Parameter space coverage 3D graphs

See the parameter-space-coverage notebook for more information.



In [1]:

    
import random

import numpy as np
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.offline as offline

offline.init_notebook_mode(connected=True)

Set the sample size:



In [2]:

    
sample_size = 1000



In [3]:

    
def plot_3d_scatter(X, Y, Z, filename):
    trace = go.Scatter3d(
        x=X,
        y=Y,
        z=Z,
        mode='markers',
        marker=dict(
            size=4,
            #line=dict(
            #    color='rgba(217, 217, 217, 0.14)',
            #    width=0.5
            #),
            opacity=0.5
        )
    )
    data = [trace]
    layout = go.Layout(
        margin=dict(
            l=0,
            r=0,
            b=0,
            t=0
        )
    )
    fig = go.Figure(data=data, layout=layout)
    return py.iplot(fig, filename=filename)

Uniform



In [4]:

    
X = [random.uniform(0, 1) for i in range(sample_size)]
Y = [random.uniform(0, 1) for i in range(sample_size)]
Z = [random.uniform(0, 1) for i in range(sample_size)]

plot_3d_scatter(X, Y, Z, 'paramspace-uniform')









    Out[4]:

Stepped

Set the step size. I'm using a larger value than in the parameter-space-coverage notebook (0.05 compared to 0.01) so that the quantization effect is more visible in 3 dimensions.



In [5]:

    
step_size = 0.05



In [6]:

    
all_points = []
for x in np.arange(0, 1, step_size):
    for y in np.arange(0, 1, step_size):
        for z in np.arange(0, 1, step_size):
            all_points.append((x, y, z))

print("Number of parameter value combinations: {:,}".format(len(all_points)))

sample = random.sample(all_points, sample_size)

X, Y, Z = zip(*sample) # unzip sample

plot_3d_scatter(X, Y, Z, 'paramspace-stepped')









    



Number of parameter value combinations: 8,000






    Out[6]: