diffsph.utils package¶
Submodules¶
diffsph.utils.consts module¶
diffsph.utils.dictionaries module¶
diffsph.utils.tools module¶
- diffsph.utils.tools.TB(brightness, theta, nu, *args, **kwargs)¶
Brightness temperature conversion
\[T_B = \frac{c^2}{2\,k\,\nu^2}I_\nu\]- Parameters:
brightness – generic brightness function in Jy/sr
theta – angular radius (as the first argument of the generic brighness function)
nu – frequency (as the second argument of the generic brighness function)
- Returns:
brightness temperature in mK
- diffsph.utils.tools.approxhalo_fd(n, theta, dist, rh)¶
Partial (\(\theta\)-dependent) flux-density halo/bulge factor (approximate formula):
\[\mathcal H_n(\theta) = \mathcal H_n(r_h,R) - 2\,\int_{R\sin(\theta)}^{r_h}dr\, r\, \kappa_1(r,R,\theta) \frac{\sin\left(\frac{n\pi r}{r_h}\right)}r\]where \(R\), \(rh\) and \(n\) are, respectively the distance, halo radius and Fourier index
- diffsph.utils.tools.approxhalo_fd_tot(n, dist, rh)¶
Total flux-density halo/bulge factor (approximate formula):
\[\mathcal H_n(r_h,R) \simeq 4\pi\int_0^{r_h}dr\, r^2 \frac{\sin\left(\frac{n\pi r}{r_h}\right)}r \ ,\]where \(R\), \(rh\) and \(n\) are, respectively the distance, halo radius and Fourier index
- diffsph.utils.tools.check_cache()¶
Function checks whether the /.diffsph_cache/ folder exists. If it does not exists, it creates it
- Returns:
folder directory name
- Return type:
str
- diffsph.utils.tools.delta_float(inp)¶
Float number for variable
'delta'- Parameters:
inp – variable
'delta'as str ('kol','kra', etc.) or float- Returns:
float number associated with
'inp'- Return type:
float
- diffsph.utils.tools.df(func, **kwargs)¶
- diffsph.utils.tools.evaluate(f, x, **kwargs)¶
Function converts string into a python function’s name and evaluates it
- Parameters:
f – function to be evaluated
x – first argument of \(f\)
- Returns:
\(f(x)\)
- diffsph.utils.tools.f(n, x)¶
Basis function in Fourier-expanded brightness formula
\[f_n(x)=2\int_x^1\frac{\sin(n\pi y) dy}{\sqrt{y^2-x^2}}\]- Returns:
\(f_n\) as a function of \(x\)
- diffsph.utils.tools.fwhm(brightness, thmax, *args, **kwargs)¶
Full width at half maximum
- Parameters:
brightness – generic brightness function
thmax – signal’s angular radius
- Returns:
Full width at half maximum in arcmin
- diffsph.utils.tools.g(n, x)¶
Basis function in Fourier-expanded flux density formula
\[g_n(x)=2\int_x^1\sqrt{y^2-x^2}\sin(n\pi y) dy\]- Returns:
\(g_n\) as a function of \(x\)
- diffsph.utils.tools.halo_fd(n, theta, dist, rh)¶
Partial (\(\theta\)-dependent) flux-density halo/bulge factor:
\[\mathcal H_n(\theta) = \mathcal H_n(r_h,R) - 2\,\int_{R\sin(\theta)}^{r_h}dr\, r\, \kappa_1(r,R,\theta) \frac{\sin\left(\frac{n\pi r}{r_h}\right)}r \ ,\]where \(R\), \(rh\) and \(n\) are, respectively the distance, halo radius and Fourier index
- diffsph.utils.tools.halo_fd_tot(n, dist, rh)¶
Total flux-density halo/bulge factor:
\[\mathcal H_n(r_h,R) = 2\,\int_0^{r_h}dr\, r\, \kappa_0(r,R) \frac{\sin\left(\frac{n\pi r}{r_h}\right)}r\ , \]where \(R\), \(rh\) and \(n\) are, respectively the distance, halo radius and Fourier index
- Returns:
Halo flux-density factor
- diffsph.utils.tools.hfd(fluxdens, thmax, *args, **kwargs)¶
Half-flux diameter
- Parameters:
brightness – generic brightness function
thmax – signal’s angular radius
- Returns:
Half-flux diameter in arcmin
- diffsph.utils.tools.hypothesis_index(hyp)¶
Index of the hypothesis (1 for decaying DM or generic scenario, 2 for WIMP self-annihilation).
- Parameters:
hyp (str) – hypothesis:
'wimp','decay'or'generic')- Returns:
hypothesis index
- Return type:
int
- diffsph.utils.tools.ker_0(r, dist)¶
- \[\kappa_0(r,R) = \frac1{R}\log\sqrt{\frac{R+r}{R-r}}\]
- diffsph.utils.tools.ker_1(r, theta, dist)¶
- \[\kappa_1(\theta,r,R) = \frac1{R}\log\frac{R\cos\theta+\sqrt{r^2-R^2\sin^2\theta}}{\sqrt{R^2-r^2}}\]
- diffsph.utils.tools.load_data(folder)¶
Function loads data from folder
- Returns:
data organized in form of a python dictionary
- Return type:
dict
- diffsph.utils.tools.sort_kwargs(**kwargs)¶
Function sorts keyword arguments alphabetically
- Returns:
sorted keywords with corresponding entries
- Return type:
dict
- diffsph.utils.tools.var_to_str(inp)¶
Dictionary for variables
'delta','hyp','galaxy','ref'and'rad_temp'- Parameters:
inp – input string or number
- Returns:
default variable name
- Return type:
str