Changeset 57eb6a4 in sasmodels
 Timestamp:
 Oct 17, 2017 4:29:59 PM (4 years ago)
 Branches:
 master, core_shell_microgels, magnetic_model, ticket1257vesicleproduct, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
 Children:
 2a602c7
 Parents:
 0d19f42
 File:

 1 edited
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explore/precision.py
r487e695 r57eb6a4 1 1 #!/usr/bin/env python 2 2 r""" 3 Show numerical precision of $2 J_1(x)/x$. 3 Show numerical precision of various expressions. 4 5 Evaluates the same function(s) in single and double precision and compares 6 the results to 500 digit mpmath evaluation of the same function. 7 8 Note: a quick way to generation C and python code for taylor series 9 expansions from sympy: 10 11 import sympy as sp 12 x = sp.var("x") 13 f = sp.sin(x)/x 14 t = sp.series(f, n=12).removeO() # taylor series with no O(x^n) term 15 p = sp.horner(t) # Horner representation 16 p = p.replace(x**2, sp.var("xsq") # simplify if alternate terms are zero 17 p = p.n(15) # evaluate coefficients to 15 digits (optional) 18 c_code = sp.ccode(p, assign_to=sp.var("p")) # convert to c code 19 py_code = c[:1] # strip semicolon to convert c to python 20 21 # mpmath has pade() rational function approximation, which might work 22 # better than the taylor series for some functions: 23 P, Q = mp.pade(sp.Poly(t.n(15),x).coeffs(), L, M) 24 P = sum(a*x**n for n,a in enumerate(reversed(P))) 25 Q = sum(a*x**n for n,a in enumerate(reversed(Q))) 26 c_code = sp.ccode(sp.horner(P)/sp.horner(Q), assign_to=sp.var("p")) 27 28 # There are richardson and shanks series accelerators in both sympy 29 # and mpmath that may be helpful. 4 30 """ 5 31 from __future__ import division, print_function
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