From 9d947a42ced99ce64085748106119e05a85f9943 Mon Sep 17 00:00:00 2001
From: Raphael Mitsch <r.mitsch@outlook.com>
Date: Mon, 24 Oct 2022 11:25:51 +0200
Subject: [PATCH] Change default value for n_trials. Log table iteratively.

---
 spacy/cli/find_threshold.py | 20 ++++++++++++--------
 1 file changed, 12 insertions(+), 8 deletions(-)

diff --git a/spacy/cli/find_threshold.py b/spacy/cli/find_threshold.py
index 6e4141d7b..9f1b14475 100644
--- a/spacy/cli/find_threshold.py
+++ b/spacy/cli/find_threshold.py
@@ -13,7 +13,7 @@ from ._util import app, Arg, Opt, import_code, setup_gpu
 from .. import util
 
 _DEFAULTS = {
-    "n_trials": 10,
+    "n_trials": 11,
     "use_gpu": -1,
     "gold_preproc": False,
 }
@@ -109,7 +109,7 @@ def find_threshold(
     except KeyError as err:
         wasabi.msg.fail(title=str(err), exits=1)
     if not hasattr(pipe, "scorer"):
-        raise AttributeError(Errors.E1047)
+        raise AttributeError(Errors.E1045)
 
     if not silent:
         wasabi.msg.info(
@@ -125,7 +125,7 @@ def find_threshold(
     def set_nested_item(
         config: Dict[str, Any], keys: List[str], value: float
     ) -> Dict[str, Any]:
-        """Set item in nested dictionary. Adapated from https://stackoverflow.com/a/54138200.
+        """Set item in nested dictionary. Adapted from https://stackoverflow.com/a/54138200.
         config (Dict[str, Any]): Configuration dictionary.
         keys (List[Any]): Path to value to set.
         value (float): Value to set.
@@ -149,6 +149,8 @@ def find_threshold(
     # Evaluate with varying threshold values.
     scores: Dict[float, float] = {}
     config_keys_full = ["components", pipe_name, *config_keys]
+    table_col_widths = (10, 10)
+    print(wasabi.tables.row(["Threshold", f"{scores_key}"], widths=table_col_widths))
     for threshold in numpy.linspace(0, 1, n_trials):
         # Reload pipeline with overrides specifying the new threshold.
         nlp = util.load_model(
@@ -173,15 +175,17 @@ def find_threshold(
                 f"scores.",
                 exits=1,
             )
+        print(
+            wasabi.row(
+                [round(threshold, 3), round(scores[threshold], 3)],
+                widths=table_col_widths,
+            )
+        )
 
     best_threshold = max(scores.keys(), key=(lambda key: scores[key]))
     if not silent:
         print(
-            f"Best threshold: {round(best_threshold, ndigits=4)} with value of {scores[best_threshold]}.",
-            wasabi.tables.table(
-                data=[(threshold, score) for threshold, score in scores.items()],
-                header=["Threshold", f"{scores_key}"],
-            ),
+            f"\nBest threshold: {round(best_threshold, ndigits=4)} with value of {scores[best_threshold]}."
         )
 
     return best_threshold, scores[best_threshold], scores