def make_sample(outfile, noise=0.0, pixsize=1.0):
'''Create a sample data file for mpi-mapmaker-test/
Creates a small rectangular map of a circular Gaussian and scans
row of detectors across the map in two orientations.
Optionally add noise.
'''
# create a fake map (from a Gaussian)
nx = 32
ny = 16
gaussfwhm = 4
xx = (np.arange(nx)-nx/2)**2
yy = (np.arange(ny)-ny/2)**2
rr = xx[:,np.newaxis] + yy
gausssig = gaussfwhm / 2.354
image = np.exp(-rr/2.0/gausssig**2)
# scan once horizontally and twice vertically
ndet = 16
nsamp = 64
# allocate arrays
det_x = np.zeros([ndet, nsamp], dtype=np.int32)
det_y = np.zeros_like(det_x)
det_s = np.zeros_like(det_x, dtype=np.float64)
# horizontal scan
offs = 0
for i in range(nx):
for j in range(ndet):
det_x[j,offs+i] = i
det_y[j,offs+i] = j
det_s[j,offs+i] = image[det_x[j,offs+i],det_y[j,offs+i]]
# first half vertical
offs += nx
for i in range(ny):
for j in range(ndet):
det_x[j,offs+i] = j
det_y[j,offs+i] = i
det_s[j,offs+i] = image[det_x[j,offs+i],det_y[j,offs+i]]
# second half vertical
offs += ny
for i in range(ny):
for j in range(ndet):
det_x[j,offs+i] = nx/2+j
det_y[j,offs+i] = i
det_s[j,offs+i] = image[det_x[j,offs+i],det_y[j,offs+i]]
# add noise
det_s += np.random.randn(ndet, nsamp) * noise
# create data file
# initialize data class
out_data = MapData(outfile, ndet, nsamp)
# write attributes
out_data.set_nx(nx)
out_data.set_ny(ny)
out_data.set_pixsize(pixsize)
# set data arrays
out_data.x[...] = det_x
out_data.y[...] = det_y
out_data.s[...] = det_s
out_data.q[...] = np.zeros([ndet,nsamp], dtype=np.uint32)
# done
out_data.close()
def convert_data(infile, outfile, pixsize, verbose=False):
'''convert data file for use by mpi_makemap
Convert input data file, as created by Jack Sayer's simulator, to
format used as input to mpi_makemap. Calculates tangent-plane
projection and saves pixel position for each sample.
Arguments:
input: name of input file (as created from Jack Sayer's simulator)
output: name of output file
pixsize: size of pixels (in degrees)
verbose: print progress messages [False]
'''
# get data from file
f = h5py.File(infile)
det_ra = f[det_ra_name].value
det_dec = f[det_dec_name].value
tel_ra = f[tel_ra_name].value
tel_dec = f[tel_dec_name].value
scannum = f[scannum_name].value
# check that coordinate system is supported
coordsys = f[det_ra_name].attrs["coordinate_system"][0]
if coordsys != "radec":
sys.stderr.write("error: coordinate system must be 'radec'")
sys.exit()
# get data lengths
nsamp,ndet = f[signal_name].shape
# use mean telescope pointing as tangent point
tan_ra = tel_ra.mean()
tan_dec = tel_dec.mean()
# WCS for coordinate transformations
w = wcs.WCS(naxis=2)
w.wcs.crpix = [0, 0]
w.wcs.cdelt = np.array([-pixsize, pixsize])
w.wcs.crval = [tan_ra, tan_dec]
w.wcs.ctype = ["RA---TAN", "DEC--TAN"]
# initialize min/max collectors
minx = np.infty
maxx = -np.infty
miny = np.infty
maxy = -np.infty
if verbose:
print "Calculating map extent:"
# loop over detectors and calculate pixel position to get map range
for d in range(ndet):
if verbose:
print "\tdetector {} of {}".format(d, ndet)
# project into tangent plane
x,y = w.wcs_world2pix(tel_ra-det_ra[d]/np.cos(tel_dec*np.pi/180),
tel_dec+det_dec[d], 0)
# convert to integers
x = np.floor(x)
y = np.floor(y)
minx = min(x.min(), minx)
maxx = max(x.max(), maxx)
miny = min(y.min(), miny)
maxy = max(y.max(), maxy)
# determine map range
nx = maxx - minx + 1
ny = maxy - miny + 1
if verbose:
print "opening output file '{}'".format(outfile)
# set up output data file
out_data = MapData(outfile, ndet, nsamp)
out_data.set_nx(nx)
out_data.set_ny(ny)
out_data.set_pixsize(pixsize)
if verbose:
print "writing data to file:"
# figure out block dimensions (powers of two, assuming blocksize is
# power of two)
ndata_block = blocksize / out_data.s.dtype.itemsize
blocksize_sqrt = np.sqrt(ndata_block)
ndet_block = np.int(np.exp2(np.floor(np.log2(blocksize_sqrt))))
ndet_block = min(ndet_block, ndet)
nsamp_block = np.int(ndata_block / ndet_block)
nsamp_block = min(nsamp_block, nsamp)
# loop over data set and write to output
this_det0 = 0
while this_det0 < ndet:
# number of detectors in this block
this_ndet = min(ndet_block, ndet-this_det0)
this_det1 = this_det0 + this_ndet
if verbose:
print "Read/write block: det {}-{} of {}".format(
this_det0, this_det1, ndet)
this_samp0 = 0
while this_samp0 < nsamp:
# number of samples in this block
this_nsamp = min(nsamp_block, nsamp-this_samp0)
this_samp1 = this_samp0 + this_nsamp
# create ra/det blocks
ra_block = tel_ra[this_samp0:this_samp1] - \
det_ra[this_det0:this_det1,np.newaxis] / \
np.cos(tel_dec[this_samp0:this_samp1]*np.pi/180)
dec_block = tel_dec[this_samp0:this_samp1] + \
det_dec[this_det0:this_det1,np.newaxis]
x,y = w.wcs_world2pix(ra_block,dec_block, 0)
x = np.floor(x) - minx
y = np.floor(y) - miny
# write to file
out_data.x[this_det0:this_det1,this_samp0:this_samp1] = x
out_data.y[this_det0:this_det1,this_samp0:this_samp1] = y
out_data.s[this_det0:this_det1,this_samp0:this_samp1] = \
np.transpose(f[signal_name][this_samp0:this_samp1,
this_det0:this_det1])
# quality (0 -> good when scannum >= 0)
thisqual = (scannum[this_samp0:this_samp1] < 0).astype(np.uint32)
out_data.q[this_det0:this_det1,this_samp0:this_samp1] = thisqual
# increment samp pointer
this_samp0 = this_samp1
# increment det pointer
this_det0 = this_det1
if verbose:
print "closing files"
# done
f.close()
out_data.close()
