Hands-On Meta Learning with Python

Generating data points

Now we define a function called sample_points for generating (x,y) pairs. It takes the parameter k as input, which implies the number of (x,y) pairs we want to sample:

def sample_points(k):        num_points = 100        #amplitude    amplitude = np.random.uniform(low=0.1, high=5.0)        #phase    phase = np.random.uniform(low=0, high=np.pi)    x = np.linspace(-5, 5, num_points)    #y = a*sin(x+b)    y = amplitude * np.sin(x + phase)        #sample k data points    sample = np.random.choice(np.arange(num_points), size=k)        return (x[sample], y[sample])