forked from IPKM/nmreval
catch errors in fit preparation
This commit is contained in:
Dominik Demuth
parent
e2e52cebde
commit
a406908a69
@ -298,7 +298,8 @@ class ParameterSingleWidget(QtWidgets.QWidget):
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self._name = name
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self.label.setText(convert(name))
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self.label.setToolTip('If this is bold then this parameter is only for this data. otherwise the general parameter is used and displayed')
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self.label.setToolTip('If this is bold then this parameter is only for this data. '
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'Otherwise, the general parameter is used and displayed')
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self.value_line.setValidator(QtGui.QDoubleValidator())
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self.value_line.textChanged.connect(lambda: self.valueChanged.emit(self.value) if self.value is not None else 0)
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@ -916,10 +916,12 @@ class NMRMainWindow(QtWidgets.QMainWindow, Ui_BaseWindow):
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self.action_odr_fit: 'odr'
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}[self.ac_group.checkedAction()]
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self.fit_dialog.fit_button.setEnabled(False)
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self.management.start_fit(parameter, links, fit_options)
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self.status.setText('Fit running...'.format(self.management.fitter.step))
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self.fit_timer.start(500)
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fit_is_ready = self.management.prepare_fit(parameter, links, fit_options)
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if fit_is_ready:
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self.management.start_fit()
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self.fit_dialog.fit_button.setEnabled(False)
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self.status.setText('Fit running...'.format(self.management.fitter.step))
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self.fit_timer.start(500)
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@QtCore.pyqtSlot(dict, int, bool)
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def show_fit_preview(self, funcs: dict, num: int, show: bool):
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@ -424,9 +424,9 @@ class UpperManagement(QtCore.QObject):
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for d in self.data.values():
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d.mask = np.ones_like(d.mask, dtype=bool)
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def start_fit(self, parameter: dict, links: list, fit_options: dict):
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def prepare_fit(self, parameter: dict, links: list, fit_options: dict) -> bool:
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if self._fit_active:
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return
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return False
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self.__fit_options = (parameter, links, fit_options)
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@ -436,67 +436,80 @@ class UpperManagement(QtCore.QObject):
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fit_mode = fit_options['fit_mode']
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we_option = fit_options['we']
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for model_id, model_p in parameter.items():
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m = Model(model_p['func'])
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models[model_id] = m
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self.fitter.fitmethod = fit_mode
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m_complex = model_p['complex']
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# all-encompassing error catch
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try:
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for model_id, model_p in parameter.items():
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m = Model(model_p['func'])
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models[model_id] = m
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# sets are not in active order but in order they first appeared in fit dialog
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# iterate over order of set id in active order and access parameter inside loop
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# instead of directly looping
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list_ids = list(model_p['parameter'].keys())
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set_order = [self.active_id.index(i) for i in list_ids]
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for pos in set_order:
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set_id = list_ids[pos]
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m_complex = model_p['complex']
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data_i = self.data[set_id]
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set_params = model_p['parameter'][set_id]
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# sets are not in active order but in order they first appeared in fit dialog
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# iterate over order of set id in active order and access parameter inside loop
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# instead of directly looping
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list_ids = list(model_p['parameter'].keys())
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set_order = [self.active_id.index(i) for i in list_ids]
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for pos in set_order:
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set_id = list_ids[pos]
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if we_option.lower() == 'deltay':
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we = data_i.y_err**2
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else:
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we = we_option
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data_i = self.data[set_id]
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set_params = model_p['parameter'][set_id]
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if m_complex is None or m_complex == 1:
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_y = data_i.y.real
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elif m_complex == 2 and np.iscomplexobj(data_i.y):
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_y = data_i.y.imag
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else:
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_y = data_i.y
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if we_option.lower() == 'deltay':
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we = data_i.y_err**2
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else:
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we = we_option
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_x = data_i.x
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if m_complex is None or m_complex == 1:
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_y = data_i.y.real
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elif m_complex == 2 and np.iscomplexobj(data_i.y):
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_y = data_i.y.imag
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else:
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_y = data_i.y
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if fit_limits == 'none':
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inside = slice(None)
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elif fit_limits == 'x':
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x_lim, _ = self.graphs[self.current_graph].ranges
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inside = np.where((_x >= x_lim[0]) & (_x <= x_lim[1]))
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else:
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inside = np.where((_x >= fit_limits[0]) & (_x <= fit_limits[1]))
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_x = data_i.x
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if isinstance(we, str):
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d = fit_d.Data(_x[inside], _y[inside], we=we, idx=set_id)
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else:
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d = fit_d.Data(_x[inside], _y[inside], we=we[inside], idx=set_id)
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if fit_limits == 'none':
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inside = slice(None)
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elif fit_limits == 'x':
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x_lim, _ = self.graphs[self.current_graph].ranges
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inside = np.where((_x >= x_lim[0]) & (_x <= x_lim[1]))
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else:
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inside = np.where((_x >= fit_limits[0]) & (_x <= fit_limits[1]))
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d.set_model(m)
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d.set_parameter(set_params[0], var=model_p['var'],
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lb=model_p['lb'], ub=model_p['ub'],
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fun_kwargs=set_params[1])
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if isinstance(we, str):
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d = fit_d.Data(_x[inside], _y[inside], we=we, idx=set_id)
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else:
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d = fit_d.Data(_x[inside], _y[inside], we=we[inside], idx=set_id)
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self.fitter.add_data(d)
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d.set_model(m)
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d.set_parameter(set_params[0], var=model_p['var'],
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lb=model_p['lb'], ub=model_p['ub'],
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fun_kwargs=set_params[1])
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model_globs = model_p['glob']
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if model_globs:
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m.set_global_parameter(**model_p['glob'])
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self.fitter.add_data(d)
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for links_i in links:
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self.fitter.set_link_parameter((models[links_i[0]], links_i[1]),
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(models[links_i[2]], links_i[3]))
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model_globs = model_p['glob']
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if model_globs:
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m.set_global_parameter(**model_p['glob'])
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for links_i in links:
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self.fitter.set_link_parameter((models[links_i[0]], links_i[1]),
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(models[links_i[2]], links_i[3]))
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return True
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except Exception as e:
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logger.error('Fit preparation failed', *e.args)
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QtWidgets.QMessageBox.warning(QtWidgets.QWidget(),
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'Fit prep failed',
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f'Fit preparation failed with message\n{e.args}')
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return False
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def start_fit(self):
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with busy_cursor():
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self.fit_worker = FitWorker(self.fitter, fit_mode)
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self.fit_worker = FitWorker(self.fitter)
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self.fit_thread = QtCore.QThread()
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self.fit_worker.moveToThread(self.fit_thread)
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@ -532,7 +545,8 @@ class UpperManagement(QtCore.QObject):
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for set_id, set_parameter in parameter.items():
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new_values = [v.value for v in res[set_id].parameter.values()]
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parameter[set_id] = (new_values, set_parameter[1])
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self.start_fit(*self.__fit_options)
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if self.prepare_fit(*self.__fit_options):
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self.start_fit()
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def make_fits(self, res: dict, opts: list, param_graph: str, show_fit: bool, parts: bool, extrapolate: list) -> None:
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"""
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@ -1270,16 +1284,15 @@ class UpperManagement(QtCore.QObject):
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class FitWorker(QtCore.QObject):
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finished = QtCore.pyqtSignal(list, bool)
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def __init__(self, fitter, mode):
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def __init__(self, fitter):
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super().__init__()
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self.fitter = fitter
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self.mode = mode
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@QtCore.pyqtSlot()
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def run(self):
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try:
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res = self.fitter.run(mode=self.mode)
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res = self.fitter.run()
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success = True
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except Exception as e:
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res = [e]
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@ -23,7 +23,7 @@ class FitAbortException(Exception):
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class FitRoutine(object):
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def __init__(self, mode='lsq'):
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self._fitmethod = mode
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self.fitmethod = mode
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self.data = []
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self.fit_model = None
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self._no_own_model = []
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@ -169,10 +169,13 @@ class FitRoutine(object):
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logger.info('Fit aborted by user')
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self._abort = True
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def run(self, mode='lsq'):
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def run(self, mode: str=None):
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self._abort = False
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self.parameter = Parameters()
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if mode is None:
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mode = self.fitmethod
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fit_groups, linked_parameter = self.prepare_links()
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for data_groups in fit_groups:
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