mdn_harder_data.py

import numpy as np

# the function
def f_of_x(X, w):
    n,d = X.shape
    X_dot_w = np.dot(X,w)
    y = np.zeros(n)
    # the inner product randomly goes through a sin
    # or a cos
    cos_flag = np.random.randn(n) < 0.0
    sin_flag = ~cos_flag
    y[cos_flag] = np.cos(X_dot_w[cos_flag])
    y[sin_flag] = np.sin(X_dot_w[sin_flag])
    return y

# generate some simulated data
n = 2500
d = 1
w = np.random.rand(d)
x_train = np.random.randn(n, d)
y_train = f_of_x(x_train, w)
x_test = np.random.randn(n, d)
y_test = f_of_x(x_test, w)