for probability in probabilities:
y_axis_data.append(logarithmic_score(probability))
plt.plot(x_axis_data, y_axis_data)
plt.xlabel("Probability assigned to correct answer")
plt.ylabel("Logarithmic score")
plt.title("Logarithmic score for probabilities 1 % - 99 %")
plt.draw()
plt.savefig("docs/charts/logarithmic.svg")
plt.clf()
y_axis_data = []
for probability in probabilities:
y_axis_data.append(practical_score(probability))
plt.plot(x_axis_data, y_axis_data)
plt.xlabel("Probability assigned to correct answer")
plt.ylabel("Practical score")
plt.title("Practical score for probabilities 1 % - 99 %")
plt.draw()
plt.savefig("docs/charts/practical.svg")
plt.clf()
y_axis_data = []
for probability in probabilities:
y_axis_data.append(quadratic_score(probability))
def test_max(self):
assert practical_score(0.9999) == approximately(2)
def test_80_percent(self):
assert practical_score(0.80) == approximately(1.356)
def test_50_percent(self):
assert practical_score(0.50) == 0
def test_20_percent(self):
assert practical_score(0.20) == approximately(-2.644)
def test_0_percent(self):
with pytest.raises(AssertionError):
assert practical_score(0.0) == 0