import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import matplotlib.patheffects as path_effects
import matplotlib.font_manager as fm
import matplotlib.colors as mcolors
from matplotlib import cm
from highlight_text import fig_text, ax_text
import matplotlib.gridspec as gridspec

# We'll only use a vertical pitch for this tutorial
from mplsoccer import VerticalPitch

from PIL import Image
import urllib
import os

font_path = "../assets/fonts"
for x in os.listdir(font_path):
    for y in os.listdir(f"{font_path}/{x}"):
        if y.split(".")[-1] == "ttf":
            fm.fontManager.addfont(f"{font_path}/{x}/{y}")
            try:
                fm.FontProperties(weight=y.split("-")[-1].split(".")[0].lower(), fname=y.split("-")[0])
            except Exception:
                continue

plt.style.use("../assets/stylesheets/soc_base.mplstyle")

df = pd.read_csv('data/belgian_shots_08292022.csv', index_col=0)

zone_areas = {
    'zone_1':{
        'x_lower_bound': 54.16, 'x_upper_bound': 68,
        'y_lower_bound': 88.5, 'y_upper_bound': 105,
    },
    'zone_2':{
        'x_lower_bound': 0, 'x_upper_bound': 13.84,
        'y_lower_bound': 88.5, 'y_upper_bound': 105,
    },
    'zone_3':{
        'x_lower_bound': 54.16, 'x_upper_bound': 68,
        'y_lower_bound': 20, 'y_upper_bound': 88.5,
    },
    'zone_4':{
        'x_lower_bound': 0, 'x_upper_bound': 13.84,
        'y_lower_bound': 20, 'y_upper_bound': 88.5,
    },
    'zone_5':{
        'x_lower_bound': 13.84, 'x_upper_bound': 24.84,
        'y_lower_bound': 88.5, 'y_upper_bound': 105,
    },
    'zone_6':{
        'x_lower_bound': 43.16, 'x_upper_bound': 54.16,
        'y_lower_bound': 88.5, 'y_upper_bound': 105,
    },
    'zone_7':{
        'x_lower_bound': 24.84, 'x_upper_bound': 43.16,
        'y_lower_bound': 88.5, 'y_upper_bound': 99.5,
    },
    'zone_8':{
        'x_lower_bound': 24.84, 'x_upper_bound': 43.16,
        'y_lower_bound': 99.5, 'y_upper_bound': 105,
    },
    'zone_9':{
        'x_lower_bound': 13.84, 'x_upper_bound': 24.84,
        'y_lower_bound': 75, 'y_upper_bound': 88.5,
    },
    'zone_10':{
        'x_lower_bound': 43.16, 'x_upper_bound': 54.16,
        'y_lower_bound': 75, 'y_upper_bound': 88.5,
    },
    'zone_11':{
        'x_lower_bound': 24.84, 'x_upper_bound': 43.16,
        'y_lower_bound': 75, 'y_upper_bound': 88.5,
    },
    'zone_12':{
        'x_lower_bound': 13.84, 'x_upper_bound': 54.16,
        'y_lower_bound': 20, 'y_upper_bound': 75,
    }
}

def assign_shot_zone(x,y):
    '''
    This function returns the zone based on the x & y coordinates of the shot
    taken.
    Args:
        - x (float): the x position of the shot based on a vertical grid.
        - y (float): the y position of the shot based on a vertical grid.
    '''

    global zone_areas

    # Conditions

    for zone in zone_areas:
        if (x >= zone_areas[zone]['x_lower_bound']) & (x <= zone_areas[zone]['x_upper_bound']):
            if (y >= zone_areas[zone]['y_lower_bound']) & (y <= zone_areas[zone]['y_upper_bound']):
                return zone

df.rename(columns={'x':'y', 'y':'x'}, inplace=True)
df = df[df['situation'] != 'Penalty'].reset_index(drop=True)

data = df.groupby(['teamId', 'teamName', 'teamColor', 'zone_area']).apply(lambda x: x.shape[0]).reset_index()
data.rename(columns={0:'num_shots'}, inplace=True)

total_shots = data.groupby(['teamId'])['num_shots'].sum().reset_index()
total_shots.rename(columns={'num_shots':'total_shots'}, inplace=True)

data = pd.merge(data, total_shots, on='teamId', how='left')
data['pct_shots'] = data['num_shots']/data['total_shots']

def plot_shot_location(ax, fig, teamId, df=data):
    '''
    This functions plots the shot location grid for a team.
    '''
    global zone_areas
    data = df.copy()

    pitch = VerticalPitch(
        pitch_type='uefa',
        half=True,
        goal_type='box',
        linewidth=1.25,
        line_color='black',
        spot_scale=0.0
    )
    pitch.draw(ax = ax)

    plot_df = data[data['teamId'] == teamId]
    max_value = plot_df['pct_shots'].max()
    team_name = plot_df['teamName'].iloc[0]
    team_color = plot_df['teamColor'].iloc[0]
    team_id = plot_df['teamId'].iloc[0]
    total_shots = plot_df['total_shots'].iloc[0]

    # Grids
    ax.plot([13.84, 13.84], [40, 88.5], ls='--', color='black', lw=1)
    ax.plot([54.16, 54.16], [40, 88.5], ls='--', color='black', lw=1)
    ax.plot([24.84, 24.84], [99.5, 88.5], ls='--', color='black', lw=1)
    ax.plot([43.16, 43.16], [99.5, 88.5], ls='--', color='black', lw=1)

    ax.plot([68, 54.16], [88.5,88.5], ls='--', color='black', lw=1)
    ax.plot([0.5, 13.84], [88.5,88.5], ls='--', color='black', lw=1)
    ax.plot([13.84, 54.16], [75,75], ls='--', color='black', lw=1)

    for zone in plot_df['zone_area']:
        shot_pct = plot_df[plot_df['zone_area'] == zone]['pct_shots'].iloc[0]
        x_lim = [zone_areas[zone]['x_lower_bound'], zone_areas[zone]['x_upper_bound']]
        y1 = zone_areas[zone]['y_lower_bound']
        y2 = zone_areas[zone]['y_upper_bound']
        ax.fill_between(
            x=x_lim, 
            y1=y1, y2=y2, 
            color='#DA70D6', alpha=(shot_pct/max_value),
            zorder=0, ec='None')
        if shot_pct > 0.05:
            x_pos = x_lim[0] + abs(x_lim[0] - x_lim[1])/2
            if y1 == 20:
                y1 = 58
            y_pos = y1 + abs(y1 - y2)/2
            text_ = ax.annotate(
                xy=(x_pos, y_pos),
                text=f'{shot_pct:.0%}',
                ha='center',
                va='center',
                color='black',
                weight='bold',
                size=7
            )
            text_.set_path_effects(
                [path_effects.Stroke(linewidth=1.5, foreground='white'), path_effects.Normal()]
            )
    # -- Transformation functions
    ax.set_ylim(ax.get_ylim()[0], ax.get_ylim()[1])
    ax.set_xlim(ax.get_xlim()[0], ax.get_xlim()[1])
    DC_to_FC = ax.transData.transform
    FC_to_NFC = fig.transFigure.inverted().transform
    # -- Take data coordinates and transform them to normalized figure coordinates
    DC_to_NFC = lambda x: FC_to_NFC(DC_to_FC(x))
    ax_coords = DC_to_NFC((11,62.5))
    ax_size = 0.021
    image_ax = fig.add_axes(
        [ax_coords[0], ax_coords[1], ax_size, ax_size],
        fc='None', anchor='C'
    )
    fotmob_url = 'https://images.fotmob.com/image_resources/logo/teamlogo/'
    club_icon = Image.open(urllib.request.urlopen(f'{fotmob_url}{team_id:.0f}.png')).convert('LA')
    image_ax.imshow(club_icon)
    image_ax.axis('off')
    ax_text(
        x=65, y=120,
        s=f'{team_name} <| shots {total_shots:.0f}>',
        highlight_textprops=[{'size':7, 'weight':'normal'}],
        ax=ax,
        weight='bold',
        size=10,
        font='DM Sans'
    )
    
    return ax

order_teams = total_shots.sort_values(by='total_shots', ascending=False)