Drawing 3D graph and using imshow

[Notice] [visualization_practice_3D]

drawing 3D graph and imshow

from mpl_toolkits import mplot3d
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

rough sketch

fig = plt.figure()
ax = plt.axes(projection = '3d')

3D plot

ax = plt.axes(projection='3d')

z = np.linspace(0, 15, 1000)
x = np.sin(z)
y = np.cos(z)

ax.plot(x, y, z, 'gray')
plt.show()

ax = plt.axes(projection='3d')

sample_size = 100
x = np.cumsum(np.random.normal(0, 1, sample_size))
y = np.cumsum(np.random.normal(0, 1, sample_size))
z = np.cumsum(np.random.normal(0, 1, sample_size))

ax.plot3D(x, y, z, alpha = 0.6, marker = 'o')


plt.title("ax.plot")
plt.show()

3D-scatter

fig = plt.figure(figsize=(10, 5))
ax = fig.add_subplot(111, projection='3d') # Axe3D object

sample_size = 500

x = np.cumsum(np.random.normal(0, 5, sample_size))
y = np.cumsum(np.random.normal(0, 5, sample_size))
z = np.cumsum(np.random.normal(0, 5, sample_size))

ax.scatter(x, y, z, c = z, s = 20, alpha = 0.5, cmap = 'Greens')


plt.title("ax.scatter")
plt.show()

Contour3D

x = np.linspace(-6, 6, 30)
y = np.linspace(-6, 6, 30)
x, y = np.meshgrid(x, y)

z = np.sin(np.sqrt(x**2 + y**2))

fig = plt.figure(figsize=(12, 6))
ax = plt.axes(projection='3d')

ax.contour3D(x, y, z, 20, cmap='Reds')

plt.title("ax.contour3D")
plt.show()

imshow

• Similar to image data, ‘imshow’ is used to visualize two-dimensional data with rows and columns.

from sklearn.datasets import load_digits

digits = load_digits()
X = digits.images[:10]
X[0]

array([[ 0.,  0.,  5., 13.,  9.,  1.,  0.,  0.],
       [ 0.,  0., 13., 15., 10., 15.,  5.,  0.],
       [ 0.,  3., 15.,  2.,  0., 11.,  8.,  0.],
       [ 0.,  4., 12.,  0.,  0.,  8.,  8.,  0.],
       [ 0.,  5.,  8.,  0.,  0.,  9.,  8.,  0.],
       [ 0.,  4., 11.,  0.,  1., 12.,  7.,  0.],
       [ 0.,  2., 14.,  5., 10., 12.,  0.,  0.],
       [ 0.,  0.,  6., 13., 10.,  0.,  0.,  0.]])

• load_digits consists of an array with values from 0 to 16.

• One array is expressed in an 8 X 8 array.

• Numbers are from 0 to 9.

fig, axes = plt.subplots(nrows=2, ncols=5, sharex=True, figsize=(12, 6), sharey=True)

for i in range(10):
    axes[i//5][i%5].imshow(X[i], cmap = 'Blues')
    axes[i//5][i%5].set_title(str(i), fontsize=20)
    
plt.tight_layout()
plt.show()

References

Matplotlib Document