Commit 98a7442a by Manuel Günther

### Switched to Numpy style documentation

parent a7a9b143
Pipeline #11466 passed with stages
in 12 minutes and 22 seconds
 ... ... @@ -254,9 +254,7 @@ def recognition_rate(cmc_scores, threshold = None, rank = 1): def cmc(cmc_scores): """cmc(cmc_scores) -> array Calculates the cumulative match characteristic (CMC) from the given input. """Calculates the cumulative match characteristic (CMC) from the given input. The input has a specific format, which is a list of two-element tuples. Each of the tuples contains the negative and the positive scores for one probe ... ... @@ -278,26 +276,29 @@ def cmc(cmc_scores): instead. Parameters: Parameters ---------- cmc_scores (:py:class:`list`): A list in the format ``[(negatives, positives), ...]`` containing the CMC scores loaded with one of the functions (:py:func:`bob.measure.load.cmc_four_column` or :py:func:`bob.measure.load.cmc_five_column`). cmc_scores : :py:class:`list` A list in the format ``[(negatives, positives), ...]`` containing the CMC scores loaded with one of the functions :py:func:`bob.measure.load.cmc_four_column`, :py:func:`bob.measure.load.cmc_five_column`, or :py:func:`bob.measure.load.cmc`. Each pair contains the ``negative`` and the ``positive`` scores for **one probe item**. Each pair can contain up to one empty array (or ``None``), i.e., in case of open set recognition. Returns: Returns ------- array: 1D :py:class:`numpy.ndarray` of `float` A 1D float array representing the CMC curve. The rank 1 recognition rate can be found in ``array[0]``, rank 2 rate in ``array[1]``, and so on. The number of ranks (``array.shape[0]``) is the number of gallery items. Values are in range ``[0,1]``. """ # If no scores are given, we cannot plot anything ... ...
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