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+# Copyright (c) 2016 Zhixian MA <zxma_sjtu@qq.com>
+# MIT license
+
+import numpy as np
+import healpy as hp
+
+# from .psparams import PixelParams
+from .base import BasePointSource
+from ...utils import grid
+from ...utils import convert
+from .psparams import PixelParams
+
+
+class StarForming(BasePointSource):
+ """
+ Generate star forming point sources, inheritate from PointSource class.
+
+ Reference
+ ---------
+ [1] Fast cirles drawing
+ https://github.com/liweitianux/fg21sim/fg21sim/utils/draw.py
+ https://github.com/liweitianux/fg21sim/fg21sim/utils/grid.py
+ """
+
+ def __init__(self, configs):
+ super().__init__(configs)
+ self.columns.append('radius (rad)')
+ self.nCols = len(self.columns)
+ self._set_configs()
+ # Number density matrix
+ self.rho_mat = self.calc_number_density()
+ # Cumulative distribution of z and lumo
+ self.cdf_z, self.cdf_lumo = self.calc_cdf()
+
+ def _set_configs(self):
+ """ Load the configs and set the corresponding class attributes"""
+ super()._set_configs()
+ pscomp = "extragalactic/pointsources/starforming/"
+ # point sources amount
+ self.num_ps = self.configs.getn(pscomp+"numps")
+ # prefix
+ self.prefix = self.configs.getn(pscomp+"prefix")
+ # redshift bin
+ z_type = self.configs.getn(pscomp+"z_type")
+ if z_type == 'custom':
+ start = self.configs.getn(pscomp+"z_start")
+ stop = self.configs.getn(pscomp+"z_stop")
+ step = self.configs.getn(pscomp+"z_step")
+ self.zbin = np.arange(start, stop + step, step)
+ else:
+ self.zbin = np.arange(0.1, 10, 0.05)
+ # luminosity bin
+ lumo_type = self.configs.getn(pscomp+"lumo_type")
+ if lumo_type == 'custom':
+ start = self.configs.getn(pscomp+"lumo_start")
+ stop = self.configs.getn(pscomp+"lumo_stop")
+ step = self.configs.getn(pscomp+"lumo_step")
+ self.lumobin = np.arange(start, stop + step, step)
+ else:
+ self.lumobin = np.arange(17, 25.5, 0.1) # [W/Hz/sr]
+
+ def calc_number_density(self):
+ """
+ Calculate number density rho(lumo,z) of FRI
+
+ References
+ ----------
+ [1] Wilman et al.,
+ "A semi-empirical simulation of the extragalactic radio continuum
+ sky for next generation radio telescopes",
+ 2008, MNRAS, 388, 1335-1348.
+ http://adsabs.harvard.edu/abs/2008MNRAS.388.1335W
+
+ Returns
+ -------
+ rho_mat: np.ndarray
+ Number density matris (joint-distribution of luminosity and
+ reshift).
+ """
+ # Init
+ rho_mat = np.zeros((len(self.lumobin), len(self.zbin)))
+ # Parameters
+ # Refer to Willman's section 2.4
+ alpha = 0.7 # spectral index
+ lumo_star = 10.0**22 # critical luminosity at 1400MHz
+ rho_l0 = 10.0**(-7) # normalization constant
+ z1 = 1.5 # cut-off redshift
+ k1 = 3.1 # index of space density revolution
+ # Calculation
+ for i, z in enumerate(self.zbin):
+ if z <= z1:
+ rho_mat[:, i] = (rho_l0 * (10**self.lumobin / lumo_star) **
+ (-alpha) * np.exp(-10**self.lumobin /
+ lumo_star) * (1 + z)**k1)
+ else:
+ rho_mat[:, i] = (rho_l0 * (10**self.lumobin / lumo_star) **
+ (-alpha) * np.exp(-10**self.lumobin /
+ lumo_star) * (1 + z1)**k1)
+
+ return rho_mat
+
+ def get_radius(self):
+ """
+ Generate the disc diameter of normal starforming galaxies.
+
+ Reference
+ ---------
+ [1] Wilman et al., Eq(7-9),
+ "A semi-empirical simulation of the extragalactic radio continuum
+ sky for next generation radio telescopes",
+ 2008, MNRAS, 388, 1335-1348.
+ http://adsabs.harvard.edu/abs/2008MNRAS.388.1335W
+ """
+ # Willman Eq. (8)
+ delta = np.random.normal(0, 0.3)
+ log_M_HI = 0.44 * np.log10(self.lumo) + 0.48 + delta
+ # Willman Eq. (7)
+ log_D_HI = ((log_M_HI - (6.52 + np.random.uniform(-0.06, 0.06))) /
+ 1.96 + np.random.uniform(-0.04, 0.04))
+ # Willman Eq. (9)
+ log_D = log_D_HI - 0.23 - np.log10(1 + self.z)
+ self.radius = 10**log_D / 2 * 1e-3 # [Mpc]
+ return self.radius
+
+ def gen_single_ps(self):
+ """
+ Generate single point source, and return its data as a list.
+ """
+ # Redshift and luminosity
+ self.z, self.lumo = self.get_lumo_redshift()
+ # angular diameter distance
+ self.param = PixelParams(self.z)
+ self.dA = self.param.dA
+ # Radius
+ self.radius = self.param.get_angle(self.get_radius()) # [rad]
+ # W/Hz/Sr to Jy
+ dA = self.dA * 3.0856775814671917E+22 # Mpc to meter
+ self.lumo = self.lumo / dA**2 / (10.0**-24) # [Jy]
+ # Position
+ x = np.random.uniform(0, 1)
+ self.lat = (np.arccos(2 * x - 1) / np.pi * 180 - 90) # [deg]
+ self.lon = np.random.uniform(0, np.pi * 2) / np.pi * 180 # [deg]
+ # Area
+ self.area = np.pi * self.radius**2 # [sr] ?
+
+ ps_list = [self.z, self.dA, self.lumo, self.lat, self.lon,
+ self.area, self.radius]
+
+ return ps_list
+
+ def draw_single_ps(self, freq):
+ """
+ Designed to draw the circular star forming and star bursting ps.
+
+ Prameters
+ ---------
+ nside: int and dyadic
+ number of sub pixel in a cell of the healpix structure
+ self.ps_catalog: pandas.core.frame.DataFrame
+ Data of the point sources
+ freq: float
+ frequency
+ """
+ # Init
+ npix = hp.nside2npix(self.nside)
+ hpmap = np.zeros((npix,))
+ # Gen Tb list
+ Tb_list = self.calc_Tb(freq)
+ # Iteratively draw the ps
+ num_ps = self.ps_catalog.shape[0]
+ resolution = self.resolution / 60 # [degree]
+ for i in range(num_ps):
+ # grid
+ ps_radius = self.ps_catalog['radius (rad)'][i] # [rad]
+ ps_radius = ps_radius * 180 / np.pi # radius [deg]
+ c_lat = self.ps_catalog['Lat (deg)'][i] # core_lat [deg]
+ c_lon = self.ps_catalog['Lon (deg)'][i] # core_lon [deg]
+ # Fill with circle
+ lon, lat, gridmap = grid.make_grid_ellipse(
+ (c_lon, c_lat), (2 * ps_radius, 2 * ps_radius), resolution)
+ indices, values = grid.map_grid_to_healpix(
+ (lon, lat, gridmap), self.nside)
+ hpmap[indices] += Tb_list[i]
+
+ return hpmap
+
+ def draw_ps(self, freq):
+ """
+ Read csv ps list file, and generate the healpix structure vector
+ with the respect frequency.
+ """
+ # Init
+ num_freq = len(freq)
+ npix = hp.nside2npix(self.nside)
+ hpmaps = np.zeros((npix, num_freq))
+
+ # Gen ps_catalog
+ self.gen_catalog()
+ # get hpmaps
+ for i in range(num_freq):
+ hpmaps[:, i] = self.draw_single_ps(freq[i])
+
+ return hpmaps
+
+ def calc_single_Tb(self, area, freq):
+ """
+ Calculate brightness temperatur of a single ps
+
+ Parameters
+ ------------
+ area: `~astropy.units.Quantity`
+ Area of the PS, e.g., `1.0*au.sr2`
+ freq: `~astropy.units.Quantity`
+ Frequency, e.g., `1.0*au.MHz`
+
+ Return
+ ------
+ Tb:`~astropy.units.Quantity`
+ Average brightness temperature, e.g., `1.0*au.K`
+ """
+ # Init
+ freq_ref = 1400 # [MHz]
+ freq = freq # [MHz]
+ # Luminosity at 1400MHz
+ lumo_1400 = self.lumo # [Jy]
+ # Calc flux
+ flux = (freq / freq_ref)**(-0.7) * lumo_1400
+ # Calc brightness temperature
+ Tb = convert.Fnu_to_Tb_fast(flux, area, freq)
+
+ return Tb
+
+ def calc_Tb(self, freq):
+ """
+ Calculate the surface brightness temperature of the point sources.
+
+ Parameters
+ ------------
+ area: `~astropy.units.Quantity`
+ Area of the PS, e.g., `1.0*au.sr`
+ freq: `~astropy.units.Quantity`
+ Frequency, e.g., `1.0*au.MHz`
+
+ Return
+ ------
+ Tb_list: list
+ Point sources brightness temperature
+ """
+ # Tb_list
+ num_ps = self.ps_catalog.shape[0]
+ Tb_list = np.zeros((num_ps,))
+ # Iteratively calculate Tb
+ for i in range(num_ps):
+ ps_area = self.ps_catalog['Area (sr)'][i] # [sr]
+ Tb_list[i] = self.calc_single_Tb(ps_area, freq)
+
+ return Tb_list