Simple user-defined models using a function

Typically, users have a particular model in mind for use in Sherpa. Here is a simple user-model example of creating a gaussian plus a constant.

I define a function 'mymodel' that accepts a Python list of parameter values and a Numpy ndarray of x values. It calculates and returns the sum of a gaussian and constant as a NumPy ndarray.

I define a 1D dataspace from [0.1, 10] with a bin size of 0.01 and load the user-model function identified as 'mdl'. Using the identifier, I populate the parameter names and initial values.

Setup the model, fake the data, and plot!

#!/usr/bin/env python
from sherpa.astro.ui import *
import numpy as np


def mymodel(pars, x, *args, **kwargs):
    """
    Evaluate a 1D Gaussian plus constant
    pars = { fwhm, pos, ampl, const } 
    """
    gfactor = 4.0*np.log(2.0)
    ratio = (x - pars[1])/pars[0]
    return pars[2] * np.exp(-gfactor * ratio * ratio) + pars[3]


# create simple grid [0.1, 10] with a bin size of 0.01
dataspace1d(0.1,10,0.01,dstype=Data1D)

# load the user-model mymodel() with parameter names into
# variable 'mdl'
load_user_model(mymodel,'mdl')
add_user_pars('mdl',['fwhm', 'pos', 'ampl', 'const'])

# initialize parameter values
mdl.pos = 5.0
mdl.fwhm = 2.5
mdl.ampl = 75
mdl.const = 0.1

# set the identifier as the associated model
set_model(mdl)

# evaluate, add poisson noise, and populate the
# dataspace
fake()

# plot faked data
plot_data()