From 10bec60c9f6e645b604f486537410a43ac44a792 Mon Sep 17 00:00:00 2001
From: Amir MOHAMMADI <amir.mohammadi@idiap.ch>
Date: Fri, 25 Feb 2022 15:20:20 +0100
Subject: [PATCH] pre-commit required changes
---
CHANGELOG | 2 +-
bob/__init__.py | 1 +
bob/fusion/__init__.py | 1 +
bob/fusion/base/__init__.py | 18 +-
bob/fusion/base/algorithm/AND.py | 13 +-
bob/fusion/base/algorithm/Algorithm.py | 34 ++-
bob/fusion/base/algorithm/AlgorithmBob.py | 12 +-
bob/fusion/base/algorithm/Empty.py | 10 +-
bob/fusion/base/algorithm/GMM.py | 20 +-
bob/fusion/base/algorithm/Weighted_Sum.py | 13 +-
bob/fusion/base/algorithm/__init__.py | 16 +-
bob/fusion/base/config/algorithm/gmm.py | 6 +-
bob/fusion/base/config/algorithm/llr_skl.py | 12 +-
bob/fusion/base/config/algorithm/mean.py | 9 +-
bob/fusion/base/config/algorithm/plr_2.py | 13 +-
bob/fusion/base/config/algorithm/plr_3.py | 13 +-
bob/fusion/base/preprocessor/Tanh.py | 8 +-
bob/fusion/base/preprocessor/ZNorm.py | 8 +-
bob/fusion/base/preprocessor/__init__.py | 12 +-
bob/fusion/base/script/__init__.py | 4 +-
bob/fusion/base/script/boundary.py | 34 ++-
bob/fusion/base/script/fuse.py | 317 +++++++++++++-------
bob/fusion/base/script/fusion.py | 4 +-
bob/fusion/base/script/resource.py | 37 ++-
bob/fusion/base/test/test_algorithm.py | 12 +-
bob/fusion/base/test/test_preprocessor.py | 50 ++-
bob/fusion/base/test/test_scripts.py | 12 +-
bob/fusion/base/tools/__init__.py | 6 +-
bob/fusion/base/tools/common.py | 67 +++--
bob/fusion/base/tools/plotting.py | 8 +-
buildout.cfg | 2 +-
develop.cfg | 1 -
doc/conf.py | 150 ++++-----
setup.py | 83 +++--
34 files changed, 585 insertions(+), 423 deletions(-)
diff --git a/CHANGELOG b/CHANGELOG
index 538671e..725a87c 100644
--- a/CHANGELOG
+++ b/CHANGELOG
@@ -1 +1 @@
-2.0.0 Initial stable release of the package.
\ No newline at end of file
+2.0.0 Initial stable release of the package.
diff --git a/bob/__init__.py b/bob/__init__.py
index 2ab1e28..edbb409 100644
--- a/bob/__init__.py
+++ b/bob/__init__.py
@@ -1,3 +1,4 @@
# see https://docs.python.org/3/library/pkgutil.html
from pkgutil import extend_path
+
__path__ = extend_path(__path__, __name__)
diff --git a/bob/fusion/__init__.py b/bob/fusion/__init__.py
index 2ab1e28..edbb409 100644
--- a/bob/fusion/__init__.py
+++ b/bob/fusion/__init__.py
@@ -1,3 +1,4 @@
# see https://docs.python.org/3/library/pkgutil.html
from pkgutil import extend_path
+
__path__ = extend_path(__path__, __name__)
diff --git a/bob/fusion/base/__init__.py b/bob/fusion/base/__init__.py
index 24c6385..0a5e912 100644
--- a/bob/fusion/base/__init__.py
+++ b/bob/fusion/base/__init__.py
@@ -1,14 +1,12 @@
-from . import algorithm
-from . import preprocessor
-from . import tools
-from . import config
-from . import script
+from . import algorithm, config, preprocessor, script, tools # noqa: F401
+
def get_config():
- """Returns a string containing the configuration information.
- """
- import bob.extension
- return bob.extension.get_config(__name__)
+ """Returns a string containing the configuration information."""
+ import bob.extension
+
+ return bob.extension.get_config(__name__)
+
# gets sphinx autodoc done right - don't remove it
-__all__ = [_ for _ in dir() if not _.startswith('_')]
+__all__ = [_ for _ in dir() if not _.startswith("_")]
diff --git a/bob/fusion/base/algorithm/AND.py b/bob/fusion/base/algorithm/AND.py
index 7c10589..2f2b6ac 100644
--- a/bob/fusion/base/algorithm/AND.py
+++ b/bob/fusion/base/algorithm/AND.py
@@ -1,14 +1,13 @@
#!/usr/bin/env python
-from __future__ import division
-from __future__ import absolute_import
+from __future__ import absolute_import, division
+
+import logging
import numpy
from .Algorithm import Algorithm
-import logging
-
logger = logging.getLogger(__name__)
@@ -18,14 +17,14 @@ class AND(Algorithm):
def __init__(self, thresholds=None, **kwargs):
super(AND, self).__init__(classifier=self, **kwargs)
self.thresholds = thresholds
- self.str['thresholds'] = thresholds
+ self.str["thresholds"] = thresholds
def fit(self, X, y):
pass
def decision_function(self, scores):
if self.thresholds is None:
- ValueError('No threshold was specified.')
+ ValueError("No threshold was specified.")
for i, th in enumerate(self.thresholds):
mask = scores[:, i + 1] < th
@@ -33,5 +32,5 @@ class AND(Algorithm):
mask = numpy.sum(numpy.isnan(scores[:, 1:]), axis=1, dtype=bool)
new_scores = numpy.array(scores[0])
- new_scores[mask] = numpy.finfo('float16').min
+ new_scores[mask] = numpy.finfo("float16").min
return new_scores
diff --git a/bob/fusion/base/algorithm/Algorithm.py b/bob/fusion/base/algorithm/Algorithm.py
index ece889d..aac95cd 100644
--- a/bob/fusion/base/algorithm/Algorithm.py
+++ b/bob/fusion/base/algorithm/Algorithm.py
@@ -1,12 +1,11 @@
#!/usr/bin/env python
-from __future__ import division
-from __future__ import absolute_import
+from __future__ import absolute_import, division
-import numpy as np
+import logging
import pickle
-import logging
+import numpy as np
logger = logging.getLogger(__name__)
@@ -22,11 +21,7 @@ class Algorithm(object):
A dictionary that its content will printed in the __str__ method.
"""
- def __init__(self,
- preprocessors=None,
- classifier=None,
- **kwargs
- ):
+ def __init__(self, preprocessors=None, classifier=None, **kwargs):
"""
Parameters
----------
@@ -44,9 +39,9 @@ class Algorithm(object):
super(Algorithm, self).__init__(**kwargs)
self.classifier = classifier
self.preprocessors = preprocessors
- self.str = {'preprocessors': preprocessors}
+ self.str = {"preprocessors": preprocessors}
if classifier is not self:
- self.str['classifier'] = classifier
+ self.str["classifier"] = classifier
def train_preprocessors(self, X, y=None):
"""Train preprocessors in order.
@@ -81,7 +76,7 @@ class Algorithm(object):
"""
train_scores = np.vstack((train_neg, train_pos))
neg_len = train_neg.shape[0]
- y = np.zeros((train_scores.shape[0],), dtype='bool')
+ y = np.zeros((train_scores.shape[0],), dtype="bool")
y[neg_len:] = True
self.classifier.fit(train_scores, y)
@@ -107,9 +102,16 @@ class Algorithm(object):
A string containing the full information of all parameters of this
(and the derived) class.
"""
- return "%s(%s)" % (str(self.__class__), ", ".join(
- ["%s=%s" % (key, value) for key, value in
- self.str.items() if value is not None]))
+ return "%s(%s)" % (
+ str(self.__class__),
+ ", ".join(
+ [
+ "%s=%s" % (key, value)
+ for key, value in self.str.items()
+ if value is not None
+ ]
+ ),
+ )
def save(self, model_file):
"""Save the instance of the algorithm.
@@ -140,6 +142,6 @@ class Algorithm(object):
with open(model_file, "rb") as f:
algo_class = pickle.load(f)
algo = algo_class()
- if not hasattr(algo, 'custom_save'):
+ if not hasattr(algo, "custom_save"):
return pickle.load(f)
return algo.load(model_file)
diff --git a/bob/fusion/base/algorithm/AlgorithmBob.py b/bob/fusion/base/algorithm/AlgorithmBob.py
index be319ee..573c357 100644
--- a/bob/fusion/base/algorithm/AlgorithmBob.py
+++ b/bob/fusion/base/algorithm/AlgorithmBob.py
@@ -1,13 +1,13 @@
#!/usr/bin/env python
-from __future__ import division
-from __future__ import absolute_import
+from __future__ import absolute_import, division
+import logging
import pickle
-from .Algorithm import Algorithm
+
from h5py import File as HDF5File
-import logging
+from .Algorithm import Algorithm
logger = logging.getLogger(__name__)
@@ -16,13 +16,13 @@ class AlgorithmBob(Algorithm):
"""A class to be used in score fusion using bob machines."""
def _get_hdf5_file(self, model_file):
- return model_file[:-3] + 'hdf5'
+ return model_file[:-3] + "hdf5"
def custom_save(self, model_file):
# dump preprocessors in a pickle file because
# we don't know how they look like
# saves the class to create it later.
- with open(model_file, 'wb') as f:
+ with open(model_file, "wb") as f:
pickle.dump(type(self), f)
pickle.dump(self.preprocessors, f)
# just for consistent string representation
diff --git a/bob/fusion/base/algorithm/Empty.py b/bob/fusion/base/algorithm/Empty.py
index 8a7806a..a2ba0d2 100644
--- a/bob/fusion/base/algorithm/Empty.py
+++ b/bob/fusion/base/algorithm/Empty.py
@@ -1,11 +1,11 @@
#!/usr/bin/env python
-from __future__ import division
-from __future__ import absolute_import
+from __future__ import absolute_import, division
-from .Algorithm import Algorithm
import logging
+from .Algorithm import Algorithm
+
logger = logging.getLogger(__name__)
@@ -15,9 +15,7 @@ class Empty(Algorithm):
preprocessors."""
def __init__(self, **kwargs):
- super(Empty, self).__init__(
- classifier=self,
- **kwargs)
+ super(Empty, self).__init__(classifier=self, **kwargs)
def fit(self, X, y):
pass
diff --git a/bob/fusion/base/algorithm/GMM.py b/bob/fusion/base/algorithm/GMM.py
index 2619fe7..29c8309 100644
--- a/bob/fusion/base/algorithm/GMM.py
+++ b/bob/fusion/base/algorithm/GMM.py
@@ -1,14 +1,14 @@
#!/usr/bin/env python
-from __future__ import division
-from __future__ import absolute_import
+from __future__ import absolute_import, division
+
+import logging
import numpy as np
from bob.learn.em.mixture import GMMMachine
-from .AlgorithmBob import AlgorithmBob
-import logging
+from .AlgorithmBob import AlgorithmBob
logger = logging.getLogger("bob.fusion.base")
@@ -64,12 +64,10 @@ class GMM(AlgorithmBob):
if self.n_gaussians is None:
self.n_gaussians = array.shape[1] + 1
logger.warning(
- "Number of Gaussians was None. " "Using {}.".format(self.n_gaussians)
+ "Number of Gaussians was None. "
+ "Using {}.".format(self.n_gaussians)
)
- # Computes input size
- input_size = array.shape[1]
-
# Creates the machines (KMeans and GMM)
logger.debug("Training GMM machine")
self.machine = GMMMachine(
@@ -84,4 +82,8 @@ class GMM(AlgorithmBob):
self.machine.fit(array)
def decision_function(self, scores):
- return np.fromiter((self.machine.log_likelihood(s) for s in scores), np.float, scores.shape[0])
+ return np.fromiter(
+ (self.machine.log_likelihood(s) for s in scores),
+ np.float,
+ scores.shape[0],
+ )
diff --git a/bob/fusion/base/algorithm/Weighted_Sum.py b/bob/fusion/base/algorithm/Weighted_Sum.py
index 556a4b0..20833f6 100644
--- a/bob/fusion/base/algorithm/Weighted_Sum.py
+++ b/bob/fusion/base/algorithm/Weighted_Sum.py
@@ -1,14 +1,13 @@
#!/usr/bin/env python
-from __future__ import division
-from __future__ import absolute_import
+from __future__ import absolute_import, division
+
+import logging
import numpy
from .Algorithm import Algorithm
-import logging
-
logger = logging.getLogger(__name__)
@@ -16,11 +15,9 @@ class Weighted_Sum(Algorithm):
"""weighted sum (default: mean)"""
def __init__(self, weights=None, **kwargs):
- super(Weighted_Sum, self).__init__(
- classifier=self,
- **kwargs)
+ super(Weighted_Sum, self).__init__(classifier=self, **kwargs)
self.weights = weights
- self.str['weights'] = weights
+ self.str["weights"] = weights
def fit(self, X, y):
pass
diff --git a/bob/fusion/base/algorithm/__init__.py b/bob/fusion/base/algorithm/__init__.py
index 74ceb6e..13b7d90 100644
--- a/bob/fusion/base/algorithm/__init__.py
+++ b/bob/fusion/base/algorithm/__init__.py
@@ -1,21 +1,21 @@
from .Algorithm import Algorithm
from .AlgorithmBob import AlgorithmBob
-from .Weighted_Sum import Weighted_Sum
-from .GMM import GMM
from .Empty import Empty
+from .GMM import GMM
+from .Weighted_Sum import Weighted_Sum
# gets sphinx autodoc done right - don't remove it
def __appropriate__(*args):
"""Says object was actually declared here, an not on the import module.
- Parameters:
+ Parameters:
- *args: An iterable of objects to modify
+ *args: An iterable of objects to modify
- Resolves `Sphinx referencing issues
- <https://github.com/sphinx-doc/sphinx/issues/3048>`
- """
+ Resolves `Sphinx referencing issues
+ <https://github.com/sphinx-doc/sphinx/issues/3048>`
+ """
for obj in args:
obj.__module__ = __name__
@@ -28,4 +28,4 @@ __appropriate__(
GMM,
Empty,
)
-__all__ = [_ for _ in dir() if not _.startswith('_')]
+__all__ = [_ for _ in dir() if not _.startswith("_")]
diff --git a/bob/fusion/base/config/algorithm/gmm.py b/bob/fusion/base/config/algorithm/gmm.py
index b4dfb98..c10b5e7 100644
--- a/bob/fusion/base/config/algorithm/gmm.py
+++ b/bob/fusion/base/config/algorithm/gmm.py
@@ -1,9 +1,11 @@
#!/usr/bin/env python
-import bob.fusion.base
from sklearn.preprocessing import StandardScaler
+import bob.fusion.base
+
algorithm = bob.fusion.base.algorithm.GMM(preprocessors=[StandardScaler()])
algorithm_tanh = bob.fusion.base.algorithm.GMM(
- preprocessors=[bob.fusion.base.preprocessor.Tanh()])
+ preprocessors=[bob.fusion.base.preprocessor.Tanh()]
+)
diff --git a/bob/fusion/base/config/algorithm/llr_skl.py b/bob/fusion/base/config/algorithm/llr_skl.py
index 891fb79..b7fc05d 100644
--- a/bob/fusion/base/config/algorithm/llr_skl.py
+++ b/bob/fusion/base/config/algorithm/llr_skl.py
@@ -1,13 +1,15 @@
#!/usr/bin/env python
-import bob.fusion.base
-from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import LogisticRegression
+from sklearn.preprocessing import StandardScaler
+
+import bob.fusion.base
algorithm = bob.fusion.base.algorithm.Algorithm(
- preprocessors=[StandardScaler()],
- classifier=LogisticRegression())
+ preprocessors=[StandardScaler()], classifier=LogisticRegression()
+)
algorithm_tanh = bob.fusion.base.algorithm.Algorithm(
preprocessors=[bob.fusion.base.preprocessor.Tanh()],
- classifier=LogisticRegression())
+ classifier=LogisticRegression(),
+)
diff --git a/bob/fusion/base/config/algorithm/mean.py b/bob/fusion/base/config/algorithm/mean.py
index fecb8f1..6b3ab2c 100644
--- a/bob/fusion/base/config/algorithm/mean.py
+++ b/bob/fusion/base/config/algorithm/mean.py
@@ -1,10 +1,13 @@
#!/usr/bin/env python
-import bob.fusion.base
from sklearn.preprocessing import StandardScaler
+import bob.fusion.base
+
algorithm = bob.fusion.base.algorithm.Weighted_Sum(
- preprocessors=[StandardScaler()])
+ preprocessors=[StandardScaler()]
+)
algorithm_tanh = bob.fusion.base.algorithm.Weighted_Sum(
- preprocessors=[bob.fusion.base.preprocessor.Tanh()])
+ preprocessors=[bob.fusion.base.preprocessor.Tanh()]
+)
diff --git a/bob/fusion/base/config/algorithm/plr_2.py b/bob/fusion/base/config/algorithm/plr_2.py
index 5874566..c0c4a20 100644
--- a/bob/fusion/base/config/algorithm/plr_2.py
+++ b/bob/fusion/base/config/algorithm/plr_2.py
@@ -1,11 +1,16 @@
#!/usr/bin/env python
+from sklearn.preprocessing import PolynomialFeatures, StandardScaler
+
import bob.fusion.base
-from sklearn.preprocessing import StandardScaler, PolynomialFeatures
algorithm = bob.fusion.base.algorithm.LLR(
- preprocessors=[StandardScaler(), PolynomialFeatures(degree=2)])
+ preprocessors=[StandardScaler(), PolynomialFeatures(degree=2)]
+)
algorithm_tanh = bob.fusion.base.algorithm.LLR(
- preprocessors=[bob.fusion.base.preprocessor.Tanh(),
- PolynomialFeatures(degree=2)])
+ preprocessors=[
+ bob.fusion.base.preprocessor.Tanh(),
+ PolynomialFeatures(degree=2),
+ ]
+)
diff --git a/bob/fusion/base/config/algorithm/plr_3.py b/bob/fusion/base/config/algorithm/plr_3.py
index 675633b..e156b4f 100644
--- a/bob/fusion/base/config/algorithm/plr_3.py
+++ b/bob/fusion/base/config/algorithm/plr_3.py
@@ -1,11 +1,16 @@
#!/usr/bin/env python
+from sklearn.preprocessing import PolynomialFeatures, StandardScaler
+
import bob.fusion.base
-from sklearn.preprocessing import StandardScaler, PolynomialFeatures
algorithm = bob.fusion.base.algorithm.LLR(
- preprocessors=[StandardScaler(), PolynomialFeatures(degree=3)])
+ preprocessors=[StandardScaler(), PolynomialFeatures(degree=3)]
+)
algorithm_tanh = bob.fusion.base.algorithm.LLR(
- preprocessors=[bob.fusion.base.preprocessor.Tanh(),
- PolynomialFeatures(degree=3)])
+ preprocessors=[
+ bob.fusion.base.preprocessor.Tanh(),
+ PolynomialFeatures(degree=3),
+ ]
+)
diff --git a/bob/fusion/base/preprocessor/Tanh.py b/bob/fusion/base/preprocessor/Tanh.py
index aae1a3e..1a445c9 100644
--- a/bob/fusion/base/preprocessor/Tanh.py
+++ b/bob/fusion/base/preprocessor/Tanh.py
@@ -1,8 +1,9 @@
-from sklearn.preprocessing import StandardScaler
import numpy as np
+from sklearn.preprocessing import StandardScaler
+
# to fix the sphinx docs
-StandardScaler.__module__ = 'sklearn.preprocessing'
+StandardScaler.__module__ = "sklearn.preprocessing"
class Tanh(StandardScaler):
@@ -22,7 +23,8 @@ class Tanh(StandardScaler):
def __init__(self, copy=True, **kwargs):
"""Initialize self. See help(type(self)) for accurate signature."""
super(Tanh, self).__init__(
- copy=copy, with_mean=True, with_std=True, **kwargs)
+ copy=copy, with_mean=True, with_std=True, **kwargs
+ )
def fit(self, X, y=None):
"""Estimates the mean and standard deviation of samples.
diff --git a/bob/fusion/base/preprocessor/ZNorm.py b/bob/fusion/base/preprocessor/ZNorm.py
index 6159cf7..fab1e00 100644
--- a/bob/fusion/base/preprocessor/ZNorm.py
+++ b/bob/fusion/base/preprocessor/ZNorm.py
@@ -1,8 +1,9 @@
-from sklearn.preprocessing import StandardScaler
import numpy as np
+from sklearn.preprocessing import StandardScaler
+
# to fix the sphinx docs
-StandardScaler.__module__ = 'sklearn.preprocessing'
+StandardScaler.__module__ = "sklearn.preprocessing"
class ZNorm(StandardScaler):
@@ -16,7 +17,8 @@ class ZNorm(StandardScaler):
def __init__(self, copy=True, **kwargs):
"""Initialize self. See help(type(self)) for accurate signature."""
super(ZNorm, self).__init__(
- copy=copy, with_mean=True, with_std=True, **kwargs)
+ copy=copy, with_mean=True, with_std=True, **kwargs
+ )
def fit(self, X, y=None):
"""Estimates the mean and standard deviation of samples.
diff --git a/bob/fusion/base/preprocessor/__init__.py b/bob/fusion/base/preprocessor/__init__.py
index fb44e5f..6002b0c 100644
--- a/bob/fusion/base/preprocessor/__init__.py
+++ b/bob/fusion/base/preprocessor/__init__.py
@@ -6,13 +6,13 @@ from .ZNorm import ZNorm
def __appropriate__(*args):
"""Says object was actually declared here, an not on the import module.
- Parameters:
+ Parameters:
- *args: An iterable of objects to modify
+ *args: An iterable of objects to modify
- Resolves `Sphinx referencing issues
- <https://github.com/sphinx-doc/sphinx/issues/3048>`
- """
+ Resolves `Sphinx referencing issues
+ <https://github.com/sphinx-doc/sphinx/issues/3048>`
+ """
for obj in args:
obj.__module__ = __name__
@@ -22,4 +22,4 @@ __appropriate__(
Tanh,
ZNorm,
)
-__all__ = [_ for _ in dir() if not _.startswith('_')]
+__all__ = [_ for _ in dir() if not _.startswith("_")]
diff --git a/bob/fusion/base/script/__init__.py b/bob/fusion/base/script/__init__.py
index 203a0fa..6494818 100644
--- a/bob/fusion/base/script/__init__.py
+++ b/bob/fusion/base/script/__init__.py
@@ -1,4 +1,4 @@
-from .fuse import routine_fusion
+from .fuse import routine_fusion # noqa: F401
# gets sphinx autodoc done right - don't remove it
-__all__ = [_ for _ in dir() if not _.startswith('_')]
+__all__ = [_ for _ in dir() if not _.startswith("_")]
diff --git a/bob/fusion/base/script/boundary.py b/bob/fusion/base/script/boundary.py
index 91fc77d..55caad6 100644
--- a/bob/fusion/base/script/boundary.py
+++ b/bob/fusion/base/script/boundary.py
@@ -1,20 +1,21 @@
"""Plots the decision boundaries of fusion algorithms.
"""
import logging
+
import click
-from bob.extension.scripts.click_helper import verbosity_option
import numpy as np
from bob.bio.base.score import load_score
+from bob.extension.scripts.click_helper import verbosity_option
+from ..algorithm import Algorithm
from ..tools import (
- get_gza_from_lines_list,
check_consistency,
+ get_gza_from_lines_list,
get_scores,
- remove_nan,
grouping,
+ remove_nan,
)
-from ..algorithm import Algorithm
logger = logging.getLogger(__name__)
@@ -58,7 +59,8 @@ def plot_boundary_decision(
x_min, x_max = X[:, i1].min() - x_pad, X[:, i1].max() + x_pad
y_min, y_max = X[:, i2].min() - y_pad, X[:, i2].max() + y_pad
xx, yy = np.meshgrid(
- np.linspace(x_min, x_max, resolution), np.linspace(y_min, y_max, resolution)
+ np.linspace(x_min, x_max, resolution),
+ np.linspace(y_min, y_max, resolution),
)
contourf = None
@@ -82,10 +84,17 @@ def plot_boundary_decision(
continue
try:
plt.scatter(
- X[:, 0], X[:, 1], marker=markers[i], alpha=alpha, c=color, label=legends[i]
+ X[:, 0],
+ X[:, 1],
+ marker=markers[i],
+ alpha=alpha,
+ c=color,
+ label=legends[i],
)
except Exception as e:
- raise RuntimeError(f"matplotlib backend: {matplotlib.get_backend()}") from e
+ raise RuntimeError(
+ f"matplotlib backend: {matplotlib.get_backend()}"
+ ) from e
plt.legend(
bbox_to_anchor=(-0.05, 1.02, 1.05, 0.102),
@@ -173,7 +182,8 @@ $ bob fusion boundary -vvv {sys1,sys2}/scores-eval -m /path/to/Model.pkl
"--skip-check",
is_flag=True,
show_default=True,
- help="If True, it will skip checking for the consistency " "between scores.",
+ help="If True, it will skip checking for the consistency "
+ "between scores.",
)
@verbosity_option()
def boundary(
@@ -201,13 +211,17 @@ def boundary(
algorithm = None
if model_file:
algorithm = Algorithm().load(model_file)
- assert threshold is not None, "threshold must be provided with the model"
+ assert (
+ threshold is not None
+ ), "threshold must be provided with the model"
# load the scores
score_lines_list_eval = [load_score(path) for path in scores]
# genuine, zero effort impostor, and attack list
- idx1, gen_le, zei_le, atk_le = get_gza_from_lines_list(score_lines_list_eval)
+ idx1, gen_le, zei_le, atk_le = get_gza_from_lines_list(
+ score_lines_list_eval
+ )
# check if score lines are consistent
if not skip_check:
diff --git a/bob/fusion/base/script/fuse.py b/bob/fusion/base/script/fuse.py
index 8ad23f3..de9d050 100644
--- a/bob/fusion/base/script/fuse.py
+++ b/bob/fusion/base/script/fuse.py
@@ -1,26 +1,40 @@
"""A script to help for score fusion experiments
"""
-from __future__ import print_function, absolute_import, division
+from __future__ import absolute_import, division, print_function
+
import logging
-import click
-from bob.extension.scripts.click_helper import (
- verbosity_option, ResourceOption)
import os
+
+import click
import numpy as np
-from bob.bio.base.score import load_score, dump_score
from bob.bio.base import utils
-
-from ..tools import get_gza_from_lines_list, \
- check_consistency, get_scores, remove_nan, get_score_lines, \
- get_2negatives_1positive
+from bob.bio.base.score import dump_score, load_score
+from bob.extension.scripts.click_helper import ResourceOption, verbosity_option
+
+from ..tools import (
+ check_consistency,
+ get_2negatives_1positive,
+ get_gza_from_lines_list,
+ get_score_lines,
+ get_scores,
+ remove_nan,
+)
logger = logging.getLogger(__name__)
-def write_info(scores, algorithm, groups, output_dir, model_file, skip_check,
- force, **kwargs):
- info = '''
+def write_info(
+ scores,
+ algorithm,
+ groups,
+ output_dir,
+ model_file,
+ skip_check,
+ force,
+ **kwargs
+):
+ info = """
scores: %s
algorithm: %s
groups: %s
@@ -29,12 +43,20 @@ model_file: %s
skip_check: %s
force: %s
kwargs: %s
- ''' % (scores, algorithm, groups, output_dir, model_file, skip_check,
- force, kwargs)
+ """ % (
+ scores,
+ algorithm,
+ groups,
+ output_dir,
+ model_file,
+ skip_check,
+ force,
+ kwargs,
+ )
logger.debug(info)
- info_file = os.path.join(output_dir, 'Experiment.info')
- with open(info_file, 'w') as f:
+ info_file = os.path.join(output_dir, "Experiment.info")
+ with open(info_file, "w") as f:
f.write("Command line:\n")
f.write(str(click.get_os_args()) + "\n\n")
f.write("Configuration:\n\n")
@@ -42,24 +64,36 @@ kwargs: %s
def save_fused_scores(save_path, fused_scores, score_lines):
- score_lines['score'] = fused_scores
+ score_lines["score"] = fused_scores
gen, zei, atk, _, _, _ = get_2negatives_1positive(score_lines)
os.makedirs(os.path.dirname(save_path), exist_ok=True)
dump_score(save_path, score_lines)
- dump_score(save_path + '-licit', np.append(gen, zei))
- dump_score(save_path + '-spoof', np.append(gen, atk))
- dump_score(save_path + '-real', np.append(gen, zei))
- dump_score(save_path + '-attack', atk)
+ dump_score(save_path + "-licit", np.append(gen, zei))
+ dump_score(save_path + "-spoof", np.append(gen, atk))
+ dump_score(save_path + "-real", np.append(gen, zei))
+ dump_score(save_path + "-attack", atk)
def routine_fusion(
- algorithm, model_file,
- scores_train_lines, scores_train, train_neg, train_pos,
- fused_train_file,
- scores_dev_lines=None, scores_dev=None, dev_neg=None, dev_pos=None,
- fused_dev_file=None,
- scores_eval_lines=None, scores_eval=None, fused_eval_file=None,
- force=False, min_file_size=1000, do_training=True):
+ algorithm,
+ model_file,
+ scores_train_lines,
+ scores_train,
+ train_neg,
+ train_pos,
+ fused_train_file,
+ scores_dev_lines=None,
+ scores_dev=None,
+ dev_neg=None,
+ dev_pos=None,
+ fused_dev_file=None,
+ scores_eval_lines=None,
+ scores_eval=None,
+ fused_eval_file=None,
+ force=False,
+ min_file_size=1000,
+ do_training=True,
+):
# load the model if model_file exists and no training data was provided
if os.path.exists(model_file) and not do_training:
@@ -70,20 +104,22 @@ def routine_fusion(
if train_neg is not None and do_training:
train_scores = np.vstack((train_neg, train_pos))
neg_len = train_neg.shape[0]
- y = np.zeros((train_scores.shape[0],), dtype='bool')
+ y = np.zeros((train_scores.shape[0],), dtype="bool")
y[neg_len:] = True
algorithm.train_preprocessors(train_scores, y)
# preprocess data
if scores_train is not None:
scores_train = algorithm.preprocess(scores_train)
- train_neg, train_pos = \
- algorithm.preprocess(train_neg), algorithm.preprocess(train_pos)
+ train_neg, train_pos = algorithm.preprocess(
+ train_neg
+ ), algorithm.preprocess(train_pos)
if scores_dev is not None:
scores_dev = algorithm.preprocess(scores_dev)
- dev_neg, dev_pos = \
- algorithm.preprocess(dev_neg), algorithm.preprocess(dev_pos)
+ dev_neg, dev_pos = algorithm.preprocess(dev_neg), algorithm.preprocess(
+ dev_pos
+ )
if scores_eval is not None:
scores_eval = algorithm.preprocess(scores_eval)
@@ -91,8 +127,7 @@ def routine_fusion(
# Train the classifier
if train_neg is not None and do_training:
if utils.check_file(model_file, force, min_file_size):
- logger.info(
- "model '%s' already exists.", model_file)
+ logger.info("model '%s' already exists.", model_file)
algorithm = algorithm.load(model_file)
else:
algorithm.train(train_neg, train_pos, dev_neg, dev_pos)
@@ -101,35 +136,36 @@ def routine_fusion(
# fuse the scores (train)
if scores_train is not None:
if utils.check_file(fused_train_file, force, min_file_size):
- logger.info(
- "score file '%s' already exists.", fused_train_file)
+ logger.info("score file '%s' already exists.", fused_train_file)
else:
fused_scores_train = algorithm.fuse(scores_train)
- save_fused_scores(fused_train_file,
- fused_scores_train, scores_train_lines)
+ save_fused_scores(
+ fused_train_file, fused_scores_train, scores_train_lines
+ )
# fuse the scores (dev)
if scores_dev is not None:
if utils.check_file(fused_dev_file, force, min_file_size):
- logger.info(
- "score file '%s' already exists.", fused_dev_file)
+ logger.info("score file '%s' already exists.", fused_dev_file)
else:
fused_scores_dev = algorithm.fuse(scores_dev)
save_fused_scores(
- fused_dev_file, fused_scores_dev, scores_dev_lines)
+ fused_dev_file, fused_scores_dev, scores_dev_lines
+ )
# fuse the scores (eval)
if scores_eval is not None:
if utils.check_file(fused_eval_file, force, min_file_size):
- logger.info(
- "score file '%s' already exists.", fused_eval_file)
+ logger.info("score file '%s' already exists.", fused_eval_file)
else:
fused_scores_eval = algorithm.fuse(scores_eval)
save_fused_scores(
- fused_eval_file, fused_scores_eval, scores_eval_lines)
+ fused_eval_file, fused_scores_eval, scores_eval_lines
+ )
-@click.command(epilog='''\b
+@click.command(
+ epilog="""\b
Examples:
# normal score fusion using the mean algorithm:
$ bob fusion fuse -vvv sys1/scores-{world,dev,eval} sys2/scores-{world,dev,eval} -a mean
@@ -143,34 +179,68 @@ $ bob fusion fuse -vvv {sys1,sys2}/scores-{dev,dev,eval} -a mean
$ bob fusion fuse -vvv {sys1,sys2}/scores-{world,dev} -g train -g dev -a mean
# run fusion with bio and pad systems:
$ bob fusion fuse -vvv sys_bio/scores-{world,dev,eval} sys_pad/scores-{train,dev,eval} -a mean
-''')
-@click.argument('scores', nargs=-1, required=True,
- type=click.Path(exists=True))
-@click.option('--algorithm', '-a', required=True, cls=ResourceOption,
- entry_point_group='bob.fusion.algorithm',
- help='The fusion algorithm '
- '(:any:`bob.fusion.algorithm.Algorithm`).')
-@click.option('--groups', '-g', default=('train', 'dev', 'eval'),
- multiple=True, show_default=True,
- type=click.Choice(('train', 'dev', 'eval')),
- help='The groups of the scores. This should correspond to the '
- 'scores that are provided. The order of options are important '
- 'and should be in the same order as (train, dev, eval). Repeat '
- 'this option for multiple values.')
-@click.option('--output-dir', '-o', required=True, default='fusion_result',
- show_default=True,
- type=click.Path(writable=True),
- help='The directory to save the annotations.')
-@click.option('--model-file', '-m',
- help='The path to where the algorithm will be saved/loaded.')
-@click.option('--skip-check', is_flag=True, show_default=True,
- help='If True, it will skip checking for '
- 'the consistency between scores.')
-@click.option('--force', '-f', is_flag=True, show_default=True,
- help='Whether to overwrite existing files.')
+"""
+)
+@click.argument("scores", nargs=-1, required=True, type=click.Path(exists=True))
+@click.option(
+ "--algorithm",
+ "-a",
+ required=True,
+ cls=ResourceOption,
+ entry_point_group="bob.fusion.algorithm",
+ help="The fusion algorithm " "(:any:`bob.fusion.algorithm.Algorithm`).",
+)
+@click.option(
+ "--groups",
+ "-g",
+ default=("train", "dev", "eval"),
+ multiple=True,
+ show_default=True,
+ type=click.Choice(("train", "dev", "eval")),
+ help="The groups of the scores. This should correspond to the "
+ "scores that are provided. The order of options are important "
+ "and should be in the same order as (train, dev, eval). Repeat "
+ "this option for multiple values.",
+)
+@click.option(
+ "--output-dir",
+ "-o",
+ required=True,
+ default="fusion_result",
+ show_default=True,
+ type=click.Path(writable=True),
+ help="The directory to save the annotations.",
+)
+@click.option(
+ "--model-file",
+ "-m",
+ help="The path to where the algorithm will be saved/loaded.",
+)
+@click.option(
+ "--skip-check",
+ is_flag=True,
+ show_default=True,
+ help="If True, it will skip checking for "
+ "the consistency between scores.",
+)
+@click.option(
+ "--force",
+ "-f",
+ is_flag=True,
+ show_default=True,
+ help="Whether to overwrite existing files.",
+)
@verbosity_option()
-def fuse(scores, algorithm, groups, output_dir, model_file, skip_check, force,
- **kwargs):
+def fuse(
+ scores,
+ algorithm,
+ groups,
+ output_dir,
+ model_file,
+ skip_check,
+ force,
+ **kwargs
+):
"""Score fusion
The script takes several scores from different biometric and pad systems
@@ -192,39 +262,49 @@ def fuse(scores, algorithm, groups, output_dir, model_file, skip_check, force,
os.makedirs(output_dir, exist_ok=True)
if not model_file:
do_training = True
- model_file = os.path.join(output_dir, 'Model.pkl')
+ model_file = os.path.join(output_dir, "Model.pkl")
else:
do_training = False
- fused_train_file = os.path.join(output_dir, 'scores-train')
- fused_dev_file = os.path.join(output_dir, 'scores-dev')
- fused_eval_file = os.path.join(output_dir, 'scores-eval')
+ fused_train_file = os.path.join(output_dir, "scores-train")
+ fused_dev_file = os.path.join(output_dir, "scores-dev")
+ fused_eval_file = os.path.join(output_dir, "scores-eval")
if not len(scores) % len(groups) == 0:
raise click.BadArgumentUsage(
- 'The number of scores must be a multiple of the number of groups.')
+ "The number of scores must be a multiple of the number of groups."
+ )
if algorithm is None:
raise click.MissingParameter(
- "algorithm must be provided.", param_type='option')
-
- write_info(scores, algorithm, groups, output_dir, model_file, skip_check,
- force, **kwargs)
+ "algorithm must be provided.", param_type="option"
+ )
+
+ write_info(
+ scores,
+ algorithm,
+ groups,
+ output_dir,
+ model_file,
+ skip_check,
+ force,
+ **kwargs
+ )
"""Do the actual fusion."""
train_files, dev_files, eval_files = [], [], []
- for i, (files, grp) in enumerate(zip(
- (train_files, dev_files, eval_files),
- ('train', 'dev', 'eval'))):
+ for i, (files, grp) in enumerate(
+ zip((train_files, dev_files, eval_files), ("train", "dev", "eval"))
+ ):
try:
idx = groups.index(grp)
- files.extend(scores[idx::len(groups)])
+ files.extend(scores[idx :: len(groups)])
except ValueError:
pass
- click.echo('train_files: %s' % train_files)
- click.echo('dev_files: %s' % dev_files)
- click.echo('eval_files: %s' % eval_files)
+ click.echo("train_files: %s" % train_files)
+ click.echo("dev_files: %s" % dev_files)
+ click.echo("eval_files: %s" % eval_files)
# load the scores
if train_files:
@@ -238,40 +318,49 @@ def fuse(scores, algorithm, groups, output_dir, model_file, skip_check, force,
# train, development and evaluation data.
if train_files:
_, gen_lt, zei_lt, atk_lt = get_gza_from_lines_list(
- score_lines_list_train)
+ score_lines_list_train
+ )
if dev_files:
_, gen_ld, zei_ld, atk_ld = get_gza_from_lines_list(
- score_lines_list_dev)
+ score_lines_list_dev
+ )
if eval_files:
_, gen_le, zei_le, atk_le = get_gza_from_lines_list(
- score_lines_list_eval)
+ score_lines_list_eval
+ )
# check if score lines are consistent
if not skip_check:
if train_files:
- logger.info('Checking the training files for consistency ...')
+ logger.info("Checking the training files for consistency ...")
check_consistency(gen_lt, zei_lt, atk_lt)
if dev_files:
- logger.info('Checking the development files for consistency ...')
+ logger.info("Checking the development files for consistency ...")
check_consistency(gen_ld, zei_ld, atk_ld)
if eval_files:
- logger.info('Checking the evaluation files for consistency ...')
+ logger.info("Checking the evaluation files for consistency ...")
check_consistency(gen_le, zei_le, atk_le)
if train_files:
scores_train = get_scores(gen_lt, zei_lt, atk_lt)
scores_train_lines = get_score_lines(
- gen_lt[0:1], zei_lt[0:1], atk_lt[0:1])
+ gen_lt[0:1], zei_lt[0:1], atk_lt[0:1]
+ )
train_neg = get_scores(zei_lt, atk_lt)
train_pos = get_scores(gen_lt)
else:
- scores_train, scores_train_lines, train_neg, train_pos = \
- None, None, None, None
+ scores_train, scores_train_lines, train_neg, train_pos = (
+ None,
+ None,
+ None,
+ None,
+ )
if dev_files:
scores_dev = get_scores(gen_ld, zei_ld, atk_ld)
scores_dev_lines = get_score_lines(
- gen_ld[0:1], zei_ld[0:1], atk_ld[0:1])
+ gen_ld[0:1], zei_ld[0:1], atk_ld[0:1]
+ )
dev_neg = get_scores(zei_ld, atk_ld)
dev_pos = get_scores(gen_ld)
else:
@@ -280,15 +369,15 @@ def fuse(scores, algorithm, groups, output_dir, model_file, skip_check, force,
if eval_files:
scores_eval = get_scores(gen_le, zei_le, atk_le)
scores_eval_lines = get_score_lines(
- gen_le[0:1], zei_le[0:1], atk_le[0:1])
+ gen_le[0:1], zei_le[0:1], atk_le[0:1]
+ )
else:
scores_eval, scores_eval_lines = None, None
# check for nan values
found_nan = False
if train_files:
- found_nan, nan_train, scores_train = remove_nan(
- scores_train, found_nan)
+ found_nan, nan_train, scores_train = remove_nan(scores_train, found_nan)
scores_train_lines = scores_train_lines[~nan_train]
found_nan, _, train_neg = remove_nan(train_neg, found_nan)
found_nan, _, train_pos = remove_nan(train_pos, found_nan)
@@ -302,10 +391,24 @@ def fuse(scores, algorithm, groups, output_dir, model_file, skip_check, force,
scores_eval_lines = scores_eval_lines[~nan_eval]
if found_nan:
- logger.warning('Some nan values were removed.')
+ logger.warning("Some nan values were removed.")
routine_fusion(
- algorithm, model_file, scores_train_lines, scores_train,
- train_neg, train_pos, fused_train_file, scores_dev_lines,
- scores_dev, dev_neg, dev_pos, fused_dev_file, scores_eval_lines,
- scores_eval, fused_eval_file, force, do_training=do_training)
+ algorithm,
+ model_file,
+ scores_train_lines,
+ scores_train,
+ train_neg,
+ train_pos,
+ fused_train_file,
+ scores_dev_lines,
+ scores_dev,
+ dev_neg,
+ dev_pos,
+ fused_dev_file,
+ scores_eval_lines,
+ scores_eval,
+ fused_eval_file,
+ force,
+ do_training=do_training,
+ )
diff --git a/bob/fusion/base/script/fusion.py b/bob/fusion/base/script/fusion.py
index 5bf22be..f30807b 100644
--- a/bob/fusion/base/script/fusion.py
+++ b/bob/fusion/base/script/fusion.py
@@ -2,11 +2,13 @@
"""
import click
import pkg_resources
+
from click_plugins import with_plugins
+
from bob.extension.scripts.click_helper import AliasedGroup
-@with_plugins(pkg_resources.iter_entry_points('bob.fusion.cli'))
+@with_plugins(pkg_resources.iter_entry_points("bob.fusion.cli"))
@click.group(cls=AliasedGroup)
def fusion():
"""Score fusion related scripts"""
diff --git a/bob/fusion/base/script/resource.py b/bob/fusion/base/script/resource.py
index e1a2898..7ed23e9 100644
--- a/bob/fusion/base/script/resource.py
+++ b/bob/fusion/base/script/resource.py
@@ -1,26 +1,41 @@
"""A script to list the resources.
"""
-from __future__ import print_function, absolute_import, division
+from __future__ import absolute_import, division, print_function
+
import logging
+
import click
-from bob.extension.scripts.click_helper import verbosity_option
+
import bob.bio.base
+from bob.extension.scripts.click_helper import verbosity_option
+
logger = logging.getLogger(__name__)
-@click.command(epilog='''\b
+@click.command(
+ epilog="""\b
Examples:
$ bob fusion resource
$ bob fusion resource -v
-''')
-@click.option('--packages', '-p', multiple=True,
- help='List only the resources from these packages.')
+"""
+)
+@click.option(
+ "--packages",
+ "-p",
+ multiple=True,
+ help="List only the resources from these packages.",
+)
@verbosity_option()
@click.pass_context
def resource(ctx, packages, **kwargs):
- """Lists fusion algorithm resources.
- """
- click.echo(bob.bio.base.list_resources(
- 'algorithm', strip=['dummy'], package_prefix='bob.fusion.',
- verbose=ctx.meta['verbosity'], packages=packages or None))
+ """Lists fusion algorithm resources."""
+ click.echo(
+ bob.bio.base.list_resources(
+ "algorithm",
+ strip=["dummy"],
+ package_prefix="bob.fusion.",
+ verbose=ctx.meta["verbosity"],
+ packages=packages or None,
+ )
+ )
diff --git a/bob/fusion/base/test/test_algorithm.py b/bob/fusion/base/test/test_algorithm.py
index 82328c4..a467c18 100644
--- a/bob/fusion/base/test/test_algorithm.py
+++ b/bob/fusion/base/test/test_algorithm.py
@@ -1,12 +1,16 @@
#!/usr/bin/env python
+import logging
+
+from tempfile import NamedTemporaryFile
+
import numpy as np
+
from numpy import array
-from tempfile import NamedTemporaryFile
+from sklearn.linear_model import LogisticRegression
+from sklearn.preprocessing import StandardScaler
+
import bob.fusion.base
import bob.learn.linear
-from sklearn.preprocessing import StandardScaler
-from sklearn.linear_model import LogisticRegression
-import logging
logger = logging.getLogger("bob.fusion.base")
diff --git a/bob/fusion/base/test/test_preprocessor.py b/bob/fusion/base/test/test_preprocessor.py
index 46bc0ca..2ffa432 100644
--- a/bob/fusion/base/test/test_preprocessor.py
+++ b/bob/fusion/base/test/test_preprocessor.py
@@ -1,21 +1,17 @@
-from bob.fusion.base.preprocessor import Tanh
-from sklearn.preprocessing import StandardScaler
import numpy as np
+from sklearn.preprocessing import StandardScaler
+
+from bob.fusion.base.preprocessor import Tanh
+
def test_tanh_preprocessor():
- DATA = [[0, 0],
- [0, 0],
- [1, 1],
- [1, 1]]
+ DATA = [[0, 0], [0, 0], [1, 1], [1, 1]]
Y = np.ones(len(DATA), dtype=bool)
MEAN = [0.5, 0.5]
- DATA_T = [[-1., - 1.],
- [-1., - 1.],
- [1., 1.],
- [1., 1.]]
+ DATA_T = [[-1.0, -1.0], [-1.0, -1.0], [1.0, 1.0], [1.0, 1.0]]
DATA2 = [[2, 2]]
- DATA2_T = [[3., 3.]]
+ DATA2_T = [[3.0, 3.0]]
scaler = StandardScaler()
scaler.fit(np.asarray(DATA))
assert np.allclose(scaler.mean_, MEAN)
@@ -28,27 +24,27 @@ def test_tanh_preprocessor():
scaler = Tanh()
scaler.fit(DATA, y=Y)
assert np.allclose(scaler.mean_, MEAN)
- assert np.allclose(scaler.transform(DATA),
- tanh(DATA, scaler.mean_, scaler.scale_))
- assert np.allclose(scaler.transform(DATA2),
- tanh(DATA2, scaler.mean_, scaler.scale_))
+ assert np.allclose(
+ scaler.transform(DATA), tanh(DATA, scaler.mean_, scaler.scale_)
+ )
+ assert np.allclose(
+ scaler.transform(DATA2), tanh(DATA2, scaler.mean_, scaler.scale_)
+ )
- assert np.allclose(scaler.inverse_transform(scaler.transform(DATA2)),
- DATA2)
+ assert np.allclose(scaler.inverse_transform(scaler.transform(DATA2)), DATA2)
- assert np.allclose(scaler.inverse_transform(scaler.transform(DATA)),
- DATA)
+ assert np.allclose(scaler.inverse_transform(scaler.transform(DATA)), DATA)
scaler = Tanh()
scaler.fit_transform(DATA, y=Y)
assert np.allclose(scaler.mean_, MEAN)
- assert np.allclose(scaler.transform(DATA),
- tanh(DATA, scaler.mean_, scaler.scale_))
- assert np.allclose(scaler.transform(DATA2),
- tanh(DATA2, scaler.mean_, scaler.scale_))
+ assert np.allclose(
+ scaler.transform(DATA), tanh(DATA, scaler.mean_, scaler.scale_)
+ )
+ assert np.allclose(
+ scaler.transform(DATA2), tanh(DATA2, scaler.mean_, scaler.scale_)
+ )
- assert np.allclose(scaler.inverse_transform(scaler.transform(DATA2)),
- DATA2)
+ assert np.allclose(scaler.inverse_transform(scaler.transform(DATA2)), DATA2)
- assert np.allclose(scaler.inverse_transform(scaler.transform(DATA)),
- DATA)
+ assert np.allclose(scaler.inverse_transform(scaler.transform(DATA)), DATA)
diff --git a/bob/fusion/base/test/test_scripts.py b/bob/fusion/base/test/test_scripts.py
index 3758980..cda42c3 100644
--- a/bob/fusion/base/test/test_scripts.py
+++ b/bob/fusion/base/test/test_scripts.py
@@ -1,13 +1,17 @@
#!/usr/bin/env python
import os
+
import numpy
-from ..script.fuse import fuse
-from ..script.boundary import boundary
-from bob.io.base.test_utils import datafile
-from bob.bio.base.score import load_score
+
from click.testing import CliRunner
+
+from bob.bio.base.score import load_score
from bob.extension.scripts.click_helper import assert_click_runner_result
+from bob.io.base.test_utils import datafile
+
+from ..script.boundary import boundary
+from ..script.fuse import fuse
train_files = [
datafile("scores-train-1", "bob.fusion.base", "test/data"),
diff --git a/bob/fusion/base/tools/__init__.py b/bob/fusion/base/tools/__init__.py
index d6fb8cd..a182e28 100644
--- a/bob/fusion/base/tools/__init__.py
+++ b/bob/fusion/base/tools/__init__.py
@@ -1,5 +1,5 @@
-from .common import *
-from .plotting import *
+from .common import * # noqa: F401,F403
+from .plotting import * # noqa: F401,F403
# gets sphinx autodoc done right - don't remove it
-__all__ = [_ for _ in dir() if not _.startswith('_')]
+__all__ = [_ for _ in dir() if not _.startswith("_")]
diff --git a/bob/fusion/base/tools/common.py b/bob/fusion/base/tools/common.py
index b625366..5339e18 100644
--- a/bob/fusion/base/tools/common.py
+++ b/bob/fusion/base/tools/common.py
@@ -1,18 +1,21 @@
-import numpy as np
+import logging
+
from collections import defaultdict
-import logging
+import numpy as np
logger = logging.getLogger(__name__)
def get_2negatives_1positive(score_lines):
- gen_mask = score_lines['claimed_id'] == score_lines['real_id']
+ gen_mask = score_lines["claimed_id"] == score_lines["real_id"]
atk_mask = np.logical_or(
- np.char.count(score_lines['real_id'], 'spoof') > 0,
- np.char.count(score_lines['real_id'], 'attack') > 0)
- zei_mask = np.logical_and(np.logical_not(
- gen_mask), np.logical_not(atk_mask))
+ np.char.count(score_lines["real_id"], "spoof") > 0,
+ np.char.count(score_lines["real_id"], "attack") > 0,
+ )
+ zei_mask = np.logical_and(
+ np.logical_not(gen_mask), np.logical_not(atk_mask)
+ )
gen = score_lines[gen_mask]
zei = score_lines[zei_mask]
atk = score_lines[atk_mask]
@@ -22,28 +25,28 @@ def get_2negatives_1positive(score_lines):
def check_consistency(gen_l, zei_l, atk_l):
if len(gen_l) < 2:
raise ValueError(
- 'Check failed since less than two system is available.')
+ "Check failed since less than two system is available."
+ )
for score_lines_list in (gen_l, zei_l, atk_l):
if not score_lines_list:
continue
score_lines0 = score_lines_list[0]
for score_lines in score_lines_list[1:]:
- match = np.all(score_lines['claimed_id'] ==
- score_lines0['claimed_id'])
+ match = np.all(
+ score_lines["claimed_id"] == score_lines0["claimed_id"]
+ )
if not match:
- raise ValueError(
- "claimed ids do not match between score files")
+ raise ValueError("claimed ids do not match between score files")
- match = np.all(score_lines['real_id'] == score_lines0['real_id'])
+ match = np.all(score_lines["real_id"] == score_lines0["real_id"])
if not match:
- raise ValueError(
- "real ids do not match between score files")
+ raise ValueError("real ids do not match between score files")
def get_scores(*args):
scores = []
for temp in zip(*args):
- scores.append(np.concatenate([a['score'] for a in temp], axis=0))
+ scores.append(np.concatenate([a["score"] for a in temp], axis=0))
return np.vstack(scores).T
@@ -51,7 +54,7 @@ def get_score_lines(*args):
# get the dtype names
names = list(args[0][0].dtype.names)
if len(names) != 4:
- names = [n for n in names if 'model_label' not in n]
+ names = [n for n in names if "model_label" not in n]
logger.debug(names)
# find the (max) size of strigns
@@ -64,7 +67,7 @@ def get_score_lines(*args):
# make a new dtype
new_dtype = []
for name in names[:-1]:
- new_dtype.append((name, 'U{}'.format(max(lengths[name]))))
+ new_dtype.append((name, "U{}".format(max(lengths[name]))))
new_dtype.append((names[-1], float))
score_lines = []
@@ -96,9 +99,11 @@ def get_gza_from_lines_list(score_lines_list):
zei_lengths = np.array(zei_lengths)
idx1 = 0 # used later if it does not enter the if.
if not (np.all(zei_lengths == 0) or np.all(zei_lengths > 0)):
- logger.info("Trying to fill-in the missing zero effort impostor scores"
- " for pad systems. If you see a numpy index error below, "
- "your biometric scores do not match your pad scores.")
+ logger.info(
+ "Trying to fill-in the missing zero effort impostor scores"
+ " for pad systems. If you see a numpy index error below, "
+ "your biometric scores do not match your pad scores."
+ )
# generate the missing ones
# find one that has zei
idx1 = zei_lengths.nonzero()[0][0]
@@ -108,20 +113,24 @@ def get_gza_from_lines_list(score_lines_list):
continue
temp = np.array(zei_full)
# make sure we replace all scores.
- temp['score'] = np.nan
+ temp["score"] = np.nan
# get the list of ids
- real_ids = np.unique(temp['real_id'])
+ real_ids = np.unique(temp["real_id"])
# find pad score of that id and replace the score
for real_id in real_ids:
# get the list of test_labels
test_labels = np.unique(
- temp['test_label'][temp['real_id'] == real_id])
+ temp["test_label"][temp["real_id"] == real_id]
+ )
for test_label in test_labels:
- idx3 = np.logical_and(temp['real_id'] == real_id,
- temp['test_label'] == test_label)
+ idx3 = np.logical_and(
+ temp["real_id"] == real_id,
+ temp["test_label"] == test_label,
+ )
idx4 = np.logical_and(
- gen_l[idx2]['real_id'] == real_id,
- gen_l[idx2]['test_label'] == test_label)
- temp['score'][idx3] = gen_l[idx2]['score'][idx4]
+ gen_l[idx2]["real_id"] == real_id,
+ gen_l[idx2]["test_label"] == test_label,
+ )
+ temp["score"][idx3] = gen_l[idx2]["score"][idx4]
zei_l[idx2] = temp
return idx1, gen_l, zei_l, atk_l
diff --git a/bob/fusion/base/tools/plotting.py b/bob/fusion/base/tools/plotting.py
index e75bcf0..7da7fb3 100644
--- a/bob/fusion/base/tools/plotting.py
+++ b/bob/fusion/base/tools/plotting.py
@@ -1,9 +1,11 @@
#!/usr/bin/env python
-import bob.learn.em
import numpy as np
+
from numpy.random import default_rng
+import bob.learn.em
+
def grouping(scores, gformat="random", npoints=500, seed=None, **kwargs):
@@ -12,7 +14,9 @@ def grouping(scores, gformat="random", npoints=500, seed=None, **kwargs):
return scores
if gformat == "kmeans":
- kmeans_machine = bob.learn.em.KMeansMachine(n_clusters=npoints, convergence_threshold=0.1, max_iter=500)
+ kmeans_machine = bob.learn.em.KMeansMachine(
+ n_clusters=npoints, convergence_threshold=0.1, max_iter=500
+ )
kmeans_machine.fit(scores)
scores = kmeans_machine.means
diff --git a/buildout.cfg b/buildout.cfg
index a959ae4..44d8d99 100644
--- a/buildout.cfg
+++ b/buildout.cfg
@@ -11,4 +11,4 @@ verbose = true
[scripts]
recipe = bob.buildout:scripts
-dependent-scripts = true
\ No newline at end of file
+dependent-scripts = true
diff --git a/develop.cfg b/develop.cfg
index b2e43bc..3e7ed68 100644
--- a/develop.cfg
+++ b/develop.cfg
@@ -26,4 +26,3 @@ bob.learn.em = git git@gitlab.idiap.ch:bob/bob.learn.em
[scripts]
recipe = bob.buildout:scripts
dependent-scripts = true
-
diff --git a/doc/conf.py b/doc/conf.py
index 66328c7..0666276 100644
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -2,32 +2,30 @@
# vim: set fileencoding=utf-8 :
import os
-import sys
-import glob
-import pkg_resources
+import pkg_resources
# -- General configuration -----------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
-needs_sphinx = '1.3'
+needs_sphinx = "1.3"
# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = [
- 'sphinx.ext.todo',
- 'sphinx.ext.coverage',
- 'sphinx.ext.ifconfig',
- 'sphinx.ext.autodoc',
- 'sphinx.ext.autosummary',
- 'sphinx.ext.doctest',
- 'sphinx.ext.graphviz',
- 'sphinx.ext.intersphinx',
- 'sphinx.ext.napoleon',
- 'sphinx.ext.viewcode',
- 'sphinx.ext.mathjax',
- #'matplotlib.sphinxext.plot_directive'
- ]
+ "sphinx.ext.todo",
+ "sphinx.ext.coverage",
+ "sphinx.ext.ifconfig",
+ "sphinx.ext.autodoc",
+ "sphinx.ext.autosummary",
+ "sphinx.ext.doctest",
+ "sphinx.ext.graphviz",
+ "sphinx.ext.intersphinx",
+ "sphinx.ext.napoleon",
+ "sphinx.ext.viewcode",
+ "sphinx.ext.mathjax",
+ # 'matplotlib.sphinxext.plot_directive'
+]
# Be picky about warnings
nitpicky = False
@@ -36,13 +34,13 @@ nitpicky = False
nitpick_ignore = []
# Allows the user to override warnings from a separate file
-if os.path.exists('nitpick-exceptions.txt'):
- for line in open('nitpick-exceptions.txt'):
+if os.path.exists("nitpick-exceptions.txt"):
+ for line in open("nitpick-exceptions.txt"):
if line.strip() == "" or line.startswith("#"):
continue
dtype, target = line.split(None, 1)
target = target.strip()
- try: # python 2.x
+ try: # python 2.x
target = unicode(target)
except NameError:
pass
@@ -58,25 +56,27 @@ autosummary_generate = True
numfig = True
# If we are on OSX, the 'dvipng' path maybe different
-dvipng_osx = '/opt/local/libexec/texlive/binaries/dvipng'
-if os.path.exists(dvipng_osx): pngmath_dvipng = dvipng_osx
+dvipng_osx = "/opt/local/libexec/texlive/binaries/dvipng"
+if os.path.exists(dvipng_osx):
+ pngmath_dvipng = dvipng_osx
# Add any paths that contain templates here, relative to this directory.
-templates_path = ['_templates']
+templates_path = ["_templates"]
# The suffix of source filenames.
-source_suffix = '.rst'
+source_suffix = ".rst"
# The encoding of source files.
-#source_encoding = 'utf-8-sig'
+# source_encoding = 'utf-8-sig'
# The master toctree document.
-master_doc = 'index'
+master_doc = "index"
# General information about the project.
-project = u'bob.fusion.base'
+project = u"bob.fusion.base"
import time
-copyright = u'%s, Idiap Research Institute' % time.strftime('%Y')
+
+copyright = u"%s, Idiap Research Institute" % time.strftime("%Y")
# Grab the setup entry
distribution = pkg_resources.require(project)[0]
@@ -92,42 +92,42 @@ release = distribution.version
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
-#language = None
+# language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
-#today = ''
+# today = ''
# Else, today_fmt is used as the format for a strftime call.
-#today_fmt = '%B %d, %Y'
+# today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
-exclude_patterns = ['links.rst']
+exclude_patterns = ["links.rst"]
# The reST default role (used for this markup: `text`) to use for all documents.
-#default_role = None
+# default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
-#add_function_parentheses = True
+# add_function_parentheses = True
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
-#add_module_names = True
+# add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
-#show_authors = False
+# show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
-pygments_style = 'sphinx'
+pygments_style = "sphinx"
# A list of ignored prefixes for module index sorting.
-#modindex_common_prefix = []
+# modindex_common_prefix = []
# Some variables which are useful for generated material
-project_variable = project.replace('.', '_')
-short_description = u'Score fusion in biometric and pad experiments'
-owner = [u'Idiap Research Institute']
+project_variable = project.replace(".", "_")
+short_description = u"Score fusion in biometric and pad experiments"
+owner = [u"Idiap Research Institute"]
# -- Options for HTML output ---------------------------------------------------
@@ -135,80 +135,81 @@ owner = [u'Idiap Research Institute']
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
import sphinx_rtd_theme
-html_theme = 'sphinx_rtd_theme'
+
+html_theme = "sphinx_rtd_theme"
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
-#html_theme_options = {}
+# html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
-#html_title = None
+# html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
-#html_short_title = project_variable
+# html_short_title = project_variable
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
-html_logo = 'img/logo.png'
+html_logo = "img/logo.png"
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
-html_favicon = 'img/favicon.ico'
+html_favicon = "img/favicon.ico"
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
-#html_static_path = ['_static']
+# html_static_path = ['_static']
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
-#html_last_updated_fmt = '%b %d, %Y'
+# html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
-#html_use_smartypants = True
+# html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
-#html_sidebars = {}
+# html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
-#html_additional_pages = {}
+# html_additional_pages = {}
# If false, no module index is generated.
-#html_domain_indices = True
+# html_domain_indices = True
# If false, no index is generated.
-#html_use_index = True
+# html_use_index = True
# If true, the index is split into individual pages for each letter.
-#html_split_index = False
+# html_split_index = False
# If true, links to the reST sources are added to the pages.
-#html_show_sourcelink = True
+# html_show_sourcelink = True
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
-#html_show_sphinx = True
+# html_show_sphinx = True
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
-#html_show_copyright = True
+# html_show_copyright = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
-#html_use_opensearch = ''
+# html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
-#html_file_suffix = None
+# html_file_suffix = None
# Output file base name for HTML help builder.
-htmlhelp_basename = project_variable + u'_doc'
+htmlhelp_basename = project_variable + u"_doc"
# -- Post configuration --------------------------------------------------------
@@ -218,26 +219,27 @@ rst_epilog = """
.. |project| replace:: Bob
.. |version| replace:: %s
.. |current-year| date:: %%Y
-""" % (version,)
+""" % (
+ version,
+)
# Default processing flags for sphinx
-autoclass_content = 'class'
-autodoc_member_order = 'bysource'
+autoclass_content = "class"
+autodoc_member_order = "bysource"
autodoc_default_options = {
- "members": True,
- "undoc-members": True,
- "show-inheritance": True,
+ "members": True,
+ "undoc-members": True,
+ "show-inheritance": True,
}
# For inter-documentation mapping:
from bob.extension.utils import link_documentation, load_requirements
+
sphinx_requirements = "extra-intersphinx.txt"
if os.path.exists(sphinx_requirements):
- intersphinx_mapping = link_documentation(
- additional_packages=['python','numpy'] + \
- load_requirements(sphinx_requirements)
- )
+ intersphinx_mapping = link_documentation(
+ additional_packages=["python", "numpy"]
+ + load_requirements(sphinx_requirements)
+ )
else:
- intersphinx_mapping = link_documentation()
-
-
+ intersphinx_mapping = link_documentation()
diff --git a/setup.py b/setup.py
index fa9959a..ffa14e5 100644
--- a/setup.py
+++ b/setup.py
@@ -1,68 +1,59 @@
#!/usr/bin/env python
# vim: set fileencoding=utf-8 :
-from setuptools import setup, dist
-dist.Distribution(dict(setup_requires=['bob.extension']))
+from setuptools import dist, setup
+
+dist.Distribution(dict(setup_requires=["bob.extension"]))
+
+from bob.extension.utils import find_packages, load_requirements
-from bob.extension.utils import load_requirements, find_packages
install_requires = load_requirements()
setup(
-
- name='bob.fusion.base',
+ name="bob.fusion.base",
version=open("version.txt").read().rstrip(),
- description='Score fusion in biometric and pad experiments',
-
- url='https://gitlab.idiap.ch/bob/bob.fusion.base',
- license='GPLv3',
- author='Amir Mohammadi',
- author_email='amir.mohammadi@idiap.ch',
- keywords='bob, score fusion, evaluation, biometric',
-
- long_description=open('README.rst').read(),
-
+ description="Score fusion in biometric and pad experiments",
+ url="https://gitlab.idiap.ch/bob/bob.fusion.base",
+ license="GPLv3",
+ author="Amir Mohammadi",
+ author_email="amir.mohammadi@idiap.ch",
+ keywords="bob, score fusion, evaluation, biometric",
+ long_description=open("README.rst").read(),
packages=find_packages(),
include_package_data=True,
zip_safe=False,
-
install_requires=install_requires,
-
entry_points={
-
# main entry for bob fusion cli
- 'bob.cli': [
- 'fusion = bob.fusion.base.script.fusion:fusion',
+ "bob.cli": [
+ "fusion = bob.fusion.base.script.fusion:fusion",
],
-
# bob fusion scripts
- 'bob.fusion.cli': [
- 'fuse = bob.fusion.base.script.fuse:fuse',
- 'resource = bob.fusion.base.script.resource:resource',
- 'boundary = bob.fusion.base.script.boundary:boundary',
+ "bob.fusion.cli": [
+ "fuse = bob.fusion.base.script.fuse:fuse",
+ "resource = bob.fusion.base.script.resource:resource",
+ "boundary = bob.fusion.base.script.boundary:boundary",
],
-
- 'bob.fusion.algorithm': [
- 'mean = bob.fusion.base.config.algorithm.mean:algorithm',
- 'mean-tanh = bob.fusion.base.config.algorithm.mean:algorithm_tanh',
- 'llr = bob.fusion.base.config.algorithm.llr_skl:algorithm',
- 'llr-tanh = bob.fusion.base.config.algorithm.llr_skl:algorithm_tanh',
- 'plr-2 = bob.fusion.base.config.algorithm.plr_2:algorithm',
- 'plr-2-tanh = bob.fusion.base.config.algorithm.plr_2:algorithm_tanh',
- 'plr-3 = bob.fusion.base.config.algorithm.plr_3:algorithm',
- 'plr-3-tanh = bob.fusion.base.config.algorithm.plr_3:algorithm_tanh',
- 'gmm = bob.fusion.base.config.algorithm.gmm:algorithm',
- 'gmm-tanh = bob.fusion.base.config.algorithm.gmm:algorithm_tanh',
+ "bob.fusion.algorithm": [
+ "mean = bob.fusion.base.config.algorithm.mean:algorithm",
+ "mean-tanh = bob.fusion.base.config.algorithm.mean:algorithm_tanh",
+ "llr = bob.fusion.base.config.algorithm.llr_skl:algorithm",
+ "llr-tanh = bob.fusion.base.config.algorithm.llr_skl:algorithm_tanh",
+ "plr-2 = bob.fusion.base.config.algorithm.plr_2:algorithm",
+ "plr-2-tanh = bob.fusion.base.config.algorithm.plr_2:algorithm_tanh",
+ "plr-3 = bob.fusion.base.config.algorithm.plr_3:algorithm",
+ "plr-3-tanh = bob.fusion.base.config.algorithm.plr_3:algorithm_tanh",
+ "gmm = bob.fusion.base.config.algorithm.gmm:algorithm",
+ "gmm-tanh = bob.fusion.base.config.algorithm.gmm:algorithm_tanh",
],
-
},
-
classifiers=[
- 'Framework :: Bob',
- 'Development Status :: 3 - Alpha',
- 'Intended Audience :: Developers',
- 'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
- 'Natural Language :: English',
- 'Programming Language :: Python',
- 'Topic :: Scientific/Engineering :: Artificial Intelligence',
+ "Framework :: Bob",
+ "Development Status :: 3 - Alpha",
+ "Intended Audience :: Developers",
+ "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
+ "Natural Language :: English",
+ "Programming Language :: Python",
+ "Topic :: Scientific/Engineering :: Artificial Intelligence",
],
)
--
GitLab