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apk() now handles None checks on numpy arrays #24

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11 changes: 7 additions & 4 deletions Python/ml_metrics/average_precision.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,12 @@ def apk(actual, predicted, k=10):
The average precision at k over the input lists

"""
if actual is None or len(actual) == 0:
return 0.0

if predicted is None or len(predicted) == 0:
return 0.0

if len(predicted)>k:
predicted = predicted[:k]

Expand All @@ -33,9 +39,6 @@ def apk(actual, predicted, k=10):
num_hits += 1.0
score += num_hits / (i+1.0)

if not actual:
return 0.0

return score / min(len(actual), k)

def mapk(actual, predicted, k=10):
Expand All @@ -48,7 +51,7 @@ def mapk(actual, predicted, k=10):
Parameters
----------
actual : list
A list of lists of elements that are to be predicted
A list of lists of elements that are to be predicted
(order doesn't matter in the lists)
predicted : list
A list of lists of predicted elements
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13 changes: 12 additions & 1 deletion Python/ml_metrics/test/test_average_precision.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,9 +9,20 @@ class TestAveragePrecision(unittest.TestCase):
def test_apk(self):
self.assertAlmostEqual(metrics.apk(range(1,6),[6,4,7,1,2], 2), 0.25)
self.assertAlmostEqual(metrics.apk(range(1,6),[1,1,1,1,1], 5), 0.2)
predicted = range(1,21)
predicted = list(range(1,21))
predicted.extend(range(200,600))
self.assertAlmostEqual(metrics.apk(range(1,100),predicted, 20), 1.0)
# numpy array test
self.assertAlmostEqual(metrics.apk(np.asarray(range(1,100)),predicted, 20), 1.0)
self.assertAlmostEqual(metrics.apk(range(1,100), np.asarray(predicted), 20), 1.0)


def test_apk_empties(self):
self.assertAlmostEqual(metrics.apk([], [1, 3], 20), 0.0)
self.assertAlmostEqual(metrics.apk(None, [1, 2], 20), 0.0)
self.assertAlmostEqual(metrics.apk([1, 3], [], 20), 0.0)
self.assertAlmostEqual(metrics.apk([1, 2], None, 20), 0.0)


def test_mapk(self):
self.assertAlmostEqual(metrics.mapk([range(1,5)],[range(1,5)],3), 1.0)
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