Begin refactor main scripts

src/Results.py

@@ -1159,3 +1159,56 @@ class Summary:
             input_data=self.best_results(score=score, n=n),
             sort_key="metric",
         )
+
+
+class PairCheck:
+    def __init__(self, score, model_a, model_b, winners=False, loosers=False):
+        self.score = score
+        self.model_a = model_a
+        self.model_b = model_b
+        self.winners = winners
+        self.loosers = loosers
+        self.winners_data = []
+        self.loosers_data = []
+        self.tie_data = []
+
+    def compute(self):
+        summary = Summary()
+        summary.acquire()
+        best_a = summary.best_result(
+            criterion="model", value=self.model_a, score=self.score
+        )
+        best_b = summary.best_result(
+            criterion="model", value=self.model_b, score=self.score
+        )
+        report_a = StubReport(os.path.join(Folders.results, best_a["file"]))
+        report_a.report()
+        report_b = StubReport(os.path.join(Folders.results, best_b["file"]))
+        report_b.report()
+        for result_a, result_b in zip(report_a.lines, report_b.lines):
+            result = result_a["score"] - result_b["score"]
+            if result > 0:
+                self.winners_data.append(result_a["dataset"])
+            elif result < 0:
+                self.loosers_data.append(result_a["dataset"])
+            else:
+                self.tie_data.append(result_a["dataset"])
+
+    def print(self):
+        print(f"{'Model':<20} {'File':<70} {'Score':<10} Win Tie Loose")
+        print("=" * 20 + " " + "=" * 70 + " " + "=" * 10 + " === === =====")
+        print(
+            f"{self.model_a:<20} {self.best_a['file']:<70} {report_1.score:10.5f}"
+        )
+        print(
+            f"{model2:<20} {best_2['file']:<70} "
+            f"{report_2.score:10.5f} "
+            f"{TextColor.GREEN}{win:3d} {TextColor.YELLOW}{tie:3d} "
+            f"{TextColor.RED}{loose:5d}"
+        )
+        if win_results:
+            print(TextColor.GREEN + "Winners:")
+            print(winners)
+        if loose_results:
+            print(TextColor.RED + "Loosers:")
+            print(loosers)

src/list

@@ -64,8 +64,8 @@ def parse_arguments():
     )
 
 
-(excel, score, model, key, number, hidden) = parse_arguments()
-
-data = Summary(hidden=hidden)
-data.acquire()
-data.list_results(score=score, model=model, sort_key=key, number=number)
+if __name__ == "__main__":
+    (excel, score, model, key, number, hidden) = parse_arguments()
+    data = Summary(hidden=hidden)
+    data.acquire()
+    data.list_results(score=score, model=model, sort_key=key, number=number)

src/main

@@ -117,41 +117,42 @@ def parse_arguments():
     )
 
 
-(
-    stratified,
-    score,
-    model,
-    folds,
-    platform,
-    quiet,
-    hyperparameters,
-    paramfile,
-    grid_paramfile,
-    report,
-    experiment_title,
-    dataset,
-) = parse_arguments()
-report = report or dataset is not None
-if grid_paramfile:
-    paramfile = False
-job = Experiment(
-    score_name=score,
-    model_name=model,
-    stratified=stratified,
-    datasets=Datasets(dataset=dataset),
-    hyperparams_dict=hyperparameters,
-    hyperparams_file=paramfile,
-    grid_paramfile=grid_paramfile,
-    progress_bar=not quiet,
-    platform=platform,
-    title=experiment_title,
-    folds=folds,
-)
-job.do_experiment()
-if report:
-    result_file = job.get_output_file()
-    report = Report(result_file)
-    report.report()
-if dataset is not None:
-    print(f"Partial result file removed: {result_file}")
-    os.remove(result_file)
+if __name__ == "__main__":
+    (
+        stratified,
+        score,
+        model,
+        folds,
+        platform,
+        quiet,
+        hyperparameters,
+        paramfile,
+        grid_paramfile,
+        report,
+        experiment_title,
+        dataset,
+    ) = parse_arguments()
+    report = report or dataset is not None
+    if grid_paramfile:
+        paramfile = False
+    job = Experiment(
+        score_name=score,
+        model_name=model,
+        stratified=stratified,
+        datasets=Datasets(dataset=dataset),
+        hyperparams_dict=hyperparameters,
+        hyperparams_file=paramfile,
+        grid_paramfile=grid_paramfile,
+        progress_bar=not quiet,
+        platform=platform,
+        title=experiment_title,
+        folds=folds,
+    )
+    job.do_experiment()
+    if report:
+        result_file = job.get_output_file()
+        report = Report(result_file)
+        report.report()
+    if dataset is not None:
+        print(f"Partial result file removed: {result_file}")
+        os.remove(result_file)

src/pair_check

@@ -59,47 +59,47 @@ def parse_arguments():
     )
 
 
-(
-    score,
-    model1,
-    model2,
-    win_results,
-    loose_results,
-) = parse_arguments()
-
-summary = Summary()
-summary.acquire()
-win = tie = loose = 0
-winners = []
-loosers = []
-best_1 = summary.best_result(criterion="model", value=model1, score=score)
-best_2 = summary.best_result(criterion="model", value=model2, score=score)
-report_1 = StubReport(os.path.join(Folders.results, best_1["file"]))
-report_1.report()
-report_2 = StubReport(os.path.join(Folders.results, best_2["file"]))
-report_2.report()
-for result1, result2 in zip(report_1.lines, report_2.lines):
-    result = result1["score"] - result2["score"]
-    if result > 0:
-        win += 1
-        winners.append(result1["dataset"])
-    elif result < 0:
-        loose += 1
-        loosers.append(result1["dataset"])
-    else:
-        tie += 1
-print(f"{'Model':<20} {'File':<70} {'Score':<10} Win Tie Loose")
-print("=" * 20 + " " + "=" * 70 + " " + "=" * 10 + " === === =====")
-print(f"{model1:<20} {best_1['file']:<70} {report_1.score:10.5f}")
-print(
-    f"{model2:<20} {best_2['file']:<70} "
-    f"{report_2.score:10.5f} "
-    f"{TextColor.GREEN}{win:3d} {TextColor.YELLOW}{tie:3d} "
-    f"{TextColor.RED}{loose:5d}"
-)
-if win_results:
-    print(TextColor.GREEN + "Winners:")
-    print(winners)
-if loose_results:
-    print(TextColor.RED + "Loosers:")
-    print(loosers)
+if __name__ == "__main__":
+    (
+        score,
+        model1,
+        model2,
+        win_results,
+        loose_results,
+    ) = parse_arguments()
+    summary = Summary()
+    summary.acquire()
+    win = tie = loose = 0
+    winners = []
+    loosers = []
+    best_1 = summary.best_result(criterion="model", value=model1, score=score)
+    best_2 = summary.best_result(criterion="model", value=model2, score=score)
+    report_1 = StubReport(os.path.join(Folders.results, best_1["file"]))
+    report_1.report()
+    report_2 = StubReport(os.path.join(Folders.results, best_2["file"]))
+    report_2.report()
+    for result1, result2 in zip(report_1.lines, report_2.lines):
+        result = result1["score"] - result2["score"]
+        if result > 0:
+            win += 1
+            winners.append(result1["dataset"])
+        elif result < 0:
+            loose += 1
+            loosers.append(result1["dataset"])
+        else:
+            tie += 1
+    print(f"{'Model':<20} {'File':<70} {'Score':<10} Win Tie Loose")
+    print("=" * 20 + " " + "=" * 70 + " " + "=" * 10 + " === === =====")
+    print(f"{model1:<20} {best_1['file']:<70} {report_1.score:10.5f}")
+    print(
+        f"{model2:<20} {best_2['file']:<70} "
+        f"{report_2.score:10.5f} "
+        f"{TextColor.GREEN}{win:3d} {TextColor.YELLOW}{tie:3d} "
+        f"{TextColor.RED}{loose:5d}"
+    )
+    if win_results:
+        print(TextColor.GREEN + "Winners:")
+        print(winners)
+    if loose_results:
+        print(TextColor.RED + "Loosers:")
+        print(loosers)

src/report

@@ -114,22 +114,23 @@ def default_report():
         )
 
 
-(file, excel, sql, compare, best, grid, score, model) = parse_arguments()
-if grid:
-    best = False
-if file is None and best is None:
-    default_report()
-else:
-    if best is not None or grid is not None:
-        report = ReportBest(score, model, best, grid)
-        report.report()
+if __name__ == "__main__":
+    (file, excel, sql, compare, best, grid, score, model) = parse_arguments()
+    if grid:
+        best = False
+    if file is None and best is None:
+        default_report()
     else:
-        report = Report(file, compare)
-        report.report()
-        if excel:
-            excel = Excel(file, compare)
-            excel.report()
-            Files.open(excel.get_file_name())
-        if sql:
-            sql = SQL(file)
-            sql.report()
+        if best is not None or grid is not None:
+            report = ReportBest(score, model, best, grid)
+            report.report()
+        else:
+            report = Report(file, compare)
+            report.report()
+            if excel:
+                excel = Excel(file, compare)
+                excel.report()
+                Files.open(excel.get_file_name())
+            if sql:
+                sql = SQL(file)
+                sql.report()

src/summary

@@ -40,26 +40,25 @@ def parse_arguments():
     )
 
 
-(
-    score,
-    model,
-    list_results,
-) = parse_arguments()
-
-all_metrics = ["accuracy", "f1-macro", "f1-micro"]
-
-metrics = all_metrics if score == "all" else [score]
-
-summary = Summary()
-summary.acquire()
-
-for metric in metrics:
-    title = f"BEST RESULT of {metric} for {model}"
-    best = summary.best_result(criterion="model", value=model, score=metric)
-    summary.show_result(data=best, title=title)
-    summary.show_result(
-        summary.best_result(score=metric), title=f"BEST RESULT of {metric}"
-    )
-    summary.show_top(score=metric, n=10)
-if list_results:
-    summary.list_results()
+if __name__ == "__main__":
+    (
+        score,
+        model,
+        list_results,
+    ) = parse_arguments()
+    all_metrics = ["accuracy", "f1-macro", "f1-micro"]
+    metrics = all_metrics if score == "all" else [score]
+    summary = Summary()
+    summary.acquire()
+    for metric in metrics:
+        title = f"BEST RESULT of {metric} for {model}"
+        best = summary.best_result(
+            criterion="model", value=model, score=metric
+        )
+        summary.show_result(data=best, title=title)
+        summary.show_result(
+            summary.best_result(score=metric), title=f"BEST RESULT of {metric}"
+        )
+        summary.show_top(score=metric, n=10)
+    if list_results:
+        summary.list_results()