def updateGroupedPlot(self, group, plot, x, y):
"""
Update the data for a single plot.
The plot you want to update is defined by the group and plot
id. Both numbers are starting at zero and simply increment when
new groups/plots are added by the user, so the second plot within
the first group is (group=0, plot=1).
:param group: (int) Group id of the plot.
:param plot: (int) Plot id of the plot.
:param x: (ndarray) New x values for plotting.
:param y: (ndarray) New y values for plotting.
"""
line = self.plotLineGroups[group][plot]
points = self.plotPointGroups[group][plot]
if len(x) != 0:
xu, yu = unique_mean(x, y)
else:
xu, yu = [], []
line.set_xdata(xu)
line.set_ydata(yu)
points.set_xdata(x)
points.set_ydata(y)
self._needRescale = True
def addGroupedPlot(self, label, x, y):
"""
Creates a new plot within the last created plot group.
Generally, this function creates two plots for a given dataset.
The first plot is a scatter plot, showing all x and y values.
The second plot is a line plot, averaging over y values if there
are multiple occurrences of x values.
The plot data can be updated by calling :func:`updateGroupedPlot`.
:param label: (str) Label to be displayed in the figure legend.
:param x: (ndarray) Array or list of x values.
:param y: (ndarray) Array or list of y values.
:returns: (int) Plot id assigned for updating plots later on.
"""
if not self.plotPointGroups: self.newPlotGroup()
assert len(self.plotPointGroups[-1]) < len(self.linestyles), "maximum number of plot group elements reached"
pointGroup = self.plotPointGroups[-1]
lineGroup = self.plotLineGroups[-1]
if len(x) != 0:
xu, yu = unique_mean(x, y)
else:
xu, yu = [], []
points = matplotlib.lines.Line2D(x, y,
color = self.colors[len(self.plotPointGroups)-1],
marker = "o", ls = "")
line = matplotlib.lines.Line2D(xu, yu, label = label,
color = self.colors[len(self.plotLineGroups)-1],
ls = self.linestyles[len(lineGroup)])
pointGroup.append(points)
lineGroup.append(line)
self._needSetupLines = True
return len(lineGroup) - 1
