From a52219ae7403f6dad968f57930a1cb125c58e53c Mon Sep 17 00:00:00 2001
From: Stefan Suwelack <stefan.suwelack@renumics.com>
Date: Tue, 19 Sep 2023 13:27:01 +0200
Subject: [PATCH] docstring added

---
 renumics/spotlight/layouts/__init__.py      |  6 ++++--
 renumics/spotlight/layouts/model_compare.py | 24 +++++++++++++++++++--
 renumics/spotlight/layouts/model_debug.py   | 18 ++++++++++++++--
 3 files changed, 42 insertions(+), 6 deletions(-)

diff --git a/renumics/spotlight/layouts/__init__.py b/renumics/spotlight/layouts/__init__.py
index c73f5fab..740fa53c 100644
--- a/renumics/spotlight/layouts/__init__.py
+++ b/renumics/spotlight/layouts/__init__.py
@@ -1,2 +1,4 @@
-from .model_debug import model_debug_classification
-from .model_compare import model_compare_classification
+from .model_debug import debug_classification
+from .model_compare import compare_classification
+
+__all__ = ["debug_classification", "compare_classification"]
diff --git a/renumics/spotlight/layouts/model_compare.py b/renumics/spotlight/layouts/model_compare.py
index 29394942..75fb5ad1 100644
--- a/renumics/spotlight/layouts/model_compare.py
+++ b/renumics/spotlight/layouts/model_compare.py
@@ -1,6 +1,8 @@
 from renumics.spotlight import layout
 from renumics.spotlight.layout import (
     Layout,
+    Tab,
+    Split,
     lenses,
     table,
     similaritymap,
@@ -11,11 +13,11 @@
     issues,
     confusion_matrix,
 )
-from typing import Optional
+from typing import Optional, Union
 from renumics.spotlight import Audio, Image
 
 
-def model_compare_classification(
+def compare_classification(
     label: str = "label",
     model1_prediction: str = "m1_prediction",
     model1_embedding: str = "",
@@ -25,6 +27,22 @@ def model_compare_classification(
     model2_correct: str = "",
     inspect: Optional[dict] = None,
 ) -> Layout:
+    """This function generates a Spotlight layout for comparing two different machine learning classification models.
+
+    Args:
+        label (str, optional): Name of the dataframe column that contains the label. Defaults to "label".
+        model1_prediction (str, optional): Name of the dataframe column that contains the prediction for model 1. Defaults to "m1_prediction".
+        model1_embedding (str, optional): Name of the dataframe column that contains thee embedding for model 1. Defaults to "".
+        model1_correct (str, optional): Name of the dataframe column that contains a flag if the data sample is predicted correctly by model 1.
+        model2_prediction (str, optional): Name of the dataframe column that contains the prediction for model 2. Defaults to "m2_prediction".
+        model2_embedding (str, optional): Name of the dataframe column that contains thee embedding for model 2. Defaults to "".
+        model2_correct (str, optional): Name and type of the dataframe columns that are displayed in the inspector, e.g. {'audio': spotlight.Audio}. Defaults to None.
+        inspect (Optional[dict], optional): Name of the dataframe column that contains a flag if the data sample is predicted correctly by model 1.
+
+    Returns:
+        Layout: _description_
+    """
+    
     # first column: table + issues
     metrics = split(
         [
@@ -100,6 +118,8 @@ def model_compare_classification(
             )
             column2_list.append(row3)
 
+    column2:Union[Tab, Split]
+
     if len(column2_list) == 1:
         column2 = column2_list[0]
     elif len(column2_list) == 2:
diff --git a/renumics/spotlight/layouts/model_debug.py b/renumics/spotlight/layouts/model_debug.py
index 576b02a1..b5281979 100644
--- a/renumics/spotlight/layouts/model_debug.py
+++ b/renumics/spotlight/layouts/model_debug.py
@@ -16,13 +16,27 @@
 from renumics.spotlight import Audio, Image
 
 
-def model_debug_classification(
+
+def debug_classification(
     label: str = "label",
     prediction: str = "prediction",
     embedding: str = "",
     inspect: Optional[dict] = None,
     features: Optional[list] = None,
 ) -> Layout:
+    """This function generates a Spotlight layout for debugging a machine learning classification model.
+
+    Args:
+        label (str, optional): Name of the dataframe column that contains the label. Defaults to "label".
+        prediction (str, optional): Name of the dataframe column that contains the prediction. Defaults to "prediction".
+        embedding (str, optional): Name of the dataframe column that contains the embedding. Defaults to "".
+        inspect (Optional[dict], optional): Name and type of the dataframe columns that are displayed in the inspector, e.g. {'audio': spotlight.Audio}. Defaults to None.
+        features (Optional[list], optional): Name of the dataframe columns that contain useful metadata and features. Defaults to None.
+
+    Returns:
+        Layout: Layout to be displayed with Spotlight.
+    """
+
     # first column: table + issues
     metrics = tab(
         metric(name="Accuracy", metric="accuracy", columns=[label, prediction]),
@@ -45,7 +59,7 @@ def model_debug_classification(
         )
     )
 
-    # third column: confusion matric, feature histograms (optional), embedding (optional)
+    # second column: confusion matric, feature histograms (optional), embedding (optional)
     if features is not None:
         histogram_list = []
         for idx, feature in enumerate(features):