Add first select table with data

README.md

@@ -1,9 +1,12 @@
+[![CI](https://github.com/Doctorado-ML/benchmark/actions/workflows/main.yml/badge.svg)](https://github.com/Doctorado-ML/benchmark/actions/workflows/main.yml)
 [![codecov](https://codecov.io/gh/Doctorado-ML/benchmark/branch/main/graph/badge.svg?token=ZRP937NDSG)](https://codecov.io/gh/Doctorado-ML/benchmark)
+[![Quality Gate Status](https://sonar.rmontanana.es/api/project_badges/measure?project=benchmark&metric=alert_status&token=336a6e501988888543c3153baa91bad4b9914dd2)](https://sonar.rmontanana.es/dashboard?id=benchmark)
+[![Technical Debt](https://sonar.rmontanana.es/api/project_badges/measure?project=benchmark&metric=sqale_index&token=336a6e501988888543c3153baa91bad4b9914dd2)](https://sonar.rmontanana.es/dashboard?id=benchmark)
 ![https://img.shields.io/badge/python-3.8%2B-blue](https://img.shields.io/badge/python-3.8%2B-brightgreen)
 
 # benchmark
 
-Benchmarking Python models
+Benchmarking models
 
 ## Experimentation
 

benchmark/Arguments.py

@@ -13,27 +13,21 @@ ALL_METRICS = (
 
 
 class EnvData:
-    def __init__(self):
-        self.args = {}
-
-    def load(self):
+    @staticmethod
+    def load():
+        args = {}
         try:
             with open(Files.dot_env) as f:
                 for line in f.read().splitlines():
                     if line == "" or line.startswith("#"):
                         continue
                     key, value = line.split("=")
-                    self.args[key] = value
+                    args[key] = value
         except FileNotFoundError:
             print(NO_ENV, file=sys.stderr)
             exit(1)
         else:
-            return self.args
-
-    def save(self):
-        with open(Files.dot_env, "w") as f:
-            for key, value in self.args.items():
-                f.write(f"{key}={value}\n")
+            return args
 
 
 class EnvDefault(argparse.Action):
@@ -41,7 +35,7 @@ class EnvDefault(argparse.Action):
     def __init__(
         self, envvar, required=True, default=None, mandatory=False, **kwargs
     ):
-        self._args = EnvData().load()
+        self._args = EnvData.load()
         self._overrides = {}
         if required and not mandatory:
             default = self._args[envvar]
@@ -160,15 +154,6 @@ class Arguments(argparse.ArgumentParser):
                     "help": "Ignore nan results",
                 },
             ],
-            "iwss": [
-                ("--iwss",),
-                {
-                    "default": False,
-                    "action": "store_true",
-                    "required": False,
-                    "help": "Do IWSS with training set and then apply to test set",
-                },
-            ],
             "key": [
                 ("-k", "--key"),
                 {
@@ -244,19 +229,6 @@ class Arguments(argparse.ArgumentParser):
                     "help": "number of folds",
                 },
             ],
-            "output": [
-                ("-o", "--output"),
-                {
-                    "type": str,
-                    "default": "local",
-                    "choices": ["local", "docker"],
-                    "required": False,
-                    "help": (
-                        "in be_flask tells if it is running in local or "
-                        "in docker {local, docker}"
-                    ),
-                },
-            ],
             "platform": [
                 ("-P", "--platform"),
                 {

benchmark/Datasets.py

@@ -32,8 +32,6 @@ class DatasetsArff:
     def get_range_features(X, c_features):
         if c_features.strip() == "all":
             return list(range(X.shape[1]))
-        if c_features.strip() == "none":
-            return []
         return json.loads(c_features)
 
     def load(self, name, class_name):
@@ -111,7 +109,7 @@ class DatasetsSurcov:
 
 class Datasets:
     def __init__(self, dataset_name=None, discretize=None):
-        env_data = EnvData().load()
+        env_data = EnvData.load()
         # DatasetsSurcov, DatasetsTanveer, DatasetsArff,...
         source_name = getattr(
             __import__(__name__),
@@ -131,28 +129,29 @@ class Datasets:
 
     def _init_names(self, dataset_name):
         file_name = os.path.join(self.dataset.folder(), Files.index)
+        default_class = "class"
         self.continuous_features = {}
         with open(file_name) as f:
             sets = f.read().splitlines()
             sets = [x for x in sets if not x.startswith("#")]
-        results = []
+            class_names = [default_class] * len(sets)
+        if "," in sets[0]:
+            result = []
             class_names = []
-        for set_name in sets:
-            try:
-                name, class_name, features = set_name.split(";")
-            except ValueError:
-                class_name = "class"
-                features = "all"
-                name = set_name
-            results.append(name)
+            for data in sets:
+                name, class_name, features = data.split(",", 2)
+                result.append(name)
                 class_names.append(class_name)
-            features = features.strip()
                 self.continuous_features[name] = features
+            sets = result
+        else:
+            for name in sets:
+                self.continuous_features[name] = None
         # Set as dataset list the dataset passed as argument
         if dataset_name is None:
-            return class_names, results
+            return class_names, sets
         try:
-            class_name = class_names[results.index(dataset_name)]
+            class_name = class_names[sets.index(dataset_name)]
         except ValueError:
             raise ValueError(f"Unknown dataset: {dataset_name}")
         return [class_name], [dataset_name]

benchmark/Experiments.py

@@ -7,17 +7,12 @@ import time
 from datetime import datetime
 from tqdm import tqdm
 import numpy as np
-from mufs import MUFS
 from sklearn.model_selection import (
     StratifiedKFold,
     KFold,
     GridSearchCV,
+    cross_validate,
 )
-from sklearn.svm import LinearSVC
-from sklearn.feature_selection import SelectFromModel
-from sklearn.preprocessing import label_binarize
-from sklearn.base import clone
-from sklearn.metrics import check_scoring, roc_auc_score
 from .Utils import Folders, Files, NO_RESULTS
 from .Datasets import Datasets
 from .Models import Models
@@ -27,7 +22,7 @@ from .Arguments import EnvData
 class Randomized:
     @staticmethod
     def seeds():
-        return json.loads(EnvData().load()["seeds"])
+        return json.loads(EnvData.load()["seeds"])
 
 
 class BestResults:
@@ -120,10 +115,9 @@ class Experiment:
         ignore_nan=True,
         fit_features=None,
         discretize=None,
-        iwss=False,
         folds=5,
     ):
-        env_data = EnvData().load()
+        env_data = EnvData.load()
         today = datetime.now()
         self.time = today.strftime("%H:%M:%S")
         self.date = today.strftime("%Y-%m-%d")
@@ -182,7 +176,6 @@ class Experiment:
         self.random_seeds = Randomized.seeds()
         self.results = []
         self.duration = 0
-        self.iwss = iwss
         self._init_experiment()
 
     def get_output_file(self):
@@ -219,358 +212,48 @@ class Experiment:
         res["state_names"] = states
         return res
 
-    # def _n_fold_crossval(self, name, X, y, hyperparameters):
-    #     if self.scores != []:
-    #         raise ValueError("Must init experiment before!")
-
-    #     loop = tqdm(
-    #         self.random_seeds,
-    #         position=1,
-    #         leave=False,
-    #         disable=not self.progress_bar,
-    #     )
-
-    #     for random_state in loop:
-    #         loop.set_description(f"Seed({random_state:4d})")
-    #         random.seed(random_state)
-    #         np.random.seed(random_state)
-
-    #         kfold = self.stratified_class(
-    #             shuffle=True, random_state=random_state, n_splits=self.folds
-    #         )
-
-    #         clf = self._build_classifier(random_state, hyperparameters)
-    #         fit_params = self._build_fit_params(name)
-    #         self.version = Models.get_version(self.model_name, clf)
-
-    #         with warnings.catch_warnings():
-    #             warnings.filterwarnings("ignore")
-
-    #             if self.iwss:
-    #                 # Manual cross-validation with IWSS feature selection
-    #                 fold_scores = []
-    #                 fold_times = []
-    #                 fold_estimators = []
-
-    #                 for train_idx, test_idx in kfold.split(X, y):
-    #                     # Split data
-    #                     X_train, X_test = X[train_idx], X[test_idx]
-    #                     y_train, y_test = y[train_idx], y[test_idx]
-
-    #                     # Apply IWSS feature selection
-    #                     transformer = MUFS()
-    #                     transformer.iwss(X_train, y_train, 0.5)
-    #                     X_train_selected = X_train[
-    #                         :, transformer.get_results()
-    #                     ]
-    #                     X_test_selected = X_test[:, transformer.get_results()]
-    #                     # print("Selected features:", transformer.get_results())
-    #                     # print(
-    #                     #     f"Number of selected features: {X_train_selected.shape[1]}"
-    #                     # )
-
-    #                     # Clone classifier to avoid data leakage between folds
-    #                     clf_fold = clone(clf)
-
-    #                     # Fit the classifier
-    #                     start_time = time.time()
-    #                     clf_fold.fit(X_train_selected, y_train)
-    #                     fit_time = time.time() - start_time
-
-    #                     # Score on test set
-    #                     score_func = get_scorer(
-    #                         self.score_name.replace("-", "_")
-    #                     )
-    #                     # Handle scoring based on the metric type
-    #                     if self.score_name in [
-    #                         "roc_auc",
-    #                         "log_loss",
-    #                         "roc_auc_ovr",
-    #                         "roc_auc_ovo",
-    #                     ]:
-    #                         # These metrics need probabilities
-    #                         if hasattr(clf_fold, "predict_proba"):
-    #                             y_score = clf_fold.predict_proba(
-    #                                 X_test_selected
-    #                             )
-
-    #                             # Handle missing classes in the fold
-    #                             if len(unique_train_classes) < len(
-    #                                 unique_all_classes
-    #                             ):
-    #                                 # Create a full probability matrix with zeros for missing classes
-    #                                 y_score_full = np.zeros(
-    #                                     (len(y_test), len(unique_all_classes))
-    #                                 )
-    #                                 for i, class_label in enumerate(
-    #                                     unique_train_classes
-    #                                 ):
-    #                                     class_idx = np.where(
-    #                                         unique_all_classes == class_label
-    #                                     )[0][0]
-    #                                     y_score_full[:, class_idx] = y_score[
-    #                                         :, i
-    #                                     ]
-    #                                 y_score = y_score_full
-    #                         else:
-    #                             # Fallback to decision_function for SVM-like models
-    #                             y_score = clf_fold.decision_function(
-    #                                 X_test_selected
-    #                             )
-
-    #                         test_score = score_func._score_func(
-    #                             y_test, y_score
-    #                         )
-    #                     else:
-    #                         # For metrics that use predictions (accuracy, f1, etc.)
-    #                         test_score = score_func(
-    #                             clf_fold, X_test_selected, y_test
-    #                         )
-
-    #                     fold_scores.append(test_score)
-    #                     fold_times.append(fit_time)
-    #                     fold_estimators.append(clf_fold)
-
-    #                 # Package results to match cross_validate output format
-    #                 res = {
-    #                     "test_score": np.array(fold_scores),
-    #                     "fit_time": np.array(fold_times),
-    #                     "estimator": fold_estimators,
-    #                 }
-    #             else:
-    #                 # Original cross_validate approach
-    #                 res = cross_validate(
-    #                     clf,
-    #                     X,
-    #                     y,
-    #                     cv=kfold,
-    #                     fit_params=fit_params,
-    #                     return_estimator=True,
-    #                     scoring=self.score_name.replace("-", "_"),
-    #                 )
-
-    #             # Handle NaN values
-    #             if np.isnan(res["test_score"]).any():
-    #                 if not self.ignore_nan:
-    #                     print(res["test_score"])
-    #                     raise ValueError("NaN in results")
-    #                 results = res["test_score"][~np.isnan(res["test_score"])]
-    #             else:
-    #                 results = res["test_score"]
-
-    #             # Store results
-    #             self.scores.extend(results)
-    #             self.times.extend(res["fit_time"])
-
-    #             for result_item in res["estimator"]:
-    #                 nodes_item, leaves_item, depth_item = (
-    #                     Models.get_complexity(self.model_name, result_item)
-    #                 )
-    #                 self.nodes.append(nodes_item)
-    #                 self.leaves.append(leaves_item)
-    #                 self.depths.append(depth_item)
-
-    # from sklearn.base import clone
-    # import numpy as np
-    # import time
-    # import warnings
-    # from tqdm import tqdm
-
     def _n_fold_crossval(self, name, X, y, hyperparameters):
         if self.scores != []:
             raise ValueError("Must init experiment before!")
-
-        # Get all unique classes and check data
-        unique_all_classes = np.sort(np.unique(y))
-        n_classes = len(unique_all_classes)
-
-        # Check if we have enough samples per class for stratified k-fold
-        min_samples_per_class = np.min(np.bincount(y))
-        if min_samples_per_class < self.folds:
-            warnings.warn(
-                f"Class imbalance detected: minimum class has {min_samples_per_class} samples. "
-                f"Consider using fewer folds or handling imbalanced data."
-            )
-
         loop = tqdm(
             self.random_seeds,
             position=1,
             leave=False,
             disable=not self.progress_bar,
         )
-
         for random_state in loop:
             loop.set_description(f"Seed({random_state:4d})")
+            random.seed(random_state)
             np.random.seed(random_state)
-
             kfold = self.stratified_class(
                 shuffle=True, random_state=random_state, n_splits=self.folds
             )
-
             clf = self._build_classifier(random_state, hyperparameters)
             fit_params = self._build_fit_params(name)
             self.version = Models.get_version(self.model_name, clf)
-
-            # Check if the classifier supports probability predictions
-            scorer = check_scoring(clf, scoring="roc_auc_ovr")
-            if not hasattr(clf, "predict_proba") and not hasattr(
-                clf, "decision_function"
-            ):
-                raise ValueError(
-                    f"Classifier {self.model_name} doesn't support probability predictions "
-                    "required for ROC-AUC scoring"
-                )
-
             with warnings.catch_warnings():
                 warnings.filterwarnings("ignore")
-
-                fold_scores = []
-                fold_times = []
-                fold_estimators = []
-
-                for fold_idx, (train_idx, test_idx) in enumerate(
-                    kfold.split(X, y)
-                ):
-                    # Split data
-                    X_train, X_test = X[train_idx], X[test_idx]
-                    y_train, y_test = y[train_idx], y[test_idx]
-
-                    # Check classes in this fold
-                    unique_test_classes = np.unique(y_test)
-                    n_test_classes = len(unique_test_classes)
-
-                    # Skip fold if we don't have at least 2 classes in test set
-                    if n_test_classes < 2:
-                        warnings.warn(
-                            f"Fold {fold_idx}: Test set has only {n_test_classes} class(es). "
-                            f"Skipping this fold for ROC-AUC calculation."
+                res = cross_validate(
+                    clf,
+                    X,
+                    y,
+                    cv=kfold,
+                    fit_params=fit_params,
+                    return_estimator=True,
+                    scoring=self.score_name.replace("-", "_"),
                 )
-                        fold_scores.append(np.nan)
-                        fold_times.append(np.nan)
-                        fold_estimators.append(None)
-                        continue
-
-                    # Apply IWSS feature selection if enabled
-                    if self.iwss:
-                        # transformer = (
-                        #     MUFS(discrete=False)
-                        #     if "cli_rad" in name
-                        #     else MUFS(discrete=True)
-                        # )
-                        # transformer.iwss(X_train, y_train, 0.5)
-                        # selected_features = transformer.get_results()
-                        # Apply L1-based feature selection
-                        # Using LinearSVC with L1 penalty
-                        lsvc = LinearSVC(
-                            C=0.1,  # Regularization parameter - adjust this for more/fewer features
-                            penalty="l1",
-                            dual=False,
-                            max_iter=2000,
-                            random_state=random_state,
-                        )
-                        selector = SelectFromModel(lsvc, prefit=False)
-                        selector.fit(X_train, y_train)
-
-                        # Transform the data
-                        X_train_selected = selector.transform(X_train)
-                        X_test_selected = selector.transform(X_test)
-
-                        # Get information about selected features
-                        selected_features = selector.get_support(indices=True)
-                        n_selected = len(selected_features)
-                        if len(selected_features) == 0:
-                            warnings.warn(
-                                f"Fold {fold_idx}: No features selected by IWSS. Using all features."
-                            )
-                            X_train_selected = X_train
-                            X_test_selected = X_test
-                        else:
-                            X_train_selected = X_train[:, selected_features]
-                            X_test_selected = X_test[:, selected_features]
-                    else:
-                        X_train_selected = X_train
-                        X_test_selected = X_test
-
-                    # Clone and fit classifier
-                    clf_fold = clone(clf)
-
-                    start_time = time.time()
-                    clf_fold.fit(X_train_selected, y_train)
-                    fit_time = time.time() - start_time
-
-                    # Get probability predictions
-                    y_proba = clf_fold.predict_proba(X_test_selected)
-
-                    # Calculate ROC-AUC score
-                    # Handle case where test set doesn't have all classes
-                    if len(clf_fold.classes_) != len(unique_test_classes):
-                        # Map probabilities to only test classes
-                        test_class_indices = [
-                            np.where(clf_fold.classes_ == c)[0][0]
-                            for c in unique_test_classes
-                            if c in clf_fold.classes_
-                        ]
-                        y_proba = y_proba[:, test_class_indices]
-
-                    # Binarize labels for multi-class ROC-AUC
-                    y_test_binarized = label_binarize(
-                        y_test, classes=unique_test_classes
-                    )
-
-                    # Calculate ROC-AUC with OVR strategy
-                    if n_test_classes == 2:
-                        # Binary classification
-                        test_score = roc_auc_score(y_test, y_proba[:, 1])
-                    else:
-                        # Multi-class with macro-average
-                        test_score = roc_auc_score(
-                            y_test_binarized,
-                            y_proba,
-                            multi_class="ovr",
-                            average="macro",
-                        )
-
-                    fold_scores.append(test_score)
-                    fold_times.append(fit_time)
-                    fold_estimators.append(clf_fold)
-
-                # Filter out NaN scores if ignore_nan is True
-                scores_array = np.array(fold_scores)
-                times_array = np.array(fold_times)
-
-                if np.isnan(scores_array).any():
+            if np.isnan(res["test_score"]).any():
                 if not self.ignore_nan:
-                        nan_folds = np.where(np.isnan(scores_array))[0]
-                        raise ValueError(
-                            f"NaN scores in folds {nan_folds}. "
-                            f"Set ignore_nan=True to skip these folds."
-                        )
+                    print(res["test_score"])
+                    raise ValueError("NaN in results")
+                results = res["test_score"][~np.isnan(res["test_score"])]
             else:
-                        # Filter out NaN values
-                        valid_mask = ~np.isnan(scores_array)
-                        scores_array = scores_array[valid_mask]
-                        times_array = times_array[valid_mask]
-                        fold_estimators = [
-                            e
-                            for e, valid in zip(fold_estimators, valid_mask)
-                            if valid
-                        ]
-
-                        if len(scores_array) == 0:
-                            warnings.warn(
-                                f"All folds resulted in NaN for seed {random_state}. Skipping."
-                            )
-                            continue
-
-                # Store results
-                self.scores.extend(scores_array)
-                self.times.extend(times_array)
-
-                # Store complexity metrics
-                for estimator in fold_estimators:
-                    if estimator is not None:
-                        nodes_item, leaves_item, depth_item = (
-                            Models.get_complexity(self.model_name, estimator)
+                results = res["test_score"]
+            self.scores.extend(results)
+            self.times.extend(res["fit_time"])
+            for result_item in res["estimator"]:
+                nodes_item, leaves_item, depth_item = Models.get_complexity(
+                    self.model_name, result_item
                 )
                 self.nodes.append(nodes_item)
                 self.leaves.append(leaves_item)

benchmark/Models.py

@@ -8,8 +8,7 @@ from sklearn.ensemble import (
 )
 from sklearn.svm import SVC
 from stree import Stree
-
-# from bayesclass.clfs import TAN, KDB, AODE, KDBNew, TANNew, AODENew, BoostAODE
+from bayesclass.clfs import TAN, KDB, AODE, KDBNew, TANNew, AODENew
 from wodt import Wodt
 from odte import Odte
 from xgboost import XGBClassifier
@@ -40,13 +39,12 @@ class Models:
     def define_models(random_state):
         return {
             "STree": Stree(random_state=random_state),
-            # "TAN": TAN(random_state=random_state),
-            # "KDB": KDB(k=2),
-            # "TANNew": TANNew(random_state=random_state),
-            # "KDBNew": KDBNew(k=2),
-            # "AODENew": AODENew(random_state=random_state),
-            # "AODE": AODE(random_state=random_state),
-            # "BoostAODE": BoostAODE(random_state=random_state),
+            "TAN": TAN(random_state=random_state),
+            "KDB": KDB(k=2),
+            "TANNew": TANNew(random_state=random_state),
+            "KDBNew": KDBNew(k=2),
+            "AODENew": AODENew(random_state=random_state),
+            "AODE": AODE(random_state=random_state),
             "Cart": DecisionTreeClassifier(random_state=random_state),
             "ExtraTree": ExtraTreeClassifier(random_state=random_state),
             "Wodt": Wodt(random_state=random_state),
@@ -71,7 +69,6 @@ class Models:
                 algorithm="SAMME",
                 random_state=random_state,
             ),
-            "AdaBoost": AdaBoostClassifier(random_state=random_state),
             "GBC": GradientBoostingClassifier(random_state=random_state),
             "RandomForest": RandomForestClassifier(random_state=random_state),
             "Mock": MockModel(random_state=random_state),
@@ -100,13 +97,13 @@ class Models:
             nodes = 0
             leaves = result.get_n_leaves()
             depth = 0
-        elif name.startswith("Bagging") or name == "AdaBoostStree":
+        elif name.startswith("Bagging") or name.startswith("AdaBoost"):
             nodes, leaves = list(
                 zip(*[x.nodes_leaves() for x in result.estimators_])
             )
             nodes, leaves = mean(nodes), mean(leaves)
             depth = mean([x.depth_ for x in result.estimators_])
-        elif name == "RandomForest" or name == "AdaBoost":
+        elif name == "RandomForest":
             leaves = mean([x.get_n_leaves() for x in result.estimators_])
             depth = mean([x.get_depth() for x in result.estimators_])
             nodes = mean([x.tree_.node_count for x in result.estimators_])

benchmark/Results.py

@@ -71,6 +71,7 @@ class Report(BaseReport):
             self._load_best_results(
                 self.data["score_name"], self.data["model"]
             )
+        self._compare_totals = {}
         self.header_line("*")
         self.header_line(
             f" {self.data['model']} ver. {self.data['version']}"

benchmark/ResultsBase.py

@@ -52,11 +52,10 @@ class BaseReport(abc.ABC):
             self.score_name = self.data["score_name"]
         self.__load_env_data()
         self.__compute_best_results_ever()
-        self._compare_totals = {}
 
     def __load_env_data(self):
         # Set the labels for nodes, leaves, depth
-        env_data = EnvData().load()
+        env_data = EnvData.load()
         self.nodes_label = env_data["nodes"]
         self.leaves_label = env_data["leaves"]
         self.depth_label = env_data["depth"]
@@ -108,12 +107,10 @@ class BaseReport(abc.ABC):
                     status = (
                         Symbols.cross
                         if accuracy <= max_value
-                        else (
-                            Symbols.upward_arrow
+                        else Symbols.upward_arrow
                         if accuracy > max_value
                         else " "
                     )
-                    )
         if status != " ":
             if status not in self._compare_totals:
                 self._compare_totals[status] = 1
@@ -151,11 +148,8 @@ class BaseReport(abc.ABC):
 
 
 class StubReport(BaseReport):
-    def __init__(self, file_name, compare=False):
-        self.compare = compare
+    def __init__(self, file_name):
         super().__init__(file_name=file_name, best_file=False)
-        if self.compare:
-            self._load_best_results(self.score_name, self.data["model"])
 
     def print_line(self, line) -> None:
         pass
@@ -163,11 +157,6 @@ class StubReport(BaseReport):
     def header(self) -> None:
         self.title = self.data["title"]
         self.duration = self.data["duration"]
-        self.model = self.data["model"]
-        self.date = self.data["date"]
-        self.time = self.data["time"]
-        self.metric = self.data["score_name"]
-        self.platform = self.data["platform"]
 
     def footer(self, accuracy: float) -> None:
         self.accuracy = accuracy
@@ -176,7 +165,7 @@ class StubReport(BaseReport):
 
 class Summary:
     def __init__(self, hidden=False, compare=False) -> None:
-        self.results = Files.get_all_results(hidden=hidden)
+        self.results = Files().get_all_results(hidden=hidden)
         self.data = []
         self.data_filtered = []
         self.datasets = {}
@@ -202,11 +191,9 @@ class Summary:
                 self.models.add(model)
                 report = StubReport(
                     os.path.join(
-                        (
                         Folders.hidden_results
                         if self.hidden
-                            else Folders.results
-                        ),
+                        else Folders.results,
                         result,
                     )
                 )

benchmark/ResultsFiles.py

@@ -299,11 +299,11 @@ class ReportDatasets:
     color2 = "#FDE9D9"
     color3 = "#B1A0C7"
 
-    def __init__(self, excel=False, book=None, output=True):
+    def __init__(self, excel=False, book=None):
         self.excel = excel
         self.env = EnvData().load()
         self.close = False
-        self.output = output
+        self.output = True
         self.header_text = f"Datasets used in benchmark ver. {__version__}"
         if excel:
             self.max_length = 0
@@ -620,7 +620,7 @@ class Benchmark:
         self.__compute_best_results_ever()
 
     def __compute_best_results_ever(self):
-        args = EnvData().load()
+        args = EnvData.load()
         key = args["source_data"]
         best = BestResultsEver()
         _, self.best_score_value = best.get_name_value(key, self._score)

benchmark/Utils.py

@@ -15,7 +15,6 @@ class Folders:
     img = "img"
     excel = "excel"
     sql = "sql"
-    current = os.getcwd()
 
     @staticmethod
     def src():

benchmark/__init__.py

@@ -10,7 +10,7 @@ from .Results import Report
 from ._version import __version__
 
 __author__ = "Ricardo Montañana Gómez"
-__copyright__ = "Copyright 2020-2024, Ricardo Montañana Gómez"
+__copyright__ = "Copyright 2020-2023, Ricardo Montañana Gómez"
 __license__ = "MIT License"
 __author_email__ = "ricardo.montanana@alu.uclm.es"
 

benchmark/_version.py

@@ -1 +1 @@
-__version__ = "1.0.1"
+__version__ = "0.5.0"

benchmark/scripts/app/app.py

@@ -1,20 +0,0 @@
-#!/usr/bin/env python
-from benchmark.Arguments import EnvData
-from flask import Flask
-from .main import main, OUTPUT
-
-FRAMEWORK = "framework"
-FRAMEWORKS = "frameworks"
-TEST = "test"
-
-
-def create_app(output="local"):
-    app = Flask(__name__)
-    config = EnvData().load()
-    app.register_blueprint(main)
-    app.config[FRAMEWORK] = config[FRAMEWORK]
-    app.config[FRAMEWORKS] = ["bootstrap", "bulma"]
-    app.config[OUTPUT] = output
-    app.jinja_env.auto_reload = True
-    app.config["TEMPLATES_AUTO_RELOAD"] = True
-    return app

benchmark/scripts/app/static/excel/.gitignore

@@ -1 +0,0 @@
-*.xlsx

benchmark/scripts/app/templates/base_bootstrap.html

@@ -1,20 +0,0 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <title>{{ title }}</title>
-    <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha3/dist/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-KK94CHFLLe+nY2dmCWGMq91rCGa5gtU4mk92HdvYe+M/SXH301p5ILy+dN9+nJOZ" crossorigin="anonymous" />
-    <link href="https://fonts.googleapis.com/css?family=Montserrat:300,400,500,600" rel="stylesheet" />
-    <link rel="stylesheet" href="https://cdn.datatables.net/1.10.25/css/jquery.dataTables.min.css" />
-    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/MaterialDesign-Webfont/7.1.96/css/materialdesignicons.css" integrity="sha512-lD1LHcZ8tFHvMFNeo6qOLY/HjzSPCasPJOAoir22byDxlZI1R71S5lZel8zRL2TZ+Dut1wOHfYgSU2lHXuL00w==" crossorigin="anonymous" referrerpolicy="no-referrer" />
-     <link rel="stylesheet" href="{{ url_for('static', filename='css/main.css') }}" />
-  </head>
-  <body>
-    {% block content %}
-
-    {% endblock %}
-  </body>
-  <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
-  {% block jscript %}
-
-  {% endblock %}
-</html>

benchmark/scripts/app/templates/base_bulma.html

@@ -1,19 +0,0 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <title>{{ title }}</title>
-    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/bulma/0.9.3/css/bulma.min.css" />
-    <link rel="stylesheet" href="https://cdn.datatables.net/1.10.25/css/jquery.dataTables.min.css" />
-    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/MaterialDesign-Webfont/7.1.96/css/materialdesignicons.css" integrity="sha512-lD1LHcZ8tFHvMFNeo6qOLY/HjzSPCasPJOAoir22byDxlZI1R71S5lZel8zRL2TZ+Dut1wOHfYgSU2lHXuL00w==" crossorigin="anonymous" referrerpolicy="no-referrer" />
-    <link rel="stylesheet" href="{{ url_for('static', filename='css/main.css') }}" />
-  </head>
-  <body>
-    {% block content %}
-
-    {% endblock %}
-  </body>
-  <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
-  {% block jscript %}
-
-  {% endblock %}
-</html>

benchmark/scripts/app/templates/datasets.html

@@ -1,68 +0,0 @@
-{% extends 'base_' ~ framework ~ '.html' %}
-{% macro javascript(file) %}
-  <script src="{{ url_for('static', filename=file) }}"></script>
-{% endmacro %}
-{% if framework == 'bootstrap' %}
-  {% set button_class = 'btn btn-primary btn-small' %}
-  {% set h1_class = 'text-center' %}
-  {% set table_class = 'table table-striped table-hover table-bordered' %}
-  {% set head_class = 'bg-primary text-white' %}
-  {% set text_right = 'text-end' %}
-  {% set container = 'container' %}
-  {% set selected = 'selected' %}
-  {%- macro header(title, close, url) -%}
-    <div class="p-4 bg-primary text-white">
-      {%- if close -%}
-        <button type="button" class="btn-close" aria-label="Close" onclick="location.href = '{{ url }}'"></button>
-      {%- endif -%}
-      <h1 class="alternate-font">{{ title }}</h1>
-    </div>
-  {%- endmacro -%}
-{% else %}
-  {% set button_class = 'button is-primary is-small' %}
-  {% set h1_class = 'title is-1 has-text-centered' %}
-  {% set table_class = 'table is-striped is-hoverable cell-border is-bordered' %}
-  {% set head_class = 'is-selected' %}
-  {% set text_right = 'has-text-right' %}
-  {% set container = 'container' %}
-  {% set selected = 'is-selected' %}
-  {%- macro header(title, close, url) -%}
-    <div class="hero is-info is-bold">
-      <div class="hero-body">
-        {%- if close -%}
-          <button class="delete is-large" onclick="location.href = '{{ url }}'"></button>
-        {%- endif -%}
-        <h1 class="is-size-3 alternate-font">{{ title }}</h1>
-      </div>
-    </div>
-  {%- endmacro -%}
-{% endif %}
-{% block content %}
-  <div class="{{ container }}">
-    {{ header('Benchmark Datasets Report', True, url_for('main.index', compare = compare)) }}
-    <button class="{{ button_class }}" onclick="excelFiles(['datasets'], false)"><i class="mdi mdi-file-excel"></i> Excel</button>
-    {% include 'partials/datasets_table.html' %}
-  </div>
-{% endblock %}
-{% block jscript %}
-{{ javascript("js/excelFiles.js") }}
-  <script>
-    $(document).ready(function () {
-      $(document).ajaxStart(function(){ 
-          $("body").addClass('ajaxLoading');
-      });
-      $(document).ajaxStop(function(){ 
-          $("body").removeClass('ajaxLoading');
-      });
-    });
-    // Check if row is selected
-    $('#file-table tbody').on('click', 'tr', function () {
-      if ($(this).hasClass('{{ selected }}')) {
-          $(this).removeClass('{{ selected }}');
-      } else {
-          $('#file-table tbody tr.{{ selected }}').removeClass("{{ selected }}")
-          $(this).addClass('{{ selected }}');
-      }
-    });
-  </script>
-{% endblock %}

benchmark/scripts/app/templates/error.html

@@ -1,20 +0,0 @@
-<!DOCTYPE html>
-<html>
-    <head>
-        <title>Error</title>
-        <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha3/dist/css/bootstrap.min.css" rel="stylesheet"
-            integrity="sha384-KK94CHFLLe+nY2dmCWGMq91rCGa5gtU4mk92HdvYe+M/SXH301p5ILy+dN9+nJOZ" crossorigin="anonymous">
-    </head>
-    <body>
-        <div class="container">
-            <div class="alert alert-danger my-5" role="alert">
-
-                <h4 class="alert-heading"><button class="btn-close btn-sm" type="button"
-                        onclick="location.href='/index/{{ compare }}';"></button>Error</h4>
-                <p>There was an error processing action, {{ message }}. Please try again later.</p>
-                <hr>
-                <p class="mb-0">If the problem persists, please contact support.</p>
-            </div>
-        </div>
-    </body>
-</html>

benchmark/scripts/app/templates/js/report.js

@@ -1,22 +0,0 @@
-$(document).ready(function () {
-    // Check if row is selected
-    $('#report-table tbody').on('click', 'tr', function () {
-        if ($(this).hasClass('{{ selected }}')) {
-            $(this).removeClass('{{ selected }}');
-        } else {
-            $('#report-table tbody tr.{{ selected }}').removeClass("{{ selected }}")
-            $(this).addClass('{{ selected }}');
-        }
-    });
-    $(document).ajaxStart(function(){ 
-        $("body").addClass('ajaxLoading');
-    });
-    $(document).ajaxStop(function(){ 
-        $("body").removeClass('ajaxLoading');
-    });
-  });
-  function excelFile() {
-    var selectedFiles = ["{{ file }}"];
-    var compare = "{{ compare }}" == "True";
-    excelFiles(selectedFiles, compare)
-}

benchmark/scripts/app/templates/js/select.js

@@ -1,97 +0,0 @@
-$(document).ready(function () {
-  var table = $("#file-table").DataTable({
-    paging: true,
-    searching: true,
-    ordering: true,
-    info: true,
-    "select.items": "row",
-    pageLength: 25,
-    columnDefs: [
-      {
-        targets: 8,
-        orderable: false,
-      },
-    ],
-    //"language": {
-    //    "lengthMenu": "_MENU_"
-    //}
-  });
-  $('#file-table').on( 'draw.dt', function () {
-    enable_disable_best_buttons();
-  } );
-  // Check if row is selected
-  $("#file-table tbody").on("click", "tr", function () {
-    if ($(this).hasClass("{{ select.selected() }}")) {
-      $(this).removeClass("{{ select.selected() }}");
-    } else {
-      table
-        .$("tr.{{ select.selected() }}")
-        .removeClass("{{ select.selected() }}");
-      $(this).addClass("{{ select.selected() }}");
-    }
-  });
-  // Show file with doubleclick
-  $("#file-table tbody").on("dblclick", "tr", function () {
-    showFile($(this).attr("id"));
-  });
-  $(document).ajaxStart(function () {
-    $("body").addClass("ajaxLoading");
-  });
-  $(document).ajaxStop(function () {
-    $("body").removeClass("ajaxLoading");
-  });
-  $('#compare').change(function() {
-    enable_disable_best_buttons();
-  });
-  enable_disable_best_buttons();
-});
-function enable_disable_best_buttons(){
-  if ($('#compare').is(':checked')) {
-    $("[name='best_buttons']").addClass("tag is-link is-normal");
-      $("[name='best_buttons']").removeAttr("hidden");
-    } else {
-      $("[name='best_buttons']").removeClass("tag is-link is-normal");
-      $("[name='best_buttons']").attr("hidden", true);
-    }
-}
-function showFile(selectedFile) {
-  var form = $(
-    '<form action="/show" method="post">' +
-      '<input type="hidden" name="selected-file" value="' +
-      selectedFile +
-      '" />' +
-      '<input type="hidden" name="compare" value=' +
-      $("#compare").is(":checked") +
-      " />" +
-      "</form>"
-  );
-  $("body").append(form);
-  form.submit();
-}
-function excel() {
-  var checkbox = document.getElementsByName("selected_files");
-  var selectedFiles = [];
-  for (var i = 0; i < checkbox.length; i++) {
-    if (checkbox[i].checked) {
-      selectedFiles.push(checkbox[i].value);
-    }
-  }
-  if (selectedFiles.length == 0) {
-    alert("Select at least one file");
-    return;
-  }
-  var compare = $("#compare").is(":checked");
-  excelFiles(selectedFiles, compare);
-}
-function setCheckBoxes(value) {
-  var checkbox = document.getElementsByName("selected_files");
-  for (i = 0; i < checkbox.length; i++) {
-    checkbox[i].checked = value;
-  }
-}
-function redirectDouble(route, parameter) {
-  location.href = "/"+ route + "/" + parameter + "/" + $("#compare").is(":checked");
-}
-function redirectSimple(route) {
-  location.href = "/" + route + "/" + $("#compare").is(":checked");
-}

benchmark/scripts/app/templates/partials/cfg_select_bootstrap.jinja

@@ -1,56 +0,0 @@
-{%- macro header(title, close=False, url="") -%}
-<div class="p-4 bg-primary text-white">
-{%- if close -%}
-    <button type="button" class="btn-close" aria-label="Close" onclick="location.href = '{{url}}'"></button>
-{%- endif -%}
-<h1 class="alternate-font">{{ title }}</h1>
-</div>
-{%- endmacro -%}
-{%- macro get_table_class() -%}
-table table-striped table-hover table-bordered
-{%- endmacro -%}
-{%- macro icon(icon_name) -%}
-<i class="mdi mdi-{{icon_name}}"></i>
-{%- endmacro -%}
-{%- macro get_button(text, action) -%}
-    <button class="btn btn-primary btn-small" onclick="{{ action }}">{{ text|safe }}</button>
-{%- endmacro -%}
-{%- macro get_button_class() -%}
-    button btn-primary btn-small
-{%- endmacro %}
-{%- macro get_button_tag(icon_name, method, visible=True, name="") -%}
-    <button class="btn btn-primary btn-small" onclick="{{ method }}" {{ "" if visible else "hidden='true'" }} {{ "" if name=="" else "name='" + name +"'"}}><i class="mdi mdi-{{ icon_name }}"></i></button>
-{%- endmacro -%}
-{%- macro get_button_reset() -%}
-<button class="btn btn-primary btn-small btn-danger" onclick="setCheckBoxes(false)"><i class="mdi mdi-checkbox-multiple-blank"></i></button>
-{%- endmacro -%}
-{%- macro get_button_all() -%}
-<button class="btn btn-primary btn-small btn-success" onclick="setCheckBoxes(true)"><i class="mdi mdi-checkbox-multiple-marked"></i></button>
-{%- endmacro -%}
-{%- macro get_tag_class() -%}
-badge bg-info bg-small
-{%- endmacro -%}
-{%- macro get_container_class() -%}
-container-fluid
-{%- endmacro -%}
-{%- macro selected() -%}
-selected
-{%- endmacro -%}
-{%- macro get_level_class() -%}
-navbar
-{%- endmacro -%}
-{%- macro get_align_right() -%}
-text-end
-{%- endmacro -%}
-{%- macro get_left_position() -%}
-float-left
-{%- endmacro -%}
-{%- macro get_right_position() -%}
-float-right
-{%- endmacro -%}
-{%- macro get_row_head_class() -%}
-bg-primary text-white
-{%- endmacro -%}
-{%- macro get_align_center() -%}
-text-center
-{%- endmacro -%}

benchmark/scripts/app/templates/partials/cfg_select_bulma.jinja

@@ -1,58 +0,0 @@
-{%- macro header(title, close=False, url="") -%}
-<div class="hero is-info is-bold">
-<div class="hero-body">
-    {%- if close -%}
-    <button class="delete is-large" onclick="location.href = '{{ url }}'"></button>
-    {%- endif -%}
-    <h1 class="is-size-3 alternate-font">{{ title }}</h1>
-</div>
-</div>
-{%- endmacro -%}
-{%- macro get_table_class() -%}
-table is-striped is-hoverable cell-border is-bordered
-{%- endmacro -%}
-{%- macro icon(icon_name) -%}
-<i class="mdi mdi-{{icon_name}}"></i>
-{%- endmacro -%}
-{%- macro get_button(text, action) -%}
-    <button class="button is-primary is-small" onclick="{{ action }}">{{ text|safe }}</button>
-{%- endmacro -%}
-{%- macro get_button_tag(icon_name, method, visible=True, name="") -%}
-    <span class="{{ "tag is-link is-normal" if visible else "" }}" type="button" onclick="{{ method }}" {{ "" if visible else "hidden='true'" }} {{ "" if name=="" else "name='" + name +"'"}}>{{icon(icon_name)}}</span>
-{%- endmacro -%}
-{%- macro get_button_reset() -%}
-    <span class="tag is-link is-danger" type="button" onclick="setCheckBoxes(false)"><i class="mdi mdi-checkbox-multiple-blank"></i></span>
-{%- endmacro -%}
-{%- macro get_button_all() -%}
-    <span class="tag is-link is-success" type="button" onclick="setCheckBoxes(true)"><i class="mdi mdi-checkbox-multiple-marked"></i></span>
-{%- endmacro -%}
-{%- macro get_tag_class() -%}
-tag is-info is-small
-{%- endmacro -%}
-{%- macro get_container_class() -%}
-container is-fluid
-{%- endmacro -%}
-{%- macro selected() -%}
-is-selected
-{%- endmacro -%}
-{%- macro get_level_class() -%}
-level
-{%- endmacro -%}
-{%- macro get_align_right() -%}
-has-text-right
-{%- endmacro -%}
-{%- macro get_align_center() -%}
-has-text-center
-{%- endmacro -%}
-{%- macro get_left_position() -%}
-float-left
-{%- endmacro -%}
-{%- macro get_right_position() -%}
-float-right
-{%- endmacro -%}
-{%- macro get_row_head_class() -%}
-is-selected
-{%- endmacro -%}
-{%- macro get_align_center() -%}
-has-text-center
-{%- endmacro -%}

benchmark/scripts/app/templates/partials/datasets_table.html

@@ -1,27 +0,0 @@
-{% extends "base_" ~ framework ~ ".html" %}
-{% block content %}
-  <table id="file-table" class="{{ table_class }}">
-    <thead>
-      <tr class="{{ head_class }}">
-        <th class="{{ text_center }}">Dataset</th>
-        <th class="{{ text_center }}">Samples</th>
-        <th class="{{ text_center }}">Features</th>
-        <th class="{{ text_center }}">Cont. Feat.</th>
-        <th class="{{ text_center }}">Classes</th>
-        <th class="{{ text_center }}">Balance</th>
-      </tr>
-    </thead>
-    <tbody>
-      {% for dataset in datasets %}
-        <tr>
-          <td>{{ dataset.dataset }}</td>
-          <td class="{{ text_right }}">{{ "{:,}".format(dataset.samples) }}</td>
-          <td class="{{ text_right }}">{{ "{:,}".format(dataset.features) }}</td>
-          <td class="{{ text_right }}">{{ dataset.cont_features }}</td>
-          <td class="{{ text_right }}">{{ dataset.classes }}</td>
-          <td>{{ dataset.balance }}</td>
-        </tr>
-      {% endfor %}
-    </tbody>
-  </table>
-{% endblock %}

benchmark/scripts/app/templates/partials/table_report.html

@@ -1,14 +0,0 @@
-{% for item in data.results %}
-  <tr>
-    <td>{{ item.dataset }}</td>
-    <td class="{{ right }}">{{ '{:,}'.format(item.samples) }}</td>
-    <td class="{{ right }}">{{"%d" % item.features}}</td>
-    <td class="{{ right }}">{{"%d" % item.classes}}</td>
-    <td class="{{ right }}">{{ '{:,.2f}'.format(item.nodes|float) }}</td>
-    <td class="{{ right }}">{{ '{:,.2f}'.format(item.leaves|float) }}</td>
-    <td class="{{ right }}">{{ '{:,.2f}'.format(item.depth|float) }}</td>
-    <td class="{{ right }}">{{"%.6f±%.4f" % (item.score, item.score_std)}} {{ item.symbol|safe }}</td>
-    <td class="{{ right }}">{{"%.6f±%.4f" % (item.time, item.time_std)}}</td>
-    <td class="{{ center }}">{{ item.hyperparameters }}</td>
-  </tr>
-{% endfor %}

benchmark/scripts/app/templates/partials/table_report_bootstrap.html

@@ -1,102 +0,0 @@
-<div id="app">
-  <section class="section">
-    <div class="container-fluid">
-      <div class="p-4 bg-primary text-white">
-        <button type="button"
-                class="btn-close"
-                aria-label="Close"
-                onclick="location.href = '{{ back }}'"></button>
-        <h1>{{ data.title }}</h1>
-      </div>
-      <div>
-        <table class="table table-bordered">
-          <thead>
-            <tr class="bg-info text-white">
-              <th class="text-center">Platform</th>
-              <th class="text-center">Model</th>
-              <th class="text-center">Date</th>
-              <th class="text-center">Time</th>
-              {% if data.duration > 7200 %}
-                {% set unit = "h" %}
-                {% set divider = 3600 %}
-              {% else %}
-                {% set unit = "min" %}
-                {% set divider = 60 %}
-              {% endif %}
-              <th class="text-center">Duration ({{ unit }})</th>
-              <th class="text-center">Stratified</th>
-              <th class="text-center">Discretized</th>
-              <th class="text-center"># Folds</th>
-            </tr>
-            <tr>
-              <th class="text-center">{{ data.platform }}</th>
-              <th class="text-center">{{ data.model }} {{ data.version }}</th>
-              <th class="text-center">{{ data.date }}</th>
-              <th class="text-center">{{ data.time }}</th>
-              <th class="text-center">{{ "%.2f" % (data.duration/divider) }}</th>
-              <th class="text-center">{{ data.stratified }}</th>
-              <th class="text-center">{{ data.discretized }}</th>
-              <th class="text-center">{{ data.folds }}</th>
-            </tr>
-            <tr>
-              <th class="text-center bg-info text-white">Language</th>
-              <th class="text-center" colspan=3>{{ data.language }} {{ data.language_version }}</th>
-              <th class="text-center bg-info text-white">Seeds</th>
-              <th class="text-center" colspan=6>{{ data.seeds }}</th>
-            </tr>
-          </thead>
-        </table>
-        <div>
-          <button class="{{ button }}" onclick="excelFile()">
-            <i class="mdi mdi-file-excel"></i> Excel
-          </button>
-        </div>
-        <table id="report-table"
-               class="table table-striped table-hover table-bordered">
-          <thead>
-            <tr class="bg-primary text-white">
-              <th class="text-center">Dataset</th>
-              <th class="text-center">Samples</th>
-              <th class="text-center">Features</th>
-              <th class="text-center">Classes</th>
-              <th class="text-center">{{ app_config.nodes }}</th>
-              <th class="text-center">{{ app_config.leaves }}</th>
-              <th class="text-center">{{ app_config.depth }}</th>
-              <th class="text-center">{{ data.score_name|capitalize }}</th>
-              <th class="text-center">Time</th>
-              <th class="text-center">hyperparameters</th>
-            </tr>
-          </thead>
-          <tbody>
-            {% include "partials/table_report.html" %}
-          </tbody>
-        </table>
-        {% if summary|length > 0 %}
-          <div class="col-4 col-lg-4">
-            <table class="table table-bordered">
-              <thead>
-                <tr>
-                  <th class="text-center bg-primary text-white">Symbol</th>
-                  <th class="text-center bg-primary text-white">Meaning</th>
-                  <th class="text-center bg-primary text-white">Count</th>
-                </tr>
-              </thead>
-              {% include "partials/table_summary.html" %}
-            </table>
-          </div>
-        {% endif %}
-        <button type="button"
-                class="btn-close"
-                aria-label="Close"
-                onclick="location.href = '{{ back }}'"></button>
-        <h7>
-        <b>
-          Total score: {{ "%.6f" % (data.results | sum(attribute="score") ) }}
-        </b>
-        </h7>
-        <h7>
-        Number of files: {{ data.results | length }}
-        </h7>
-      </div>
-    </section>
-  </div>

benchmark/scripts/app/templates/partials/table_report_bulma.html

@@ -1,100 +0,0 @@
-<div id="app">
-  <header>
-    <div class="container is-fluid">
-      <div class="hero is-info is-bold">
-        <div class="hero-body">
-          <button class="delete is-large" onclick="location.href = '{{ back }}'"></button>
-          <h1 class="is-size-3">{{ data.title }}</h1>
-        </div>
-      </div>
-    </div>
-  </header>
-  <section class="section">
-    <div class="container is-fluid">
-      <div>
-        <table class="table is-fullwidth is-striped is-bordered">
-          <thead>
-            <tr class="is-selected">
-              <th class="has-text-centered">Platform</th>
-              <th class="has-text-centered">Model</th>
-              <th class="has-text-centered">Date</th>
-              <th class="has-text-centered">Time</th>
-              {% if data.duration > 7200 %}
-                {% set unit = "h" %}
-                {% set divider = 3600 %}
-              {% else %}
-                {% set unit = "min" %}
-                {% set divider = 60 %}
-              {% endif %}
-              <th class="has-text-centered">Duration ({{ unit }})</th>
-              <th class="has-text-centered">Stratified</th>
-              <th class="has-text-centered">Discretized</th>
-              <th class="has-text-centered"># Folds</th>
-            </tr>
-            <tr>
-              <th class="has-text-centered">{{ data.platform }}</th>
-              <th class="has-text-centered">{{ data.model }} {{ data.version }}</th>
-              <th class="has-text-centered">{{ data.date }}</th>
-              <th class="has-text-centered">{{ data.time }}</th>
-              <th class="has-text-centered">{{ "%.2f" % (data.duration/divider) }}</th>
-              <th class="has-text-centered">{{ data.stratified }}</th>
-              <th class="has-text-centered">{{ data.discretized }}</th>
-              <th class="has-text-centered">{{ data.folds }}</th>
-            </tr>
-            <tr>
-              <th class="has-text-center is-selected">Language</th>
-              <th class="has-text-centered" colspan=3>{{ data.language }} {{ data.language_version }}</th>
-              <th class="has-text-centered is-selected">Seeds</th>
-              <th class="has-text-centered" colspan=6>{{ data.seeds }}</th>
-            </tr>
-          </thead>
-        </table>
-        <div>
-          <button class="{{ button }}" onclick="excelFile()">
-            <i class="mdi mdi-file-excel"></i> Excel
-          </button>
-        </div>
-        <table id="report-table"
-               class="table is-fullwidth is-striped is-hoverable is-bordered">
-          <thead>
-            <tr class="is-selected">
-              <th class="has-text-centered">Dataset</th>
-              <th class="has-text-centered">Samples</th>
-              <th class="has-text-centered">Features</th>
-              <th class="has-text-centered">Classes</th>
-              <th class="has-text-centered">{{ app_config.nodes }}</th>
-              <th class="has-text-centered">{{ app_config.leaves }}</th>
-              <th class="has-text-centered">{{ app_config.depth }}</th>
-              <th class="has-text-centered">{{ data.score_name|capitalize }}</th>
-              <th class="has-text-centered">Time</th>
-              <th class="has-text-centered">hyperparameters</th>
-            </tr>
-          </thead>
-          <tbody>
-            {% include "partials/table_report.html" %}
-          </tbody>
-        </table>
-        {% if summary|length > 0 %}
-          <div class="col-2 col-lg-2">
-            <table class="table is-bordered">
-              <thead>
-                <tr class="is-selected">
-                  <th class="has-text-centered">Symbol</th>
-                  <th class="has-text-centered">Meaning</th>
-                  <th class="has-text-centered">Count</th>
-                </tr>
-              </thead>
-              {% include "partials/table_summary.html" %}
-            </table>
-          </div>
-        {% endif %}
-        <h2 class="has-text-white has-background-primary">
-          <b>
-            <button class="delete" onclick="location.href = '{{ back }}'"></button>
-            Total score: {{ "%.6f" % (data.results | sum(attribute="score") ) }}
-          </b>
-        </h2>
-        <h2>Number of files: {{ data.results | length }}</h2>
-      </div>
-    </section>
-  </div>

benchmark/scripts/app/templates/partials/table_select.html

@@ -1,41 +0,0 @@
-<table id="file-table" class="{{ select.get_table_class() }}">
-  <thead>
-    <tr>
-      <th>Model</th>
-      <th>Metric</th>
-      <th>Platform</th>
-      <th>Date</th>
-      <th>Time</th>
-      <th>Stratified</th>
-      <th>Title</th>
-      <th>Score</th>
-      <th>{{ select.get_button_reset()|safe }} {{ select.get_button_all()|safe }}</th>
-    </tr>
-  </thead>
-  <tbody>
-    {% for file, data in files.items() %} 
-      {% set parts = file.split('_') %} 
-      {% set stratified = parts[6].split('.')[0] %}
-      <tr id="{{ file }}">
-        <td>{{ parts[2] }}</td>
-        <td>{{ parts[1] }}</td>
-        <td>{{ parts[3] }}</td>
-        <td>{{ parts[4] }}</td>
-        <td>{{ parts[5] }}</td>
-        <td>{{ 'True' if stratified =='1' else 'False' }}</td>
-        <td>{{ "%s" % data["title"] }}</td>
-        <td class="{{ select.get_align_right() }}">{{ "%.6f" % data["score"] }}</td>
-        <td>
-          {{ select.get_button_tag("table-eye", "showFile('" ~ file ~ "')") | safe }}
-          {% set file_best = "best_results_" ~ parts[1] ~ "_" ~ parts[2] ~ ".json" %}
-          {{ select.get_button_tag("star-circle-outline", "redirectDouble('best_results', '" ~ file_best ~ "')", visible=False, name="best_buttons") | safe }}
-          <input
-            type="checkbox"
-            name="selected_files"
-            value="{{ file }}"
-          />
-        </td>
-      </tr>
-    {% endfor %}
-  </tbody>
-</table>

benchmark/scripts/app/templates/partials/table_select_design.html

@@ -1,15 +0,0 @@
-<div class="{{ select.get_container_class() }}">
-    {{ select.header("Benchmark Results") }}
-    <div class="{{ select.get_level_class() }}">
-        <div class="{{ select.get_left_position() }}">
-            {{ select.get_button("Use " ~ candidate, "redirectDouble('config', '" ~ candidate ~ "')")|safe }}
-            {{ select.get_button(select.icon("excel") ~ " Excel", "excel()")|safe }}
-            {{ select.get_button(select.icon("database-eye") ~ " Datasets", "redirectSimple('datasets')")|safe }}
-        </div>
-        <div class="{{ select.get_right_position() }}">
-            <input type="checkbox" id="compare" name="compare" {% if compare %} {{ "checked" }} {% endif %}>
-            <span class="{{ select.get_tag_class() }}">Comparing with best results</span>
-        </div>
-    </div>
-    {% include "partials/table_select.html" %}
-</div>

benchmark/scripts/app/templates/partials/table_summary.html

@@ -1,13 +0,0 @@
-{% for key, value in summary.items() %}
-    <tr>
-        <td class="{{ center }}">
-            {{key}}
-        </td>
-        <td >
-            {{value[0]}}
-        </td>
-        <td class={{ right }}>
-            {{'{:,}'.format(value[1])}}
-        </td>
-    </tr>
-{% endfor %}

benchmark/scripts/app/templates/report.html

@@ -1,29 +0,0 @@
-{% macro javascript(file) %}
-  <script src="{{ url_for('static', filename=file) }}"></script>
-{% endmacro %}
-{% set title = 'Report Viewer' %}
-{% extends 'base_' ~ framework ~ '.html' %}
-{% block content %}
-  {% if framework == 'bootstrap' %}
-    {% set center = 'text-center' %}
-    {% set right = 'text-end' %}
-    {% set button = 'btn btn-primary' %}
-    {% include 'partials/table_report_bootstrap.html' %}
-  {% else %}
-    {% set center = 'has-text-centered' %}
-    {% set right = 'has-text-right' %}
-    {% set button = 'button is-primary' %}
-    {% include 'partials/table_report_bulma.html' %}
-  {% endif %}
-{% endblock %}
-{% block jscript %}
-  {% if framework == 'bootstrap' %}
-    {% set selected = 'selected' %}
-  {% else %}
-    {% set selected = 'is-selected' %}
-  {% endif %}
-  <script>
-    {% include "js/report.js" %}
-  </script>
-  {{ javascript("js/excelFiles.js") }}
-{% endblock %}

benchmark/scripts/app/templates/report_best.html

@@ -1,47 +0,0 @@
-{% set title = "Best Results" %}
-{% extends "base_" ~ framework ~ ".html" %}
-{% import "partials/cfg_select_" ~ framework ~ ".jinja" as select %}
-{% block content %}
-    <div class="container">
-        {{ select.header(title, True, url_for("main.index", compare=compare)) }}
-        <table id="file-table" class="{{ select.get_table_class() }}">
-            <thead>
-                <tr class="{{ select.get_row_head_class() }}">
-                <th class="{{ select.get_align_center() }}">Dataset</th>
-                <th class="{{ select.get_align_center() }}">Score</th>
-                <th class="{{ select.get_align_center() }}">Hyperparameters</th>
-                <th class="{{ select.get_align_center() }}">File</th>
-                </tr>
-            </thead>
-            <tbody>
-                {% for dataset, info in data.items() %}
-                <tr>
-                    <td>{{ dataset }}</td>
-                    <td class="{{ select.get_align_right() }}">{{ '%9.7f' % info[0] }}</td>
-                    <td class="{{ select.get_align_center() }}">{{ info[1] }}</td>
-                    <td>
-                    {% set url = url_for(request.endpoint, **request.view_args)|urlencode %}
-                    <a href="{{ url_for('main.showfile', file_name = info[2], compare = compare) }}?url={{ url }}">{{ info[2] }}</a>
-                    </td>
-                </tr>
-                {% endfor %}
-            </tbody>
-        </table>
-    </div>
-{% endblock %}
-{% block jscript %}
-<script>
-    $(document).ready(function () {
-        // Check if row is selected
-        $('#file-table tbody').on('click', 'tr', function () {
-            if ($(this).hasClass('{{ select.selected() }}')) {
-                $(this).removeClass('{{ select.selected() }}');
-            } else {
-                $('#file-table tbody tr.{{ select.selected() }}').removeClass("{{ select.selected() }}")
-                $(this).addClass('{{ select.selected() }}');
-            }
-        });
-  });
-</script>
-{% endblock %}
-

benchmark/scripts/app/templates/select.html

@@ -1,20 +0,0 @@
-{% macro javascript(file) %}
-  <script src="{{ url_for('static', filename=file) }}"></script>
-{% endmacro %}
-{% set title = 'Benchmark Results' %}
-{% extends 'base_' ~ framework ~ '.html' %}
-{% import 'partials/cfg_select_' ~ framework ~ '.jinja' as select %}
-{% block content %}
-  {% include 'partials/table_select_design.html' %}
-{% endblock %}
-
-{% block jscript %}
-  <script src="https://cdn.datatables.net/1.10.25/js/jquery.dataTables.min.js"></script>
-  {% if framework == 'bootstrap' %}
-    <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.2.3/dist/js/bootstrap.min.js" integrity="sha384-cuYeSxntonz0PPNlHhBs68uyIAVpIIOZZ5JqeqvYYIcEL727kskC66kF92t6Xl2V" crossorigin="anonymous"></script>
-  {% endif %}
-  <script>
-    {% include'/js/select.js' %}
-  </script>
-  {{ javascript('js/excelFiles.js') }}
-{% endblock %}

benchmark/scripts/be_flask.py

@@ -1,18 +1,14 @@
 #!/usr/bin/env python
 import webbrowser
-from benchmark.Arguments import Arguments
-from benchmark.scripts.app.app import create_app, TEST, OUTPUT
+from benchmark.scripts.flask_app.app import create_app
+
 
 # Launch a flask server to serve the results
-
 def main(args_test=None):
-    arguments = Arguments(prog="be_flask")
-    arguments.xset("output")
-    args = arguments.parse(args_test)
     app = create_app()
-    app.config[TEST] = args_test is not None
-    app.config[OUTPUT] = args.output
-    print("Output is ", args.output)
-    if args.output == "local":
+    app.config["TEST"] = args_test is not None
+    output = app.config["OUTPUT"]
+    print("Output is ", output)
+    if output == "local":
         webbrowser.open_new("http://127.0.0.1:1234/")
     app.run(port=1234, host="0.0.0.0")

benchmark/scripts/be_main.py

@@ -14,7 +14,7 @@ def main(args_test=None):
     arguments.xset("stratified").xset("score").xset("model", mandatory=True)
     arguments.xset("n_folds").xset("platform").xset("quiet").xset("title")
     arguments.xset("report").xset("ignore_nan").xset("discretize")
-    arguments.xset("fit_features").xset("iwss")
+    arguments.xset("fit_features")
     arguments.add_exclusive(
         ["grid_paramfile", "best_paramfile", "hyperparameters"]
     )
@@ -43,7 +43,6 @@ def main(args_test=None):
             folds=args.n_folds,
             fit_features=args.fit_features,
             discretize=args.discretize,
-            iwss=args.iwss,
         )
         job.do_experiment()
     except ValueError as e:

benchmark/scripts/flask_app/.env

@@ -0,0 +1,2 @@
+OUTPUT="local"
+FRAMEWORK="bulma"

benchmark/scripts/flask_app/app.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python
+from flask import Flask
+from flask_bootstrap import Bootstrap5
+from flask_login import LoginManager
+from .config import Config
+from .models import User, db
+
+from .results.main import results
+from .main import main
+
+bootstrap = Bootstrap5()
+
+login_manager = LoginManager()
+
+
+@login_manager.user_loader
+def load_user(user_id):
+    return User.query.get(int(user_id))
+
+
+def make_shell_context():
+    return {"db": db, "User": User}
+
+
+def create_app():
+    app = Flask(__name__)
+    bootstrap.init_app(app)
+    # app.register_blueprint(results)
+    app.config.from_object(Config)
+    db.init_app(app)
+    login_manager.init_app(app)
+    login_manager.login_view = "main.login"
+    app.jinja_env.auto_reload = True
+    app.register_blueprint(results, url_prefix="/results")
+    app.register_blueprint(main)
+    app.shell_context_processor(make_shell_context)
+    with app.app_context():
+        db.create_all()
+    return app

benchmark/scripts/flask_app/config.py

@@ -0,0 +1,17 @@
+import os
+from dotenv import load_dotenv
+
+basedir = os.path.abspath(os.path.dirname(__file__))
+load_dotenv(os.path.join(basedir, ".env"))
+
+
+class Config(object):
+    FRAMEWORKS = ["bootstrap", "bulma"]
+    FRAMEWORK = os.environ.get("FRAMEWORK") or FRAMEWORKS[0]
+    OUTPUT = os.environ.get("OUTPUT") or "local"  # local or docker
+    TEMPLATES_AUTO_RELOAD = True
+    SECRET_KEY = os.environ.get("SECRET_KEY") or "really-hard-to-guess-key"
+    SQLALCHEMY_DATABASE_URI = os.environ.get(
+        "DATABASE_URL"
+    ) or "sqlite:///" + os.path.join(basedir, "app.db")
+    SQLALCHEMY_TRACK_MODIFICATIONS = False

benchmark/scripts/flask_app/forms.py

@@ -0,0 +1,22 @@
+from flask_wtf import FlaskForm
+from wtforms import (
+    StringField,
+    PasswordField,
+    BooleanField,
+    SubmitField,
+)
+from wtforms.validators import (
+    DataRequired,
+    Length,
+)
+
+
+class LoginForm(FlaskForm):
+    username = StringField(
+        "Username", validators=[DataRequired(), Length(1, 20)]
+    )
+    password = PasswordField(
+        "Password", validators=[DataRequired(), Length(4, 150)]
+    )
+    remember_me = BooleanField("Remember me")
+    submit = SubmitField()

benchmark/scripts/flask_app/main.py

@@ -0,0 +1,51 @@
+from flask import (
+    Blueprint,
+    render_template,
+    url_for,
+    flash,
+    redirect,
+    request,
+)
+from flask_login import login_user, current_user, logout_user, login_required
+from werkzeug.urls import url_parse
+from .forms import LoginForm
+from .models import User
+
+main = Blueprint("main", __name__)
+
+
+@main.route("/")
+@main.route("/index")
+def index():
+    return render_template("index.html")
+
+
+@main.route("/config")
+@login_required
+def config():
+    return render_template("config.html")
+
+
+@main.route("/login", methods=["GET", "POST"])
+def login():
+    if current_user.is_authenticated:
+        return redirect(url_for("main.index"))
+    form = LoginForm()
+    if form.validate_on_submit():
+        user = User.query.filter_by(username=form.username.data).first()
+        if user is None or not user.check_password(form.password.data):
+            flash("Invalid username or password")
+            return redirect(url_for("main.login"))
+        login_user(user, remember=form.remember_me.data)
+        flash("Logged in successfully.")
+        next_page = request.args.get("next")
+        if not next_page or url_parse(next_page).netloc != "":
+            next_page = url_for("main.index")
+        return redirect(next_page)
+    return render_template("login.html", title="Sign In", form=form)
+
+
+@main.route("/logout")
+def logout():
+    logout_user()
+    return redirect(url_for("main.index"))

benchmark/scripts/flask_app/models.py

@@ -0,0 +1,29 @@
+from hashlib import md5
+from flask_sqlalchemy import SQLAlchemy
+from sqlalchemy import Column, Integer, String
+from flask_login import UserMixin
+from werkzeug.security import generate_password_hash, check_password_hash
+
+db = SQLAlchemy()
+
+
+class User(UserMixin, db.Model):
+    id = Column(Integer, primary_key=True)
+    username = Column(String(64), index=True, unique=True)
+    email = Column(String(120), index=True, unique=True)
+    password_hash = Column(String(128))
+
+    def __repr__(self):
+        return "<User {} {}>".format(self.username, self.email)
+
+    def set_password(self, password):
+        self.password_hash = generate_password_hash(password)
+
+    def check_password(self, password):
+        return check_password_hash(self.password_hash, password)
+
+    def avatar(self, size):
+        digest = md5(self.email.lower().encode("utf-8")).hexdigest()
+        return "https://www.gravatar.com/avatar/{}?d=identicon&s={}".format(
+            digest, size
+        )

benchmark/scripts/flask_app/results/main.py

@@ -0,0 +1,46 @@
+import os
+import json
+import shutil
+import xlsxwriter
+from benchmark.Utils import Files, Folders
+from benchmark.Arguments import EnvData
+from benchmark.ResultsBase import StubReport
+from benchmark.ResultsFiles import Excel, ReportDatasets
+from benchmark.Datasets import Datasets
+from flask import Blueprint, current_app, send_file
+from flask import render_template, current_app, request, redirect, url_for
+from flask_login import login_required
+
+results = Blueprint("results", __name__, template_folder="templates")
+
+
+@results.route("/select")
+@login_required
+def select(compare="False"):
+    # Get a list of files in a directory
+    files = {}
+    names = Files.get_all_results(hidden=False)
+    for name in names:
+        report = StubReport(os.path.join(Folders.results, name))
+        report.report()
+        files[name] = {
+            "duration": report.duration,
+            "score": report.score,
+            "title": report.title,
+        }
+    candidate = current_app.config["FRAMEWORKS"].copy()
+    candidate.remove(current_app.config["FRAMEWORK"])
+    return render_template(
+        "select.html",
+        files=files,
+        candidate=candidate[0],
+        framework=current_app.config["FRAMEWORK"],
+        compare=compare.capitalize() == "True",
+    )
+    return render_template("test.html")
+
+
+@results.route("/datasets")
+@login_required
+def datasets(compare="False"):
+    return render_template("test.html")

benchmark/scripts/flask_app/results/results.ant.py

@@ -1,89 +1,91 @@
 #!/usr/bin/env python
-import os
-import json
-import shutil
-import xlsxwriter
-from dotenv import dotenv_values
-from benchmark.Utils import Files, Folders
-from benchmark.Arguments import EnvData
-from benchmark.ResultsBase import StubReport
-from benchmark.ResultsFiles import Excel, ReportDatasets
-from benchmark.Datasets import Datasets
-from flask import Blueprint, current_app, send_file
-from flask import render_template, request, redirect, url_for
+# import os
+# import json
+# import shutil
+# import xlsxwriter
+# from benchmark.Utils import Files, Folders
+# from benchmark.Arguments import EnvData
+# from benchmark.ResultsBase import StubReport
+# from benchmark.ResultsFiles import Excel, ReportDatasets
+# from benchmark.Datasets import Datasets
+# from flask import Blueprint, current_app, send_file
+# from flask import render_template, request, redirect, url_for
+from flask import Blueprint, render_template
 
 
-main = Blueprint("main", __name__)
-FRAMEWORK = "framework"
-FRAMEWORKS = "frameworks"
-OUTPUT = "output"
-TEST = "test"
+results = Blueprint("results", __name__, template_folder="results")
+# FRAMEWORK = "framework"
+# FRAMEWORKS = "frameworks"
+# OUTPUT = "output"
+# TEST = "test"
 
 
-class AjaxResponse:
-    def __init__(self, success, file_name, code=200):
-        self.success = success
-        self.file_name = file_name
-        self.code = code
+# class AjaxResponse:
+#     def __init__(self, success, file_name, code=200):
+#         self.success = success
+#         self.file_name = file_name
+#         self.code = code
 
-    def to_string(self):
-        return (
-            json.dumps(
-                {
-                    "success": self.success,
-                    "file": self.file_name,
-                    "output": current_app.config[OUTPUT],
-                }
-            ),
-            self.code,
-            {"ContentType": "application/json"},
-        )
+#     def to_string(self):
+#         return (
+#             json.dumps(
+#                 {
+#                     "success": self.success,
+#                     "file": self.file_name,
+#                     "output": current_app.config[OUTPUT],
+#                 }
+#             ),
+#             self.code,
+#             {"ContentType": "application/json"},
+#         )
 
 
-def process_data(file_name, compare, data):
-    report = StubReport(
-        os.path.join(Folders.results, file_name), compare=compare
-    )
-    new_list = []
-    for result in data["results"]:
-        symbol = report._compute_status(result["dataset"], result["score"])
-        result["symbol"] = symbol if symbol != " " else " "
-        new_list.append(result)
-    data["results"] = new_list
-    # Compute summary with explanation of symbols
-    summary = {}
-    for key, value in report._compare_totals.items():
-        summary[key] = (report._status_meaning(key), value)
-    return summary
+# def process_data(file_name, compare, data):
+#     report = StubReport(
+#         os.path.join(Folders.results, file_name), compare=compare
+#     )
+#     new_list = []
+#     for result in data["results"]:
+#         symbol = report._compute_status(result["dataset"], result["score"])
+#         result["symbol"] = symbol if symbol != " " else " "
+#         new_list.append(result)
+#     data["results"] = new_list
+#     # Compute summary with explanation of symbols
+#     summary = {}
+#     for key, value in report._compare_totals.items():
+#         summary[key] = (report._status_meaning(key), value)
+#     return summary
 
 
-@main.route("/index/<compare>")
-@main.route("/")
-def index(compare="False"):
-    # Get a list of files in a directory
-    files = {}
-    names = Files.get_all_results(hidden=False)
-    for name in names:
-        report = StubReport(os.path.join(Folders.results, name))
-        report.report()
-        files[name] = {
-            "duration": report.duration,
-            "score": report.score,
-            "title": report.title,
-        }
-    candidate = current_app.config[FRAMEWORKS].copy()
-    candidate.remove(current_app.config[FRAMEWORK])
-    return render_template(
-        "select.html",
-        files=files,
-        candidate=candidate[0],
-        framework=current_app.config[FRAMEWORK],
-        compare=compare.capitalize() == "True",
-    )
+@results.route("/results/<compare>")
+def results(compare="False"):
+    # # Get a list of files in a directory
+    # files = {}
+    # names = Files.get_all_results(hidden=False)
+    # for name in names:
+    #     report = StubReport(os.path.join(Folders.results, name))
+    #     report.report()
+    #     files[name] = {
+    #         "duration": report.duration,
+    #         "score": report.score,
+    #         "title": report.title,
+    #     }
+    # candidate = current_app.config[FRAMEWORKS].copy()
+    # candidate.remove(current_app.config[FRAMEWORK])
+    # return render_template(
+    #     "select.html",
+    #     files=files,
+    #     candidate=candidate[0],
+    #     framework=current_app.config[FRAMEWORK],
+    #     compare=compare.capitalize() == "True",
+    # )
+    return render_template("test.html")
 
 
-@main.route("/datasets/<compare>")
-def datasets(compare):
+""" 
+@results.route("/datasets/<compare>")
+@results.route("datasets")
+def datasets(compare=False):
     dt = Datasets()
     datos = []
     for dataset in dt:
@@ -96,11 +98,11 @@ def datasets(compare):
     )
 
 
-@main.route("/showfile/<file_name>/<compare>")
+@results.route("/showfile/<file_name>/<compare>")
 def showfile(file_name, compare, back=None):
     compare = compare.capitalize() == "True"
     back = request.args["url"] if back is None else back
-    app_config = dotenv_values(".env")
+    print(f"back [{back}]")
     with open(os.path.join(Folders.results, file_name)) as f:
         data = json.load(f)
     try:
@@ -114,11 +116,10 @@ def showfile(file_name, compare, back=None):
         summary=summary,
         framework=current_app.config[FRAMEWORK],
         back=back,
-        app_config=app_config,
     )
 
 
-@main.route("/show", methods=["post"])
+@results.route("/show", methods=["post"])
 def show():
     selected_file = request.form["selected-file"]
     compare = request.form["compare"]
@@ -131,7 +132,7 @@ def show():
     )
 
 
-@main.route("/excel", methods=["post"])
+@results.route("/excel", methods=["post"])
 def excel():
     selected_files = request.json["selectedFiles"]
     compare = request.json["compare"]
@@ -171,7 +172,7 @@ def excel():
     return AjaxResponse(True, Files.be_list_excel).to_string()
 
 
-@main.route("/download/<file_name>")
+@results.route("/download/<file_name>")
 def download(file_name):
     src = os.path.join(Folders.current, Folders.excel, file_name)
     dest = os.path.join(
@@ -181,7 +182,7 @@ def download(file_name):
     return send_file(dest, as_attachment=True)
 
 
-@main.route("/config/<framework>/<compare>")
+@results.route("/config/<framework>/<compare>")
 def config(framework, compare):
     if framework not in current_app.config[FRAMEWORKS]:
         message = f"framework {framework} not supported"
@@ -194,7 +195,7 @@ def config(framework, compare):
     return redirect(url_for("main.index", compare=compare))
 
 
-@main.route("/best_results/<file>/<compare>")
+@results.route("/best_results/<file>/<compare>")
 def best_results(file, compare):
     compare = compare.capitalize() == "True"
     try:
@@ -208,3 +209,4 @@ def best_results(file, compare):
         compare=compare,
         framework=current_app.config[FRAMEWORK],
     )
+ """

benchmark/scripts/flask_app/results/templates/_table_select.html

@@ -0,0 +1,50 @@
+{%- macro get_button_tag(icon_name, method, visible=True, name="") -%}
+<button class="btn btn-primary btn-small" onclick="{{ method }}" {{ "" if visible else "hidden='true'" }} {{ "" if name=="" else "name='" + name +"'"}}><i class="mdi mdi-{{ icon_name }}"></i>
+</button>
+{%- endmacro -%}
+<table id="file-table"
+       class="table table-striped table-hover table-bordered">
+    <thead>
+        <tr>
+            <th>Model</th>
+            <th>Metric</th>
+            <th>Platform</th>
+            <th>Date</th>
+            <th>Time</th>
+            <th>Stratified</th>
+            <th>Title</th>
+            <th>Score</th>
+            <th>
+                <button class="btn btn-primary btn-small btn-danger"
+                        onclick="setCheckBoxes(false)">
+                    <i class="mdi mdi-checkbox-multiple-blank"></i>
+                </button>
+                <button class="btn btn-primary btn-small btn-success"
+                        onclick="setCheckBoxes(true)">
+                    <i class="mdi mdi-checkbox-multiple-marked"></i>
+                </button>
+            </tr>
+        </thead>
+        <tbody>
+            {% for file, data in files.items() %}
+                {% set parts = file.split('_') %}
+                {% set stratified = parts[6].split('.')[0] %}
+                <tr id="{{ file }}">
+                    <td>{{ parts[2] }}</td>
+                    <td>{{ parts[1] }}</td>
+                    <td>{{ parts[3] }}</td>
+                    <td>{{ parts[4] }}</td>
+                    <td>{{ parts[5] }}</td>
+                    <td>{{ 'True' if stratified =='1' else 'False' }}</td>
+                    <td>{{ "%s" % data["title"] }}</td>
+                    <td class="text-end">{{ "%.6f" % data["score"] }}</td>
+                    <td>
+                        {{ get_button_tag("table-eye", "showFile('" ~ file ~ "') ") | safe }}
+                        {% set file_best = "best_results_" ~ parts[1] ~ "_" ~ parts[2] ~ ".json" %}
+                        {{ get_button_tag("star-circle-outline", "redirectDouble('best_results', '" ~ file_best ~ "') ", visible=False, name="best_buttons") | safe }}
+                        <input type="checkbox" name="selected_files" value="{{ file }}" />
+                    </td>
+                </tr>
+            {% endfor %}
+        </tbody>
+    </table>

benchmark/scripts/flask_app/results/templates/select.html

@@ -0,0 +1,9 @@
+{% extends "base.html" %}
+{% block content %}
+    {% include "_table_select.html" %}
+{% endblock %}
+{% block jscript %}
+    {{ super() }}
+    <script src="https://cdn.datatables.net/1.10.25/js/jquery.dataTables.min.js"></script>
+    <script src="{{ url_for('static', filename="js/select.js") }}"></script>
+{% endblock %}

benchmark/scripts/flask_app/static/css/main.css

@@ -28,3 +28,24 @@ tbody {
   padding: 0.25rem 0.5rem;
   font-size: 0.75rem;
 }
+
+body {
+  padding-bottom: 20px;
+}
+
+.navbar {
+  margin-bottom: 20px;
+}
+
+pre {
+    background: #ddd;
+    padding: 10px;
+}
+
+h2 {
+    margin-top: 20px;
+}
+
+footer {
+    margin: 20px;
+}

benchmark/scripts/flask_app/static/js/select.js

@@ -0,0 +1,97 @@
+$(document).ready(function () {
+    var table = $("#file-table").DataTable({
+      paging: true,
+      searching: true,
+      ordering: true,
+      info: true,
+      "select.items": "row",
+      pageLength: 25,
+      columnDefs: [
+        {
+          targets: 8,
+          orderable: false,
+        },
+      ],
+      //"language": {
+      //    "lengthMenu": "_MENU_"
+      //}
+    });
+    $('#file-table').on( 'draw.dt', function () {
+      enable_disable_best_buttons();
+    } );
+    // Check if row is selected
+    $("#file-table tbody").on("click", "tr", function () {
+      if ($(this).hasClass("selected")) {
+        $(this).removeClass("selected");
+      } else {
+        table
+          .$("tr.selected")
+          .removeClass("selected");
+        $(this).addClass("selected");
+      }
+    });
+    // Show file with doubleclick
+    $("#file-table tbody").on("dblclick", "tr", function () {
+      showFile($(this).attr("id"));
+    });
+    $(document).ajaxStart(function () {
+      $("body").addClass("ajaxLoading");
+    });
+    $(document).ajaxStop(function () {
+      $("body").removeClass("ajaxLoading");
+    });
+    $('#compare').change(function() {
+      enable_disable_best_buttons();
+    });
+    enable_disable_best_buttons();
+  });
+  function enable_disable_best_buttons(){
+    if ($('#compare').is(':checked')) {
+      $("[name='best_buttons']").addClass("tag is-link is-normal");
+        $("[name='best_buttons']").removeAttr("hidden");
+      } else {
+        $("[name='best_buttons']").removeClass("tag is-link is-normal");
+        $("[name='best_buttons']").attr("hidden", true);
+      }
+  }
+  function showFile(selectedFile) {
+    var form = $(
+      '<form action="/show" method="post">' +
+        '<input type="hidden" name="selected-file" value="' +
+        selectedFile +
+        '" />' +
+        '<input type="hidden" name="compare" value=' +
+        $("#compare").is(":checked") +
+        " />" +
+        "</form>"
+    );
+    $("body").append(form);
+    form.submit();
+  }
+  function excel() {
+    var checkbox = document.getElementsByName("selected_files");
+    var selectedFiles = [];
+    for (var i = 0; i < checkbox.length; i++) {
+      if (checkbox[i].checked) {
+        selectedFiles.push(checkbox[i].value);
+      }
+    }
+    if (selectedFiles.length == 0) {
+      alert("Select at least one file");
+      return;
+    }
+    var compare = $("#compare").is(":checked");
+    excelFiles(selectedFiles, compare);
+  }
+  function setCheckBoxes(value) {
+    var checkbox = document.getElementsByName("selected_files");
+    for (i = 0; i < checkbox.length; i++) {
+      checkbox[i].checked = value;
+    }
+  }
+  function redirectDouble(route, parameter) {
+    location.href = "/"+ route + "/" + parameter + "/" + $("#compare").is(":checked");
+  }
+  function redirectSimple(route) {
+    location.href = "/" + route + "/" + $("#compare").is(":checked");
+  }

benchmark/scripts/flask_app/templates/_nav.html

@@ -0,0 +1,30 @@
+{% from 'bootstrap5/nav.html' import render_nav_item %}
+<nav class="navbar navbar-expand-sm navbar-light bg-light mb-4 justify-content-end">
+    <div class="container">
+        <button class="navbar-toggler"
+                type="button"
+                data-bs-toggle="collapse"
+                data-bs-target="#navbarSupportedContent"
+                aria-controls="navbarSupportedContent"
+                aria-expanded="false"
+                aria-label="Toggle navigation">
+            <span class="navbar-toggler-icon"></span>
+        </button>
+        <div class="collapse navbar-collapse" id="navbarSupportedContent">
+            <!-- Left side of navbar -->
+            <ul class="navbar-nav me-auto">
+                {{ render_nav_item('main.index', 'Home') }}
+            </ul>
+            <ul class="navbar-nav justify-content-end">
+                {{ render_nav_item('results.select', 'Results') }}
+                {{ render_nav_item('results.datasets', 'Datasets') }}
+                {{ render_nav_item('main.config', 'Config') }}
+                {% if current_user.is_authenticated %}
+                    {{ render_nav_item('main.logout', 'Logout') }}
+                {% else %}
+                    {{ render_nav_item('main.login', 'Login') }}
+                {% endif %}
+            </ul>
+        </div>
+    </div>
+</nav>

benchmark/scripts/flask_app/templates/base.html

@@ -0,0 +1,27 @@
+<!DOCTYPE html>
+<html lang="en">
+    <head>
+        {% block head %}
+            <meta charset="utf-8">
+            <meta name="viewport"
+                  content="width=device-width, initial-scale=1, shrink-to-fit=no">
+            {% block styles %}{{ bootstrap.load_css() }}{% endblock %}
+            <title>Benchmark</title>
+        {% endblock %}
+    </head>
+    <body>
+        {% include "_nav.html" %}
+        {% with messages = get_flashed_messages() %}
+            {% if messages %}
+                {% for message in messages %}<div class="alert alert-info" role="alert">{{ message }}</div>{% endfor %}
+            {% endif %}
+        {% endwith %}
+        <div class="container">
+            {% block content %}{% endblock %}
+        </div>
+    </body>
+    {% block jscript %}
+        <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
+        {{ bootstrap.load_js() }}
+    {% endblock %}
+</html>

benchmark/scripts/flask_app/templates/config.html

@@ -0,0 +1,5 @@
+{% extends "base.html" %}
+{% block content %}
+    <h1>Home</h1>
+    <p>Welcome to the home page!</p>
+{% endblock content %}

benchmark/scripts/flask_app/templates/index.html

@@ -0,0 +1,5 @@
+{% extends "base.html" %}
+{% block content %}
+    <h1>My First Heading</h1>
+    <p>My first paragraph.</p>
+{% endblock %}

benchmark/scripts/flask_app/templates/login.html

@@ -0,0 +1,6 @@
+{% extends 'base.html' %}
+{% from 'bootstrap5/form.html' import render_form %}
+{% block content %}
+    <h2>Login</h2>
+    {{ render_form(form) }}
+{% endblock content %}

benchmark/tests/Arguments_test.py

@@ -68,7 +68,7 @@ class ArgumentsTest(TestBase):
         test_args = ["-n", "3", "-k", "date"]
         with self.assertRaises(SystemExit):
             arguments.parse(test_args)
-        self.assertRegex(
+        self.assertRegexpMatches(
             stderr.getvalue(),
             r"error: the following arguments are required: -m/--model",
         )
@@ -79,7 +79,7 @@ class ArgumentsTest(TestBase):
         test_args = ["-n", "3", "-m", "SVC"]
         with self.assertRaises(SystemExit):
             arguments.parse(test_args)
-        self.assertRegex(
+        self.assertRegexpMatches(
             stderr.getvalue(),
             r"error: the following arguments are required: -k/--key",
         )
@@ -114,7 +114,7 @@ class ArgumentsTest(TestBase):
         test_args = None
         with self.assertRaises(SystemExit):
             arguments.parse(test_args)
-        self.assertRegex(
+        self.assertRegexpMatches(
             stderr.getvalue(),
             r"error: the following arguments are required: -m/--model, "
             "-k/--key, --title",

benchmark/tests/Models_test.py

@@ -102,7 +102,7 @@ class ModelTest(TestBase):
         test = {
             "STree": ((11, 6, 4), 1.0),
             "Wodt": ((303, 152, 50), 0.9382022471910112),
-            "ODTE": ((786, 443, 337), 1.0),
+            "ODTE": ((7.86, 4.43, 3.37), 1.0),
             "Cart": ((23, 12, 5), 1.0),
             "SVC": ((0, 0, 0), 0.7078651685393258),
             "RandomForest": ((21.3, 11, 5.26), 1.0),

benchmark/tests/Util_test.py

@@ -118,7 +118,7 @@ class UtilTest(TestBase):
     def test_Files_get_results(self):
         os.chdir(os.path.dirname(os.path.abspath(__file__)))
         self.assertCountEqual(
-            Files.get_all_results(hidden=False),
+            Files().get_all_results(hidden=False),
             [
                 "results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json",
                 "results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json",
@@ -130,7 +130,7 @@ class UtilTest(TestBase):
             ],
         )
         self.assertCountEqual(
-            Files.get_all_results(hidden=True),
+            Files().get_all_results(hidden=True),
             [
                 "results_accuracy_STree_iMac27_2021-11-01_23:55:16_0.json",
                 "results_accuracy_XGBoost_MacBookpro16_2022-05-04_11:00:35_"
@@ -143,7 +143,7 @@ class UtilTest(TestBase):
         # check with results
         os.rename(Folders.results, f"{Folders.results}.test")
         try:
-            Files.get_all_results(hidden=False)
+            Files().get_all_results(hidden=False)
         except ValueError:
             pass
         else:
@@ -153,7 +153,7 @@ class UtilTest(TestBase):
         # check with hidden_results
         os.rename(Folders.hidden_results, f"{Folders.hidden_results}.test")
         try:
-            Files.get_all_results(hidden=True)
+            Files().get_all_results(hidden=True)
         except ValueError:
             pass
         else:

benchmark/tests/datasets/all.txt

@@ -1,2 +1,2 @@
-iris;class;all
-wine;class;[0, 1]
+iris,class,all
+wine,class,[0, 1]

benchmark/tests/results/grid_output_accuracy_STree.json

@@ -6,7 +6,7 @@
             "kernel": "liblinear",
             "multiclass_strategy": "ovr"
         },
-        "v. 1.4.0, Computed on Test on 2022-02-22 at 12:00:00 took 1s"
+        "v. 1.3.1, Computed on Test on 2022-02-22 at 12:00:00 took 1s"
     ],
     "balloons": [
         0.625,
@@ -15,6 +15,6 @@
             "kernel": "linear",
             "multiclass_strategy": "ovr"
         },
-        "v. 1.4.0, Computed on Test on 2022-02-22 at 12:00:00 took 1s"
+        "v. 1.3.1, Computed on Test on 2022-02-22 at 12:00:00 took 1s"
     ]
 }

benchmark/tests/scripts/Be_Main_test.py

@@ -120,7 +120,7 @@ class BeMainTest(TestBase):
                 module.main(parameter)
             self.assertEqual(msg.exception.code, 2)
             self.assertEqual(stderr.getvalue(), "")
-            self.assertRegex(stdout.getvalue(), message)
+            self.assertRegexpMatches(stdout.getvalue(), message)
 
     def test_be_main_best_params_non_existent(self):
         model = "GBC"

benchmark/tests/test_files/exreport_excel_Datasets.test

@@ -1,4 +1,4 @@
-1;1;"Datasets used in benchmark ver. 1.0.1"
+1;1;"Datasets used in benchmark ver. 0.5.0"
 2;1;" Default score accuracy"
 2;2;"Cross validation"
 2;6;"5 Folds"

benchmark/tests/test_files/report_datasets.test

@@ -1,4 +1,4 @@
-Datasets used in benchmark ver. 1.0.1
+Datasets used in benchmark ver. 0.5.0
 
 Dataset                        Sampl. Feat. Cont Cls Balance
 ============================== ====== ===== ==== === ==========================================

requirements.txt

@@ -1,11 +1,18 @@
 pandas
 scikit-learn
 scipy
+python-dotenv
+flask
+bootstrap-flask
+flask-wtf
+flask-login
+flask-migrate
+flask_sqlalchemy
 odte
 cython
 fimdlp
 mufs
-#bayesclass @ git+ssh://git@github.com/doctorado-ml/bayesclass.git
+bayesclass @ git+ssh://git@github.com/doctorado-ml/bayesclass.git
 xlsxwriter
 openpyxl
 tqdm
@@ -13,4 +20,3 @@ xgboost
 graphviz
 Wodt @ git+ssh://git@github.com/doctorado-ml/Wodt.git#egg=Wodt
 unittest-xml-reporting
-flask

setup.py

@@ -39,7 +39,6 @@ def script_names():
         "report",
         "summary",
         "init_project",
-        "flask",
     ]
     result = []
     for script in scripts: