# Path: examples/context.py



import matplotlib
import numpy as np
import pdb
import matplotlib.pylab as plt
from scipy import special
from .context import vfe, compute_kernel, compute_psi_weave
print "importing stuff..."
matplotlib.use('Agg')

jitter = 1e-5


class AutoSGPR(object):

    def __init__(self, X_train, Y_train, M):
        self.N_train = Y_train.shape[0]
        self.Dout = Y_train.shape[1]
        self.Din = Y_train.shape[1]
        self.M = M
        models = []
        for i in range(self.Dout):
            if i == 0:
                X_train_i = X_train
            else:
                X_train_i = np.hstack(
                    (X_train, Y_train[:, :i].reshape((self.N_train, i))))
            y_train_i = Y_train[:, [i]]

# Path: examples/context.py



# Path: examples/gpr_autoreg_example.py
import matplotlib
import numpy as np
import pdb
import matplotlib.pylab as plt
from scipy import special
from .context import vfe, compute_kernel, compute_psi_weave

print "importing stuff..."
matplotlib.use('Agg')

jitter = 1e-5


class AutoSGPR(object):

    def __init__(self, X_train, Y_train, M):
        self.N_train = Y_train.shape[0]
        self.Dout = Y_train.shape[1]
        self.Din = Y_train.shape[1]
        self.M = M
        models = []
        for i in range(self.Dout):
            if i == 0:
                X_train_i = X_train
            else:
                X_train_i = np.hstack(
                    (X_train, Y_train[:, :i].reshape((self.N_train, i))))
            y_train_i = Y_train[:, [i]]

            model_i = vfe.SGPR(X_train_i, y_train_i, M)