def random_vs_ttc(n_courses, n_students, min_cap, max_cap, iters):
"""
Compare RandomLottery outcome with RL+TTC outcome.
"""
f = Factory(n_courses, n_students, min_cap, max_cap)
student_diffs = []
total_diffs = []
mean_student_diffs = []
for i in xrange(iters):
courses, students = f.generate()
# Run the RandomLottery
rl = RandomLottery(courses, students)
rl_students = rl.run()
rl_utils = [s.get_studycard_value() for s in rl.students]
rl_welfare = sum(rl_utils)
# Run TTC on the output of RandomLottery
ttc = TTC(deepcopy(rl_students))
ttc.run()
ttc_utils = [s.get_studycard_value() for s in ttc.students]
ttc_welfare = sum(ttc_utils)
# Compute summary statistics
total_diff = (ttc_welfare - rl_welfare) / float(ttc_welfare + rl_welfare) * 100
total_diffs.append(total_diff)
student_diff = [(t - r) / float(t + r) * 100 if t +
r else 0 for t, r in zip(ttc_utils, rl_utils)]
student_diffs.append(student_diff)
mean_student_diff = np.mean(student_diff)
mean_student_diffs.append(mean_student_diff)
print
print "=========================================="
print "Overall Welfare Improvement (%): "
print "mean: ", np.mean(total_diffs), "std: ", np.std(total_diffs)
print "=========================================="
print "Mean Individual Welfare Improvement (%):"
print "mean: ", np.mean(mean_student_diffs), "std: ", np.std(mean_student_diffs)
print "=========================================="
print
return student_diffs, total_diffs, mean_student_diffs
