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|
# coding: utf-8
# /*##########################################################################
#
# Copyright (C) 2016-2018 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# ###########################################################################*/
__authors__ = ["V. Valls"]
__license__ = "MIT"
__date__ = "08/01/2021"
import numpy
import logging
import silx.gui.plot
from silx.gui import qt
from silx.gui import icons
import pyFAI.utils
from pyFAI.calibrant import Calibrant
from .AbstractCalibrationTask import AbstractCalibrationTask
import pyFAI.detectors
from ..dialog.DetectorSelectorDialog import DetectorSelectorDialog
from ..helper.SynchronizeRawView import SynchronizeRawView
from ..CalibrationContext import CalibrationContext
from ..utils import units
from ..utils import validators
from ..utils import FilterBuilder
from ..helper.SynchronizePlotBackground import SynchronizePlotBackground
_logger = logging.getLogger(__name__)
class ExperimentTask(AbstractCalibrationTask):
def _initGui(self):
qt.loadUi(pyFAI.utils.get_ui_file("calibration-experiment.ui"), self)
icon = icons.getQIcon("pyfai:gui/icons/task-settings")
self.setWindowIcon(icon)
self.initNextStep()
self._detectorLabel.setAcceptDrops(True)
self._image.setAcceptDrops(True)
self._mask.setAcceptDrops(True)
self._imageLoader.setDialogTitle("Load calibration image")
self._maskLoader.setDialogTitle("Load mask image")
self._customDetector.clicked.connect(self.__customDetector)
self.__plot = self.__createPlot(parent=self._imageHolder)
self.__plot.setObjectName("plot-experiment")
self.__plotBackground = SynchronizePlotBackground(self.__plot)
layout = qt.QVBoxLayout(self._imageHolder)
layout.addWidget(self.__plot)
layout.setContentsMargins(1, 1, 1, 1)
self._imageHolder.setLayout(layout)
self._detectorFileDescription.setElideMode(qt.Qt.ElideMiddle)
self._calibrant.setFileLoadable(True)
self._calibrant.sigLoadFileRequested.connect(self.loadCalibrant)
self.__synchronizeRawView = SynchronizeRawView()
self.__synchronizeRawView.registerTask(self)
self.__synchronizeRawView.registerPlot(self.__plot)
validator = validators.AdvancedDoubleValidator(self)
validator.setBottom(0)
validator.setIncludedBound(False, True)
validator.setAllowEmpty(True)
self._energy.setValidator(validator)
self._wavelength.setValidator(validator)
def __createPlot(self, parent):
plot = silx.gui.plot.PlotWidget(parent=parent)
plot.setKeepDataAspectRatio(True)
plot.setDataMargins(0.1, 0.1, 0.1, 0.1)
plot.setGraphXLabel("X")
plot.setGraphYLabel("Y")
colormap = CalibrationContext.instance().getRawColormap()
plot.setDefaultColormap(colormap)
from silx.gui.plot import tools
toolBar = tools.InteractiveModeToolBar(parent=self, plot=plot)
plot.addToolBar(toolBar)
toolBar = tools.ImageToolBar(parent=self, plot=plot)
colormapDialog = CalibrationContext.instance().getColormapDialog()
toolBar.getColormapAction().setColorDialog(colormapDialog)
plot.addToolBar(toolBar)
toolBar = qt.QToolBar(self)
plot3dAction = qt.QAction(self)
plot3dAction.setIcon(icons.getQIcon("pyfai:gui/icons/3d"))
plot3dAction.setText("3D visualization")
plot3dAction.setToolTip("Display a 3D visualization of the detector")
plot3dAction.triggered.connect(self.__display3dDialog)
toolBar.addAction(plot3dAction)
plot.addToolBar(toolBar)
return plot
def __display3dDialog(self):
from ..dialog.Detector3dDialog import Detector3dDialog
dialog = Detector3dDialog(self)
settings = self.model().experimentSettingsModel()
detector = settings.detectorModel().detector()
image = settings.image().value()
mask = settings.mask().value()
colormap = CalibrationContext.instance().getRawColormap()
dialog.setData(detector=detector,
image=image, mask=mask, colormap=colormap,
geometry=None)
dialog.exec_()
def _updateModel(self, model):
self.__synchronizeRawView.registerModel(model.rawPlotView())
settings = model.experimentSettingsModel()
self._calibrant.setModel(settings.calibrantModel())
self._detectorLabel.setDetectorModel(settings.detectorModel())
self._image.setModel(settings.image())
self._imageLoader.setModel(settings.image())
self._mask.setModel(settings.mask())
self._maskLoader.setModel(settings.mask())
self._wavelength.setModelUnit(units.Unit.METER_WL)
self._wavelength.setDisplayedUnit(units.Unit.ANGSTROM)
self._energy.setModelUnit(units.Unit.METER_WL)
self._energy.setDisplayedUnit(units.Unit.ENERGY)
self._wavelength.setModel(settings.wavelength())
self._energy.setModel(settings.wavelength())
settings.image().changed.connect(self.__imageUpdated)
settings.calibrantModel().changed.connect(self.__calibrantChanged)
settings.detectorModel().changed.connect(self.__detectorModelUpdated)
settings.wavelength().changed.connect(self.__waveLengthChanged)
settings.changed.connect(self.__settingsChanged)
self.__imageUpdated()
self.__waveLengthChanged()
self.__calibrantChanged()
self.__detectorModelUpdated()
self.__settingsChanged()
def __settingsChanged(self):
settings = self.model().experimentSettingsModel()
settings.detectorModel().changed.connect(self.__detectorModelUpdated)
image = settings.image().value()
detectorModel = settings.detectorModel().detector()
calibrantModel = settings.calibrantModel().calibrant()
wavelength = settings.wavelength().value()
warnings = []
if image is None:
warnings.append("An image have to be specified")
if detectorModel is None:
warnings.append("A detector have to be specified")
if calibrantModel is None:
warnings.append("A calibrant have to be specified")
if wavelength is None:
warnings.append("An energy have to be specified")
if image is not None and calibrantModel is not None:
try:
detector = settings.detector()
binning = detector.guess_binning(image)
if not binning:
raise Exception("inconsistancy")
except Exception:
warnings.append("Inconsistancy between sizes of image and detector")
self._globalWarnings = warnings
self.updateNextStepStatus()
def nextStepWarning(self):
if len(self._globalWarnings) == 0:
return None
else:
warning = ""
for w in self._globalWarnings:
warning += "<li>%s</li>" % w
warning = "<ul>%s</ul>" % warning
warning = "<html>%s</html>" % warning
return warning
def __customDetector(self):
settings = self.model().experimentSettingsModel()
detector = settings.detectorModel().detector()
dialog = DetectorSelectorDialog(self)
dialog.selectDetector(detector)
result = dialog.exec_()
if result:
newDetector = dialog.selectedDetector()
settings.detectorModel().setDetector(newDetector)
def __waveLengthChanged(self):
settings = self.model().experimentSettingsModel()
self._calibrantPreview.setWaveLength(settings.wavelength().value())
def __calibrantChanged(self):
settings = self.model().experimentSettingsModel()
self._calibrantPreview.setCalibrant(settings.calibrantModel().calibrant())
def __detectorModelUpdated(self):
detector = self.model().experimentSettingsModel().detectorModel().detector()
self._detectorSizeUnit.setVisible(detector is not None)
if detector is None:
self._detectorLabel.setStyleSheet("QLabel { color: red }")
self._detectorSize.setText("")
self._detectorPixelSize.setText("")
self._detectorFileDescription.setVisible(False)
self._detectorFileDescriptionTitle.setVisible(False)
else:
self._detectorLabel.setStyleSheet("QLabel { }")
text = [str(s) for s in detector.max_shape]
text = u" × ".join(text)
self._detectorSize.setText(text)
try:
text = ["%0.1f" % (s * 10 ** 6) for s in [detector.pixel1, detector.pixel2]]
text = u" × ".join(text)
except Exception as e:
# Is heterogeneous detectors have pixel size?
_logger.debug(e, exc_info=True)
text = "N.A."
self._detectorPixelSize.setText(text)
if detector.HAVE_TAPER or detector.__class__ == pyFAI.detectors.Detector:
fileDescription = detector.get_splineFile()
elif isinstance(detector, pyFAI.detectors.NexusDetector):
fileDescription = detector.filename
else:
fileDescription = None
if fileDescription is not None:
fileDescription = fileDescription.strip()
if fileDescription == "":
fileDescription = None
self._detectorFileDescription.setVisible(fileDescription is not None)
self._detectorFileDescriptionTitle.setVisible(fileDescription is not None)
self._detectorFileDescription.setText(fileDescription if fileDescription else "")
self.__updateDetector()
def __displayError(self, label, message=""):
self._error.setVisible(True)
self._binning.setVisible(False)
self._binningLabel.setVisible(False)
# self._nextStep.setEnabled(False)
self._error.setText(label)
self._error.setToolTip(message)
def __updateDetectorTemplate(self):
try:
detector = self.model().experimentSettingsModel().detector()
except Exception:
detector = self.model().experimentSettingsModel().detectorModel().detector()
if detector is None:
self._detectorSize.setText("")
self._detectorPixelSize.setText("")
self.__plot.removeMarker("xmin")
self.__plot.removeMarker("xmax")
self.__plot.removeMarker("ymin")
self.__plot.removeMarker("ymax")
else:
try:
binning = detector.get_binning()
except Exception:
binning = 1, 1
# clamping
if binning[0] == 0:
binning = 1, binning[1]
if binning[1] == 0:
binning = binning[0], 1
shape = detector.max_shape[1] // binning[1], detector.max_shape[0] // binning[0]
self.__plot.addXMarker(x=0, legend="xmin", color="grey")
self.__plot.addXMarker(x=shape[0], legend="xmax", color="grey")
self.__plot.addYMarker(y=0, legend="ymin", color="grey")
self.__plot.addYMarker(y=shape[1], legend="ymax", color="grey")
dummy = numpy.array([[[0xF0, 0xF0, 0xF0]]], dtype=numpy.uint8)
self.__plot.addImage(data=dummy, scale=shape, legend="dummy", z=-10, replace=False)
self.__plot.resetZoom()
def __updateDetector(self):
image = self.model().experimentSettingsModel().image().value()
if image is None:
self.__displayError("No image")
self.__updateDetectorTemplate()
return
try:
detector = self.model().experimentSettingsModel().detector()
if detector is None:
self._error.setVisible(False)
self.__updateDetectorTemplate()
return
binning = detector.get_binning()
except Exception as e:
_logger.error(e.args[0])
_logger.debug("Backtrace", exc_info=True)
self.__displayError("Sizes not valid", "Inconsistency between image and detector")
self.__updateDetectorTemplate()
return
self._detectorSizeUnit.setVisible(detector is not None)
self.__updateDetectorTemplate()
if detector.guess_binning(image):
text = [str(s) for s in binning]
text = u" × ".join(text)
self._binning.setText(text)
self._binning.setVisible(True)
self._binningLabel.setVisible(True)
self._error.setVisible(False)
else:
self.__displayError("Sizes not valid", "Inconsistency between image and detector")
def __imageUpdated(self):
image = self.model().experimentSettingsModel().image().value()
self._imageSize.setVisible(image is not None)
self._imageSizeLabel.setVisible(image is not None)
self._imageSizeUnit.setVisible(image is not None)
if image is not None:
self.__plot.addImage(image, legend="image", z=-1, replace=False, copy=False)
text = [str(s) for s in image.shape]
text = u" × ".join(text)
self._imageSize.setText(text)
else:
self.__plot.removeImage("image")
self._imageSize.setText("")
self.__plot.resetZoom()
self.__updateDetector()
def createImageDialog(self, title, forMask=False, previousFile=None):
dialog = CalibrationContext.instance().createFileDialog(self, previousFile=previousFile)
dialog.setWindowTitle(title)
dialog.setModal(True)
builder = FilterBuilder.FilterBuilder()
builder.addImageFormat("EDF image files", "edf")
builder.addImageFormat("TIFF image files", "tif tiff")
builder.addImageFormat("NumPy binary files", "npy")
builder.addImageFormat("CBF files", "cbf")
builder.addImageFormat("MarCCD image files", "mccd")
if forMask:
builder.addImageFormat("Fit2D mask files", "msk")
dialog.setNameFilters(builder.getFilters())
dialog.setFileMode(qt.QFileDialog.ExistingFile)
return dialog
def createCalibrantDialog(self, title):
dialog = CalibrationContext.instance().createFileDialog(self)
dialog.setWindowTitle(title)
dialog.setModal(True)
builder = FilterBuilder.FilterBuilder()
builder.addFileFormat("Calibrant files", "D d DS ds")
dialog.setNameFilters(builder.getFilters())
dialog.setFileMode(qt.QFileDialog.ExistingFile)
return dialog
def loadCalibrant(self):
dialog = self.createCalibrantDialog("Load calibrant file")
result = dialog.exec_()
if not result:
return
filename = dialog.selectedFiles()[0]
try:
calibrant = Calibrant(filename=filename)
except Exception as e:
_logger.error(e.args[0])
_logger.debug("Backtrace", exc_info=True)
# FIXME Display error dialog
return
except KeyboardInterrupt:
raise
try:
settings = self.model().experimentSettingsModel()
settings.calibrantModel().setCalibrant(calibrant)
except Exception as e:
_logger.error(e.args[0])
_logger.debug("Backtrace", exc_info=True)
# FIXME Display error dialog
except KeyboardInterrupt:
raise
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