Returns a normal pdf at grid x that can be used as an error distribution. Here, grid x is linearly spaced between -cutoff to +cutoff sigma of the loc.

err_pdf.py

import scipy.stats as st
import numpy as np

def err_pdf( loc, scale, size=15, cutoff=5):
    """
    PURPOSE
    --------
    Returns gaussian pdf at grid x that can be used as an error distribution.
    Here, grid x is linearly spaced between -cutoff to +cutoff sigma of the loc.
    
    INPUT
    ------
    loc    = scalar or a vector 
    scale  = scalar or a vector
    size   = 15 #refinement of the grid. For small cutoff use larze size and viceversa.
    cutoff = 3 #Grid is created between +-5*sigma (here, scale) on either side of loc

    OUTPUT
    -------
    Gaussian(x) at corresponding x
    """
      
    #Converting to an array, just in case
    loc   = np.array( loc, copy=False, ndmin=1)
    scale = np.array( scale, copy=False, ndmin=1)
    
    if cutoff<3:
        print 'Are you sure you just want to use <+-3sigma value on either side?'
    grid    = loc + scale*np.linspace(-cutoff, cutoff, size)[:,None].repeat(loc.shape[0],axis=1)
    err_pdf = st.norm.pdf( grid, loc=loc, scale=scale)
    return err_pdf, grid