def __init__(self, kernel=stheno.EQ(), **kw_args):
self.gp = stheno.GP(kernel, graph=stheno.Graph())
DataGenerator.__init__(self, **kw_args)
Returns:
number: `x` rounded to the nearest above multiple of `multiple`.
"""
if x % multiple == 0:
return x
else:
return x + multiple - x % multiple
if __name__ == "__main__":
# example data
from data.GP.GP_data_generator import MultiClassGPGenerator
import stheno
train_data = MultiClassGPGenerator(
[stheno.EQ(), stheno.EQ().periodic(1)],
0.5,
kernel_names=["EQ", "Periodic"],
batch_size=64,
num_tasks=10)
task, label = train_data.generate_task()
x_context = task["x_context"]
y_context = task["y_context"]
x_target = task["x"]
y_target = task["y"]
learn_length_scale = True
points_per_unit = 10
type_CNN = "UNet"
num_input_channels = 1
num_output_channels = 2
import stheno
import numpy as np
import matplotlib.pyplot as plt
if __name__ == "__main__":
kernels = [stheno.EQ().stretch(1) * 0.1, stheno.EQ().stretch(0.1) * 1]
gps = [stheno.GP(kernel) for kernel in kernels]
labels = [""]
num_samples = 5
step = 0.01
x = np.arange(-2,2 + step, step)
dir_plot = "../figures/write_up/gps/gp.svg"
for i in range(len(gps)):
for j in range(num_samples):
y = gps[i](x).sample()
plt.plot(x,y,alpha=0.5,color="b")
plt.ylim([-4,4])
plt.xlabel("x",fontsize=15)
plt.ylabel("y",fontsize=15)
dir_plot_local = dir_plot[:-4] + str(i) + dir_plot[-4:]
plt.savefig(dir_plot_local)
plt.close()