Exemplo n.º 1
0
    def __init__(self, fits_file, settings, database, project=None):
        super(CalibrateSpectrum, self).__init__()
        self.project=project
        self.settings = settings
        self.fits_spectrum = FitsSpectrum(fits_file)
        self.fits_spectrum.spectrum.normalize_to_max()
        self.fits_file = fits_file
        self.ui = Ui_CalibrateSpectrum()
        self.ui.setupUi(self)
        self.toolbar = QToolBar('Calibration Toolbar')
        self.toolbar.setToolButtonStyle(Qt.ToolButtonTextBesideIcon)
        self.ui.x_axis_pick.setMenu(QMenu())
        self.ui.x_axis_pick.menu().addAction("Maximum from range").triggered.connect(lambda: self.pick_from_range('maximum'))
        self.ui.x_axis_pick.menu().addAction("Minimum from range").triggered.connect(lambda: self.pick_from_range('minimum'))
        self.ui.x_axis_pick.menu().addAction("Central value from range").triggered.connect(lambda: self.pick_from_range('central'))
        self.ui.wavelength_pick.clicked.connect(lambda: self.lines_dialog.show())
        
        save_action = self.toolbar.addAction(QIcon(':/save_20'), 'Save', self.save_spectrum)
        self.spectrum_plot = QtCommons.nestWidget(self.ui.spectrum_plot_widget, QMathPlotWidget())
        
        self.reference_spectra_dialog = ReferenceSpectraDialog(database)
        self.reference_spectra_dialog.setup_menu(self.toolbar, self.spectrum_plot.axes, settings)

        self.object_properties = ObjectProperties(self.fits_file, project=project)
        self.object_properties_dialog = ObjectPropertiesDialog(settings, self.object_properties)
        self.toolbar.addAction("Object properties", self.object_properties_dialog.show)

        self.calibration_model = QStandardItemModel()
        self.calibration_model.setHorizontalHeaderLabels(["x-axis", "wavelength", "error"])
        self.ui.calibration_points.setModel(self.calibration_model)
        self.ui.calibration_points.selectionModel().selectionChanged.connect(lambda selected, deselected: self.ui.remove_calibration_point.setEnabled(len(selected.indexes()) > 0)  )
        self.ui.add_calibration_point.clicked.connect(self.add_calibration_point)
        self.ui.remove_calibration_point.setEnabled(False)
        self.ui.remove_calibration_point.clicked.connect(self.remove_calibration_point)
        if project and project.avg_dispersion():
            self.ui.set_dispersion.setMenu(QMenu())
            self.ui.set_dispersion.menu().addAction('From input value', self.calculate_calibration)
            self.ui.set_dispersion.menu().addAction('From Project', lambda: self.calculate_calibration(project.avg_dispersion()))
        else:
            self.ui.set_dispersion.clicked.connect(self.calculate_calibration)
        self.ui.point_is_star.toggled.connect(lambda checked: self.ui.wavelength_pick.setEnabled(not checked))
        self.ui.point_is_star.toggled.connect(lambda checked: self.ui.point_wavelength.setEnabled(not checked))
        self.fits_spectrum.plot_to(self.spectrum_plot.axes)
        
        self.toolbar.addSeparator()
        self.toolbar.addAction("Zoom", self.spectrum_plot.select_zoom)
        self.toolbar.addAction("Reset Zoom", lambda: self.spectrum_plot.reset_zoom(self.fits_spectrum.spectrum.wavelengths, self.fits_spectrum.spectrum.fluxes.min(), self.fits_spectrum.spectrum.fluxes.max()))
        self.toolbar.addSeparator()
        
        self.lines_dialog = LinesDialog(database, settings, self.spectrum_plot, enable_picker = False, selection_mode = 'single')
        self.lines_dialog.lines.connect(self.picked_line)

        hdu_calibration_points = [h for h in self.fits_file if h.name == FitsSpectrum.CALIBRATION_DATA]
        if len(hdu_calibration_points) > 0:                
            for point in hdu_calibration_points[-1].data:
                self.add_calibration_point_data(point[0], point[1])
        self.calculate_calibration()
Exemplo n.º 2
0
    def __init__(self, fits_file, settings, database, project=None):
        super(CalibrateSpectrum, self).__init__()
        self.project = project
        self.settings = settings
        self.fits_spectrum = FitsSpectrum(fits_file)
        self.fits_spectrum.spectrum.normalize_to_max()
        self.fits_file = fits_file
        self.ui = Ui_CalibrateSpectrum()
        self.ui.setupUi(self)
        self.toolbar = QToolBar('Calibration Toolbar')
        self.toolbar.setToolButtonStyle(Qt.ToolButtonTextBesideIcon)
        self.ui.x_axis_pick.setMenu(QMenu())
        self.ui.x_axis_pick.menu().addAction(
            "Maximum from range").triggered.connect(
                lambda: self.pick_from_range('maximum'))
        self.ui.x_axis_pick.menu().addAction(
            "Minimum from range").triggered.connect(
                lambda: self.pick_from_range('minimum'))
        self.ui.x_axis_pick.menu().addAction(
            "Central value from range").triggered.connect(
                lambda: self.pick_from_range('central'))
        self.ui.wavelength_pick.clicked.connect(
            lambda: self.lines_dialog.show())

        save_action = self.toolbar.addAction(QIcon(':/save_20'), 'Save',
                                             self.save_spectrum)
        self.spectrum_plot = QtCommons.nestWidget(self.ui.spectrum_plot_widget,
                                                  QMathPlotWidget())

        self.reference_spectra_dialog = ReferenceSpectraDialog(database)
        self.reference_spectra_dialog.setup_menu(self.toolbar,
                                                 self.spectrum_plot.axes,
                                                 settings)

        self.object_properties = ObjectProperties(self.fits_file,
                                                  project=project)
        self.object_properties_dialog = ObjectPropertiesDialog(
            settings, self.object_properties)
        self.toolbar.addAction("Object properties",
                               self.object_properties_dialog.show)

        self.calibration_model = QStandardItemModel()
        self.calibration_model.setHorizontalHeaderLabels(
            ["x-axis", "wavelength", "error"])
        self.ui.calibration_points.setModel(self.calibration_model)
        self.ui.calibration_points.selectionModel().selectionChanged.connect(
            lambda selected, deselected: self.ui.remove_calibration_point.
            setEnabled(len(selected.indexes()) > 0))
        self.ui.add_calibration_point.clicked.connect(
            self.add_calibration_point)
        self.ui.remove_calibration_point.setEnabled(False)
        self.ui.remove_calibration_point.clicked.connect(
            self.remove_calibration_point)
        if project and project.avg_dispersion():
            self.ui.set_dispersion.setMenu(QMenu())
            self.ui.set_dispersion.menu().addAction('From input value',
                                                    self.calculate_calibration)
            self.ui.set_dispersion.menu().addAction(
                'From Project',
                lambda: self.calculate_calibration(project.avg_dispersion()))
        else:
            self.ui.set_dispersion.clicked.connect(self.calculate_calibration)
        self.ui.point_is_star.toggled.connect(
            lambda checked: self.ui.wavelength_pick.setEnabled(not checked))
        self.ui.point_is_star.toggled.connect(
            lambda checked: self.ui.point_wavelength.setEnabled(not checked))
        self.fits_spectrum.plot_to(self.spectrum_plot.axes)

        self.toolbar.addSeparator()
        self.toolbar.addAction("Zoom", self.spectrum_plot.select_zoom)
        self.toolbar.addAction(
            "Reset Zoom", lambda: self.spectrum_plot.reset_zoom(
                self.fits_spectrum.spectrum.wavelengths,
                self.fits_spectrum.spectrum.fluxes.min(),
                self.fits_spectrum.spectrum.fluxes.max()))
        self.toolbar.addSeparator()

        self.lines_dialog = LinesDialog(database,
                                        settings,
                                        self.spectrum_plot,
                                        enable_picker=False,
                                        selection_mode='single')
        self.lines_dialog.lines.connect(self.picked_line)

        hdu_calibration_points = [
            h for h in self.fits_file
            if h.name == FitsSpectrum.CALIBRATION_DATA
        ]
        if len(hdu_calibration_points) > 0:
            for point in hdu_calibration_points[-1].data:
                self.add_calibration_point_data(point[0], point[1])
        self.calculate_calibration()
Exemplo n.º 3
0
class CalibrateSpectrum(QWidget):
    def __init__(self, fits_file, settings, database, project=None):
        super(CalibrateSpectrum, self).__init__()
        self.project=project
        self.settings = settings
        self.fits_spectrum = FitsSpectrum(fits_file)
        self.fits_spectrum.spectrum.normalize_to_max()
        self.fits_file = fits_file
        self.ui = Ui_CalibrateSpectrum()
        self.ui.setupUi(self)
        self.toolbar = QToolBar('Calibration Toolbar')
        self.toolbar.setToolButtonStyle(Qt.ToolButtonTextBesideIcon)
        self.ui.x_axis_pick.setMenu(QMenu())
        self.ui.x_axis_pick.menu().addAction("Maximum from range").triggered.connect(lambda: self.pick_from_range('maximum'))
        self.ui.x_axis_pick.menu().addAction("Minimum from range").triggered.connect(lambda: self.pick_from_range('minimum'))
        self.ui.x_axis_pick.menu().addAction("Central value from range").triggered.connect(lambda: self.pick_from_range('central'))
        self.ui.wavelength_pick.clicked.connect(lambda: self.lines_dialog.show())
        
        save_action = self.toolbar.addAction(QIcon(':/save_20'), 'Save', self.save_spectrum)
        self.spectrum_plot = QtCommons.nestWidget(self.ui.spectrum_plot_widget, QMathPlotWidget())
        
        self.reference_spectra_dialog = ReferenceSpectraDialog(database)
        self.reference_spectra_dialog.setup_menu(self.toolbar, self.spectrum_plot.axes, settings)

        self.object_properties = ObjectProperties(self.fits_file, project=project)
        self.object_properties_dialog = ObjectPropertiesDialog(settings, self.object_properties)
        self.toolbar.addAction("Object properties", self.object_properties_dialog.show)

        self.calibration_model = QStandardItemModel()
        self.calibration_model.setHorizontalHeaderLabels(["x-axis", "wavelength", "error"])
        self.ui.calibration_points.setModel(self.calibration_model)
        self.ui.calibration_points.selectionModel().selectionChanged.connect(lambda selected, deselected: self.ui.remove_calibration_point.setEnabled(len(selected.indexes()) > 0)  )
        self.ui.add_calibration_point.clicked.connect(self.add_calibration_point)
        self.ui.remove_calibration_point.setEnabled(False)
        self.ui.remove_calibration_point.clicked.connect(self.remove_calibration_point)
        if project and project.avg_dispersion():
            self.ui.set_dispersion.setMenu(QMenu())
            self.ui.set_dispersion.menu().addAction('From input value', self.calculate_calibration)
            self.ui.set_dispersion.menu().addAction('From Project', lambda: self.calculate_calibration(project.avg_dispersion()))
        else:
            self.ui.set_dispersion.clicked.connect(self.calculate_calibration)
        self.ui.point_is_star.toggled.connect(lambda checked: self.ui.wavelength_pick.setEnabled(not checked))
        self.ui.point_is_star.toggled.connect(lambda checked: self.ui.point_wavelength.setEnabled(not checked))
        self.fits_spectrum.plot_to(self.spectrum_plot.axes)
        
        self.toolbar.addSeparator()
        self.toolbar.addAction("Zoom", self.spectrum_plot.select_zoom)
        self.toolbar.addAction("Reset Zoom", lambda: self.spectrum_plot.reset_zoom(self.fits_spectrum.spectrum.wavelengths, self.fits_spectrum.spectrum.fluxes.min(), self.fits_spectrum.spectrum.fluxes.max()))
        self.toolbar.addSeparator()
        
        self.lines_dialog = LinesDialog(database, settings, self.spectrum_plot, enable_picker = False, selection_mode = 'single')
        self.lines_dialog.lines.connect(self.picked_line)

        hdu_calibration_points = [h for h in self.fits_file if h.name == FitsSpectrum.CALIBRATION_DATA]
        if len(hdu_calibration_points) > 0:                
            for point in hdu_calibration_points[-1].data:
                self.add_calibration_point_data(point[0], point[1])
        self.calculate_calibration()
    
  
    def picked_from_range(self, type, min, max):
        min=(self.fits_spectrum.spectrum.wavelength_index(min))
        max=(self.fits_spectrum.spectrum.wavelength_index(max))
        add_line = lambda x: self.spectrum_plot.add_line("x_axis_pick", self.fits_spectrum.spectrum.wavelengths[x], color='r')
        set_x_value = lambda x: self.ui.point_x_axis.setValue(x)

        if type != 'central':
            subplot = SelectPlottedPoints(self.fits_spectrum.spectrum.fluxes, min, max+1, self.settings, type)
            subplot.point.connect(add_line)
            subplot.point.connect(set_x_value)
            subplot.show()
            return
        point = min+(max-min)/2
        self.ui.point_x_axis.setValue(point)
        set_x_value(point)
        add_line(point)

    def pick_from_range(self, type):
        self.spectrum_plot.add_span_selector('pick_x_axis', lambda min,max: self.picked_from_range(type, min, max),direction='horizontal')

    def remove_calibration_point(self):
        self.calibration_model.removeRow(self.ui.calibration_points.selectionModel().selectedIndexes()[0].row())
        self.calculate_calibration()
    
    def add_calibration_point_data(self, x_value, wavelength):
        x_axis_item = QStandardItem("star" if x_value == 0 else "{}".format(x_value))
        x_axis_item.setData(x_value)
        wavelength_item = QStandardItem("{:.2f}".format(wavelength))
        wavelength_item.setData(wavelength)
        self.calibration_model.appendRow([x_axis_item, wavelength_item, QStandardItem("n/a")])
        self.spectrum_plot.rm_element('x_axis_pick')
        
    def picked_line(self, lines):
        self.ui.point_wavelength.setValue(lines[0]['lambda'])
    
    def add_calibration_point(self):
        self.add_calibration_point_data(self.ui.point_x_axis.value(), 0 if self.ui.point_is_star.isChecked() else self.ui.point_wavelength.value())
        self.calculate_calibration()
        
    def calibration_points(self):
        return [{'row': row, 'x': self.calibration_model.item(row, 0).data(), 'wavelength': self.calibration_model.item(row, 1).data()} for row in range(self.calibration_model.rowCount())]
    

    def calculate_calibration(self, dispersion = None):
        points_number = self.calibration_model.rowCount()
        self.ui.set_dispersion.setEnabled(points_number == 1)
        self.ui.dispersion.setEnabled(points_number == 1)
        
        if points_number == 0:
            self.fits_spectrum.reset()
            self.lines_dialog.set_picker_enabled(False)
        else:
            self.lines_dialog.set_picker_enabled(True)
            points = sorted(self.calibration_points(), key=lambda point: point['x'])
            self.fits_spectrum.calibrate(points, dispersion if dispersion else self.ui.dispersion.value() )
            for row, value in [(p['row'], "{:.2f}".format( p['wavelength']-self.fits_spectrum.spectrum.wavelengths[p['x']])) for p in points]:
                self.calibration_model.item(row, 2).setText(value)
            
        self.ui.dispersion.setValue(self.fits_spectrum.spectrum.dispersion())
        self.fits_spectrum.plot_to(self.spectrum_plot.axes)
        
    def save_spectrum(self):
        if not self.project:
            save_file_sticky('Save plot...', 'FITS file (.fit)', lambda f: self.save(f[0]), self.settings, CALIBRATED_PROFILE, [RAW_PROFILE])
            return
        self.project.add_file(Project.CALIBRATED_PROFILE, object_properties = self.object_properties, on_added=self.save)
        
    def save(self, filename):
        self.fits_spectrum.save(filename, self.calibration_points())
Exemplo n.º 4
0
class CalibrateSpectrum(QWidget):
    def __init__(self, fits_file, settings, database, project=None):
        super(CalibrateSpectrum, self).__init__()
        self.project = project
        self.settings = settings
        self.fits_spectrum = FitsSpectrum(fits_file)
        self.fits_spectrum.spectrum.normalize_to_max()
        self.fits_file = fits_file
        self.ui = Ui_CalibrateSpectrum()
        self.ui.setupUi(self)
        self.toolbar = QToolBar('Calibration Toolbar')
        self.toolbar.setToolButtonStyle(Qt.ToolButtonTextBesideIcon)
        self.ui.x_axis_pick.setMenu(QMenu())
        self.ui.x_axis_pick.menu().addAction(
            "Maximum from range").triggered.connect(
                lambda: self.pick_from_range('maximum'))
        self.ui.x_axis_pick.menu().addAction(
            "Minimum from range").triggered.connect(
                lambda: self.pick_from_range('minimum'))
        self.ui.x_axis_pick.menu().addAction(
            "Central value from range").triggered.connect(
                lambda: self.pick_from_range('central'))
        self.ui.wavelength_pick.clicked.connect(
            lambda: self.lines_dialog.show())

        save_action = self.toolbar.addAction(QIcon(':/save_20'), 'Save',
                                             self.save_spectrum)
        self.spectrum_plot = QtCommons.nestWidget(self.ui.spectrum_plot_widget,
                                                  QMathPlotWidget())

        self.reference_spectra_dialog = ReferenceSpectraDialog(database)
        self.reference_spectra_dialog.setup_menu(self.toolbar,
                                                 self.spectrum_plot.axes,
                                                 settings)

        self.object_properties = ObjectProperties(self.fits_file,
                                                  project=project)
        self.object_properties_dialog = ObjectPropertiesDialog(
            settings, self.object_properties)
        self.toolbar.addAction("Object properties",
                               self.object_properties_dialog.show)

        self.calibration_model = QStandardItemModel()
        self.calibration_model.setHorizontalHeaderLabels(
            ["x-axis", "wavelength", "error"])
        self.ui.calibration_points.setModel(self.calibration_model)
        self.ui.calibration_points.selectionModel().selectionChanged.connect(
            lambda selected, deselected: self.ui.remove_calibration_point.
            setEnabled(len(selected.indexes()) > 0))
        self.ui.add_calibration_point.clicked.connect(
            self.add_calibration_point)
        self.ui.remove_calibration_point.setEnabled(False)
        self.ui.remove_calibration_point.clicked.connect(
            self.remove_calibration_point)
        if project and project.avg_dispersion():
            self.ui.set_dispersion.setMenu(QMenu())
            self.ui.set_dispersion.menu().addAction('From input value',
                                                    self.calculate_calibration)
            self.ui.set_dispersion.menu().addAction(
                'From Project',
                lambda: self.calculate_calibration(project.avg_dispersion()))
        else:
            self.ui.set_dispersion.clicked.connect(self.calculate_calibration)
        self.ui.point_is_star.toggled.connect(
            lambda checked: self.ui.wavelength_pick.setEnabled(not checked))
        self.ui.point_is_star.toggled.connect(
            lambda checked: self.ui.point_wavelength.setEnabled(not checked))
        self.fits_spectrum.plot_to(self.spectrum_plot.axes)

        self.toolbar.addSeparator()
        self.toolbar.addAction("Zoom", self.spectrum_plot.select_zoom)
        self.toolbar.addAction(
            "Reset Zoom", lambda: self.spectrum_plot.reset_zoom(
                self.fits_spectrum.spectrum.wavelengths,
                self.fits_spectrum.spectrum.fluxes.min(),
                self.fits_spectrum.spectrum.fluxes.max()))
        self.toolbar.addSeparator()

        self.lines_dialog = LinesDialog(database,
                                        settings,
                                        self.spectrum_plot,
                                        enable_picker=False,
                                        selection_mode='single')
        self.lines_dialog.lines.connect(self.picked_line)

        hdu_calibration_points = [
            h for h in self.fits_file
            if h.name == FitsSpectrum.CALIBRATION_DATA
        ]
        if len(hdu_calibration_points) > 0:
            for point in hdu_calibration_points[-1].data:
                self.add_calibration_point_data(point[0], point[1])
        self.calculate_calibration()

    def picked_from_range(self, type, min, max):
        min = (self.fits_spectrum.spectrum.wavelength_index(min))
        max = (self.fits_spectrum.spectrum.wavelength_index(max))
        add_line = lambda x: self.spectrum_plot.add_line(
            "x_axis_pick",
            self.fits_spectrum.spectrum.wavelengths[x],
            color='r')
        set_x_value = lambda x: self.ui.point_x_axis.setValue(x)

        if type != 'central':
            subplot = SelectPlottedPoints(self.fits_spectrum.spectrum.fluxes,
                                          min, max + 1, self.settings, type)
            subplot.point.connect(add_line)
            subplot.point.connect(set_x_value)
            subplot.show()
            return
        point = min + (max - min) / 2
        self.ui.point_x_axis.setValue(point)
        set_x_value(point)
        add_line(point)

    def pick_from_range(self, type):
        self.spectrum_plot.add_span_selector(
            'pick_x_axis',
            lambda min, max: self.picked_from_range(type, min, max),
            direction='horizontal')

    def remove_calibration_point(self):
        self.calibration_model.removeRow(
            self.ui.calibration_points.selectionModel().selectedIndexes()
            [0].row())
        self.calculate_calibration()

    def add_calibration_point_data(self, x_value, wavelength):
        x_axis_item = QStandardItem("star" if x_value ==
                                    0 else "{}".format(x_value))
        x_axis_item.setData(x_value)
        wavelength_item = QStandardItem("{:.2f}".format(wavelength))
        wavelength_item.setData(wavelength)
        self.calibration_model.appendRow(
            [x_axis_item, wavelength_item,
             QStandardItem("n/a")])
        self.spectrum_plot.rm_element('x_axis_pick')

    def picked_line(self, lines):
        self.ui.point_wavelength.setValue(lines[0]['lambda'])

    def add_calibration_point(self):
        self.add_calibration_point_data(
            self.ui.point_x_axis.value(),
            0 if self.ui.point_is_star.isChecked() else
            self.ui.point_wavelength.value())
        self.calculate_calibration()

    def calibration_points(self):
        return [{
            'row': row,
            'x': self.calibration_model.item(row, 0).data(),
            'wavelength': self.calibration_model.item(row, 1).data()
        } for row in range(self.calibration_model.rowCount())]

    def calculate_calibration(self, dispersion=None):
        points_number = self.calibration_model.rowCount()
        self.ui.set_dispersion.setEnabled(points_number == 1)
        self.ui.dispersion.setEnabled(points_number == 1)

        if points_number == 0:
            self.fits_spectrum.reset()
            self.lines_dialog.set_picker_enabled(False)
        else:
            self.lines_dialog.set_picker_enabled(True)
            points = sorted(self.calibration_points(),
                            key=lambda point: point['x'])
            self.fits_spectrum.calibrate(
                points,
                dispersion if dispersion else self.ui.dispersion.value())
            for row, value in [(p['row'], "{:.2f}".format(
                    p['wavelength'] -
                    self.fits_spectrum.spectrum.wavelengths[p['x']]))
                               for p in points]:
                self.calibration_model.item(row, 2).setText(value)

        self.ui.dispersion.setValue(self.fits_spectrum.spectrum.dispersion())
        self.fits_spectrum.plot_to(self.spectrum_plot.axes)

    def save_spectrum(self):
        if not self.project:
            save_file_sticky('Save plot...', 'FITS file (.fit)',
                             lambda f: self.save(f[0]), self.settings,
                             CALIBRATED_PROFILE, [RAW_PROFILE])
            return
        self.project.add_file(Project.CALIBRATED_PROFILE,
                              object_properties=self.object_properties,
                              on_added=self.save)

    def save(self, filename):
        self.fits_spectrum.save(filename, self.calibration_points())