Commit 3fe154b9 authored by Theophile GENTILHOMME's avatar Theophile GENTILHOMME

Fix code and doc after removing the bio-related files

parent caea2795
Pipeline #17700 canceled with stage
......@@ -7,9 +7,7 @@ from . import version
from .version import module as __version__
from . import plot
from . import load
from . import calibration
from . import openbr
import numpy
def mse (estimation, target):
......@@ -134,9 +132,7 @@ def recognition_rate(cmc_scores, threshold = None, rank = 1):
The input has a specific format, which is a list of two-element tuples. Each
of the tuples contains the negative :math:`\\{S_p^-\\}` and the positive
:math:`\\{S_p^+\\}` scores for one probe item :math:`p`, or ``None`` in case
of open set recognition. To read the lists from score files in 4 or 5 column
format, please use the :py:func:`bob.measure.load.cmc_four_column` or
:py:func:`bob.measure.load.cmc_five_column` function.
of open set recognition.
If ``threshold`` is set to ``None``, the rank 1 recognition rate is defined
as the number of test items, for which the highest positive
......@@ -172,9 +168,9 @@ def recognition_rate(cmc_scores, threshold = None, rank = 1):
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`).
positives), ...]`` containing the CMC scores (i.e. :py:class:`list`:
A list of tuples, where each tuple contains the
``negative`` and ``positive`` scores for one probe of the database).
Each pair contains the ``negative`` and the ``positive`` scores for **one
probe item**. Each pair can contain up to one empty array (or ``None``),
......@@ -258,9 +254,7 @@ def cmc(cmc_scores):
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
item. To read the lists from score files in 4 or 5 column format, please use
the :py:func:`bob.measure.load.cmc_four_column` or
:py:func:`bob.measure.load.cmc_five_column` function.
item.
For each probe item the probability that the rank :math:`r` of the positive
score is calculated. The rank is computed as the number of negative scores
......@@ -281,10 +275,7 @@ def cmc(cmc_scores):
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`.
scores.
Each pair contains the ``negative`` and the ``positive`` scores for **one
probe item**. Each pair can contain up to one empty array (or ``None``),
......@@ -345,9 +336,7 @@ def detection_identification_rate(cmc_scores, threshold, rank = 1):
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`).
positives), ...]`` containing the 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``),
......@@ -406,9 +395,9 @@ def false_alarm_rate(cmc_scores, threshold):
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`).
positives), ...]`` containing the CMC scores (i.e. :py:class:`list`:
A list of tuples, where each tuple contains the
``negative`` and ``positive`` scores for one probe of the database).
Each pair contains the ``negative`` and the ``positive`` scores for **one
probe item**. Each pair can contain up to one empty array (or ``None``),
......
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