def __init__(self, scan, wgeo):
# Build the pointing interpolator
self.trans = TransformPos2Pix(scan, wgeo.gwcs)
self.poly = pmat.PolyInterpol(self.trans, scan.boresight, scan.offsets)
# Build the pixel shift information. This assumes ces-like scans in equ-like systems
self.sdir = pmat.get_scan_dir(scan.boresight[:, 1])
self.period = pmat.get_scan_period(scan.boresight[:, 1], scan.srate)
self.wgeo = wgeo
self.nphi = int(np.abs(360. / wgeo.gwcs.wcs.cdelt[0]))
self.core = pmat.get_core(wgeo.dtype)
self.scan = scan
def __init__(self, scan, wgeo): # Build the pointing interpolator self.trans = TransformPos2Pix(scan, wgeo.gwcs) self.poly = pmat.PolyInterpol(self.trans, scan.boresight, scan.offsets) # Build the pixel shift information. This assumes ces-like scans in equ-like systems self.sdir = pmat.get_scan_dir(scan.boresight[:,1]) self.period = pmat.get_scan_period(scan.boresight[:,1], scan.srate) self.wgeo = wgeo self.nphi = int(np.abs(360./wgeo.gwcs.wcs.cdelt[0])) self.core = pmat.get_core(wgeo.dtype) self.scan = scan
def build_workspace_geometry(wid,
bore,
point_offset,
global_wcs,
site=None,
tagger=None,
padding=100,
max_ra_width=2.5 * utils.degree,
ncomp=3,
dtype=np.float64):
if tagger is None: tagger = WorkspaceTagger()
if isinstance(wid, basestring): wid = tagger.analyze(wid)
if not valid_az_range(wid[0], wid[1]):
raise WorkspaceError("Azimuth crosses north/south")
trans = TransformPos2Pospix(global_wcs, site=site)
az1, az2, el, ra1 = wid
# Extract the workspace definition of the tag name
ra_ref = ra1 + tagger.ra_step / 2
# We want ra(dec) for up- and down-sweeps for the middle of
# the workspace. First find a t that will result in a sweep
# that crosses through the middle of the workspace.
foc_offset = np.mean(point_offset, 0)
t0 = utils.ctime2mjd(bore[0, 0])
t_ref = find_t_giving_ra(az1 + foc_offset[0],
el + foc_offset[1],
ra_ref,
site=site,
t0=t0)
# We also need the corners of the full workspace area.
t1 = find_t_giving_ra(az1 + foc_offset[0],
el + foc_offset[1],
ra1,
site=site,
t0=t0)
t2 = find_t_giving_ra(az1 + foc_offset[0],
el + foc_offset[1],
ra1 + tagger.ra_step + max_ra_width,
site=site,
t0=t0)
#print "t1", t1, "t2", t2
#print "az1", az1/utils.degree, "az2", az2/utils.degree
#print "ra", ra1/utils.degree, (ra1+tagger.ra_step+max_ra_width)/utils.degree
bore_box_hor = np.array([[t1, az1, el], [t2, az2, el]])
bore_corners_hor = utils.box2corners(bore_box_hor)
work_corners_hor = bore_corners_hor[None, :, :] + (
point_offset[:, [0, 0, 1]] * [0, 1, 1])[:, None, :]
work_corners_hor = work_corners_hor.T.reshape(3, -1)
work_corners = trans(work_corners_hor[1:], time=work_corners_hor[0])
ixcorn, iycorn = np.round(work_corners[2:]).astype(int)
iybox = np.array([np.min(iycorn) - padding, np.max(iycorn) + 1 + padding])
# Generate an up and down sweep
srate = get_srate(bore[0])
period = pmat.get_scan_period(bore[1], srate)
dmjd = period / 2. / 24 / 3600
xshifts = []
yshifts = []
work_dazs = []
nwxs, nwys = [], []
for si, (afrom, ato) in enumerate([[az1, az2], [az2, az1]]):
sweep = generate_sweep_by_dec_pix(
[[t_ref, afrom + foc_offset[0], el + foc_offset[1]],
[t_ref + dmjd, ato + foc_offset[0], el + foc_offset[1]]], iybox,
trans)
# Get the shift in ra pix per dec pix. At this point,
# the shifts are just relative to the lowest-dec pixel
xshift = np.round(sweep[5] - sweep[5, 0, None]).astype(int)
# Get the shift in dec pix per dec pix. These tell us where
# each working pixel starts as a function of normal dec pixel.
# For example [0,1,3,6] would mean that the work to normal pixel
# mapping is [0,1,1,2,2,2]. This is done to make dwdec/daz approximately
# constant
daz = np.abs(sweep[1, 1:] - sweep[1, :-1])
daz_ratio = np.maximum(1, daz / np.min(daz[1:-1]))
yshift = np.round(utils.cumsum(daz_ratio, endpoint=True)).astype(int)
yshift -= yshift[0]
# Now that we have the x and y mapping, we can determine the
# bounds of our workspace by transforming the corners of our
# input coordinates.
#print "iyc", iycorn-iybox[0]
#print "ixc", ixcorn
#for i in np.argsort(iycorn):
# print "A %6d %6d" % (iycorn[i], ixcorn[i])
#print "min(ixc)", np.min(ixcorn)
#print "max(ixc)", np.max(ixcorn)
#print "xshift", xshift[iycorn-iybox[0]]
wycorn = ixcorn - xshift[iycorn - iybox[0]]
#print "wycorn", wycorn
#print "min(wyc)", np.min(wycorn)
#print "max(wyc)", np.max(wycorn)
# Modify the shifts so that any scan in this workspace is always transformed
# to valid positions. wx and wy are transposed relative to x and y.
# Padding is needed because of the rounding involved in recovering the
# az and el from the wid.
xshift += np.min(wycorn)
xshift -= padding
wycorn2 = ixcorn - xshift[iycorn - iybox[0]]
#print "wycorn2", wycorn2
#print "min(wyc2)", np.min(wycorn2)
#print "max(wyc2)", np.max(wycorn2)
#sys.stdout.flush()
nwy = np.max(wycorn) - np.min(wycorn) + 1 + 2 * padding
nwx = yshift[-1] + 1
# Get the average azimuth spacing in wx
work_daz = (sweep[1, -1] - sweep[1, 0]) / (yshift[-1] - yshift[0])
print work_daz / utils.degree
# And collect so we can pass them to the Workspace construtor later
xshifts.append(xshift)
yshifts.append(yshift)
nwxs.append(nwx)
nwys.append(nwy)
work_dazs.append(work_daz)
# The shifts from each sweep are guaranteed to have the same length,
# since they are based on the same iybox.
nwx = np.max(nwxs)
# To translate the noise properties, we need a mapping from the x and t
# fourier spaces. For this we need the azimuth scanning speed.
scan_speed = 2 * (az2 - az1) / period
work_daz = np.mean(work_dazs)
wgeo = WorkspaceGeometry(nwys,
nwx,
xshifts,
yshifts,
iybox[0],
scan_speed,
work_daz,
global_wcs,
ncomp=ncomp,
dtype=dtype)
return wgeo
ok = True
nbox = [ndet, 11]
err = np.max(np.abs(pos_exact - pos_inter) / errlim[:, None]) * acc
err2 = np.max(np.std(pos_exact - pos_inter, 1) / errlim) * acc
# Set up arrays
map = map_orig.copy()
tod = np.arange(tod.size, dtype=dtype).reshape(tod.shape) * 1e-8
# Precompute pixels if necessary
tpre = 0
if ipname == "fast":
pix = np.zeros([ndet, nsamp], np.int32)
phase = np.zeros([ndet, nsamp, 2], dtype)
sdir = pmat.get_scan_dir(bore[:, 1])
period = pmat.get_scan_period(bore[:, 1], srate)
wbox, wshift = pmat.build_work_shift(transfun, wibox, period)
t1 = time.time()
core.pmat_map_get_pix_poly_shift(pix.T, phase.T, bore.T, hwp.T,
det_comps.T, poly.coeffs.T, sdir,
wbox.T, wshift.T)
t2 = time.time()
tpre = t2 - t1
t1 = time.time()
times = np.zeros(5, dtype=ptype)
iptoks = ipname.split("_")
for i in range(args.ntime):
if ipname == "fast":
core.pmat_map_use_pix_shift(dir, tod.T, 1, map.T, 1, pix.T,
phase.T, wbox.T, wshift.T, nphi,
def build_workspace_geometry(wid, bore, point_offset, global_wcs, site=None, tagger=None,
padding=100, max_ra_width=2.5*utils.degree, ncomp=3, dtype=np.float64):
if tagger is None: tagger = WorkspaceTagger()
if isinstance(wid, basestring): wid = tagger.analyze(wid)
if not valid_az_range(wid[0], wid[1]): raise WorkspaceError("Azimuth crosses north/south")
trans = TransformPos2Pospix(global_wcs, site=site)
az1, az2, el, ra1 = wid
# Extract the workspace definition of the tag name
ra_ref = ra1 + tagger.ra_step/2
# We want ra(dec) for up- and down-sweeps for the middle of
# the workspace. First find a t that will result in a sweep
# that crosses through the middle of the workspace.
foc_offset = np.mean(point_offset,0)
t0 = utils.ctime2mjd(bore[0,0])
t_ref = find_t_giving_ra(az1+foc_offset[0], el+foc_offset[1], ra_ref, site=site, t0=t0)
# We also need the corners of the full workspace area.
t1 = find_t_giving_ra(az1+foc_offset[0], el+foc_offset[1], ra1, site=site, t0=t0)
t2 = find_t_giving_ra(az1+foc_offset[0], el+foc_offset[1], ra1+tagger.ra_step+max_ra_width, site=site, t0=t0)
#print "t1", t1, "t2", t2
#print "az1", az1/utils.degree, "az2", az2/utils.degree
#print "ra", ra1/utils.degree, (ra1+tagger.ra_step+max_ra_width)/utils.degree
bore_box_hor = np.array([[t1,az1,el],[t2,az2,el]])
bore_corners_hor = utils.box2corners(bore_box_hor)
work_corners_hor = bore_corners_hor[None,:,:] + (point_offset[:,[0,0,1]] * [0,1,1])[:,None,:]
work_corners_hor = work_corners_hor.T.reshape(3,-1)
work_corners = trans(work_corners_hor[1:], time=work_corners_hor[0])
ixcorn, iycorn = np.round(work_corners[2:]).astype(int)
iybox = np.array([np.min(iycorn)-padding,np.max(iycorn)+1+padding])
# Generate an up and down sweep
srate = get_srate(bore[0])
period = pmat.get_scan_period(bore[1], srate)
dmjd = period/2./24/3600
xshifts = []
yshifts = []
work_dazs = []
nwxs, nwys = [], []
for si, (afrom,ato) in enumerate([[az1,az2],[az2,az1]]):
sweep = generate_sweep_by_dec_pix(
[[ t_ref, afrom+foc_offset[0],el+foc_offset[1]],
[t_ref+dmjd,ato +foc_offset[0],el+foc_offset[1]]
],iybox,trans)
# Get the shift in ra pix per dec pix. At this point,
# the shifts are just relative to the lowest-dec pixel
xshift = np.round(sweep[5]-sweep[5,0,None]).astype(int)
# Get the shift in dec pix per dec pix. These tell us where
# each working pixel starts as a function of normal dec pixel.
# For example [0,1,3,6] would mean that the work to normal pixel
# mapping is [0,1,1,2,2,2]. This is done to make dwdec/daz approximately
# constant
daz = np.abs(sweep[1,1:]-sweep[1,:-1])
daz_ratio = np.maximum(1,daz/np.min(daz[1:-1]))
yshift = np.round(utils.cumsum(daz_ratio, endpoint=True)).astype(int)
yshift -= yshift[0]
# Now that we have the x and y mapping, we can determine the
# bounds of our workspace by transforming the corners of our
# input coordinates.
#print "iyc", iycorn-iybox[0]
#print "ixc", ixcorn
#for i in np.argsort(iycorn):
# print "A %6d %6d" % (iycorn[i], ixcorn[i])
#print "min(ixc)", np.min(ixcorn)
#print "max(ixc)", np.max(ixcorn)
#print "xshift", xshift[iycorn-iybox[0]]
wycorn = ixcorn - xshift[iycorn-iybox[0]]
#print "wycorn", wycorn
#print "min(wyc)", np.min(wycorn)
#print "max(wyc)", np.max(wycorn)
# Modify the shifts so that any scan in this workspace is always transformed
# to valid positions. wx and wy are transposed relative to x and y.
# Padding is needed because of the rounding involved in recovering the
# az and el from the wid.
xshift += np.min(wycorn)
xshift -= padding
wycorn2= ixcorn - xshift[iycorn-iybox[0]]
#print "wycorn2", wycorn2
#print "min(wyc2)", np.min(wycorn2)
#print "max(wyc2)", np.max(wycorn2)
#sys.stdout.flush()
nwy = np.max(wycorn)-np.min(wycorn)+1 + 2*padding
nwx = yshift[-1]+1
# Get the average azimuth spacing in wx
work_daz = (sweep[1,-1]-sweep[1,0])/(yshift[-1]-yshift[0])
print work_daz/utils.degree
# And collect so we can pass them to the Workspace construtor later
xshifts.append(xshift)
yshifts.append(yshift)
nwxs.append(nwx)
nwys.append(nwy)
work_dazs.append(work_daz)
# The shifts from each sweep are guaranteed to have the same length,
# since they are based on the same iybox.
nwx = np.max(nwxs)
# To translate the noise properties, we need a mapping from the x and t
# fourier spaces. For this we need the azimuth scanning speed.
scan_speed = 2*(az2-az1)/period
work_daz = np.mean(work_dazs)
wgeo = WorkspaceGeometry(nwys, nwx, xshifts, yshifts, iybox[0], scan_speed, work_daz, global_wcs, ncomp=ncomp, dtype=dtype)
return wgeo
ok = True
nbox = [ndet, 11]
err = np.max(np.abs(pos_exact-pos_inter)/errlim[:,None])*acc
err2 = np.max(np.std(pos_exact-pos_inter,1)/errlim)*acc
# Set up arrays
map = map_orig.copy()
tod = np.arange(tod.size,dtype=dtype).reshape(tod.shape)*1e-8
# Precompute pixels if necessary
tpre = 0
if ipname == "fast":
pix = np.zeros([ndet,nsamp],np.int32)
phase = np.zeros([ndet,nsamp,2],dtype)
sdir = pmat.get_scan_dir(bore[:,1])
period = pmat.get_scan_period(bore[:,1], srate)
wbox, wshift = pmat.build_work_shift(transfun, wibox, period)
t1 = time.time()
core.pmat_map_get_pix_poly_shift(pix.T, phase.T, bore.T, hwp.T, det_comps.T,
poly.coeffs.T, sdir, wbox.T, wshift.T)
t2 = time.time()
tpre = t2-t1
t1 = time.time()
times = np.zeros(5, dtype=ptype)
iptoks = ipname.split("_")
for i in range(args.ntime):
if ipname == "fast":
core.pmat_map_use_pix_shift(dir, tod.T, 1, map.T, 1, pix.T, phase.T, wbox.T, wshift.T, nphi, times)
elif iptoks[0] == "std":
pmet = {"bi":1,"gr":2}[iptoks[1]]