def get_inputs(args):
data = args[0]
d_max = float(args[1])
if (len(args) > 2):
rg = float(args[2])
else:
rg = 0
prior = None
data = saxs_read_write.read_standard_ascii_qis(data)
if (rg == 0):
msga = guinier_analyses.multi_step_rg_engine(data)
rg = msga.median_rg
m = 1.0 / data.i[0]
data.multiply_add(m, 0.0)
n_params = 10
n_fst_pass = 4
# fitter = fixed_dmax_fitter(prior, data, d_max, n_params, n_fst_pass, n_trial=4, n_simplex=10)
# fitter.best_fit.show_pr( open("best.pr",'w') )
# fitter.best_fit.show_obs_vs_calc( open("best.qii",'w') )
delta = rg
step = 2
d_max_scan = dmax_scan(prior,
data,
d_max,
delta,
step,
rg,
n_params,
n_fst_pass,
n_trial=1,
n_simplex=10)
d_max_scan.get_best_dmax()
def get_rg(data, out=None):
global stdfile
out = stdfile
msga = guinier_analyses.multi_step_rg_engine(data, out)
return msga.median_rg, msga.median_io
def get_rg(self, data, out=None):
out = self.file
msga = guinier_analyses.multi_step_rg_engine(data, out)
return msga.median_rg, msga.median_io
def get_rg(data, out=None):
msga = guinier_analyses.multi_step_rg_engine(data, out)
return msga.median_rg