def graph_sample_paths\
(sample_paths, title, x_label, y_label, output_type=Fig.OutType.SHOW,
legends=None, transparency=1, common_color_code=None,
if_same_color=False):
"""
:param sample_paths: a list of sample paths
:param title: (string) title of the figure
:param x_label: (string) x-axis label
:param y_label: (string) y-axis label
:param output_type: select from OutType.SHOW, OutType.PDF, or OutType.JPG
:param legends: list of strings for legend
:param transparency: float (0.0 transparent through 1.0 opaque)
:param common_color_code: (string) color code if all sample paths should have the same color
'b' blue 'g' green 'r' red 'c' cyan 'm' magenta 'y' yellow 'k' black
:param if_same_color: logical, default False, if set True, paint the sample paths the same color
"""
if len(sample_paths) == 1:
raise ValueError('Only one sample path is provided. Use graph_sample_path instead.')
fig = plt.figure(title)
plt.title(title) # title
plt.xlabel(x_label) # x-axis label
plt.ylabel(y_label) # y-axis label
# color
color_marker_text = '-'
if not (common_color_code is None):
color_marker_text = common_color_code+color_marker_text
# x and y values
if if_same_color:
for path in sample_paths:
x_values = path.get_times()
y_values = path.get_values()
# plot
plt.plot(x_values, y_values, common_color_code, alpha=transparency)
else:
for path in sample_paths:
x_values = path.get_times()
y_values = path.get_values()
# plot
plt.plot(x_values, y_values, color_marker_text, alpha=transparency)
# add legend if provided
if not (legends is None):
if common_color_code is None:
plt.legend(legends)
else:
plt.legend([legends])
# set the minimum of y-axis to zero
plt.ylim(ymin=0) # the minimum has to be set after plotting the values
# output figure
Fig.output_figure(plt, output_type, title)
def graph_sample_path(sample_path, title, x_label, y_label,
output_type=Fig.OutType.SHOW, legend=None, color_code=None):
"""
produces a sample path
:param sample_path: a sample path
:param title: (string) title of the figure
:param x_label: (string) x-axis label
:param y_label: (string) y-axis label
:param output_type: select from OutType.SHOW, OutType.PDF, or OutType.JPG
:param legend: string for the legend
:param color_code: (string) 'b' blue 'g' green 'r' red 'c' cyan 'm' magenta 'y' yellow 'k' black
"""
fig = plt.figure(title)
plt.title(title) # title
plt.xlabel(x_label) # x-axis label
plt.ylabel(y_label) # y-axis label
# x and y values
x_values = sample_path.get_times()
y_values = sample_path.get_values()
# color
color_marker_text = '-'
if not (color_code is None):
color_marker_text = color_code + color_marker_text
# plot
plt.plot(x_values, y_values, color_marker_text)
# add legend if provided
if not (legend is None):
plt.legend([legend])
# set the minimum of y-axis to zero
plt.ylim(ymin=0) # the minimum has to be set after plotting the values
# output figure
Fig.output_figure(plt, output_type, title)
def show_CE_plane(self,
title,
x_label,
y_label,
show_names=False,
show_clouds=False,
show_legend=False,
figure_size=6):
"""
:param title: title of the figure
:param x_label: (string) x-axis label
:param y_label: (string) y-axis label
:param show_names: logical, show strategy names
:param show_clouds: logical, show true sample observation of strategies
:param show_legend: shows the legend of strategies, would only be used when show_clouds is true
:param figure_size: int, specify the figure size
"""
# plots
# operate on local variable data rather than self attribute
data = self._dfStrategies_shifted
data["Dominated_result"] = self._dfStrategies["Dominated"]
# re-sorted according to Effect to draw line
line_plot = data.loc[data["Dominated_result"] == False].sort_values(
'E[Effect]')
# show observation clouds for strategies
if show_clouds:
plt.figure(figsize=(figure_size, figure_size))
for strategy_i, color in zip(
self._shifted_strategies,
cm.rainbow(np.linspace(0, 1, self._n))):
x_values = strategy_i.effectObs
y_values = strategy_i.costObs
# plot clouds
plt.scatter(x_values,
y_values,
c=color,
alpha=0.5,
s=25,
label=strategy_i.name)
if show_legend:
plt.legend(
) # to customize legend: loc='lower right', numpoints=1, ncol=3, fontsize=8)
plt.scatter(data['E[Effect]'],
data['E[Cost]'],
marker='x',
c='k',
s=50,
linewidths=2)
else:
plt.figure(figsize=(figure_size, figure_size))
plt.scatter(data['E[Effect]'],
data['E[Cost]'],
c=list(data['Color']),
s=50)
plt.plot(line_plot['E[Effect]'], line_plot['E[Cost]'], c='k')
plt.axhline(y=0, c='k', linewidth=0.5)
plt.axvline(x=0, c='k', linewidth=0.5)
plt.title(title)
plt.xlabel(x_label)
plt.ylabel(y_label)
# show names of strategies
if show_names:
if not show_clouds:
for label, x, y in zip(data['Name'], data['E[Effect]'],
data['E[Cost]']):
plt.annotate(label,
xy=(x, y),
xycoords='data',
xytext=(x - 0.6, y + 0.3),
textcoords='data',
weight='bold')
elif show_clouds:
for label, x, y in zip(data['Name'], data['E[Effect]'],
data['E[Cost]']):
plt.annotate(label,
xy=(x, y),
xycoords='data',
xytext=(x - 0.8, y + 0.8),
textcoords='data',
arrowprops=dict(arrowstyle='->',
connectionstyle='arc3',
shrinkA=0,
shrinkB=2),
weight='bold',
bbox=dict(pad=0,
facecolor="none",
edgecolor="none"))
# show the figure
Fig.output_figure(plt, Fig.OutType.SHOW, title)
