def match_kdtree_catalog(wcs, catfn):
from astrometry.libkd.spherematch import (
tree_open,
tree_close,
tree_build_radec,
tree_free,
trees_match,
tree_permute,
)
from astrometry.libkd import spherematch_c
from astrometry.util.starutil_numpy import deg2dist, xyztoradec
import numpy as np
import sys
rc, dc = wcs.get_center()
rr = wcs.get_radius()
kd = tree_open(catfn)
kd2 = tree_build_radec(np.array([rc]), np.array([dc]))
r = deg2dist(rr)
I, J, nil = trees_match(kd, kd2, r, permuted=False)
# HACK
# I2,J,d = trees_match(kd, kd2, r)
xyz = spherematch_c.kdtree_get_positions(kd, I.astype(np.uint32))
# print 'I', I
I2 = tree_permute(kd, I)
# print 'I2', I2
tree_free(kd2)
tree_close(kd)
tra, tdec = xyztoradec(xyz)
return tra, tdec, I2
def other_passes(self, tile, tiles):
'''
Given tile number *tile*, return the obstatus rows for the other passes
on this tile center.
Returns: *otherpasses*, table object
'''
if tiles != self.tiles:
from astrometry.libkd.spherematch import match_radec
# Could also use the fact that the passes are offset from each other
# by a fixed index (15872 for decam)...
# Max separation is about 0.6 degrees for DECam...
#### FIXME for Mosaic this is much smaller... and the three passes
#### for a tile are not necessarily relatively close to each other.
I,J,d = match_radec(tile.ra, tile.dec, tiles.ra, tiles.dec, 1.)
# Omit 'tile' itself...
K = np.flatnonzero(tiles.tileid[J] != tile.tileid)
J = J[K]
return tiles[J]
if self.tiletree is None:
from astrometry.libkd.spherematch import tree_build_radec
self.tiletree = tree_build_radec(self.tiles.ra, self.tiles.dec)
from astrometry.libkd.spherematch import tree_search_radec
J = tree_search_radec(self.tiletree, tile.ra, tile.dec, 1.0)
# Omit 'tile' itself...
K = np.flatnonzero(tiles.tileid[J] != tile.tileid)
J = J[K]
return tiles[J]
def _match_tile(X):
tid, tile_ra, tile_dec, tile_obstime, tile_theta, tile_obsha, match_radius = X
loc_ra, loc_dec = xy2radec(hw, tile_ra, tile_dec, tile_obstime, tile_theta,
tile_obsha, stuck_x, stuck_y, False, 0)
kd = tree_build_radec(loc_ra, loc_dec)
I, J, d = trees_match(starkd, kd, match_radius)
print('Tile', tid, 'matched', len(I), 'stars')
if len(I):
res = tid, I, loc_ra[J], loc_dec[J], stuck_loc[J], np.rad2deg(
d) * 3600.
else:
res = None
return res
def match_kdtree_catalog(wcs, catfn):
from astrometry.libkd.spherematch import tree_open, tree_close, tree_build_radec, tree_free, trees_match, tree_permute
from astrometry.libkd import spherematch_c
from astrometry.util.starutil_numpy import deg2dist, xyztoradec
import numpy as np
import sys
rc,dc = wcs.get_center()
rr = wcs.get_radius()
kd = tree_open(catfn)
kd2 = tree_build_radec(np.array([rc]), np.array([dc]))
r = deg2dist(rr)
I,J,nil = trees_match(kd, kd2, r, permuted=False)
del kd2
xyz = kd.get_data(I.astype(np.uint32))
I = kd.permute(I)
del kd
tra,tdec = xyztoradec(xyz)
return tra, tdec, I
def match_kdtree_catalog(wcs, catfn):
from astrometry.libkd.spherematch import tree_open, tree_close, tree_build_radec, tree_free, trees_match, tree_permute
from astrometry.libkd import spherematch_c
from astrometry.util.starutil_numpy import deg2dist, xyztoradec
import numpy as np
import sys
rc,dc = wcs.get_center()
rr = wcs.get_radius()
kd = tree_open(catfn)
kd2 = tree_build_radec(np.array([rc]), np.array([dc]))
r = deg2dist(rr)
I,J,nil = trees_match(kd, kd2, r, permuted=False)
del kd2
xyz = kd.get_data(I.astype(np.uint32))
I = kd.permute(I)
del kd
tra,tdec = xyztoradec(xyz)
return tra, tdec, I
def bricks_touching_radec_box(self, bricks,
ralo, rahi, declo, dechi):
'''
Returns an index vector of the bricks that touch the given RA,Dec box.
'''
if bricks is None:
bricks = self.get_bricks_readonly()
if self.cache_tree and bricks == self.bricks:
from astrometry.libkd.spherematch import tree_build_radec, tree_search_radec
# Use kdtree
if self.bricktree is None:
self.bricktree = tree_build_radec(bricks.ra, bricks.dec)
# brick size
radius = np.sqrt(2.)/2. * self.bricksize
# + RA,Dec box size
radius = radius + degrees_between(ralo, declo, rahi, dechi) / 2.
dec = (dechi + declo) / 2.
c = (np.cos(np.deg2rad(rahi)) + np.cos(np.deg2rad(ralo))) / 2.
s = (np.sin(np.deg2rad(rahi)) + np.sin(np.deg2rad(ralo))) / 2.
ra = np.rad2deg(np.arctan2(s, c))
J = tree_search_radec(self.bricktree, ra, dec, radius)
I = J[np.nonzero((bricks.ra1[J] <= rahi ) * (bricks.ra2[J] >= ralo) *
(bricks.dec1[J] <= dechi) * (bricks.dec2[J] >= declo))[0]]
return I
if rahi < ralo:
# Wrap-around
print('In Dec slice:', len(np.flatnonzero((bricks.dec1 <= dechi) *
(bricks.dec2 >= declo))))
print('Above RAlo=', ralo, ':', len(np.flatnonzero(bricks.ra2 >= ralo)))
print('Below RAhi=', rahi, ':', len(np.flatnonzero(bricks.ra1 <= rahi)))
print('In RA slice:', len(np.nonzero(np.logical_or(bricks.ra2 >= ralo,
bricks.ra1 <= rahi))))
I, = np.nonzero(np.logical_or(bricks.ra2 >= ralo, bricks.ra1 <= rahi) *
(bricks.dec1 <= dechi) * (bricks.dec2 >= declo))
print('In RA&Dec slice', len(I))
else:
I, = np.nonzero((bricks.ra1 <= rahi ) * (bricks.ra2 >= ralo) *
(bricks.dec1 <= dechi) * (bricks.dec2 >= declo))
return I
def bricks_touching_radec_box(self, bricks,
ralo, rahi, declo, dechi):
'''
Returns an index vector of the bricks that touch the given RA,Dec box.
'''
if bricks is None:
bricks = self.get_bricks_readonly()
if self.cache_tree and bricks == self.bricks:
from astrometry.libkd.spherematch import tree_build_radec, tree_search_radec
# Use kdtree
if self.bricktree is None:
self.bricktree = tree_build_radec(bricks.ra, bricks.dec)
# brick size
radius = np.sqrt(2.)/2. * self.bricksize
# + RA,Dec box size
radius = radius + degrees_between(ralo, declo, rahi, dechi) / 2.
dec = (dechi + declo) / 2.
c = (np.cos(np.deg2rad(rahi)) + np.cos(np.deg2rad(ralo))) / 2.
s = (np.sin(np.deg2rad(rahi)) + np.sin(np.deg2rad(ralo))) / 2.
ra = np.rad2deg(np.arctan2(s, c))
J = tree_search_radec(self.bricktree, ra, dec, radius)
I = J[np.nonzero((bricks.ra1[J] <= rahi ) * (bricks.ra2[J] >= ralo) *
(bricks.dec1[J] <= dechi) * (bricks.dec2[J] >= declo))[0]]
return I
if rahi < ralo:
# Wrap-around
print('In Dec slice:', len(np.flatnonzero((bricks.dec1 <= dechi) *
(bricks.dec2 >= declo))))
print('Above RAlo=', ralo, ':', len(np.flatnonzero(bricks.ra2 >= ralo)))
print('Below RAhi=', rahi, ':', len(np.flatnonzero(bricks.ra1 <= rahi)))
print('In RA slice:', len(np.nonzero(np.logical_or(bricks.ra2 >= ralo,
bricks.ra1 <= rahi))))
I, = np.nonzero(np.logical_or(bricks.ra2 >= ralo, bricks.ra1 <= rahi) *
(bricks.dec1 <= dechi) * (bricks.dec2 >= declo))
print('In RA&Dec slice', len(I))
else:
I, = np.nonzero((bricks.ra1 <= rahi ) * (bricks.ra2 >= ralo) *
(bricks.dec1 <= dechi) * (bricks.dec2 >= declo))
return I
def match_kdtree_catalog(wcs, catfn):
from astrometry.libkd.spherematch import tree_open, tree_close, tree_build_radec, tree_free, trees_match, tree_permute
from astrometry.libkd import spherematch_c
from astrometry.util.starutil_numpy import deg2dist, xyztoradec
import numpy as np
import sys
rc, dc = wcs.get_center()
rr = wcs.get_radius()
kd = tree_open(catfn)
kd2 = tree_build_radec(np.array([rc]), np.array([dc]))
r = deg2dist(rr)
I, J, nil = trees_match(kd, kd2, r, permuted=False)
# HACK
#I2,J,d = trees_match(kd, kd2, r)
xyz = spherematch_c.kdtree_get_positions(kd, I.astype(np.uint32))
#print 'I', I
I2 = tree_permute(kd, I)
#print 'I2', I2
tree_free(kd2)
tree_close(kd)
tra, tdec = xyztoradec(xyz)
return tra, tdec, I2
def plot_wcs_outline(wcsfn,
plotfn,
W=256,
H=256,
width=36,
zoom=True,
zoomwidth=3.6,
grid=10,
hd=False,
hd_labels=False,
tycho2=False):
anutil.log_init(3)
#anutil.log_set_level(3)
wcs = anutil.Tan(wcsfn, 0)
ra, dec = wcs.radec_center()
plot = ps.Plotstuff(outformat='png', size=(W, H), rdw=(ra, dec, width))
plot.linestep = 1.
plot.color = 'verydarkblue'
plot.plot('fill')
plot.fontsize = 12
#plot.color = 'gray'
# dark gray
plot.rgb = (0.3, 0.3, 0.3)
if grid is not None:
plot.plot_grid(*([grid] * 4))
plot.rgb = (0.4, 0.6, 0.4)
ann = plot.annotations
ann.NGC = ann.bright = ann.HD = 0
ann.constellations = 1
ann.constellation_labels = 1
ann.constellation_labels_long = 1
plot.plot('annotations')
plot.stroke()
ann.constellation_labels = 0
ann.constellation_labels_long = 0
ann.constellation_lines = 0
ann.constellation_markers = 1
plot.markersize = 3
plot.rgb = (0.4, 0.6, 0.4)
plot.plot('annotations')
plot.fill()
ann.constellation_markers = 0
ann.bright_labels = False
ann.bright = True
plot.markersize = 2
if zoom >= 2:
ann.bright_labels = True
plot.plot('annotations')
ann.bright = False
ann.bright_labels = False
plot.fill()
if hd:
ann.HD = True
ann.HD_labels = hd_labels
ps.plot_annotations_set_hd_catalog(ann, settings.HENRY_DRAPER_CAT)
plot.plot('annotations')
plot.stroke()
ann.HD = False
ann.HD_labels = False
if tycho2 and settings.TYCHO2_KD:
from astrometry.libkd.spherematch import tree_open, tree_close, tree_build_radec, tree_free, trees_match
from astrometry.libkd import spherematch_c
from astrometry.util.starutil_numpy import deg2dist, xyztoradec
import numpy as np
import sys
kd = tree_open(settings.TYCHO2_KD)
# this is a bit silly: build a tree with a single point, then do match()
kd2 = tree_build_radec(np.array([ra]), np.array([dec]))
r = deg2dist(width * np.sqrt(2.) / 2.)
#r = deg2dist(wcs.radius())
I, nil, nil = trees_match(kd, kd2, r, permuted=False)
del nil
#print 'Matched', len(I)
xyz = spherematch_c.kdtree_get_positions(kd, I)
del I
tree_free(kd2)
tree_close(kd)
#print >>sys.stderr, 'Got', xyz.shape, xyz
tra, tdec = xyztoradec(xyz)
#print >>sys.stderr, 'RA,Dec', ra,dec
plot.apply_settings()
for r, d in zip(tra, tdec):
plot.marker_radec(r, d)
plot.fill()
ann.NGC = 1
plot.plot('annotations')
ann.NGC = 0
plot.color = 'white'
plot.lw = 3
out = plot.outline
out.wcs_file = wcsfn
plot.plot('outline')
if zoom:
# MAGIC width, height are arbitrary
zoomwcs = anutil.anwcs_create_box(ra, dec, zoomwidth, 1000, 1000)
out.wcs = zoomwcs
plot.lw = 1
plot.dashed(3)
plot.plot('outline')
plot.write(plotfn)
print('Kd bounding-box:', spherematch.tree_bbox(kd))
print('Kd bounding-box:', kd.bbox)
print('Kd data:', spherematch.tree_data(kd, np.array([0,3,5]).astype(np.uint32)))
print('Kd data:', kd.get_data(np.array([0,3,5]).astype(np.uint32)))
print('Permute:', spherematch.tree_permute(kd, np.array([3,5,7]).astype(np.int32)))
print('Permute:', kd.permute(np.array([0,99,199]).astype(np.int32)))
ra,dec = np.meshgrid(np.arange(0, 360), np.arange(-90, 91, 1))
ra1 = ra.ravel()
dec1 = dec.ravel()
rdkd1 = spherematch.tree_build_radec(ra1, dec1)
print('RdKd:', rdkd1.n, rdkd1.bbox)
ra2 = np.random.uniform(-10, 10, size=1000)
dec2 = np.random.uniform(-10, 10, size=1000)
rdkd2 = spherematch.tree_build_radec(ra2, dec2)
I = spherematch.tree_search_radec(rdkd1, ra2[0], dec2[0], 2.)
print('search_radec:', I)
I,J,d = spherematch.match_radec(ra1, dec1, ra2, dec2, 1.)
print('Matches:', len(I))
I,J,d = spherematch.match_radec(ra1, dec1, ra2, dec2, 1., nearest=True)
print('Nearest matches:', len(I))
for i in range(len(T)): if not plot.wcs.is_inside(T.ra[i], T.dec[i]): continue ann.add_target(T.ra[i], T.dec[i], 'Abell %i' % T.aco[i]) if opt.t2cat: from astrometry.libkd.spherematch import tree_open, tree_close, tree_build_radec, tree_free, trees_match from astrometry.libkd import spherematch_c from astrometry.util.starutil_numpy import deg2dist, xyztoradec import numpy as np import sys wcs = plot.wcs rc,dc = wcs.get_center() rr = wcs.get_radius() kd = tree_open(opt.t2cat) kd2 = tree_build_radec(np.array([rc]), np.array([dc])) r = deg2dist(rr) I,J,d = trees_match(kd, kd2, r, permuted=False) # HACK I2,J,d = trees_match(kd, kd2, r) xyz = spherematch_c.kdtree_get_positions(kd, I) tree_free(kd2) tree_close(kd) tra,tdec = xyztoradec(xyz) T = fits_table(opt.t2cat, hdu=6) for r,d,t1,t2,t3 in zip(tra,tdec, T.tyc1[I2], T.tyc2[I2], T.tyc3[I2]): if not plot.wcs.is_inside(r, d): continue ann.add_target(r, d, 'Tycho-2 %i-%i-%i' % (t1,t2,t3))
print('Kd bounding-box:', spherematch.tree_bbox(kd))
print('Kd bounding-box:', kd.bbox)
print('Kd data:', spherematch.tree_data(kd, np.array([0,3,5]).astype(np.uint32)))
print('Kd data:', kd.get_data(np.array([0,3,5]).astype(np.uint32)))
print('Permute:', spherematch.tree_permute(kd, np.array([3,5,7]).astype(np.int32)))
print('Permute:', kd.permute(np.array([0,99,199]).astype(np.int32)))
ra,dec = np.meshgrid(np.arange(0, 360), np.arange(-90, 91, 1))
ra1 = ra.ravel()
dec1 = dec.ravel()
rdkd1 = spherematch.tree_build_radec(ra1, dec1)
print('RdKd:', rdkd1.n, rdkd1.bbox)
ra2 = np.random.uniform(-10, 10, size=1000)
dec2 = np.random.uniform(-10, 10, size=1000)
rdkd2 = spherematch.tree_build_radec(ra2, dec2)
I = spherematch.tree_search_radec(rdkd1, ra2[0], dec2[0], 2.)
print('search_radec:', I)
I,J,d = spherematch.match_radec(ra1, dec1, ra2, dec2, 1.)
print('Matches:', len(I))
I,J,d = spherematch.match_radec(ra1, dec1, ra2, dec2, 1., nearest=True)
print('Nearest matches:', len(I))
def map_decam_depth(req,
ver,
zoom,
x,
y,
savecache=False,
band=None,
ignoreCached=False):
global Tdepth
global Tdepthkd
if band is None:
band = req.GET.get('band')
if not band in ['g', 'r', 'z']:
raise RuntimeError('Invalid band')
tag = 'decam-depth-%s' % band
zoom = int(zoom)
zoomscale = 2.**zoom
x = int(x)
y = int(y)
if zoom < 0 or x < 0 or y < 0 or x >= zoomscale or y >= zoomscale:
raise RuntimeError('Invalid zoom,x,y %i,%i,%i' % (zoom, x, y))
ver = int(ver)
if not ver in tileversions[tag]:
raise RuntimeError('Invalid version %i for tag %s' % (ver, tag))
basedir = settings.DATA_DIR
tilefn = os.path.join(basedir, 'tiles', tag,
'%i/%i/%i/%i.jpg' % (ver, zoom, x, y))
if os.path.exists(tilefn) and not ignoreCached:
print('Cached:', tilefn)
return send_file(tilefn,
'image/jpeg',
expires=oneyear,
modsince=req.META.get('HTTP_IF_MODIFIED_SINCE'))
from astrometry.util.util import Tan
from astrometry.libkd.spherematch import match_radec
from astrometry.libkd.spherematch import tree_build_radec, tree_search_radec
from astrometry.util.fits import fits_table
from astrometry.util.starutil_numpy import degrees_between
import numpy as np
import fitsio
try:
wcs, W, H, zoomscale, zoom, x, y = get_tile_wcs(zoom, x, y)
except RuntimeError as e:
return HttpResponse(e.strerror)
rlo, d = wcs.pixelxy2radec(W, H / 2)[-2:]
rhi, d = wcs.pixelxy2radec(1, H / 2)[-2:]
r, d1 = wcs.pixelxy2radec(W / 2, 1)[-2:]
r, d2 = wcs.pixelxy2radec(W / 2, H)[-2:]
r, d = wcs.pixelxy2radec(W / 2, H / 2)[-2:]
rad = max(degrees_between(r, d, rlo, d1), degrees_between(r, d, rhi, d2))
if Tdepth is None:
T = fits_table(os.path.join(basedir, 'decals-zpt-nondecals.fits'),
columns=[
'ccdra', 'ccddec', 'arawgain', 'avsky', 'ccdzpt',
'filter', 'crpix1', 'crpix2', 'crval1', 'crval2',
'cd1_1', 'cd1_2', 'cd2_1', 'cd2_2', 'naxis1',
'naxis2', 'exptime', 'fwhm'
])
T.rename('ccdra', 'ra')
T.rename('ccddec', 'dec')
Tdepth = {}
Tdepthkd = {}
for b in ['g', 'r', 'z']:
Tdepth[b] = T[T.filter == b]
Tdepthkd[b] = tree_build_radec(Tdepth[b].ra, Tdepth[b].dec)
T = Tdepth[band]
Tkd = Tdepthkd[band]
#I,J,d = match_radec(T.ra, T.dec, r, d, rad + 0.2)
I = tree_search_radec(Tkd, r, d, rad + 0.2)
print(len(I), 'CCDs in range')
if len(I) == 0:
from django.http import HttpResponseRedirect
return HttpResponseRedirect(settings.STATIC_URL + 'blank.jpg')
depthiv = np.zeros((H, W), np.float32)
for t in T[I]:
twcs = Tan(*[
float(x) for x in [
t.crval1, t.crval2, t.crpix1, t.crpix2, t.cd1_1, t.cd1_2,
t.cd2_1, t.cd2_2, t.naxis1, t.naxis2
]
])
w, h = t.naxis1, t.naxis2
r, d = twcs.pixelxy2radec([1, 1, w, w], [1, h, h, 1])
ok, x, y = wcs.radec2pixelxy(r, d)
#print 'x,y coords of CCD:', x, y
x0 = int(x.min())
x1 = int(x.max())
y0 = int(y.min())
y1 = int(y.max())
if y1 < 0 or x1 < 0 or x0 >= W or y0 >= H:
continue
readnoise = 10. # e-; 7.0 to 15.0 according to DECam Data Handbook
skysig = np.sqrt(t.avsky * t.arawgain + readnoise**2) / t.arawgain
zpscale = 10.**((t.ccdzpt - 22.5) / 2.5) * t.exptime
sig1 = skysig / zpscale
psf_sigma = t.fwhm / 2.35
# point-source depth
psfnorm = 1. / (2. * np.sqrt(np.pi) * psf_sigma)
detsig1 = sig1 / psfnorm
#print '5-sigma point-source depth:', NanoMaggies.nanomaggiesToMag(detsig1 * 5.)
div = 1 / detsig1**2
depthiv[max(y0, 0):min(y1, H), max(x0, 0):min(x1, W)] += div
ptsrc = -2.5 * (np.log10(np.sqrt(1. / depthiv) * 5) - 9)
ptsrc[depthiv == 0] = 0.
if savecache:
trymakedirs(tilefn)
else:
import tempfile
f, tilefn = tempfile.mkstemp(suffix='.jpg')
os.close(f)
import pylab as plt
plt.imsave(tilefn, ptsrc, vmin=22., vmax=25., cmap='hot') #nipy_spectral')
return send_file(tilefn, 'image/jpeg', unlink=(not savecache))
def plot_wcs_outline(wcsfn, plotfn, W=256, H=256, width=36, zoom=True,
zoomwidth=3.6, grid=10, hd=False, hd_labels=False,
tycho2=False):
anutil.log_init(3)
#anutil.log_set_level(3)
wcs = anutil.Tan(wcsfn, 0)
ra,dec = wcs.radec_center()
plot = ps.Plotstuff(outformat='png', size=(W, H), rdw=(ra,dec,width))
plot.linestep = 1.
plot.color = 'verydarkblue'
plot.plot('fill')
plot.fontsize = 12
#plot.color = 'gray'
# dark gray
plot.rgb = (0.3,0.3,0.3)
if grid is not None:
plot.plot_grid(*([grid]*4))
plot.rgb = (0.4, 0.6, 0.4)
ann = plot.annotations
ann.NGC = ann.bright = ann.HD = 0
ann.constellations = 1
ann.constellation_labels = 1
ann.constellation_labels_long = 1
plot.plot('annotations')
plot.stroke()
ann.constellation_labels = 0
ann.constellation_labels_long = 0
ann.constellation_lines = 0
ann.constellation_markers = 1
plot.markersize = 3
plot.rgb = (0.4, 0.6, 0.4)
plot.plot('annotations')
plot.fill()
ann.constellation_markers = 0
ann.bright_labels = False
ann.bright = True
plot.markersize = 2
if zoom >= 2:
ann.bright_labels = True
plot.plot('annotations')
ann.bright = False
ann.bright_labels = False
plot.fill()
if hd:
ann.HD = True
ann.HD_labels = hd_labels
ps.plot_annotations_set_hd_catalog(ann, settings.HENRY_DRAPER_CAT)
plot.plot('annotations')
plot.stroke()
ann.HD = False
ann.HD_labels = False
if tycho2:
from astrometry.libkd.spherematch import tree_open, tree_close, tree_build_radec, tree_free, trees_match
from astrometry.libkd import spherematch_c
from astrometry.util.starutil_numpy import deg2dist, xyztoradec
import numpy as np
import sys
kd = tree_open(settings.TYCHO2_KD)
# this is a bit silly: build a tree with a single point, then do match()
kd2 = tree_build_radec(np.array([ra]), np.array([dec]))
r = deg2dist(width * np.sqrt(2.) / 2.)
#r = deg2dist(wcs.radius())
I,J,d = trees_match(kd, kd2, r, permuted=False)
del J
del d
#print 'Matched', len(I)
xyz = spherematch_c.kdtree_get_positions(kd, I)
del I
tree_free(kd2)
tree_close(kd)
#print >>sys.stderr, 'Got', xyz.shape, xyz
tra,tdec = xyztoradec(xyz)
#print >>sys.stderr, 'RA,Dec', ra,dec
plot.apply_settings()
for r,d in zip(tra,tdec):
plot.marker_radec(r,d)
plot.fill()
ann.NGC = 1
plot.plot('annotations')
ann.NGC = 0
plot.color = 'white'
plot.lw = 3
out = plot.outline
out.wcs_file = wcsfn
plot.plot('outline')
if zoom:
# MAGIC width, height are arbitrary
zoomwcs = anutil.anwcs_create_box(ra, dec, zoomwidth, 1000,1000)
out.wcs = zoomwcs
plot.lw = 1
plot.dashed(3)
plot.plot('outline')
plot.write(plotfn)
def get_healpix_tree(self, healpix):
from astrometry.util.fits import fits_table
fname = self.fnpattern % dict(hp=healpix)
tab = fits_table(fname, columns=self.columns)
kd = tree_build_radec(tab.ra, tab.dec)
return (kd, tab)
wcs.write_to(base + '-wcs.fits')
#bomb()
fns = keepfns
names = [fn.replace('-bright.fits', '') for fn in fns]
outlines = [getwcsoutline(wcs) for wcs in WCS]
overlaps, areas = find_overlaps(outlines)
print('Reading tables...')
TT = [fits_table(fn) for fn in fns]
print('Building trees...')
kds = [tree_build_radec(T.ra, T.dec) for T in TT]
for T, name in zip(TT, names):
T.name = np.array([name] * len(T))
allra = np.hstack([T.ra for T in TT])
alldec = np.hstack([T.dec for T in TT])
minra = np.min(allra)
maxra = np.max(allra)
mindec = np.min(alldec)
maxdec = np.max(alldec)
print('RA,Dec range:', minra, maxra, mindec, maxdec)
plothist(allra, alldec)
plt.axis([maxra, minra, mindec, maxdec])
def map_decam_depth(req, ver, zoom, x, y, savecache=False, band=None,
ignoreCached=False):
global Tdepth
global Tdepthkd
if band is None:
band = req.GET.get('band')
if not band in ['g','r','z']:
raise RuntimeError('Invalid band')
tag = 'decam-depth-%s' % band
zoom = int(zoom)
zoomscale = 2.**zoom
x = int(x)
y = int(y)
if zoom < 0 or x < 0 or y < 0 or x >= zoomscale or y >= zoomscale:
raise RuntimeError('Invalid zoom,x,y %i,%i,%i' % (zoom,x,y))
ver = int(ver)
if not ver in tileversions[tag]:
raise RuntimeError('Invalid version %i for tag %s' % (ver, tag))
basedir = settings.DATA_DIR
tilefn = os.path.join(basedir, 'tiles', tag,
'%i/%i/%i/%i.jpg' % (ver, zoom, x, y))
if os.path.exists(tilefn) and not ignoreCached:
print 'Cached:', tilefn
return send_file(tilefn, 'image/jpeg', expires=oneyear,
modsince=req.META.get('HTTP_IF_MODIFIED_SINCE'))
from astrometry.util.util import Tan
from astrometry.libkd.spherematch import match_radec
from astrometry.libkd.spherematch import tree_build_radec, tree_search_radec
from astrometry.util.fits import fits_table
from astrometry.util.starutil_numpy import degrees_between
import numpy as np
import fitsio
try:
wcs, W, H, zoomscale, zoom,x,y = get_tile_wcs(zoom, x, y)
except RuntimeError as e:
return HttpResponse(e.strerror)
rlo,d = wcs.pixelxy2radec(W, H/2)[-2:]
rhi,d = wcs.pixelxy2radec(1, H/2)[-2:]
r,d1 = wcs.pixelxy2radec(W/2, 1)[-2:]
r,d2 = wcs.pixelxy2radec(W/2, H)[-2:]
r,d = wcs.pixelxy2radec(W/2, H/2)[-2:]
rad = max(degrees_between(r, d, rlo, d1),
degrees_between(r, d, rhi, d2))
if Tdepth is None:
T = fits_table(os.path.join(basedir, 'decals-zpt-nondecals.fits'),
columns=['ccdra','ccddec','arawgain', 'avsky',
'ccdzpt', 'filter', 'crpix1','crpix2',
'crval1','crval2','cd1_1','cd1_2',
'cd2_1','cd2_2', 'naxis1', 'naxis2', 'exptime', 'fwhm'])
T.rename('ccdra', 'ra')
T.rename('ccddec', 'dec')
Tdepth = {}
Tdepthkd = {}
for b in ['g','r','z']:
Tdepth[b] = T[T.filter == b]
Tdepthkd[b] = tree_build_radec(Tdepth[b].ra, Tdepth[b].dec)
T = Tdepth[band]
Tkd = Tdepthkd[band]
#I,J,d = match_radec(T.ra, T.dec, r, d, rad + 0.2)
I = tree_search_radec(Tkd, r, d, rad + 0.2)
print len(I), 'CCDs in range'
if len(I) == 0:
from django.http import HttpResponseRedirect
return HttpResponseRedirect(settings.STATIC_URL + 'blank.jpg')
depthiv = np.zeros((H,W), np.float32)
for t in T[I]:
twcs = Tan(*[float(x) for x in [
t.crval1, t.crval2, t.crpix1, t.crpix2,
t.cd1_1, t.cd1_2, t.cd2_1, t.cd2_2, t.naxis1, t.naxis2]])
w,h = t.naxis1, t.naxis2
r,d = twcs.pixelxy2radec([1,1,w,w], [1,h,h,1])
ok,x,y = wcs.radec2pixelxy(r, d)
#print 'x,y coords of CCD:', x, y
x0 = int(x.min())
x1 = int(x.max())
y0 = int(y.min())
y1 = int(y.max())
if y1 < 0 or x1 < 0 or x0 >= W or y0 >= H:
continue
readnoise = 10. # e-; 7.0 to 15.0 according to DECam Data Handbook
skysig = np.sqrt(t.avsky * t.arawgain + readnoise**2) / t.arawgain
zpscale = 10.**((t.ccdzpt - 22.5)/2.5) * t.exptime
sig1 = skysig / zpscale
psf_sigma = t.fwhm / 2.35
# point-source depth
psfnorm = 1./(2. * np.sqrt(np.pi) * psf_sigma)
detsig1 = sig1 / psfnorm
#print '5-sigma point-source depth:', NanoMaggies.nanomaggiesToMag(detsig1 * 5.)
div = 1 / detsig1**2
depthiv[max(y0,0):min(y1,H), max(x0,0):min(x1,W)] += div
ptsrc = -2.5 * (np.log10(np.sqrt(1./depthiv) * 5) - 9)
ptsrc[depthiv == 0] = 0.
if savecache:
trymakedirs(tilefn)
else:
import tempfile
f,tilefn = tempfile.mkstemp(suffix='.jpg')
os.close(f)
import pylab as plt
plt.imsave(tilefn, ptsrc, vmin=22., vmax=25., cmap='hot')#nipy_spectral')
return send_file(tilefn, 'image/jpeg', unlink=(not savecache))
def map_sdss(req, ver, zoom, x, y, savecache=None, tag='sdss',
get_images=False,
ignoreCached=False,
wcs=None,
forcecache=False,
forcescale=None,
**kwargs):
from decals import settings
if savecache is None:
savecache = settings.SAVE_CACHE
zoom = int(zoom)
zoomscale = 2.**zoom
x = int(x)
y = int(y)
if zoom < 0 or x < 0 or y < 0 or x >= zoomscale or y >= zoomscale:
raise RuntimeError('Invalid zoom,x,y %i,%i,%i' % (zoom,x,y))
ver = int(ver)
if not ver in tileversions[tag]:
raise RuntimeError('Invalid version %i for tag %s' % (ver, tag))
basedir = settings.DATA_DIR
tilefn = os.path.join(basedir, 'tiles', tag,
'%i/%i/%i/%i.jpg' % (ver, zoom, x, y))
if os.path.exists(tilefn) and not ignoreCached:
if get_images:
return None
return send_file(tilefn, 'image/jpeg', expires=oneyear,
modsince=req.META.get('HTTP_IF_MODIFIED_SINCE'))
if not savecache:
import tempfile
f,tilefn = tempfile.mkstemp(suffix='.jpg')
os.close(f)
if wcs is None:
try:
wcs, W, H, zoomscale, zoom,x,y = get_tile_wcs(zoom, x, y)
except RuntimeError as e:
if get_images:
return None
return HttpResponse(e.strerror)
else:
W = wcs.get_width()
H = wcs.get_height()
from astrometry.util.fits import fits_table
import numpy as np
from astrometry.libkd.spherematch import tree_build_radec, tree_search_radec
from astrometry.util.starutil_numpy import degrees_between, arcsec_between
from astrometry.util.resample import resample_with_wcs, OverlapError
from astrometry.util.util import Tan, Sip
import fitsio
print 'Tile wcs: center', wcs.radec_center(), 'pixel scale', wcs.pixel_scale()
global w_flist
global w_flist_tree
if w_flist is None:
w_flist = fits_table(os.path.join(settings.DATA_DIR, 'sdss',
'window_flist.fits'),
columns=['run','rerun','camcol','field','ra','dec','score'])
print 'Read', len(w_flist), 'window_flist entries'
w_flist.cut(w_flist.rerun == '301')
print 'Cut to', len(w_flist), 'in rerun 301'
w_flist_tree = tree_build_radec(w_flist.ra, w_flist.dec)
# SDSS field size
radius = 1.01 * np.hypot(10., 14.)/2. / 60.
# leaflet tile size
ra,dec = wcs.pixelxy2radec(W/2., H/2.)[-2:]
r0,d0 = wcs.pixelxy2radec(1, 1)[-2:]
r1,d1 = wcs.pixelxy2radec(W, H)[-2:]
radius = radius + max(degrees_between(ra,dec, r0,d0), degrees_between(ra,dec, r1,d1))
J = tree_search_radec(w_flist_tree, ra, dec, radius)
print len(J), 'overlapping SDSS fields found'
if len(J) == 0:
if get_images:
return None
if forcecache:
# create symlink to blank.jpg!
trymakedirs(tilefn)
src = os.path.join(settings.STATIC_ROOT, 'blank.jpg')
if os.path.exists(tilefn):
os.unlink(tilefn)
os.symlink(src, tilefn)
print 'Symlinked', tilefn, '->', src
from django.http import HttpResponseRedirect
return HttpResponseRedirect(settings.STATIC_URL + 'blank.jpg')
ww = [1, W*0.25, W*0.5, W*0.75, W]
hh = [1, H*0.25, H*0.5, H*0.75, H]
r,d = wcs.pixelxy2radec(
[1]*len(hh) + ww + [W]*len(hh) + list(reversed(ww)),
hh + [1]*len(ww) + list(reversed(hh)) + [H]*len(ww))[-2:]
scaled = 0
scalepat = None
scaledir = 'sdss'
if zoom <= 13 and forcescale is None:
# Get *actual* pixel scales at the top & bottom
r1,d1 = wcs.pixelxy2radec(W/2., H)[-2:]
r2,d2 = wcs.pixelxy2radec(W/2., H-1.)[-2:]
r3,d3 = wcs.pixelxy2radec(W/2., 1.)[-2:]
r4,d4 = wcs.pixelxy2radec(W/2., 2.)[-2:]
# Take the min = most zoomed-in
scale = min(arcsec_between(r1,d1, r2,d2), arcsec_between(r3,d3, r4,d4))
native_scale = 0.396
scaled = int(np.floor(np.log2(scale / native_scale)))
print 'Zoom:', zoom, 'x,y', x,y, 'Tile pixel scale:', scale, 'Scale step:', scaled
scaled = np.clip(scaled, 1, 7)
dirnm = os.path.join(basedir, 'scaled', scaledir)
scalepat = os.path.join(dirnm, '%(scale)i%(band)s', '%(rerun)s', '%(run)i', '%(camcol)i', 'sdss-%(run)i-%(camcol)i-%(field)i-%(band)s.fits')
if forcescale is not None:
scaled = forcescale
bands = 'gri'
rimgs = [np.zeros((H,W), np.float32) for band in bands]
rns = [np.zeros((H,W), np.float32) for band in bands]
from astrometry.sdss import AsTransWrapper, DR9
sdss = DR9(basedir=settings.SDSS_DIR)
sdss.saveUnzippedFiles(settings.SDSS_DIR)
#sdss.setFitsioReadBZ2()
if settings.SDSS_PHOTOOBJS:
sdss.useLocalTree(photoObjs=settings.SDSS_PHOTOOBJS,
resolve=settings.SDSS_RESOLVE)
for jnum,j in enumerate(J):
print 'SDSS field', jnum, 'of', len(J), 'for zoom', zoom, 'x', x, 'y', y
im = w_flist[j]
if im.score >= 0.5:
weight = 1.
else:
weight = 0.001
for band,rimg,rn in zip(bands, rimgs, rns):
if im.rerun != '301':
continue
tmpsuff = '.tmp%08i' % np.random.randint(100000000)
basefn = sdss.retrieve('frame', im.run, im.camcol, field=im.field,
band=band, rerun=im.rerun, tempsuffix=tmpsuff)
if scaled > 0:
fnargs = dict(band=band, rerun=im.rerun, run=im.run,
camcol=im.camcol, field=im.field)
fn = get_scaled(scalepat, fnargs, scaled, basefn,
read_base_wcs=read_astrans, read_wcs=_read_sip_wcs)
print 'get_scaled:', fn
else:
fn = basefn
frame = None
if fn == basefn:
frame = sdss.readFrame(im.run, im.camcol, im.field, band,
filename=fn)
h,w = frame.getImageShape()
# Trim off the overlapping top of the image
# Wimp out and instead of trimming 128 pix, trim 124!
trim = 124
subh = h - trim
astrans = frame.getAsTrans()
fwcs = AsTransWrapper(astrans, w, subh)
fullimg = frame.getImage()
fullimg = fullimg[:-trim,:]
else:
fwcs = Sip(fn)
fitsimg = fitsio.FITS(fn)[0]
h,w = fitsimg.get_info()['dims']
fullimg = fitsimg.read()
try:
#Yo,Xo,Yi,Xi,nil = resample_with_wcs(wcs, fwcs, [], 3)
Yo,Xo,Yi,Xi,[resamp] = resample_with_wcs(wcs, fwcs, [fullimg], 2)
except OverlapError:
continue
if len(Xi) == 0:
#print 'No overlap'
continue
if sdssps is not None:
x0 = Xi.min()
x1 = Xi.max()
y0 = Yi.min()
y1 = Yi.max()
slc = (slice(y0,y1+1), slice(x0,x1+1))
if frame is not None:
img = frame.getImageSlice(slc)
else:
img = fitsimg[slc]
#rimg[Yo,Xo] += img[Yi-y0, Xi-x0]
rimg[Yo,Xo] += resamp * weight
rn [Yo,Xo] += weight
if sdssps is not None:
# goodpix = np.ones(img.shape, bool)
# fpM = sdss.readFpM(im.run, im.camcol, im.field, band)
# for plane in [ 'INTERP', 'SATUR', 'CR', 'GHOST' ]:
# fpM.setMaskedPixels(plane, goodpix, False, roi=[x0,x1,y0,y1])
plt.clf()
#ima = dict(vmin=-0.05, vmax=0.5)
#ima = dict(vmin=-0.5, vmax=2.)
ima = dict(vmax=np.percentile(img, 99))
plt.subplot(2,3,1)
dimshow(img, ticks=False, **ima)
plt.title('image')
rthis = np.zeros_like(rimg)
#rthis[Yo,Xo] += img[Yi-y0, Xi-x0]
rthis[Yo,Xo] += resamp
plt.subplot(2,3,2)
dimshow(rthis, ticks=False, **ima)
plt.title('resampled')
# plt.subplot(2,3,3)
# dimshow(goodpix, ticks=False, vmin=0, vmax=1)
# plt.title('good pix')
plt.subplot(2,3,4)
dimshow(rimg / np.maximum(rn, 1), ticks=False, **ima)
plt.title('coadd')
plt.subplot(2,3,5)
dimshow(rn, vmin=0, ticks=False)
plt.title('coverage: max %i' % rn.max())
plt.subplot(2,3,6)
rgb = sdss_rgb([rimg/np.maximum(rn,1)
for rimg,rn in zip(rimgs,rns)], bands)
dimshow(rgb)
plt.suptitle('SDSS %s, R/C/F %i/%i/%i' % (band, im.run, im.camcol, im.field))
sdssps.savefig()
for rimg,rn in zip(rimgs, rns):
rimg /= np.maximum(rn, 1e-3)
del rns
if get_images:
return rimgs
rgb = sdss_rgb(rimgs, bands)
trymakedirs(tilefn)
save_jpeg(tilefn, rgb)
print 'Wrote', tilefn
return send_file(tilefn, 'image/jpeg', unlink=(not savecache))
def map_sdss(req,
ver,
zoom,
x,
y,
savecache=None,
tag='sdss',
get_images=False,
ignoreCached=False,
wcs=None,
forcecache=False,
forcescale=None,
bestOnly=False,
bands='gri',
**kwargs):
from decals import settings
if savecache is None:
savecache = settings.SAVE_CACHE
zoom = int(zoom)
zoomscale = 2.**zoom
x = int(x)
y = int(y)
if zoom < 0 or x < 0 or y < 0 or x >= zoomscale or y >= zoomscale:
raise RuntimeError('Invalid zoom,x,y %i,%i,%i' % (zoom, x, y))
ver = int(ver)
if not ver in tileversions[tag]:
raise RuntimeError('Invalid version %i for tag %s' % (ver, tag))
basedir = settings.DATA_DIR
tilefn = os.path.join(basedir, 'tiles', tag,
'%i/%i/%i/%i.jpg' % (ver, zoom, x, y))
if os.path.exists(tilefn) and not ignoreCached:
if get_images:
return None
return send_file(tilefn,
'image/jpeg',
expires=oneyear,
modsince=req.META.get('HTTP_IF_MODIFIED_SINCE'))
if not savecache:
import tempfile
f, tilefn = tempfile.mkstemp(suffix='.jpg')
os.close(f)
if wcs is None:
try:
wcs, W, H, zoomscale, zoom, x, y = get_tile_wcs(zoom, x, y)
except RuntimeError as e:
if get_images:
return None
return HttpResponse(e.strerror)
else:
W = wcs.get_width()
H = wcs.get_height()
from astrometry.util.fits import fits_table
import numpy as np
from astrometry.libkd.spherematch import tree_build_radec, tree_search_radec
from astrometry.util.starutil_numpy import degrees_between, arcsec_between
from astrometry.util.resample import resample_with_wcs, OverlapError
from astrometry.util.util import Tan, Sip
import fitsio
print('Tile wcs: center', wcs.radec_center(), 'pixel scale',
wcs.pixel_scale())
global w_flist
global w_flist_tree
if w_flist is None:
w_flist = fits_table(
os.path.join(settings.DATA_DIR, 'sdss', 'window_flist.fits'),
columns=['run', 'rerun', 'camcol', 'field', 'ra', 'dec', 'score'])
print('Read', len(w_flist), 'window_flist entries')
w_flist.cut(w_flist.rerun == '301')
print('Cut to', len(w_flist), 'in rerun 301')
w_flist_tree = tree_build_radec(w_flist.ra, w_flist.dec)
# SDSS field size
radius = 1.01 * np.hypot(10., 14.) / 2. / 60.
# leaflet tile size
ra, dec = wcs.pixelxy2radec(W / 2., H / 2.)[-2:]
r0, d0 = wcs.pixelxy2radec(1, 1)[-2:]
r1, d1 = wcs.pixelxy2radec(W, H)[-2:]
radius = radius + max(degrees_between(ra, dec, r0, d0),
degrees_between(ra, dec, r1, d1))
J = tree_search_radec(w_flist_tree, ra, dec, radius)
print(len(J), 'overlapping SDSS fields found')
if len(J) == 0:
if get_images:
return None
if forcecache:
# create symlink to blank.jpg!
trymakedirs(tilefn)
src = os.path.join(settings.STATIC_ROOT, 'blank.jpg')
if os.path.exists(tilefn):
os.unlink(tilefn)
os.symlink(src, tilefn)
print('Symlinked', tilefn, '->', src)
from django.http import HttpResponseRedirect
return HttpResponseRedirect(settings.STATIC_URL + 'blank.jpg')
ww = [1, W * 0.25, W * 0.5, W * 0.75, W]
hh = [1, H * 0.25, H * 0.5, H * 0.75, H]
r, d = wcs.pixelxy2radec(
[1] * len(hh) + ww + [W] * len(hh) + list(reversed(ww)),
hh + [1] * len(ww) + list(reversed(hh)) + [H] * len(ww))[-2:]
scaled = 0
scalepat = None
scaledir = 'sdss'
if zoom <= 13 and forcescale is None:
# Get *actual* pixel scales at the top & bottom
r1, d1 = wcs.pixelxy2radec(W / 2., H)[-2:]
r2, d2 = wcs.pixelxy2radec(W / 2., H - 1.)[-2:]
r3, d3 = wcs.pixelxy2radec(W / 2., 1.)[-2:]
r4, d4 = wcs.pixelxy2radec(W / 2., 2.)[-2:]
# Take the min = most zoomed-in
scale = min(arcsec_between(r1, d1, r2, d2),
arcsec_between(r3, d3, r4, d4))
native_scale = 0.396
scaled = int(np.floor(np.log2(scale / native_scale)))
print('Zoom:', zoom, 'x,y', x, y, 'Tile pixel scale:', scale,
'Scale step:', scaled)
scaled = np.clip(scaled, 1, 7)
dirnm = os.path.join(basedir, 'scaled', scaledir)
scalepat = os.path.join(
dirnm, '%(scale)i%(band)s', '%(rerun)s', '%(run)i', '%(camcol)i',
'sdss-%(run)i-%(camcol)i-%(field)i-%(band)s.fits')
if forcescale is not None:
scaled = forcescale
rimgs = [np.zeros((H, W), np.float32) for band in bands]
rns = [np.zeros((H, W), np.float32) for band in bands]
from astrometry.sdss import AsTransWrapper, DR9
sdss = DR9(basedir=settings.SDSS_DIR)
sdss.saveUnzippedFiles(settings.SDSS_DIR)
#sdss.setFitsioReadBZ2()
if settings.SDSS_PHOTOOBJS:
sdss.useLocalTree(photoObjs=settings.SDSS_PHOTOOBJS,
resolve=settings.SDSS_RESOLVE)
for jnum, j in enumerate(J):
print('SDSS field', jnum, 'of', len(J), 'for zoom', zoom, 'x', x, 'y',
y)
im = w_flist[j]
if im.score >= 0.5:
weight = 1.
else:
weight = 0.001
for band, rimg, rn in zip(bands, rimgs, rns):
if im.rerun != '301':
continue
tmpsuff = '.tmp%08i' % np.random.randint(100000000)
basefn = sdss.retrieve('frame',
im.run,
im.camcol,
field=im.field,
band=band,
rerun=im.rerun,
tempsuffix=tmpsuff)
if scaled > 0:
fnargs = dict(band=band,
rerun=im.rerun,
run=im.run,
camcol=im.camcol,
field=im.field)
fn = get_scaled(scalepat,
fnargs,
scaled,
basefn,
read_base_wcs=read_astrans,
read_wcs=read_sip_wcs)
print('get_scaled:', fn)
else:
fn = basefn
frame = None
if fn == basefn:
frame = sdss.readFrame(im.run,
im.camcol,
im.field,
band,
filename=fn)
h, w = frame.getImageShape()
# Trim off the overlapping top of the image
# Wimp out and instead of trimming 128 pix, trim 124!
trim = 124
subh = h - trim
astrans = frame.getAsTrans()
fwcs = AsTransWrapper(astrans, w, subh)
fullimg = frame.getImage()
fullimg = fullimg[:-trim, :]
else:
fwcs = Sip(fn)
fitsimg = fitsio.FITS(fn)[0]
h, w = fitsimg.get_info()['dims']
fullimg = fitsimg.read()
try:
#Yo,Xo,Yi,Xi,nil = resample_with_wcs(wcs, fwcs, [], 3)
Yo, Xo, Yi, Xi, [resamp
] = resample_with_wcs(wcs, fwcs, [fullimg], 2)
except OverlapError:
continue
if len(Xi) == 0:
#print 'No overlap'
continue
if sdssps is not None:
x0 = Xi.min()
x1 = Xi.max()
y0 = Yi.min()
y1 = Yi.max()
slc = (slice(y0, y1 + 1), slice(x0, x1 + 1))
if frame is not None:
img = frame.getImageSlice(slc)
else:
img = fitsimg[slc]
#rimg[Yo,Xo] += img[Yi-y0, Xi-x0]
if bestOnly:
K = np.flatnonzero(weight > rn[Yo, Xo])
print('Updating', len(K), 'of', len(Yo), 'pixels')
if len(K):
rimg[Yo[K], Xo[K]] = resamp[K] * weight
rn[Yo[K], Xo[K]] = weight
else:
rimg[Yo, Xo] += resamp * weight
rn[Yo, Xo] += weight
if sdssps is not None:
# goodpix = np.ones(img.shape, bool)
# fpM = sdss.readFpM(im.run, im.camcol, im.field, band)
# for plane in [ 'INTERP', 'SATUR', 'CR', 'GHOST' ]:
# fpM.setMaskedPixels(plane, goodpix, False, roi=[x0,x1,y0,y1])
plt.clf()
#ima = dict(vmin=-0.05, vmax=0.5)
#ima = dict(vmin=-0.5, vmax=2.)
ima = dict(vmax=np.percentile(img, 99))
plt.subplot(2, 3, 1)
dimshow(img, ticks=False, **ima)
plt.title('image')
rthis = np.zeros_like(rimg)
#rthis[Yo,Xo] += img[Yi-y0, Xi-x0]
rthis[Yo, Xo] += resamp
plt.subplot(2, 3, 2)
dimshow(rthis, ticks=False, **ima)
plt.title('resampled')
# plt.subplot(2,3,3)
# dimshow(goodpix, ticks=False, vmin=0, vmax=1)
# plt.title('good pix')
plt.subplot(2, 3, 4)
dimshow(rimg / np.maximum(rn, 1), ticks=False, **ima)
plt.title('coadd')
plt.subplot(2, 3, 5)
dimshow(rn, vmin=0, ticks=False)
plt.title('coverage: max %i' % rn.max())
plt.subplot(2, 3, 6)
rgb = sdss_rgb(
[rimg / np.maximum(rn, 1) for rimg, rn in zip(rimgs, rns)],
bands)
dimshow(rgb)
plt.suptitle('SDSS %s, R/C/F %i/%i/%i' %
(band, im.run, im.camcol, im.field))
sdssps.savefig()
for rimg, rn in zip(rimgs, rns):
rimg /= np.maximum(rn, 1e-3)
del rns
if get_images:
return rimgs
rgb = sdss_rgb(rimgs, bands)
trymakedirs(tilefn)
save_jpeg(tilefn, rgb)
print('Wrote', tilefn)
return send_file(tilefn, 'image/jpeg', unlink=(not savecache))
def find_alignments(fns, wcsfns, gaia_fn, aff_fn, aligned_fn):
from astrometry.libkd.spherematch import tree_build_radec, trees_match
from astrometry.libkd.spherematch import match_radec
from astrometry.util.plotutils import plothist
from astrometry.util.util import Tan
import fitsio
from astrom_common import getwcsoutline
from singles import find_overlaps
if True:
WCS = []
for fn in wcsfns:
wcs = Tan(fn)
WCS.append(wcs)
names = [fn.replace('-bright.fits', '') for fn in fns]
outlines = [getwcsoutline(wcs) for wcs in WCS]
overlaps, areas = find_overlaps(outlines)
print('Reading tables...')
TT = [fits_table(fn) for fn in fns]
print('Building trees...')
kds = [tree_build_radec(T.ra, T.dec) for T in TT]
for T, name in zip(TT, names):
T.name = np.array([name] * len(T))
allra = np.hstack([T.ra for T in TT])
alldec = np.hstack([T.dec for T in TT])
minra = np.min(allra)
maxra = np.max(allra)
mindec = np.min(alldec)
maxdec = np.max(alldec)
print('RA,Dec range:', minra, maxra, mindec, maxdec)
plothist(allra, alldec)
plt.axis([maxra, minra, mindec, maxdec])
plt.xlabel('RA (deg)')
plt.ylabel('Dec (deg)')
plt.savefig('match-all.png')
Tref = fits_table(gaia_fn)
r_arcsec = 0.2
I, J, d = match_radec(Tref.ra, Tref.dec, allra, alldec, r_arcsec / 3600.)
dec = alldec[J]
cosdec = np.cos(np.deg2rad(dec))
dr = (Tref.ra[I] - allra[J]) * cosdec * 3600.
dd = (Tref.dec[I] - alldec[J]) * 3600.
plt.clf()
rr = (-r_arcsec * 1000, +r_arcsec * 1000)
plothist(dr * 1000., dd * 1000., nbins=100, range=(rr, rr))
plt.xlabel('dRA (milli-arcsec)')
plt.ylabel('dDec (milli-arcsec)')
plt.savefig('match-all-ref-before.png')
# Initial matching of all stars
r_arcsec = 0.2
I, J, d = match_radec(allra,
alldec,
allra,
alldec,
r_arcsec / 3600.,
notself=True)
dec = alldec[I]
cosdec = np.cos(np.deg2rad(dec))
dr = (allra[I] - allra[J]) * cosdec * 3600.
dd = (alldec[I] - alldec[J]) * 3600.
plt.clf()
rr = (-r_arcsec * 1000, +r_arcsec * 1000)
plothist(dr * 1000., dd * 1000., nbins=100, range=(rr, rr))
plt.xlabel('dRA (milli-arcsec)')
plt.ylabel('dDec (milli-arcsec)')
plt.savefig('match-all-before.png')
hulls = []
from scipy.spatial import ConvexHull
for T in TT:
hull = ConvexHull(np.vstack((T.ra, T.dec)).T)
ra = T.ra[hull.vertices]
ra = np.append(ra, ra[0])
dec = T.dec[hull.vertices]
dec = np.append(dec, dec[0])
hulls.append((ra, dec))
aligns = {}
#for i in []:
for i in range(len(kds)):
for j in range(i + 1, len(kds)):
print('Matching trees', i, 'and', j)
r_arcsec = 0.2
radius = np.deg2rad(r_arcsec / 3600)
I, J, d2 = trees_match(kds[i], kds[j], radius)
print(len(I), 'matches')
if len(I) == 0:
continue
Ti = TT[i]
Tj = TT[j]
dec = Ti[I].dec
cosdec = np.cos(np.deg2rad(dec))
dr = (Ti[I].ra - Tj[J].ra) * cosdec * 3600.
dd = (Ti[I].dec - Tj[J].dec) * 3600.
if False:
al = Alignment(Ti, Tj, searchradius=r_arcsec)
print('Aligning...')
if not al.shift():
print('Failed to find Alignment between fields')
continue
aligns[(i, j)] = al
plt.clf()
plotalignment(al)
plt.savefig('match-align-%02i-%02i.png' % (i, j))
plt.clf()
#plothist(np.append(Ti.ra, Tj.ra), np.append(Ti.dec, Tj.dec), docolorbar=False, doclf=False, dohot=False,
# imshowargs=dict(cmap=antigray))
plothist(Ti.ra[I], Ti.dec[I], docolorbar=False, doclf=False)
r, d = hulls[i]
plt.plot(r, d, 'r-')
r, d = hulls[j]
plt.plot(r, d, 'b-')
mra = Ti.ra[I]
mdec = Ti.dec[I]
mnra = np.min(mra)
mxra = np.max(mra)
mndec = np.min(mdec)
mxdec = np.max(mdec)
plt.plot([mnra, mnra, mxra, mxra, mnra],
[mndec, mxdec, mxdec, mndec, mndec], 'g-')
plt.axis([maxra, minra, mindec, maxdec])
plt.xlabel('RA (deg)')
plt.ylabel('Dec (deg)')
plt.savefig('match-radec-%02i-%02i.png' % (i, j))
plt.clf()
rr = (-r_arcsec, +r_arcsec)
plothist(dr, dd, nbins=100, range=(rr, rr))
plt.xlabel('dRA (arcsec)')
plt.ylabel('dDec (arcsec)')
plt.savefig('match-dradec-%02i-%02i.png' % (i, j))
#for roundi,(Nk,R) in enumerate(NkeepRads):
refrad = 0.15
targetrad = 0.005
ps = PlotSequence('shift')
from astrom_intra import intrabrickshift
from singles import plot_all_alignments
#Rads = [0.25, 0.1]
Rads = [0.2, 0.050, 0.020]
#Rads = [0.1]
affs = None
# this is the reference point around which rotations take place, NOT reference catalog stars.
refrd = None
for roundi, R in enumerate(Rads):
if roundi > 0:
refrad = 0.050
TT1 = TT
nb = int(np.ceil(R / targetrad))
nb = max(nb, 5)
if nb % 2 == 0:
nb += 1
print('Round', roundi + 1, ': matching with radius', R)
print('Nbins:', nb)
# kwargs to pass to intrabrickshift
ikwargs = {}
minoverlap = 0.01
tryoverlaps = (overlaps > minoverlap)
ikwargs.update(
do_affine=True, #mp=mp,
#alignplotargs=dict(bins=25),
alignplotargs=dict(bins=50),
overlaps=tryoverlaps)
ikwargs.update(ref=Tref, refrad=refrad)
# kwargs to pass to Alignment
akwargs = {}
i1 = intrabrickshift(TT1,
matchradius=R,
refradecs=refrd,
align_kwargs=dict(histbins=nb, **akwargs),
**ikwargs)
refrd = i1.get_reference_radecs()
filts = ['' for n in names]
ap = i1.alplotgrid
Nk = 100000
plot_all_alignments(ap, R * 1000, refrad * 1000, roundi + 1, names,
filts, ps, overlaps, outlines, Nk)
for T, aff in zip(TT, i1.affines):
T.ra, T.dec = aff.apply(T.ra, T.dec)
if affs is None:
affs = i1.affines
else:
for a, a2 in zip(affs, i1.affines):
a.add(a2)
from astrom_common import Affine
T = Affine.toTable(affs)
T.filenames = fns
#T.flt = fltfns
#T.gst = gstfns
#T.chip = chips
# FAKE -- used as a name in alignment_plots
T.gst = np.array([n + '.gst.fits' for n in names])
T.writeto(aff_fn)
# Final matching of all stars
allra = np.hstack([T.ra for T in TT])
alldec = np.hstack([T.dec for T in TT])
r_arcsec = 0.2
I, J, d = match_radec(allra,
alldec,
allra,
alldec,
r_arcsec / 3600.,
notself=True)
dec = alldec[I]
cosdec = np.cos(np.deg2rad(dec))
dr = (allra[I] - allra[J]) * cosdec * 3600.
dd = (alldec[I] - alldec[J]) * 3600.
plt.clf()
rr = (-r_arcsec * 1000, +r_arcsec * 1000)
plothist(dr * 1000., dd * 1000., nbins=100, range=(rr, rr))
plt.xlabel('dRA (milli-arcsec)')
plt.ylabel('dDec (milli-arcsec)')
plt.savefig('match-all-after.png')
I, J, d = match_radec(Tref.ra, Tref.dec, allra, alldec, r_arcsec / 3600.)
dec = alldec[J]
cosdec = np.cos(np.deg2rad(dec))
dr = (Tref.ra[I] - allra[J]) * cosdec * 3600.
dd = (Tref.dec[I] - alldec[J]) * 3600.
plt.clf()
rr = (-r_arcsec * 1000, +r_arcsec * 1000)
plothist(dr * 1000., dd * 1000., nbins=100, range=(rr, rr))
plt.xlabel('dRA (milli-arcsec)')
plt.ylabel('dDec (milli-arcsec)')
plt.savefig('match-all-ref-after.png')
r_arcsec = 0.02
I, J, d = match_radec(allra,
alldec,
allra,
alldec,
r_arcsec / 3600.,
notself=True)
dec = alldec[I]
cosdec = np.cos(np.deg2rad(dec))
dr = (allra[I] - allra[J]) * cosdec * 3600.
dd = (alldec[I] - alldec[J]) * 3600.
plt.clf()
rr = (-r_arcsec * 1000, +r_arcsec * 1000)
plothist(dr * 1000., dd * 1000., nbins=100, range=(rr, rr))
plt.xlabel('dRA (milli-arcsec)')
plt.ylabel('dDec (milli-arcsec)')
plt.savefig('match-all-after2.png')
T = fits_table()
T.ra = allra
T.dec = alldec
for col in [
'f814w_vega', 'f475w_vega', 'f336w_vega', 'f275w_vega',
'f110w_vega', 'f160w_vega', 'name'
]:
T.set(col, np.hstack([t.get(col) for t in TT]))
T.writeto(aligned_fn)
if False:
from singles import alignment_plots
dataset = 'M31'
Nkeep = 100000
R = 0.1
minoverlap = 0.01
perfield = False
nocache = True
from astrometry.util.multiproc import multiproc
mp = multiproc()
filts = ['F475W' for n in names]
chips = [-1] * len(names)
exptimes = [1] * len(names)
Nall = [0] * len(names)
rd = (minra, maxra, mindec, maxdec)
cnames = names
meta = (chips, names, cnames, filts, exptimes, Nall, rd)
alignment_plots(afffn,
dataset,
Nkeep,
0,
R,
minoverlap,
perfield,
nocache,
mp,
0,
tables=(TT, outlines, meta),
lexsort=False)
def main():
os.environ['DESIMODEL'] = '/global/homes/d/dstn/desimodel-data'
global hw
global stuck_x
global stuck_y
global stuck_loc
global starkd
hw = load_hardware()
# From fiberassign/stucksky.py: find X,Y positions of stuck positioners.
# (grab the hw dictionaries once -- these are python wrappers over C++ so not simple accessors)
state = hw.state
devtype = hw.loc_device_type
stuck_loc = [
loc for loc in hw.locations
if (((state[loc] & (FIBER_STATE_STUCK | FIBER_STATE_BROKEN)
) == FIBER_STATE_STUCK) and (devtype[loc] == 'POS'))
]
print(len(stuck_loc), 'stuck positioners')
theta_pos = hw.loc_theta_pos
theta_off = hw.loc_theta_offset
phi_pos = hw.loc_phi_pos
phi_off = hw.loc_phi_offset
stuck_theta = [theta_pos[loc] + theta_off[loc] for loc in stuck_loc]
stuck_phi = [phi_pos[loc] + phi_off[loc] for loc in stuck_loc]
curved_mm = hw.loc_pos_curved_mm
theta_arm = hw.loc_theta_arm
phi_arm = hw.loc_phi_arm
theta_min = hw.loc_theta_min
theta_max = hw.loc_theta_max
phi_min = hw.loc_phi_min
phi_max = hw.loc_phi_max
# Convert positioner angle orientations to curved focal surface X / Y (not CS5)
# Note: we could add some methods to the python bindings to vectorize this or make it less clunky...
stuck_x = np.zeros(len(stuck_loc))
stuck_y = np.zeros(len(stuck_loc))
for iloc, (loc, theta,
phi) in enumerate(zip(stuck_loc, stuck_theta, stuck_phi)):
loc_x, loc_y = hw.thetaphi_to_xy(curved_mm[loc], theta, phi,
theta_arm[loc], phi_arm[loc],
theta_off[loc], phi_off[loc],
theta_min[loc], phi_min[loc],
theta_max[loc], phi_max[loc], True)
stuck_x[iloc] = loc_x
stuck_y[iloc] = loc_y
tiles = Table.read(
'/global/cfs/cdirs/desi/target/surveyops/ops/tiles-main.ecsv')
print(len(tiles), 'tiles')
# Deduplicate tiles with same RA,Dec center
tilera = tiles['RA']
tiledec = tiles['DEC']
tileid = tiles['TILEID']
rdtile = {}
tilemap = {}
for tid, r, d in zip(tileid, tilera, tiledec):
key = r, d
if key in rdtile:
# already seen a tile with this RA,Dec; point to it
tilemap[tid] = rdtile[key]
else:
rdtile[key] = tid
del rdtile
tnow = datetime.now()
tile_obstime = tnow.isoformat(timespec='seconds')
mjd = Time(tnow).mjd
stars = fits_table(
'/global/cfs/cdirs/cosmo/data/legacysurvey/dr9/masking/gaia-mask-dr9.fits.gz'
)
print(len(stars), 'stars for masking')
print('Moving to MJD', mjd)
ra, dec = radec_at_mjd(stars.ra, stars.dec, stars.ref_epoch.astype(float),
stars.pmra, stars.pmdec, stars.parallax, mjd)
assert (np.all(np.isfinite(ra)))
assert (np.all(np.isfinite(dec)))
stars.ra = ra
stars.dec = dec
print('Building kd-tree...')
starkd = tree_build_radec(stars.ra, stars.dec)
match_radius = deg2dist(30. / 3600.)
stuck_loc = np.array(stuck_loc)
allresults = {}
mp = multiproc(32)
print('Building arg lists...')
args = []
for tid, tile_ra, tile_dec, tile_obsha in zip(tileid, tilera, tiledec,
tiles['DESIGNHA']):
# skip duplicate tiles
if tid in tilemap:
continue
# "fieldrot"
tile_theta = field_rotation_angle(tile_ra, tile_dec, mjd)
args.append((tid, tile_ra, tile_dec, tile_obstime, tile_theta,
tile_obsha, match_radius))
print('Matching', len(args), 'unique tile RA,Decs in parallel...')
res = mp.map(_match_tile, args)
print('Organizing results...')
T = fits_table()
T.tileid = []
T.loc = []
T.petal = []
T.device = []
T.fiber = []
T.pos_ra = []
T.pos_dec = []
T.star_ra = []
T.star_dec = []
T.dist_arcsec = []
T.mask_mag = []
loc_to_petal = hw.loc_petal
loc_to_device = hw.loc_device
loc_to_fiber = hw.loc_fiber
for vals in res:
if vals is None:
continue
tileid, I, pos_ra, pos_dec, pos_loc, dists = vals
T.tileid.extend([tileid] * len(I))
T.loc.extend(pos_loc)
for loc in pos_loc:
T.petal.append(loc_to_petal[loc])
T.device.append(loc_to_device[loc])
T.fiber.append(loc_to_fiber[loc])
T.pos_ra.extend(pos_ra)
T.pos_dec.extend(pos_dec)
T.star_ra.extend(stars.ra[I])
T.star_dec.extend(stars.dec[I])
T.dist_arcsec.extend(dists)
T.mask_mag.extend(stars.mask_mag[I])
T.to_np_arrays()
T.writeto('stuck-on-stars.fits')
