import polars as pl import numpy as np import requests def calculate_arm_angles(df: pl.DataFrame,pitcher_id:int) -> pl.DataFrame: df_arm_angle = pl.read_csv('stuff_model/pitcher_arm_angles_2024.csv') #pitcher_id = 489446 df_filter = df.filter(pl.col("pitcher_id") == pitcher_id) # data = requests.get(f'https://statsapi.mlb.com/api/v1/people?personIds={pitcher_id}').json() if pitcher_id not in df_arm_angle["pitcher"]: data = requests.get(f'https://statsapi.mlb.com/api/v1/people?personIds={pitcher_id}').json() height_in = data['people'][0]['height'] height = int(height_in.split("'")[0]) * 12 + int(height_in.split("'")[1].split('"')[0]) df_filter = (df_filter.with_columns( (pl.col("release_pos_x") * 12).alias("release_pos_x"), (pl.col("release_pos_z") * 12).alias("release_pos_z"), (pl.lit(height * 0.70)).alias("shoulder_pos"), ) .with_columns( (pl.col("release_pos_z") - pl.col("shoulder_pos")).alias("Opp"), pl.col("release_pos_x").abs().alias("Adj"), ) .with_columns( pl.struct(["Opp", "Adj"]).map_elements(lambda x: np.arctan2(x["Opp"], x["Adj"])).alias("arm_angle_rad") )) df_filter = (df_filter.with_columns( pl.col("arm_angle_rad").degrees().alias("arm_angle") #.drop(["Opp", "arm_angle_rad"]) )) else: shoulder_x = df_arm_angle.filter(pl.col("pitcher") == pitcher_id)["relative_shoulder_x"][0] shoulder_z = df_arm_angle.filter(pl.col("pitcher") == pitcher_id)["shoulder_z"][0] ball_angle = df_arm_angle.filter(pl.col("pitcher") == pitcher_id)["ball_angle"][0] print(shoulder_x, shoulder_z) df_filter = (df_filter.with_columns( ) .with_columns( (pl.col("release_pos_z") - shoulder_z).alias("Opp"), (pl.col("release_pos_x") - shoulder_x).alias("Adj"), ) .with_columns( pl.struct(["Opp", "Adj"]).map_elements(lambda x: np.arctan2(x["Opp"], x["Adj"])).alias("arm_angle_rad") ) .with_columns( pl.col("arm_angle_rad").degrees().alias("arm_angle") ) #.drop(["Opp", "arm_angle_rad"]) ) df_filter = df_filter.with_columns( ((pl.col("arm_angle") * 0.25) + (ball_angle * 0.75)).alias("arm_angle") ) return df_filter