* Documentation update.

master
Wirawan Purwanto 8 years ago
parent f436222852
commit bfc96d4335
  1. 34
      TESTS/test_stochastic_fitting.py

@ -26,7 +26,7 @@ def setup_MC_TZ():
def test_fit_PEC_MC_TZ(show_samples=True, save_fig=False):
def test_fit_PEC_MC_TZ(show_samples=True, save_fig=False, rng=None, num_iter=200):
"""20150528
PEC fitting, using `morse2` functional form.
@ -55,6 +55,33 @@ def test_fit_PEC_MC_TZ(show_samples=True, save_fig=False):
Final parameters : -2.187(10) 9.85(61) 1.8044(66) 1.864(83)
Total execution time = 0.55 secs
All testings passed.
Where the input variables are:
x = bond length (angstrom)
y, dy = binding energy (eV)
and the final (output) parameters are (in the same order as above):
Ebind = binding energy minimum (eV)
k = spring constant (eV/angstrom**2)
r0 = equilibrium bond length (angstrom)
a = morse2 nonlinear constant (angstrom**-1)
The guess params from NLF above are the same as what gnuplot fitting
routine gives, which are:
Final set of parameters Asymptotic Standard Error
======================= ==========================
E0 = -2.18626 +/- 0.03193 (1.46%)
k = 9.82591 +/- 1.59 (16.19%)
re = 1.80454 +/- 0.01763 (0.9771%)
a = 1.86206 +/- 0.2172 (11.66%)
Nonlinear-fitting.pl (perl script) gives the stochastic fit result:
-2.183(11) 9.97(65) 1.8046(69) 1.886(90)
Excellent agreement!
"""
from numpy import array
from wpylib.text_tools import matrix_str, str_indent
@ -70,7 +97,8 @@ def test_fit_PEC_MC_TZ(show_samples=True, save_fig=False):
# parameters etc
ansatz = morse2_fit_func()
rng = dict(seed=378711, rng_class=numpy.random.RandomState)
if rng is None:
rng = dict(seed=378711, rng_class=numpy.random.RandomState)
rawdata = Cr2_TZ_data_20140728uhf
sfit = MC_TZ_PEC_fit = StochasticFitting()
@ -90,7 +118,7 @@ def test_fit_PEC_MC_TZ(show_samples=True, save_fig=False):
with Timer() as tmr:
sfit.mcfit_loop_begin_()
sfit.mcfit_loop1_(num_iter=200, save_fig=save_fig)
sfit.mcfit_loop1_(num_iter=num_iter, save_fig=save_fig)
sfit.mcfit_loop_end_()
sfit.mcfit_analysis_()
sfit.mcfit_report_final_params()

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