from data_filters import *
import pandas as pd


def categorize_shots(shots):
    if shots >= 12:
        return 2
    elif shots <= 6:
        return 0
    else:
        return 1

def categorize_passes(pass_count):
    if pass_count < 400:
        return 0  #słabo
    elif 400 <= pass_count <= 500:
        return 1  #średnio
    else:
        return 2  #dużo
        
def categorize_possesion(shots):
    if shots >= 56:
        return 2
    elif shots <= 40:
        return 0
    else:
        return 1
    
def categorize_points(data, row, teamHome, matches_type):
    if teamHome:
        data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
        points = calculatePoints(data_5,row['home_team'])
    else:
        data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
        points = calculatePoints(data_5,row['away_team'])
    if points <=1:
        return 0
    elif points >=2:
        return 2
    else:
        return 1

def get_method(data, home_away, method, matches_type):
    values = []
    for index, row in data.iterrows():
        values.append(method(data, row, home_away, matches_type))
    return values

def get_points_home(data):
    points = []
    for index, row in data.iterrows():
        points.append(categorize_points(data, row, True))
    return points




def get_points_away(data):
    points = []
    for index, row in data.iterrows():
        points.append(categorize_points(data, row, False))
    return points



def categorize_diff(data, row, teamHome, matches_type):
    if teamHome:
        data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
        diff = calculateGoalDifference(data_5,row['home_team'])
    else:
        data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
        diff = calculateGoalDifference(data_5,row['away_team'])
    if diff <=0:
        return 0
    else:
        return 1

def categorize_aggression(data, row, teamHome, matches_type):
    if teamHome:
        data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
        diff = calculateAggression(data_5,row['home_team'])
    else:
        data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
        diff = calculateAggression(data_5,row['away_team'])
    return diff
   # if diff <=0:
    #    return 0
   # else:
   #     return 1
def get_diff_home(data):
    points = []
    for index, row in data.iterrows():
        points.append(categorize_diff(data, row, True))
    return points




def get_diff_away(data):
    points = []
    for index, row in data.iterrows():
        points.append(categorize_diff(data, row, False))
    return points




def add_column(data_frame, transform_function, new_column, existing_column=None):
    if existing_column != None:
        new_column_values = data_frame[existing_column].apply(transform_function)
        data_frame[new_column] = new_column_values
    else:
        new_column_values = transform_function
        data_frame[new_column] = new_column_values
    return data_frame

def get_result_list(df, home_team):
    results = []
    for score in df['result_full']:
        results.append(getResult(score,home_team))
    return results