#!/usr/bin/env python3
#spencer jackson
#find games that could be higher ranked if they just got more ratings
import bgg_get_game_stats as bggstats
import bgg_top_ranked as bggtr
import numpy as np
import matplotlib.pyplot as matplot
import regression as reg
top = bggtr.getTopRankedGames(100)
stats = bggstats.getStatsSlowly(top)
filterwidth = 46
smoothwidth = 5 #keep this odd
nvotes = stats[:,bggstats.voters_col].astype(np.int)
print("med" ,np.median(nvotes),"mean", np.mean(nvotes))
exit()
l = stats.shape[0]
#this could maybe be done with broadcasting but I'd have to look it up
medvotes = np.r_[:l-filterwidth]
for i in range(l-filterwidth):
medvotes[i] = np.median(nvotes[i:i+filterwidth])
size = l-filterwidth - smoothwidth +1
smoothvotes = np.r_[:size]
#another pass to smooth it further
for i in range(size):
smoothvotes[i] = np.mean(medvotes[i:i+smoothwidth])
import bgg_get_game_stats as bggstats
import bgg_most_played as bggmp
import numpy as np
import matplotlib.pyplot as matplot
ntop = 10
monthwindow = 12
year = 20
month = 4
unpub = 18291
top = bggmp.getTopPlayedGamesTill(year, month, monthwindow, 10) #top played
top = top[top[:, bggmp.gameid_col] != unpub, :] #exclude unpublished prototype
idlist = top[:, bggmp.gameid_col]
stats = bggstats.getStatsSlowly(idlist)
#top and stats should be aligned so the id cols match
print(top.shape, stats.shape)
print(type(top[0, bggmp.gameid_col])) #int
print(type(stats[0, bggstats.gameid_col])) #str
for i in range(top.shape[0]):
#if top[i, bggmp.gameid_col] != stats[i, bggstats.gameid_col]:
a = int(top[i, bggmp.gameid_col])
b = int(stats[i, bggstats.gameid_col])
# if int(top[i, bggmp.gameid_col]) != stats[i, bggstats.gameid_col]:
if a != b:
print(i, a, b)
print(i, int(top[i, bggmp.gameid_col]), stats[i, bggstats.gameid_col])
print("oh no! The fetched data doesn't match!")