"""
==========
Model Grid
==========
Fit a line based on parameters output from a grid of models
Module API
^^^^^^^^^^
"""
import numpy as np
from pyspeckit.mpfit import mpfit
import matplotlib.cbook as mpcb
import copy
try:
import scipy.interpolate
import scipy.ndimage
scipyOK = True
except ImportError:
scipyOK=False
[docs]def gaussian_line(xax, maxamp, tau, offset, width):
"""
A Gaussian line function in which the
"""
return np.exp(-(xax-offset)**2/(2.0*width**2)) * maxamp * (1.0-np.exp(-1*tau))
[docs]def line_params_2D(gridval1, gridval2, griddim1, griddim2, valuegrid):
"""
Given a 2D grid of modeled line values - the amplitude, e.g. excitation temperature,
and the optical depth, tau - return the model spectrum
griddims contains the names of the axes and their values... it should have the same
number of entries as gridpars
"""
if not scipyOK:
raise ImportError("Scipy could not be imported, therefore interpolation is not available.")
#matchpt1 = np.argmin( np.abs( gridval1 - griddim1[0,:] ))
#matchpt2 = np.argmin( np.abs( gridval2 - griddim2[:,0] ))
return scipy.ndimage.map_coordinates(valuegrid,np.array([[gridval2],[gridval1]]),order=1)
interpgrid = scipy.interpolate.interp2d(
griddim1[ gridval1-5:gridval1+5, gridval2-5:gridval2+5].ravel(),
griddim2[ gridval1-5:gridval1+5, gridval2-5:gridval2+5].ravel(),
valuegrid[gridval1-5:gridval1+5, gridval2-5:gridval2+5].ravel())
return interpgrid(gridval1,gridval2)
[docs]def line_model_2par(xax, center, width, gridval1, gridval2, griddim1, griddim2, maxampgrid, taugrid,
linefunction=gaussian_line):
"""
Returns the spectral line that matches the given x-axis
xax, center, width must be in the same units!
"""
maxamp = line_params_2D(gridval1, gridval2, griddim1, griddim2, maxampgrid)
tau = line_params_2D(gridval1, gridval2, griddim1, griddim2, taugrid)
return linefunction(xax,maxamp,tau,offset,width)
