selected_data = data_set.map(lambda x: x['student']).distinct()
for student in selected_data:
if participation_table.has_key(student):
participation_table[student].append(index)
else:
participation_table[student] = [index]
# print participation_table
################################################
### Figure for number of labs joined per lab ###
################################################
plot_data = [[0 for i in xrange(LAB_NUMBER)] for j in xrange(LAB_NUMBER)]
for student in participation_table:
status = participation_table[student]
for lab in status:
plot_data[LAB_NUMBER - len(status)][lab] += 1
fig, ax = toolkit.prepare_plot(gridWidth=0)
tem_bottom = [0] * LAB_NUMBER
color = plt.cm.Blues_r(np.linspace(.2, .8, LAB_NUMBER))
p = []
ind = np.arange(LAB_NUMBER)
width = .5
for i in range(LAB_NUMBER):
bar = plt.bar(ind,
plot_data[i],
width,
color=color[i],
bottom=tem_bottom,
edgecolor=color[i])
p.append(bar)
for j in range(LAB_NUMBER):
tem_bottom[j] += plot_data[i][j]
selected_data = data_set.map(lambda x: x['student']).distinct()
for student in selected_data:
if participation_table.has_key(student):
participation_table[student].append(index)
else:
participation_table[student] = [index]
# print participation_table
################################################
### Figure for number of labs joined per lab ###
################################################
plot_data = [[0 for i in xrange(LAB_NUMBER)] for j in xrange(LAB_NUMBER)]
for student in participation_table:
status = participation_table[student]
for lab in status:
plot_data[LAB_NUMBER-len(status)][lab] += 1
fig, ax = toolkit.prepare_plot(gridWidth=0)
tem_bottom = [0] * LAB_NUMBER
color = plt.cm.Blues_r(np.linspace(.2, .8, LAB_NUMBER))
p = []
ind = np.arange(LAB_NUMBER)
width=.5
for i in range(LAB_NUMBER):
bar = plt.bar(ind, plot_data[i], width, color=color[i], bottom=tem_bottom, edgecolor=color[i])
p.append(bar)
for j in range(LAB_NUMBER):
tem_bottom[j] += plot_data[i][j]
plt.ylabel('Number of students')
plt.title('Number of other labs a student has participated in')
plt.xticks(ind+width/2., LABS)
# plt.yticks(np.arange(0,81,10))
plt.legend(p, ('{} other lab(s)'.format(LAB_NUMBER-x-1) for x in range(LAB_NUMBER)))
######################################
### Number of sessions per student ###
######################################
session_counter = []
tem_data = data_set.sort_by(lambda x: x['a_time']).group_by(lambda x: x['student'])
for item in tem_data:
# WARNING: This may throw an exception!
session_cnt = toolkit.get_session_info(item[1])
if session_cnt == 0:
continue
while session_cnt > len(session_counter):
session_counter.append(0)
session_counter[session_cnt-1] += 1
# Print it out
fig, ax = toolkit.prepare_plot(gridWidth=0)
x = np.arange(len(session_counter))
width = 0.5
rects = plt.bar(x, session_counter, width, color='gray', alpha=0.7, edgecolor="gray")
plt.ylabel('Number of students')
plt.xticks(x + width/2., ["{:,} session(s)".format(item+1) for item in range(len(session_counter))])
toolkit.autolabel(rects, ax)
plt.savefig('session_cnt.png')
########################################
### Number of submissions per prompt ###
########################################
submission_counter = [0] * NUM_QUESTION
for prompt in range(NUM_QUESTION):
submission_counter[prompt] = data_set.filter_by(lambda x: x['specifier']==prompt).count()