Eugine Kang kangeugine

## mma-tracking-data-example.csv

          
            Frame
            Round
            Time [s]
            Body_x
             Body_y
             Fist_x
             Fist_y
             Fist_z
             Knee_x
             Knee_y
             Knee_z

            
              11000
               2
               150
               ??
               ??
               ??
               ??
               ??
               ??
               ??
               ??

            
              11025
               2
               151
               ??
               ??
               ??
               ??
               ??
               ??
               ??
               ??

            
              11050
               2
               152
               ??
               ??
               ??
               ??
               ??
               ??
               ??
               ??

## soccer-tracking-data-example.csv

          
            Frame
            Period
            Time [s]
            Home_11_x
            Home_11_y
            Home_1_x
            Home_1_y
            ball_x
            ball_y

            
              1
              1
              0.04
              -52.913
              1.198
              -18.393
              -10.418
              -4.799
              7.677

            
              2
              1
              0.08
              -52.898
              1.198
              -18.393
              -10.418
              -0.376
              6.353

            
              3
              1
              0.12
              -52.879
              1.198
              -18.393
              -10.418
              3.938
              5.061

            
              4
              1
              0.16
              -52.871
              1.198
              -18.420
              -10.415
              5.666
              5.282

            
              5
              1
              0.2
              -52.863
              1.198
              -18.447
              -10.382
              5.842
              6.412

## knapsack-ip2.py
from pulp import *

player = [str(i) for i in range(data.shape[0])]
point = {str(i): data['Points'][i] for i in range(data.shape[0])}
cost = {str(i): data['Cost'][i] for i in range(data.shape[0])}
gk = {str(i): 1 if data['Position'][i] == 'GK' else 0 for i in range(data.shape[0])}
defe = {str(i): 1 if data['Position'][i] == 'DEF' else 0 for i in range(data.shape[0])}
mid = {str(i): 1 if data['Position'][i] == 'MID' else 0 for i in range(data.shape[0])}
stri = {str(i): 1 if data['Position'][i] == 'STR' else 0 for i in range(data.shape[0])}
xi = {str(i): 1 for i in range(data.shape[0])}

## knapsack-ip.py
from pulp import *

player = [str(i) for i in range(data.shape[0])]
point = {str(i): data['Points'][i] for i in range(data.shape[0])}
cost = {str(i): data['Cost'][i] for i in range(data.shape[0])}
gk = {str(i): 1 if data['Position'][i] == 'GK' else 0 for i in range(data.shape[0])}
defe = {str(i): 1 if data['Position'][i] == 'DEF' else 0 for i in range(data.shape[0])}
mid = {str(i): 1 if data['Position'][i] == 'MID' else 0 for i in range(data.shape[0])}
stri = {str(i): 1 if data['Position'][i] == 'STR' else 0 for i in range(data.shape[0])}
xi = {str(i): 1 for i in range(data.shape[0])}

## knapsack-lp.py
from scipy.optimize import linprog

points = data['Points']
cost = data['Cost']
gk   = data['Position'].apply(lambda x: 1 if x == 'GK' else 0)
defe = data['Position'].apply(lambda x: 1 if x == 'DEF' else 0)
mid  = data['Position'].apply(lambda x: 1 if x == 'MID' else 0)
stri = data['Position'].apply(lambda x: 1 if x == 'STR' else 0)
xi   = np.ones(data.shape[0])

## knapsack-dp-example.py
# Example
val = [60, 100, 120, 120]
wt = [10, 20, 30, 20]
W = 50
n = len(val)
K = knapSack(W, wt, val, n)
ix = knapSackIndex(W, wt, val, n ,K)

print("Max value:{}, with items:{}".format(K[-1][-1], str(ix)))
# Max value:280, with items:[3, 1, 0]

## knapsack-dp.py
def knapSack(W, wt, val, n):
    K = [[0 for x in range(W+1)] for x in range(n+1)]
    for i in range(n+1):
        for w in range(W+1):
            if i==0 or w==0:
                K[i][w] = 0
            elif wt[i-1] <= w:
                K[i][w] = max(val[i-1] + K[i-1][w-wt[i-1]], K[i-1][w])
            else:
                K[i][w] = K[i-1][w]

## fantasy-football-randomwalk.py
def random_walk(n):
    return np.random.rand(11) * n

def to_int(x):
    # gives players at each end equal probability to be picked
    # 0.5 - 1.5 -> 1
    # 0.0 - 0.5 -> 0 (half the probability)
    return (x - 0.5).astype(int)

def objective(x):

## fantasy-football-constraints-3.py
def constraint_all(x):
    test = [constraint_cost(x) >= 0,
            constraint_unique(x) == 0,
            constraint_gk(x) == 0,
            constraint_def_3(x) >= 0,
            constraint_def_5(x) >= 0,
            constraint_mid_3(x) >= 0,
            constraint_mid_5(x) >= 0,
            constraint_str_1(x) >= 0,
            constraint_str_3(x) >= 0]

## fantasy-football-constraints-2.py
def constraint_unique(x):
    n1 = x.size
    n2 = np.unique(to_int(x)).size
    return n1 - n2
# if constraint_unique(x) == 0, test passed
Frame	Round	Time [s]	Body_x	Body_y	Fist_x	Fist_y	Fist_z	Knee_x	Knee_y	Knee_z
11000	2	150	??	??	??	??	??	??	??	??
11025	2	151	??	??	??	??	??	??	??	??
11050	2	152	??	??	??	??	??	??	??	??
Frame	Period	Time [s]	Home_11_x	Home_11_y	Home_1_x	Home_1_y	ball_x	ball_y
1	1	0.04	-52.913	1.198	-18.393	-10.418	-4.799	7.677
2	1	0.08	-52.898	1.198	-18.393	-10.418	-0.376	6.353
3	1	0.12	-52.879	1.198	-18.393	-10.418	3.938	5.061
4	1	0.16	-52.871	1.198	-18.420	-10.415	5.666	5.282
5	1	0.2	-52.863	1.198	-18.447	-10.382	5.842	6.412
	from pulp import *

	player = [str(i) for i in range(data.shape[0])]
	point = {str(i): data['Points'][i] for i in range(data.shape[0])}
	cost = {str(i): data['Cost'][i] for i in range(data.shape[0])}
	gk = {str(i): 1 if data['Position'][i] == 'GK' else 0 for i in range(data.shape[0])}
	defe = {str(i): 1 if data['Position'][i] == 'DEF' else 0 for i in range(data.shape[0])}
	mid = {str(i): 1 if data['Position'][i] == 'MID' else 0 for i in range(data.shape[0])}
	stri = {str(i): 1 if data['Position'][i] == 'STR' else 0 for i in range(data.shape[0])}
	xi = {str(i): 1 for i in range(data.shape[0])}
	from scipy.optimize import linprog

	points = data['Points']
	cost = data['Cost']
	gk = data['Position'].apply(lambda x: 1 if x == 'GK' else 0)
	defe = data['Position'].apply(lambda x: 1 if x == 'DEF' else 0)
	mid = data['Position'].apply(lambda x: 1 if x == 'MID' else 0)
	stri = data['Position'].apply(lambda x: 1 if x == 'STR' else 0)
	xi = np.ones(data.shape[0])
	# Example
	val = [60, 100, 120, 120]
	wt = [10, 20, 30, 20]
	W = 50
	n = len(val)
	K = knapSack(W, wt, val, n)
	ix = knapSackIndex(W, wt, val, n ,K)

	print("Max value:{}, with items:{}".format(K[-1][-1], str(ix)))
	# Max value:280, with items:[3, 1, 0]
	def knapSack(W, wt, val, n):
	K = [[0 for x in range(W+1)] for x in range(n+1)]
	for i in range(n+1):
	for w in range(W+1):
	if i==0 or w==0:
	K[i][w] = 0
	elif wt[i-1] <= w:
	K[i][w] = max(val[i-1] + K[i-1][w-wt[i-1]], K[i-1][w])
	else:
	K[i][w] = K[i-1][w]
	def random_walk(n):
	return np.random.rand(11) * n

	def to_int(x):
	# gives players at each end equal probability to be picked
	# 0.5 - 1.5 -> 1
	# 0.0 - 0.5 -> 0 (half the probability)
	return (x - 0.5).astype(int)

	def objective(x):
	def constraint_all(x):
	test = [constraint_cost(x) >= 0,
	constraint_unique(x) == 0,
	constraint_gk(x) == 0,
	constraint_def_3(x) >= 0,
	constraint_def_5(x) >= 0,
	constraint_mid_3(x) >= 0,
	constraint_mid_5(x) >= 0,
	constraint_str_1(x) >= 0,
	constraint_str_3(x) >= 0]
	def constraint_unique(x):
	n1 = x.size
	n2 = np.unique(to_int(x)).size
	return n1 - n2
	# if constraint_unique(x) == 0, test passed