def mass_gradient(r, rho, autoDebug=True):
if autoDebug:
sam.type_check(r, sam.TYPES_numbers, 'r')
sam.type_check(rho, sam.TYPES_numbers, 'rho')
dMdr = 4 * np.pi * r**2 * rho
return dMdr
def blackbody_fit(wavelengths,
emissivity,
tempRange=(100, 6500),
step=5,
rtype="dict",
autoDebug=False):
#Error Checking
if autoDebug == True:
sam.type_check(wavelengths, np.ndarray, 'wavelengths')
sam.type_check(emissivity, np.ndarray, 'emissivity')
sam.value_check(emissivity.shape, (wavelengths.shape, ), 'discrete',
'emissivity')
sam.type_check(tempRange, (tuple, list, np.ndarray), 'tempRange')
sam.value_check(len(tempRange), (1), 'f', "tempRange")
sam.type_check(step, (float, int), 'step')
if len(tempRange) <= 2:
sam.value_check(step, (tempRange[-1] - tempRange[0]) / 2, 'g',
"tempRange")
sam.type_check(rtype, str, 'rtype')
sam.value_check(
rtype, [0, "tuple", "t", "list", 1, "dict", "dictionary", "d"],
"d", "rtype")
try:
#Checking for normalization
if np.max(emissivity) > 1.0:
emissivity = emissivity / np.max(emissivity)
if len(tempRange) == 2:
tempRange = range(tempRange[0], tempRange[1], step)
RMS = np.zeros(len(tempRange))
for index, temp in enumerate(tempRange):
bb = sam.astro.blackbody(T=temp,
ranges=wavelengths,
normalize=True)
rms = sam.sig_proc.rms2(bb, emissivity)
RMS[index] = rms
bestFitTemp = tempRange[np.argmin(RMS)]
bestBlackbody = sam.astro.blackbody(T=bestFitTemp, ranges=wavelengths)
if rtype in [0, "tuple", "t", "list"]:
return wavelengths, emissivity, bestBlackbody, np.asarray(
RMS), bestFitTemp
if rtype in [1, "dict", "dictionary", "d"]:
return {
"wavelengths": wavelengths,
"emissivity": emissivity,
"bestBlackbody": bestBlackbody,
"rms": np.asarray(RMS),
"bestFitTemp": bestFitTemp
}
except Exception as e:
sam.debug(e)
def gas_pressure2(T, P, autoDebug=True):
"""
calculcates gas pressure by subtracting radiation pressure from
total pressure in star
"""
if autoDebug:
sam.type_check(T, sam.TYPES_numbers, 'T')
sam.type_check(P, sam.TYPES_numbers, 'P')
Pg = P - (sam.CONSTANT_third * sam.CONSTANT_a * T**4)
return Pg
def luminosity(r,T,autoDebug=True): """ calculates the luminosity based off of the Stefan-Boltzmann law :inputs: r [np.ndarray,int,float] -- radius or radii of star T [np.ndarray,int,float] -- effective temperature or effective temperatures :returns: L [np.ndarray,float] -- effective luminosity or luminosities """ #-----------BEGIN ERROR CHECKING---------- if autoDebug: sam.type_check(r, sam.TYPES_math, "r") sam.type_check(T, sam.TYPES_math, "T") sam.value_check(r,.0,">","r") sam.value_check(T,.0,">","T") #-----------END ERROR CHECKING---------- L = 4 * sam.CONSTANT_pi * r**2 * sam.CONSTANT_SB* T**4 return L
def luminosity_gradient(r, rho, epsilon, autoDebug=True):
if autoDebug:
sam.type_check(r, sam.TYPES_numbers, 'r')
sam.type_check(rho, sam.TYPES_numbers, 'rho')
sam.type_check(epsilon, sam.TYPES_numbers, 'epsilon')
dLdr = sam.CONSTANT_4pi * r**2 * rho * epsilon
return dLdr
def pressure_gradient(r, rho, Mr, autoDebug=True):
if autoDebug:
sam.type_check(r, sam.TYPES_numbers, 'r')
sam.type_check(rho, sam.TYPES_numbers, 'rho')
sam.type_check(Mr, sam.TYPES_numbers, 'Mr')
dPdr = (-sam.CONSTANT_G * Mr * rho) / (r**2)
return dPdr
def rho(T, P, mu, autoDebug=True):
if autoDebug:
sam.type_check(T, sam.TYPES_numbers, 'T')
sam.type_check(P, sam.TYPES_numbers, 'P')
sam.type_check(mu, sam.TYPES_numbers, 'mu')
Pg = gas_pressure2(T, P)
rho = (Pg * mu * sam.CONSTANT_mh) / (sam.CONSTANT_k * T)
return rho
def temperature_gradient_adiabatic(r, gamma, mu, Mr, autoDebug=True):
if autoDebug:
sam.type_check(r, sam.TYPES_numbers, 'gamma')
sam.type_check(mu, sam.TYPES_numbers, 'mu')
sam.type_check(Mr, sam.TYPES_numbers, 'Mr')
mh = sam.CONSTANT_mh
k = sam.CONSTANT_k
G = sam.CONSTANT_G
adiabaticGrad = -1 * (1 - 1 / gamma) * (mu * mh) / k * (G * Mr) / (r**2)
return adiabaticGrad