def closeEvent(self, event):
poniFile = self.model().experimentSettingsModel().poniFile()
if not poniFile.isSynchronized():
button = qt.QMessageBox.question(
self, "calib2",
"The PONI file was not saved.\nDo you really want to close the application?",
qt.QMessageBox.Cancel | qt.QMessageBox.No | qt.QMessageBox.Yes,
qt.QMessageBox.Yes)
if button != qt.QMessageBox.Yes:
event.ignore()
return
event.accept()
CalibrationContext._releaseSingleton()
def pyFAI_calib2_main():
# It have to be done before loading Qt
# --help must also work without Qt
options = parse_options()
if options.debug:
logging.root.setLevel(logging.DEBUG)
# Then we can load Qt
if options.opengl:
silx.config.DEFAULT_PLOT_BACKEND = "opengl"
pyFAI.resources.silx_integration()
settings = qt.QSettings(qt.QSettings.IniFormat, qt.QSettings.UserScope,
"pyfai", "pyfai-calib2", None)
context = CalibrationContext(settings)
context.restoreSettings()
setup_model(context.getCalibrationModel(), options)
window = CalibrationWindowXdart(context)
window.setVisible(True)
window.setAttribute(qt.Qt.WA_DeleteOnClose, True)
context.saveSettings()
def main():
# It have to be done before loading Qt
# --help must also work without Qt
options = parse_options()
if options.debug:
logging.root.setLevel(logging.DEBUG)
# Then we can load Qt
import silx
from silx.gui import qt
if options.opengl:
silx.config.DEFAULT_PLOT_BACKEND = "opengl"
# Make sure matplotlib is loaded first by silx
import silx.gui.plot.matplotlib
from pyFAI.gui.CalibrationWindow import CalibrationWindow
from pyFAI.gui.CalibrationContext import CalibrationContext
sys.excepthook = logUncaughtExceptions
if options.qtargs is None:
qtArgs = []
else:
qtArgs = options.qtargs.split()
app = qt.QApplication(qtArgs)
pyFAI.resources.silx_integration()
settings = qt.QSettings(qt.QSettings.IniFormat, qt.QSettings.UserScope,
"pyfai", "pyfai-calib2", None)
context = CalibrationContext(settings)
context.restoreSettings()
setup_model(context.getCalibrationModel(), options)
window = CalibrationWindow(context)
window.setVisible(True)
window.setAttribute(qt.Qt.WA_DeleteOnClose, True)
result = app.exec_()
context.saveSettings()
# remove ending warnings relative to QTimer
app.deleteLater()
return result
def initPeaksFromControlPoints(peakSelectionModel, controlPoints, context=None):
"""Initialize peak selection model using control points object
:rtype: pyFAI.control_points.ControlPoints
"""
if not isinstance(peakSelectionModel, PeakSelectionModel):
raise TypeError("Unexpected model type")
if not isinstance(controlPoints, ControlPoints):
raise TypeError("Unexpected model type")
if context is None:
context = CalibrationContext.instance()
peakSelectionModel.clear()
for label in controlPoints.get_labels():
group = controlPoints.get(lbl=label)
peakModel = createRing(group.points, peakSelectionModel=peakSelectionModel, context=context)
peakModel.setRingNumber(group.ring + 1)
peakModel.setName(label)
peakSelectionModel.append(peakModel)
def createRing(points, peakSelectionModel, ringNumber=None, context=None):
"""Create a new ring from a group of points
:rtype: PeakModel
"""
if context is None:
context = CalibrationContext.instance()
name = _findUnusedName(peakSelectionModel)
if ringNumber is None:
ringNumber = 1
color = context.getMarkerColor(ringNumber - 1)
peakModel = PeakModel(peakSelectionModel)
peakModel.setName(name)
peakModel.setColor(color)
peakModel.setCoords(points)
peakModel.setRingNumber(ringNumber)
return peakModel
def main():
# It have to be done before loading Qt
# --help must also work without Qt
options = parse_options()
if options.debug:
logging.root.setLevel(logging.DEBUG)
# Then we can load Qt
import silx
from silx.gui import qt
if options.opengl:
silx.config.DEFAULT_PLOT_BACKEND = "opengl"
# Make sure matplotlib is loaded first by silx
import silx.gui.plot.matplotlib
from pyFAI.gui.CalibrationWindow import CalibrationWindow
from pyFAI.gui.CalibrationContext import CalibrationContext
sys.excepthook = logUncaughtExceptions
if options.qtargs is None:
qtArgs = []
else:
qtArgs = options.qtargs.split()
app = qt.QApplication(qtArgs)
pyFAI.resources.silx_integration()
settings = qt.QSettings(qt.QSettings.IniFormat,
qt.QSettings.UserScope,
"pyfai",
"pyfai-calib2",
None)
context = CalibrationContext(settings)
context.restoreSettings()
setup_model(context.getCalibrationModel(), options)
window = CalibrationWindow(context)
window.setVisible(True)
window.setAttribute(qt.Qt.WA_DeleteOnClose, True)
result = app.exec_()
context.saveSettings()
# remove ending warnings relative to QTimer
app.deleteLater()
return result
def createRing(points, peakSelectionModel, context=None):
"""Create a new ring from a group of points"""
if context is None:
context = CalibrationContext.instance()
# reach the bigger name
names = ["% 8s" % p.name() for p in peakSelectionModel]
if len(names) > 0:
names = list(sorted(names))
bigger = names[-1].strip()
number = 0
for c in bigger:
number = number * 26 + (ord(c) - ord('a'))
else:
number = -1
number = number + 1
# compute the next one
name = ""
if number == 0:
name = "a"
else:
n = number
while n > 0:
c = n % 26
n = n // 26
name = chr(c + ord('a')) + name
color = context.getMarkerColor(number)
# TODO: color and name should be removed from the model
# TODO: As result this function should be removed
peakModel = PeakModel(peakSelectionModel)
peakModel.setName(name)
peakModel.setColor(color)
peakModel.setCoords(points)
peakModel.setRingNumber(1)
return peakModel
def createRing(points, peakSelectionModel, context=None):
"""Create a new ring from a group of points"""
if context is None:
context = CalibrationContext.instance()
# reach the bigger name
names = ["% 8s" % p.name() for p in peakSelectionModel]
if len(names) > 0:
names = list(sorted(names))
bigger = names[-1].strip()
number = 0
for c in bigger:
number = number * 26 + (ord(c) - ord('a'))
else:
number = -1
number = number + 1
# compute the next one
name = ""
if number == 0:
name = "a"
else:
n = number
while n > 0:
c = n % 26
n = n // 26
name = chr(c + ord('a')) + name
color = context.getMarkerColor(number)
# TODO: color and name should be removed from the model
# TODO: As result this function should be removed
peakModel = PeakModel(peakSelectionModel)
peakModel.setName(name)
peakModel.setColor(color)
peakModel.setCoords(points)
peakModel.setRingNumber(1)
return peakModel
def initPeaksFromControlPoints(peakSelectionModel, controlPoints, context=None):
"""Initialize peak selection model using control points object
:rtype: pyFAI.control_points.ControlPoints
"""
if not isinstance(peakSelectionModel, PeakSelectionModel):
raise TypeError("Unexpected model type")
if not isinstance(controlPoints, ControlPoints):
raise TypeError("Unexpected model type")
if context is None:
context = CalibrationContext.instance()
peakSelectionModel.clear()
for label in controlPoints.get_labels():
group = controlPoints.get(lbl=label)
color = context.getMarkerColor(group.ring)
points = numpy.array(group.points)
peakModel = createRing(points, peakSelectionModel=peakSelectionModel, context=context)
peakModel.setRingNumber(group.ring + 1)
peakModel.setColor(color)
peakModel.setName(label)
peakSelectionModel.append(peakModel)
def create_context(self):
settings = qt.QSettings()
context = CalibrationContext(settings)
return context
def setUp(self):
# FIXME: It would be good to remove this singleton
CalibrationContext._releaseSingleton()
super(TestCalibration, self).setUp()
def main():
# It have to be done before loading Qt
# --help must also work without Qt
options = parse_options()
if options.debug:
logging.root.setLevel(logging.DEBUG)
# Then we can load Qt
import silx
from silx.gui import qt
if options.opengl:
silx.config.DEFAULT_PLOT_BACKEND = "opengl"
# Make sure matplotlib is loaded first by silx
import silx.gui.plot.matplotlib
from pyFAI.gui.CalibrationWindow import CalibrationWindow
from pyFAI.gui.CalibrationContext import CalibrationContext
sys.excepthook = logUncaughtExceptions
if options.qtargs is None:
qtArgs = []
else:
qtArgs = options.qtargs.split()
app = qt.QApplication(qtArgs)
pyFAI.resources.silx_integration()
settings = qt.QSettings(
qt.QSettings.IniFormat, qt.QSettings.UserScope, "pyfai", "pyfai-calib2", None
)
context = CalibrationContext(settings)
context.restoreSettings()
setup_model(context.getCalibrationModel(), options)
window = CalibrationWindow(context)
# Begin modifications for bluesky_widgets
from qtpy.QtWidgets import QDialog
from bluesky_widgets.components.search.searches import Search
from bluesky_widgets.qt.searches import QtSearch
from bluesky_widgets.examples.utils.generate_msgpack_data import get_catalog
from bluesky_widgets.examples.utils.add_search_mixin import columns
from qtpy.QtWidgets import QAction, QHBoxLayout, QPushButton, QVBoxLayout, QWidget
example_catalog = get_catalog()
class SearchDialog(QDialog):
"""
Combine the QtSearches widget with a button that processes selected Runs.
"""
def __init__(self, model, *args, **kwargs):
super().__init__(*args, **kwargs)
layout = QVBoxLayout()
self.setLayout(layout)
self.setModal(True)
layout.addWidget(QtSearch(model))
accept = QPushButton("Open")
reject = QPushButton("Cancel")
# We'll just slip this into an existing widget --- not great form, but
# this is just a silly example.
accept.clicked.connect(self.accept)
reject.clicked.connect(self.reject)
buttons_widget = QWidget()
buttons_layout = QHBoxLayout()
buttons_widget.setLayout(buttons_layout)
buttons_layout.addWidget(accept)
buttons_layout.addWidget(reject)
layout.addWidget(buttons_widget)
def launch_dialog():
model = Search(example_catalog, columns=columns)
dialog = SearchDialog(model)
def open_catalog():
catalog = model.selection_as_catalog
# TODO Extract the data from this.
print(f"Open {len(catalog)} runs")
dialog.accepted.connect(open_catalog)
dialog.exec()
menu = window.menuBar().addMenu("&Data Broker")
launch_dialog_action = QAction("&Search")
menu.addAction(launch_dialog_action)
launch_dialog_action.triggered.connect(launch_dialog)
# End modifications for bluesky_widgets
window.setVisible(True)
window.setAttribute(qt.Qt.WA_DeleteOnClose, True)
result = app.exec_()
context.saveSettings()
# remove ending warnings relative to QTimer
app.deleteLater()
return result