File Content: _tstutils.py ''' Parameters used in test and benchmark methods ''' from __future__ import division, print_function, absolute_import from random import random from scipy.optimize import zeros as cc def f1(x): return x*(x-1.) def f2(x): return x**2 - 1 def f3(x): return x*(x-1.)*(x-2.)*(x-3.) def f4(x): if x > 1: return 1.0 + .1*x if x < 1: return -1.0 + .1*x return 0 def f5(x): if x != 1: return 1.0/(1. - x) return 0 def f6(x): if x > 1: return random() elif x < 1: return -random() else: return 0 description = """ f2 is a symmetric parabola, x**2 - 1 f3 is a quartic polynomial with large hump in interval f4 is step function with a discontinuity at 1 f5 is a hyperbola with vertical asymptote at 1 f6 has random values positive to left of 1, negative to right of course these are not real problems. They just test how the 'good' solvers behave in bad circumstances where bisection is really the best. A good solver should not be much worse than bisection in such circumstance, while being faster for smooth monotone sorts of functions. """ methods = [cc.bisect,cc.ridder,cc.brenth,cc.brentq] mstrings = ['cc.bisect','cc.ridder','cc.brenth','cc.brentq'] functions = [f2,f3,f4,f5,f6] fstrings = ['f2','f3','f4','f5','f6'] Submit