def __init__(self, model, *args, **kwargs):
super().__init__(*args, **kwargs)
self.model = model
layout = QHBoxLayout()
self.setLayout(layout)
layout.addWidget(QtSearchListWithButton(model.searches))
layout.addWidget(QtFigures(model.viewer.figures))
def __init__(self, model, *args, **kwargs):
super().__init__(*args, **kwargs)
self.model = model
layout = QHBoxLayout()
self.setLayout(layout)
layout.addWidget(QtSearchWithButton(model.search))
plot_layout = QVBoxLayout()
plot_layout.addWidget(QtAddCustomPlot(self.model))
plot_layout.addWidget(QtFigures(model.auto_plot_builder.figures))
layout.addLayout(plot_layout)
def __init__(self, model, *args, **kwargs):
super().__init__(*args, **kwargs)
self.model = model
layout = QHBoxLayout()
self.setLayout(layout)
layout.addWidget(QtSearchWithButton(model.search))
plot_layout = QVBoxLayout()
plot_layout.addWidget(QtAddCustomPlot(self.model))
# How would this work with a list of auto plot builders?
for auto_plot_builder in self.model.auto_plot_builders:
plot_layout.addWidget(QtFigures(auto_plot_builder.figures))
layout.addLayout(plot_layout)
def __init__(self, parent):
BaseWidget.__init__(self, parent)
#self.searches = SearchListWithButton()
#QtSearchListWithButton.__init__(self, self.searches)
QtFigures.__init__(self, FigureSpecList(), parent=parent)
"""
Use within IPython like
ipython --gui=qt
In [1]: %run -m bluesky_widgets.examples.ipy_qt_images
"""
from bluesky_widgets.examples.utils.generate_msgpack_data import get_catalog
from bluesky_widgets.models.auto_plot_builders import AutoImages
from bluesky_widgets.qt.figures import QtFigures
catalog = get_catalog()
counts = catalog.search({"plan_name": "count"})
run = counts[-1]
model = AutoImages()
model.add_run(run)
view = QtFigures(model.figures)
view.show()
def main():
# First, some boilerplate to make a super-minimal Qt application that we want
# to add some bluesky-widgets components into.
app = QApplication(["Some App"])
window = QMainWindow()
central_widget = QWidget(window)
window.setCentralWidget(central_widget)
central_widget.setLayout(QVBoxLayout())
central_widget.layout().addWidget(QLabel("This is part of the 'original' app."))
window.show()
# *** INTEGRATION WITH BLUESKY-WIDGETS STARTS HERE. ***
# Ensure that any background workers started by bluesky-widgets stop
# gracefully when the application closes.
from bluesky_widgets.qt.threading import wait_for_workers_to_quit
app.aboutToQuit.connect(wait_for_workers_to_quit)
# Model a list of figures.
# This will generate line plot automatically based on the structure (shape)
# of the data and its hints. Other models could be used for more explicit
# control of what gets plotted. See the examples in
# http://blueskyproject.io/bluesky-widgets/reference.html#plot-builders
from bluesky_widgets.models.auto_plot_builders import AutoLines
model = AutoLines(max_runs=3)
# Feed it data from the RunEngine. In actual practice, the RunEngine should
# be in a separate process and we should be receiving these documents
# over a network via publish--subscribe. See
# bluesky_widgets.examples.advanced.qt_viewer_with_search for an example of
# that. Here, we keep it simple.
from bluesky_widgets.utils.streaming import stream_documents_into_runs
from bluesky import RunEngine
RE = RunEngine()
RE.subscribe(stream_documents_into_runs(model.add_run))
# Add a tabbed pane of figures to the app.
from bluesky_widgets.qt.figures import QtFigures
view = QtFigures(model.figures) # view is a QWidget
central_widget.layout().addWidget(view)
# When the model receives data or is otherwise updated, any changes to
# model.figures will be reflected in changes to the view.
# Just for this example, generate some data before starting this app.
# Again, in practice, this should happen in a separate process and send
# the results over a network.
from bluesky.plans import scan
from ophyd.sim import motor, det
def plan():
for i in range(1, 5):
yield from scan([det], motor, -1, 1, 1 + 2 * i)
RE(plan())
# *** INTEGRATION WITH BLUESKY-WIDGETS ENDS HERE. ***
# Run the app.
app.exec_()
def start_dichro_plot(monitor='Ion Ch 4', detector='Ion Ch 5', fluo=True):
model = AutoDichroPlot(monitor=monitor, detector=detector, fluo=fluo)
view = QtFigures(model.figures)
view.show()
RE.subscribe(stream_documents_into_runs(model.add_run))
return model, view