def calc_dt(xfrac, dens, z=-1):
'''
Calculate the differential brightness temperature assuming T_s >> T_CMB
Parameters:
* xfrac (XfracFile object, string or numpy array): the ionization fraction
* dens (DensityFile object, string or numpy array): density in cgs units
* z = -1 (float): The redshift (if < 0 this will be figured out from the files)
Returns:
The differential brightness temperature as a numpy array with
the same dimensions as xfrac.
'''
xi, xi_type = get_data_and_type(xfrac)
rho, rho_type = get_data_and_type(dens)
xi = xi.astype('float64')
rho = rho.astype('float64')
if z < 0:
z = determine_redshift_from_filename(xfrac)
if z < 0:
z = determine_redshift_from_filename(dens)
if z < 0:
raise Exception(
'No redshift specified. Could not determine from file.')
print_msg('Making dT box for z=%f' % z)
#Calculate dT
return _dt(rho, xi, z)
def calc_dt(xfrac, dens, z=-1):
"""
Calculate the differential brightness temperature assuming T_s >> T_CMB
Parameters:
* xfrac (XfracFile object, string or numpy array): the ionization fraction
* dens (DensityFile object, string or numpy array): density in cgs units
* z = -1 (float): The redshift (if < 0 this will be figured out from the files)
Returns:
The differential brightness temperature as a numpy array with
the same dimensions as xfrac.
"""
xi, xi_type = get_data_and_type(xfrac)
rho, rho_type = get_data_and_type(dens)
xi = xi.astype("float64")
rho = rho.astype("float64")
if z < 0:
z = determine_redshift_from_filename(xfrac)
if z < 0:
z = determine_redshift_from_filename(dens)
if z < 0:
raise Exception("No redshift specified. Could not determine from file.")
print_msg("Making dT box for z=%f" % z)
# Calculate dT
return _dt(rho, xi, z)
def calc_dt_full(xfrac, dens, temp, z = -1, correct=True):
'''
Calculate the differential brightness temperature assuming only that Lyman alpha is fully coupled so T_s = T_k
(NOT T_s >> T_CMB)
Parameters:
* xfrac (XfracFile object, string or numpy array): the ionization fraction
* dens (DensityFile object, string or numpy array): density in cgs units
* temp (TemperFile object, string or numpy array): the temperature in K
* z = -1 (float): The redshift (if < 0 this will be figured out from the files)
* correct = True (bool): if true include a correction for partially ionized cells.
Returns:
The differential brightness temperature as a numpy array with
the same dimensions as xfrac.
'''
xi, xi_type = get_data_and_type(xfrac)
Ts, Ts_type = get_data_and_type(temp)
rho, rho_type = get_data_and_type(dens)
xi = xi.astype('float64')
Ts = Ts.astype('float64')
rho = rho.astype('float64')
if z < 0:
z = determine_redshift_from_filename(xfrac)
if z < 0: z = determine_redshift_from_filename(dens)
if z < 0: z = determine_redshift_from_filename(temp)
if z < 0: raise Exception('No redshift specified. Could not determine from file.')
print_msg('Making full dT box for z=%f' % z)
print "Calculating corrected dbt"
return _dt_full(rho, xi, Ts, z, correct)
def calc_dt_full(xfrac, temp, dens, z=-1):
"""
Calculate the differential brightness temperature assuming only that Lyman alpha is fully coupled so T_s = T_k
(NOT T_s >> T_CMB)
Parameters:
* xfrac (XfracFile object, string or numpy array): the ionization fraction
* temp (TemperFile object, string or numpy array): the temperature in K
* dens (DensityFile object, string or numpy array): density in cgs units
* z = -1 (float): The redshift (if < 0 this will be figured out from the files)
Returns:
The differential brightness temperature as a numpy array with
the same dimensions as xfrac.
"""
xi, xi_type = get_data_and_type(xfrac)
Ts, Ts_type = get_data_and_type(temp)
rho, rho_type = get_data_and_type(dens)
xi = xi.astype("float64")
Ts = Ts.astype("float64")
rho = rho.astype("float64")
if z < 0:
z = determine_redshift_from_filename(xfrac)
if z < 0:
z = determine_redshift_from_filename(dens)
if z < 0:
z = determine_redshift_from_filename(temp)
if z < 0:
raise Exception("No redshift specified. Could not determine from file.")
print_msg("Making full dT box for z=%f" % z)
# Calculate dT
print "calculating corrected dbt"
return _dt_full_corrected(dens, xfrac, temp, z) # rho, Ts, xi, z)
def calc_dt_full(xfrac, dens, temp, z=-1, correct=True):
'''
Calculate the differential brightness temperature assuming only that Lyman alpha is fully coupled so T_s = T_k
(NOT T_s >> T_CMB)
Parameters:
* xfrac (XfracFile object, string or numpy array): the ionization fraction
* dens (DensityFile object, string or numpy array): density in cgs units
* temp (TemperFile object, string or numpy array): the temperature in K
* z = -1 (float): The redshift (if < 0 this will be figured out from the files)
* correct = True (bool): if true include a correction for partially ionized cells.
Returns:
The differential brightness temperature as a numpy array with
the same dimensions as xfrac.
'''
xi, xi_type = get_data_and_type(xfrac)
Ts, Ts_type = get_data_and_type(temp)
rho, rho_type = get_data_and_type(dens)
xi = xi.astype('float64')
Ts = Ts.astype('float64')
rho = rho.astype('float64')
if z < 0:
z = determine_redshift_from_filename(xfrac)
if z < 0: z = determine_redshift_from_filename(dens)
if z < 0: z = determine_redshift_from_filename(temp)
if z < 0:
raise Exception(
'No redshift specified. Could not determine from file.')
print_msg('Making full dT box for z=%f' % z)
print "Calculating corrected dbt"
return _dt_full(rho, xi, Ts, z, correct)
def _get_file_redshifts(redshifts_in, filenames):
'''
If redshifts_in is None, try to determine from file names
If it's a directory, read the redshifts
Else, return as is
'''
if hasattr(redshifts_in, '__iter__'):
redshifts_out = redshifts_in
elif redshifts_in == None:
redshifts_out = [determine_redshift_from_filename(f) for f in filenames]
redshifts_out = np.array(redshifts_out)
elif os.path.exists(redshifts_in):
redshifts_out = np.loadtxt(redshifts_in)
else:
raise Exception('Invalid data for file redshifts.')
return redshifts_out
def _get_file_redshifts(redshifts_in, filenames):
'''
If redshifts_in is None, try to determine from file names
If it's a directory, read the redshifts
Else, return as is
'''
if hasattr(redshifts_in, '__iter__'):
redshifts_out = redshifts_in
elif redshifts_in == None:
redshifts_out = [
determine_redshift_from_filename(f) for f in filenames
]
redshifts_out = np.array(redshifts_out)
elif os.path.exists(redshifts_in):
redshifts_out = np.loadtxt(redshifts_in)
else:
raise Exception('Invalid data for file redshifts.')
return redshifts_out
