# This file is part of libkd. # Licensed under a 3-clause BSD style license - see LICENSE from astrometry.libkd import spherematch import numpy as np from time import time N1 = 1000 N2 = 1000 D = 2 r = 0.02 x1 = np.random.rand(N1, D) x2 = np.random.rand(N2, D) t0 = time() (inds,dists) = spherematch.match(x1, x2, r) dt = time() - t0 print 'spherematch.match: found', len(inds), 'pairs in', int(dt*1000.), 'ms' order = np.argsort(inds[:,0]*N2 + inds[:,1]) inds = inds[order] dists = dists[order] t0 = time() pairs = [] truedists = [] for i in range(N1): pt1 = x1[i,:] d2s = np.sum((x2 - pt1)**2, axis=1) good = np.where(d2s <= r**2)[0]
def whynot(field, index, qidx, wcs):
# find index stars in the field.
(ra,dec) = wcs.get_radec_center()
rad = arcsec2deg(wcs.get_pixel_scale() * hypot(wcs.get_width(), wcs.get_height()))
(xyz, radec, starinds) = index_search_stars(index, ra, dec, rad)
print('xyz', xyz.shape)
print('radec', radec.shape)
print('starinds', starinds.shape)
istars = tabledata()
istars.xyz = xyz
istars.radec = radec
istars.starind = starinds
W,H = wcs.get_width(), wcs.get_height()
pix = array([wcs.radec2pixelxy(r, d) for (r,d) in radec])
print('pix', pix.shape)
# within image bounds
I = (pix[:,0] > 0) * (pix[:,0] < W) * (pix[:,1] > 0) * (pix[:,1] < H)
# find nearby pairs of stars...
nsigma = 3
pixeljitter = 1
sigma = hypot(index.index_jitter / wcs.get_pixel_scale(), pixeljitter)
rad = nsigma * sigma
fieldxy = vstack((field.x, field.y)).T
print('field', fieldxy.shape)
(cinds, cdists) = match(pix, fieldxy, rad)
print('matches:', cinds.shape)
#print cdists.shape
corrs = tabledata()
corrs.dist = cdists[:,0]
corrs.star = starinds[cinds[:,0]]
corrs.field = cinds[:,1]
allquads = []
# All quads built from stars in the field...
for starind in starinds[I]:
#print qidx, starind
quads = qidxfile_get_quad_list(qidxfile_addr(qidx), starind)
#print 'quads:', quads.shape
allquads.append(quads)
allquads = unique(hstack(allquads))
print('%i unique quads touch stars in the field' % len(allquads))
'''
"quads" object: all quads that touch index stars in this field.
.quad : (int) quad index
.stars : (DQ x int) star indices
.starsinfield: (DQ x bool) stars in field
'''
quads = tabledata()
quads.quad = allquads
qstars = quadfile_get_stars_for_quads(quadfile_addr(index), quads.quad)
print('stars in quads:', qstars.shape)
#print qstars
quads.stars = qstars
quads.starsinfield = array([[s in starinds[I] for s in q] for q in qstars])
#print quads.starsinfield
allin = quads.starsinfield.min(axis=1)
#print quads.allin
quads.allin = allin
quadsin = quads[allin]
print('%i quads use stars that are in the field' % (len(quadsin)))
print('stars:', starinds)
c_s2f = {}
for c in corrs: #i in range(len(corrs)):
#print 'corr', c
if not c.star in c_s2f:
c_s2f[c.star] = []
c_s2f[c.star].append(c.field)
#c_s2f[corrs.star[i]]
#print c_s2f
# [[[213], [35], [265], [63]], [[186]], [[]], [[11], [19]], ...]
# For each quad, for each star in the quad, the list of field stars corresponding.
fq = []
for q in quadsin.stars:
fq1 = []
for s in q:
if s in c_s2f:
fq1.append(c_s2f[s])
else:
fq1.append([])
fq.append(fq1)
#print fq
# For each quad, the list of sets of field stars corresponding.
# [[[213, 35, 265, 63]], [], [],
fq2 = []
for q in fq:
#print 'q:', q
#ac = allcombinations([q[0]], q[1:])
#ac = allcombinations([[]], q)
#print '--> ac:', ac
fq2.append(allcombinations([[]], q))
#print fq2
quadsin.fq2 = fq2
hasf = array([len(x) > 0 for x in quadsin.fq2])
#print 'hasf:', hasf
okquads = quadsin[hasf]
#forder = argsort([max(x) for x in okquads.fq2])
#okquads = okquads[forder]
print('ok quads:', len(okquads))
print('quad nums:', okquads.quad)
print('stars:', okquads.stars)
print('field stars:', okquads.fq2)
#qmatches = table_data()
#fqs = []
#qs = []
#for okq,fq in zip(okquads, okquads.fq2):
# fqs = fqs + fq
# qs.append(okq)
#qmatches.fieldquad = fqs
qmatches = []
for okq,fqs in zip(okquads, okquads.fq2):
for fq in fqs:
#print 'field stars', fq
#print 'quad:', okq.quad
qmatches.append((fq, okq))
forder = argsort([max(fq) for fq,okq in qmatches])
#print 'forder', forder
print()
print('Quads in the order they will be found')
for i in forder:
fq,okq = qmatches[i]
print()
print('object', max(fq))
print('field stars', fq)
print('quad:', okq.quad)
# Index stars, by sweep (or "r" mag)...
# --which quads are they part of
#skdt = starkd_addr(index)
istars.sweep = array([startree_get_sweep(index.starkd, si) for si in istars.starind])
mystars = istars[I]
order = argsort(mystars.sweep)
print()
print()
print('Index stars:', end=' ')
for ms in mystars[order]:
print()
print('Star', ms.starind, 'sweep', ms.sweep, 'radec', ms.radec)
print('Field star(s) nearby:', len(c_s2f.get(ms.starind, [])))
for c in corrs[corrs.star == ms.starind]:
print(' field star', c.field, 'dist', c.dist, 'pixels')
myquads = quads[array([(ms.starind in q.stars) for q in quads])]
print('In %i quads' % len(myquads))
for q in myquads:
print(' quad %i: %i stars in the field' % (q.quad, sum(q.starsinfield)))
if q.allin:
print(' stars:', q.stars)
print(' correspondences for stars:', [c_s2f.get(s, None) for s in q.stars])
def plotshift(ixy,
rxy,
dcell=50,
ncells=18,
outfn=None,
W=None,
H=None,
hist=False,
nhistbins=21):
#histbinsize=None):
# correspondences we could have hit...
radius = dcell * sqrt(2.)
#print 'ixy', ixy.shape
#print 'rxy', rxy.shape
assert ((len(rxy) == 0) or (rxy.shape[1] == 2))
assert ((len(ixy) == 0) or (ixy.shape[1] == 2))
ix = ixy[:, 0]
iy = ixy[:, 1]
if W is None:
W = max(ix)
if H is None:
H = max(iy)
if len(rxy):
keep = (rxy[:, 0] > -dcell) * (rxy[:, 0] < W + dcell) * (
rxy[:, 1] > -dcell) * (rxy[:, 1] < H + dcell)
rxy = rxy[keep]
#print 'Cut to %i ref sources in range' % len(rxy)
cellsize = sqrt(W * H / ncells)
nw = int(round(W / cellsize))
nh = int(round(H / cellsize))
#print 'Grid cell size', cellsize
#print 'N cells', nw, 'x', nh
edgesx = linspace(0, W, nw + 1)
edgesy = linspace(0, H, nh + 1)
#print 'Edges:'
#print ' x:', edgesx
#print ' y:', edgesy
if len(rxy) == 0:
binx = array([])
biny = array([])
else:
binx = digitize(rxy[:, 0], edgesx)
biny = digitize(rxy[:, 1], edgesy)
binx = clip(binx - 1, 0, nw - 1)
biny = clip(biny - 1, 0, nh - 1)
bin = biny * nw + binx
clf()
for i in range(nh):
for j in range(nw):
thisbin = i * nw + j
R = (bin == thisbin)
#print 'cell %i, %i' % (j, i)
#print '%i ref sources' % sum(R)
matchdx = []
if sum(R) > 0:
(inds, dists) = spherematch.match(rxy[R, :], ixy, radius)
#print 'Found %i matches within %g pixels' % (len(dists), radius)
ri = inds[:, 0]
# un-cut ref inds...
ri = (flatnonzero(R))[ri]
ii = inds[:, 1]
matchx = rxy[ri, 0]
matchy = rxy[ri, 1]
matchdx = ix[ii] - matchx
matchdy = iy[ii] - matchy
#print 'All matches:'
#for dx,dy in zip(matchdx,matchdy):
# print ' %.1f, %.1f' % (dx,dy)
ok = (matchdx >= -dcell) * (matchdx <= dcell) * (
matchdy >= -dcell) * (matchdy <= dcell)
matchdx = matchdx[ok]
matchdy = matchdy[ok]
#print 'Cut to %i within %g x %g square' % (sum(ok), dcell*2, dcell*2)
#print 'Cut matches:'
#for dx,dy in zip(matchdx,matchdy):
# print ' %.1f, %.1f' % (dx,dy)
# Subplot places plots left-to-right, TOP-to-BOTTOM.
subplot(nh, nw, 1 + ((nh - i - 1) * nw + j))
if len(matchdx) > 0:
#plot(matchdx, matchdy, 'ro', mec='r', mfc='r', ms=5, alpha=0.2)
#plot(matchdx, matchdy, 'ro', mec='r', mfc='none', ms=5, alpha=0.2)
if hist:
#if histbinsize is None:
# histbinsize = dcell / 10.
edges = linspace(-dcell, dcell, nhistbins + 1)
(H, xe, ye) = histogram2d(matchdx,
matchdy,
bins=(edges, edges))
imshow(H.T,
extent=(min(xe), max(xe), min(ye), max(ye)),
aspect='auto',
origin='lower',
interpolation='nearest')
text(dcell,
dcell,
'%i' % H.max(),
color='y',
horizontalalignment='right',
verticalalignment='top')
else:
plot(matchdx, matchdy, 'r.', alpha=0.3)
if hist:
axhline(0, color='b', alpha=0.8)
axvline(0, color='b', alpha=0.8)
else:
axhline(0, color='k', alpha=0.5)
axvline(0, color='k', alpha=0.5)
if i == 0 and j == 0:
xticks([-dcell, 0, dcell])
yticks([-dcell, 0, dcell])
else:
xticks([], [])
yticks([], [])
axis('scaled')
axis([-dcell, dcell, -dcell, dcell])
if outfn is not None:
#print 'Saving', outfn
savefig(outfn)
def showSipSolutions(srcs, wcs0, andDir, x0, y0, W, H, filterName, plotPrefix):
'''
srcs: afw Catalog of sources
wcs0: original WCS
andDir: astrometry_net_data directory
'''
imargs = dict(imageSize=(W, H), filterName=filterName, x0=x0, y0=y0)
# Set up astrometry_net_data
os.environ['ASTROMETRY_NET_DATA_DIR'] = andDir
andConfig = measAstrom.AstrometryNetDataConfig()
fn = os.path.join(andDir, 'andConfig.py')
andConfig.load(fn)
# Set up meas_astrom
conf = measAstrom.ANetBasicAstrometryConfig(sipOrder=4)
ast = measAstrom.ANetBasicAstrometryTask(conf,
andConfig,
logLevel=Log.DEBUG)
# What reference sources are in the original WCS
refs = ast.getReferenceSourcesForWcs(wcs0, **imargs)
print('Got', len(refs), 'reference objects for initial WCS')
# How does a straight TAN solution look?
conf2 = measAstrom.ANetBasicAstrometryConfig(sipOrder=4,
calculateSip=False)
ast2 = measAstrom.ANetBasicAstrometryTask(conf2,
andConfig,
logLevel=Log.DEBUG)
solve = ast2.determineWcs2(srcs, **imargs)
tanwcs = solve.tanWcs
# How about if we fit a SIP WCS using the *original* WCS?
wcs2 = ast.getSipWcsFromWcs(wcs0, (W, H), x0=x0, y0=y0)
# (We determineWcs() for a SIP solution below...)
# Make some plots in pixel space by pushing ref sources through WCSes
rx0, ry0 = [], []
rx2, ry2 = [], []
rx3, ry3 = [], []
for src in refs:
xy = wcs0.skyToPixel(src.getCoord())
rx0.append(xy[0])
ry0.append(xy[1])
xy = tanwcs.skyToPixel(src.getCoord())
rx2.append(xy[0])
ry2.append(xy[1])
xy = wcs2.skyToPixel(src.getCoord())
rx3.append(xy[0])
ry3.append(xy[1])
rx0 = np.array(rx0)
ry0 = np.array(ry0)
rx2 = np.array(rx2)
ry2 = np.array(ry2)
rx3 = np.array(rx3)
ry3 = np.array(ry3)
x = np.array([src.getX() for src in srcs])
y = np.array([src.getY() for src in srcs])
from astrometry.libkd.spherematch import match
from astrometry.util.plotutils import plothist, PlotSequence
ps = PlotSequence(plotPrefix)
# Match up various sources...
R = 2.
II, d = match(np.vstack((x, y)).T, np.vstack((rx0, ry0)).T, R)
I = II[:, 0]
J = II[:, 1]
pa = dict(range=((-R, R), (-R, R)))
plt.clf()
plothist(x[I] - rx0[J], y[I] - ry0[J], 200, **pa)
plt.title('Source positions - Reference positions (initial WCS)')
plt.xlabel('delta-X (pixels)')
plt.ylabel('delta-Y (pixels)')
ps.savefig()
II, d = match(np.vstack((x, y)).T, np.vstack((rx2, ry2)).T, R)
I = II[:, 0]
J = II[:, 1]
plt.clf()
plothist(x[I] - rx2[J], y[I] - ry2[J], 200, **pa)
plt.title('Source positions - Reference positions (TAN WCS)')
plt.xlabel('delta-X (pixels)')
plt.ylabel('delta-Y (pixels)')
ps.savefig()
II, d = match(np.vstack((x, y)).T, np.vstack((rx3, ry3)).T, R)
I = II[:, 0]
J = II[:, 1]
plt.clf()
plothist(x[I] - rx3[J], y[I] - ry3[J], 200, **pa)
plt.title('Source positions - Reference positions (SIP WCS #2)')
plt.xlabel('delta-X (pixels)')
plt.ylabel('delta-Y (pixels)')
ps.savefig()
II, d = match(np.vstack((rx0, ry0)).T, np.vstack((rx3, ry3)).T, R)
I = II[:, 0]
J = II[:, 1]
plt.clf()
plothist(rx0[I] - rx3[J], ry0[I] - ry3[J], 200, **pa)
plt.title(
'Reference positions (Original WCS) - Reference positions (SIP WCS #2)'
)
plt.xlabel('delta-X (pixels)')
plt.ylabel('delta-Y (pixels)')
ps.savefig()
matches = solve.tanMatches
msx, msy = [], []
mrx, mry = [], []
for m in matches:
ref, src = m.first, m.second
xy = tanwcs.skyToPixel(ref.getCoord())
mrx.append(xy[0])
mry.append(xy[1])
msx.append(src.getX())
msy.append(src.getY())
plt.clf()
plt.plot(x, y, 'r.')
plt.plot(msx, msy, 'o', mec='r')
plt.plot(rx0, ry0, 'g.')
plt.plot(mrx, mry, 'gx')
plt.title('TAN matches')
ps.savefig()
# Get SIP solution (4th order)
solve = ast.determineWcs2(srcs, **imargs)
wcs1 = solve.sipWcs
matches = solve.sipMatches
msx, msy = [], []
mrx, mry = [], []
for m in matches:
ref, src = m.first, m.second
xy = tanwcs.skyToPixel(ref.getCoord())
mrx.append(xy[0])
mry.append(xy[1])
msx.append(src.getX())
msy.append(src.getY())
plt.clf()
plt.plot(x, y, 'r.')
plt.plot(msx, msy, 'o', mec='r')
plt.plot(rx0, ry0, 'g.')
plt.plot(mrx, mry, 'gx')
plt.title('SIP matches')
ps.savefig()
rx1, ry1 = [], []
for src in refs:
xy = wcs1.skyToPixel(src.getCoord())
rx1.append(xy[0])
ry1.append(xy[1])
rx1 = np.array(rx1)
ry1 = np.array(ry1)
plt.clf()
plt.plot(x, y, 'o', mec='r', mfc='none')
plt.plot(rx0, ry0, 'bx')
plt.plot(rx1, ry1, 'g+')
plt.plot(rx2, ry2, 'mx')
plt.plot(rx3, ry3, 'r+')
ps.savefig()
plt.axis([x0, x0 + 500, y0, y0 + 500])
ps.savefig()
II, d = match(np.vstack((x, y)).T, np.vstack((rx1, ry1)).T, R)
I = II[:, 0]
J = II[:, 1]
plt.clf()
plothist(x[I] - rx1[J], y[I] - ry1[J], 200, **pa)
plt.title('Source positions - Reference positions (SIP WCS)')
plt.xlabel('delta-X (pixels)')
plt.ylabel('delta-Y (pixels)')
ps.savefig()
def OLD_radec_to_sdss_rcf(ra, dec, spherematch=True, radius=0, tablefn=None, contains=False):
# This file is generated by merging the files "dr7_e.fits", "dr7_g.fits", and "dr7_a.fits",
# whose construction is described in http://trac.astrometry.net/browser/trunk/projects/sdss-tests/README
# (and in comments below that I didn't notice before writing this)
if tablefn is None:
tablefn = find_data_file('dr7fields.fits')
sdss = table_fields(tablefn)
if sdss is None:
print('Failed to read table of SDSS fields from file', tablefn)
raise Exception('Failed to read table of SDSS fields from file: "' + str(tablefn) + '"')
sdssxyz = radectoxyz(sdss.ra, sdss.dec)
## HACK - magic 13x9 arcmin.
if radius == 0:
radius = sqrt(13.**2 + 9.**2)/2.
radius2 = arcmin2distsq(radius)
if not spherematch:
rcfs = []
for r,d in broadcast(ra,dec):
xyz = radectoxyz(r,d)
dist2s = sum((xyz - sdssxyz)**2, axis=1)
I = flatnonzero(dist2s < radius2)
if False:
print('I:', I)
print('fields:', sdss[I].run, sdss[I].field, sdss[I].camcol)
print('RA', sdss[I].ra)
print('Dec', sdss[I].dec)
rcfs.append(zip(sdss[I].run, sdss[I].camcol, sdss[I].field, sdss[I].ra, sdss[I].dec))
else:
from astrometry.libkd import spherematch
rds = array([x for x in broadcast(ra,dec)])
xyz = radectoxyz(rds[:,0], rds[:,1]).astype(double)
(inds,dists) = spherematch.match(xyz, sdssxyz, sqrt(radius2))
#print 'found %i matches' % len(inds)
if len(inds) == 0:
return []
#print 'inds:', inds.shape
I = np.argsort(dists[:,0])
#print 'dists:', dists.shape
inds = inds[I,:]
rcfs = [[] for i in range(len(rds))]
cols = sdss.columns()
gotem = False
if contains:
if 'ramin' in cols and 'ramax' in cols and 'decmin' in cols and 'decmax' in cols:
gotem = True
for i,j in inds:
(r,d) = rds[i]
if r >= sdss.ramin[j] and r <= sdss.ramax[j] and d >= sdss.decmin[j] and d <= sdss.decmax[j]:
rcfs[i].append((sdss.run[j], sdss.camcol[j], sdss.field[j], sdss.ra[j], sdss.dec[j]))
print('%i fields contain the first query RA,Dec' % len(rcfs[0]))
else:
print('you requested fields *containing* the query RA,Dec,')
print('but the fields list file \"%s\" doesn\'t contain RAMIN,RAMAX,DECMIN, and DECMAX columns' % tablefn)
if not gotem:
for i,j in inds:
rcfs[i].append((sdss.run[j], sdss.camcol[j], sdss.field[j], sdss.ra[j], sdss.dec[j]))
if isscalar(ra) and isscalar(dec):
return rcfs[0]
return rcfs
def OLD_radec_to_sdss_rcf(ra,
dec,
spherematch=True,
radius=0,
tablefn=None,
contains=False):
# This file is generated by merging the files "dr7_e.fits", "dr7_g.fits", and "dr7_a.fits",
# whose construction is described in http://trac.astrometry.net/browser/trunk/projects/sdss-tests/README
# (and in comments below that I didn't notice before writing this)
if tablefn is None:
tablefn = find_data_file('dr7fields.fits')
sdss = table_fields(tablefn)
if sdss is None:
print('Failed to read table of SDSS fields from file', tablefn)
raise Exception('Failed to read table of SDSS fields from file: "' +
str(tablefn) + '"')
sdssxyz = radectoxyz(sdss.ra, sdss.dec)
## HACK - magic 13x9 arcmin.
if radius == 0:
radius = sqrt(13.**2 + 9.**2) / 2.
radius2 = arcmin2distsq(radius)
if not spherematch:
rcfs = []
for r, d in broadcast(ra, dec):
xyz = radectoxyz(r, d)
dist2s = sum((xyz - sdssxyz)**2, axis=1)
I = flatnonzero(dist2s < radius2)
if False:
print('I:', I)
print('fields:', sdss[I].run, sdss[I].field, sdss[I].camcol)
print('RA', sdss[I].ra)
print('Dec', sdss[I].dec)
rcfs.append(
zip(sdss[I].run, sdss[I].camcol, sdss[I].field, sdss[I].ra,
sdss[I].dec))
else:
from astrometry.libkd import spherematch
rds = array([x for x in broadcast(ra, dec)])
xyz = radectoxyz(rds[:, 0], rds[:, 1]).astype(double)
(inds, dists) = spherematch.match(xyz, sdssxyz, sqrt(radius2))
#print 'found %i matches' % len(inds)
if len(inds) == 0:
return []
#print 'inds:', inds.shape
I = np.argsort(dists[:, 0])
#print 'dists:', dists.shape
inds = inds[I, :]
rcfs = [[] for i in range(len(rds))]
cols = sdss.columns()
gotem = False
if contains:
if 'ramin' in cols and 'ramax' in cols and 'decmin' in cols and 'decmax' in cols:
gotem = True
for i, j in inds:
(r, d) = rds[i]
if r >= sdss.ramin[j] and r <= sdss.ramax[
j] and d >= sdss.decmin[j] and d <= sdss.decmax[j]:
rcfs[i].append(
(sdss.run[j], sdss.camcol[j], sdss.field[j],
sdss.ra[j], sdss.dec[j]))
print('%i fields contain the first query RA,Dec' %
len(rcfs[0]))
else:
print('you requested fields *containing* the query RA,Dec,')
print(
'but the fields list file \"%s\" doesn\'t contain RAMIN,RAMAX,DECMIN, and DECMAX columns'
% tablefn)
if not gotem:
for i, j in inds:
rcfs[i].append((sdss.run[j], sdss.camcol[j], sdss.field[j],
sdss.ra[j], sdss.dec[j]))
if isscalar(ra) and isscalar(dec):
return rcfs[0]
return rcfs
from pylab import *
from numpy import *
import os
if __name__ == '__main__':
parser = OptionParser()
parser.add_option('-p', '--prefix', dest='prefix', help='Prefix for output plot names')
parser.add_option('-r', '--range', dest='range', type='float', help='Set search radius range (in arcsec) of stars-1 plot, default 15')
parser.set_defaults(prefix='', range=15.)
opt,args = parser.parse_args()
if 'plots' in args: # DEBUG!
cat = fits_table('cat2.fits')
xyz = radectoxyz(cat.ra, cat.dec)
R = 15.
inds,dists = match(xyz, xyz, deg2rad(R/3600.))
notself = (inds[:,0] != inds[:,1])
clf()
hist(rad2deg(dists[notself]) * 3600., 200)
title('ImSim reference catalog')
xlabel('Distance between pairs of sources (arcsec)')
ylabel('Counts')
xlim(0, R)
savefig('cat-stars-1.png')
cat = fits_table('stars3.fits')
xyz = radectoxyz(cat.ra, cat.dec)
R = 15.
inds,dists = match(xyz, xyz, deg2rad(R/3600.))
notself = (inds[:,0] != inds[:,1])
clf()
from pylab import *
from numpy import *
import os
if __name__ == '__main__':
parser = OptionParser()
parser.add_option('-p', '--prefix', dest='prefix', help='Prefix for output plot names')
parser.add_option('-r', '--range', dest='range', type='float', help='Set search radius range (in arcsec) of stars-1 plot, default 15')
parser.set_defaults(prefix='', range=15.)
opt,args = parser.parse_args()
if 'plots' in args: # DEBUG!
cat = fits_table('cat2.fits')
xyz = radectoxyz(cat.ra, cat.dec)
R = 15.
inds,dists = match(xyz, xyz, deg2rad(R/3600.))
notself = (inds[:,0] != inds[:,1])
clf()
hist(rad2deg(dists[notself]) * 3600., 200)
title('ImSim reference catalog')
xlabel('Distance between pairs of sources (arcsec)')
ylabel('Counts')
xlim(0, R)
savefig('cat-stars-1.png')
cat = fits_table('stars3.fits')
xyz = radectoxyz(cat.ra, cat.dec)
R = 15.
inds,dists = match(xyz, xyz, deg2rad(R/3600.))
notself = (inds[:,0] != inds[:,1])
clf()
# This file is part of libkd.
# Licensed under a 3-clause BSD style license - see LICENSE
from astrometry.libkd import spherematch
import numpy as np
from time import time
N1 = 1000
N2 = 1000
D = 2
r = 0.02
x1 = np.random.rand(N1, D)
x2 = np.random.rand(N2, D)
t0 = time()
(inds, dists) = spherematch.match(x1, x2, r)
dt = time() - t0
print 'spherematch.match: found', len(inds), 'pairs in', int(dt * 1000.), 'ms'
order = np.argsort(inds[:, 0] * N2 + inds[:, 1])
inds = inds[order]
dists = dists[order]
t0 = time()
pairs = []
truedists = []
for i in range(N1):
pt1 = x1[i, :]
d2s = np.sum((x2 - pt1)**2, axis=1)
good = np.where(d2s <= r**2)[0]
def whynot(field, index, qidx, wcs):
# find index stars in the field.
(ra,dec) = wcs.get_radec_center()
rad = arcsec2deg(wcs.get_pixel_scale() * hypot(wcs.get_width(), wcs.get_height()))
(xyz, radec, starinds) = index_search_stars(index, ra, dec, rad)
print 'xyz', xyz.shape
print 'radec', radec.shape
print 'starinds', starinds.shape
istars = tabledata()
istars.xyz = xyz
istars.radec = radec
istars.starind = starinds
W,H = wcs.get_width(), wcs.get_height()
pix = array([wcs.radec2pixelxy(r, d) for (r,d) in radec])
print 'pix', pix.shape
# within image bounds
I = (pix[:,0] > 0) * (pix[:,0] < W) * (pix[:,1] > 0) * (pix[:,1] < H)
# find nearby pairs of stars...
nsigma = 3
pixeljitter = 1
sigma = hypot(index.index_jitter / wcs.get_pixel_scale(), pixeljitter)
rad = nsigma * sigma
fieldxy = vstack((field.x, field.y)).T
print 'field', fieldxy.shape
(cinds, cdists) = match(pix, fieldxy, rad)
print 'matches:', cinds.shape
#print cdists.shape
corrs = tabledata()
corrs.dist = cdists[:,0]
corrs.star = starinds[cinds[:,0]]
corrs.field = cinds[:,1]
allquads = []
# All quads built from stars in the field...
for starind in starinds[I]:
#print qidx, starind
quads = qidxfile_get_quad_list(qidxfile_addr(qidx), starind)
#print 'quads:', quads.shape
allquads.append(quads)
allquads = unique(hstack(allquads))
print '%i unique quads touch stars in the field' % len(allquads)
'''
"quads" object: all quads that touch index stars in this field.
.quad : (int) quad index
.stars : (DQ x int) star indices
.starsinfield: (DQ x bool) stars in field
'''
quads = tabledata()
quads.quad = allquads
qstars = quadfile_get_stars_for_quads(quadfile_addr(index), quads.quad)
print 'stars in quads:', qstars.shape
#print qstars
quads.stars = qstars
quads.starsinfield = array([[s in starinds[I] for s in q] for q in qstars])
#print quads.starsinfield
allin = quads.starsinfield.min(axis=1)
#print quads.allin
quads.allin = allin
quadsin = quads[allin]
print '%i quads use stars that are in the field' % (len(quadsin))
print 'stars:', starinds
c_s2f = {}
for c in corrs: #i in range(len(corrs)):
#print 'corr', c
if not c.star in c_s2f:
c_s2f[c.star] = []
c_s2f[c.star].append(c.field)
#c_s2f[corrs.star[i]]
#print c_s2f
# [[[213], [35], [265], [63]], [[186]], [[]], [[11], [19]], ...]
# For each quad, for each star in the quad, the list of field stars corresponding.
fq = []
for q in quadsin.stars:
fq1 = []
for s in q:
if s in c_s2f:
fq1.append(c_s2f[s])
else:
fq1.append([])
fq.append(fq1)
#print fq
# For each quad, the list of sets of field stars corresponding.
# [[[213, 35, 265, 63]], [], [],
fq2 = []
for q in fq:
#print 'q:', q
#ac = allcombinations([q[0]], q[1:])
#ac = allcombinations([[]], q)
#print '--> ac:', ac
fq2.append(allcombinations([[]], q))
#print fq2
quadsin.fq2 = fq2
hasf = array([len(x) > 0 for x in quadsin.fq2])
#print 'hasf:', hasf
okquads = quadsin[hasf]
#forder = argsort([max(x) for x in okquads.fq2])
#okquads = okquads[forder]
print 'ok quads:', len(okquads)
print 'quad nums:', okquads.quad
print 'stars:', okquads.stars
print 'field stars:', okquads.fq2
#qmatches = table_data()
#fqs = []
#qs = []
#for okq,fq in zip(okquads, okquads.fq2):
# fqs = fqs + fq
# qs.append(okq)
#qmatches.fieldquad = fqs
qmatches = []
for okq,fqs in zip(okquads, okquads.fq2):
for fq in fqs:
#print 'field stars', fq
#print 'quad:', okq.quad
qmatches.append((fq, okq))
forder = argsort([max(fq) for fq,okq in qmatches])
#print 'forder', forder
print
print 'Quads in the order they will be found'
for i in forder:
fq,okq = qmatches[i]
print
print 'object', max(fq)
print 'field stars', fq
print 'quad:', okq.quad
# Index stars, by sweep (or "r" mag)...
# --which quads are they part of
#skdt = starkd_addr(index)
istars.sweep = array([startree_get_sweep(index.starkd, si) for si in istars.starind])
mystars = istars[I]
order = argsort(mystars.sweep)
print
print
print 'Index stars:',
for ms in mystars[order]:
print
print 'Star', ms.starind, 'sweep', ms.sweep, 'radec', ms.radec
print 'Field star(s) nearby:', len(c_s2f.get(ms.starind, []))
for c in corrs[corrs.star == ms.starind]:
print ' field star', c.field, 'dist', c.dist, 'pixels'
myquads = quads[array([(ms.starind in q.stars) for q in quads])]
print 'In %i quads' % len(myquads)
for q in myquads:
print ' quad %i: %i stars in the field' % (q.quad, sum(q.starsinfield))
if q.allin:
print ' stars:', q.stars
print ' correspondences for stars:', [c_s2f.get(s, None) for s in q.stars]
def plotshift(ixy, rxy, dcell=50, ncells=18, outfn=None, W=None, H=None, hist=False,
nhistbins=21):
print 'plotshift...'
# correspondences we could have hit...
radius = dcell * sqrt(2.)
print 'ixy', ixy.shape
print 'rxy', rxy.shape
print 'asserts'
assert((len(rxy) == 0) or (rxy.shape[1] == 2))
assert((len(ixy) == 0) or (ixy.shape[1] == 2))
print 'slice'
ix = ixy[:,0]
iy = ixy[:,1]
print 'w,h'
if W is None:
W = max(ix)
if H is None:
H = max(iy)
print 'rxy'
if len(rxy):
keep = (rxy[:,0] > -dcell) * (rxy[:,0] < W+dcell) * (rxy[:,1] > -dcell) * (rxy[:,1] < H+dcell)
rxy = rxy[keep]
print 'Cut to %i ref sources in range' % len(rxy)
print 'bin...'
cellsize = sqrt(W * H / ncells)
nw = int(round(W / cellsize))
nh = int(round(H / cellsize))
#print 'Grid cell size', cellsize
#print 'N cells', nw, 'x', nh
edgesx = linspace(0, W, nw+1)
edgesy = linspace(0, H, nh+1)
#print 'Edges:'
#print ' x:', edgesx
#print ' y:', edgesy
if len(rxy) == 0:
binx = array([])
biny = array([])
else:
binx = digitize(rxy[:,0], edgesx)
biny = digitize(rxy[:,1], edgesy)
binx = clip(binx - 1, 0, nw-1)
biny = clip(biny - 1, 0, nh-1)
bin = biny * nw + binx
print 'plot...'
plt.clf()
for i in range(nh):
for j in range(nw):
print 'cell %i, %i' % (j, i)
thisbin = i * nw + j
R = (bin == thisbin)
print '%i ref sources' % sum(R)
matchdx = []
if sum(R) > 0:
print 'match...'
(inds,dists) = spherematch.match(rxy[R,:], ixy, radius)
#print 'Found %i matches within %g pixels' % (len(dists), radius)
ri = inds[:,0]
# un-cut ref inds...
ri = (flatnonzero(R))[ri]
ii = inds[:,1]
matchx = rxy[ri,0]
matchy = rxy[ri,1]
matchdx = ix[ii] - matchx
matchdy = iy[ii] - matchy
#print 'All matches:'
#for dx,dy in zip(matchdx,matchdy):
# print ' %.1f, %.1f' % (dx,dy)
ok = (matchdx >= -dcell) * (matchdx <= dcell) * (matchdy >= -dcell) * (matchdy <= dcell)
matchdx = matchdx[ok]
matchdy = matchdy[ok]
#print 'Cut to %i within %g x %g square' % (sum(ok), dcell*2, dcell*2)
#print 'Cut matches:'
#for dx,dy in zip(matchdx,matchdy):
# print ' %.1f, %.1f' % (dx,dy)
# Subplot places plots left-to-right, TOP-to-BOTTOM.
subplot(nh, nw, 1 + ((nh - i - 1)*nw + j))
if len(matchdx) > 0:
#plot(matchdx, matchdy, 'ro', mec='r', mfc='r', ms=5, alpha=0.2)
#plot(matchdx, matchdy, 'ro', mec='r', mfc='none', ms=5, alpha=0.2)
if hist:
#if histbinsize is None:
# histbinsize = dcell / 10.
edges = linspace(-dcell, dcell, nhistbins+1)
(H,xe,ye) = histogram2d(matchdx, matchdy, bins=(edges,edges))
imshow(H.T, extent=(min(xe), max(xe), min(ye), max(ye)),
aspect='auto', origin='lower', interpolation='nearest')
text(dcell, dcell, '%i' % H.max(), color='y',
horizontalalignment='right', verticalalignment='top')
else:
plot(matchdx, matchdy, 'r.', alpha=0.3)
if hist:
axhline(0, color='b', alpha=0.8)
axvline(0, color='b', alpha=0.8)
else:
axhline(0, color='k', alpha=0.5)
axvline(0, color='k', alpha=0.5)
if i == 0 and j == 0:
xticks([-dcell,0,dcell])
yticks([-dcell,0,dcell])
else:
xticks([],[])
yticks([],[])
axis('scaled')
axis([-dcell, dcell, -dcell, dcell])
if outfn is not None:
#print 'Saving', outfn
savefig(outfn)
def plotCorrespondences(imgsources, refsources, matches, wcs, W, H, prefix):
ix = np.array([s.getXAstrom() for s in imgsources])
iy = np.array([s.getYAstrom() for s in imgsources])
rx, ry = [], []
for r in refsources:
xy = wcs.skyToPixel(r.getRaDec())
rx.append(xy[0])
ry.append(xy[1])
rx = np.array(rx)
ry = np.array(ry)
# correspondences we could have hit...
ixy = np.vstack((ix, iy)).T
rxy = np.vstack((rx, ry)).T
dcell = 50.
radius = dcell * np.sqrt(2.)
# print 'ixy', ixy.shape
# print 'rxy', rxy.shape
if False:
(inds, dists) = spherematch.match(rxy, ixy, radius)
mi = inds[:, 0]
ii = inds[:, 1]
matchx = rx[mi]
matchy = ry[mi]
matchdx = ix[ii] - matchx
matchdy = iy[ii] - matchy
ok = (matchdx >= -dcell) * (matchdx <= dcell) * (matchdy >= -dcell) * (
matchdy <= dcell)
matchx = matchx[ok]
matchy = matchy[ok]
matchdx = matchdx[ok]
matchdy = matchdy[ok]
mi = mi[ok]
ii = ii[ok]
print('Found %i matches within %g pixels' % (len(dists), radius))
ncells = 18.
cellsize = np.sqrt(W * H / ncells)
nw = int(round(W / cellsize))
nh = int(round(H / cellsize))
# print 'Grid cell size', cellsize
# print 'N cells', nw, 'x', nh
edgesx = np.linspace(0, W, nw + 1)
edgesy = np.linspace(0, H, nh + 1)
binx = np.digitize(rx, edgesx)
biny = np.digitize(ry, edgesy)
binx = np.clip(binx - 1, 0, nw - 1)
biny = np.clip(biny - 1, 0, nh - 1)
bin = biny * nw + binx
plt.clf()
for i in range(nh):
for j in range(nw):
thisbin = i * nw + j
R = (bin == thisbin)
# print 'cell %i, %i' % (j, i)
# print '%i ref sources' % sum(R)
if sum(R) == 0:
continue
(inds, dists) = spherematch.match(rxy[R, :], ixy, radius)
# print 'Found %i matches within %g pixels' % (len(dists), radius)
ri = inds[:, 0]
# un-cut ref inds...
ri = (np.flatnonzero(R))[ri]
ii = inds[:, 1]
matchx = rx[ri]
matchy = ry[ri]
matchdx = ix[ii] - matchx
matchdy = iy[ii] - matchy
ok = (matchdx >= -dcell) * (matchdx <= dcell) * (
matchdy >= -dcell) * (matchdy <= dcell)
# matchx = matchx[ok]
# matchy = matchy[ok]
matchdx = matchdx[ok]
matchdy = matchdy[ok]
# print 'Cut to %i within %g x %g square' % (sum(ok), dcell*2, dcell*2)
# Subplot places plots left-to-right, TOP-to-BOTTOM.
plt.subplot(nh, nw, 1 + ((nh - i - 1) * nw + j))
plt.plot(matchdx, matchdy, 'ro', mec='r', mfc='r', ms=5, alpha=0.2)
plt.plot(matchdx,
matchdy,
'ro',
mec='r',
mfc='none',
ms=5,
alpha=0.2)
plt.axhline(0, color='k', alpha=0.5)
plt.axvline(0, color='k', alpha=0.5)
plt.xticks([], [])
plt.yticks([], [])
plt.axis('scaled')
plt.axis([-dcell, dcell, -dcell, dcell])
fn = prefix + '-missed.png'
print('Saving', fn)
plt.savefig(fn)
# Licensed under a 3-clause BSD style license - see LICENSE
from __future__ import print_function
from astrometry.libkd import spherematch
import numpy as np
from time import time
N1 = 1000
N2 = 1000
D = 2
r = 0.02
x1 = np.random.rand(N1, D)
x2 = np.random.rand(N2, D)
t0 = time()
(inds,dists) = spherematch.match(x1, x2, r)
dt = time() - t0
print('spherematch.match: found', len(inds), 'pairs in', int(dt*1000.), 'ms')
order = np.argsort(inds[:,0]*N2 + inds[:,1])
inds = inds[order]
dists = dists[order]
t0 = time()
pairs = []
truedists = []
for i in range(N1):
pt1 = x1[i,:]
d2s = np.sum((x2 - pt1)**2, axis=1)
good = np.where(d2s <= r**2)[0]
# Licensed under a 3-clause BSD style license - see LICENSE
from __future__ import print_function
from astrometry.libkd import spherematch
import numpy as np
from time import time
N1 = 1000
N2 = 1000
D = 2
r = 0.02
x1 = np.random.rand(N1, D)
x2 = np.random.rand(N2, D)
t0 = time()
(inds, dists) = spherematch.match(x1, x2, r)
dt = time() - t0
print('spherematch.match: found', len(inds), 'pairs in', int(dt * 1000.), 'ms')
order = np.argsort(inds[:, 0] * N2 + inds[:, 1])
inds = inds[order]
dists = dists[order]
t0 = time()
pairs = []
truedists = []
for i in range(N1):
pt1 = x1[i, :]
d2s = np.sum((x2 - pt1)**2, axis=1)
good = np.where(d2s <= r**2)[0]
# Licensed under a 3-clause BSD style license - see LICENSE
from __future__ import print_function
from astrometry.libkd import spherematch
import numpy as np
from time import time
N1 = 1000
N2 = 1000
D = 2
r = 0.02
x1 = np.random.rand(N1, D)
x2 = np.random.rand(N2, D)
t0 = time()
(inds,dists) = spherematch.match(x1, x2, r)
dt = time() - t0
print('spherematch.match: found', len(inds), 'pairs in', int(dt*1000.), 'ms')
order = np.argsort(inds[:,0]*N2 + inds[:,1])
inds = inds[order]
dists = dists[order]
t0 = time()
pairs = []
truedists = []
for i in range(N1):
pt1 = x1[i,:]
d2s = np.sum((x2 - pt1)**2, axis=1)
good = np.where(d2s <= r**2)[0]
