Source code for sas.qtgui.Perspectives.Fitting.OptionsWidget

"""
Widget/logic for smearing data.
"""
import numpy as np
from PyQt5 import QtCore
from PyQt5 import QtGui
from PyQt5 import QtWidgets

from sas.qtgui.Plotting.PlotterData import Data2D
import sas.qtgui.Utilities.GuiUtils as GuiUtils

# Local UI
from sas.qtgui.Perspectives.Fitting.UI.OptionsWidgetUI import Ui_tabOptions

[docs]class DataWidgetMapper(QtWidgets.QDataWidgetMapper): """ Custom version of the standard QDataWidgetMapper allowing for proper response to index change in comboboxes """
[docs] def addMapping(self, widget, section, propertyName=None): if propertyName is None: super(DataWidgetMapper, self).addMapping(widget, section) else: super(DataWidgetMapper, self).addMapping(widget, section, propertyName) if isinstance(widget, QtWidgets.QComboBox): delegate = self.itemDelegate() widget.currentIndexChanged.connect(lambda: delegate.commitData.emit(widget)) elif isinstance(widget, QtWidgets.QCheckBox): delegate = self.itemDelegate() widget.stateChanged.connect(lambda: delegate.commitData.emit(widget))
[docs]class OptionsWidget(QtWidgets.QWidget, Ui_tabOptions): plot_signal = QtCore.pyqtSignal() QMIN_DEFAULT = 0.0005 QMAX_DEFAULT = 0.5 NPTS_DEFAULT = 50 MODEL = [ 'MIN_RANGE', 'MAX_RANGE', 'NPTS', 'NPTS_FIT', 'LOG_SPACED'] def __init__(self, parent=None, logic=None): super(OptionsWidget, self).__init__() self.setupUi(self) # Logic component self.logic = logic self.parent = parent # Weight radio box group self.weightingGroup = QtWidgets.QButtonGroup() self.weighting = 0 # Group boxes self.boxWeighting.setEnabled(False) self.cmdMaskEdit.setEnabled(False) # Button groups self.weightingGroup.addButton(self.rbWeighting1) self.weightingGroup.addButton(self.rbWeighting2) self.weightingGroup.addButton(self.rbWeighting3) self.weightingGroup.addButton(self.rbWeighting4) # Let only floats in the range edits self.txtMinRange.setValidator(GuiUtils.DoubleValidator()) self.txtMaxRange.setValidator(GuiUtils.DoubleValidator()) # Let only ints in the number of points edit self.txtNpts.setValidator(QtGui.QIntValidator()) # disable npts/fit - this is a read only control self.txtNptsFit.setEnabled(False) # Attach slots self.cmdReset.clicked.connect(self.onRangeReset) self.cmdMaskEdit.clicked.connect(self.onMaskEdit) self.chkLogData.stateChanged.connect(self.toggleLogData) # Button groups self.weightingGroup.buttonClicked.connect(self.onWeightingChoice) self.qmin = self.QMIN_DEFAULT self.qmax = self.QMAX_DEFAULT self.npts = self.NPTS_DEFAULT self.npts_fit = self.NPTS_DEFAULT if self.logic.data_is_loaded: self.qmin, self.qmax, self.npts = self.logic.computeDataRange() self.npts_fit = self.npts2fit(data=self.logic.data) self.initModel() self.initMapper() self.model.blockSignals(True) self.updateQRange(self.qmin, self.qmax, self.npts) self.txtMaxRange.setText(str(self.qmax)) self.txtMinRange.setText(str(self.qmin)) self.txtNpts.setText(str(self.npts)) self.txtNptsFit.setText(str(self.npts_fit)) self.model.blockSignals(False) new_font = 'font-family: -apple-system, "Helvetica Neue", "Ubuntu";' self.label_13.setStyleSheet(new_font) self.label_15.setStyleSheet(new_font)
[docs] def initModel(self): """ Initialize the state """ self.model = QtGui.QStandardItemModel() for model_item in range(len(self.MODEL)): self.model.setItem(model_item, QtGui.QStandardItem()) # Attach slot self.model.dataChanged.connect(self.onModelChange)
[docs] def initMapper(self): """ Initialize model item <-> UI element mapping """ self.mapper = DataWidgetMapper(self) self.mapper.setModel(self.model) self.mapper.setOrientation(QtCore.Qt.Vertical) self.mapper.addMapping(self.txtMinRange, self.MODEL.index('MIN_RANGE')) self.mapper.addMapping(self.txtMaxRange, self.MODEL.index('MAX_RANGE')) self.mapper.addMapping(self.txtNpts, self.MODEL.index('NPTS')) self.mapper.addMapping(self.txtNptsFit, self.MODEL.index('NPTS_FIT')) self.mapper.addMapping(self.chkLogData, self.MODEL.index('LOG_SPACED')) self.mapper.toFirst()
[docs] def toggleLogData(self, isChecked): """ Toggles between log and linear data sets """ pass
[docs] def onMaskEdit(self): """ Callback for running the mask editor """ if isinstance(self.logic.data, Data2D): self.parent.communicate.maskEditorSignal.emit(self.logic.data)
[docs] def onRangeReset(self): """ Callback for resetting qmin/qmax """ self.updateQRange(self.qmin, self.qmax, self.npts)
[docs] def onWeightingChoice(self, button): """ Update weighting in the fit state """ button_id = button.group().checkedId() self.weighting = abs(button_id + 2) self.plot_signal.emit()
[docs] def onModelChange(self, top, bottom): """ Respond to model change by updating the plot """ # "bottom" is unused # update if there's something to update item_text = self.model.item(top.row()).text() if not item_text: return # Update the npts/fit value if top.row() in [0, 1, 2]: qmin, qmax, npts, _, _ = self.state() # if this is a Q value, update NPt/fit value = float(item_text) if top.row() == 0: qmin = value if qmin >= qmax: qmin = self.qmin self.model.item(self.MODEL.index('MIN_RANGE')).setText(str(self.qmin)) self.npts_fit = self.npts2fit(data=self.logic.data, qmin=qmin, qmax=qmax, npts=npts) elif top.row() == 1: qmax = value if qmax <= qmin: qmax = self.qmax self.model.item(self.MODEL.index('MAX_RANGE')).setText(str(self.qmax)) self.npts_fit = self.npts2fit(data=self.logic.data, qmin=qmin, qmax=qmax, npts=npts) else: # This is only possible for theories. Just post the number to the field, if valid npts = int(value) if npts <= 0: npts = self.npts self.npts_fit = npts self.model.item(self.MODEL.index('NPTS')).setText(str(npts)) self.model.item(self.MODEL.index('NPTS_FIT')).setText(str(self.npts_fit)) # update the plot(s) self.plot_signal.emit()
[docs] def setEnablementOnDataLoad(self): """ Enable/disable various UI elements based on data loaded """ is2Ddata = isinstance(self.logic.data, Data2D) self.boxWeighting.setEnabled(True) self.cmdMaskEdit.setEnabled(is2Ddata) # Switch off txtNpts related controls self.txtNpts.setEnabled(False) self.chkLogData.setEnabled(False) # Weighting controls if self.logic.di_flag: self.rbWeighting2.setEnabled(True) self.rbWeighting2.setChecked(True) self.onWeightingChoice(self.rbWeighting2) else: self.rbWeighting2.setEnabled(False) self.rbWeighting1.setChecked(True) self.onWeightingChoice(self.rbWeighting1)
[docs] def updateQRange(self, q_range_min, q_range_max, npts): """ Update the local model based on calculated values """ qmax = str(q_range_max) qmin = str(q_range_min) self.model.item(self.MODEL.index('MIN_RANGE')).setText(qmin) self.model.item(self.MODEL.index('MAX_RANGE')).setText(qmax) self.model.item(self.MODEL.index('NPTS')).setText(str(npts)) self.qmin, self.qmax, self.npts = q_range_min, q_range_max, npts npts_fit = self.npts2fit(self.logic.data) self.model.item(self.MODEL.index('NPTS_FIT')).setText(str(npts_fit))
[docs] def state(self): """ Returns current state of controls """ q_range_min = float(self.model.item(self.MODEL.index('MIN_RANGE')).text()) q_range_max = float(self.model.item(self.MODEL.index('MAX_RANGE')).text()) npts = int(self.model.item(self.MODEL.index('NPTS')).text()) npts_fit = int(self.model.item(self.MODEL.index('NPTS_FIT')).text()) log_points = str(self.model.item(self.MODEL.index('LOG_SPACED')).text()) == 'true' return (q_range_min, q_range_max, npts, log_points, self.weighting)
[docs] def npts2fit(self, data=None, qmin=None, qmax=None, npts=None): """ return numbers of data points within qrange :Note: This is to normalize chisq by Npts of fit """ npts2fit = 0 if data is None: return npts2fit qmin_c, qmax_c, npts_c = self.logic.computeDataRange() if qmin is None: qmin = qmin_c if qmax is None: qmax = qmax_c if npts is None: npts = npts_c if isinstance(data, Data2D): radius = np.sqrt(data.qx_data * data.qx_data + data.qy_data * data.qy_data) index_data = (qmin <= radius) & (radius <= qmax) index_data = (index_data) & (data.mask) index_data = (index_data) & (np.isfinite(data.data)) npts2fit = len(data.data[index_data]) else: for qx in data.x: if qmax >= qx >= qmin: npts2fit += 1 return npts2fit