def straightSampleTrainTestVal(data):
# number of games in data set
N = len(data.X)
# round up counts for train and validate
Ntrain = int(N*0.6) + 1
Nval = int(N*0.8) + 1
# initialize train, test, and validate sets
train = dataSet()
test = dataSet()
validate = dataSet()
# get variable sets
trainVars = vars(train).values()
testVars = vars(test).values()
valVars = vars(validate).values()
dataVars = vars(data).values()
# cycle through all variables in the dataset
for i, var in enumerate(dataVars):
# copy appropriate variables
trainVars[i] += var[:Ntrain]
valVars[i] += var[Ntrain:Nval]
testVars[i] += var[Nval:]
return train, test, validate
def randomSampleTrainTestVal(data):
# number of games in data set, sample initial indexes
N = len(data.X)
samples = random.sample(range(N),N)
# round up counts for train and validate
Ntrain = int(N*0.6) + 1
Nval = int(N*0.8) + 1
# initialize train, test, and validate sets
train = dataSet()
test = dataSet()
validate = dataSet()
# get variable sets
trainVars = vars(train).values()
testVars = vars(test).values()
valVars = vars(validate).values()
dataVars = vars(data).values()
# cycle through all variables in the dataset
for i, var in enumerate(dataVars):
mangled_var = var[samples]
# copy appropriate variables
trainVars[i] += mangled_var[:Ntrain]
valVars[i] += mangled_var[Ntrain:Nval]
testVars[i] += mangled_var[Nval:]
return train, test, validate
def randomSampleTrainTestVal(data):
# number of games in data set, sample initial indexes
N = len(data.X)
samples = random.sample(range(N), N)
# round up counts for train and validate
Ntrain = int(N * 0.6) + 1
Nval = int(N * 0.8) + 1
# initialize train, test, and validate sets
train = dataSet()
test = dataSet()
validate = dataSet()
# get variable sets
trainVars = vars(train).values()
testVars = vars(test).values()
valVars = vars(validate).values()
dataVars = vars(data).values()
# cycle through all variables in the dataset
for i, var in enumerate(dataVars):
mangled_var = var[samples]
# copy appropriate variables
trainVars[i] += mangled_var[:Ntrain]
valVars[i] += mangled_var[Ntrain:Nval]
testVars[i] += mangled_var[Nval:]
return train, test, validate
def straightSampleTrainTestVal(data):
# number of games in data set
N = len(data.X)
# round up counts for train and validate
Ntrain = int(N * 0.6) + 1
Nval = int(N * 0.8) + 1
# initialize train, test, and validate sets
train = dataSet()
test = dataSet()
validate = dataSet()
# get variable sets
trainVars = vars(train).values()
testVars = vars(test).values()
valVars = vars(validate).values()
dataVars = vars(data).values()
# cycle through all variables in the dataset
for i, var in enumerate(dataVars):
# copy appropriate variables
trainVars[i] += var[:Ntrain]
valVars[i] += var[Ntrain:Nval]
testVars[i] += var[Nval:]
return train, test, validate
def sampleTrainTestValByYear(data):
# number of games in data set
N = len(data.X)
# initialize train, test, and validate sets
train = dataSet()
test = dataSet()
validate = dataSet()
# get variable sets
trainVars = vars(train).values()
testVars = vars(test).values()
valVars = vars(validate).values()
dataVars = vars(data).values()
# cycle through all games
for n in range(N):
# check year for training
if data.yearList[n] < 2012:
# copy all variables from that game to training set
for i, var in enumerate(dataVars):
trainVars[i].append(var[n])
# check year for test set (2013)
elif data.yearList[n] == 2013:
# copy all variables from that game to validation set
for i, var in enumerate(dataVars):
testVars[i].append(var[n])
# remaining data is validation set
else:
# copy all variables from that game to test set
for i, var in enumerate(dataVars):
valVars[i].append(var[n])
return train, test, validate
def sampleTrainTestValByYear(data):
# number of games in data set
N = len(data.X)
# initialize train, test, and validate sets
train = dataSet()
test = dataSet()
validate = dataSet()
# get variable sets
trainVars = vars(train).values()
testVars = vars(test).values()
valVars = vars(validate).values()
dataVars = vars(data).values()
# cycle through all games
for n in range(N):
# check year for training
if data.yearList[n] < 2012:
# copy all variables from that game to training set
for i, var in enumerate(dataVars):
trainVars[i].append(var[n])
# check year for test set (2013)
elif data.yearList[n] == 2013:
# copy all variables from that game to validation set
for i, var in enumerate(dataVars):
testVars[i].append(var[n])
# remaining data is validation set
else:
# copy all variables from that game to test set
for i, var in enumerate(dataVars):
valVars[i].append(var[n])
return train, test, validate
