673 lines
26 KiB
Python
Executable File
673 lines
26 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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_author_ = "Markus Rosenstihl"
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import hashlib,uuid
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import time
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import os,sys,re,signal
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import matplotlib
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matplotlib.use('agg')
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from matplotlib import pyplot
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from matplotlib.colors import hex2color
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#matplotlib.rc_file("default.mplrc")
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from PyQt4.QtCore import *
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from PyQt4.QtGui import *
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import numpy as np
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import pyqtgraph as pg
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from Container import Conductivity, PowerComplex, Static, Peak, YAFF
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from ContainerWidgets import ParameterWidget
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from BDSMathlib import FunctionRegister, FitRoutine
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from Data import Data
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import QDSMain
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import ExtraDifferentialWidget
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class AppWindow(QMainWindow):
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def __init__(self, files=[], parent=None):
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super(AppWindow, self).__init__(parent)
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self.ui = QDSMain.Ui_MainWindow()
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self.ui.setupUi(self)
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self._file_paths = self._sortInputFiles(files)
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self._last_written_header = None
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actions = {
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self.ui.actionAdd_Peak:self.addPeak,
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self.ui.actionAdd_Cond:self.addCond,
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self.ui.actionAdd_PowerLaw:self.addPowerComplex,
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self.ui.actionAdd_Eps_Infty:self.addEpsInfty,
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self.ui.actionYAFF:self.addYaff,
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}
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self.myActionGroup = QActionGroup(self)
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for a in actions.keys(): self.myActionGroup.addAction(a)
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self._init_menu()
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self.function_registry = FunctionRegister()
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self.session_id = uuid.uuid4()
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self.peakId = 0
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self.parameterWidget = ParameterWidget()
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self.ui.dockWidget_3.setWidget(self.parameterWidget)
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self.data = Data()
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self.fit_boundary_imag = pg.LinearRegionItem(brush=QColor(0,127,254,15))
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self.fit_boundary_real = pg.LinearRegionItem(brush=QColor(0,127,254,15))
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self.ui.pgPlotWidget_imag.addItem(self.data.data_curve_imag)
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self.ui.pgPlotWidget_real.addItem(self.data.data_curve_real)
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self.ui.pgPlotWidget_imag.addItem(self.data.fitted_curve_imag)
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self.ui.pgPlotWidget_real.addItem(self.data.fitted_curve_real)
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self.ui.pgPlotWidget_imag.addItem(self.fit_boundary_imag)
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self.ui.pgPlotWidget_real.addItem(self.fit_boundary_real)
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# fit boundary signals
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self.fit_boundary_imag.sigRegionChanged.connect(self._update_fit_boundary_imag)
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self.fit_boundary_imag.sigRegionChangeFinished.connect(self.updatePlot)
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self.fit_boundary_real.sigRegionChanged.connect(self._update_fit_boundary_real)
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self.fit_boundary_real.sigRegionChangeFinished.connect(self.updatePlot)
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for pltwidgt in (self.ui.pgPlotWidget_real, self.ui.pgPlotWidget_imag):
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pltwidgt.setLogMode(x=True, y=True)
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pltwidgt.showGrid(x=True, y=True)
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pltwidgt.disableAutoRange()
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pltwidgt.setLabel("bottom", "Frequency", units="Hz")
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self.ui.pgPlotWidget_imag.setLabel("left", u'Dielectric loss ε"' , units="Debye")
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self.ui.pgPlotWidget_real.setLabel("left", u"Dielectric loss ε' ", units="Debye")
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sc_real = self.ui.pgPlotWidget_real.scene()
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sc_real.sigMouseClicked.connect(self.mousePress)
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sc_real.sigMouseMoved.connect(self.updateCrosshair)
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sc_imag = self.ui.pgPlotWidget_imag.scene()
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sc_imag.sigMouseClicked.connect(self.mousePress)
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sc_imag.sigMouseMoved.connect(self.updateCrosshair)
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self._fit_thread = QThread()
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self._fit_method = FitRoutine()
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self._fit_method.moveToThread(self._fit_thread)
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self._fit_method.finished_fit.connect(self.fitData_update)
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self._fit_method.data_ready.connect(self.updateIntermediatePlot)
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self._fit_thread.started.connect(self._fit_method.fit)
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# finally process cmd line args
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if files != []:
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self.openFile(unicode(self._file_paths[0]))
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self._current_file_index = 0
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def _init_menu(self):
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fileMenu = self.menuBar().addMenu("File")
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openFile = QAction("&Open", self)
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openFile.setShortcut(QKeySequence.Open)
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openFile.triggered.connect(self.getFileNames)
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fileMenu.addAction(openFile)
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nextFile = QAction("Next", self)
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nextFile.setShortcut(QKeySequence("Ctrl+k"))
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nextFile.triggered.connect(self.nextFile)
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fileMenu.addAction(nextFile)
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previousFile = QAction("Previous", self)
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previousFile.setShortcut(QKeySequence("Ctrl+j"))
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previousFile.triggered.connect(self.previousFile)
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fileMenu.addAction(previousFile)
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saveFile = QAction("&Save Fit Result", self)
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saveFile.setShortcut(QKeySequence.Save)
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saveFile.triggered.connect(self.saveFitResult)
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fileMenu.addAction(saveFile)
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# fitting methods
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fitMenu = self.menuBar().addMenu("Standard Fits")
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# lm
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fit_lmAction = QAction("Complex NLS", self)
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fit_lmAction.setShortcut(QKeySequence("Ctrl+F"))
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fitMenu.addAction(fit_lmAction)
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# lbfgsb
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fit_lbfgsbAction = QAction("NLS (Imag.)", self)
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fitMenu.addAction(fit_lbfgsbAction)
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# Simulated Annealing
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fit_annealAction = QAction("&Simulated Annealing", self)
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fitMenu.addAction(fit_annealAction)
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self.ui.actionActionAbortFit.triggered.connect(self.abortFit)
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self.signalMapper = QSignalMapper(self)
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for i, fit_action in enumerate([fit_lmAction, fit_lbfgsbAction, fit_annealAction
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]):
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self.signalMapper.setMapping(fit_action, i)
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fit_action.triggered.connect(self.signalMapper.map)
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self.signalMapper.mapped.connect(self.fitData_start)
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self.ui.actionShow_Derivative.triggered.connect(self.show_derivative)
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def show_derivative(self):
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self.xtra_wdgt = ExtraDifferentialWidget.DifferentialWidget()
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#self.xtra_wdgt.set
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deriv_r = np.diff(np.log10(self.data.epsilon.real))
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deriv_i = np.diff(np.log10(self.data.epsilon.imag))*0
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deriv_i = -np.pi/2 * np.diff(np.log10(self.data.epsilon.real))/np.diff(np.log10(self.data.frequency))
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self.xtra_wdgt.plot(self.data.frequency[:-1], deriv_r, deriv_i)
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# self.xtra_wdgt.plot([0,1], [0,1], [0,1])
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self.xtra_wdgt.setGeometry(self.ui.pgPlotWidget_real.geometry())
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self.xtra_wdgt.show()
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#self.xtra_wdgt.showCenterd()
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self.xtra_wdgt.raise_()
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def updateCrosshair(self,evt):
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vb_real = self.ui.pgPlotWidget_real.getPlotItem().vb
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vb_imag = self.ui.pgPlotWidget_imag.getPlotItem().vb
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if self.ui.pgPlotWidget_imag.underMouse():
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pos = vb_imag.mapSceneToView(evt)
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elif self.ui.pgPlotWidget_real.underMouse():
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pos = vb_real.mapSceneToView(evt)
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else:
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pos = QPointF(0.0, 0.0)
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self.last_pos = pos
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def mousePress(self, evt):
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data_pos = self.last_pos
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mouse_in_imag = self.ui.pgPlotWidget_imag.underMouse()
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mouse_in_real = self.ui.pgPlotWidget_real.underMouse()
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msgBox = QMessageBox()
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if self.ui.actionAdd_Peak.isChecked():
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if mouse_in_imag:
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self.addPeak(data_pos)
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self.ui.actionAdd_Peak.setChecked(False)
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else:
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msgBox.setText("Click in imaginary part")
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msgBox.exec_()
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if self.ui.actionAdd_Cond.isChecked():
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if mouse_in_imag:
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self.addCond(data_pos)
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self.ui.actionAdd_Cond.setChecked(False)
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else:
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msgBox.setText("Click in imaginary part")
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msgBox.exec_()
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if self.ui.actionYAFF.isChecked():
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if mouse_in_imag:
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self.addYaff(data_pos)
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self.ui.actionYAFF.setChecked(False)
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else:
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msgBox.setText("Click in imaginary part")
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msgBox.exec_()
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if self.ui.actionAdd_PowerLaw.isChecked():
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if mouse_in_imag:
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self.addPowerComplex(data_pos)
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self.ui.actionAdd_PowerLaw.setChecked(False)
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else:
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msgBox.setText("Click in imaginary part")
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msgBox.exec_()
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if self.ui.actionAdd_Eps_Infty.isChecked():
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if mouse_in_real:
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self.addEpsInfty(data_pos)
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self.ui.actionAdd_Eps_Infty.setChecked(False)
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else:
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msgBox.setText("Click in real part")
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msgBox.exec_()
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def abortFit(self):
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for container in self.function_registry.get_registered_functions():
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container.abort(True)
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self._fit_thread.terminate()
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def saveFitResult(self):
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"""
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Saving fit parameters to fitresults.log
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including temperature
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"""
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self._saveFitFigure()
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if not os.path.exists("fitresults.log"):
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f = open("fitresults.log", "w")
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else:
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f = open("fitresults.log", "a")
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# prepare header
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file_id = hashlib.md5(open(self._file_paths[self._current_file_index]).read()).hexdigest()
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pre_header = "# Date: {date}\n".format(date=time.strftime("%Y-%m-%d"))
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pre_header += "# Time: {time}\n# SessionID={id}\n".format(time=time.strftime("%H:%M:%S"), id=self.session_id)
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pars = []
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base_filename, file_ext = os.path.splitext(self.filepath)
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# print "Registered Functions (saveFitResult): ",self.function_registry.get_registered_functions()
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header = "{n1:13}{n2:13}".format(n1="# 0:T", n2="1:invT")
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varnum = 2 # T, invT are the first two columns
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# sort peaks by time constant tau
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sorted_functions = list()
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tau_comp = 0
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for i_fcn, fcn in enumerate(self.function_registry.get_registered_functions()):
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if fcn.id_string == "hn":
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for i,varname in enumerate(fcn.widget.names):
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if varname == "tau":
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if fcn._beta[i] <= tau_comp:
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sorted_functions.append(fcn)
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else:
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sorted_functions.insert(0,fcn)
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tau_comp = fcn._beta[i]
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# eps_infty to the front
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for a in self.function_registry.get_registered_functions():
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print a.id_string
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if a.id_string == "eps_infty":
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sorted_functions.insert(0,a)
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print a
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# sort the rest lexigraphically
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for a in self.function_registry.get_registered_functions():
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if a.id_string == "pwr":
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sorted_functions.append(a)
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print a
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for a in self.function_registry.get_registered_functions():
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if a.id_string == "cond":
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sorted_functions.append(a)
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print a
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for a in self.function_registry.get_registered_functions():
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if a.id_string == "yaff":
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print a
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sorted_functions.append(a)
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print sorted_functions
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for i_fcn, fcn in enumerate(sorted_functions):
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fit_function_name = fcn.id_string
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for i, name in enumerate(fcn.widget.names): # get variable names
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header += "{n:13}{n_sd:13}".format(n="%i:%s"%(varnum, name), n_sd="%i:%s_sd"%(varnum+1, name))
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varnum += 2
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# write for each function an extra file
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fit_filename = "%s_%i.fit"%(base_filename, i_fcn)
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f_fcn = open(fit_filename, 'w')
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# retrieve correct function type peak
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#if fit_function_name == "hn":
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f_fcn.write("# type=%s\n"%fcn.widget.func_type)
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f_fcn.write("# SourceID=%s\n"%file_id)
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#else:
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# f_fcn.write("# type=%s\n"%fit_function_name)
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for i,par in enumerate(fcn._beta): # params # TODO: ughh
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if fcn._selector_mask is not None:
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if fcn._selector_mask[i]:
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pars.extend([par])
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pars.extend([fcn._sd_beta[i]])
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f_fcn.write('# param=%s %e %e\n'%(fcn.widget.names[i], par, fcn._sd_beta[i]))
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else:
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pars.extend([par])
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pars.extend([fcn._sd_beta[i]])
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f_fcn.write('# param=%s %e %e\n'%(fcn.widget.names[i], par, fcn._sd_beta[i]))
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# finish writing fit function file
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f_fcn.flush()
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np.savetxt(f_fcn, fcn.resampleData(self.data.frequency))
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f_fcn.close()
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# append fit limits header
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header += "%-13s%-13s\n"%("fit_xlow", "fit_xhigh")
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# write new header if fit model changed TODO: more robust detection
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if self._last_written_header != header:
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f.write(pre_header)
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f.write(header)
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f.flush()
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self._last_written_header = header
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else:
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pass
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pars.insert(0, self.data.meta["T"])
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pars.insert(1, 1e3/self.data.meta["T"])
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pars.append(self.data.fit_limits[0])
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pars.append(self.data.fit_limits[1])
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pars = np.array([pars])
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np.savetxt(f, pars, fmt='%-12.3e', delimiter=" ")
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f.close()
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def _saveFitFigure(self):
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fig = pyplot.figure(figsize=(3.54*1.4, 2.75*1.4))
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font = {'family' : 'sans serif',
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'weight' : 'normal',
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'size' : 9}
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matplotlib.rc('font', **font)
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pyplot.grid(linestyle="solid",alpha=0.3, color="0.5")
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pyplot.loglog(self.data.frequency, self.data.epsilon.imag, 'bo', markersize=4, label="Data")
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pyplot.loglog(self.data.frequency_fit, self.data.epsilon_fit.imag, 'r-', lw=1.2, label="Fit")
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for fcn in self.function_registry.get_registered_functions():
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f,eps = fcn.get_data()
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label = fcn.id_label
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color = hex2color(str(fcn.color.name()))
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pyplot.loglog(f,eps[1], ls=":", color=color, lw=1, dashes=(1,1), label=label)
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for i in (0,1): pyplot.axvline(x=self.data.fit_limits[i], color='b', ls="-", lw=0.5)
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pyplot.legend(title = "T=%.1f K"%(self.data.meta["T"]))
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pyplot.xlabel('f/Hz')
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pyplot.ylabel(u'ε"')
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pyplot.ylim(self.data.epsilon.imag.min(), self.data.epsilon.imag.max() )
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#pyplot.savefig(os.path.splitext(self.filepath)[0]+".png")
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pyplot.savefig(os.path.splitext(self.filepath)[0]+".pdf")
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fig.clear()
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del (fig)
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def _saveFitFigureGrace(self):
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#agrtemplate = open('template.agr').read()
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agrtemplate = """
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"""
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#TODO: need interface/method for adding function blocks, this is too repetitive
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def addYaff(self, pos):
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_yaff = YAFF(plt_real=self.ui.pgPlotWidget_real,
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plt_imag=self.ui.pgPlotWidget_imag,
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limits=self.data.fit_limits)
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_yaff.blockSignals(True)
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_yaff.changedData.connect(self.updatePlot)
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_yaff.removeObj.connect(self.delParamterObject)
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gg_y = 10**pos.y()*2
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gg_x = 1/(10**pos.x()*2*np.pi)
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yaff_par = [ gg_y, gg_x , 20.0, 1.0, 0.5, gg_x/100, 1.0, 1.0]
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_yaff.setParameter(beta=yaff_par)
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self.parameterWidget.add(_yaff.widget)
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self.function_registry.register_function(_yaff)
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self.updatePlot()
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_yaff.blockSignals(False)
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def addCond(self, pos):
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_conductivity = Conductivity(plt_real=self.ui.pgPlotWidget_real,
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plt_imag=self.ui.pgPlotWidget_imag,
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limits=self.data.fit_limits)
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_conductivity.blockSignals(True)
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_conductivity.changedData.connect(self.updatePlot)
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_conductivity.removeObj.connect(self.delParamterObject)
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cond_par = [0.0, 10**(pos.y() + pos.x())*2*np.pi , 1.0]
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_conductivity.setParameter(beta=cond_par)
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self.parameterWidget.add(_conductivity.widget)
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self.function_registry.register_function(_conductivity)
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self.updatePlot()
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_conductivity.blockSignals(False)
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def addPowerComplex(self, pos):
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_power_complex = PowerComplex(plt_imag=self.ui.pgPlotWidget_imag,
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plt_real=self.ui.pgPlotWidget_real,
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limits=self.data.fit_limits)
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_power_complex.changedData.connect(self.updatePlot)
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_power_complex.removeObj.connect(self.delParamterObject)
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cond_par = [10**(pos.y() + pos.x())*2*np.pi , 1.0]
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_power_complex.setParameter(beta=cond_par)
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self.parameterWidget.add(_power_complex.widget)
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self.function_registry.register_function(_power_complex)
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self.updatePlot()
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def addEpsInfty(self, pos):
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_eps_infty = Static(plt_imag=self.ui.pgPlotWidget_imag,
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plt_real=self.ui.pgPlotWidget_real,
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limits=self.data.fit_limits)
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_eps_infty.changedData.connect(self.updatePlot)
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_eps_infty.removeObj.connect(self.delParamterObject)
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cond_par = [10**pos.y()]
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_eps_infty.setParameter(beta=cond_par)
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self.parameterWidget.add(_eps_infty.widget)
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self.function_registry.register_function(_eps_infty)
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self.updatePlot()
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def delParamterObject(self, obj):
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self.function_registry.unregister_function(obj)
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self.updatePlot()
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def addPeak(self, pos):
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id_list = [ key.id_num for key in
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self.function_registry.get_registered_functions()
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if key.id_string == 'hn']
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for k in self.function_registry.get_registered_functions():
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print k.id_num,k.id_label
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|
self.peakId = 1
|
|
print id_list
|
|
while self.peakId in id_list:
|
|
self.peakId += 1
|
|
_peak = Peak(id_num=self.peakId,
|
|
plt_real=self.ui.pgPlotWidget_real,
|
|
plt_imag=self.ui.pgPlotWidget_imag,
|
|
limits=self.data.fit_limits)
|
|
self.function_registry.register_function(_peak)
|
|
|
|
_peak.changedData.connect(self.updatePlot)
|
|
_peak.removeObj.connect(self.delParamterObject)
|
|
new_peak_beta0 = [2*10**pos.y(), 1 / (2*np.pi*10**pos.x()), 1, 1]
|
|
_peak.setParameter(beta = new_peak_beta0)
|
|
self.parameterWidget.add(_peak.widget)
|
|
self.updatePlot()
|
|
|
|
def fitData_start(self, method):
|
|
#fit_methods = [fit_odr_cmplx, fit_odr_imag, fit_lbfgsb, fit_anneal]
|
|
self.fit_boundary_real.hide()
|
|
self.fit_boundary_imag.hide()
|
|
fit_method = [
|
|
self._fit_method.fit_odr_cmplx,
|
|
self._fit_method.fit_odr_imag,
|
|
][method]
|
|
|
|
# build function list
|
|
p0,funcs,fixed_params = [],[],[]
|
|
for fcn in self.function_registry.get_registered_functions():
|
|
p0.extend(fcn.getParameter())
|
|
funcs.append(fcn)
|
|
fixed_params.extend(fcn.getFixed())
|
|
fcn.clearData()
|
|
_freq, _fit = self.data.get_data()
|
|
|
|
if not self._fit_thread.isRunning():
|
|
#self._fit_method.fit_odr_cmplx(_freq, _fit, p0, fixed_params, funcs)
|
|
fit_method(_freq, _fit, p0, fixed_params, funcs)
|
|
self._fit_thread.start()
|
|
self.ui.statusbar.showMessage("Fitting ...")
|
|
else:
|
|
self.ui.statusbar.showMessage("Still fitting ...")
|
|
|
|
def fitData_update(self):
|
|
self._fit_thread.quit()
|
|
odr_result = self._fit_method.result()
|
|
p0,funcs,fixed_params = [],[],[]
|
|
for fcn in self.function_registry.get_registered_functions():
|
|
p0.extend(fcn.getParameter())
|
|
funcs.append(fcn)
|
|
fixed_params.extend(fcn.getFixed())
|
|
|
|
for container in self.function_registry.get_registered_functions():
|
|
container.abort(False)
|
|
|
|
|
|
self.data.set_fit(odr_result.beta, funcs)
|
|
self.ui.statusbar.showMessage(" ".join(odr_result.stopreason))
|
|
ndx = 0
|
|
for i,fcn in enumerate(self.function_registry.get_registered_functions()):
|
|
num_p = len(fcn.getParameter())
|
|
beta = odr_result.beta[ndx:num_p+ndx]
|
|
if odr_result.sd_beta is not None:
|
|
sd_beta = odr_result.sd_beta[ndx:num_p+ndx]
|
|
else:
|
|
sd_beta = None
|
|
fcn.setParameter(beta, sd_beta)
|
|
ndx += num_p
|
|
|
|
self.fit_boundary_real.show()
|
|
self.fit_boundary_imag.show()
|
|
|
|
def getFileNames(self):
|
|
tmp = QFileDialog.getOpenFileNames(self, "Open file", "", '*.dat *.TXT')
|
|
if len(tmp) != 0:
|
|
self._file_paths = tmp
|
|
self._current_file_index = 0
|
|
path = unicode(self._file_paths[self._current_file_index])
|
|
self.openFile(path)
|
|
|
|
def nextFile(self):
|
|
lim = self.fit_boundary_imag.getRegion() # store limits
|
|
if len(self._file_paths) > self._current_file_index+1: # wrap around
|
|
self._current_file_index += 1
|
|
else:
|
|
self._current_file_index = 0
|
|
path = unicode(self._file_paths[self._current_file_index])
|
|
self.openFile(path)
|
|
self.fit_boundary_imag.setRegion(lim)
|
|
|
|
def previousFile(self):
|
|
lim = self.fit_boundary_imag.getRegion() # store limits
|
|
if self._current_file_index == 0: # wrap around
|
|
self._current_file_index = len(self._file_paths) - 1
|
|
else:
|
|
self._current_file_index -= 1
|
|
path = unicode(self._file_paths[self._current_file_index])
|
|
self.openFile(path)
|
|
self.fit_boundary_imag.setRegion(lim)
|
|
|
|
def _sortInputFiles( self, files ):
|
|
return QStringList(sorted(files, key=lambda x: re.findall("\d+\.\d+K", x)))
|
|
|
|
|
|
def openFile(self,path):
|
|
print "opening: %s"%path
|
|
self.filepath=path
|
|
# TODO analyze file (LF,MF, HF) and act accordingly
|
|
data = np.loadtxt(path, skiprows=4)
|
|
numpat = re.compile('\d+\.\d+')
|
|
try:
|
|
Temp = None
|
|
for line in open(path).readlines():
|
|
if re.search("Fixed", line) or re.search("Temp", line):
|
|
print "Found line containing 'Fixed' or 'Temp':"
|
|
print line
|
|
Temp = float(re.search(numpat, line).group())
|
|
print "Temperature found in file:", Temp
|
|
break
|
|
search_temp_in_filename = re.search('\d+\.\d+K', path)
|
|
if search_temp_in_filename:
|
|
Temp = float(search_temp_in_filename.group()[:-1])
|
|
if Temp == None: raise ValueError
|
|
except:
|
|
Temp = QInputDialog.getDouble(self, "No temperature found in data set", "Temperature/K:", value=0.00)[0]
|
|
# mask the data to values > 0 (loglog plot)
|
|
self.setWindowTitle("%s - %.2f K"%(os.path.basename(path), Temp))
|
|
|
|
mask = (data[:, 1] > 0) & (data[:, 2] > 0) #& (data[:,2]>1e-3) & (data[:,0] > 1e-2)
|
|
_freq = data[mask, 0]
|
|
_die_stor = data[mask, 1]
|
|
_die_loss = data[mask, 2]
|
|
self.data.set_data(_freq, _die_stor, _die_loss)
|
|
self.data.meta["T"] = Temp
|
|
self.fit_boundary_imag.setRegion([np.log10(_freq.min()), np.log10(_freq.max())])
|
|
# self.ui.pgPlotWidget_imag.enableAutoRange()
|
|
# self.ui.pgPlotWidget_real.enableAutoRange()
|
|
self.ui.pgPlotWidget_imag.disableAutoRange()
|
|
self.ui.pgPlotWidget_real.disableAutoRange()
|
|
|
|
self.ui.pgPlotWidget_imag.setXRange(np.log10(_freq.min()), np.log10(_freq.max()))
|
|
self.ui.pgPlotWidget_imag.setYRange(np.log10(_die_loss.min()), np.log10(_die_loss.max()))
|
|
|
|
self.ui.pgPlotWidget_real.setXRange(np.log10(_freq.min()), np.log10(_freq.max()))
|
|
self.ui.pgPlotWidget_real.setYRange(np.log10(_die_stor.min()), np.log10(_die_stor.max()))
|
|
|
|
|
|
#self.ui.pgPlotWidget_real.setRange(xRange=(_freq.min(), _freq.max()),
|
|
# yRange=(_die_stor.min(), _die_stor.max()) )
|
|
self.updatePlot()
|
|
|
|
|
|
|
|
def updatePlot(self):
|
|
log10fmin, log10fmax = self.fit_boundary_imag.getRegion()
|
|
self.data.set_fit_xlimits(10**log10fmin, 10**log10fmax)
|
|
|
|
p0,funcs = [],[]
|
|
for fcn in self.function_registry.get_registered_functions():
|
|
p0.extend(fcn.getParameter())
|
|
funcs.append(fcn)
|
|
|
|
|
|
# calculate parametrized curve
|
|
self.data.set_fit(p0, funcs)
|
|
|
|
|
|
# replot data and fit, TODO: replot only if measurement data changed
|
|
self.data.data_curve_real.setData(self.data.frequency, self.data.epsilon.real)
|
|
self.data.data_curve_imag.setData(self.data.frequency, self.data.epsilon.imag)
|
|
#print "updatePlot: ",self.data.frequency_fit, self.data.epsilon_fit
|
|
if len(funcs) > 0:
|
|
#print "funcs > 0:",self.data.frequency_fit, self.data.epsilon_fit
|
|
self.data.fitted_curve_real.setData(x=self.data.frequency_fit, y=self.data.epsilon_fit.real)
|
|
self.data.fitted_curve_imag.setData(x=self.data.frequency_fit, y=self.data.epsilon_fit.imag)
|
|
else:
|
|
self.data.fitted_curve_real.setData(x=np.array([np.nan]), y=np.array([np.nan]))
|
|
self.data.fitted_curve_imag.setData(x=np.array([np.nan]), y=np.array([np.nan]))
|
|
|
|
|
|
def updateIntermediatePlot(self, freq, intermediate_data):
|
|
self.data.fitted_curve_real.setData(freq, intermediate_data[0])
|
|
self.data.fitted_curve_imag.setData(freq, intermediate_data[1])
|
|
|
|
def _update_fit_boundary_imag( self ):
|
|
"""
|
|
Update real region when with imag reagion
|
|
"""
|
|
self.fit_boundary_real.setRegion(self.fit_boundary_imag.getRegion())
|
|
self._update_fit_boundary()
|
|
|
|
def _update_fit_boundary_real( self ):
|
|
"""
|
|
Update imag region when with real reagion
|
|
"""
|
|
self.fit_boundary_imag.setRegion(self.fit_boundary_real.getRegion())
|
|
self._update_fit_boundary()
|
|
|
|
def _update_fit_boundary(self):
|
|
"""
|
|
Update limits in container.
|
|
"""
|
|
for container in self.function_registry.get_registered_functions():
|
|
lims = [10**i for i in self.fit_boundary_real.getRegion()]
|
|
container.set_limits(lims)
|
|
|
|
def sigint_handler(*args):
|
|
"""
|
|
Handler for the SIGINT signal (CTRL + C).
|
|
"""
|
|
sys.stderr.write('\r')
|
|
if QMessageBox.question(None, '', "Are you sure you want to quit?",
|
|
QMessageBox.Yes | QMessageBox.No,
|
|
QMessageBox.Yes) == QMessageBox.Yes:
|
|
QApplication.quit()
|
|
|
|
|
|
if __name__ == '__main__':
|
|
signal.signal(signal.SIGINT, sigint_handler)
|
|
files = sys.argv[1:]
|
|
app = QApplication(sys.argv)
|
|
timer = QTimer()
|
|
timer.start(1000) # Check every second for Strg-c on Cmd line
|
|
timer.timeout.connect(lambda: None)
|
|
main = AppWindow(files=files)
|
|
main.showMaximized()
|
|
main.raise_()
|
|
sys.exit(app.exec_())
|