def getPointSourcePatch(self,
px,
py,
minval=0.,
modelMask=None,
radius=None,
**kwargs):
from astrometry.util.miscutils import get_overlapping_region
img = self.getImage(px, py)
assert (np.all(np.isfinite(img)))
if radius is not None:
R = int(np.ceil(radius))
H, W = img.shape
cx = W // 2
cy = H // 2
img = img[max(cy - R, 0):min(cy + R + 1, H - 1),
max(cx - R, 0):min(cx + R + 1, W - 1)]
H, W = img.shape
ix = int(np.round(px))
iy = int(np.round(py))
dx = px - ix
dy = py - iy
x0 = ix - W // 2
y0 = iy - H // 2
if modelMask is None:
outimg = lanczos_shift_image(img, dx, dy)
return Patch(x0, y0, outimg)
mh, mw = modelMask.shape
mx0, my0 = modelMask.x0, modelMask.y0
# print 'PixelizedPSF + modelMask'
# print 'mx0,my0', mx0,my0, '+ mw,mh', mw,mh
# print 'PSF image x0,y0', x0,y0, '+ W,H', W,H
if ((mx0 >= x0 + W) or (mx0 + mw <= x0) or (my0 >= y0 + H)
or (my0 + mh <= y0)):
# No overlap
return None
# Otherwise, we'll just produce the Lanczos-shifted PSF
# image as usual, and then copy it into the modelMask
# space.
L = 3
padding = L
# Create a modelMask + padding sized stamp and insert PSF image into it
mm = np.zeros((mh + 2 * padding, mw + 2 * padding), np.float32)
yi, yo = get_overlapping_region(my0 - y0 - padding,
my0 - y0 + mh - 1 + padding, 0, H - 1)
xi, xo = get_overlapping_region(mx0 - x0 - padding,
mx0 - x0 + mw - 1 + padding, 0, W - 1)
mm[yo, xo] = img[yi, xi]
mm = lanczos_shift_image(mm, dx, dy)
mm = mm[padding:-padding, padding:-padding]
assert (np.all(np.isfinite(mm)))
return Patch(mx0, my0, mm)
def addTo(self, img, scale=1.):
if self.patch is None:
return
(ih,iw) = img.shape
(ph,pw) = self.shape
(outx, inx) = get_overlapping_region(self.x0, self.x0+pw-1, 0, iw-1)
(outy, iny) = get_overlapping_region(self.y0, self.y0+ph-1, 0, ih-1)
if inx == [] or iny == []:
return
p = self.patch[iny,inx]
img[outy, outx] += p * scale
def addTo(self, img, scale=1.):
if self.patch is None:
return
(ih, iw) = img.shape
(ph, pw) = self.shape
(outx, inx) = get_overlapping_region(self.x0, self.x0 + pw - 1, 0,
iw - 1)
(outy, iny) = get_overlapping_region(self.y0, self.y0 + ph - 1, 0,
ih - 1)
if inx == [] or iny == []:
return
p = self.patch[iny, inx]
img[outy, outx] += p * scale
def getSlices(self, shape):
'''
shape = (H,W).
Returns (spatch, sparent), slices that yield the overlapping regions
in this Patch and the given image.
'''
(ph,pw) = self.shape
(ih,iw) = shape
(outx, inx) = get_overlapping_region(self.x0, self.x0+pw-1, 0, iw-1)
(outy, iny) = get_overlapping_region(self.y0, self.y0+ph-1, 0, ih-1)
if inx == [] or iny == []:
return (slice(0,0),slice(0,0)), (slice(0,0),slice(0,0))
return (iny,inx), (outy,outx)
def hasNonzeroOverlapWith(self, other):
if not self.hasBboxOverlapWith(other):
return False
ext = self.getExtent()
(x0, x1, y0, y1) = ext
oext = other.getExtent()
(ox0, ox1, oy0, oy1) = oext
ix, ox = get_overlapping_region(ox0, ox1 - 1, x0, x1 - 1)
iy, oy = get_overlapping_region(oy0, oy1 - 1, y0, y1 - 1)
ix = slice(ix.start - x0, ix.stop - x0)
iy = slice(iy.start - y0, iy.stop - y0)
sub = self.patch[iy, ix]
osub = other.patch[oy, ox]
assert (sub.shape == osub.shape)
return np.sum(sub * osub) > 0.
def hasNonzeroOverlapWith(self, other):
if not self.hasBboxOverlapWith(other):
return False
ext = self.getExtent()
(x0,x1,y0,y1) = ext
oext = other.getExtent()
(ox0,ox1,oy0,oy1) = oext
ix,ox = get_overlapping_region(ox0, ox1-1, x0, x1-1)
iy,oy = get_overlapping_region(oy0, oy1-1, y0, y1-1)
ix = slice(ix.start - x0, ix.stop - x0)
iy = slice(iy.start - y0, iy.stop - y0)
sub = self.patch[iy,ix]
osub = other.patch[oy,ox]
assert(sub.shape == osub.shape)
return np.sum(sub * osub) > 0.
def getSlices(self, shape):
'''
shape = (H,W).
Returns (spatch, sparent), slices that yield the overlapping regions
in this Patch and the given image.
'''
(ph, pw) = self.shape
(ih, iw) = shape
(outx, inx) = get_overlapping_region(self.x0, self.x0 + pw - 1, 0,
iw - 1)
(outy, iny) = get_overlapping_region(self.y0, self.y0 + ph - 1, 0,
ih - 1)
if inx == [] or iny == []:
return (slice(0, 0), slice(0, 0)), (slice(0, 0), slice(0, 0))
return (iny, inx), (outy, outx)
def setMaskedPixels(self, name, img, val, roi=None):
M = self.getMaskPlane(name)
if M is None:
return
if roi is not None:
x0,x1,y0,y1 = roi
for (c0,c1,r0,r1,coff,roff) in zip(M.cmin,M.cmax,M.rmin,M.rmax,
M.col0, M.row0):
assert(coff == 0)
assert(roff == 0)
if roi is not None:
(outx,nil) = get_overlapping_region(c0-x0, c1+1-x0, 0, x1-x0)
(outy,nil) = get_overlapping_region(r0-y0, r1+1-y0, 0, y1-y0)
img[outy,outx] = val
else:
img[r0:r1+1, c0:c1+1] = val
def setMaskedPixels(self, name, img, val, roi=None):
M = self.getMaskPlane(name)
if M is None:
return
if roi is not None:
x0,x1,y0,y1 = roi
for (c0,c1,r0,r1,coff,roff) in zip(M.cmin,M.cmax,M.rmin,M.rmax,
M.col0, M.row0):
assert(coff == 0)
assert(roff == 0)
if roi is not None:
(outx,nil) = get_overlapping_region(c0-x0, c1+1-x0, 0, x1-x0)
(outy,nil) = get_overlapping_region(r0-y0, r1+1-y0, 0, y1-y0)
img[outy,outx] = val
else:
img[r0:r1+1, c0:c1+1] = val
def _realGetUnitFluxModelPatch(self, img, px, py, minval, modelMask=None):
if modelMask is not None:
x0, y0 = modelMask.x0, modelMask.y0
else:
# choose the patch size
halfsize = self._getUnitFluxPatchSize(img,
px=px,
py=py,
minval=minval)
# find overlapping pixels to render
(outx,
inx) = get_overlapping_region(int(np.floor(px - halfsize)),
int(np.ceil(px + halfsize + 1)), 0,
img.getWidth())
(outy,
iny) = get_overlapping_region(int(np.floor(py - halfsize)),
int(np.ceil(py + halfsize + 1)), 0,
img.getHeight())
if inx == [] or iny == []:
# no overlap
return None
x0, x1 = outx.start, outx.stop
y0, y1 = outy.start, outy.stop
psf = img.getPsf()
# We have two methods of rendering profile galaxies: If the
# PSF can be represented as a mixture of Gaussians, then we do
# the analytic Gaussian convolution, producing a larger
# mixture of Gaussians, and we render that. Otherwise
# (pixelized PSFs), we FFT the PSF, multiply by the analytic
# FFT of the galaxy, and IFFT back to get the rendered
# profile.
# The "HybridPSF" class is just a marker to indicate whether this
# code should treat the PSF as a hybrid.
from tractor.psf import HybridPSF
hybrid = isinstance(psf, HybridPSF)
def run_mog(amix=None, mm=None):
''' This runs the mixture-of-Gaussians convolution method.
'''
if amix is None:
amix = self._getAffineProfile(img, px, py)
if mm is None:
mm = modelMask
# now convolve with the PSF, analytically
# (note that the psf's center is *not* set to px,py; that's just
# the position to use for spatially-varying PSFs)
psfmix = psf.getMixtureOfGaussians(px=px, py=py)
cmix = amix.convolve(psfmix)
if mm is None:
#print('Mixture to patch: amix', amix, 'psfmix', psfmix, 'cmix', cmix)
return mp.mixture_to_patch(cmix, x0, x1, y0, y1, minval)
# The convolved mixture *already* has the px,py offset added
# (via px,py to amix) so set px,py=0,0 in this call.
if mm.mask is not None:
p = cmix.evaluate_grid_masked(mm.x0, mm.y0, mm.mask, 0., 0.)
else:
p = cmix.evaluate_grid(mm.x0, mm.x1, mm.y0, mm.y1, 0., 0.)
assert (p.shape == mm.shape)
return p
if hasattr(psf, 'getMixtureOfGaussians') and not hybrid:
return run_mog(mm=modelMask)
# Otherwise, FFT:
imh, imw = img.shape
if modelMask is None:
# Avoid huge galaxies -> huge halfsize in a tiny image (blob)
imsz = max(imh, imw)
halfsize = min(halfsize, imsz)
# FIXME -- should take some kind of combination of
# modelMask, PSF, and Galaxy sizes!
else:
# ModelMask sets the sizes.
mh, mw = modelMask.shape
x1 = x0 + mw
y1 = y0 + mh
halfsize = max(mh / 2., mw / 2.)
# How far from the source center to furthest modelMask edge?
# FIXME -- add 1 for Lanczos margin?
halfsize = max(
halfsize,
max(max(1 + px - x0, 1 + x1 - px), max(1 + py - y0,
1 + y1 - py)))
psfh, psfw = psf.shape
halfsize = max(halfsize, max(psfw / 2., psfh / 2.))
#print('Halfsize:', halfsize)
# is the source center outside the modelMask?
sourceOut = (px < x0 or px > x1 - 1 or py < y0 or py > y1 - 1)
# print('mh,mw', mh,mw, 'sourceout?', sourceOut)
if sourceOut:
if hybrid:
return run_mog(mm=modelMask)
# Super Yuck -- FFT, modelMask, source is outside the
# box.
neardx, neardy = 0., 0.
if px < x0:
neardx = x0 - px
if px > x1:
neardx = px - x1
if py < y0:
neardy = y0 - py
if py > y1:
neardy = py - y1
nearest = np.hypot(neardx, neardy)
#print('Nearest corner:', nearest, 'vs radius', self.getRadius())
if nearest > self.getRadius():
return None
# how far is the furthest point from the source center?
farw = max(abs(x0 - px), abs(x1 - px))
farh = max(abs(y0 - py), abs(y1 - py))
bigx0 = int(np.floor(px - farw))
bigx1 = int(np.ceil(px + farw))
bigy0 = int(np.floor(py - farh))
bigy1 = int(np.ceil(py + farh))
bigw = 1 + bigx1 - bigx0
bigh = 1 + bigy1 - bigy0
boffx = x0 - bigx0
boffy = y0 - bigy0
assert (bigw >= mw)
assert (bigh >= mh)
assert (boffx >= 0)
assert (boffy >= 0)
bigMask = np.zeros((bigh, bigw), bool)
if modelMask.mask is not None:
bigMask[boffy:boffy + mh,
boffx:boffx + mw] = modelMask.mask
else:
bigMask[boffy:boffy + mh, boffx:boffx + mw] = True
bigMask = ModelMask(bigx0, bigy0, bigMask)
# print('Recursing:', self, ':', (mh,mw), 'to', (bigh,bigw))
bigmodel = self._realGetUnitFluxModelPatch(img,
px,
py,
minval,
modelMask=bigMask)
return Patch(
x0, y0, bigmodel.patch[boffy:boffy + mh, boffx:boffx + mw])
# print('Getting Fourier transform of PSF at', px,py)
# print('Tim shape:', img.shape)
P, (cx, cy), (pH, pW), (v,
w) = psf.getFourierTransform(px, py, halfsize)
dx = px - cx
dy = py - cy
if modelMask is not None:
# the Patch we return *must* have this origin.
ix0 = x0
iy0 = y0
# the difference that we have to handle by shifting the model image
mux = dx - ix0
muy = dy - iy0
# we will handle the integer portion by computing a shifted image
# and copying it into the result
sx = int(np.round(mux))
sy = int(np.round(muy))
# the subpixel portion will be handled with a Lanczos interpolation
mux -= sx
muy -= sy
else:
# Put the integer portion of the offset into Patch x0,y0
ix0 = int(np.round(dx))
iy0 = int(np.round(dy))
# the subpixel portion will be handled with a Lanczos interpolation
mux = dx - ix0
muy = dy - iy0
# At this point, mux,muy are both in [-0.5, 0.5]
assert (np.abs(mux) <= 0.5)
assert (np.abs(muy) <= 0.5)
amix = self._getShearedProfile(img, px, py)
fftmix = amix
mogmix = None
#print('Galaxy affine profile:', amix)
if hybrid:
# Split "amix" into terms that we will evaluate using MoG
# vs FFT.
vv = amix.var[:, 0, 0] + amix.var[:, 1, 1]
nsigma = 3.
# Terms that will wrap-around significantly...
I = ((vv * nsigma**2) > (pW**2))
if np.any(I):
# print('Evaluating', np.sum(I), 'terms as MoGs')
mogmix = mp.MixtureOfGaussians(
amix.amp[I],
amix.mean[I, :] + np.array([px, py])[np.newaxis, :],
amix.var[I, :, :],
quick=True)
I = np.logical_not(I)
if np.any(I):
# print('Evaluating', np.sum(I), 'terms with FFT')
fftmix = mp.MixtureOfGaussians(amix.amp[I],
amix.mean[I, :],
amix.var[I, :, :],
quick=True)
else:
fftmix = None
if fftmix is not None:
Fsum = fftmix.getFourierTransform(v, w, zero_mean=True)
# In Intel's mkl_fft library, the irfftn code path is faster than irfft2
# (the irfft2 version sets args (to their default values) which triggers padding
# behavior, changing the FFT size and copying behavior)
#G = np.fft.irfft2(Fsum * P, s=(pH, pW))
G = np.fft.irfftn(Fsum * P)
assert (G.shape == (pH, pW))
# FIXME -- we could try to be sneaky and Lanczos-interp
# after cutting G down to nearly its final size... tricky
# tho
# Lanczos-3 interpolation in ~the same way we do for
# pixelized PSFs.
from tractor.psf import lanczos_shift_image
G = G.astype(np.float32)
lanczos_shift_image(G, mux, muy, inplace=True)
else:
G = np.zeros((pH, pW), np.float32)
if modelMask is not None:
gh, gw = G.shape
if sx != 0 or sy != 0:
yi, yo = get_overlapping_region(-sy, -sy + mh - 1, 0, gh - 1)
xi, xo = get_overlapping_region(-sx, -sx + mw - 1, 0, gw - 1)
# shifted
# FIXME -- are yo,xo always the whole image? If so, optimize
shG = np.zeros((mh, mw), G.dtype)
shG[yo, xo] = G[yi, xi]
if debug_ps is not None:
_fourier_galaxy_debug_plots(G, shG, xi, yi, xo, yo, P,
Fsum, pW, pH, psf)
G = shG
if gh > mh or gw > mw:
G = G[:mh, :mw]
assert (G.shape == modelMask.shape)
else:
# Clip down to suggested "halfsize"
if x0 > ix0:
G = G[:, x0 - ix0:]
ix0 = x0
if y0 > iy0:
G = G[y0 - iy0:, :]
iy0 = y0
gh, gw = G.shape
if gw + ix0 > x1:
G = G[:, :x1 - ix0]
if gh + iy0 > y1:
G = G[:y1 - iy0, :]
if mogmix is not None:
if modelMask is not None:
mogpatch = run_mog(amix=mogmix, mm=modelMask)
else:
gh, gw = G.shape
mogpatch = run_mog(amix=mogmix, mm=ModelMask(ix0, iy0, gw, gh))
assert (mogpatch.patch.shape == G.shape)
G += mogpatch.patch
return Patch(ix0, iy0, G)
def read_outlier_mask_file(survey,
tims,
brickname,
subimage=True,
output=True,
ps=None,
outlier_mask_file=None,
apply_masks=True):
'''if subimage=True, assume that 'tims' are subimages, and demand that they have the same
x0,y0 pixel offsets and size as the outlier mask files.
if subimage=False, assume that 'tims' are full-CCD images, and
apply the mask to the relevant subimage.
*output* determines where we search for the file: treating it as output, or input?
'''
from legacypipe.bits import DQ_BITS
if outlier_mask_file is None:
fn = survey.find_file('outliers_mask', brick=brickname, output=output)
else:
fn = outlier_mask_file
if not os.path.exists(fn):
print('Failed to apply outlier mask: No such file:', fn)
return False
F = fitsio.FITS(fn)
for tim in tims:
extname = '%s-%s-%s' % (tim.imobj.camera, tim.imobj.expnum,
tim.imobj.ccdname)
if not extname in F:
print('WARNING: Did not find extension', extname,
'in outlier-mask file', fn)
return False
mask = F[extname].read()
hdr = F[extname].read_header()
if subimage:
if mask.shape != tim.shape:
print('Warning: Outlier mask', fn,
'does not match shape of tim', tim)
return False
x0 = hdr['X0']
y0 = hdr['Y0']
maskbits = get_bits_to_mask()
if subimage:
if x0 != tim.x0 or y0 != tim.y0:
print('Warning: Outlier mask', fn,
'x0,y0 does not match that of tim', tim)
return False
if apply_masks:
# Apply this mask!
tim.dq |= ((mask & maskbits) > 0) * DQ_BITS['outlier']
tim.inverr[(mask & maskbits) > 0] = 0.
else:
from astrometry.util.miscutils import get_overlapping_region
mh, mw = mask.shape
th, tw = tim.shape
my, ty = get_overlapping_region(tim.y0, tim.y0 + th - 1, y0,
y0 + mh - 1)
mx, tx = get_overlapping_region(tim.x0, tim.x0 + tw - 1, x0,
x0 + mw - 1)
# have to shift the "m" slices down by x0,y0
my = slice(my.start - y0, my.stop - y0)
mx = slice(mx.start - x0, mx.stop - x0)
if apply_masks:
# Apply this mask!
tim.dq[ty, tx] |= (
(mask[my, mx] & maskbits) > 0) * DQ_BITS['outlier']
tim.inverr[ty, tx][(mask[my, mx] & maskbits) > 0] = 0.
if ps is not None:
import pylab as plt
print('Mask extent: x [%i, %i], vs tim extent x [%i, %i]' %
(x0, x0 + mw, tim.x0, tim.x0 + tw))
print('Mask extent: y [%i, %i], vs tim extent y [%i, %i]' %
(y0, y0 + mh, tim.y0, tim.y0 + th))
print('x slice: mask', mx, 'tim', tx)
print('y slice: mask', my, 'tim', ty)
print('tim shape:', tim.shape)
print('mask shape:', mask.shape)
newdq = np.zeros(tim.shape, bool)
newdq[ty, tx] = ((mask[my, mx] & maskbits) > 0)
print('Total of', np.sum(newdq), 'pixels masked')
plt.clf()
plt.imshow(tim.getImage(),
interpolation='nearest',
origin='lower',
vmin=-2. * tim.sig1,
vmax=5. * tim.sig1,
cmap='gray')
ax = plt.axis()
from legacypipe.detection import plot_boundary_map
plot_boundary_map(newdq, iterations=3, rgb=(0, 128, 255))
plt.axis(ax)
ps.savefig()
plt.axis([tx.start, tx.stop, ty.start, ty.stop])
ps.savefig()
return True
def _realGetUnitFluxModelPatch(self, img, px, py, minval, extent=None,
modelMask=None):
'''
extent: if not None, [x0,x1,y0,y1], where the range to render
is [x0, x1), [y0,y1).
'''
#####
global psfft
if do_fft_timing:
global fft_timing
global fft_timing_id
fft_timing_id += 1
timing_id = fft_timing_id
tpatch = CpuMeas()
fft_timing.append((timing_id, 'get_unit_patch', 0,
(self,)))
if modelMask is None:
# now choose the patch size
halfsize = self._getUnitFluxPatchSize(img, px, py, minval)
if modelMask is not None:
x0,y0 = modelMask.x0, modelMask.y0
elif extent is None:
# find overlapping pixels to render
(outx, inx) = get_overlapping_region(
int(np.floor(px-halfsize)), int(np.ceil(px+halfsize+1)),
0, img.getWidth())
(outy, iny) = get_overlapping_region(
int(np.floor(py-halfsize)), int(np.ceil(py+halfsize+1)),
0, img.getHeight())
if inx == [] or iny == []:
# no overlap
if do_fft_timing:
fft_timing.append((timing_id, 'no_overlap', CpuMeas().cpu_seconds_since(tpatch)))
return None
x0,x1 = outx.start, outx.stop
y0,y1 = outy.start, outy.stop
else:
x0,x1,y0,y1 = extent
psf = img.getPsf()
# We have two methods of rendering profile galaxies: If the
# PSF can be represented as a mixture of Gaussians, then we do
# the analytic Gaussian convolution, producing a larger
# mixture of Gaussians, and we render that. Otherwise
# (pixelized PSFs), we FFT the PSF, multiply by the analytic
# FFT of the galaxy, and IFFT back to get the rendered
# profile.
if hasattr(psf, 'getMixtureOfGaussians'):
amix = self._getAffineProfile(img, px, py)
# now convolve with the PSF, analytically
psfmix = psf.getMixtureOfGaussians(px=px, py=py)
cmix = amix.convolve(psfmix)
# print('galaxy affine mixture:', amix)
# print('psf mixture:', psfmix)
# print('convolved mixture:', cmix)
# print('_realGetUnitFluxModelPatch: extent', x0,x1,y0,y1)
if modelMask is None:
return mp.mixture_to_patch(cmix, x0, x1, y0, y1, minval,
exactExtent=(extent is not None))
else:
# The convolved mixture *already* has the px,py offset added
# (via px,py to amix) so set px,py=0,0 in this call.
p = cmix.evaluate_grid_masked(x0, y0, modelMask.patch, 0., 0.)
assert(p.shape == modelMask.shape)
return p
# Otherwise, FFT:
imh,imw = img.shape
haveExtent = (modelMask is not None) or (extent is not None)
if not haveExtent:
halfsize = self._getUnitFluxPatchSize(img, px, py, minval)
# Avoid huge galaxies -> huge halfsize in a tiny image (blob)
imsz = max(imh,imw)
halfsize = min(halfsize, imsz)
else:
# FIXME -- max of modelMask, PSF, and Galaxy sizes!
if modelMask is not None:
mh,mw = modelMask.shape
x1 = x0 + mw
y1 = y0 + mh
else:
# x0,x1,y0,y1 were set to extent, above.
mw = x1 - x0
mh = y1 - y0
# is the source center outside the modelMask?
sourceOut = (px < x0 or px > x1-1 or py < y0 or py > y1-1)
if sourceOut:
# FIXME -- could also *think* about switching to a
# Gaussian approximation when very far from the source
# center...
#
#print('modelMask does not contain source center! Fetching bigger model...')
# If the source is *way* outside the patch, return zero.
neardx,neardy = 0., 0.
if px < x0:
neardx = x0 - px
if px > x1:
neardx = px - x1
if py < y0:
neardy = y0 - py
if py > y1:
neardy = py - y1
nearest = np.hypot(neardx, neardy)
if nearest > self.getRadius():
if do_fft_timing:
fft_timing.append((timing_id, 'source_way_outside', CpuMeas().cpu_seconds_since(tpatch)))
return None
# how far is the furthest point from the source center?
farw = max(abs(x0 - px), abs(x1 - px))
farh = max(abs(y0 - py), abs(y1 - py))
bigx0 = int(np.floor(px - farw))
bigx1 = int(np.ceil (px + farw))
bigy0 = int(np.floor(py - farh))
bigy1 = int(np.ceil (py + farh))
bigw = 1 + bigx1 - bigx0
bigh = 1 + bigy1 - bigy0
boffx = x0 - bigx0
boffy = y0 - bigy0
assert(bigw >= mw)
assert(bigh >= mh)
assert(boffx >= 0)
assert(boffy >= 0)
if modelMask is None:
bigMask = np.ones((bigh,bigw), bool)
else:
bigMask = np.zeros((bigh,bigw), bool)
bigMask[boffy:boffy+mh, boffx:boffx+mw] = modelMask.patch
bigMask = Patch(bigx0, bigy0, bigMask)
if do_fft_timing:
fft_timing.append((timing_id, 'calling_sourceout', None))
t0 = CpuMeas()
# print('Recursing:', self, ':', (mh,mw), 'to', (bigh,bigw))
bigmodel = self._realGetUnitFluxModelPatch(
img, px, py, minval, extent=None, modelMask=bigMask)
if do_fft_timing:
t1 = CpuMeas()
fft_timing.append((timing_id, 'sourceout', t1.cpu_seconds_since(t0),
(bigMask.shape, (mh,mw))))
return Patch(x0, y0,
bigmodel.patch[boffy:boffy+mh, boffx:boffx+mw])
halfsize = max(mh/2., mw/2.)
psfh,psfw = psf.shape
halfsize = max(halfsize, max(psfw/2., psfh/2.))
if do_fft_timing:
t0 = CpuMeas()
P,(cx,cy),(pH,pW),(v,w) = psf.getFourierTransform(px, py, halfsize)
#print('Computing', self, ': halfsize=', halfsize, 'FFT', (pH,pW))
if do_fft_timing:
t1 = CpuMeas()
fft_timing.append((timing_id, 'psf_fft', t1.cpu_seconds_since(t0),
(haveExtent, halfsize)))
# print('PSF Fourier transform size:', P.shape)
# print('Padded size:', pH,pW)
# print('PSF center in padded image:', cx,cy)
# print('Source center px,py', px,py)
# One example:
# pH,pW = (256, 256)
# P.shape = (256, 129)
# cx,cy = (127, 127)
dx = px - cx
dy = py - cy
if haveExtent:
# the Patch we return *must* have this origin.
ix0 = x0
iy0 = y0
# Put the difference into the galaxy FFT.
mux = dx - ix0
muy = dy - iy0
# ASSUME square PSF
assert(pH == pW)
psfh,psfw = psf.shape
# How much padding on the PSF image?
psfmargin = cx - psfw/2
gx0 = gy0 = 0
if abs(mux) >= psfmargin or abs(muy) >= psfmargin:
# Wrap-around is possible (likely). Compute a shifted image
# and then copy it into the result.
gx0 = int(np.round(mux))
gy0 = int(np.round(muy))
mux -= gx0
muy -= gy0
else:
# Put the integer portion of the offset into Patch x0,y0
ix0 = int(np.round(dx))
iy0 = int(np.round(dy))
# Put the subpixel portion into the galaxy FFT.
mux = dx - ix0
muy = dy - iy0
if do_fft_timing:
t0 = CpuMeas()
amix = self._getAffineProfile(img, mux, muy)
if do_fft_timing:
t1 = CpuMeas()
Fsum = amix.getFourierTransform(v, w)
if do_fft_timing:
t2 = CpuMeas()
fft_timing.append((timing_id, 'get_affine', t1.cpu_seconds_since(t0),
(haveExtent,)))
fft_timing.append((timing_id, 'get_ft', t2.cpu_seconds_since(t1),
(haveExtent,)))
if False:
# for fakedx in []:#0]:#, 1, 10]:
amix2 = self._getAffineProfile(img, mux + fakedx, muy)
Fsum2 = amix2.getFourierTransform(v, w)
plt.clf()
plt.subplot(3,3,1)
plt.imshow(Fsum2.real, interpolation='nearest', origin='lower')
plt.title('Galaxy FFT')
plt.subplot(3,3,2)
plt.imshow(P.real, interpolation='nearest', origin='lower')
plt.title('PSF FFT')
plt.subplot(3,3,3)
plt.imshow((Fsum2 * P).real,
interpolation='nearest', origin='lower')
plt.title('Galaxy * PSF FFT')
plt.subplot(3,3,4)
plt.imshow(Fsum2.imag, interpolation='nearest', origin='lower')
plt.title('Galaxy FFT')
plt.subplot(3,3,5)
plt.imshow(P.imag, interpolation='nearest', origin='lower')
plt.title('PSF FFT')
plt.subplot(3,3,6)
plt.imshow((Fsum2 * P).imag,
interpolation='nearest', origin='lower')
plt.title('Galaxy * PSF FFT')
plt.subplot(3,3,7)
plt.imshow(np.fft.irfft2(Fsum2, s=(pH,pW)),
interpolation='nearest', origin='lower')
plt.title('iFFT Galaxy')
plt.subplot(3,3,8)
plt.imshow(np.fft.irfft2(P, s=(pH,pW)),
interpolation='nearest', origin='lower')
plt.title('iFFT PSF')
plt.subplot(3,3,9)
plt.imshow(np.fft.irfft2(Fsum2*P, s=(pH,pW)),
interpolation='nearest', origin='lower')
plt.title('iFFT Galaxy*PSF')
plt.suptitle('dx = %i pixel' % fakedx)
psfft.savefig()
if haveExtent:
if False:
plt.clf()
plt.imshow(np.fft.irfft2(Fsum * P, s=(pH,pW)),
interpolation='nearest', origin='lower')
plt.title('iFFT in PSF shape')
psfft.savefig()
if do_fft_timing:
t0 = CpuMeas()
G = np.fft.irfft2(Fsum * P, s=(pH,pW))
if do_fft_timing:
t1 = CpuMeas()
fft_timing.append((timing_id, 'irfft2', t1.cpu_seconds_since(t0),
(haveExtent, (pH,pW))))
gh,gw = G.shape
if gx0 != 0 or gy0 != 0:
#print('gx0,gy0', gx0,gy0)
yi,yo = get_overlapping_region(-gy0, -gy0+mh-1, 0, gh-1)
xi,xo = get_overlapping_region(-gx0, -gx0+mw-1, 0, gw-1)
# shifted
shG = np.zeros((mh,mw), G.dtype)
shG[yo,xo] = G[yi,xi]
G = shG
if gh > mh or gw > mw:
G = G[:mh,:mw]
if modelMask is not None:
assert(G.shape == modelMask.shape)
else:
assert(G.shape == (mh,mw))
else:
#print('iFFT', (pW,pH))
# psfim = np.fft.irfft2(P)
# print('psf iFFT', psfim.shape, psfim.sum())
# psfim /= psfim.sum()
# xx,yy = np.meshgrid(np.arange(pW), np.arange(pH))
# print('centroid', np.sum(psfim*xx), np.sum(psfim*yy))
if do_fft_timing:
t0 = CpuMeas()
G = np.fft.irfft2(Fsum * P, s=(pH,pW))
if do_fft_timing:
t1 = CpuMeas()
fft_timing.append((timing_id, 'irfft2_b', t1.cpu_seconds_since(t0),
(haveExtent, (pH,pW))))
# print('Evaluating iFFT with shape', pH,pW)
# print('G shape:', G.shape)
if False:
plt.clf()
plt.imshow(G, interpolation='nearest', origin='lower')
plt.title('iFFT in padded PSF shape')
psfft.savefig()
# Clip down to suggested "halfsize"
if x0 > ix0:
G = G[:,x0 - ix0:]
ix0 = x0
if y0 > iy0:
G = G[y0 - iy0:, :]
iy0 = y0
gh,gw = G.shape
if gw+ix0 > x1:
G = G[:,:x1-ix0]
if gh+iy0 > y1:
G = G[:y1-iy0,:]
if do_fft_timing:
fft_timing.append((timing_id, 'get_unit_patch_finished', CpuMeas().cpu_seconds_since(tpatch),
(self,)))
return Patch(ix0, iy0, G)
def _realGetUnitFluxModelPatch(self, img, px, py, minval, extent=None,
modelMask=None):
'''
extent: if not None, [x0,x1,y0,y1], where the range to render
is [x0, x1), [y0,y1).
'''
#####
global psfft
if do_fft_timing:
global fft_timing
global fft_timing_id
fft_timing_id += 1
timing_id = fft_timing_id
tpatch = CpuMeas()
fft_timing.append((timing_id, 'get_unit_patch', 0,
(self,)))
if modelMask is None:
# now choose the patch size
halfsize = self._getUnitFluxPatchSize(img, px, py, minval)
if modelMask is not None:
x0,y0 = modelMask.x0, modelMask.y0
elif extent is None:
# find overlapping pixels to render
(outx, inx) = get_overlapping_region(
int(np.floor(px-halfsize)), int(np.ceil(px+halfsize+1)),
0, img.getWidth())
(outy, iny) = get_overlapping_region(
int(np.floor(py-halfsize)), int(np.ceil(py+halfsize+1)),
0, img.getHeight())
if inx == [] or iny == []:
# no overlap
if do_fft_timing:
fft_timing.append((timing_id, 'no_overlap', CpuMeas().cpu_seconds_since(tpatch)))
return None
x0,x1 = outx.start, outx.stop
y0,y1 = outy.start, outy.stop
else:
x0,x1,y0,y1 = extent
psf = img.getPsf()
# We have two methods of rendering profile galaxies: If the
# PSF can be represented as a mixture of Gaussians, then we do
# the analytic Gaussian convolution, producing a larger
# mixture of Gaussians, and we render that. Otherwise
# (pixelized PSFs), we FFT the PSF, multiply by the analytic
# FFT of the galaxy, and IFFT back to get the rendered
# profile.
if hasattr(psf, 'getMixtureOfGaussians'):
amix = self._getAffineProfile(img, px, py)
# now convolve with the PSF, analytically
psfmix = psf.getMixtureOfGaussians(px=px, py=py)
cmix = amix.convolve(psfmix)
# print('galaxy affine mixture:', amix)
# print('psf mixture:', psfmix)
# print('convolved mixture:', cmix)
# print('_realGetUnitFluxModelPatch: extent', x0,x1,y0,y1)
if modelMask is None:
return mp.mixture_to_patch(cmix, x0, x1, y0, y1, minval,
exactExtent=(extent is not None))
else:
# The convolved mixture *already* has the px,py offset added
# (via px,py to amix) so set px,py=0,0 in this call.
p = cmix.evaluate_grid_masked(x0, y0, modelMask.patch, 0., 0.)
assert(p.shape == modelMask.shape)
return p
# Otherwise, FFT:
imh,imw = img.shape
haveExtent = (modelMask is not None) or (extent is not None)
if not haveExtent:
halfsize = self._getUnitFluxPatchSize(img, px, py, minval)
# Avoid huge galaxies -> huge halfsize in a tiny image (blob)
imsz = max(imh,imw)
halfsize = min(halfsize, imsz)
else:
# FIXME -- max of modelMask, PSF, and Galaxy sizes!
if modelMask is not None:
mh,mw = modelMask.shape
x1 = x0 + mw
y1 = y0 + mh
else:
# x0,x1,y0,y1 were set to extent, above.
mw = x1 - x0
mh = y1 - y0
# is the source center outside the modelMask?
sourceOut = (px < x0 or px > x1-1 or py < y0 or py > y1-1)
if sourceOut:
# FIXME -- could also *think* about switching to a
# Gaussian approximation when very far from the source
# center...
#
#print('modelMask does not contain source center! Fetching bigger model...')
# If the source is *way* outside the patch, return zero.
neardx,neardy = 0., 0.
if px < x0:
neardx = x0 - px
if px > x1:
neardx = px - x1
if py < y0:
neardy = y0 - py
if py > y1:
neardy = py - y1
nearest = np.hypot(neardx, neardy)
if nearest > self.getRadius():
if do_fft_timing:
fft_timing.append((timing_id, 'source_way_outside', CpuMeas().cpu_seconds_since(tpatch)))
return None
# how far is the furthest point from the source center?
farw = max(abs(x0 - px), abs(x1 - px))
farh = max(abs(y0 - py), abs(y1 - py))
bigx0 = int(np.floor(px - farw))
bigx1 = int(np.ceil (px + farw))
bigy0 = int(np.floor(py - farh))
bigy1 = int(np.ceil (py + farh))
bigw = 1 + bigx1 - bigx0
bigh = 1 + bigy1 - bigy0
boffx = x0 - bigx0
boffy = y0 - bigy0
assert(bigw >= mw)
assert(bigh >= mh)
assert(boffx >= 0)
assert(boffy >= 0)
if modelMask is None:
bigMask = np.ones((bigh,bigw), bool)
else:
bigMask = np.zeros((bigh,bigw), bool)
bigMask[boffy:boffy+mh, boffx:boffx+mw] = modelMask.patch
bigMask = Patch(bigx0, bigy0, bigMask)
if do_fft_timing:
fft_timing.append((timing_id, 'calling_sourceout', None))
t0 = CpuMeas()
# print('Recursing:', self, ':', (mh,mw), 'to', (bigh,bigw))
bigmodel = self._realGetUnitFluxModelPatch(
img, px, py, minval, extent=None, modelMask=bigMask)
if do_fft_timing:
t1 = CpuMeas()
fft_timing.append((timing_id, 'sourceout', t1.cpu_seconds_since(t0),
(bigMask.shape, (mh,mw))))
return Patch(x0, y0,
bigmodel.patch[boffy:boffy+mh, boffx:boffx+mw])
halfsize = max(mh/2., mw/2.)
psfh,psfw = psf.shape
halfsize = max(halfsize, max(psfw/2., psfh/2.))
if do_fft_timing:
t0 = CpuMeas()
P,(cx,cy),(pH,pW),(v,w) = psf.getFourierTransform(px, py, halfsize)
#print('Computing', self, ': halfsize=', halfsize, 'FFT', (pH,pW))
if do_fft_timing:
t1 = CpuMeas()
fft_timing.append((timing_id, 'psf_fft', t1.cpu_seconds_since(t0),
(haveExtent, halfsize)))
# print('PSF Fourier transform size:', P.shape)
# print('Padded size:', pH,pW)
# print('PSF center in padded image:', cx,cy)
# print('Source center px,py', px,py)
# One example:
# pH,pW = (256, 256)
# P.shape = (256, 129)
# cx,cy = (127, 127)
dx = px - cx
dy = py - cy
if haveExtent:
# the Patch we return *must* have this origin.
ix0 = x0
iy0 = y0
# Put the difference into the galaxy FFT.
mux = dx - ix0
muy = dy - iy0
# ASSUME square PSF
assert(pH == pW)
psfh,psfw = psf.shape
# How much padding on the PSF image?
psfmargin = cx - psfw/2
gx0 = gy0 = 0
if abs(mux) >= psfmargin or abs(muy) >= psfmargin:
# Wrap-around is possible (likely). Compute a shifted image
# and then copy it into the result.
gx0 = int(np.round(mux))
gy0 = int(np.round(muy))
mux -= gx0
muy -= gy0
else:
# Put the integer portion of the offset into Patch x0,y0
ix0 = int(np.round(dx))
iy0 = int(np.round(dy))
# Put the subpixel portion into the galaxy FFT.
mux = dx - ix0
muy = dy - iy0
if do_fft_timing:
t0 = CpuMeas()
amix = self._getAffineProfile(img, mux, muy)
if do_fft_timing:
t1 = CpuMeas()
Fsum = amix.getFourierTransform(v, w)
if do_fft_timing:
t2 = CpuMeas()
fft_timing.append((timing_id, 'get_affine', t1.cpu_seconds_since(t0),
(haveExtent,)))
fft_timing.append((timing_id, 'get_ft', t2.cpu_seconds_since(t1),
(haveExtent,)))
if False:
# for fakedx in []:#0]:#, 1, 10]:
amix2 = self._getAffineProfile(img, mux + fakedx, muy)
Fsum2 = amix2.getFourierTransform(v, w)
plt.clf()
plt.subplot(3,3,1)
plt.imshow(Fsum2.real, interpolation='nearest', origin='lower')
plt.title('Galaxy FFT')
plt.subplot(3,3,2)
plt.imshow(P.real, interpolation='nearest', origin='lower')
plt.title('PSF FFT')
plt.subplot(3,3,3)
plt.imshow((Fsum2 * P).real,
interpolation='nearest', origin='lower')
plt.title('Galaxy * PSF FFT')
plt.subplot(3,3,4)
plt.imshow(Fsum2.imag, interpolation='nearest', origin='lower')
plt.title('Galaxy FFT')
plt.subplot(3,3,5)
plt.imshow(P.imag, interpolation='nearest', origin='lower')
plt.title('PSF FFT')
plt.subplot(3,3,6)
plt.imshow((Fsum2 * P).imag,
interpolation='nearest', origin='lower')
plt.title('Galaxy * PSF FFT')
plt.subplot(3,3,7)
plt.imshow(np.fft.irfft2(Fsum2, s=(pH,pW)),
interpolation='nearest', origin='lower')
plt.title('iFFT Galaxy')
plt.subplot(3,3,8)
plt.imshow(np.fft.irfft2(P, s=(pH,pW)),
interpolation='nearest', origin='lower')
plt.title('iFFT PSF')
plt.subplot(3,3,9)
plt.imshow(np.fft.irfft2(Fsum2*P, s=(pH,pW)),
interpolation='nearest', origin='lower')
plt.title('iFFT Galaxy*PSF')
plt.suptitle('dx = %i pixel' % fakedx)
psfft.savefig()
if haveExtent:
if False:
plt.clf()
plt.imshow(np.fft.irfft2(Fsum * P, s=(pH,pW)),
interpolation='nearest', origin='lower')
plt.title('iFFT in PSF shape')
psfft.savefig()
if do_fft_timing:
t0 = CpuMeas()
G = np.fft.irfft2(Fsum * P, s=(pH,pW))
if do_fft_timing:
t1 = CpuMeas()
fft_timing.append((timing_id, 'irfft2', t1.cpu_seconds_since(t0),
(haveExtent, (pH,pW))))
gh,gw = G.shape
if gx0 != 0 or gy0 != 0:
#print('gx0,gy0', gx0,gy0)
yi,yo = get_overlapping_region(-gy0, -gy0+mh-1, 0, gh-1)
xi,xo = get_overlapping_region(-gx0, -gx0+mw-1, 0, gw-1)
# shifted
shG = np.zeros((mh,mw), G.dtype)
shG[yo,xo] = G[yi,xi]
G = shG
if gh > mh or gw > mw:
G = G[:mh,:mw]
if modelMask is not None:
assert(G.shape == modelMask.shape)
else:
assert(G.shape == (mh,mw))
else:
#print('iFFT', (pW,pH))
# psfim = np.fft.irfft2(P)
# print('psf iFFT', psfim.shape, psfim.sum())
# psfim /= psfim.sum()
# xx,yy = np.meshgrid(np.arange(pW), np.arange(pH))
# print('centroid', np.sum(psfim*xx), np.sum(psfim*yy))
if do_fft_timing:
t0 = CpuMeas()
G = np.fft.irfft2(Fsum * P, s=(pH,pW))
if do_fft_timing:
t1 = CpuMeas()
fft_timing.append((timing_id, 'irfft2_b', t1.cpu_seconds_since(t0),
(haveExtent, (pH,pW))))
# print('Evaluating iFFT with shape', pH,pW)
# print('G shape:', G.shape)
if False:
plt.clf()
plt.imshow(G, interpolation='nearest', origin='lower')
plt.title('iFFT in padded PSF shape')
psfft.savefig()
# Clip down to suggested "halfsize"
if x0 > ix0:
G = G[:,x0 - ix0:]
ix0 = x0
if y0 > iy0:
G = G[y0 - iy0:, :]
iy0 = y0
gh,gw = G.shape
if gw+ix0 > x1:
G = G[:,:x1-ix0]
if gh+iy0 > y1:
G = G[:y1-iy0,:]
if do_fft_timing:
fft_timing.append((timing_id, 'get_unit_patch_finished', CpuMeas().cpu_seconds_since(tpatch),
(self,)))
return Patch(ix0, iy0, G)
