diff --git a/bob/measure/load.py b/bob/measure/load.py
index 5ed4035e275ca655079466ad5d90b727a1bb83c1..41e6e6cbf29ce9f486b04d8111c00e0d40aaa493 100644
--- a/bob/measure/load.py
+++ b/bob/measure/load.py
@@ -263,6 +263,92 @@ def cmc_five_column(filename):
return _split_cmc_scores(score_lines, 2)
+def scores(filename, ncolumns=None):
+ """scores(filename, ncolumns=None) -> tuple
+
+ Loads the scores from the given score file and yield its lines.
+ Depending on the score file format, four or five elements are yielded, see :py:func:`bob.measure.load.four_column` and :py:func:`bob.measure.load.five_column` for details.
+
+ Parameters:
+
+ filename: :py:class:`str`, ``file-like``:
+ The file object that will be opened with :py:func:`open_file` containing the scores.
+
+ ncolumns: any
+ ignored
+
+ Yields:
+
+ tuple:
+ see :py:func:`bob.measure.load.four_column` or :py:func:`bob.measure.load.five_column`
+ """
+ return _iterate_score_file(filename)
+
+
+def split(filename, ncolumns=None):
+ """split(filename, ncolumns=None) -> negatives, positives
+
+ Loads the scores from the given score file and splits them into positives and negatives.
+
+ Depending on the score file format, it calls see :py:func:`bob.measure.load.split_four_column` and `:py:func:`bob.measure.load.split_five_column` for details.
+
+ Parameters:
+
+ filename: :py:class:`str`, ``file-like``:
+ The file object that will be opened with :py:func:`open_file` containing the scores.
+
+ ncolumns: int or ``None``
+ If specified to be ``4`` or ``5``, the score file will be assumed to be in the given format.
+ If not specified, the score file format will be estimated automatically
+
+ Returns:
+
+ negatives: 1D :py:class:`numpy.ndarray` of type float
+ This array contains the list of scores, for which the ``claimed_id`` and the ``real_id`` are different (see :py:func:`four_column`)
+
+ positives: 1D :py:class:`numpy.ndarray` of type float
+ This array contains the list of scores, for which the ``claimed_id`` and the ``real_id`` are identical (see :py:func:`four_column`)
+
+ """
+ ncolumns = _estimate_score_file_format(filename, ncolumns)
+ if ncolumns == 4:
+ return split_four_column(filename)
+ else:
+ assert ncolumns == 5
+ return split_five_column(filename)
+
+
+def cmc(filename, ncolumns=None):
+ """cmc(filename, ncolumns=None) -> list
+
+ Loads scores to compute CMC curves.
+
+ Depending on the score file format, it calls see :py:func:`bob.measure.load.cmc_four_column` and `:py:func:`bob.measure.load.cmc_five_column` for details.
+
+ Parameters:
+
+ filename: :py:class:`str`, ``file-like``:
+ The file object that will be opened with :py:func:`open_file` containing the scores.
+
+ ncolumns: int or ``None``
+ If specified to be ``4`` or ``5``, the score file will be assumed to be in the given format.
+ If not specified, the score file format will be estimated automatically
+
+ Returns:
+
+ list: [(neg,pos)]
+ A list of tuples, where each tuple contains the ``negative`` and
+ ``positive`` scores for one probe of the database.
+ """
+ ncolumns = _estimate_score_file_format(filename, ncolumns)
+ if ncolumns == 4:
+ return cmc_four_column(filename)
+ else:
+ assert ncolumns == 5
+ return cmc_five_column(filename)
+
+
+
def load_score(filename, ncolumns=None, minimal=False, **kwargs):
"""Load scores using numpy.loadtxt and return the data as a numpy array.
@@ -291,17 +377,7 @@ def load_score(filename, ncolumns=None, minimal=False, **kwargs):
def convertfunc(x):
return x
- if ncolumns not in (4, 5):
- f = open_file(filename)
- try:
- line = f.readline()
- ncolumns = len(line.split())
- except Exception:
- logger.warn('Could not guess the number of columns in file: {}. '
- 'Assuming 4 column format.'.format(filename))
- ncolumns = 4
- finally:
- f.close()
+ ncolumns = _estimate_score_file_format(filename, ncolumns)
usecols = kwargs.pop('usecols', None)
if ncolumns == 4:
@@ -393,6 +469,26 @@ def dump_score(filename, score_lines):
numpy.savetxt(filename, score_lines, fmt=fmt)
+def _estimate_score_file_format(filename, ncolumns=None):
+ """Estimates the score file format from the given score file.
+ If ``ncolumns`` is in ``(4,5)``, then ``ncolumns`` is returned instead.
+ """
+ if ncolumns in (4, 5):
+ return ncolumns
+
+ f = open_file(filename, 'rb')
+ try:
+ line = f.readline()
+ ncolumns = len(line.split())
+ except Exception:
+ logger.warn('Could not guess the number of columns in file: {}. '
+ 'Assuming 4 column format.'.format(filename))
+ ncolumns = 4
+ finally:
+ f.close()
+ return ncolumns
+
+
def _iterate_score_file(filename):
"""Opens the score file for reading and yields the score file line by line in a tuple/list.
diff --git a/bob/measure/script/plot_cmc.py b/bob/measure/script/plot_cmc.py
index 583b2036ecedf3c6a5739401982cc6d883fd645c..d2d6dd16b657a9815da073a4139eb7ceb50500f2 100644
--- a/bob/measure/script/plot_cmc.py
+++ b/bob/measure/script/plot_cmc.py
@@ -75,21 +75,7 @@ def main(user_input=None):
from .. import load
# Loads score file
- f = load.open_file(args['<scores>'])
- try:
- line = f.readline()
- ncolumns = len(line.split())
- except Exception:
- logger.warn('Could not guess the number of columns in file: {}. '
- 'Assuming 4 column format.'.format(args['<scores>']))
- ncolumns = 4
- finally:
- f.close()
-
- if ncolumns == 4:
- data = load.cmc_four_column(args['<scores>'])
- else:
- data = load.cmc_five_column(args['<scores>'])
+ data = load.cmc(args['<scores>'])
# compute recognition rate
from .. import recognition_rate
diff --git a/bob/measure/test_error.py b/bob/measure/test_error.py
index 65b70787ce9aafbc7025505fd298566933bad416..75de57c811e2f6760712cfec84470ad60a1d8d9b 100644
--- a/bob/measure/test_error.py
+++ b/bob/measure/test_error.py
@@ -308,6 +308,13 @@ def test_cmc():
cmc_ = cmc(data)
assert (cmc_ == desired_cmc).all()
+ data = load.cmc(F('scores-cmc-5col.txt'))
+ rr = recognition_rate(data)
+ nose.tools.eq_(rr, desired_rr)
+ cmc_ = cmc(data)
+ assert (cmc_ == desired_cmc).all()
+
+
def test_calibration():
@@ -342,7 +349,7 @@ def test_calibration():
def test_open_set_rates():
# No error files
- cmc_scores = bob.measure.load.cmc_four_column(F("scores-cmc-4col-open-set.txt"))
+ cmc_scores = bob.measure.load.cmc(F("scores-cmc-4col-open-set.txt"))
assert abs(bob.measure.detection_identification_rate(cmc_scores, threshold=0.5) - 1.0) < 1e-8
assert abs(bob.measure.false_alarm_rate(cmc_scores, threshold=0.5)) < 1e-8
@@ -350,7 +357,7 @@ def test_open_set_rates():
assert abs(bob.measure.recognition_rate(cmc_scores, threshold=0.5) - 1.0) < 1e-8
# One error
- cmc_scores = bob.measure.load.cmc_four_column(F("scores-cmc-4col-open-set-one-error.txt"))
+ cmc_scores = bob.measure.load.cmc(F("scores-cmc-4col-open-set-one-error.txt"))
assert abs(bob.measure.detection_identification_rate(cmc_scores, threshold=0.5) - 6./7.) < 1e-8
assert abs(bob.measure.false_alarm_rate(cmc_scores, threshold=0.5)) < 1e-8
diff --git a/bob/measure/test_io.py b/bob/measure/test_io.py
index ad62468bb1f99fb7748633644705b60aae01a25d..84fdc3d9eac8d47c34fcaab95b57ce810eb7b6e5 100644
--- a/bob/measure/test_io.py
+++ b/bob/measure/test_io.py
@@ -16,7 +16,6 @@ import bob.io.base.test_utils
def test_load_scores():
# This function tests the IO functionality of loading score files in different ways
- scores = []
load_functions = {'4col' : bob.measure.load.four_column, '5col' : bob.measure.load.five_column}
cols = {'4col' : 4, '5col' : 5}
@@ -36,6 +35,55 @@ def test_load_scores():
assert all(len(c) == cols[variant] for c in compressed_scores)
assert all(c[i] == s[i] for c,s in zip(compressed_scores, normal_scores) for i in range(cols[variant]))
+ ### Use auto-estimated score file contents
+ # read score file in normal way
+ normal_scores = list(bob.measure.load.scores(normal_score_file))
+
+ assert len(normal_scores) == 910
+ assert all(len(s) == cols[variant] for s in normal_scores)
+
+ # read the compressed score file
+ compressed_scores = list(bob.measure.load.scores(compressed_score_file))
+
+ assert len(compressed_scores) == len(normal_scores)
+ assert all(len(c) == cols[variant] for c in compressed_scores)
+ assert all(c[i] == s[i] for c,s in zip(compressed_scores, normal_scores) for i in range(cols[variant]))
+
+
+def test_split_scores():
+ # This function tests the IO functionality of loading score files in different ways
+
+ split_functions = {'4col' : bob.measure.load.split_four_column, '5col' : bob.measure.load.split_five_column}
+ cols = {'4col' : 4, '5col' : 5}
+
+ for variant in cols:
+ # read score file in normal way
+ normal_score_file = bob.io.base.test_utils.datafile('dev-%s.txt' % variant, 'bob.measure')
+ negatives, positives = split_functions[variant](normal_score_file)
+
+ assert len(negatives) == 520, len(negatives)
+ assert len(positives) == 390, len(positives)
+
+ # read the compressed score file
+ compressed_score_file = bob.io.base.test_utils.datafile('dev-%s.tar.gz' % variant, 'bob.measure')
+ negatives, positives = split_functions[variant](compressed_score_file)
+
+ assert len(negatives) == 520, len(negatives)
+ assert len(positives) == 390, len(positives)
+
+ ### Use auto-estimated score file contents
+ # read score file in normal way
+ negatives, positives = bob.measure.load.split(normal_score_file)
+
+ assert len(negatives) == 520, len(negatives)
+ assert len(positives) == 390, len(positives)
+
+ # read the compressed score file
+ negatives, positives = bob.measure.load.split(compressed_score_file)
+
+ assert len(negatives) == 520, len(negatives)
+ assert len(positives) == 390, len(positives)
+
def test_load_score():
# This function tests the IO functionality of loading score files in different ways
diff --git a/doc/guide.rst b/doc/guide.rst
index d08f4e928002305afbccbcdac21f85c16b79f044..44c3b2fff38e7d5dd204d48f5fed939210d8549f 100644
--- a/doc/guide.rst
+++ b/doc/guide.rst
@@ -390,8 +390,7 @@ Usually, there is only a single positive score per probe, but this is not a fixe
.. note::
The complex data structure can be read from our default 4 or 5 column score
- files using the :py:func:`bob.measure.load.cmc_four_column` or
- :py:func:`bob.measure.load.cmc_five_column` function.
+ files using the :py:func:`bob.measure.load.cmc` function.
Detection & Identification Curve
diff --git a/doc/py_api.rst b/doc/py_api.rst
index 55875a92b94c8a24bf4aec29a617777b37265529..356a55aeeda08114413e06932eacfff1b1a8b7c3 100644
--- a/doc/py_api.rst
+++ b/doc/py_api.rst
@@ -69,6 +69,9 @@ Loading data
.. autosummary::
bob.measure.load.open_file
+ bob.measure.load.scores
+ bob.measure.load.split
+ bob.measure.load.cmc
bob.measure.load.four_column
bob.measure.load.split_four_column
bob.measure.load.cmc_four_column