def getData(X_train, fn, noisepct):
"""
TODO use eval or something to make this less noisy
"""
from apprentice import testData
if fn == "f1":
Y_train = [testData.f1(x) for x in X_train]
elif fn == "f2":
Y_train = [testData.f2(x) for x in X_train]
elif fn == "f3":
Y_train = [testData.f3(x) for x in X_train]
elif fn == "f4":
Y_train = [testData.f4(x) for x in X_train]
elif fn == "f5":
Y_train = [testData.f5(x) for x in X_train]
elif fn == "f6":
Y_train = [testData.f6(x) for x in X_train]
elif fn == "f7":
Y_train = [testData.f7(x) for x in X_train]
elif fn == "f8":
Y_train = [testData.f8(x) for x in X_train]
elif fn == "f9":
Y_train = [testData.f9(x) for x in X_train]
elif fn == "f10":
Y_train = [testData.f10(x) for x in X_train]
elif fn == "f12":
Y_train = [testData.f12(x) for x in X_train]
elif fn == "f13":
Y_train = [testData.f13(x) for x in X_train]
elif fn == "f14":
Y_train = [testData.f14(x) for x in X_train]
elif fn == "f15":
Y_train = [testData.f15(x) for x in X_train]
elif fn == "f16":
Y_train = [testData.f16(x) for x in X_train]
elif fn == "f17":
Y_train = [testData.f17(x) for x in X_train]
elif fn == "f18":
Y_train = [testData.f18(x) for x in X_train]
elif fn == "f19":
Y_train = [testData.f19(x) for x in X_train]
elif fn == "f20":
Y_train = [testData.f20(x) for x in X_train]
elif fn == "f21":
Y_train = [testData.f21(x) for x in X_train]
elif fn == "f22":
Y_train = [testData.f22(x) for x in X_train]
elif fn == "f23":
Y_train = [testData.f23(x) for x in X_train]
elif fn == "f24":
Y_train = [testData.f24(x) for x in X_train]
else:
raise Exception("function {} not implemented, exiting".format(fn))
# stdnormalnoise = np.zeros(shape = (len(Y_train)), dtype =np.float64)
# for i in range(len(Y_train)):
# stdnormalnoise[i] = np.random.normal(0,1)
# return np.atleast_2d(np.array(Y_train)*(1+ noisepct*stdnormalnoise))
return Y_train
def getData(X_train, fn, noisepct):
"""
TODO use eval or something to make this less noisy
"""
from apprentice import testData
if fn==1:
Y_train = [testData.f1(x) for x in X_train]
elif fn==2:
Y_train = [testData.f2(x) for x in X_train]
elif fn==3:
Y_train = [testData.f3(x) for x in X_train]
elif fn==4:
Y_train = [testData.f4(x) for x in X_train]
elif fn==5:
Y_train = [testData.f5(x) for x in X_train]
elif fn==6:
Y_train = [testData.f6(x) for x in X_train]
elif fn==7:
Y_train = [testData.f7(x) for x in X_train]
elif fn==8:
Y_train = [testData.f8(x) for x in X_train]
elif fn==9:
Y_train = [testData.f9(x) for x in X_train]
elif fn==10:
Y_train = [testData.f10(x) for x in X_train]
elif fn==12:
Y_train = [testData.f12(x) for x in X_train]
elif fn==13:
Y_train = [testData.f13(x) for x in X_train]
elif fn==14:
Y_train = [testData.f14(x) for x in X_train]
elif fn==15:
Y_train = [testData.f15(x) for x in X_train]
elif fn==16:
Y_train = [testData.f16(x) for x in X_train]
elif fn==17:
Y_train = [testData.f17(x) for x in X_train]
elif fn==18:
Y_train = [testData.f18(x) for x in X_train]
elif fn==19:
Y_train = [testData.f19(x) for x in X_train]
elif fn==20:
Y_train = [testData.f20(x) for x in X_train]
elif fn==21:
Y_train = [testData.f21(x) for x in X_train]
elif fn==22:
Y_train = [testData.f22(x) for x in X_train]
elif fn==23:
Y_train = [testData.f23(x) for x in X_train]
elif fn==24:
Y_train = [testData.f24(x) for x in X_train]
else:
raise Exception("function {} not implemented, exiting".format(fn))
stdnormalnoise = np.zeros(shape = (len(Y_train)), dtype =np.float64)
for i in range(len(Y_train)):
stdnormalnoise[i] = np.random.normal(0,1)
return np.atleast_2d(np.array(Y_train)*(1+ noisepct*stdnormalnoise))
def getData(X_train, fn, noisepct):
"""
TODO use eval or something to make this less noisy
"""
from apprentice import testData
if fn == "f1":
Y_train = [testData.f1(x) for x in X_train]
elif fn == "f2":
Y_train = [testData.f2(x) for x in X_train]
elif fn == "f3":
Y_train = [testData.f3(x) for x in X_train]
elif fn == "f4":
Y_train = [testData.f4(x) for x in X_train]
elif fn == "f5":
Y_train = [testData.f5(x) for x in X_train]
elif fn == "f6":
Y_train = [testData.f6(x) for x in X_train]
elif fn == "f7":
Y_train = [testData.f7(x) for x in X_train]
elif fn == "f8":
Y_train = [testData.f8(x) for x in X_train]
elif fn == "f9":
Y_train = [testData.f9(x) for x in X_train]
elif fn == "f10":
Y_train = [testData.f10(x) for x in X_train]
elif fn == "f12":
Y_train = [testData.f12(x) for x in X_train]
elif fn == "f13":
Y_train = [testData.f13(x) for x in X_train]
elif fn == "f14":
Y_train = [testData.f14(x) for x in X_train]
elif fn == "f15":
Y_train = [testData.f15(x) for x in X_train]
elif fn == "f16":
Y_train = [testData.f16(x) for x in X_train]
elif fn == "f17":
Y_train = [testData.f17(x) for x in X_train]
elif fn == "f18":
Y_train = [testData.f18(x) for x in X_train]
elif fn == "f19":
Y_train = [testData.f19(x) for x in X_train]
elif fn == "f20":
Y_train = [testData.f20(x) for x in X_train]
elif fn == "f21":
Y_train = [testData.f21(x) for x in X_train]
elif fn == "f22":
Y_train = [testData.f22(x) for x in X_train]
elif fn == "f23":
Y_train = [testData.f23(x) for x in X_train]
elif fn == "f24":
Y_train = [testData.f24(x) for x in X_train]
else:
raise Exception("function {} not implemented, exiting".format(fn))
return Y_train
def getData(X_train, fn, noisepct, seed):
"""
TODO use eval or something to make this less noisy
"""
from apprentice import testData
if fn == "f18":
Y_train = [testData.f18(x) for x in X_train]
elif fn == "f20":
Y_train = [testData.f20(x) for x in X_train]
else:
raise Exception("function {} not implemented, exiting".format(fn))
np.random.seed(seed)
stdnormalnoise = np.zeros(shape=(len(Y_train)), dtype=np.float64)
for i in range(len(Y_train)):
stdnormalnoise[i] = np.random.normal(0, 1)
# return Y_train
return np.atleast_2d(
np.array(Y_train) * (1 + noisepct * stdnormalnoise))