def skill(self, path='', threshold=15):
"""Draws graph of mean skill and mean response time per session.
:param threshold: how many sessions to draw -- default is 10
:param path: output directory -- default is '' (current_dir)
"""
if not path:
path = self.current_dir+'/graphs/'
data = analysis.mean_skill_session(self.frame,self.difficulties,threshold)[0]
if not data.empty:
fig, ax = plt.subplots()
ind = arange(len(data.index))
width=0.4
ax.bar(ind+width/2,data.values,width=width, color="green")
ax.set_title(u"Progress of skill over sessions")
ax.set_xticklabels(ind)
ax.set_xticks(ind+width)
ax.set_xlabel('Session number')
ax.set_ylabel('Mean success rate', color='green')
#ax.yaxis.set_major_formatter(FuncFormatter(lambda x,y: "%1.2f%%"%(100*x))) #sets y-axis to show percentages
for tl in ax.get_yticklabels():
tl.set_color('green')
plt.savefig(path+'skill.svg', bbox_inches='tight')
plt.close()
def skill(self, binning_function=None, path="", number_of_bins=6):
"""Draws map of skill per country.
:param binning_function: which function to use for binning -- default is None (-> jenks_classification)
:param path: output directory -- default is '' (current dir)
:param number_of_bins: how many bins to divide data into-- default is 6
"""
if not path:
path = self.current_dir + "/maps/"
data = analysis.mean_skill_session(self.frame, self.difficulties, threshold=None)[1]
data = analysis.success_probabilities(data, self.difficulties)
colours = None
if not data.empty:
(data, colours) = self.bin_data(data, binning_function, number_of_bins, colour_range="RdYlGn")
self.generate_css(data[["country", "rgb"]], path=self.current_dir + "/style.css")
self.draw_map(path + "skill.svg", "Skill ", colours)