Add experiment title and model version to reports

src/Experiments.py

@@ -133,6 +133,7 @@ class Experiment:
         hyperparams_dict,
         hyperparams_file,
         platform,
+        title,
         progress_bar=True,
         folds=5,
     ):
@@ -152,6 +153,7 @@ class Experiment:
         )
         self.score_name = score_name
         self.model_name = model_name
+        self.title = title
         self.stratified = stratified == "1"
         self.stratified_class = StratifiedKFold if self.stratified else KFold
         self.model = Models.get_model(model_name)
@@ -231,6 +233,7 @@ class Experiment:
 
     def _add_results(self, name, hyperparameters, samples, features, classes):
         record = {}
+        record["title"] = self.title
         record["dataset"] = name
         record["samples"] = samples
         record["features"] = features

src/Results.py

@@ -140,12 +140,13 @@ class Report(BaseReport):
             f" with {self.data['folds']} Folds "
             f"cross validation and {len(self.data['seeds'])} random seeds"
         )
+        self.header_line(f" {self.data['title']}")
         self.header_line(
             f" Random seeds: {self.data['seeds']} Stratified: "
             f"{self.data['stratified']}"
         )
         self.header_line(
-            f" Execution took {self.data['duration']:7.2f} seconds on an "
+            f" Execution took {self.data['duration']:7.2f} seconds on "
             f"{self.data['platform']}"
         )
         self.header_line(f" Score is {self.data['score_name']}")
@@ -238,7 +239,7 @@ class ReportBest(BaseReport):
 
 
 class Excel(BaseReport):
-    row = 5
+    row = 6
 
     def __init__(self, file_name, compare=False):
         super().__init__(file_name)
@@ -271,21 +272,27 @@ class Excel(BaseReport):
         self.sheet.write(
             1,
             0,
-            f" Execution took {self.data['duration']:7.2f} seconds on an "
+            f" {self.data['title']}",
+            subheader,
+        )
+        self.sheet.write(
+            2,
+            0,
+            f" Execution took {self.data['duration']:7.2f} seconds on "
             f"{self.data['platform']}",
             subheader,
         )
         self.sheet.write(
-            1,
+            2,
             5,
             f"Random seeds: {self.data['seeds']}",
             subheader,
         )
         self.sheet.write(
-            2, 0, f" Score is {self.data['score_name']}", subheader
+            3, 0, f" Score is {self.data['score_name']}", subheader
         )
         self.sheet.write(
-            2,
+            3,
             5,
             f"Stratified: {self.data['stratified']}",
             subheader,
@@ -309,7 +316,7 @@ class Excel(BaseReport):
         bold = self.book.add_format({"bold": True, "font_size": 14})
         i = 0
         for item, length in header_cols:
-            self.sheet.write(4, i, item, bold)
+            self.sheet.write(5, i, item, bold)
             self.sheet.set_column(i, i, length)
             i += 1
 
@@ -378,12 +385,14 @@ class SQL(BaseReport):
             "date",
             "time",
             "type",
+            "title",
             "stratified",
             "score_name",
             "score",
             "score_std",
             "dataset",
             "classifier",
+            "version",
             "norm",
             "stand",
             "time_spent",
@@ -407,12 +416,14 @@ class SQL(BaseReport):
             self.data["date"],
             self.data["time"],
             "crossval",
+            self.data["title"],
             "1" if self.data["stratified"] else "0",
             self.data["score_name"],
             result["score"],
             result["score_std"],
             result["dataset"],
             self.data["model"],
+            self.data["version"],
             0,
             1,
             result["time"],
@@ -702,6 +713,8 @@ class Summary:
             print(f"*{title:^{length - 2}s}*")
             print("*" + "-" * (length - 2) + "*")
         print("*" + whites(length - 2))
+        print(f"* {result.data['title']:^{length - 4}} *")
+        print("*" + whites(length - 2))
         print(
             f"* Model: {result.data['model']:15s} "
             f"Ver. {result.data['version']:10s} "

src/main.py

@@ -49,6 +49,9 @@ def parse_arguments():
     ap.add_argument(
         "-f", "--paramfile", type=bool, required=False, default=False
     )
+    ap.add_argument(
+        "--title", type=str, required=True, help="experiment title"
+    )
     ap.add_argument(
         "-q",
         "--quiet",
@@ -85,6 +88,7 @@ def parse_arguments():
         args.hyperparameters,
         args.paramfile,
         args.report,
+        args.title,
     )
 
 
@@ -98,6 +102,7 @@ def parse_arguments():
     hyperparameters,
     paramfile,
     report,
+    experiment_title,
 ) = parse_arguments()
 job = Experiment(
     score_name=score,
@@ -108,6 +113,7 @@ job = Experiment(
     hyperparams_file=paramfile,
     progress_bar=not quiet,
     platform=platform,
+    title=experiment_title,
     folds=folds,
 )
 job.do_experiment()

src/repara.py

@@ -12,6 +12,9 @@ for result in results:
     file_name = os.path.join(Folders.results, result)
     with open(file_name) as f:
         data = json.load(f)
+        if "title" not in data:
+            print(f"Repairing title in {result}")
+            data["title"] = "default"
         if "version" not in data:
             print(f"Repairing version in {result}")
             model = data["model"]

src/summary.py

@@ -1,5 +1,6 @@
 import argparse
 from Results import Summary
+from Utils import EnvDefault
 
 
 def parse_arguments():
@@ -8,6 +9,8 @@ def parse_arguments():
         "-m",
         "--model",
         type=str,
+        action=EnvDefault,
+        envvar="model",
         required=True,
         help="model name",
     )
@@ -15,19 +18,31 @@ def parse_arguments():
         "-s",
         "--score",
         type=str,
+        action=EnvDefault,
+        envvar="score",
         required=True,
         help="score name {accuracy, f1_micro, f1_macro, all}",
     )
+    ap.add_argument(
+        "-l",
+        "--list",
+        type=bool,
+        required=False,
+        default=False,
+        help="List all results",
+    )
     args = ap.parse_args()
     return (
         args.score,
         args.model,
+        args.list,
     )
 
 
 (
     score,
     model,
+    list_results,
 ) = parse_arguments()
 
 all_metrics = ["accuracy", "f1-macro", "f1-micro"]
@@ -44,3 +59,5 @@ for metric in metrics:
     summary.show_result(
         summary.best_result(score=metric), title=f"BEST RESULT of {metric}"
     )
+if list_results:
+    summary.list()