except ValueError, e:
print "Skipping text values (%s)"%','.join(r)
# fit type
if options.func_name == "lognorm":
func = lognormal_function.func()
elif options.func_name == "gauss":
func = gauss_function.func()
elif options.func_name == "exp":
func = exp_function.func()
elif options.func_name == "gamma":
func = gamma_function.func()
elif options.func_name == "lin":
func = lin_function.func()
else:
func = doubleexp_function.func()
fr = function_fit(d, func, p0)
# fit results
print fr.fit()
# blank line
print
wrt = csv.writer(sys.stdout)
# output is outer join of function and fit
d_dict = dict(d)
f_dict = dict(fr.eval(start=tstart, end=tend, points=points))
for time in sorted(list(set(d_dict.keys() + f_dict.keys()))):
res = lead_cols.get(time, padding) + [time, d_dict.get(time, NA), time, f_dict.get(time, NA)]
if options.label:
return self.f def eval(self, start=None, end=None, points=None): if start is None or end is None or points is None: t = self.x else: t = list(numpy.linspace(start,end,points)) return [p for p in self.f.evalPoints(t)] ######################### if __name__ == '__main__': import doubleexp_function # simple demos pf = doubleexp_function.func(_A=30250, _alpha=690, _beta=30.5) pf.printPoints(0, .1) print pf p0 = [22000, 600, 10, .005] v = [ (0.0, 0.0), (0.0010101010101, 14722.0870054), (0.0020202020202, 21385.9328302), (0.0030303030303, 24171.3509832), (0.0040404040404, 25096.7012502), (0.0050505050505, 25136.414614), (0.0070707070707, 24196.4109866), (0.0090909090909, 22881.6344439), (0.0111111111111, 21544.8974262), (0.0121212121212, 20896.1721771), (0.0161616161616, 18477.4771294),
