Commit 3991aee9 authored by Manuel Günther's avatar Manuel Günther

Fixed doctest outputs (which are based on random values) not to be written any more

parent 4ef35122
...@@ -189,8 +189,7 @@ For each probe item, the scores for negative and positive comparisons are comput ...@@ -189,8 +189,7 @@ For each probe item, the scores for negative and positive comparisons are comput
... pos = numpy.random.normal(1, 1, 1) ... pos = numpy.random.normal(1, 1, 1)
... neg = numpy.random.normal(0, 1, 19) ... neg = numpy.random.normal(0, 1, 19)
... rr_scores.append((neg, pos)) ... rr_scores.append((neg, pos))
>>> bob.measure.recognition_rate(rr_scores, rank=1) >>> rr = bob.measure.recognition_rate(rr_scores, rank=1)
0.3
For open set identification, according to Li and Jain (2005) there are two different error measures defined. For open set identification, according to Li and Jain (2005) there are two different error measures defined.
The first measure is the :py:func:`bob.measure.detection_identification_rate`, which counts the number of correctly classified in-gallery probe items. The first measure is the :py:func:`bob.measure.detection_identification_rate`, which counts the number of correctly classified in-gallery probe items.
...@@ -206,10 +205,8 @@ Both functions require that at least one probe item exists, which has no accordi ...@@ -206,10 +205,8 @@ Both functions require that at least one probe item exists, which has no accordi
... pos = None ... pos = None
... neg = numpy.random.normal(-2, 1, 10) ... neg = numpy.random.normal(-2, 1, 10)
... rr_scores.append((neg, pos)) ... rr_scores.append((neg, pos))
>>> bob.measure.detection_identification_rate(rr_scores, threshold = 0, rank=1) >>> dir = bob.measure.detection_identification_rate(rr_scores, threshold = 0, rank=1)
0.3 >>> far = bob.measure.false_alarm_rate(rr_scores, threshold = 0)
>>> bob.measure.false_alarm_rate(rr_scores, threshold = 0)
0.2
Plotting Plotting
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