def plot_15hr_selection():
"""make plots of the 15hr selection
"""
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/binned_wiggleZ/"
pc.make_cube_movie(root_directory + "reg15montecarlo.npy",
"reg15montecarlo",
"MC Selection",
cube_frame_dir + "reg15montecarlo",
sigmarange=None)
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/binned_wiggleZ/"
pc.make_cube_movie(root_directory + "reg15separable.npy",
"15hr_Wigglez_separable_selection", "# galaxies/pixel",
cube_frame_dir + "15hr_Wigglez_separable_selection")
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/binned_wiggleZ/"
pc.make_cube_movie(root_directory + "reg15selection.npy",
"15hr_Wigglez_selection", "# galaxies/pixel",
cube_frame_dir + "15hr_Wigglez_selection")
pc.make_cube_movie("delta_selection.npy", "delta_selection",
"Difference in selection",
cube_frame_dir + "delta_selection")
pc.make_cube_movie("reg15selection_est.npy",
"reg15selection_est",
"Full selection",
cube_frame_dir + "reg15selection_est",
sigmarange=None)
def plot_gbt_simset(fieldname, outputdir="/cita/d/www/home/eswitzer/movies/"):
datapath_db = data_paths.DataPath()
#keyname = "%s" % fieldname
#filename = datapath_db.fetch(keyname, pick='0')
#pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
# sigmarange=3., outputdir=outputdir, multiplier=1000.,
# transverse=False, filetag_suffix="_"+fieldname)
#keyname = "%s_beam" % fieldname
#filename = datapath_db.fetch(keyname, pick='0')
#pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
# sigmarange=3., outputdir=outputdir, multiplier=1000.,
# transverse=False, filetag_suffix="_"+fieldname)
#keyname = "%s_beam_conv" % fieldname
#filename = datapath_db.fetch(keyname, pick='0')
#pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
# sigmarange=3., outputdir=outputdir, multiplier=1000.,
# transverse=False, filetag_suffix="_"+fieldname)
keyname = "%s_beam_meansub" % fieldname
filename = datapath_db.fetch(keyname, pick='0')
pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
sigmarange=3., outputdir=outputdir, multiplier=1000.,
transverse=False, filetag_suffix="_"+fieldname)
keyname = "%s_beam_meansubconv" % fieldname
filename = datapath_db.fetch(keyname, pick='0')
pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
sigmarange=3., outputdir=outputdir, multiplier=1000.,
transverse=False, filetag_suffix="_"+fieldname)
def plot_mode_amplitudes(mapkey, outputdir="/cita/d/www/home/eswitzer/movies/"):
datapath_db = data_paths.DataPath()
map_cases = datapath_db.fileset_cases(mapkey, "pair;product;treatment")
print map_cases
for pair in map_cases['pair']:
source_key = "db:%s:%s;modes;100modes" % (mapkey, pair)
pc.make_cube_movie(source_key, "Mode amp", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False, convolve=False, logscale=True)
def plot_individual(filename, outputdir="/cita/d/www/home/eswitzer/movies/"):
pc.make_cube_movie(filename,
"Temperature (mK)",
pc.cube_frame_dir,
sigmarange=3.,
outputdir=outputdir,
multiplier=1000.,
transverse=False,
filetag_suffix="_simloss",
physical=True)
def plot_first_few_amps(dbitem, modelist):
datapath_db = data_paths.DataPath()
frame_dir = "/scratch/eswitzer/cube_frames/"
dbname = "db:%s:A_with_B;modes;100modes" % dbitem
for modeindex in modelist:
filename = "%s_%d.eps" % (dbitem, modeindex)
plot_cube.make_cube_movie(dbname,
"Amplitude", frame_dir,
saveslice=modeindex, saveslice_file=filename,
sigmarange=-1, multiplier=1.,
title="%s" % filename)
def plot_window(outputdir="/cita/d/www/home/eswitzer/movies/"):
file1 = './observed_window.npy'
file2 = './physical_window.npy'
fieldname = '15hr'
pc.make_cube_movie(file1, "Window", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False, filetag_suffix="_"+fieldname,
physical=True)
pc.make_cube_movie(file2, "Window", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False, filetag_suffix="_"+fieldname,
physical=True)
def plot_manual(fieldname, outputdir="/cita/d/www/home/eswitzer/movies/"):
datapath_db = data_paths.DataPath()
file2 = './physical_cube.npy'
keyname = "simideal_%s_physical" % fieldname
filename = datapath_db.fetch(keyname, pick='1')
pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
sigmarange=3., outputdir=outputdir, multiplier=1000.,
transverse=False, filetag_suffix="_"+fieldname,
physical=True)
pc.make_cube_movie(file2, "Temperature (mK)", pc.cube_frame_dir,
sigmarange=3., outputdir=outputdir, multiplier=1000.,
transverse=False, filetag_suffix="_"+fieldname,
physical=True)
def plot_mode_amplitudes(mapkey,
outputdir="/cita/d/www/home/eswitzer/movies/"):
datapath_db = data_paths.DataPath()
map_cases = datapath_db.fileset_cases(mapkey, "pair;product;treatment")
print map_cases
for pair in map_cases['pair']:
source_key = "db:%s:%s;modes;100modes" % (mapkey, pair)
pc.make_cube_movie(source_key,
"Mode amp",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False,
convolve=False,
logscale=True)
def plot_first_few_amps(dbitem, modelist):
datapath_db = data_paths.DataPath()
frame_dir = "/scratch/eswitzer/cube_frames/"
dbname = "db:%s:A_with_B;modes;100modes" % dbitem
for modeindex in modelist:
filename = "%s_%d.eps" % (dbitem, modeindex)
plot_cube.make_cube_movie(dbname,
"Amplitude",
frame_dir,
saveslice=modeindex,
saveslice_file=filename,
sigmarange=-1,
multiplier=1.,
title="%s" % filename)
def plotting(filename, file_directory="/tmp/mufma/data/",
title_name="Video", scale_name="Temperature(mK)",
frame_directory="/tmp/mufma/data/", data_type="npy",
output_directory="/cita/d/www/home/mufma/movies/",
multiplier_num=1000.):
r"""given a datafile plot a movie to www directory"""
# TODO: determine how to specify title
datapath_db = data_paths.DataPath()
frame_dir = frame_directory
given_tag = string.rstrip(filename, data_type)
plot_cube.make_cube_movie(file_directory+filename, scale_name,
frame_dir,
sigmarange=[0., 0.5*10.**(11)],
multiplier=multiplier_num,
title=title_name,
outputdir=output_directory,
tag=given_tag)
def save_and_plot(array, template, filename):
array = algebra.make_vect(array, axis_names=('freq', 'ra', 'dec'))
array.copy_axis_info(template)
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)
freq_data *= 1.0e6
beamobj = beam.GaussianBeam(beam_data, freq_data)
array_beam = beamobj.apply(array)
algebra.save(filename, array_beam)
outputdir = "/cita/d/www/home/eswitzer/movies/"
pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
sigmarange=3., outputdir=outputdir, multiplier=1000.,
transverse=False, filetag_suffix="_trial")
def plot_gbt_simset(fieldname, outputdir="/cita/d/www/home/eswitzer/movies/"):
datapath_db = data_paths.DataPath()
#keyname = "%s" % fieldname
#filename = datapath_db.fetch(keyname, pick='0')
#pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
# sigmarange=3., outputdir=outputdir, multiplier=1000.,
# transverse=False, filetag_suffix="_"+fieldname)
#keyname = "%s_beam" % fieldname
#filename = datapath_db.fetch(keyname, pick='0')
#pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
# sigmarange=3., outputdir=outputdir, multiplier=1000.,
# transverse=False, filetag_suffix="_"+fieldname)
#keyname = "%s_beam_conv" % fieldname
#filename = datapath_db.fetch(keyname, pick='0')
#pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
# sigmarange=3., outputdir=outputdir, multiplier=1000.,
# transverse=False, filetag_suffix="_"+fieldname)
keyname = "%s_beam_meansub" % fieldname
filename = datapath_db.fetch(keyname, pick='0')
pc.make_cube_movie(filename,
"Temperature (mK)",
pc.cube_frame_dir,
sigmarange=3.,
outputdir=outputdir,
multiplier=1000.,
transverse=False,
filetag_suffix="_" + fieldname)
keyname = "%s_beam_meansubconv" % fieldname
filename = datapath_db.fetch(keyname, pick='0')
pc.make_cube_movie(filename,
"Temperature (mK)",
pc.cube_frame_dir,
sigmarange=3.,
outputdir=outputdir,
multiplier=1000.,
transverse=False,
filetag_suffix="_" + fieldname)
def plot_gbt_comb_modeset(map_key, outputdir="/cita/d/www/home/eswitzer/movies/",
convolve=False, divider_token=";"):
datapath_db = data_paths.DataPath()
input_fdb = datapath_db.fetch(map_key, intend_read=True, silent=True)
map_treatments = []
for filekey in input_fdb[0]:
keyparse = filekey.split(divider_token)
if len(keyparse) == 2:
treatment = keyparse[-1]
if "modes" in treatment:
map_treatments.append(treatment)
map_treatments = unique_list(map_treatments)
for treatment in map_treatments:
source_key = "db:%s:map;%s" % (map_key, treatment)
print source_key, treatment
pc.make_cube_movie(source_key, "Temperature (mK)", pc.cube_frame_dir,
sigmarange=3., outputdir=outputdir, multiplier=1000.,
transverse=False, convolve=convolve)
source_key = "db:%s:product;%s" % (map_key, treatment)
pc.make_cube_movie(source_key, "Cleaned map times weights", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1000.,
transverse=False, convolve=convolve)
source_key = "db:%s:weight;%s" % (map_key, treatment)
pc.make_cube_movie(source_key, "inverse variance weight", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False)
def plot_window(outputdir="/cita/d/www/home/eswitzer/movies/"):
file1 = './observed_window.npy'
file2 = './physical_window.npy'
fieldname = '15hr'
pc.make_cube_movie(file1,
"Window",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False,
filetag_suffix="_" + fieldname,
physical=True)
pc.make_cube_movie(file2,
"Window",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False,
filetag_suffix="_" + fieldname,
physical=True)
def plot_wigglez(fieldname, outputdir="/cita/d/www/home/eswitzer/movies/",
complete=False):
datapath_db = data_paths.DataPath()
if complete:
ctag = "complete_"
else:
ctag = ""
db_key = "WiggleZ_%s_%sdelta_binned_data" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename, "counts", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False, filetag_suffix="_"+fieldname)
db_key = "WiggleZ_%s_%sbinned_data" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename, "counts", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False, filetag_suffix="_"+fieldname)
db_key = "WiggleZ_%s_%sselection" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename, "selection", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False, filetag_suffix="_"+fieldname)
db_key = "WiggleZ_%s_%sseparable_selection" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename, "selection", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False, filetag_suffix="_"+fieldname)
db_key = "WiggleZ_%s_%smontecarlo" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename, "selection", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1.,
transverse=False, filetag_suffix="_"+fieldname)
def plot_15hr_selection():
"""make plots of the 15hr selection
"""
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/binned_wiggleZ/"
pc.make_cube_movie(root_directory + "reg15montecarlo.npy",
"reg15montecarlo",
"MC Selection", cube_frame_dir + "reg15montecarlo",
sigmarange=None)
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/binned_wiggleZ/"
pc.make_cube_movie(root_directory + "reg15separable.npy",
"15hr_Wigglez_separable_selection",
"# galaxies/pixel", cube_frame_dir + "15hr_Wigglez_separable_selection")
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/binned_wiggleZ/"
pc.make_cube_movie(root_directory + "reg15selection.npy",
"15hr_Wigglez_selection",
"# galaxies/pixel", cube_frame_dir + "15hr_Wigglez_selection")
pc.make_cube_movie("delta_selection.npy",
"delta_selection",
"Difference in selection", cube_frame_dir + "delta_selection")
pc.make_cube_movie("reg15selection_est.npy",
"reg15selection_est",
"Full selection", cube_frame_dir + "reg15selection_est",
sigmarange=None)
def plot_manual(fieldname, outputdir="/cita/d/www/home/eswitzer/movies/"):
datapath_db = data_paths.DataPath()
file2 = './physical_cube.npy'
keyname = "simideal_%s_physical" % fieldname
filename = datapath_db.fetch(keyname, pick='1')
pc.make_cube_movie(filename,
"Temperature (mK)",
pc.cube_frame_dir,
sigmarange=3.,
outputdir=outputdir,
multiplier=1000.,
transverse=False,
filetag_suffix="_" + fieldname,
physical=True)
pc.make_cube_movie(file2,
"Temperature (mK)",
pc.cube_frame_dir,
sigmarange=3.,
outputdir=outputdir,
multiplier=1000.,
transverse=False,
filetag_suffix="_" + fieldname,
physical=True)
def plot_gbt_comb_modeset(map_key,
outputdir="/cita/d/www/home/eswitzer/movies/",
convolve=False,
divider_token=";"):
datapath_db = data_paths.DataPath()
input_fdb = datapath_db.fetch(map_key, intend_read=True, silent=True)
map_treatments = []
for filekey in input_fdb[0]:
keyparse = filekey.split(divider_token)
if len(keyparse) == 2:
treatment = keyparse[-1]
if "modes" in treatment:
map_treatments.append(treatment)
map_treatments = unique_list(map_treatments)
for treatment in map_treatments:
source_key = "db:%s:map;%s" % (map_key, treatment)
print source_key, treatment
pc.make_cube_movie(source_key,
"Temperature (mK)",
pc.cube_frame_dir,
sigmarange=3.,
outputdir=outputdir,
multiplier=1000.,
transverse=False,
convolve=convolve)
source_key = "db:%s:product;%s" % (map_key, treatment)
pc.make_cube_movie(source_key,
"Cleaned map times weights",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1000.,
transverse=False,
convolve=convolve)
source_key = "db:%s:weight;%s" % (map_key, treatment)
pc.make_cube_movie(source_key,
"inverse variance weight",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False)
def plot_15hr_selection():
"""make plots of the 22hr selection
"""
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/binned_wiggleZ/"
pc.make_cube_movie(root_directory + "reg22montecarlo.npy",
"reg22montecarlo",
"MC Selection", cube_frame_dir + "reg22montecarlo",
sigmarange=None)
pc.make_cube_movie(root_directory + "reg22selection.npy",
"reg22selection",
"Selection", cube_frame_dir + "reg22selection",
sigmarange=None)
pc.make_cube_movie(root_directory + "reg22separable.npy",
"reg22separable",
"Separable Selection", cube_frame_dir + "reg22separable",
sigmarange=None)
def plot_15hr_selection():
"""make plots of the 22hr selection
"""
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/binned_wiggleZ/"
pc.make_cube_movie(root_directory + "reg22montecarlo.npy",
"reg22montecarlo",
"MC Selection",
cube_frame_dir + "reg22montecarlo",
sigmarange=None)
pc.make_cube_movie(root_directory + "reg22selection.npy",
"reg22selection",
"Selection",
cube_frame_dir + "reg22selection",
sigmarange=None)
pc.make_cube_movie(root_directory + "reg22separable.npy",
"reg22separable",
"Separable Selection",
cube_frame_dir + "reg22separable",
sigmarange=None)
sigmarange=None)
pc.make_cube_movie(root_directory + "reg22selection.npy",
"reg22selection",
"Selection", cube_frame_dir + "reg22selection",
sigmarange=None)
pc.make_cube_movie(root_directory + "reg22separable.npy",
"reg22separable",
"Separable Selection", cube_frame_dir + "reg22separable",
sigmarange=None)
# make plots of the 15hr field
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/combined_maps/"
pc.make_cube_movie(root_directory + "combined_41-73_cleaned_clean_test.npy",
"combined_41-73_cleaned_clean_test",
"Temperature (mK)", cube_frame_dir + "combined_41-73_cleaned_clean_test",
sigmarange=6., multiplier = 1000.)
pc.make_cube_movie(root_directory + "combined_41-73_cleaned_noise_inv_test.npy",
"combined_41-73_cleaned_noise_inv_test",
"Covariance", cube_frame_dir + "combined_41-73_cleaned_noise_inv_test",
sigmarange=-1)
# make plots of the 22hr field
#root_directory = "/mnt/raid-project/gmrt/calinliv/wiggleZ/corr/84_ABCD_all_15_modes/"
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/combined_maps/"
pc.make_cube_movie(root_directory + "combined_22hr_41-84_cleaned_clean.npy",
"combined_22hr_41-84_cleaned_clean.npy",
"Temperature (mK)", cube_frame_dir + "combined_22hr_41-84_cleaned_clean.npy",
sigmarange=6, multiplier = 1000.)
pc.make_cube_movie(root_directory + "combined_22hr_41-84_cleaned_noise_inv.npy",
diagweight_file = "diag_noise_inv_weight.npy"
# load the diag(N^-1)
#noise_inv = algebra.make_mat(algebra.open_memmap(fullnoiseinv_file, mode='r'))
#noise_inv_diag = noise_inv.mat_diag()
#algebra.save(fullweight_file, noise_inv_diag)
# load the diag(N) and take the inverse, write to disk
#diag_noise = algebra.make_vect(algebra.load(diagnoise_file))
#diag_noise_inv = 1./diag_noise
#diag_noise_inv[diag_noise < 1.e-20] = 0.
#algebra.save(diagweight_file, 1./diag_noise)
# make movies of both
outputdir = "/cita/d/www/home/eswitzer/movies/"
pc.make_cube_movie(fullweight_file,
"Full N^-1",
pc.cube_frame_dir,
sigmarange=[0, 1e7],
outputdir=outputdir,
multiplier=1000.,
transverse=False)
pc.make_cube_movie(diagweight_file,
"(diag N)^-1",
pc.cube_frame_dir,
sigmarange=[0, 1e7],
outputdir=outputdir,
multiplier=1000.,
transverse=False)
def plot_individual(filename, outputdir="/cita/d/www/home/eswitzer/movies/"):
pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
sigmarange=3., outputdir=outputdir, multiplier=1000.,
transverse=False, filetag_suffix="_simloss",
physical=True)
"Selection",
cube_frame_dir + "reg22selection",
sigmarange=None)
pc.make_cube_movie(root_directory + "reg22separable.npy",
"reg22separable",
"Separable Selection",
cube_frame_dir + "reg22separable",
sigmarange=None)
# make plots of the 15hr field
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/combined_maps/"
pc.make_cube_movie(root_directory + "combined_41-73_cleaned_clean_test.npy",
"combined_41-73_cleaned_clean_test",
"Temperature (mK)",
cube_frame_dir + "combined_41-73_cleaned_clean_test",
sigmarange=6.,
multiplier=1000.)
pc.make_cube_movie(root_directory +
"combined_41-73_cleaned_noise_inv_test.npy",
"combined_41-73_cleaned_noise_inv_test",
"Covariance",
cube_frame_dir + "combined_41-73_cleaned_noise_inv_test",
sigmarange=-1)
# make plots of the 22hr field
#root_directory = "/mnt/raid-project/gmrt/calinliv/wiggleZ/corr/84_ABCD_all_15_modes/"
root_directory = "/mnt/raid-project/gmrt/eswitzer/wiggleZ/combined_maps/"
pc.make_cube_movie(root_directory + "combined_22hr_41-84_cleaned_clean.npy",
"combined_22hr_41-84_cleaned_clean.npy",
"Temperature (mK)",
input_root = '/mnt/raid-project/gmrt/kiyo/gbt_out/maps/apr16.2012/'
fullpath_maplist = [ input_root + item for item in maplist]
weightlist = ["sess_%d_calib_15hr_41-73_weight_I.npy" % item for item in live_sessions]
output_root = "/mnt/raid-project/gmrt/eswitzer/GBT/maps/self_calibrated_2/"
weightlist_fullpath = [ output_root + item for item in weightlist]
reference_clean = [input_root + "sess_most_calib_15hr_41-73_clean_map_I.npy"]
reference_weight = [output_root + "sess_most_calib_15hr_41-73_weight_I.npy"]
#for filename in weightlist_fullpath:
for filename in reference_weight:
outputdir = "/cita/d/www/home/eswitzer/movies/"
tag = ".".join(filename.split(".")[:-1]) # extract root name
tag = tag.split("/")[-1]
tag += "_v2"
pc.make_cube_movie(filename, "Weight", pc.cube_frame_dir,
sigmarange=-1, outputdir=outputdir, multiplier=1000.,
transverse=False, filetag_suffix="", tag=tag)
#for filename in fullpath_maplist:
for filename in reference_clean:
outputdir = "/cita/d/www/home/eswitzer/movies/"
tag = ".".join(filename.split(".")[:-1]) # extract root name
tag = tag.split("/")[-1]
tag += "_v2"
pc.make_cube_movie(filename, "Temperature (mK)", pc.cube_frame_dir,
sigmarange=3., outputdir=outputdir, multiplier=1000.,
transverse=False, filetag_suffix="", tag=tag)
from plotting import plot_cube as pc
if __name__ == '__main__':
root = "/mnt/raid-project/gmrt/tcv/maps/"
fullnoiseinv_file = root + "sec_A_15hr_41-90_noise_inv_I.npy"
fullweight_file = "full_noise_inv_weight.npy"
diagnoise_file = root + "sec_A_15hr_41-90_noise_diag_I.npy"
diagweight_file = "diag_noise_inv_weight.npy"
# load the diag(N^-1)
#noise_inv = algebra.make_mat(algebra.open_memmap(fullnoiseinv_file, mode='r'))
#noise_inv_diag = noise_inv.mat_diag()
#algebra.save(fullweight_file, noise_inv_diag)
# load the diag(N) and take the inverse, write to disk
#diag_noise = algebra.make_vect(algebra.load(diagnoise_file))
#diag_noise_inv = 1./diag_noise
#diag_noise_inv[diag_noise < 1.e-20] = 0.
#algebra.save(diagweight_file, 1./diag_noise)
# make movies of both
outputdir="/cita/d/www/home/eswitzer/movies/"
pc.make_cube_movie(fullweight_file, "Full N^-1", pc.cube_frame_dir,
sigmarange=[0,1e7], outputdir=outputdir, multiplier=1000.,
transverse=False)
pc.make_cube_movie(diagweight_file, "(diag N)^-1", pc.cube_frame_dir,
sigmarange=[0,1e7], outputdir=outputdir, multiplier=1000.,
transverse=False)
def plot_wigglez(fieldname,
outputdir="/cita/d/www/home/eswitzer/movies/",
complete=False):
datapath_db = data_paths.DataPath()
if complete:
ctag = "complete_"
else:
ctag = ""
db_key = "WiggleZ_%s_%sdelta_binned_data" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename,
"counts",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False,
filetag_suffix="_" + fieldname)
db_key = "WiggleZ_%s_%sbinned_data" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename,
"counts",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False,
filetag_suffix="_" + fieldname)
db_key = "WiggleZ_%s_%sselection" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename,
"selection",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False,
filetag_suffix="_" + fieldname)
db_key = "WiggleZ_%s_%sseparable_selection" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename,
"selection",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False,
filetag_suffix="_" + fieldname)
db_key = "WiggleZ_%s_%smontecarlo" % (fieldname, ctag)
filename = datapath_db.fetch(db_key)
pc.make_cube_movie(filename,
"selection",
pc.cube_frame_dir,
sigmarange=-1,
outputdir=outputdir,
multiplier=1.,
transverse=False,
filetag_suffix="_" + fieldname)
#full_list = ["/mnt/raid-project/gmrt/eswitzer/GBT/maps/1hr_oldcal_july16/secA_1hr_41-90_clean_map_I_800.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/1hr_oldcal_july16/secA_1hr_41-90_noise_weight_I_800.npy"]
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/1hr_oldcal_july16/secA_1hr_41-90_noise_weight_I_800.npy"]
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/1hr_oldcal_july16/secA_1hr_41-90_noise_weight_I_800.npy"]
#full_list = ["/mnt/raid-project/gmrt/eswitzer/GBT/maps/1hr_oldcal_july16/secB_1hr_41-90_noise_weight_I_800.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/1hr_oldcal_july16/secC_1hr_41-90_noise_weight_I_800.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/1hr_oldcal_july16/secD_1hr_41-90_noise_weight_I_800.npy"]
#full_list = ["/mnt/raid-project/gmrt/eswitzer/GBT/maps/15hr_optimal_july11/secA_15hr_41-90_clean_map_I_all.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/15hr_optimal_july11/secB_15hr_41-90_clean_map_I_all.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/15hr_optimal_july11/secC_15hr_41-90_clean_map_I_all.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/15hr_optimal_july11/secD_15hr_41-90_clean_map_I_all.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/15hr_optimal_july11/secA_15hr_41-90_noise_inv_diag_I_all.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/15hr_optimal_july11/secB_15hr_41-90_noise_inv_diag_I_all.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/15hr_optimal_july11/secC_15hr_41-90_noise_inv_diag_I_all.npy",
# "/mnt/raid-project/gmrt/eswitzer/GBT/maps/15hr_optimal_july11/secD_15hr_41-90_noise_inv_diag_I_all.npy"]
cbtitle = ""
multiplier = 1.
#sigmarange = -1.
sigmarange = 4.
for filename in full_list:
outputdir = "/cita/d/www/home/eswitzer/movies/"
tag = ".".join(filename.split(".")[:-1]) # extract root name
tag = tag.split("/")[-1]
pc.make_cube_movie(filename, cbtitle, pc.cube_frame_dir,
sigmarange=sigmarange, outputdir=outputdir,
multiplier=multiplier, logscale=False,
transverse=False, filetag_suffix="", tag=tag)
# "Temperature (mK)", frame_dir,
# saveslice=127, saveslice_file="GBT_15hr_map_secA.eps",
# sigmarange=3., multiplier=1000.,
# title="GBT 15hr field (%(freq)3.1f MHz, z = %(redshift)3.3f)")
#plot_cube.make_cube_movie("db:GBT_1hr_map_oldcalkiyo:A;clean_map",
# "Temperature (mK)", frame_dir,
# saveslice=127, saveslice_file="GBT_1hr_map_secA.eps",
# sigmarange=3., multiplier=1000.,
# title="GBT 1hr field (%(freq)3.1f MHz, z = %(redshift)3.3f)")
plot_cube.make_cube_movie(
"db:GBT_15hr_map_oldcal_cleaned_combined:map;20modes",
"Temperature (mK)",
frame_dir,
saveslice=127,
saveslice_file="cleaned_15hr_map_20modes.eps",
sigmarange=0.4,
multiplier=1000.,
title="GBT 15hr field, cleaned (%(freq)3.1f MHz, z = %(redshift)3.3f)")
plot_cube.make_cube_movie(
"db:GBT_15hr_map_oldcal_cleaned_combined:map;20modes",
"Temperature (mK)",
frame_dir,
saveslice=127,
saveslice_file="cleaned_15hr_map_20modes_convolved.eps",
convolve=True,
sigmarange=0.4,
multiplier=1000.,
title=
