Begin refactor arguments

benchmark/Arguments.py

@@ -0,0 +1,147 @@
+import argparse
+from .Experiments import Models
+from .Utils import Files
+
+ALL_METRICS = (
+    "accuracy",
+    "f1-macro",
+    "f1-micro",
+    "f1-weighted",
+    "roc-auc-ovr",
+)
+
+
+class EnvData:
+    @staticmethod
+    def load():
+        args = {}
+        with open(Files.dot_env) as f:
+            for line in f.read().splitlines():
+                if line == "" or line.startswith("#"):
+                    continue
+                key, value = line.split("=")
+                args[key] = value
+        return args
+
+
+class EnvDefault(argparse.Action):
+    # Thanks to https://stackoverflow.com/users/445507/russell-heilling
+    def __init__(self, envvar, required=True, default=None, **kwargs):
+        self._args = EnvData.load()
+        default = self._args[envvar]
+        required = False
+        super(EnvDefault, self).__init__(
+            default=default, required=required, **kwargs
+        )
+
+    def __call__(self, parser, namespace, values, option_string=None):
+        setattr(namespace, self.dest, values)
+
+
+class Arguments:
+    def __init__(self):
+        self.ap = argparse.ArgumentParser()
+        models_data = Models.define_models(random_state=0)
+        models = "{" + ", ".join(models_data) + "}"
+        self.parameters = {
+            "best": [
+                ("-b", "--best"),
+                {
+                    "type": str,
+                    "required": False,
+                    "help": "best results of models",
+                },
+            ],
+            "color": [],
+            "compare": [
+                ("-c", "--compare"),
+                {
+                    "type": bool,
+                    "required": False,
+                    "help": "Compare accuracy with best results",
+                },
+            ],
+            "dataset": [],
+            "excel": [
+                ("-x", "--excel"),
+                {
+                    "type": bool,
+                    "required": False,
+                    "default": False,
+                    "help": "Generate Excel File",
+                },
+            ],
+            "file": [
+                ("-f", "--file"),
+                {"type": str, "required": False, "help": "Result file"},
+            ],
+            "grid": [
+                ("-g", "--grid"),
+                {
+                    "type": str,
+                    "required": False,
+                    "help": "grid results of model",
+                },
+            ],
+            "grid_paramfile": [],
+            "hidden": [],
+            "hyperparameters": [],
+            "key": [],
+            "lose": [],
+            "model": [
+                ("-m", "--model"),
+                {
+                    "type": str,
+                    "required": True,
+                    "choices": list(models_data),
+                    "help": f"model name: {models}",
+                },
+            ],
+            "model1": [],
+            "model2": [],
+            "nan": [],
+            "number": [],
+            "n_folds": [],
+            "paramfile": [],
+            "platform": [],
+            "quiet": [],
+            "report": [],
+            "score": [
+                ("-s", "--score"),
+                {
+                    "action": EnvDefault,
+                    "envvar": "score",
+                    "type": str,
+                    "required": True,
+                    "choices": ALL_METRICS,
+                },
+            ],
+            "sql": [
+                ("-q", "--sql"),
+                {"type": bool, "required": False, "help": "Generate SQL File"},
+            ],
+            "stratified": [],
+            "tex_output": [
+                ("-t", "--tex-output"),
+                {
+                    "type": bool,
+                    "required": False,
+                    "default": False,
+                    "help": "Generate Tex file with the table",
+                },
+            ],
+            "title": [],
+            "win": [],
+        }
+
+    def xset(self, *arg_name, **kwargs):
+        print("parameters", arg_name[0])
+        names, default = self.parameters[arg_name[0]]
+        self.ap.add_argument(
+            *names,
+            **{**default, **kwargs},
+        )
+        return self
+
+    def parse(self):
+        return self.ap.parse_args()

benchmark/Experiments.py

@@ -13,7 +13,8 @@ from sklearn.model_selection import (
     GridSearchCV,
     cross_validate,
 )
-from .Utils import Folders, Files, EnvData
+from .Utils import Folders, Files
+from .Arguments import EnvData
 from .Models import Models
 
 

benchmark/Utils.py

@@ -1,6 +1,5 @@
 import os
 import subprocess
-import argparse
 
 BEST_ACCURACY_STREE = 40.282203
 ALL_METRICS = (
@@ -132,33 +131,6 @@ class Symbols:
     better_best = black_star
 
 
-class EnvData:
-    @staticmethod
-    def load():
-        args = {}
-        with open(Files.dot_env) as f:
-            for line in f.read().splitlines():
-                if line == "" or line.startswith("#"):
-                    continue
-                key, value = line.split("=")
-                args[key] = value
-        return args
-
-
-class EnvDefault(argparse.Action):
-    # Thanks to https://stackoverflow.com/users/445507/russell-heilling
-    def __init__(self, envvar, required=True, default=None, **kwargs):
-        self._args = EnvData.load()
-        default = self._args[envvar]
-        required = False
-        super(EnvDefault, self).__init__(
-            default=default, required=required, **kwargs
-        )
-
-    def __call__(self, parser, namespace, values, option_string=None):
-        setattr(namespace, self.dest, values)
-
-
 class TextColor:
     BLUE = "\033[94m"
     CYAN = "\033[96m"

benchmark/__init__.py

@@ -1,6 +1,6 @@
 from .Experiments import Experiment, Datasets, DatasetsSurcov, DatasetsTanveer
 from .Results import Report, Summary
-from .Utils import EnvDefault
+from .Arguments import EnvDefault
 
 __author__ = "Ricardo Montañana Gómez"
 __copyright__ = "Copyright 2020-2022, Ricardo Montañana Gómez"

benchmark/scripts/be_benchmark

@@ -1,47 +1,19 @@
 #!/usr/bin/env python
 from benchmark.Results import Benchmark
-from benchmark.Utils import ALL_METRICS, Files, EnvDefault
+from benchmark.Utils import Files
-import argparse
+from benchmark.Arguments import Arguments
 
 
-def parse_arguments():
+arguments = Arguments()
-    ap = argparse.ArgumentParser()
+arguments.xset("score").xset("excel").xset("tex_output")
-    ap.add_argument(
+ar = arguments.parse()
-        "-s",
+benchmark = Benchmark(score=ar.score, visualize=True)
-        "--score",
-        action=EnvDefault,
-        envvar="score",
-        type=str,
-        required=True,
-        choices=ALL_METRICS,
-        help="score name {accuracy, f1_macro, ...}",
-    )
-    ap.add_argument(
-        "-x",
-        "--excel",
-        type=bool,
-        required=False,
-        help="Generate Excel File",
-    )
-    ap.add_argument(
-        "-t",
-        "--tex-output",
-        type=bool,
-        required=False,
-        default=False,
-    )
-    args = ap.parse_args()
-    return (args.score, args.excel, args.tex_output)
-
-
-(score, excel, tex_output) = parse_arguments()
-benchmark = Benchmark(score=score, visualize=True)
 benchmark.compile_results()
 benchmark.save_results()
-benchmark.report(tex_output)
+benchmark.report(ar.tex_output)
 benchmark.exreport()
-if excel:
+if ar.excel:
     benchmark.excel()
     Files.open(benchmark.get_excel_file_name())
-if tex_output:
+if ar.tex_output:
     print(f"File {benchmark.get_tex_file()} generated")

benchmark/scripts/be_best

@@ -1,29 +1,17 @@
 #!/usr/bin/env python
-import argparse
 import json
 from benchmark.Results import Summary
-from benchmark.Utils import EnvDefault, ALL_METRICS
+from benchmark.Utils import ALL_METRICS, Arguments
 
 
-def parse_arguments():
+arguments = Arguments()
-    ap = argparse.ArgumentParser()
+metrics = list(ALL_METRICS)
-    ap.add_argument(
+metrics.append("all")
-        "-s",
+arguments.xset("score", choices=metrics)
-        "--score",
+args = arguments.parse()
-        type=str,
-        action=EnvDefault,
-        envvar="score",
-        required=True,
-        choices=ALL_METRICS,
-        help="score name {accuracy, f1-macro, f1-weighted, roc-auc-ovr}",
-    )
-    args = ap.parse_args()
-    return (args.score,)
 
 
-(score,) = parse_arguments()
+metrics = ALL_METRICS if args.score == "all" else [args.score]
-
-metrics = ALL_METRICS if score == "all" else [score]
 
 summary = Summary()
 summary.acquire()

benchmark/scripts/be_report

@@ -1,9 +1,12 @@
 #!/usr/bin/env python
-import argparse
 import numpy as np
 from benchmark.Experiments import Datasets
 from benchmark.Results import Report, Excel, SQL, ReportBest
-from benchmark.Utils import ALL_METRICS, Files, TextColor, EnvDefault
+from benchmark.Utils import (
+    Files,
+    TextColor,
+)
+from benchmark.Arguments import Arguments
 
 
 """Build report on screen of a result file, optionally generate excel and sql
@@ -12,83 +15,6 @@ If no argument is set, displays the datasets and its characteristics
 """
 
 
-def parse_arguments():
-    ap = argparse.ArgumentParser()
-    ap.add_argument(
-        "-f",
-        "--file",
-        type=str,
-        required=False,
-        help="Result file",
-    )
-    ap.add_argument(
-        "-x",
-        "--excel",
-        type=bool,
-        required=False,
-        help="Generate Excel file",
-    )
-    ap.add_argument(
-        "-q",
-        "--sql",
-        type=bool,
-        required=False,
-        help="Generate sql file",
-    )
-    ap.add_argument(
-        "-c",
-        "--compare",
-        type=bool,
-        required=False,
-        help="Compare accuracy with best results",
-    )
-    ap.add_argument(
-        "-b",
-        "--best",
-        type=str,
-        required=False,
-        help="best results of models",
-    )
-    ap.add_argument(
-        "-g",
-        "--grid",
-        type=str,
-        required=False,
-        help="grid results of model",
-    )
-    ap.add_argument(
-        "-m",
-        "--model",
-        action=EnvDefault,
-        envvar="model",
-        type=str,
-        required=True,
-        help="model name",
-    )
-    ap.add_argument(
-        "-s",
-        "--score",
-        action=EnvDefault,
-        envvar="score",
-        type=str,
-        required=True,
-        choices=ALL_METRICS,
-        help="score name {accuracy, f1_macro, ...}",
-    )
-    args = ap.parse_args()
-
-    return (
-        args.file,
-        args.excel,
-        args.sql,
-        args.compare,
-        args.best,
-        args.grid,
-        args.score,
-        args.model,
-    )
-
-
 def default_report():
     sets = Datasets()
     color_line = TextColor.LINE1
@@ -116,22 +42,26 @@ def default_report():
 
 
 if __name__ == "__main__":
-    (file, excel, sql, compare, best, grid, score, model) = parse_arguments()
+    arguments = Arguments()
-    if grid:
+    arguments.xset("file").xset("excel").xset("sql").xset("compare")
-        best = False
+    arguments.xset("best").xset("grid").xset("model").xset("score")
-    if file is None and best is None:
+    args = arguments.parse()
+
+    if args.grid:
+        args.best = False
+    if args.file is None and args.best is None:
         default_report()
     else:
-        if best is not None or grid is not None:
+        if args.best is not None or args.grid is not None:
-            report = ReportBest(score, model, best, grid)
+            report = ReportBest(args.score, args.model, args.best, args.grid)
             report.report()
         else:
-            report = Report(file, compare)
+            report = Report(args.file, args.compare)
             report.report()
-            if excel:
+            if args.excel:
-                excel = Excel(file, compare)
+                excel = Excel(args.file, args.compare)
                 excel.report()
                 Files.open(excel.get_file_name())
-            if sql:
+            if args.sql:
-                sql = SQL(file)
+                sql = SQL(args.file)
                 sql.report()

benchmark/tests/Util_test.py

@@ -266,3 +266,8 @@ class UtilTest(TestBase):
         self.assertEqual(TextColor.ENDC, "\033[0m")
         self.assertEqual(TextColor.BOLD, "\033[1m")
         self.assertEqual(TextColor.UNDERLINE, "\033[4m")
+
+    def test_Arguments(self):
+        arguments = Arguments()
+        arg_list = ["score", "excel", "tex_output"]
+        arguments.set_arguments(arg_list)