ULSA.sky_map.produce_absorbed_sky_map.absorption_JRZ¶
class:
class ULSA.sky_map.produce_absorbed_sky_map.absorption_JRZ(object):
method:
- __init__(self, v, nside, clumping_factor, index_type, distance, emi_form, I_E_form, R0_R1_equal, using_raw_diffuse, test, using_default_params=True, params_408=np.array([71.19, 4.23, 0.03, 0.47, 0.77]), critical_dis=False, output_absorp_free_skymap=False, beta_1=0.7, v_1=1.0)¶
initial parameter function
- Parameters
float (v) – The frequency of output sky map
nside (int) – The Nside value one choose in healpix mode, must be 2^N.
clumping_factor (int) – the clumping factor influnce the absorption, the value set to one in our model.
index_type (str) – (‘constant_index_minus_I_E’, ‘freq_dependence_index_minus_I_E’, ‘pixel_dependence_index_minus_I_E’), one of them can be choose as different type of spectral index one need to consider.
distance (int) – the maximux integrated distance of galaxy, normally setting to 50kpc.
emi_form – [‘exp’,’sech’] the distribution form of emissivity, normally choosen ‘exponantial’.
I_E_form (str) – (‘seiffert’), the form of extragalactic component except for CMB.
R0_R1_equal (bool) – fixed True
using_raw_diffuse (bool) – if True, using the raw input data without smoothing.
test (test bool) – if True, one can do some test with different parameter using in the code. normally fixed False.
using_default_params (bool) – if True, using the default spectral index value, if False calculate the spectral index value with the code, otherwise, one can simply input the spectral index to variable of using_default_params.
params_408 (array) – if the input of params_408 == [0.,0.,0.,0.,0.], the code will fit the parameters of emissivity in 408Mhz, or one can simply input the parameters of some other fitting result to params_408, if you input nothing, the code will take the default parameters.
critical_dis (bool) – if True, calculate the critial distance (time consuming), otherwise False.
output_absorp_free_skymap (bool) – if True, output the absorption free sky map in input frequency.
beta_1 (float) – beta = beta0 + beta_1*exp(freq/v_1)
v_1 (float) – beta = beta0 + beta_1*exp(freq/v_1)
- mpi()¶
return array([pixel_number, pixel_value]) in healpix mode, shape as (12*nside**2,2).
- Returns
a numpy array shape as [12*Nside^2, 2] will be return one can simply plot in healpy.mollview.
- Return type
np.array