isotrackTrainRegressor.py File Reference

Go to the source code of this file.

Namespaces
	isotrackTrainRegressor

Functions
def	isotrackTrainRegressor.fac0
def	isotrackTrainRegressor.fac1
def	isotrackTrainRegressor.fac2
def	isotrackTrainRegressor.propweights

Variables
tuple	isotrackTrainRegressor._ = plt.plot(lims, lims)
list	isotrackTrainRegressor.a0 = [0.973, 0.998, 0.992, 0.965 ]
	marinas correction form More...
list	isotrackTrainRegressor.a1 = [0, -0.318, -0.261, -0.406]
list	isotrackTrainRegressor.a2 = [0, 0, 0.047, 0.089]
list	isotrackTrainRegressor.cols_to_minmax = ['t_delta', 't_hmaxNearP','t_emaxNearP', 't_hAnnular', 't_eAnnular','t_pt','t_nVtx','t_ieta','t_eHcal10', 't_eHcal30','t_rhoh','t_eHcal_x']
	isotrackTrainRegressor.data = df.values
tuple	isotrackTrainRegressor.df = pd.read_pickle(fName)
tuple	isotrackTrainRegressor.dop = (X_test[:,16]/X_test[:,13])
tuple	isotrackTrainRegressor.eop = (X_test[:,15]/X_test[:,13])
tuple	isotrackTrainRegressor.fName = parser.parse_args()
tuple	isotrackTrainRegressor.history = model.fit(X_train,Y_train , batch_size=5000, epochs=100, validation_split=0.2, verbose=1,sample_weight=propweights(Y_train))
list	isotrackTrainRegressor.keya = []
list	isotrackTrainRegressor.lims = [0, 200]
list	isotrackTrainRegressor.marinascorr = X_test[:,15]
list	isotrackTrainRegressor.maxa = []
tuple	isotrackTrainRegressor.mcorrval = vec0(abs(X_test[:,17]))
tuple	isotrackTrainRegressor.meany = np.mean(Y_train)
list	isotrackTrainRegressor.mina = []
tuple	isotrackTrainRegressor.model = Sequential()
tuple	isotrackTrainRegressor.modv = parser.parse_args()
int	isotrackTrainRegressor.ntest = 20000
tuple	isotrackTrainRegressor.parser = argparse.ArgumentParser()
list	isotrackTrainRegressor.pmom = X_test[:,13]
tuple	isotrackTrainRegressor.preds = model.predict(X_test[:,0:12])
tuple	isotrackTrainRegressor.RMS = keras.optimizers.RMSprop(lr=0.001, rho=0.9)
tuple	isotrackTrainRegressor.stdy = np.std(Y_train)
list	isotrackTrainRegressor.targets = data[:,12]
list	isotrackTrainRegressor.testindx = data.shape[0]
list	isotrackTrainRegressor.uncorrected = X_test[:,15]
tuple	isotrackTrainRegressor.vec0 = np.vectorize(fac0)
tuple	isotrackTrainRegressor.vec1 = np.vectorize(fac1)
tuple	isotrackTrainRegressor.vec2 = np.vectorize(fac2)
list	isotrackTrainRegressor.X_test = data[testindx:,:]
list	isotrackTrainRegressor.X_train = data[:testindx,0:12]
list	isotrackTrainRegressor.Y_train = data[:testindx,12]