diff options
Diffstat (limited to 'silx/math/fit/fitmanager.py')
| -rw-r--r-- | silx/math/fit/fitmanager.py | 36 |
1 files changed, 26 insertions, 10 deletions
diff --git a/silx/math/fit/fitmanager.py b/silx/math/fit/fitmanager.py index f62dedb..2dc63a1 100644 --- a/silx/math/fit/fitmanager.py +++ b/silx/math/fit/fitmanager.py @@ -1,7 +1,7 @@ # coding: utf-8 # /*######################################################################### # -# Copyright (c) 2004-2018 European Synchrotron Radiation Facility +# Copyright (c) 2004-2020 European Synchrotron Radiation Facility # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal @@ -411,8 +411,9 @@ class FitManager(object): 6: 'SUM', 7: 'IGNORE'} - xwork = self.xdata - ywork = self.ydata + # Filter-out not finite data + xwork = self.xdata[self._finite_mask] + ywork = self.ydata[self._finite_mask] # estimate the background bg_params, bg_constraints = self.estimate_bkg(xwork, ywork) @@ -516,8 +517,8 @@ class FitManager(object): from a list of parameter dictionaries, if field ``code`` is not set to ``"IGNORE"``. """ - if x is None: - x = self.xdata + x = self.xdata if x is None else numpy.array(x, copy=False) + if paramlist is None: paramlist = self.fit_results active_params = [] @@ -528,8 +529,18 @@ class FitManager(object): else: active_params.append(param['estimation']) - newdata = self.fitfunction(numpy.array(x), *active_params) - return newdata + # Mask x with not finite (support nD x) + finite_mask = numpy.all(numpy.isfinite(x), axis=tuple(range(1, x.ndim))) + + if numpy.all(finite_mask): # All values are finite: fast path + return self.fitfunction(numpy.array(x, copy=True), *active_params) + + else: # Only run fitfunction on finite data and complete result with NaNs + # Create result with same number as elements as x, filling holes with NaNs + result = numpy.full((x.shape[0],), numpy.nan, dtype=numpy.float64) + result[finite_mask] = self.fitfunction( + numpy.array(x[finite_mask], copy=True), *active_params) + return result def get_estimation(self): """Return the list of fit parameter names.""" @@ -750,6 +761,10 @@ class FitManager(object): self.ydata = self.ydata[bool_array] self.sigmay = self.sigmay[bool_array] if sigmay is not None else None + self._finite_mask = numpy.logical_and( + numpy.all(numpy.isfinite(self.xdata), axis=tuple(range(1, self.xdata.ndim))), + numpy.isfinite(self.ydata)) + def enableweight(self): """This method can be called to set :attr:`sigmay`. If :attr:`sigmay0` was filled with actual uncertainties in :meth:`setdata`, use these values. @@ -822,13 +837,14 @@ class FitManager(object): param_val.append(param['estimation']) param_constraints.append([param['code'], param['cons1'], param['cons2']]) - ywork = self.ydata - + # Filter-out not finite data + ywork = self.ydata[self._finite_mask] + xwork = self.xdata[self._finite_mask] try: params, covariance_matrix, infodict = leastsq( self.fitfunction, # bg + actual model function - self.xdata, ywork, param_val, + xwork, ywork, param_val, sigma=self.sigmay, constraints=param_constraints, model_deriv=self.theories[self.selectedtheory].derivative, |