from IPython.core.display import display

import itertools

from nfl_analytics.core import players as nfl_players
from nfl_analytics.core import fantasy
from nfl_analytics.core import queries

import datetime
import numpy
import pandas
from matplotlib import style
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.cbook as cbook
%matplotlib inline

pids = ["8439", "13994", "2330"]
season = 'NFL - 2015'

players = [nfl_players.NFLPlayerSeason(pid, season) for pid in pids]

for p in players:
    p.prep()

months = mdates.MonthLocator()
monthsFmt = mdates.DateFormatter('%B %d')
weeks = mdates.WeekdayLocator()

# Seaborn's visual styling was inspired by ggplot,
#   so this style should be very similar:
plt.style.use('ggplot')
#plt.style.use('default')
plt.rcParams['xtick.minor.visible'] = True

def plotPlayersPoints(players_list):
    
    colors = [c for (p,c) in zip(players_list,
                                 itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k']))]
    shape_formats = ['go--', 'bo--', 'ko--', 'ro--',]
    
    
    plt.rcParams['xtick.minor.visible'] = False
    
    fig, ax = plt.subplots(figsize = (12, 9))
    ax.set_title('QB Fantasy Football Points, 2015 Season')
    
    #
    
    
    # Axis Labels
    ax.set_xlabel("Week")
    ax.set_ylabel("Points per Game")

    # x-axis Ticks
    ax.xaxis.set_ticks([r for r in range(1,18)])

    # Define x-Axis Limits
    weekmin = 0.5
    weekmax = 17.5
    
    y_max = -999
    lines = []
    for i, player in enumerate(players_list):
        color = colors[i]
        p,  = ax.plot(player.ppg.week,
                      player.ppg.points,
                      c = color,
                      marker = 'o',
                      linestyle='--',
                      label=player.name,
                      markersize=8)
        lines.append(p)
        y_max = max(y_max, 
                    player.ppg.points.max())

    
    # Set Axis limits
    ax.set_xlim(weekmin, weekmax)
    ax.set_ylim(0, y_max + 10)

    # Set Legent from Lines
    ax.legend(lines, [l.get_label() for l in lines])

    plt.grid(True)
    plt.show()

plotPlayersPoints(players)

season = 'NFL - 2015'
db_path = 'data/NFLGames'

qbs = queries.fetchPlayersPositionSeason('QB', season=season, db_path=db_path)
print(qbs.shape)
qbs.head()

players = [nfl_players.NFLPlayerSeason(pid=pid, season=season) for pid in qbs.pid]

for p in players:
    p.prep()

# Filter out players with no games..
print(len(players))
players = [p for p in players if p.ppg.shape[0] > 0]
print(len(players))

# Remove players with less than 5 games:
target_players = [p for p in players if p.ppg.shape[0] >= 7]
print(len(target_players))

ppgs = pandas.DataFrame([{'pid' : p.pid,
                          'name' : p.name,
                          'total_points' : sum(p.ppg.points)} \
                          for p in target_players])
ppgs.sort_values(by='total_points', ascending=False, inplace=True)
display(ppgs.head(12))
display(ppgs.describe(percentiles=[.50, .75, .85]))

# Build a big dataframe with all the ppgs
ppg_dfs = pandas.concat([p.ppg for p in target_players])
ppg_dfs.index = range(ppg_dfs.shape[0])
ppg_dfs.week = [int(w) for w in ppg_dfs.week]
print(ppg_dfs.shape)
ppg_dfs.head()

week_stats = []
for name, group in ppg_dfs.groupby('week'):
    week_stats.append({'week' : int(name),
                       'avg' : group['points'].mean(),
                       'std' : group['points'].std()})
week_stats = pandas.DataFrame(week_stats)
week_stats.sort_values(by='week', inplace=True)
week_stats = week_stats.reset_index()
week_stats.week = [int(w) for w in week_stats.week]
week_stats.head()

fig, ax = plt.subplots(figsize = (16, 12))
ax.set_title('QB Fantasy Football Points, 2015 Season')

# Axis Labels
ax.set_xlabel("Week in Season")
ax.set_ylabel("Points per Game")

# x-axis Ticks
ax.xaxis.set_ticks([r for r in range(1,18)])

# Define x-Axis Limits
weekmin = 0.5
weekmax = 17.5

lines = []

e = ax.errorbar(x = 'week',
                y = 'avg',
                yerr = 'std',
                data = week_stats,
                color='k',
                fmt='^',
                markersize=10,
                label='Average')
lines.append(e)

# Plot the top n
y_max = -999
n = 3
colors = [c for (p,c) in zip(range(n),
                             itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k']))]
for i, np in enumerate(zip(list(ppgs.name)[:n],
                                  list(ppgs.pid)[:n])
                              ):
    name, pid = np
    data = ppg_dfs[ppg_dfs.pid==pid]
    color = colors[i]
    p,  = ax.plot(data.week,
                  data.points,
                  c = color,
                  marker = 'o',
                  linestyle='-.',
                  label=name,
                  markersize=10)
    y_max = max(y_max,
                data.points.max())
    lines.append(p)
    

# Set Axis limits
ax.set_xlim(0.5, 17.5)
ax.set_ylim(0, y_max + 5)

# Set Legent from Lines
ax.legend(lines, [l.get_label() for l in lines])

plt.grid(True)
plt.show()