Source code for species.util.read_util

"""
Utility functions for reading data.
"""

import math

import numpy as np

from scipy.integrate import simps

from species.core import constants
from species.read import read_model, read_planck


[docs]def get_mass(model_param): """ Parameters ---------- model_param : dict Model parameter values. Should contain the surface gravity and radius. Returns ------- float Mass (Mjup). """ logg = 1e-2 * 10.**model_param['logg'] # [m s-1] radius = model_param['radius'] # [Rjup] radius *= constants.R_JUP # [m] mass = logg*radius**2/constants.GRAVITY # [kg] mass /= constants.M_JUP # [Mjup] return mass
[docs]def add_luminosity(modelbox): """ Function to add the luminosity of a model spectrum to the parameter dictionary of the box. The luminosity is by default calculated at a spectral resolution of 1000. Parameters ---------- modelbox : species.core.box.ModelBox Box with the model spectrum. Should also contain the dictionary with the model parameters, the radius in particular. Returns ------- species.core.box.ModelBox The input box with the luminosity added in the parameter dictionary. """ if modelbox.model == 'planck': readmodel = read_planck.ReadPlanck(wavel_range=(1e-1, 1e3)) fullspec = readmodel.get_spectrum(model_param=modelbox.parameters, spec_res=1000.) else: readmodel = read_model.ReadModel(model=modelbox.model) fullspec = readmodel.get_model(model_param=modelbox.parameters) flux = simps(fullspec.flux, fullspec.wavelength) if 'distance' in modelbox.parameters: luminosity = 4.*math.pi*(fullspec.parameters['distance']*constants.PARSEC)**2*flux # [W] else: luminosity = 4.*math.pi*(fullspec.parameters['radius']*constants.R_JUP)**2*flux # [W] modelbox.parameters['luminosity'] = luminosity/constants.L_SUN # [Lsun] return modelbox
[docs]def smooth_spectrum(wavelength, flux, spec_res, size=11): """ Function to convolve a spectrum with a Gaussian kernel to a fixed spectral resolution. The kernel size is set to 5 times the FWHM of the Gaussian. The FWHM of the Gaussian is equal to the the wavelength divided by the spectral resolution. If the kernel does not fit within the available wavelength grid (i.e., at the edge of the array) then the flux values are set to NaN. Parameters ---------- wavelength : numpy.ndarray Wavelength points (micron). Should be equally-spaced. flux : numpy.ndarray Flux density (W m-2 micron-1). spec_res : float Spectral resolution size : int Kernel size (odd number). Returns ------- numpy.ndarray Smoothed spectrum (W m-2 micron-1) at the same wavelength points as the input spectrum. """ def _gaussian(size, sigma): pos = range(-(size-1)//2, (size-1)//2+1) kernel = [math.exp(-float(x)**2/(2.*sigma**2))/(sigma*math.sqrt(2.*math.pi)) for x in pos] return np.asarray(kernel/sum(kernel)) if size % 2 == 0: raise ValueError('The kernel size should be an odd number.') spacing = np.mean(np.diff(wavelength)) # [micron] flux_smooth = np.zeros(flux.shape) # [W m-2 micron-1] for i, item in enumerate(wavelength): fwhm = item/spec_res # [micron] sigma = fwhm/(2.*math.sqrt(2.*math.log(2.))) # [micron] size = int(5.*sigma/spacing) # Kernel size 5 times the FWHM if size % 2 == 0: size += 1 gaussian = _gaussian(size, sigma/spacing) try: flux_smooth[i] = np.sum(gaussian * flux[i-(size-1)//2:i+(size-1)//2+1]) except ValueError: flux_smooth[i] = np.nan return flux_smooth