def plot_many_sunearth_vec(d, comveceq, obsveceq, ctime, ltcomcel, axisdata,
ra_img_higher, ra_img_lower, border, pixwidth,
pixheight, rafmin, decmin, scale, comsunfill,
featur_fill, fnt, fixwrapsbool):
nolines = 24
lperday = 24
timearray = np.empty((nolines, 2), dtype=float)
timearray[:,
0] = np.arange(-0.5, -0.5 - nolines / lperday, -1 /
lperday) + np.floor(ctime.jd * lperday) / lperday
for ta in range(nolines):
timearray[ta, 1] = abs(comveceq[:, 0] - timearray[ta, 0]).argmin()
for n in range(nolines):
#creates an array of ra/dec values along sun-comet line
cmsam = 10001
offsets = np.ones(cmsam) + np.linspace(-1, 1, cmsam)
comsun = np.empty((cmsam, 4), dtype=float)
for cs in range(0, cmsam):
ctemp = pos2radec(
offsets[cs] * comveceq[timearray[n, 1], 6:9] -
obsveceq[ltcomcel, 6:9], fixwrapsbool)
comsun[cs, 0] = ctemp[0]
comsun[cs, 1] = ctemp[1]
#slims this array down to within image limits
csvrange = np.intersect1d(
np.intersect1d(
np.where(comsun[:, 0] < ra_img_higher)[0],
np.where(comsun[:, 0] > ra_img_lower)[0]),
np.intersect1d(
np.where(comsun[:, 1] < axisdata[9])[0],
np.where(comsun[:, 1] > axisdata[8])[0]))
comsun = comsun[csvrange[0]:csvrange[-1], :]
#convert to ra and dec, and plot
comsun[:, 2] = ra2xpix(comsun[:, 0], border, pixwidth, rafmin, scale)
comsun[:, 3] = dec2ypix(comsun[:, 1], border, pixheight, decmin, scale)
for ca in range(0, (np.shape(comsun)[0] - 1)):
d.line([(comsun[ca, 2], comsun[ca, 3]),
(comsun[ca + 1, 2], comsun[ca + 1, 3])],
fill=comsunfill)
def plot_sunearth_vec(d, comveceq, obsveceq, ltcomcel, axisdata, ra_img_higher,
ra_img_lower, border, pixwidth, pixheight, rafmin,
decmin, scale, comsunfill, featur_fill, fnt,
fixwrapsbool):
#creates an array of ra/dec values along sun-comet line
cmsam = 10001
offsets = np.ones(cmsam) + np.linspace(-1, 1, cmsam)
comsun = np.empty((cmsam, 4), dtype=float)
for cs in range(0, cmsam):
ctemp = pos2radec(
offsets[cs] * comveceq[int(ltcomcel), 6:9] -
obsveceq[int(ltcomcel), 6:9], fixwrapsbool)
comsun[cs, 0] = ctemp[0]
comsun[cs, 1] = ctemp[1]
#slims this array down to within image limits
csvrange = np.intersect1d(
np.intersect1d(
np.where(comsun[:, 0] < ra_img_higher)[0],
np.where(comsun[:, 0] > ra_img_lower)[0]),
np.intersect1d(
np.where(comsun[:, 1] < axisdata[9])[0],
np.where(comsun[:, 1] > axisdata[8])[0]))
comsun = comsun[csvrange[0]:csvrange[-1], :]
#convert to ra and dec, and plot
comsun[:, 2] = ra2xpix(comsun[:, 0], border, pixwidth, rafmin, scale)
comsun[:, 3] = dec2ypix(comsun[:, 1], border, pixheight, decmin, scale)
for ca in range(0, (np.shape(comsun)[0] - 1)):
d.line([(comsun[ca, 2], comsun[ca, 3]),
(comsun[ca + 1, 2], comsun[ca + 1, 3])],
fill=comsunfill)
d.text((2*border + pixwidth + 30,border + 310), \
"Comet-Sun\nVector:",font=fnt, fill= featur_fill)
d.line([(2 * border + pixwidth + 30, border + 355),
(2 * border + pixwidth + 170, border + 355)],
fill=comsunfill)
com_box_path[len0:len0+len1-1,0] = ra[1:,-1]
com_box_path[len0:len0+len1-1,1] = dec[1:,-1]
com_box_path[len0+len1-1:2*len0+len1-2,0] = ra[-1,-2::-1]
com_box_path[len0+len1-1:2*len0+len1-2,1] = dec[-1,-2::-1]
com_box_path[2*len0+len1-2:2*len0+2*len1-3,0] = ra[-2::-1,0]
com_box_path[2*len0+len1-2:2*len0+2*len1-3,1] = dec[-2::-1,0]
com_Path = mplPath.Path(com_box_path)
[ctime,uncertainty_range_exists] = image_time_stereo(filebase)
#find relevant observer parameters of comet at observer time
comcel = np.where(abs(obsveceq[:,0] - ctime.jd)==abs(obsveceq[:,0] - ctime.jd).min())[0][0]
LT_cor = int(np.round(np.linalg.norm(comveceq[comcel,6:9] -
obsveceq[comcel,6:9])*8.316746397269274))
com_ra_dec = pos2radec(comveceq[comcel - LT_cor,6:9] - obsveceq[comcel,6:9],fixwrapsbool)
com_in_image = com_Path.contains_point((com_ra_dec[0]-np.mean(ra_m-ra),com_ra_dec[1]))
if com_in_image == False:
break
com_ra_dec_array = np.zeros((1,2))
com_ra_dec_array[0,0] = com_ra_dec[0] - np.mean(ra_m-ra); com_ra_dec_array[0,1] = com_ra_dec[1]
compos = tuple(np.round(w.wcs_world2pix(com_ra_dec_array,0)[0][::-1]).astype(int))
nucvals[fidx] = colr[compos]
jdeez[fidx] = ctime.jd
fidx +=1
jdeez = jdeez[0:fidx]
& (comobs[:,5] < trafmax))[0]
obsdecloc = np.where((comobs[:,6] > tdecmin) \
& (comobs[:,6] < tdecmax))[0]
trajrough = np.intersect1d(obsraloc, obsdecloc)
if trajrough.size != 0:
#use this to calculate ra and dec of comet for a purposely oversized range
vno = 0
vext = int(np.size(trajrough))
vtraj = np.empty((np.size(trajrough) + 2 * vext - 1, 11),
dtype=float)
tcellmax = min(trajrough[-1] + vext, np.shape(comveceq)[0])
for tcell in range(trajrough[0] - vext, tcellmax):
vtemp = comveceq[tcell, 6:9] - obsveceq[comcel, 6:9]
ptemp = pos2radec(vtemp, bool_val)
vtraj[vno, 0] = ptemp[0]
vtraj[vno, 1] = ptemp[1]
vtraj[vno, 4] = tcell
vtraj[vno, 5] = tcell + round(
np.linalg.norm(vtemp) * 8.316746397269274)
vtraj[vno, 6:11] = comveceq[tcell, 1:6]
vno += 1
#use these ra and dec values to slim data down to within image borders
trajrange = np.intersect1d(
np.intersect1d(
np.where(vtraj[:, 0] < trafmax)[0],
np.where(vtraj[:, 0] > trafmin)[0]),
np.intersect1d(
np.where(vtraj[:, 1] < tdecmax)[0],
def plot_orbit(comobs, comveceq, obsveceq, axisdata, d, comcel, trajfill,
ra_img_lower, ra_img_higher, border, pixwidth, rafmin, scale,
pixheight, decmin, fnt, featur_fill, con_in_image,
fixwrapsbool):
#find rough cell range of traj from observer data
obsraloc = np.where((comobs[:,5] > ra_img_lower) \
& (comobs[:,5] < ra_img_higher))[0]
obsdecloc = np.where((comobs[:,6] > axisdata[8]) \
& (comobs[:,6] < axisdata[9]))[0]
trajrough = np.intersect1d(obsraloc, obsdecloc)
if trajrough.size != 0:
#use this to calculate ra and dec of comet for a purposely oversized range
vno = 0
vext = int(np.size(trajrough))
vtraj = np.empty((np.size(trajrough) + 2 * vext - 1, 11), dtype=float)
tcellmax = min(trajrough[-1] + vext, np.shape(comveceq)[0])
for tcell in range(trajrough[0] - vext, tcellmax):
vtemp = comveceq[tcell, 6:9] - obsveceq[comcel, 6:9]
ptemp = pos2radec(vtemp, fixwrapsbool)
vtraj[vno, 0] = ptemp[0]
vtraj[vno, 1] = ptemp[1]
vtraj[vno, 4] = tcell
vtraj[vno, 5] = tcell + round(
np.linalg.norm(vtemp) * 8.316746397269274)
vtraj[vno, 6:11] = comveceq[tcell, 1:6]
vno += 1
#use these ra and dec values to slim data down to within image borders
trajrange = np.intersect1d(
np.intersect1d(
np.where(vtraj[:, 0] < ra_img_higher)[0],
np.where(vtraj[:, 0] > ra_img_lower)[0]),
np.intersect1d(
np.where(vtraj[:, 1] < axisdata[9])[0],
np.where(vtraj[:, 1] > axisdata[8])[0]))
vtraj = vtraj[trajrange[0]:trajrange[-1], :]
#find relevant cell in vtraj and comveceq accounting for LT
if con_in_image == True:
vtrajcel = np.where(abs(vtraj[:, 5] - comcel) < 1e-4)[0][0]
ltcomcel = vtraj[vtrajcel, 4]
else:
ltcomcel = None
vtrajcel = None
#convert to ra and dec, and plot
vtraj[:, 2] = ra2xpix(vtraj[:, 0], border, pixwidth, rafmin, scale)
vtraj[:, 3] = dec2ypix(vtraj[:, 1], border, pixheight, decmin, scale)
for ta in range(0, (np.shape(vtraj)[0] - 1)):
d.line([(vtraj[ta,2],vtraj[ta,3]),(vtraj[ta+1,2],vtraj[ta+1,3])],\
fill = trajfill)
#plot the path
d.text((2*border + pixwidth + 30,border + 200), \
"Orbital Path:",font=fnt, fill= featur_fill)
d.line([(2 * border + pixwidth + 30, border + 230),
(2 * border + pixwidth + 170, border + 230)],
fill=trajfill)
else:
ltcomcel = None
vtraj = None
vtrajcel = None
return ltcomcel, vtraj, vtrajcel