def load_spectrum(self): """initializes a wraith spectrum""" self.spectrum = spectra_fitting.Spectrum() xdata = analysis.xdata_calc(self.cube_data, self.cube_dataview) ydata = analysis.ydata_calc(self.cube_data, self.cube_dataview) self.spectrum.EE = xdata self.spectrum.data = ydata
def initialize_vbox(self, label_min, label_max, edit_min, edit_max): label_min.setText('Min') label_max.setText('Max') xdata = analysis.xdata_calc(self.data, self.dataview) edit_min.setText(str(xdata[0])) edit_max.setText(str(xdata[-1])) self.update_visualization_settings()
def __init__(self, data, data_view, spectrum_holder, parent=None): super(Form, self).__init__(parent) self.filename = data.filename self.xdata = module_copy.copy(analysis.xdata_calc(data, data_view)) self.xdata = np.float64(self.xdata) self.data = data self.ydata = module_copy.copy(analysis.ydata_calc(data, data_view)) self.x = module_copy.copy(data_view.x) self.y = module_copy.copy(data_view.y) self.spectrum_holder = spectrum_holder self.spectrum_viewer = spectrum_viewer.SpectrumViewer(spectrum_holder) self.display_ev = copy(data_view.display_ev) self.setWindowTitle('Interactive XPS Explorer') self.ignore_signals = False self.files = {} #self.data = DataHolder() self.series_list_model = QStandardItemModel() self.series_list_root = self.series_list_model.invisibleRootItem() self.series_list_model.itemChanged.connect(self.update_file_checks) #self.create_menu() self.create_main_frame() self.create_status_bar() self.load_file() self.update_file_checks(self.series_list_model.item(0)) self.threadPool = [] self.update_ui() self.on_show()
def initialize_vbox(self,label_min, label_max, edit_min, edit_max): label_min.setText('Min') label_max.setText('Max') xdata = analysis.xdata_calc(self.data, self.dataview) edit_min.setText(str(xdata[0])) edit_max.setText(str(xdata[-1])) self.update_visualization_settings()
def update_control(self): xdata = analysis.xdata_calc(self.data, self.dataview) slice1 = self.dataview.slider_val if self.dataview.display_ev: self.ui.imageslice.setText('%0.2f' % float(xdata[slice1])) else: self.ui.imageslice.setText('%0.0f ' % float(xdata[slice1])) self.ui.graphslicex.setText('%d' % self.dataview.x) self.ui.graphslicey.setText('%d' % self.dataview.y)
def update_control(self): xdata = analysis.xdata_calc(self.data, self.dataview) slice1 = self.dataview.slider_val if self.dataview.display_ev: self.ui.imageslice.setText('%0.2f'%float(xdata[slice1])) else: self.ui.imageslice.setText('%0.0f '%float(xdata[slice1])) self.ui.graphslicex.setText('%d'%self.dataview.x) self.ui.graphslicey.setText('%d'%self.dataview.y)
def export_spectrum(filename, data, data_view): """ export the current spectrum to an excel file in the original file's folder """ location = 'x' + str(data_view.x) + 'y' + str(data_view.y) no_ext_filename, ext = os.path.splitext(filename) out_filename = no_ext_filename + location + '.csv' xdata = analysis.xdata_calc(data, data_view) ydata = analysis.ydata_calc(data, data_view) out = np.c_[xdata, ydata] np.savetxt(str(out_filename), out, delimiter=",", fmt="%10.5f")
def export_spectrum(filename, data, data_view): """ export the current spectrum to an excel file in the original file's folder """ location = 'x' + str(data_view.x) + 'y' + str(data_view.y) no_ext_filename, ext = os.path.splitext(filename) out_filename = no_ext_filename + location + '.csv' xdata = analysis.xdata_calc(data,data_view) ydata = analysis.ydata_calc(data,data_view) out = np.c_[xdata,ydata] np.savetxt(str(out_filename), out, delimiter=",", fmt="%10.5f")
def change_display(axes, data, dataview): """ changes the view between ev and wavelength for ev and wavelength data """ axes.cla() xdata = analysis.xdata_calc(data, dataview) ydata = analysis.ydata_calc(data, dataview) img2, = axes.plot(xdata, ydata, ".") if dataview.display_ev: axes.set_xlabel("ev") else: axes.set_xlabel("$\lambda$ [nm]") return img2
def change_display(axes, data, dataview): """ changes the view between ev and wavelength for ev and wavelength data """ axes.cla() xdata = analysis.xdata_calc(data, dataview) ydata = analysis.ydata_calc(data, dataview) img2, = axes.plot(xdata, ydata, '.') if dataview.display_ev: axes.set_xlabel('ev') else: axes.set_xlabel('$\lambda$ [nm]') return img2
def initialize_image(axes, data, dataview): "Initializes the image from the datacube" yimage = analysis.yimage_calc(data, dataview) maxval = analysis.maxval_calc(data, dataview) img = axes.imshow(yimage, interpolation="nearest", clim=(0, maxval), cmap="spectral") xdata = analysis.xdata_calc(data, dataview) slice1 = dataview.slider_val if dataview.display_ev: axes.set_title("Current Slice ev:%0.2f" % float(xdata[slice1])) else: axes.set_title("Current Slice Wavelength:%0.2f" % float(xdata[slice1])) plt.yticks([]) plt.xticks([]) return img
def initialize_graph(axes, data, dataview): """ initializes the graph on screen xs and ys start from 0 """ axes.cla() xdata = analysis.xdata_calc(data, dataview) ydata = analysis.ydata_calc(data, dataview) maxval = analysis.maxval_calc(data, dataview) axes.set_ylim((-maxval / 10, maxval)) img2, = axes.plot(xdata, ydata, ".") if dataview.display_ev: plt.xlabel("ev") else: plt.xlabel("$\lambda$ [nm]") return img2
def initialize_graph(axes, data, dataview): """ initializes the graph on screen xs and ys start from 0 """ axes.cla() xdata = analysis.xdata_calc(data, dataview) ydata = analysis.ydata_calc(data, dataview) maxval = analysis.maxval_calc(data, dataview) axes.set_ylim((-maxval / 10, maxval)) img2, = axes.plot(xdata, ydata, '.') if dataview.display_ev: plt.xlabel('ev') else: plt.xlabel('$\lambda$ [nm]') return img2
def plot_image(img, axes, data, dataview): """updates the image on screen with a new cube slice from slider""" yimage = analysis.yimage_calc(data, dataview) img.set_array(yimage) max_color, min_color = analysis.colors_calc(data, dataview) if dataview.auto_color: img.autoscale() vmin, vmax = img.get_clim() dataview.mincolor = vmin dataview.maxcolor = vmax else: img.set_clim(vmax=max_color, vmin=min_color) xdata = analysis.xdata_calc(data, dataview) slice1 = dataview.slider_val if dataview.display_ev: axes.set_title("Current Slice ev:%0.2f" % float(xdata[slice1])) else: axes.set_title("Current Slice Wavelength:%0.0f " % float(xdata[slice1])) img.figure.canvas.draw()
def plot_image(img, axes, data, dataview): """updates the image on screen with a new cube slice from slider""" yimage = analysis.yimage_calc(data, dataview) img.set_array(yimage) max_color, min_color = analysis.colors_calc(data, dataview) if dataview.auto_color: img.autoscale() vmin, vmax = img.get_clim() dataview.mincolor = vmin dataview.maxcolor = vmax else: img.set_clim(vmax=max_color, vmin=min_color) xdata = analysis.xdata_calc(data, dataview) slice1 = dataview.slider_val if dataview.display_ev: axes.set_title('Current Slice ev:%0.2f' % float(xdata[slice1])) else: axes.set_title('Current Slice Wavelength:%0.0f ' % float(xdata[slice1])) img.figure.canvas.draw()
def initialize_image(axes, data, dataview): 'Initializes the image from the datacube' yimage = analysis.yimage_calc(data, dataview) maxval = analysis.maxval_calc(data, dataview) img = axes.imshow(yimage, interpolation='nearest', clim=(0, maxval), cmap='spectral') xdata = analysis.xdata_calc(data, dataview) slice1 = dataview.slider_val if dataview.display_ev: axes.set_title('Current Slice ev:%0.2f' % float(xdata[slice1])) else: axes.set_title('Current Slice Wavelength:%0.2f' % float(xdata[slice1])) plt.yticks([]) plt.xticks([]) return img
def graph_pyqt(curve1, curve2, data, dataview): xdata = analysis.xdata_calc(data, dataview) ydata = analysis.ydata_calc(data, dataview) curve1.setData(xdata, ydata, pen="w") curve2.setData(xdata, ydata, pen="w")