def _resolve(self, permute, concat):
"""Determine what data to plot on which axis"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots(permute)
pivot_vals = list(pivot_vals)
num_of_axes = len(self.c_mgr) if concat else len_pivots
# Create a 2D Layout
self._layout = PlotLayout(self._attr["per_line"],
num_of_axes,
width=self._attr["width"],
length=self._attr["length"],
title=self._attr['title'])
self._fig = self._layout.get_fig()
# Determine what constraint to plot and the corresponding pivot value
if permute:
legend_len = self.c_mgr._max_len
pivots = [y for _, y in pivot_vals]
c_dict = {c: str(c) for c in self.c_mgr}
c_list = sorted(c_dict.items(),
key=lambda x:
(x[1].split(":")[-1], x[1].split(":")[0]))
constraints = [c[0] for c in c_list]
cp_pairs = [(c, p) for c in constraints
for p in sorted(set(pivots))]
else:
legend_len = len_pivots if concat else len(self.c_mgr)
pivots = pivot_vals
cp_pairs = [(c, p) for c in self.c_mgr for p in pivots
if p in c.result]
# Initialise legend data and colormap
self._attr["_legend_handles"] = [None] * legend_len
self._attr["_legend_labels"] = [None] * legend_len
if "colors" in self._attr:
self._cmap = ColorMap.rgb_cmap(self._attr["colors"])
else:
self._cmap = ColorMap(legend_len)
# Group constraints/series with the axis they are to be plotted on
figure_data = ddict(list)
for i, (constraint, pivot) in enumerate(cp_pairs):
axis = self._layout.get_axis(
constraint.trace_index if concat else i)
figure_data[axis].append((constraint, pivot))
# Plot each axis
for axis, series_list in figure_data.items():
self.plot_axis(axis, series_list, permute, self._attr["concat"],
self._attr["args_to_forward"])
if self._attr["xlim"]:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"]:
axis.set_ylim(self._attr["ylim"])
# Show legend
legend = self._fig.legend(self._attr["_legend_handles"],
self._attr["_legend_labels"],
loc='lower center',
ncol=self._attr["legend_ncol"],
borderaxespad=0.)
legend.get_frame().set_facecolor('#F4F4F4')
self._layout.finish(num_of_axes)
def _resolve(self, permute, concat):
"""Determine what data to plot on which axis"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots(permute)
pivot_vals = list(pivot_vals)
num_of_axes = len(self.c_mgr) if concat else len_pivots
# Create a 2D Layout
self._layout = PlotLayout(
self._attr["per_line"],
num_of_axes,
width=self._attr["width"],
length=self._attr["length"],
title=self._attr['title'])
self._fig = self._layout.get_fig()
# Determine what constraint to plot and the corresponding pivot value
if permute:
legend_len = self.c_mgr._max_len
pivots = [y for _, y in pivot_vals]
c_dict = {c : str(c) for c in self.c_mgr}
c_list = sorted(c_dict.items(), key=lambda x: (x[1].split(":")[-1], x[1].split(":")[0]))
constraints = [c[0] for c in c_list]
cp_pairs = [(c, p) for c in constraints for p in sorted(set(pivots))]
else:
legend_len = len_pivots if concat else len(self.c_mgr)
pivots = pivot_vals
cp_pairs = [(c, p) for c in self.c_mgr for p in pivots if p in c.result]
# Initialise legend data and colormap
self._attr["_legend_handles"] = [None] * legend_len
self._attr["_legend_labels"] = [None] * legend_len
if "colors" in self._attr:
self._cmap = ColorMap.rgb_cmap(self._attr["colors"])
else:
self._cmap = ColorMap(legend_len)
# Group constraints/series with the axis they are to be plotted on
figure_data = ddict(list)
for i, (constraint, pivot) in enumerate(cp_pairs):
axis = self._layout.get_axis(constraint.trace_index if concat else i)
figure_data[axis].append((constraint, pivot))
# Plot each axis
for axis, series_list in figure_data.iteritems():
self.plot_axis(
axis,
series_list,
permute,
self._attr["concat"],
self._attr["args_to_forward"]
)
if self._attr["xlim"]:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"]:
axis.set_ylim(self._attr["ylim"])
# Show legend
legend = self._fig.legend(self._attr["_legend_handles"],
self._attr["_legend_labels"],
loc='lower center',
ncol=self._attr["legend_ncol"],
borderaxespad=0.)
legend.get_frame().set_facecolor('#F4F4F4')
self._layout.finish(num_of_axes)
