class PlotView(View):
'''
classdocs
'''
def __init__(self, *args, **kwargs):
'''
Constructor
'''
View.__init__(self,*args,**kwargs)
self._plot = PlotWidget()
self.addWidget(self._plot)
self.setTitle("PlotView")
self._pen = {'width':5}
def update_slot(self, args):
'''
Method called to update the plot. In this case, arguments to specify how to draw a line plot.
Parameters:
- args (:class:`dict`) : a `dict` with at least two fields - "xAxis" and "yAxis". "yAxis" may be a list, in which case all the arrays within will be overlaid. Any extra fields within `args` will be passed along to the :class:`PlotWidget.plot` function.
Returns:
- N/A
'''
assert type(args) is dict, 'PlotView did not receive a dict while calling update.'
assert 'xAxis' in args, 'PlotView did not receive an x-axis'
assert 'yAxis' in args, 'PlotView did not receive any y-axis'
xAxis = args['xAxis']
yAxis = args['yAxis']
del args['xAxis']
del args['yAxis']
if 'pen' not in args:
args['pen'] = self._pen
if type(yAxis) is list:
self._plot.clear()
for dset in yAxis:
self._plot.plot(xAxis,dset,**args)
else:
self._plot.plot(xAxis,yAxis,clear=True,**args)
class QtPlotView(QtControl, ProxyPlotView):
__weakref__ = None
widget = Typed(PlotWidget)
_views = List()
_colors = List(default=['r', 'g', 'b'])
def create_widget(self):
self.widget = PlotWidget(self.parent_widget(), background='w')
def init_widget(self):
super(QtPlotView, self).init_widget()
d = self.declaration
#self.widget.setSizePolicy(QSizePolicy.Expanding,QSizePolicy.Expanding)
self.set_data(d.data)
self.set_antialiasing(d.antialiasing)
self.set_aspect_locked(d.aspect_locked)
self.set_axis_scales(d.axis_scales)
self.set_labels(d.labels)
self.widget.showGrid(d.grid[0], d.grid[1], d.grid_alpha)
d.setup(self.widget)
def set_title(self, title):
self.set_labels(self.declaration.labels)
def set_labels(self, labels):
if self.declaration.title:
labels['title'] = self.declaration.title
self.widget.setLabels(**labels)
def set_antialiasing(self, enabled):
self.widget.setAntialiasing(enabled)
def set_aspect_locked(self, locked):
self.widget.setAspectLocked(locked)
def set_axis_scales(self, scales):
if not scales:
return
for k, v in scales.items():
if k in self.widget.plotItem.axes:
self.widget.plotItem.axes[k]['item'].setScale(v)
def set_grid(self, grid):
d = self.declaration
self.widget.showGrid(grid[0], grid[1], d.grid_alpha)
def set_grid_alpha(self, alpha):
d = self.declaration
self.widget.showGrid(d.grid[0], d.grid[1], alpha)
def set_data(self, data):
self.widget.clear()
if not data:
return
if isinstance(data, (list, tuple)) and \
isinstance(data[0], GraphicsObject):
self._set_graphic_items(data)
else:
self._set_numeric_data(data)
def _set_graphic_items(self, items):
self.widget.clear()
for item in items:
self.widget.addItem(item)
def _set_numeric_data(self, data):
self.widget.plotItem.clear()
if self._views:
for view in self._views:
view.clear()
views = []
i = 0
if self.declaration.multi_axis:
for i, plot in enumerate(data):
if i > 3:
break
if 'pen' not in plot:
plot['pen'] = self._colors[i]
if i > 0:
view = ViewBox()
views.append(view)
self.widget.plotItem.scene().addItem(view)
if i == 1:
axis = self.widget.plotItem.getAxis('right')
elif i > 1:
axis = AxisItem('right')
axis.setZValue(-10000)
self.widget.plotItem.layout.addItem(axis, 2, 3)
axis.linkToView(view)
view.setXLink(self.widget.plotItem)
view.addItem(PlotCurveItem(**plot))
else:
self.widget.plot(**plot)
if i > 0:
def syncViews():
for v in views:
v.setGeometry(self.widget.plotItem.vb.sceneBoundingRect())
v.linkedViewChanged(self.widget.plotItem.vb, v.XAxis)
syncViews()
self.widget.plotItem.vb.sigResized.connect(syncViews)
self._views = views
class QtPlotView(QtControl, ProxyPlotView):
__weakref__ = None
widget = Typed(PlotWidget)
_views = List()
_colors = List(default=['r', 'g', 'b'])
def create_widget(self):
self.widget = PlotWidget(self.parent_widget(), background='w')
def init_widget(self):
super(QtPlotView, self).init_widget()
d = self.declaration
#self.widget.setSizePolicy(QSizePolicy.Expanding,QSizePolicy.Expanding)
self.set_data(d.data)
self.set_antialiasing(d.antialiasing)
self.set_aspect_locked(d.aspect_locked)
self.set_axis_scales(d.axis_scales)
self.set_labels(d.labels)
self.widget.showGrid(d.grid[0], d.grid[1], d.grid_alpha)
d.setup(self.widget)
def set_title(self, title):
self.set_labels(self.declaration.labels)
def set_labels(self, labels):
if self.declaration.title:
labels['title'] = self.declaration.title
self.widget.setLabels(**labels)
def set_antialiasing(self,enabled):
self.widget.setAntialiasing(enabled)
def set_aspect_locked(self,locked):
self.widget.setAspectLocked(locked)
def set_axis_scales(self,scales):
if not scales:
return
for k, v in scales.items():
if k in self.widget.plotItem.axes:
self.widget.plotItem.axes[k]['item'].setScale(v)
def set_data(self, data):
self.widget.clear()
if not data:
return
if isinstance(data, (list, tuple)) and isinstance(data[0],
GraphicsObject):
self._set_graphic_items(data)
else:
self._set_numeric_data(data)
def _set_graphic_items(self, items):
self.widget.clear()
for item in items:
self.widget.addItem(item)
def _set_numeric_data(self,data):
self.widget.plotItem.clear()
if self._views:
for view in self._views:
view.clear()
views = []
i = 0
if self.declaration.multi_axis:
for i,plot in enumerate(data):
if i>3:
break
if 'pen' not in plot:
plot['pen'] = self._colors[i]
if i>0:
view = ViewBox()
views.append(view)
self.widget.plotItem.scene().addItem(view)
if i==1:
axis = self.widget.plotItem.getAxis('right')
elif i>1:
axis = AxisItem('right')
axis.setZValue(-10000)
self.widget.plotItem.layout.addItem(axis,2,3)
axis.linkToView(view)
view.setXLink(self.widget.plotItem)
view.addItem(PlotCurveItem(**plot))
else: #view.setYLink(self.widget.plotItem)
self.widget.plot(**plot)
if i>0:
def syncViews():
for v in views:
v.setGeometry(self.widget.plotItem.vb.sceneBoundingRect())
v.linkedViewChanged(self.widget.plotItem.vb,v.XAxis)
syncViews()
self.widget.plotItem.vb.sigResized.connect(syncViews)
self._views = views
class ScatterPlotWidget(pg.QtGui.QSplitter):
"""
This is a high-level widget for exploring relationships in tabular data.
Given a multi-column record array, the widget displays a scatter plot of a
specific subset of the data. Includes controls for selecting the columns to
plot, filtering data, and determining symbol color and shape.
The widget consists of four components:
1) A list of column names from which the user may select 1 or 2 columns
to plot. If one column is selected, the data for that column will be
plotted in a histogram-like manner by using :func:`pseudoScatter()
<pyqtgraph.pseudoScatter>`. If two columns are selected, then the
scatter plot will be generated with x determined by the first column
that was selected and y by the second.
2) A DataFilter that allows the user to select a subset of the data by
specifying multiple selection criteria.
3) A ColorMap that allows the user to determine how points are colored by
specifying multiple criteria.
4) A PlotWidget for displaying the data.
"""
sigScatterPlotClicked = pg.QtCore.Signal(object, object, object)
def __init__(self, parent=None):
pg.QtGui.QSplitter.__init__(self, pg.QtCore.Qt.Horizontal)
self.ctrlPanel = pg.QtGui.QSplitter(pg.QtCore.Qt.Vertical)
self.addWidget(self.ctrlPanel)
self.fieldList = pg.QtGui.QListWidget()
self.fieldList.setSelectionMode(self.fieldList.ExtendedSelection)
self.ptree = pg.parametertree.ParameterTree(showHeader=False)
self.filter = DataFilterParameter()
self.colorMap = ColorMapParameter()
self.style = StyleMapParameter()
self.params = pg.parametertree.Parameter.create(name='params', type='group', children=[self.filter, self.colorMap, self.style])
self.ptree.setParameters(self.params, showTop=False)
self.plot = PlotWidget()
self.ctrlPanel.addWidget(self.fieldList)
self.ctrlPanel.addWidget(self.ptree)
self.addWidget(self.plot)
fg = pg.mkColor(pg.getConfigOption('foreground'))
fg.setAlpha(150)
self.filterText = pg.TextItem(border=pg.getConfigOption('foreground'), color=fg)
self.filterText.setPos(60,20)
self.filterText.setParentItem(self.plot.plotItem)
self.data = None
self.indices = None
self.mouseOverField = None
self.scatterPlot = None
self.selectionScatter = None
self.selectedIndices = []
self._visibleXY = None # currently plotted points
self._visibleData = None # currently plotted records
self._visibleIndices = None
self._indexMap = None
self.fieldList.itemSelectionChanged.connect(self.fieldSelectionChanged)
self.filter.sigFilterChanged.connect(self.filterChanged)
self.colorMap.sigColorMapChanged.connect(self.updatePlot)
self.style.sigStyleChanged.connect(self.updatePlot)
def setFields(self, fields, mouseOverField=None):
"""
Set the list of field names/units to be processed.
The format of *fields* is the same as used by
:func:`ColorMapWidget.setFields <pyqtgraph.widgets.ColorMapWidget.ColorMapParameter.setFields>`
"""
self.fields = OrderedDict(fields)
self.mouseOverField = mouseOverField
self.fieldList.clear()
for f,opts in fields:
item = pg.QtGui.QListWidgetItem(f)
item.opts = opts
item = self.fieldList.addItem(item)
self.filter.setFields(fields)
self.colorMap.setFields(fields)
self.style.setFields(fields)
def setSelectedFields(self, *fields):
self.fieldList.itemSelectionChanged.disconnect(self.fieldSelectionChanged)
try:
self.fieldList.clearSelection()
for f in fields:
i = list(self.fields.keys()).index(f)
item = self.fieldList.item(i)
item.setSelected(True)
finally:
self.fieldList.itemSelectionChanged.connect(self.fieldSelectionChanged)
self.fieldSelectionChanged()
def setData(self, data):
"""
Set the data to be processed and displayed.
Argument must be a numpy record array.
"""
self.data = data
self.indices = np.arange(len(data))
self.filtered = None
self.filteredIndices = None
self.updatePlot()
def setSelectedIndices(self, inds):
"""Mark the specified indices as selected.
Must be a sequence of integers that index into the array given in setData().
"""
self.selectedIndices = inds
self.updateSelected()
def setSelectedPoints(self, points):
"""Mark the specified points as selected.
Must be a list of points as generated by the sigScatterPlotClicked signal.
"""
self.setSelectedIndices([pt.originalIndex for pt in points])
def fieldSelectionChanged(self):
sel = self.fieldList.selectedItems()
if len(sel) > 2:
self.fieldList.blockSignals(True)
try:
for item in sel[1:-1]:
item.setSelected(False)
finally:
self.fieldList.blockSignals(False)
self.updatePlot()
def filterChanged(self, f):
self.filtered = None
self.updatePlot()
desc = self.filter.describe()
if len(desc) == 0:
self.filterText.setVisible(False)
else:
self.filterText.setText('\n'.join(desc))
self.filterText.setVisible(True)
def updatePlot(self):
self.plot.clear()
if self.data is None or len(self.data) == 0:
return
if self.filtered is None:
mask = self.filter.generateMask(self.data)
self.filtered = self.data[mask]
self.filteredIndices = self.indices[mask]
data = self.filtered
if len(data) == 0:
return
colors = np.array([pg.mkBrush(*x) for x in self.colorMap.map(data)])
style = self.style.map(data)
## Look up selected columns and units
sel = list([str(item.text()) for item in self.fieldList.selectedItems()])
units = list([item.opts.get('units', '') for item in self.fieldList.selectedItems()])
if len(sel) == 0:
self.plot.setTitle('')
return
if len(sel) == 1:
self.plot.setLabels(left=('N', ''), bottom=(sel[0], units[0]), title='')
if len(data) == 0:
return
#x = data[sel[0]]
#y = None
xy = [data[sel[0]], None]
elif len(sel) == 2:
self.plot.setLabels(left=(sel[1],units[1]), bottom=(sel[0],units[0]))
if len(data) == 0:
return
xy = [data[sel[0]], data[sel[1]]]
#xydata = []
#for ax in [0,1]:
#d = data[sel[ax]]
### scatter catecorical values just a bit so they show up better in the scatter plot.
##if sel[ax] in ['MorphologyBSMean', 'MorphologyTDMean', 'FIType']:
##d += np.random.normal(size=len(cells), scale=0.1)
#xydata.append(d)
#x,y = xydata
## convert enum-type fields to float, set axis labels
enum = [False, False]
for i in [0,1]:
axis = self.plot.getAxis(['bottom', 'left'][i])
if xy[i] is not None and (self.fields[sel[i]].get('mode', None) == 'enum' or xy[i].dtype.kind in ('S', 'O')):
vals = self.fields[sel[i]].get('values', list(set(xy[i])))
xy[i] = np.array([vals.index(x) if x in vals else len(vals) for x in xy[i]], dtype=float)
axis.setTicks([list(enumerate(vals))])
enum[i] = True
else:
axis.setTicks(None) # reset to automatic ticking
## mask out any nan values
mask = np.ones(len(xy[0]), dtype=bool)
if xy[0].dtype.kind == 'f':
mask &= np.isfinite(xy[0])
if xy[1] is not None and xy[1].dtype.kind == 'f':
mask &= np.isfinite(xy[1])
xy[0] = xy[0][mask]
for k in style.keys():
if style[k] is None:
continue
style[k] = style[k][mask]
style['symbolBrush'] = colors[mask]
data = data[mask]
indices = self.filteredIndices[mask]
## Scatter y-values for a histogram-like appearance
if xy[1] is None:
## column scatter plot
xy[1] = pg.pseudoScatter(xy[0])
else:
xy[1] = xy[1][mask]
## beeswarm plots
for ax in [0,1]:
if not enum[ax]:
continue
imax = int(xy[ax].max()) if len(xy[ax]) > 0 else 0
for i in range(imax+1):
keymask = xy[ax] == i
scatter = pg.pseudoScatter(xy[1-ax][keymask], bidir=True)
if len(scatter) == 0:
continue
smax = np.abs(scatter).max()
if smax != 0:
scatter *= 0.2 / smax
xy[ax][keymask] += scatter
if self.scatterPlot is not None:
try:
self.scatterPlot.sigPointsClicked.disconnect(self.plotClicked)
except:
pass
self._visibleXY = xy
self._visibleData = data
self._visibleIndices = indices
self._indexMap = None
self.scatterPlot = self.plot.plot(xy[0], xy[1], data=data, **style)
self.scatterPlot.sigPointsClicked.connect(self.plotClicked)
self.updateSelected()
def updateSelected(self):
if self._visibleXY is None:
return
# map from global index to visible index
indMap = self._getIndexMap()
inds = [indMap[i] for i in self.selectedIndices if i in indMap]
x,y = self._visibleXY[0][inds], self._visibleXY[1][inds]
if self.selectionScatter is not None:
self.plot.plotItem.removeItem(self.selectionScatter)
if len(x) == 0:
return
self.selectionScatter = self.plot.plot(x, y, pen=None, symbol='s', symbolSize=12, symbolBrush=None, symbolPen='y')
def _getIndexMap(self):
# mapping from original data index to visible point index
if self._indexMap is None:
self._indexMap = {j:i for i,j in enumerate(self._visibleIndices)}
return self._indexMap
def plotClicked(self, plot, points, ev):
# Tag each point with its index into the original dataset
for pt in points:
pt.originalIndex = self._visibleIndices[pt.index()]
self.sigScatterPlotClicked.emit(self, points, ev)
