diff --git a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/random_forest.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/random_forest.py
index 54eb985b1c1f548f6ced4458e96399a62502eaed..8b2caef15dd827e0c30ec3984512d72f6a154c65 100644
--- a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/random_forest.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/random_forest.py
@@ -10,9 +10,43 @@ __status__ = "Prototype" # Production, Development, Prototype
classifier_class_name = "RandomForest"
class RandomForest(RandomForestClassifier, BaseMonoviewClassifier):
+ """RandomForest Classifier Class
+ Parameters
+ ----------
+ random_state
+
+ n_estimators
+
+ max_depth : int maximum of depth (default : 10)
+
+ criterion : criteria (default : 'gini')
+
+ kwargs
+
+ Attributes
+ ----------
+ param_names
+
+ distribs
+
+ classed_params
+
+ weird_strings
+
+ """
def __init__(self, random_state=None, n_estimators=10,
max_depth=None, criterion='gini', **kwargs):
+ """
+
+ Parameters
+ ----------
+ random_state
+ n_estimators
+ max_depth
+ criterion
+ kwargs
+ """
super(RandomForest, self).__init__(
n_estimators=n_estimators,
max_depth=max_depth,
@@ -28,13 +62,29 @@ class RandomForest(RandomForestClassifier, BaseMonoviewClassifier):
self.weird_strings = {}
def canProbas(self):
- """Used to know if the classifier can return label probabilities"""
+ """Used to know if the classifier can return label probabilities
+
+ Returns
+ -------
+ True
+ """
return True
def getInterpret(self, directory, y_test):
- interpretString = ""
- interpretString += self.getFeatureImportance(directory)
- return interpretString
+ """
+
+ Parameters
+ ----------
+ directory
+ y_test
+
+ Returns
+ -------
+ string for interpretation interpret_string
+ """
+ interpret_string = ""
+ interpret_string += self.getFeatureImportance(directory)
+ return interpret_string
# def formatCmdArgs(args):
diff --git a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm.py
index 4988a2a7e15a421e74043ab6d465a6156488e930..8cae0d38380bd850efc454dd13d4dc04b470a2df 100644
--- a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm.py
@@ -44,9 +44,41 @@ __status__ = "Prototype" # Production, Development, Prototype
classifier_class_name = "SCM"
class SCM(scm, BaseMonoviewClassifier):
+ """
+ SCM Classifier
+ Parameters
+ ----------
+ random_state (default : None)
+ model_type : string (default: "conjunction")
+ max_rules : int number maximum of rules (default : 10)
+ p : float value(default : 0.1 )
+
+ kwarg : others arguments
+
+ Attributes
+ ----------
+ param_names
+
+ distribs
+
+ classed_params
+
+ weird_strings
+
+ """
def __init__(self, random_state=None, model_type="conjunction",
max_rules=10, p=0.1, **kwargs):
+ """
+
+ Parameters
+ ----------
+ random_state
+ model_type
+ max_rules
+ p
+ kwargs
+ """
super(SCM, self).__init__(
random_state=random_state,
model_type=model_type,
@@ -61,7 +93,13 @@ class SCM(scm, BaseMonoviewClassifier):
self.weird_strings = {}
def canProbas(self):
- """Used to know if the classifier can return label probabilities"""
+ """
+ Used to know if the classifier can return label probabilities
+
+ Returns
+ -------
+ return False in any case
+ """
return False
def getInterpret(self, directory, y_test):
diff --git a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen.py
index ced608365e87a9f0e80daf5f2a6db941b5062808..57026c02e2ba84d4a16deac4a6f8554e02f636fc 100644
--- a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen.py
@@ -14,7 +14,32 @@ __status__ = "Prototype" # Production, Development, Prototype
classifier_class_name = "SCMPregen"
class SCMPregen(BaseMonoviewClassifier, PregenClassifier, scm):
+ """
+ Parameters
+ ----------
+ random_state
+ model_type
+ max_rules
+ p
+ n_stumps
+ self_complemented
+ estimators_generator
+ max_depth
+ kwargs
+
+ Attributes
+ ----------
+ param_names
+
+ distribs
+ classed_params
+ weird_strings
+ self_complemented
+ n_stumps
+ estimators_generator
+ max_depth
+ """
def __init__(self, random_state=None, model_type="conjunction",
max_rules=10, p=0.1, n_stumps=10, self_complemented=True,
estimators_generator="Stumps", max_depth=1, **kwargs):
@@ -39,13 +64,46 @@ class SCMPregen(BaseMonoviewClassifier, PregenClassifier, scm):
self.max_depth=1
def get_params(self, deep=True):
+ """
+
+ Parameters
+ ----------
+ deep : boolean (default : True) not used
+
+ Returns
+ -------
+ parame
+ """
params = super(SCMPregen, self).get_params(deep)
params["estimators_generator"] = self.estimators_generator
params["max_depth"] = self.max_depth
params["n_stumps"] = self.n_stumps
return params
- def fit(self, X, y, tiebreaker=None, iteration_callback=None, **fit_params):
+ def fit(self, X, y, tiebreaker=None, iteration_callback=None,
+ **fit_params):
+ """
+ fit function
+
+ Parameters
+ ----------
+ X {array-like, sparse matrix}, shape (n_samples, n_features)
+ For kernel="precomputed", the expected shape of X is
+ (n_samples_test, n_samples_train).
+ y : { array-like, shape (n_samples,)
+ Target values class labels in classification
+
+ tiebreaker
+
+ iteration_callback : (default : None)
+
+ fit_params : others parameters
+
+ Returns
+ -------
+ self : object
+ Returns self.
+ """
pregen_X, _ = self.pregen_voters(X, y)
list_files = os.listdir(".")
a = int(self.random_state.randint(0, 10000))
@@ -66,6 +124,20 @@ class SCMPregen(BaseMonoviewClassifier, PregenClassifier, scm):
return self
def predict(self, X):
+ """
+
+ Parameters
+ ----------
+ X : {array-like, sparse matrix}, shape (n_samples, n_features)
+ Training vectors, where n_samples is the number of samples
+ and n_features is the number of features.
+ For kernel="precomputed", the expected shape of X is
+ (n_samples, n_samples).
+
+ Returns
+ -------
+ y_pred : array, shape (n_samples,)
+ """
pregen_X, _ = self.pregen_voters(X)
list_files = os.listdir(".")
a = int(self.random_state.randint(0, 10000))
@@ -83,12 +155,29 @@ class SCMPregen(BaseMonoviewClassifier, PregenClassifier, scm):
return self.classes_[self.model_.predict(place_holder)]
def canProbas(self):
- """Used to know if the classifier can return label probabilities"""
+ """
+ Used to know if the classifier can return label probabilities
+ Returns
+ -------
+ False in any case
+ """
+
return False
def getInterpret(self, directory, y_test):
- interpretString = "Model used : " + str(self.model_)
- return interpretString
+ """
+
+ Parameters
+ ----------
+ directory
+ y_test
+
+ Returns
+ -------
+ interpret_string string of interpretation
+ """
+ interpret_string = "Model used : " + str(self.model_)
+ return interpret_string
# def formatCmdArgs(args):
diff --git a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/sgd.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/sgd.py
index 22bbad8dcb3c3c8df9248597a0f7716725dca43b..f8a10d6fa5df4f5b39d4c7681fb9bc72303be47a 100644
--- a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/sgd.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/sgd.py
@@ -9,9 +9,19 @@ __status__ = "Prototype" # Production, Development, Prototype
classifier_class_name = "SGD"
class SGD(SGDClassifier, BaseMonoviewClassifier):
+ """
+ Parameters
+ ----------
+ random_state
+ loss
+ penalty
+ alpha
+ kwargs
+ """
def __init__(self, random_state=None, loss='hinge',
penalty='l2', alpha=0.0001, **kwargs):
+
super(SGD, self).__init__(
loss=loss,
penalty=penalty,
@@ -26,12 +36,31 @@ class SGD(SGDClassifier, BaseMonoviewClassifier):
self.weird_strings = {}
def canProbas(self):
- """Used to know if the classifier can return label probabilities"""
+ """
+ Used to know if the classifier can return label probabilities
+
+ Returns
+ -------
+ return True in all case
+ """
+
return True
def getInterpret(self, directory, y_test):
- interpretString = ""
- return interpretString
+ """
+
+ Parameters
+ ----------
+ directory
+
+ y_test
+
+ Returns
+ -------
+ interpret_string str to interpreted
+ """
+ interpret_string = ""
+ return interpret_string
# def formatCmdArgs(args):
diff --git a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_linear.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_linear.py
index 87f4c4ed4511f41e160223178f023780fa87f6e9..e26e5796256450cff500f416469900c1d08c1d46 100644
--- a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_linear.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_linear.py
@@ -9,8 +9,17 @@ __status__ = "Prototype" # Production, Development, Prototype
classifier_class_name = "SVMLinear"
class SVMLinear(SVCClassifier, BaseMonoviewClassifier):
+ """SVMLinear
+ Parameters
+ ----------
+ random_state
+ C
+ kwargs
+
+ """
def __init__(self, random_state=None, C=1.0, **kwargs):
+
super(SVMLinear, self).__init__(
C=C,
kernel='linear',
diff --git a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_poly.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_poly.py
index 386868656e84286bb1979539f1c93e197a4f011a..3d389802abb7fe0ba56a384c3e27074aef8db4c2 100644
--- a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_poly.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_poly.py
@@ -9,8 +9,28 @@ __status__ = "Prototype" # Production, Development, Prototype
classifier_class_name = "SVMPoly"
class SVMPoly(SVCClassifier, BaseMonoviewClassifier):
+ """
+ Class of SVMPoly for SVC Classifier
+ Parameters
+ ----------
+ random_state
+
+ C
+
+ degree
+
+ kwargs
+
+ Attributes
+ ----------
+
+ param_names : list of parameters names
+
+ distribs : list of random_state distribution
+ """
def __init__(self, random_state=None, C=1.0, degree=3, **kwargs):
+
super(SVMPoly, self).__init__(
C=C,
kernel='poly',
diff --git a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_rbf.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_rbf.py
index f2ac82543e90b47a2e9126116ef98846ef765740..16727901006e0e451b18c82c8f7008f56916701b 100644
--- a/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_rbf.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_rbf.py
@@ -9,8 +9,24 @@ __status__ = "Prototype" # Production, Development, Prototype
classifier_class_name = "SVMRBF"
class SVMRBF(SVCClassifier, BaseMonoviewClassifier):
+ """
+ class SVMRBF for classifier SVCC
+ Parameters
+ ----------
+ random_state
+ C
+ kwargs
+
+ Attributes
+ ----------
+
+ param_names : list of parameters names
+
+ distribs : list of random_state distribution
+ """
def __init__(self, random_state=None, C=1.0, **kwargs):
+
super(SVMRBF, self).__init__(
C=C,
kernel='rbf',
@@ -27,6 +43,18 @@ class SVMRBF(SVCClassifier, BaseMonoviewClassifier):
def paramsToSet(nIter, randomState):
+ """
+
+ Parameters
+ ----------
+ nIter : int number of iterations
+
+ randomState :
+
+ Returns
+ -------
+ paramsSet list of parameters dictionary with key "C"
+ """
paramsSet = []
for _ in range(nIter):
paramsSet.append({"C": randomState.randint(1, 10000), })
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview/analyze_results.py b/multiview_platform/mono_multi_view_classifiers/multiview/analyze_results.py
index 2c4a90e159d9fd7b1df1500b4e429e236b430524..90637f5d70b256275e0cad083701c3f748b2a422 100644
--- a/multiview_platform/mono_multi_view_classifiers/multiview/analyze_results.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/analyze_results.py
@@ -6,26 +6,60 @@ __status__ = "Prototype" # Production, Development, Prototype
def printMetricScore(metricScores, metric_list):
- metricScoreString = "\n\n"
+ """
+ this function print the metrics scores
+
+ Parameters
+ ----------
+ metricScores : the score of metrics
+
+ metric_list : list of metrics
+
+ Returns
+ -------
+ metric_score_string string constaining all metric results
+ """
+ metric_score_string = "\n\n"
for metric in metric_list:
- metricModule = getattr(metrics, metric[0])
+ metric_module = getattr(metrics, metric[0])
if metric[1] is not None:
- metricKWARGS = dict((index, metricConfig) for index, metricConfig in
+ metric_kwargs = dict((index, metricConfig) for index, metricConfig in
enumerate(metric[1]))
else:
- metricKWARGS = {}
- metricScoreString += "\tFor " + metricModule.getConfig(
- **metricKWARGS) + " : "
- metricScoreString += "\n\t\t- Score on train : " + str(
+ metric_kwargs = {}
+ metric_score_string += "\tFor " + metric_module.getConfig(
+ **metric_kwargs) + " : "
+ metric_score_string += "\n\t\t- Score on train : " + str(
metricScores[metric[0]][0])
- metricScoreString += "\n\t\t- Score on test : " + str(
+ metric_score_string += "\n\t\t- Score on test : " + str(
metricScores[metric[0]][1])
- metricScoreString += "\n\n"
- return metricScoreString
+ metric_score_string += "\n\n"
+ return metric_score_string
def getTotalMetricScores(metric, trainLabels, testLabels, validationIndices,
learningIndices, labels):
+ """
+
+ Parameters
+ ----------
+
+ metric :
+
+ trainLabels : labels of train
+
+ testLabels : labels of test
+
+ validationIndices :
+
+ learningIndices :
+
+ labels :
+
+ Returns
+ -------
+ list of [trainScore, testScore]
+ """
metricModule = getattr(metrics, metric[0])
if metric[1] is not None:
metricKWARGS = dict((index, metricConfig) for index, metricConfig in
@@ -63,6 +97,52 @@ def execute(classifier, trainLabels,
name, KFolds,
hyper_param_search, nIter, metric_list,
views_indices, random_state, labels, classifierModule):
+ """
+
+ Parameters
+ ----------
+ classifier : classifier used
+
+ trainLabels : labels of train
+
+ testLabels : labels of test
+
+ DATASET :
+
+ classificationKWARGS
+
+ classificationIndices
+
+ labels_dictionary
+
+ views
+
+ nbCores
+
+ times
+
+ name
+
+ KFolds
+
+ hyper_param_search
+
+ nIter
+
+ metric_list
+
+ views_indices
+
+ random_state
+
+ labels
+
+ classifierModule
+
+ Returns
+ -------
+ retuern tuple of (stringAnalysis, imagesAnalysis, metricsScore)
+ """
classifier_name = classifier.short_name
learningIndices, validationIndices, testIndicesMulticlass = classificationIndices
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py b/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
index bf68fa9b1680a91779c5884d361ba888d6f1c941..7cca55ea9613cc0b33d16a6524c17789d9f31673 100644
--- a/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
@@ -18,9 +18,33 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def init_constants(kwargs, classification_indices, metrics, name, nb_cores, k_folds,
+def init_constants(kwargs, classification_indices, metrics,
+ name, nb_cores, k_folds,
dataset_var):
- """Used to init the constants"""
+ """
+ Used to init the constants
+ Parameters
+ ----------
+ kwargs :
+
+ classification_indices :
+
+ metrics :
+
+ name :
+
+ nb_cores : nint number of cares to execute
+
+ k_folds :
+
+ dataset_var : {array-like} shape (n_samples, n_features)
+ dataset variable
+
+ Returns
+ -------
+ tuple of (classifier_name, t_start, views_indices,
+ classifier_config, views, learning_rate)
+ """
views = kwargs["view_names"]
views_indices = kwargs["view_indices"]
if not metrics:
@@ -39,12 +63,40 @@ def init_constants(kwargs, classification_indices, metrics, name, nb_cores, k_fo
for view_index, view_name in zip(views_indices, views):
logging.info("Info:\t Shape of " + str(view_name) + " :" + str(
dataset_var.get_shape()))
- return classifier_name, t_start, views_indices, classifier_config, views, learning_rate
+ return classifier_name, t_start, views_indices,\
+ classifier_config, views, learning_rate
def save_results(classifier, labels_dictionary, string_analysis, views, classifier_module,
classification_kargs, directory, learning_rate, name,
images_analysis):
+ """
+ Save results in derectory
+
+ Parameters
+ ----------
+
+ classifier : classifier class
+
+ labels_dictionary : dict dictionary of labels
+
+ string_analysis : str
+
+ views :
+
+ classifier_module : module of the classifier
+
+ classification_kargs :
+
+ directory : str directory
+
+ learning_rate :
+
+ name :
+
+ images_analysis :
+
+ """
labels_set = set(labels_dictionary.values())
logging.info(string_analysis)
views_string = "-".join(views)
@@ -83,6 +135,52 @@ def exec_multiview_multicore(directory, core_index, name, learning_rate, nb_fold
random_state, labels,
hyper_param_search=False, nb_cores=1, metrics=None,
n_iter=30, **arguments):
+ """
+ execute multiview process on
+
+ Parameters
+ ----------
+
+ directory : indicate the directory
+
+ core_index :
+
+ name : name of the data file to perform
+
+ learning_rate :
+
+ nb_folds :
+
+ database_type :
+
+ path : path to the data name
+
+ labels_dictionary
+
+ random_state : int seed, RandomState instance, or None (default=None)
+ The seed of the pseudo random number generator to use when
+ shuffling the data.
+
+ labels :
+
+ hyper_param_search :
+
+ nb_cores : in number of cores
+
+ metrics : metric to use
+
+ n_iter : int number of iterations
+
+ arguments : others arguments
+
+ Returns
+ -------
+ exec_multiview on directory, dataset_var, name, learning_rate, nb_folds, 1,
+ database_type, path, labels_dictionary,
+ random_state, labels,
+ hyper_param_search=hyper_param_search, metrics=metrics,
+ n_iter=n_iter, **arguments
+ """
"""Used to load an HDF5 dataset_var for each parallel job and execute multiview classification"""
dataset_var = h5py.File(path + name + str(core_index) + ".hdf5", "r")
return exec_multiview(directory, dataset_var, name, learning_rate, nb_folds, 1,
@@ -96,7 +194,50 @@ def exec_multiview(directory, dataset_var, name, classification_indices, k_folds
nb_cores, database_type, path,
labels_dictionary, random_state, labels,
hyper_param_search=False, metrics=None, n_iter=30, **kwargs):
- """Used to execute multiview classification and result analysis"""
+ """Used to execute multiview classification and result analysis
+
+ Parameters
+ ----------
+
+ directory : indicate the directory
+
+
+ dataset_var :
+
+ name
+
+ classification_indices
+
+ k_folds
+
+ nb_cores
+
+ database_type
+
+ path
+
+ labels_dictionary : dict dictionary of labels
+
+ random_state : int seed, RandomState instance, or None (default=None)
+ The seed of the pseudo random number generator to use when
+ shuffling the data.
+
+ labels
+
+ hyper_param_search
+
+ metrics
+
+ n_iter : int number of iterations
+
+ kwargs
+
+ Returns
+ -------
+
+ ``MultiviewResult``
+ """
+
logging.debug("Start:\t Initialize constants")
cl_type, \
t_start, \
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview/multiview_utils.py b/multiview_platform/mono_multi_view_classifiers/multiview/multiview_utils.py
index 02956fa810e828b35f7e66f04d3b2ad748abd269..5a2deaa365bbab9cd1bf7796f6a550f7e837ea3f 100644
--- a/multiview_platform/mono_multi_view_classifiers/multiview/multiview_utils.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/multiview_utils.py
@@ -28,13 +28,34 @@ def get_names(classed_list):
class BaseMultiviewClassifier(BaseEstimator, ClassifierMixin):
+ """
+ BaseMultiviewClassifier base of Multiview classifiers
+
+ Parameters
+ ----------
+ random_state : int seed, RandomState instance, or None (default=None)
+ The seed of the pseudo random number generator to use when
+ shuffling the data.
+ """
def __init__(self, random_state):
+
self.random_state = random_state
self.short_name = self.__class__.__name__
self.weird_strings = {}
- def genBestParams(self, detector):
+ def gen_best_params(self, detector):
+ """
+ return best parameters of detector
+ Parameters
+ ----------
+ detector :
+
+ Returns
+ -------
+ best param : dictionary with param name as key and best parameters
+ value
+ """
return dict((param_name, detector.best_params_[param_name])
for param_name in self.param_names)
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/weighted_linear_early_fusion.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/weighted_linear_early_fusion.py
index 16d6bc241aebcca93ac2a02f3e7d77df6cdc22b3..e63ebbb63b35e5d69baa113f68889ee9ca389ce4 100644
--- a/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/weighted_linear_early_fusion.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/weighted_linear_early_fusion.py
@@ -2,19 +2,36 @@ import numpy as np
import inspect
# from ..utils.dataset import get_v
-from ..multiview.multiview_utils import BaseMultiviewClassifier, get_examples_views_indices, ConfigGenerator, get_available_monoview_classifiers
-from .additions.fusion_utils import BaseFusionClassifier
-from .. import monoview_classifiers
+from multiview_platform.mono_multi_view_classifiers.multiview.multiview_utils import BaseMultiviewClassifier
+from multiview_platform.mono_multi_view_classifiers.multiview.multiview_utils import get_examples_views_indices
+from multiview_platform.mono_multi_view_classifiers.multiview.multiview_utils import ConfigGenerator
+from multiview_platform.mono_multi_view_classifiers.multiview.multiview_utils import get_available_monoview_classifiers
+from multiview_platform.mono_multi_view_classifiers.multiview_classifiers.additions.fusion_utils import BaseFusionClassifier
+
+from multiview_platform.mono_multi_view_classifiers import monoview_classifiers
classifier_class_name = "WeightedLinearEarlyFusion"
class WeightedLinearEarlyFusion(BaseMultiviewClassifier, BaseFusionClassifier):
-
+ """
+ WeightedLinearEarlyFusion
+
+ Parameters
+ ----------
+ random_state
+ view_weights
+ monoview_classifier_name
+ monoview_classifier_config
+
+ Attributes
+ ----------
+ """
def __init__(self, random_state=None, view_weights=None,
monoview_classifier_name="decision_tree",
monoview_classifier_config={}):
+
super(WeightedLinearEarlyFusion, self).__init__(random_state=random_state)
self.view_weights = view_weights
self.monoview_classifier_name = monoview_classifier_name
diff --git a/multiview_platform/tests/__init__.py b/multiview_platform/tests/__init__.py
index 3fd5c6b4ff2b4d4fa0a02e0647991fb2e204bf8d..b7887f5996bd1484d567e919608c364fe9a64c63 100644
--- a/multiview_platform/tests/__init__.py
+++ b/multiview_platform/tests/__init__.py
@@ -1 +1,2 @@
from . import test_ExecClassif
+from .utils import rm_tmp, gen_test_dataset, tmp_path
\ No newline at end of file
diff --git a/multiview_platform/tests/test_ExecClassif.py b/multiview_platform/tests/test_ExecClassif.py
index c3c8b6c355f351a2b000e8dc68e9cc5961c0cc83..abbcd77f933e6c9f49dc74213388551bbe85e61d 100644
--- a/multiview_platform/tests/test_ExecClassif.py
+++ b/multiview_platform/tests/test_ExecClassif.py
@@ -4,7 +4,7 @@ import unittest
import h5py
import numpy as np
-from .utils import rm_tmp, tmp_path, test_dataset
+from multiview_platform.tests.utils import rm_tmp, tmp_path, test_dataset
from multiview_platform.mono_multi_view_classifiers import exec_classif
diff --git a/multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py b/multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py
index 1e1625ae0e293c550ad53e625eecc8796d440522..8b24579332aec06011ba54094b0a2a1841a0cb5e 100644
--- a/multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py
+++ b/multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py
@@ -5,10 +5,10 @@ import h5py
import numpy as np
from sklearn.model_selection import StratifiedKFold
-from ..utils import rm_tmp, tmp_path
+from multiview_platform.tests.utils import rm_tmp, tmp_path
-from ...mono_multi_view_classifiers.monoview import exec_classif_mono_view
-from ...mono_multi_view_classifiers.monoview_classifiers import decision_tree
+from multiview_platform.mono_multi_view_classifiers.monoview import exec_classif_mono_view
+from multiview_platform.mono_multi_view_classifiers.monoview_classifiers import decision_tree
class Test_initConstants(unittest.TestCase):
diff --git a/multiview_platform/tests/test_mono_view/test_MonoviewUtils.py b/multiview_platform/tests/test_mono_view/test_MonoviewUtils.py
index a68c710a446bf09dbee7acc542564a775423b3b7..bdbbcf262d3e1c309fe24f2cf90cb53f940fd37c 100644
--- a/multiview_platform/tests/test_mono_view/test_MonoviewUtils.py
+++ b/multiview_platform/tests/test_mono_view/test_MonoviewUtils.py
@@ -4,7 +4,7 @@ import numpy as np
from sklearn.model_selection import StratifiedKFold
from sklearn.tree.tree import DecisionTreeClassifier
-from ...mono_multi_view_classifiers.monoview import monoview_utils
+from multiview_platform.mono_multi_view_classifiers.monoview import monoview_utils
class Test_genTestFoldsPreds(unittest.TestCase):
diff --git a/multiview_platform/tests/test_multiview_classifiers/test_additions/test_diversity_utils.py b/multiview_platform/tests/test_multiview_classifiers/test_additions/test_diversity_utils.py
index c6f4c653382c48b34bcd4b072eb9bfd091e8e6b8..61595f63880c5cc1a01d5b5e96cf68cbf7c397c2 100644
--- a/multiview_platform/tests/test_multiview_classifiers/test_additions/test_diversity_utils.py
+++ b/multiview_platform/tests/test_multiview_classifiers/test_additions/test_diversity_utils.py
@@ -1,7 +1,7 @@
import unittest
import numpy as np
-from ....mono_multi_view_classifiers.multiview_classifiers.additions import diversity_utils
+import multiview_platform.mono_multi_view_classifiers.multiview_classifiers.additions.diversity_utils as du
class FakeDataset():
@@ -19,7 +19,7 @@ class FakeDataset():
return np.unique(self.labels[example_indices])
-class FakeDivCoupleClf(diversity_utils.CoupleDiversityFusionClassifier):
+class FakeDivCoupleClf(du.CoupleDiversityFusionClassifier):
def __init__(self, rs, classifier_names=None,
classifiers_config=None, monoview_estimators=None):
@@ -33,7 +33,7 @@ class FakeDivCoupleClf(diversity_utils.CoupleDiversityFusionClassifier):
return self.rs.randint(0,100)
-class FakeDivGlobalClf(diversity_utils.GlobalDiversityFusionClassifier):
+class FakeDivGlobalClf(du.GlobalDiversityFusionClassifier):
def __init__(self, rs, classifier_names=None,
classifiers_config=None, monoview_estimators=None):
diff --git a/multiview_platform/tests/test_multiview_classifiers/test_difficulty_fusion.py b/multiview_platform/tests/test_multiview_classifiers/test_difficulty_fusion.py
index b49eb1f61389a4c3eb7b63b768bc9ec81dcf9ac6..ff298b8c07ed5a8225f27885ad911b935bbd17ba 100644
--- a/multiview_platform/tests/test_multiview_classifiers/test_difficulty_fusion.py
+++ b/multiview_platform/tests/test_multiview_classifiers/test_difficulty_fusion.py
@@ -2,7 +2,7 @@ import unittest
import numpy as np
-from ...mono_multi_view_classifiers.multiview_classifiers import difficulty_fusion
+from multiview_platform.mono_multi_view_classifiers.multiview_classifiers import difficulty_fusion
class Test_difficulty_fusion(unittest.TestCase):
diff --git a/multiview_platform/tests/test_multiview_classifiers/test_disagree_fusion.py b/multiview_platform/tests/test_multiview_classifiers/test_disagree_fusion.py
index 3ae051fa653f7e2ad132087682cc3fef4996f5f6..bb08e016e5ea75ac78f373ead873e8721eea31e3 100644
--- a/multiview_platform/tests/test_multiview_classifiers/test_disagree_fusion.py
+++ b/multiview_platform/tests/test_multiview_classifiers/test_disagree_fusion.py
@@ -3,7 +3,7 @@
import numpy as np
import unittest
#
-from ...mono_multi_view_classifiers.multiview_classifiers import disagree_fusion
+from multiview_platform.mono_multi_view_classifiers.multiview_classifiers import disagree_fusion
class Test_disagree(unittest.TestCase):
diff --git a/multiview_platform/tests/test_multiview_classifiers/test_double_fault_fusion.py b/multiview_platform/tests/test_multiview_classifiers/test_double_fault_fusion.py
index 3a0b7f6f29edeb3ee196e7f9cb60309fec96f2b4..7e6fd3d70bd5ad84ec62aee0b3e00c8ec336cc34 100644
--- a/multiview_platform/tests/test_multiview_classifiers/test_double_fault_fusion.py
+++ b/multiview_platform/tests/test_multiview_classifiers/test_double_fault_fusion.py
@@ -2,7 +2,7 @@
import numpy as np
import unittest
-from ...mono_multi_view_classifiers.multiview_classifiers import double_fault_fusion
+from multiview_platform.mono_multi_view_classifiers.multiview_classifiers import double_fault_fusion
class Test_disagree(unittest.TestCase):
diff --git a/multiview_platform/tests/test_multiview_classifiers/test_entropy_fusion.py b/multiview_platform/tests/test_multiview_classifiers/test_entropy_fusion.py
index 765a0b793c0deab1687d540d565f7f17002b9f17..dc88bfcc3070b57707f4f8931a55ea1c337f468d 100644
--- a/multiview_platform/tests/test_multiview_classifiers/test_entropy_fusion.py
+++ b/multiview_platform/tests/test_multiview_classifiers/test_entropy_fusion.py
@@ -2,7 +2,7 @@ import unittest
import numpy as np
-from ...mono_multi_view_classifiers.multiview_classifiers import entropy_fusion
+from multiview_platform.mono_multi_view_classifiers.multiview_classifiers import entropy_fusion
class Test_difficulty_fusion(unittest.TestCase):
diff --git a/multiview_platform/tests/test_multiview_classifiers/test_weighted_linear_early_fusion.py b/multiview_platform/tests/test_multiview_classifiers/test_weighted_linear_early_fusion.py
index 65541a03c067f8e2a26e5367314b1fc89d7af9ed..c86607525dc958adf14907a8d3da190682a6adb8 100644
--- a/multiview_platform/tests/test_multiview_classifiers/test_weighted_linear_early_fusion.py
+++ b/multiview_platform/tests/test_multiview_classifiers/test_weighted_linear_early_fusion.py
@@ -3,7 +3,7 @@ import unittest
import numpy as np
import os
-from ..utils import rm_tmp, tmp_path, test_dataset
+from multiview_platform.tests.utils import rm_tmp, tmp_path, test_dataset
from multiview_platform.mono_multi_view_classifiers.multiview_classifiers import \
weighted_linear_early_fusion
diff --git a/multiview_platform/tests/test_utils/test_GetMultiviewDB.py b/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
index 1f1c3b0a3b6ba853dc421c98148d923635db2c6f..a61bfbf3d0e967b8d849893f52c3e7e5967d545e 100644
--- a/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
+++ b/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
@@ -4,8 +4,9 @@ import unittest
import h5py
import numpy as np
-from ...mono_multi_view_classifiers.utils import get_multiview_db
-from ..utils import rm_tmp, tmp_path, test_dataset
+from multiview_platform.mono_multi_view_classifiers.utils import get_multiview_db
+from multiview_platform.tests.utils import rm_tmp, tmp_path
+
class Test_get_classic_db_hdf5(unittest.TestCase):
diff --git a/multiview_platform/tests/test_utils/test_configuration.py b/multiview_platform/tests/test_utils/test_configuration.py
index 5e487e769c7dc6ecdb7753a3c61630d0c62d223f..2d2b9f41ca6c4a105ee063bb5c5cf21435aea3a7 100644
--- a/multiview_platform/tests/test_utils/test_configuration.py
+++ b/multiview_platform/tests/test_utils/test_configuration.py
@@ -3,17 +3,19 @@ import unittest
import yaml
import numpy as np
-from ..utils import rm_tmp, tmp_path
-
+from multiview_platform.tests.utils import rm_tmp, tmp_path
from multiview_platform.mono_multi_view_classifiers.utils import configuration
+
class Test_get_the_args(unittest.TestCase):
@classmethod
def setUpClass(cls):
rm_tmp()
cls.path_to_config_file = tmp_path+"config_temp.yml"
- os.mkdir("./multiview_platform/tests/tmp_tests")
+ path_file = os.path.dirname(os.path.abspath(__file__))
+ make_tmp_dir = os.path.join(path_file, "../tmp_tests")
+ os.mkdir(make_tmp_dir)
data = {"Base":{"first_arg": 10, "second_arg":[12.5, 1e-06]}, "Classification":{"third_arg":True}}
with open(cls.path_to_config_file, "w") as config_file:
yaml.dump(data, config_file)
diff --git a/multiview_platform/tests/test_utils/test_dataset.py b/multiview_platform/tests/test_utils/test_dataset.py
index 381dca70e699c1383c0c50de5af172769fb41b26..dcfcb353d97ae45109c3f86c6a8d2e705f9d7207 100644
--- a/multiview_platform/tests/test_utils/test_dataset.py
+++ b/multiview_platform/tests/test_utils/test_dataset.py
@@ -3,9 +3,8 @@ import h5py
import numpy as np
import os
-from ..utils import rm_tmp, tmp_path
-
-from ...mono_multi_view_classifiers.utils import dataset
+from multiview_platform.tests.utils import rm_tmp, tmp_path
+from multiview_platform.mono_multi_view_classifiers.utils import dataset
class Test_Dataset(unittest.TestCase):
diff --git a/multiview_platform/tests/test_utils/test_execution.py b/multiview_platform/tests/test_utils/test_execution.py
index 3a351de12f7dfd5ac9846fb5fd68a96016b18599..14e064e393bb731cd42f9a37b0c01dcc197ae080 100644
--- a/multiview_platform/tests/test_utils/test_execution.py
+++ b/multiview_platform/tests/test_utils/test_execution.py
@@ -3,9 +3,9 @@ import unittest
import numpy as np
-from ..utils import rm_tmp, tmp_path
+from multiview_platform.tests.utils import rm_tmp, tmp_path
-from ...mono_multi_view_classifiers.utils import execution
+from multiview_platform.mono_multi_view_classifiers.utils import execution
class Test_parseTheArgs(unittest.TestCase):
@@ -56,14 +56,14 @@ class Test_getDatabaseFunction(unittest.TestCase):
def test_simple(cls):
getDB = execution.get_database_function(cls.name, cls.type)
- from ...mono_multi_view_classifiers.utils.get_multiview_db import \
+ from multiview_platform.mono_multi_view_classifiers.utils.get_multiview_db import \
get_classic_db_csv
cls.assertEqual(getDB, get_classic_db_csv)
def test_hdf5(cls):
cls.type = ".hdf5"
getDB = execution.get_database_function(cls.name, cls.type)
- from ...mono_multi_view_classifiers.utils.get_multiview_db import \
+ from multiview_platform.mono_multi_view_classifiers.utils.get_multiview_db import \
get_classic_db_hdf5
cls.assertEqual(getDB, get_classic_db_hdf5)
@@ -71,7 +71,7 @@ class Test_getDatabaseFunction(unittest.TestCase):
cls.name = "plausible"
cls.type = ".hdf5"
getDB = execution.get_database_function(cls.name, cls.type)
- from ...mono_multi_view_classifiers.utils.get_multiview_db import \
+ from multiview_platform.mono_multi_view_classifiers.utils.get_multiview_db import \
get_plausible_db_hdf5
cls.assertEqual(getDB, get_plausible_db_hdf5)
diff --git a/multiview_platform/tests/test_utils/test_hyper_parameter_search.py b/multiview_platform/tests/test_utils/test_hyper_parameter_search.py
index 4917c207ce7e1cf87fbc080430df99225e306a38..b5dfe409c98f7ecc18ddeccf6eaca53216f53aed 100644
--- a/multiview_platform/tests/test_utils/test_hyper_parameter_search.py
+++ b/multiview_platform/tests/test_utils/test_hyper_parameter_search.py
@@ -4,12 +4,13 @@ import unittest
import h5py
import numpy as np
from sklearn.model_selection import StratifiedKFold
+from multiview_platform.tests.utils import rm_tmp, tmp_path
-from ..utils import rm_tmp, tmp_path
-from ...mono_multi_view_classifiers.utils.dataset import Dataset
-from ...mono_multi_view_classifiers.utils import hyper_parameter_search
-from ...mono_multi_view_classifiers.multiview_classifiers import weighted_linear_early_fusion
+from multiview_platform.mono_multi_view_classifiers.utils.dataset import Dataset
+from multiview_platform.mono_multi_view_classifiers.utils import hyper_parameter_search
+from multiview_platform.mono_multi_view_classifiers.multiview_classifiers import weighted_linear_early_fusion
+
class Test_randomized_search(unittest.TestCase):
diff --git a/multiview_platform/tests/test_utils/test_multiclass.py b/multiview_platform/tests/test_utils/test_multiclass.py
index 52cac2a3c257d4e30903fe7e2ab313abe766cd57..f4ffbad929828fd04161f792366a5df1c4d6813d 100644
--- a/multiview_platform/tests/test_utils/test_multiclass.py
+++ b/multiview_platform/tests/test_utils/test_multiclass.py
@@ -2,7 +2,7 @@ import unittest
import numpy as np
-from ...mono_multi_view_classifiers.utils import multiclass
+import multiview_platform.mono_multi_view_classifiers.utils.multiclass as mm
class Test_genMulticlassLabels(unittest.TestCase):
@@ -21,7 +21,7 @@ class Test_genMulticlassLabels(unittest.TestCase):
cls.testIndices[1]]]
def test_one_versus_one(cls):
- multiclassLabels, labelsIndices, oldIndicesMulticlass = multiclass.gen_multiclass_labels(
+ multiclassLabels, labelsIndices, oldIndicesMulticlass = mm.gen_multiclass_labels(
cls.labels, "oneVersusOne", cls.classification_indices)
cls.assertEqual(len(multiclassLabels), 10)
cls.assertEqual(labelsIndices,