self.nn = tups[0:self.k]
return self.nn
class NearestNeighboursVP(NearestNeighboursAbstract):
def __init__(self,windows,k=100,weighted=False,dist = custom_dtw_distance):
self.vptree = VPTree(windows,dist)
self.k = k
self.weighted = weighted
def search_k_nearest_neighbours(self,window,log=True):
self.nn = get_nearest_neighbors(self.vptree,window,self.k)
return self.nn
if __name__ == '__main__':
trainset = getAllWindows(5,10)
testset = getAllWindows(0, 3)
knn = NearestNeighboursBF(trainset,100,True)
cnt = 0
for window in testset:
if window.is_goal() and cnt < 6:
t0 = pc()
result = knn.predict_shotprobgoalprob(window,log=True)
print(result)
print(window.is_defensive_error_shot())
print(pc()-t0, "seconds elapsed")
fig,ax = plt.subplots(5,5)
window.plot(ax[0,0],False,False,True)
for i in range(1,25):
#print(knn.nn[i][0])
knn.nn[i][1].plot(ax[i//5,i%5],False,False,True)
'''
Created on 16 Mar 2016
@author: Temp
'''
from eav.window import getAllWindows
from eav.event import Event
from db.prozoneDB import DB
import matplotlib.pyplot as plt
import numpy as np
import tools.logger as logger
c = DB.c
window = getAllWindows(0, 1)[1000]
virtual = window.events[0:21]
#for event in window.events[0:20]:
#print(event.to_string())
time = window.get_time()
matchid = window.matchhalf.matchid
halfid = window.matchhalf.halfid
qry = """
select locationx, locationy,eventname,duel,teamid,idactor1,position,
eventid,eventtime
from eventstream
where matchid = ? and halfid = ?
and eventtime > ? and eventtime < ? + 10000
"""
rows = c.execute(qry,(matchid,halfid,time,time)).fetchall()
#for row in rows: