot.pgsci(1)
ppgplot.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]))
ppgplot.pgsci(1)
ppgplot.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))
ppgplot.pgmtxt(
"T", 2.4, 0.0, 0.0, "Stat: %5.1f+-%.1f (%.1f-%.1f)" %
(np.mean(ff.zmax), np.std(ff.zmax), ff.vmin, ff.vmax))
ppgplot.pgmtxt("T", 0.3, 0.0, 0.0, iod_line)
ppgplot.pgsch(1.0)
ppgplot.pgwnad(0.0, ff.nx, 0.0, ff.ny)
ppgplot.pglab("x (pix)", "y (pix)", " ")
ppgplot.pgctab(heat_l, heat_r, heat_g, heat_b, 5, 1.0, 0.5)
ppgplot.pgimag(ff.zmax, ff.nx, ff.ny, 0, ff.nx - 1, 0, ff.ny - 1,
ff.vmax, ff.vmin, tr)
ppgplot.pgbox("BCTSNI", 0., 0, "BCTSNI", 0., 0)
ppgplot.pgstbg(1)
ppgplot.pgsci(0)
if id.catalog.find("classfd.tle") > 0:
ppgplot.pgsci(4)
elif id.catalog.find("inttles.tle") > 0:
ppgplot.pgsci(3)
ppgplot.pgpt(np.array([x0]), np.array([y0]), 4)
ppgplot.pgmove(xmin, ymin)
ppgplot.pgdraw(xmax, ymax)
ppgplot.pgsch(0.65)
ppgplot.pgtext(np.array([x0]), np.array([y0]), " %05d" % id.norad)
ppgplot.pgsch(1.0)
ppgplot.pgsci(1)
ppgplot.pgend()
elif id.catalog.find("classfd.tle") > 0:
# Track and stack
t = np.linspace(0.0, ff.texp)
x, y = id.x0 + id.dxdt * t, id.y0 + id.dydt * t
c = (x > 0) & (x < ff.nx) & (y > 0) & (y < ff.ny)
# Skip if no points selected
if np.sum(c) == 0:
continue
# Compute track
tmid = np.mean(t[c])
mjd = ff.mjd + tmid / 86400.0
xmid = id.x0 + id.dxdt * tmid
ymid = id.y0 + id.dydt * tmid
ztrk = ndimage.gaussian_filter(ff.track(id.dxdt, id.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)
if xmin < 0: xmin = 0
if ymin < 0: ymin = 0
if xmax > ff.nx: xmax = ff.nx - 1
if ymax > ff.ny: ymax = ff.ny - 1
# Find peak
x0, y0, w, sigma = peakfind(ztrk[ymin:ymax, xmin:xmax])
x0 += xmin
y0 += ymin
# Skip if peak is not significant
if sigma < trksig:
continue
# Skip if point is outside selection area
if inside_selection(id, xmid, ymid, x0, y0) == False:
continue
# Format IOD line
cospar = get_cospar(id.norad)
obs = observation(ff, mjd, x0, y0)
iod_line = "%s" % format_iod_line(id.norad, cospar, ff.site_id,
obs.nfd, obs.ra, obs.de)
print(iod_line)
if id.catalog.find("classfd.tle") > 0:
outfname = "classfd.dat"
elif id.catalog.find("inttles.tle") > 0:
outfname = "inttles.dat"
else:
outfname = "catalog.dat"
f = open(outfname, "a")
f.write("%s\n" % iod_line)
f.close()
# Plot
ppgplot.pgopen(
fname.replace(".fits", "") + "_%05d.png/png" % id.norad)
ppgplot.pgpap(0.0, 1.0)
ppgplot.pgsvp(0.1, 0.95, 0.1, 0.8)
ppgplot.pgsch(0.8)
ppgplot.pgmtxt(
"T", 6.0, 0.0, 0.0,
"UT Date: %.23s COSPAR ID: %04d" % (ff.nfd, ff.site_id))
ppgplot.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]))
ppgplot.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))
ppgplot.pgmtxt(
"T", 2.4, 0.0, 0.0, "Stat: %5.1f+-%.1f (%.1f-%.1f)" %
(np.mean(ff.zmax), np.std(ff.zmax), ff.vmin, ff.vmax))
ppgplot.pgmtxt("T", 0.3, 0.0, 0.0, iod_line)
ppgplot.pgsch(1.0)
ppgplot.pgwnad(0.0, ff.nx, 0.0, ff.ny)
ppgplot.pglab("x (pix)", "y (pix)", " ")
ppgplot.pgctab(heat_l, heat_r, heat_g, heat_b, 5, 1.0, 0.5)
ppgplot.pgimag(ztrk, ff.nx, ff.ny, 0, ff.nx - 1, 0, ff.ny - 1,
vmax, vmin, tr)
ppgplot.pgbox("BCTSNI", 0., 0, "BCTSNI", 0., 0)
ppgplot.pgstbg(1)
plot_selection(id, xmid, ymid)
ppgplot.pgsci(0)
if id.catalog.find("classfd.tle") > 0:
ppgplot.pgsci(4)
elif id.catalog.find("inttles.tle") > 0:
ppgplot.pgsci(3)
ppgplot.pgpt(np.array([id.x0]), np.array([id.y0]), 17)
ppgplot.pgmove(id.x0, id.y0)
ppgplot.pgdraw(id.x1, id.y1)
ppgplot.pgpt(np.array([x0]), np.array([y0]), 4)
ppgplot.pgsch(0.65)
ppgplot.pgtext(np.array([id.x0]), np.array([id.y0]),
" %05d" % id.norad)
ppgplot.pgsch(1.0)
ppgplot.pgsci(1)
ppgplot.pgend()