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"""

===================

3D box surface plot

===================

Given data on a gridded volume ``X``, ``Y``, ``Z``, this example plots the

data values on the volume surfaces.

The strategy is to select the data from each surface and plot

contours separately using `.axes3d.Axes3D.contourf` with appropriate

parameters *zdir* and *offset*.

"""

import matplotlib.pyplot as plt

import numpy as np

# Define dimensions

Nx, Ny, Nz = 100, 300, 500

X, Y, Z = np.meshgrid(np.arange(Nx), np.arange(Ny), -np.arange(Nz))

# Create fake data

data = (((X+100)**2 + (Y-20)**2 + 2*Z)/1000+1)

kw = {

'vmin': data.min(),

'vmax': data.max(),

'levels': np.linspace(data.min(), data.max(), 10),

}

# Create a figure with 3D ax

fig = plt.figure(figsize=(5, 4))

ax = fig.add_subplot(111, projection='3d')

# Plot contour surfaces

_ = ax.contourf(

X[:, :, 0], Y[:, :, 0], data[:, :, 0],

zdir='z', offset=0, **kw

)

_ = ax.contourf(

X[0, :, :], data[0, :, :], Z[0, :, :],

zdir='y', offset=0, **kw

)

C = ax.contourf(

data[:, -1, :], Y[:, -1, :], Z[:, -1, :],

zdir='x', offset=X.max(), **kw

)

# --

# Set limits of the plot from coord limits

xmin, xmax = X.min(), X.max()

ymin, ymax = Y.min(), Y.max()

zmin, zmax = Z.min(), Z.max()

ax.set(xlim=[xmin, xmax], ylim=[ymin, ymax], zlim=[zmin, zmax])

# Plot edges

edges_kw = dict(color='0.4', linewidth=1, zorder=1e3)

ax.plot([xmax, xmax], [ymin, ymax], 0, **edges_kw)

ax.plot([xmin, xmax], [ymin, ymin], 0, **edges_kw)

ax.plot([xmax, xmax], [ymin, ymin], [zmin, zmax], **edges_kw)

# Set labels and zticks

ax.set(

xlabel='X [km]',

ylabel='Y [km]',

zlabel='Z [m]',

zticks=[0, -150, -300, -450],

)

# Set zoom and angle view

ax.view_init(40, -30, 0)

ax.set_box_aspect(None, zoom=0.9)

# Colorbar

fig.colorbar(C, ax=ax, fraction=0.02, pad=0.1, label='Name [units]')

# Show Figure

plt.show()

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