feat: これどこにcommitされるんだ

app.py

@@ -1,4 +1,74 @@
-import streamlit as st
+import matplotlib.pyplot
+import pandas as pd
+import os
+import random
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+
+def main():
+    df = readcsv(10)
+    if df is not None:
+        plt = simulate_games(df, num_games=2000)
+        plt.show()
+
+
+def readcsv(filter: int = 10) -> pd.DataFrame | None:
+    # CSVファイルの存在確認
+    csv_file = "saka.csv"
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    csv_path = os.path.join(current_dir, csv_file)
+    if not os.path.isfile(csv_path):
+        print(f"Error: {csv_file} does not exist.")
+        return None
+
+    # CSVファイルの読み込み
+    df = pd.read_csv(csv_path)
+
+    filtered_df = df[df.iloc[:, 0] == filter]
+
+    # フィルター後のデータフレームを表示
+    print(filtered_df)
+    return filtered_df
+
+
+def simulate_games(df, num_games: int = 1000, max_score: int = 20000):
+    results = {}
+
+    for index, row in df.iterrows():
+        place = row["place"]
+        win_score = row["win"]
+        lose_score = row["lose"]
+        draw_score = row["draw"]
+        win_rate = row["win_rate"]
+        lose_rate = row["lose_rate"]
+        draw_rate = row["draw_rate"]
+        init_score = row["init_score"]
+
+        scores = [init_score]
+        for _ in range(num_games):
+            result = random.choices([1, 2, 3], weights=[win_rate, lose_rate, draw_rate])[0]
+            if result == 1:
+                scores.append(scores[-1] + win_score)
+            elif result == 2:
+                scores.append(scores[-1] + lose_score)
+            else:
+                scores.append(scores[-1] + draw_score)
+
+        results[place] = scores
+        df.at[index, "reached_goal"] = any([score >= row["rank_up_score"] for score in scores])
+        df.at[index, "rank_down"] = any([score <= 0 for score in scores])
+
+    matplotlib.pyplot.figure(figsize=(10, 6))
+    for place, scores in results.items():
+        matplotlib.pyplot.plot(range(num_games + 1), scores, label=place)
+    matplotlib.pyplot.axhline(y=df.iloc[0]["init_score"], color="black", linestyle="--", label="initial score")
+    matplotlib.pyplot.axhline(y=df.iloc[0]["rank_up_score"], color="red", linestyle="--", label="goal")
+    matplotlib.pyplot.xlabel("Game")
+    matplotlib.pyplot.ylabel("Score")
+    matplotlib.pyplot.ylim(0, max_score)
+    matplotlib.pyplot.title("Score Transition")
+    matplotlib.pyplot.legend()
+    return matplotlib.pyplot
+
+
+if __name__ == "__main__":
+    main()

saka.csv

@@ -0,0 +1,17 @@
+dan,place,win,draw,lose,win_rate,draw_rate,lose_rate,init_score,rank_up_score
+10,enton,90,0,-120,0.3506,0.3742,0.2752,3800,7600
+10,enhan,135,0,-180,0.35,0.38,0.30,3800,7600
+10,ginton,160,0,-180,0.3636,0.3322,0.3042,3800,7600
+10,ginhan,240,0,-270,0.3481,0.3754,0.2827,3800,7600
+7,ginton,160,0,-150,0.35,0.38,0.27,2300,4600
+8,ginton,160,0,-160,0.35,0.38,0.27,2800,5600
+9,ginton,160,0,-170,0.35,0.38,0.27,3300,6600
+7,ginhan,240,0,-225,0.35,0.38,0.27,2300,4600
+8,ginhan,240,0,-240,0.35,0.38,0.27,2800,5600
+9,ginhan,240,0,-255,0.35,0.38,0.27,3300,6600
+7,enton,90,0,-90,0.35,0.38,0.27,2300,4600
+8,enton,90,0,-100,0.35,0.38,0.27,2800,5600
+9,enton,90,0,-110,0.35,0.38,0.27,3300,6600
+7,enhan,135,0,-135,0.35,0.38,0.27,2300,4600
+8,enhan,135,0,-150,0.35,0.38,0.27,2800,5600
+9,enhan,135,0,-165,0.35,0.38,0.27,3300,6600

sample.py

@@ -0,0 +1,74 @@
+import matplotlib.pyplot
+import pandas as pd
+import os
+import random
+
+
+def main():
+    df = readcsv(10)
+    if df is not None:
+        plt = simulate_games(df, num_games=2000)
+        plt.show()
+
+
+def readcsv(filter: int = 10) -> pd.DataFrame | None:
+    # CSVファイルの存在確認
+    csv_file = "saka.csv"
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    csv_path = os.path.join(current_dir, csv_file)
+    if not os.path.isfile(csv_path):
+        print(f"Error: {csv_file} does not exist.")
+        return None
+
+    # CSVファイルの読み込み
+    df = pd.read_csv(csv_path)
+
+    filtered_df = df[df.iloc[:, 0] == filter]
+
+    # フィルター後のデータフレームを表示
+    print(filtered_df)
+    return filtered_df
+
+
+def simulate_games(df, num_games: int = 1000, max_score: int = 20000):
+    results = {}
+
+    for index, row in df.iterrows():
+        place = row["place"]
+        win_score = row["win"]
+        lose_score = row["lose"]
+        draw_score = row["draw"]
+        win_rate = row["win_rate"]
+        lose_rate = row["lose_rate"]
+        draw_rate = row["draw_rate"]
+        init_score = row["init_score"]
+
+        scores = [init_score]
+        for _ in range(num_games):
+            result = random.choices([1, 2, 3], weights=[win_rate, lose_rate, draw_rate])[0]
+            if result == 1:
+                scores.append(scores[-1] + win_score)
+            elif result == 2:
+                scores.append(scores[-1] + lose_score)
+            else:
+                scores.append(scores[-1] + draw_score)
+
+        results[place] = scores
+        df.at[index, "reached_goal"] = any([score >= row["rank_up_score"] for score in scores])
+        df.at[index, "rank_down"] = any([score <= 0 for score in scores])
+
+    matplotlib.pyplot.figure(figsize=(10, 6))
+    for place, scores in results.items():
+        matplotlib.pyplot.plot(range(num_games + 1), scores, label=place)
+    matplotlib.pyplot.axhline(y=df.iloc[0]["init_score"], color="black", linestyle="--", label="initial score")
+    matplotlib.pyplot.axhline(y=df.iloc[0]["rank_up_score"], color="red", linestyle="--", label="goal")
+    matplotlib.pyplot.xlabel("Game")
+    matplotlib.pyplot.ylabel("Score")
+    matplotlib.pyplot.ylim(0, max_score)
+    matplotlib.pyplot.title("Score Transition")
+    matplotlib.pyplot.legend()
+    return matplotlib.pyplot
+
+
+if __name__ == "__main__":
+    main()