def createDs(func):
outputMax = -np.inf
outputMin = np.inf
global outputMax
global outputMin
ds = SupervisedDataSet(2, 1)
for j in range(N):
for i in range(N):
input = [i, j]
output = func(j, i) # math.sqrt(i**2+j**2)
ds.appendLinked(input, output)
if output > outputMax:
outputMax = output
if outputMin > output:
outputMin = output
ds.outputMax = outputMax
ds.outputMin = outputMin
return ds
def createDs(func):
outputMax = -np.inf
outputMin = np.inf
global outputMax
global outputMin
ds = SupervisedDataSet( 1, 1 )
#for j in range(N):
rs = []
for i in range(N):
rs.append(random.random())
rs.sort()
for r in rs:
input = r#[i]
output = nonLinearFunc(r)
ds.appendLinked(input , output)
if output > outputMax:
outputMax = output
if outputMin > output:
outputMin = output
ds.outputMax = outputMax
ds.outputMin = outputMin
return ds
