def __init__(self,
data=None,
figure=None,
axes=None,
layer_artist_container=None):
"""
Create a new ScatterClient object
:param data: :class:`~glue.core.data.DataCollection` to use
:param figure:
Which matplotlib figure instance to draw to. One will be created if
not provided
:param axes:
Which matplotlib axes instance to use. Will be created if necessary
"""
Client.__init__(self, data=data)
figure, axes = init_mpl(figure, axes)
self.artists = layer_artist_container
if self.artists is None:
self.artists = LayerArtistContainer()
self._layer_updated = False # debugging
self._xset = False
self._yset = False
self.axes = axes
self._connect()
self._set_limits()
def __init__(self, data=None, figure=None, axes=None,
layer_artist_container=None):
"""
Create a new ScatterClient object
:param data: :class:`~glue.core.data.DataCollection` to use
:param figure:
Which matplotlib figure instance to draw to. One will be created if
not provided
:param axes:
Which matplotlib axes instance to use. Will be created if necessary
"""
Client.__init__(self, data=data)
figure, axes = init_mpl(figure, axes)
self.artists = layer_artist_container
if self.artists is None:
self.artists = LayerArtistContainer()
self._layer_updated = False # debugging
self._xset = False
self._yset = False
self.axes = axes
self._connect()
self._set_limits()
def __init__(self, data, figure, layer_artist_container=None):
super(HistogramClient, self).__init__(data)
self._artists = layer_artist_container or LayerArtistContainer()
self._figure, self._axes = init_mpl(figure=figure, axes=None)
self._component = None
self._saved_nbins = None
self._xlim_cache = {}
self._xlog_cache = {}
self._sync_enabled = True
self._xlog_curr = False
def __init__(self, data, figure, layer_artist_container=None):
super(HistogramClient, self).__init__(data)
self._artists = layer_artist_container or LayerArtistContainer()
self._figure, self._axes = init_mpl(figure=figure, axes=None)
self._component = None
self._saved_nbins = None
self._xlim_cache = {}
self._xlog_cache = {}
self._sync_enabled = True
self._xlog_curr = False
def __init__(self, session, parent=None, wcs=None, state=None):
super(MatplotlibDataViewer, self).__init__(session, parent, state=state)
# Use MplWidget to set up a Matplotlib canvas inside the Qt window
self.mpl_widget = MplWidget()
self.setCentralWidget(self.mpl_widget)
# TODO: shouldn't have to do this
self.central_widget = self.mpl_widget
self.figure, self._axes = init_mpl(self.mpl_widget.canvas.fig, wcs=wcs)
self.state.add_callback('aspect', self.update_aspect)
self.update_aspect()
self.state.add_callback('x_min', self.limits_to_mpl)
self.state.add_callback('x_max', self.limits_to_mpl)
self.state.add_callback('y_min', self.limits_to_mpl)
self.state.add_callback('y_max', self.limits_to_mpl)
self.limits_to_mpl()
self.state.add_callback('x_log', self.update_x_log, priority=1000)
self.state.add_callback('y_log', self.update_y_log, priority=1000)
self.update_x_log()
self.axes.callbacks.connect('xlim_changed', self.limits_from_mpl)
self.axes.callbacks.connect('ylim_changed', self.limits_from_mpl)
self.axes.set_autoscale_on(False)
self.state.add_callback('x_axislabel', self.update_x_axislabel)
self.state.add_callback('x_axislabel_weight', self.update_x_axislabel)
self.state.add_callback('x_axislabel_size', self.update_x_axislabel)
self.state.add_callback('y_axislabel', self.update_y_axislabel)
self.state.add_callback('y_axislabel_weight', self.update_y_axislabel)
self.state.add_callback('y_axislabel_size', self.update_y_axislabel)
self.state.add_callback('x_ticklabel_size', self.update_x_ticklabel)
self.state.add_callback('y_ticklabel_size', self.update_y_ticklabel)
self.update_x_axislabel()
self.update_y_axislabel()
self.update_x_ticklabel()
self.update_y_ticklabel()
self.central_widget.resize(600, 400)
self.resize(self.central_widget.size())
def __init__(self, session, parent=None):
super(MatplotlibDataViewer, self).__init__(session, parent)
# Use MplWidget to set up a Matplotlib canvas inside the Qt window
self.mpl_widget = MplWidget()
self.setCentralWidget(self.mpl_widget)
# TODO: shouldn't have to do this
self.central_widget = self.mpl_widget
self.figure, self._axes = init_mpl(self.mpl_widget.canvas.fig)
# Set up the state which will contain everything needed to represent
# the current state of the viewer
self.state = self._state_cls()
self.state.data_collection = session.data_collection
# Set up the options widget, which will include options that control the
# viewer state
self.options = self._options_cls(viewer_state=self.state,
session=session)
add_callback(self.state, 'x_min', nonpartial(self.limits_to_mpl))
add_callback(self.state, 'x_max', nonpartial(self.limits_to_mpl))
add_callback(self.state, 'y_min', nonpartial(self.limits_to_mpl))
add_callback(self.state, 'y_max', nonpartial(self.limits_to_mpl))
self.axes.callbacks.connect('xlim_changed',
nonpartial(self.limits_from_mpl))
self.axes.callbacks.connect('ylim_changed',
nonpartial(self.limits_from_mpl))
self.state.add_callback('x_log', nonpartial(self.update_x_log))
self.state.add_callback('y_log', nonpartial(self.update_y_log))
self.axes.set_autoscale_on(False)
# TODO: in future could move the following to a more basic data viewer class
# When layer artists are removed from the layer artist container, we need
# to make sure we remove matching layer states in the viewer state
# layers attribute.
self._layer_artist_container.on_changed(
nonpartial(self._sync_state_layers))
# And vice-versa when layer states are removed from the viewer state, we
# need to keep the layer_artist_container in sync
self.state.add_callback('layers',
nonpartial(self._sync_layer_artist_container))
def __init__(self, parent=None):
super(Line1DWidget, self).__init__(parent)
self.figure = plt.figure(facecolor='white')
# Canvas Widget that displays the `figure` it takes the `figure`
# instance as a parameter to __init__
canvas = FigureCanvas(self.figure)
# Double reference; Glue's toolbar abstraction requires that the
# central widget of its parent have a reference to the canvas object
self.central_widget = canvas
self.central_widget.canvas = canvas
# Navigation widget, it takes the Canvas widget and a parent
self.toolbar = MatplotlibViewerToolbar(self)
self.addToolBar(self.toolbar)
self.setCentralWidget(self.central_widget)
_, self._axes = init_mpl(figure=self.figure)
self._artists = []
def __init__(self, session, parent=None, wcs=None, state=None):
super(MatplotlibDataViewer, self).__init__(session, parent, state=state)
# Use MplWidget to set up a Matplotlib canvas inside the Qt window
self.mpl_widget = MplWidget()
self.setCentralWidget(self.mpl_widget)
# TODO: shouldn't have to do this
self.central_widget = self.mpl_widget
self.figure, self._axes = init_mpl(self.mpl_widget.canvas.fig, wcs=wcs)
self.state.add_callback('aspect', self.update_aspect)
self.update_aspect()
self.state.add_callback('x_min', nonpartial(self.limits_to_mpl))
self.state.add_callback('x_max', nonpartial(self.limits_to_mpl))
self.state.add_callback('y_min', nonpartial(self.limits_to_mpl))
self.state.add_callback('y_max', nonpartial(self.limits_to_mpl))
self.limits_to_mpl()
self.state.add_callback('x_log', nonpartial(self.update_x_log))
self.state.add_callback('y_log', nonpartial(self.update_y_log))
self.update_x_log()
self.axes.callbacks.connect('xlim_changed', nonpartial(self.limits_from_mpl))
self.axes.callbacks.connect('ylim_changed', nonpartial(self.limits_from_mpl))
self.axes.set_autoscale_on(False)
self.central_widget.resize(600, 400)
self.resize(self.central_widget.size())
def _setup_mpl(self, figure, axes):
figure, axes = init_mpl(figure, axes, wcs=True)
self._axes = axes
self._axes.get_xaxis().set_ticks([])
self._axes.get_yaxis().set_ticks([])
self._figure = figure
# custom axes formatter
def format_coord(x, y):
data = self.display_data
if data is None:
# MPL default method
return type(self._axes).format_coord(self._axes, x, y)
info = self.point_details(x, y)
return ' '.join(info['labels'])
self._axes.format_coord = format_coord
self._cid = self._axes.figure.canvas.mpl_connect('button_release_event',
self.check_update)
if hasattr(self._axes.figure.canvas, 'homeButton'):
# test code doesn't always use Glue's custom FigureCanvas
self._axes.figure.canvas.homeButton.connect(self.check_update)
def _setup_mpl(self, figure, axes):
figure, axes = init_mpl(figure, axes, wcs=True)
self._axes = axes
self._axes.get_xaxis().set_ticks([])
self._axes.get_yaxis().set_ticks([])
self._figure = figure
# custom axes formatter
def format_coord(x, y):
data = self.display_data
if data is None:
# MPL default method
return type(self._axes).format_coord(self._axes, x, y)
info = self.point_details(x, y)
return ' '.join(info['labels'])
self._axes.format_coord = format_coord
self._cid = self._axes.figure.canvas.mpl_connect(
'button_release_event', self.check_update)
if hasattr(self._axes.figure.canvas, 'homeButton'):
# test code doesn't always use Glue's custom FigureCanvas
self._axes.figure.canvas.homeButton.connect(self.check_update)
def _setup_axes(self):
from glue.viewers.common.viz_client import init_mpl
_, self._axes = init_mpl(self.central_widget.canvas.fig, axes=None, wcs=True)
self._axes.set_aspect('equal', adjustable='datalim')
def _setup_axes(self):
from glue.viewers.common.viz_client import init_mpl
_, self._axes = init_mpl(self.central_widget.canvas.fig,
axes=None,
wcs=True)
self._axes.set_aspect('equal', adjustable='datalim')
