Improve user interface

autoemulate/compare.py

@@ -125,8 +125,13 @@ def setup(
         self.n_jobs = n_jobs
         self.logger = _configure_logging(log_to_file=log_to_file)
         self.is_set_up = True
+        self.dim_reducer = dim_reducer
+        self.reduce_dim = reduce_dim
+        self.folds = folds
         self.cv_results = {}
 
+        self.print_settings()
+
     def _check_input(self, X, y):
         """Checks and possibly converts the input data.
 
@@ -198,7 +203,12 @@ def compare(self):
         self.scores_df = pd.DataFrame(
             columns=["model", "metric", "fold", "score"]
         ).astype(
-            {"model": "object", "metric": "object", "fold": "int64", "score": "float64"}
+            {
+                "model": "object",
+                "metric": "object",
+                "fold": "int64",
+                "score": "float64",
+            }
         )
 
         for i in range(len(self.models)):
@@ -368,6 +378,74 @@ def load_model(self, path=None):
 
         return serialiser._load_model(path)
 
+    def print_settings(self):
+        if not self.is_set_up:
+            raise RuntimeError("Must run setup() before print_settings()")
+            return
+
+        models = "\n- " + "\n- ".join(
+            [
+                x[1].__class__.__name__
+                for pipeline in self.models
+                for x in pipeline.steps
+                if x[0] == "model"
+            ]
+        )
+        metrics = "\n- " + "\n- ".join([metric.__name__ for metric in self.metrics])
+
+        settings = pd.DataFrame(
+            [
+                str(self.X.shape),
+                str(self.y.shape),
+                str(self.train_idxs.shape),
+                str(self.test_idxs.shape),
+                str(self.param_search),
+                str(self.search_type),
+                str(self.param_search_iters),
+                str(self.scale),
+                str(
+                    self.scaler.__class__.__name__ if self.scaler is not None else None
+                ),
+                str(self.reduce_dim),
+                str(
+                    self.dim_reducer.__class__.__name__
+                    if self.dim_reducer is not None
+                    else None
+                ),
+                str(self.cv.__class__.__name__ if self.cv is not None else "None"),
+                str(self.folds),
+                str(self.n_jobs),
+            ],
+            index=[
+                "Simulation input shape (X)",
+                "Simulation output shape (y)",
+                "Training dataset shape (train_idxs)",
+                "Test dataset shape (test_idxs)",
+                "Do hyperparameter search (param_search)",
+                "Type of hyperparameter search (search_type)",
+                "# sampled parameter settings (param_search_iters)",
+                "Scale data before fitting (scale)",
+                "Scaler (scaler)",
+                "Dimensionality reduction before fitting (reduce_dim)",
+                "Dimensionality reduction method (dim_reducer)",
+                "Cross-validation strategy (cv)",
+                "# folds (folds)",
+                "# parallel jobs (n_jobs)",
+            ],
+            columns=["Values"],
+        )
+
+        settings_str = settings.to_string(index=True, header=False)
+        width = len(settings_str.split("\n")[0])
+
+        print("AutoEmulate is set up with the following settings:")
+        print("-" * width)
+        print(settings_str)
+        print("-" * width)
+        print("Models:" + models)
+        print("-" * width)
+        print("Metrics:" + metrics)
+
     def print_results(self, model=None, sort_by="r2"):
         """Print cv results.
 
@@ -470,5 +548,10 @@ def plot_model(self, model, plot="standard", n_cols=2, figsize=None):
             Number of columns in the plot grid for multi-output. Default is 2.
         """
         _plot_model(
-            model, self.X[self.test_idxs], self.y[self.test_idxs], plot, n_cols, figsize
+            model,
+            self.X[self.test_idxs],
+            self.y[self.test_idxs],
+            plot,
+            n_cols,
+            figsize,
         )