From eb88e9baf72486f0156887e1533c79db1a697e00 Mon Sep 17 00:00:00 2001
From: americast <sayan.sinha@cc.gatech.edu>
Date: Thu, 9 Nov 2023 23:50:55 -0500
Subject: [PATCH] update docs

---
 docs/source/reference/ai/model-forecasting.rst |  2 +-
 evadb/functions/forecast.py                    | 12 +++++++-----
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/docs/source/reference/ai/model-forecasting.rst b/docs/source/reference/ai/model-forecasting.rst
index 589d5b23e..1d97ffa8b 100644
--- a/docs/source/reference/ai/model-forecasting.rst
+++ b/docs/source/reference/ai/model-forecasting.rst
@@ -75,7 +75,7 @@ EvaDB's default forecast framework is `statsforecast <https://nixtla.github.io/s
 
 .. note::
   
-   `Forecasting` function also logs suggestions. Logged information, such as metrics and suggestions, is sent to STDOUT by default. If you wish not to print it, please send `FALSE` as an optional argument while calling the function. Eg. `SELECT Forecast(FALSE);`
+   `Forecasting` function also logs suggestions. Logged information, such as metrics and suggestions, is sent to STDOUT by default. A figure is also plotted and is saved in a binary format supported by OpenCV in the `plot` column of the output table. It maybe rendered using the `cv2.imdecode` function. If you wish not to obtain the logged information, please send `FALSE` as an optional argument while calling the function. Eg. `SELECT Forecast(FALSE);`
 
 
 Below is an example query specifying the above parameters:
diff --git a/evadb/functions/forecast.py b/evadb/functions/forecast.py
index 6533ee419..2545150ec 100644
--- a/evadb/functions/forecast.py
+++ b/evadb/functions/forecast.py
@@ -86,7 +86,7 @@ def forward(self, data) -> pd.DataFrame:
 
         # Feedback
         if len(data) == 0 or list(list(data.iloc[0]))[0] is True:
-            # Suggestions
+            ## Suggestions
             suggestion_list = []
             # 1: Flat predictions
             if self.library == "statsforecast":
@@ -102,7 +102,7 @@ def forward(self, data) -> pd.DataFrame:
             for suggestion in set(suggestion_list):
                 log_str += "\nSUGGESTION: " + self.suggestion_dict[suggestion]
 
-            # Metrics
+            ## Metrics
             if self.rmse is not None:
                 log_str += "\nMean normalized RMSE: " + str(self.rmse)
             if self.hypers is not None:
@@ -142,7 +142,7 @@ def forward(self, data) -> pd.DataFrame:
             plt.legend()
             plt.tight_layout()
 
-            # convert plt figure to opencv https://copyprogramming.com/howto/convert-matplotlib-figure-to-cv2-image-a-complete-guide-with-examples#converting-matplotlib-figure-to-cv2-image
+            # convert plt figure to opencv, inspired from https://copyprogramming.com/howto/convert-matplotlib-figure-to-cv2-image-a-complete-guide-with-examples#converting-matplotlib-figure-to-cv2-image
             # convert figure to canvas
             canvas = plt.get_current_fig_manager().canvas
 
@@ -156,13 +156,15 @@ def forward(self, data) -> pd.DataFrame:
             # convert image to cv2 format
             cv2_img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
 
-            ## Conver to bytes
+            # Conver to bytes
             _, buffer = cv2.imencode(".jpg", cv2_img)
             img_bytes = buffer.tobytes()
 
-            ## Add to dataframe as a plot
+            # Add to dataframe as a plot
             forecast_df["plot"] = [img_bytes] + [None] * (len(forecast_df) - 1)
 
+            log_str += "\nA plot has been saved in the 'plot' column of the output table. It maybe rendered using the cv2.imdecode function."
+
             print(log_str)
 
         forecast_df = forecast_df.rename(