def find_map_dimensions(map_in, silent=False):
r"""print various aspects of the maps"""
if isinstance(map_in, str):
map_in = algebra.make_vect(algebra.load(map_in))
cosmology = Cosmology()
ra_axis = map_in.get_axis('ra')
#print ra_axis
mmd_ra = axis_param(ra_axis)
dec_axis = map_in.get_axis('dec')
#print dec_axis
mmd_dec = axis_param(dec_axis)
freq_axis = map_in.get_axis('freq') / 1.e6
mmd_freq = axis_param(freq_axis)
beam_data = sp.array([
0.316148488246, 0.306805630985, 0.293729620792, 0.281176247549,
0.270856788455, 0.26745856078, 0.258910010848, 0.249188429031
])
freq_data = sp.array([695, 725, 755, 785, 815, 845, 875, 905], dtype=float)
beam_FWHM = interp1d(freq_data, beam_data)
if (mmd_freq[0] < freq_data.min()):
beam_minfreq = beam_FWHM(freq_data.min())
#print "warning: no beam data for this freq, using %s" % beam_minfreq
else:
beam_minfreq = beam_FWHM(mmd_freq[0])
if (mmd_freq[1] > freq_data.max()):
beam_maxfreq = beam_FWHM(freq_data.max())
#print "warning: no beam data for this freq, using %s" % beam_maxfreq
else:
beam_maxfreq = beam_FWHM(mmd_freq[1])
ra_fact = sp.cos(sp.pi * map_in.info['dec_centre'] / 180.0)
dracosdec = mmd_ra[2] * ra_fact
pixelfrac_ramin = dracosdec / beam_minfreq
pixelfrac_decmin = mmd_dec[2] / beam_minfreq
pixelfrac_ramax = dracosdec / beam_maxfreq
pixelfrac_decmax = mmd_dec[2] / beam_maxfreq
# cosmological sizes
dfreq = mmd_freq[2]
z1 = cc.freq_21cm_MHz / mmd_freq[0] - 1. # z at min freq
z2 = cc.freq_21cm_MHz / mmd_freq[1] - 1. # z at max freq
dz1 = cc.freq_21cm_MHz / (mmd_freq[0] + dfreq) - 1.
dz2 = cc.freq_21cm_MHz / (mmd_freq[1] - dfreq) - 1.
d1 = cosmology.proper_distance(z1)
d2 = cosmology.proper_distance(z2)
c1 = cosmology.comoving_distance(z1)
c2 = cosmology.comoving_distance(z2)
dc1 = cosmology.comoving_distance(dz1)
dc2 = cosmology.comoving_distance(dz2)
ra_extent_z1 = mmd_ra[3] * d1 * units.degree * ra_fact
ra_pixel_extent_z1 = mmd_ra[2] * d1 * units.degree * ra_fact
ra_extent_z2 = mmd_ra[3] * d2 * units.degree * ra_fact
ra_pixel_extent_z2 = mmd_ra[2] * d2 * units.degree * ra_fact
dec_extent_z1 = mmd_dec[3] * d1 * units.degree
dec_pixel_extent_z1 = mmd_dec[2] * d1 * units.degree
dec_extent_z2 = mmd_dec[3] * d2 * units.degree
dec_pixel_extent_z2 = mmd_dec[2] * d2 * units.degree
redshift_extent = c1 - c2
redshift_pixel_extent_z1 = c1 - dc1
redshift_pixel_extent_z2 = dc2 - c2
if not silent:
infolist = [
'ra_centre', 'ra_delta', 'dec_centre', 'dec_delta', 'freq_centre',
'freq_delta'
]
for key in infolist:
print "%s: %s" % (key, map_in.info[key])
sexagesimal = misc.radec_to_sexagesimal(map_in.info["ra_centre"],
map_in.info["dec_centre"])
(ralong, declong, decsign) = sexagesimal
print "RA: %dH:%dm:%10.5fs, dec %s %dd:%dm:%10.5fs" % \
(ralong[0], ralong[1], ralong[2], decsign, declong[0], declong[1],
declong[2])
shp = map_in.shape
print shp
# 2^30 or 10^9...
covsize = shp[0] * shp[1]**2. * shp[2]**2. * 4. / 2.**30.
print "covariance size in GB: %g" % covsize
print "RA min=%g deg, max=%g deg, delta=%g deg, extent=%g deg, N=%d" % mmd_ra
print "Dec min=%g deg, max=%g deg, delta=%g deg, extent=%g deg, N=%d" % mmd_dec
print "Freq min=%g MHz, max=%g MHz, delta=%g MHz, extent=%g MHz, N=%d" % mmd_freq
print "Note that these fractions are in delta RA * cos(Dec)"
print "beam FWHM at %g MHz=%g deg; pixel frac RA, Dec=(%g, %g)" % \
(mmd_freq[0], beam_minfreq, pixelfrac_ramin, pixelfrac_decmin)
print "beam FWHM at %g MHz=%g deg; pixel frac RA, Dec=(%g, %g)" % \
(mmd_freq[1], beam_maxfreq, pixelfrac_ramax, pixelfrac_decmax)
print "redshift range: z=%g-%g" % (z2, z1)
print "proper distance range (h^-1 cMpc): d=%g-%g" % (d2, d1)
print "comoving distance range (h^-1 cMpc): d=%g-%g, extent = %g" % \
(c2, c1, redshift_extent)
print "at %g MHz, width in RA=%g Dec=%g h^-1 cMpc" % \
(mmd_freq[0], ra_extent_z1, dec_extent_z1)
print "at %g MHz, pixel width in RA=%g Dec=%g h^-1 cMpc" % \
(mmd_freq[0], ra_pixel_extent_z1, dec_pixel_extent_z1)
print "the freq bin starting at %g MHz has width %g" % \
(mmd_freq[0], redshift_pixel_extent_z1)
print "at %g MHz, width in RA=%g Dec=%g h^-1 cMpc" % \
(mmd_freq[1], ra_extent_z2, dec_extent_z2)
print "at %g MHz, pixel width in RA=%g Dec=%g h^-1 cMpc" % \
(mmd_freq[1], ra_pixel_extent_z2, dec_pixel_extent_z2)
print "the freq bin starting at %g MHz has width %g" % \
(mmd_freq[1], redshift_pixel_extent_z2)
print "-" * 80
# return the sampling at the finest resolution
return (pixelfrac_ramax, pixelfrac_decmax)
def find_map_dimensions(map_in, silent=False):
r"""print various aspects of the maps"""
if isinstance(map_in, str):
map_in = algebra.make_vect(algebra.load(map_in))
cosmology = Cosmology()
ra_axis = map_in.get_axis("ra")
# print ra_axis
mmd_ra = axis_param(ra_axis)
dec_axis = map_in.get_axis("dec")
# print dec_axis
mmd_dec = axis_param(dec_axis)
freq_axis = map_in.get_axis("freq") / 1.0e6
mmd_freq = axis_param(freq_axis)
beam_data = sp.array(
[
0.316148488246,
0.306805630985,
0.293729620792,
0.281176247549,
0.270856788455,
0.26745856078,
0.258910010848,
0.249188429031,
]
)
freq_data = sp.array([695, 725, 755, 785, 815, 845, 875, 905], dtype=float)
beam_FWHM = interp1d(freq_data, beam_data)
if mmd_freq[0] < freq_data.min():
beam_minfreq = beam_FWHM(freq_data.min())
# print "warning: no beam data for this freq, using %s" % beam_minfreq
else:
beam_minfreq = beam_FWHM(mmd_freq[0])
if mmd_freq[1] > freq_data.max():
beam_maxfreq = beam_FWHM(freq_data.max())
# print "warning: no beam data for this freq, using %s" % beam_maxfreq
else:
beam_maxfreq = beam_FWHM(mmd_freq[1])
ra_fact = sp.cos(sp.pi * map_in.info["dec_centre"] / 180.0)
dracosdec = mmd_ra[2] * ra_fact
pixelfrac_ramin = dracosdec / beam_minfreq
pixelfrac_decmin = mmd_dec[2] / beam_minfreq
pixelfrac_ramax = dracosdec / beam_maxfreq
pixelfrac_decmax = mmd_dec[2] / beam_maxfreq
# cosmological sizes
dfreq = mmd_freq[2]
z1 = cc.freq_21cm_MHz / mmd_freq[0] - 1.0 # z at min freq
z2 = cc.freq_21cm_MHz / mmd_freq[1] - 1.0 # z at max freq
dz1 = cc.freq_21cm_MHz / (mmd_freq[0] + dfreq) - 1.0
dz2 = cc.freq_21cm_MHz / (mmd_freq[1] - dfreq) - 1.0
d1 = cosmology.proper_distance(z1)
d2 = cosmology.proper_distance(z2)
c1 = cosmology.comoving_distance(z1)
c2 = cosmology.comoving_distance(z2)
dc1 = cosmology.comoving_distance(dz1)
dc2 = cosmology.comoving_distance(dz2)
ra_extent_z1 = mmd_ra[3] * d1 * units.degree * ra_fact
ra_pixel_extent_z1 = mmd_ra[2] * d1 * units.degree * ra_fact
ra_extent_z2 = mmd_ra[3] * d2 * units.degree * ra_fact
ra_pixel_extent_z2 = mmd_ra[2] * d2 * units.degree * ra_fact
dec_extent_z1 = mmd_dec[3] * d1 * units.degree
dec_pixel_extent_z1 = mmd_dec[2] * d1 * units.degree
dec_extent_z2 = mmd_dec[3] * d2 * units.degree
dec_pixel_extent_z2 = mmd_dec[2] * d2 * units.degree
redshift_extent = c1 - c2
redshift_pixel_extent_z1 = c1 - dc1
redshift_pixel_extent_z2 = dc2 - c2
if not silent:
infolist = ["ra_centre", "ra_delta", "dec_centre", "dec_delta", "freq_centre", "freq_delta"]
for key in infolist:
print "%s: %s" % (key, map_in.info[key])
sexagesimal = misc.radec_to_sexagesimal(map_in.info["ra_centre"], map_in.info["dec_centre"])
(ralong, declong, decsign) = sexagesimal
print "RA: %dH:%dm:%10.5fs, dec %s %dd:%dm:%10.5fs" % (
ralong[0],
ralong[1],
ralong[2],
decsign,
declong[0],
declong[1],
declong[2],
)
shp = map_in.shape
print shp
# 2^30 or 10^9...
covsize = shp[0] * shp[1] ** 2.0 * shp[2] ** 2.0 * 4.0 / 2.0 ** 30.0
print "covariance size in GB: %g" % covsize
print "RA min=%g deg, max=%g deg, delta=%g deg, extent=%g deg, N=%d" % mmd_ra
print "Dec min=%g deg, max=%g deg, delta=%g deg, extent=%g deg, N=%d" % mmd_dec
print "Freq min=%g MHz, max=%g MHz, delta=%g MHz, extent=%g MHz, N=%d" % mmd_freq
print "Note that these fractions are in delta RA * cos(Dec)"
print "beam FWHM at %g MHz=%g deg; pixel frac RA, Dec=(%g, %g)" % (
mmd_freq[0],
beam_minfreq,
pixelfrac_ramin,
pixelfrac_decmin,
)
print "beam FWHM at %g MHz=%g deg; pixel frac RA, Dec=(%g, %g)" % (
mmd_freq[1],
beam_maxfreq,
pixelfrac_ramax,
pixelfrac_decmax,
)
print "redshift range: z=%g-%g" % (z2, z1)
print "proper distance range (h^-1 cMpc): d=%g-%g" % (d2, d1)
print "comoving distance range (h^-1 cMpc): d=%g-%g, extent = %g" % (c2, c1, redshift_extent)
print "at %g MHz, width in RA=%g Dec=%g h^-1 cMpc" % (mmd_freq[0], ra_extent_z1, dec_extent_z1)
print "at %g MHz, pixel width in RA=%g Dec=%g h^-1 cMpc" % (
mmd_freq[0],
ra_pixel_extent_z1,
dec_pixel_extent_z1,
)
print "the freq bin starting at %g MHz has width %g" % (mmd_freq[0], redshift_pixel_extent_z1)
print "at %g MHz, width in RA=%g Dec=%g h^-1 cMpc" % (mmd_freq[1], ra_extent_z2, dec_extent_z2)
print "at %g MHz, pixel width in RA=%g Dec=%g h^-1 cMpc" % (
mmd_freq[1],
ra_pixel_extent_z2,
dec_pixel_extent_z2,
)
print "the freq bin starting at %g MHz has width %g" % (mmd_freq[1], redshift_pixel_extent_z2)
print "-" * 80
# return the sampling at the finest resolution
return (pixelfrac_ramax, pixelfrac_decmax)
from utils import cosmology from simulations import corr from utils.cosmology import Cosmology redshift = 1. cosmo = Cosmology() proper = cosmo.proper_distance(redshift) comoving = cosmo.comoving_distance(redshift) comoving_inv = cosmology.inverse_approx(cosmo.comoving_distance, 0.6, 1.) print proper, comoving, comoving_inv(2355.35909781)
def make_cube_movie(source_key, colorbar_title, frame_dir,
filetag_suffix="", saveslice=None, saveslice_file=None,
outputdir="./", sigmarange=6., ignore=None, multiplier=1.,
transverse=False, title=None, sigmacut=None,
logscale=False, physical=False, convolve=False, tag=None):
"""Make a stack of spatial slice maps and animate them
transverse plots along RA and freq and image plane is in Dec
First mask any points that exceed `sigmacut`, and then report the extent of
`sigmarange` away from the mean
"""
datapath_db = data_paths.DataPath()
cosmology = Cosmology()
littleh = (cosmology.H0 / 100.0)
beam_data = np.array([0.316148488246, 0.306805630985, 0.293729620792,
0.281176247549, 0.270856788455, 0.26745856078,
0.258910010848, 0.249188429031])
freq_data = np.array([695, 725, 755, 785, 815, 845, 875, 905],
dtype=float)
beam_fwhm = interp1d(freq_data, beam_data)
freq_data_Hz = freq_data * 1.0e6
if tag is None:
tag = '_'.join(source_key.split(";"))
tag = '-'.join(tag.split(":"))
# for a given path
#tag = ".".join(source_key.split(".")[:-1]) # extract root name
#tag = tag.split("/")[-1]
if title is None:
title = "%(tag)s (i = %(index)d, "
title += "freq = %(freq)3.1f MHz, z = %(redshift)3.3f, "
title += "Dc=%(distance)3.0f cMpc)"
print tag
fileprefix = frame_dir + tag
nlevels = 500
if transverse:
orientation = "_freqRA"
else:
orientation = "_RADec"
# prepare the data
#cube = algebra.make_vect(algebra.load(source_key)) * multiplier
cube = datapath_db.fetch_multi(source_key) * multiplier
if logscale:
cube[cube < 0] = np.min(np.abs(cube))
cube = np.log10(cube)
isnan = np.isnan(cube)
isinf = np.isinf(cube)
maskarray = ma.mask_or(isnan, isinf)
if ignore is not None:
maskarray = ma.mask_or(maskarray, (cube == ignore))
convolved = ""
if convolve:
convolved = "_convolved"
beamobj = beam.GaussianBeam(beam_data, freq_data_Hz)
cube = beamobj.apply(cube)
if sigmacut:
#np.set_printoptions(threshold=np.nan, precision=4)
deviation = np.abs((cube - np.mean(cube)) / np.std(cube))
extend_maskarray = (cube > (sigmacut * deviation))
maskarray = ma.mask_or(extend_maskarray, maskarray)
mcube = ma.masked_array(cube, mask=maskarray)
try:
whmaskarray = np.where(maskarray)[0]
mask_fraction = float(len(whmaskarray)) / float(cube.size)
except:
mask_fraction = 0.
print "fraction of map clipped: %f" % mask_fraction
(cube_mean, cube_std) = (mcube.mean(), mcube.std())
print "cube mean=%g std=%g" % (cube_mean, cube_std)
try:
len(sigmarange)
color_axis = np.linspace(sigmarange[0], sigmarange[1],
nlevels, endpoint=True)
except TypeError:
if (sigmarange > 0.):
color_axis = np.linspace(cube_mean - sigmarange * cube_std,
cube_mean + sigmarange * cube_std,
nlevels, endpoint=True)
else:
if saveslice is not None:
color_axis = np.linspace(ma.min(mcube[saveslice, :, :]),
ma.max(mcube[saveslice, :, :]),
nlevels, endpoint=True)
else:
color_axis = np.linspace(ma.min(mcube), ma.max(mcube),
nlevels, endpoint=True)
print "using range: [%g, %g]" % (np.min(color_axis), np.max(color_axis))
freq_axis = cube.get_axis('freq')
(ra_axis, dec_axis) = (cube.get_axis('ra'), cube.get_axis('dec'))
runlist = []
# TODO: make transverse work with gnuplot
if transverse:
for decind in range(cube.shape[2]):
fulltitle = tag + " (dec = %3.1f)" % (dec_axis[decind])
runlist.append((decind, cube[:, :, decind], freq_axis,
ra_axis, color_axis, ["Freq", "Ra"], 20.,
fulltitle, colorbar_title, fileprefix, 800.))
else:
for freqind in range(cube.shape[0]):
outfilename = fileprefix + str('.%03d' % freqind) + '.jpeg'
# if in angle, freq coordinates
if not physical:
freq_MHz = freq_axis[freqind] / 1.e6
z_here = cc.freq_21cm_MHz / freq_MHz - 1.
comoving_distance = cosmology.comoving_distance(z_here) / littleh
proper_distance = cosmology.proper_distance(z_here) / littleh
angular_scale = 20. / units.degree / proper_distance
title_info = {"index": freqind,
"redshift": z_here,
"distance": comoving_distance,
"freq": freq_MHz,
"tag": tag}
fulltitle = title % title_info
if (freq_MHz <= freq_data.min()) or \
(freq_MHz >= freq_data.max()):
fwhm = 0.
else:
fwhm = beam_fwhm(freq_MHz)
FWHM_circle = {"primitive": "circle",
"center_x": 0.9,
"center_y": 0.15,
"radius": fwhm / 2.,
"width": 5,
"color": "purple" }
region_scale = {"primitive": "rect",
"center_x": 0.9,
"center_y": 0.15,
"size_x": angular_scale,
"size_y": angular_scale,
"width": 3,
"color": "black" }
draw_objects = [FWHM_circle, region_scale]
runlist.append((outfilename, cube[freqind, :, :], ra_axis,
dec_axis, color_axis, ["RA", "Dec"], 1.,
fulltitle, colorbar_title, draw_objects))
else:
distance = freq_axis[freqind] / 1.e6
fulltitle = "%s (i = %d, Dc = %10.3f cMpc)" % \
(title, freqind, distance)
runlist.append((outfilename, cube[freqind, :, :], ra_axis,
dec_axis, color_axis,
["x (RA, cMpc/h)", "y (Dec, cMpc/h)"], 1.,
fulltitle, colorbar_title, draw_objects))
if saveslice is not None:
print "saving just slice %d" % saveslice
(outfilename, cube_slice, xaxis, yaxis, vaxis, xylabels, \
aspect, fulltitle, cbar_title, draw_objects) = runlist[saveslice]
plot_slice.gnuplot_2D(outfilename, cube_slice, xaxis, yaxis, vaxis, xylabels,
aspect, fulltitle, cbar_title,
eps_outfile=saveslice_file,
draw_objects=draw_objects)
else:
pool = multiprocessing.Pool(processes=(multiprocessing.cpu_count() - 4))
pool.map(gnuplot_single_slice, runlist)
#gnuplot_single_slice(runlist[0]) # for troubleshooting
argument = frame_dir + tag + '.%03d.jpeg'
outfile = outputdir + tag + filetag_suffix + orientation + convolved + '.mp4'
subprocess.check_call(('ffmpeg', '-vb', '2500000', '-r', '10',
'-y', '-i', argument, outfile))
for fileindex in range(len(runlist)):
os.remove(fileprefix + str('.%03d' % fileindex) + '.jpeg')
