From e0b160f07182f63cfd1a73c61a6a7cd1fb7c56a2 Mon Sep 17 00:00:00 2001
From: Krzysztof Rudnicki <krzysztofrudnicki0@gmail.com>
Date: Mon, 29 May 2023 21:39:56 +0200
Subject: [PATCH] feat: add seed to randomizing anime

---
 .vscode/extensions.json             | 3 +++
 midterm/{ => code}/main.py          | 4 ++--
 midterm/{ => code}/requirements.txt | 0
 3 files changed, 5 insertions(+), 2 deletions(-)
 create mode 100644 .vscode/extensions.json
 rename midterm/{ => code}/main.py (98%)
 rename midterm/{ => code}/requirements.txt (100%)

diff --git a/.vscode/extensions.json b/.vscode/extensions.json
new file mode 100644
index 00000000..cd8d3d51
--- /dev/null
+++ b/.vscode/extensions.json
@@ -0,0 +1,3 @@
+{
+  "recommendations": ["james-yu.latex-workshop"]
+}
diff --git a/midterm/main.py b/midterm/code/main.py
similarity index 98%
rename from midterm/main.py
rename to midterm/code/main.py
index 69625c20..cc026d0c 100644
--- a/midterm/main.py
+++ b/midterm/code/main.py
@@ -156,12 +156,12 @@ def preprocessing(rating_data, anime_contact_data, debug=False):
     return pivot_table
 
 
-def predict(prediction_model, pivot_table):
+def predict(prediction_model, pivot_table, seed=42):
     """
     This will choose a random anime name and our prediction_model will predict similar anime.
     """
+    np.random.seed(seed)
     random_anime = np.random.choice(pivot_table.shape[0])
-
     query = pivot_table.iloc[random_anime, :].values.reshape(1, -1)
     distance, suggestions = prediction_model.kneighbors(query, n_neighbors=6)
     random_anime_name = pivot_table.index[random_anime]
diff --git a/midterm/requirements.txt b/midterm/code/requirements.txt
similarity index 100%
rename from midterm/requirements.txt
rename to midterm/code/requirements.txt