def _lanczos_interpolate(L, ixi, iyi, dx, dy, laccs, limages,
table=True):
'''
L: int, Lanczos order
ixi: int, 1-d numpy array, len n, x coord in input images
iyi: ----""---- y
dx: float, 1-d numpy array, len n, fractional x coord
dy: ----""---- y
laccs: list of [float, 1-d numpy array, len n]: outputs
limages list of [float, 2-d numpy array, shape h,w]: inputs
'''
from miscutils import lanczos_filter
lfunc = lanczos_filter
if L == 3:
try:
from util import lanczos3_filter, lanczos3_filter_table
# 0: no rangecheck
if table:
#lfunc = lambda nil,x,y: lanczos3_filter_table(x,y, 0)
lfunc = lambda nil,x,y: lanczos3_filter_table(x,y, 1)
else:
lfunc = lambda nil,x,y: lanczos3_filter(x,y)
except:
pass
h,w = limages[0].shape
n = len(ixi)
# sum of lanczos terms
fsum = np.zeros(n)
off = np.arange(-L, L+1)
#fx = np.zeros(n)
#fy = np.zeros(n)
fx = np.zeros(n, np.float32)
fy = np.zeros(n, np.float32)
for oy in off:
#print 'dy range:', min(-oy + dy), max(-oy + dy)
lfunc(L, -oy + dy, fy)
for ox in off:
lfunc(L, -ox + dx, fx)
#print 'dx range:', min(-ox + dx), max(-ox + dx)
for lacc,im in zip(laccs, limages):
lacc += fx * fy * im[np.clip(iyi + oy, 0, h-1),
np.clip(ixi + ox, 0, w-1)]
fsum += fx*fy
for lacc in laccs:
lacc /= fsum
def _lanczos_interpolate(L, ixi, iyi, dx, dy, laccs, limages,
table=True):
'''
L: int, Lanczos order
ixi: int, 1-d numpy array, len n, x coord in input images
iyi: ----""---- y
dx: float, 1-d numpy array, len n, fractional x coord
dy: ----""---- y
laccs: list of [float, 1-d numpy array, len n]: outputs
limages list of [float, 2-d numpy array, shape h,w]: inputs
'''
from miscutils import lanczos_filter
lfunc = lanczos_filter
if L == 3:
try:
from util import lanczos3_filter, lanczos3_filter_table
# 0: no rangecheck
if table:
#lfunc = lambda nil,x,y: lanczos3_filter_table(x,y, 0)
lfunc = lambda nil,x,y: lanczos3_filter_table(x,y, 1)
else:
lfunc = lambda nil,x,y: lanczos3_filter(x,y)
except:
pass
h,w = limages[0].shape
n = len(ixi)
# sum of lanczos terms
fsum = np.zeros(n)
off = np.arange(-L, L+1)
#fx = np.zeros(n)
#fy = np.zeros(n)
fx = np.zeros(n, np.float32)
fy = np.zeros(n, np.float32)
for oy in off:
#print 'dy range:', min(-oy + dy), max(-oy + dy)
lfunc(L, -oy + dy, fy)
for ox in off:
lfunc(L, -ox + dx, fx)
#print 'dx range:', min(-ox + dx), max(-ox + dx)
for lacc,im in zip(laccs, limages):
lacc += fx * fy * im[np.clip(iyi + oy, 0, h-1),
np.clip(ixi + ox, 0, w-1)]
fsum += fx*fy
for lacc in laccs:
lacc /= fsum
from astrometry.util.util import lanczos3_filter, lanczos3_filter_table
# x = np.linspace(-4, 4, 500)
# L = np.zeros_like(x)
# L2 = np.zeros(len(x), np.float32)
# lanczos3_filter(x, L)
# lanczos3_filter_table(x.astype(np.float32), L2, 1)
# plt.clf()
# plt.plot(x, L, 'r-')
# plt.plot(x, L2, 'b-')
# plt.savefig('l1.png')
x = np.linspace(-3.5, 4.5, 8192).astype(np.float32)
L1 = np.zeros_like(x)
L2 = np.zeros_like(x)
lanczos3_filter(x, L1)
lanczos3_filter_table(x, L2, 1)
print 'L2 - L1 RMS:', np.sqrt(np.mean((L2-L1)**2))
if True:
ra,dec = 0.,0.,
pixscale = 1e-3
W,H = 10,1
cowcs = Tan(ra, dec, (W+1)/2., (H+1)/2.,
-pixscale, 0., 0., pixscale, W, H)
dx,dy = 0.25, 0.
wcs = Tan(ra, dec, (W+1)/2. + dx, (H+1)/2. + dy,
-pixscale, 0., 0., pixscale, W, H)
pix = np.zeros((H,W), np.float32)
from astrometry.util.util import lanczos3_filter, lanczos3_filter_table
# x = np.linspace(-4, 4, 500)
# L = np.zeros_like(x)
# L2 = np.zeros(len(x), np.float32)
# lanczos3_filter(x, L)
# lanczos3_filter_table(x.astype(np.float32), L2, 1)
# plt.clf()
# plt.plot(x, L, 'r-')
# plt.plot(x, L2, 'b-')
# plt.savefig('l1.png')
x = np.linspace(-3.5, 4.5, 8192).astype(np.float32)
L1 = np.zeros_like(x)
L2 = np.zeros_like(x)
lanczos3_filter(x, L1)
lanczos3_filter_table(x, L2, 1)
print 'L2 - L1 RMS:', np.sqrt(np.mean((L2 - L1)**2))
if True:
ra, dec = 0., 0.,
pixscale = 1e-3
W, H = 10, 1
cowcs = Tan(ra, dec, (W + 1) / 2., (H + 1) / 2., -pixscale, 0., 0.,
pixscale, W, H)
dx, dy = 0.25, 0.
wcs = Tan(ra, dec, (W + 1) / 2. + dx, (H + 1) / 2. + dy, -pixscale, 0.,
0., pixscale, W, H)
pix = np.zeros((H, W), np.float32)
