Heat Wave Mirage Pattern using Python

 

import numpy as np

import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D

x = np.linspace(-5, 5, 100)

y = np.linspace(-5, 5, 100)

X, Y = np.meshgrid(x, y)

heat_source_x, heat_source_y = 0, 0 

sigma = 1.5  

Z = np.exp(-((X - heat_source_x)**2 + (Y - heat_source_y)**2) / (2 * sigma**2))

fig=plt.figure(figsize=(10,7))

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

ax.plot_surface(X,Y,Z,cmap="hot",edgecolor="none")

ax.set_xlabel("X Axis")

ax.set_ylabel("Y Axis")

ax.set_zlabel("Heat Intensity")

ax.set_title("Heat Wave Mirage pattern")

ax.set_xticks([])

ax.set_yticks([])

ax.set_zticks([])

plt.show()

#source code --> clcoding.com 

Code Explanation:

Import Required Libraries

import numpy as np

import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D

NumPy (np): Used for creating numerical arrays and mesh grids.

 Matplotlib (plt): Used for creating the 3D surface plot.

 mpl_toolkits.mplot3d: Enables 3D plotting in Matplotlib.

 

Create a Grid for Heat Simulation

x = np.linspace(-5, 5, 100)  # X-axis range (-5 to 5) with 100 points

y = np.linspace(-5, 5, 100)  # Y-axis range (-5 to 5) with 100 points

X, Y = np.meshgrid(x, y)     # Create a 2D mesh grid from x and y values

np.linspace(-5, 5, 100): Creates 100 evenly spaced points from -5 to 5 in both x and y directions.

 np.meshgrid(x, y): Creates a grid of (X, Y) points where each (x, y) pair forms a coordinate in a 2D plane.

 

Define Heat Source and Heat Diffusion Formula

heat_source_x, heat_source_y = 0, 0  # Heat source at (0,0)

sigma = 1.5  # Controls the spread of heat

Z = np.exp(-((X - heat_source_x)**2 + (Y - heat_source_y)**2) / (2 * sigma**2))

(heat_source_x, heat_source_y): Defines the center of the heat source.

sigma: Controls how fast heat dissipates (higher value = wider spread).

This equation models how heat intensity decreases as we move away from the heat source.

High intensity at (0,0) and gradual fading outward.

 

Create a 3D Plot

fig = plt.figure(figsize=(10, 7))  # Create figure with size 10x7

ax = fig.add_subplot(111, projection="3d")  # Add 3D subplot

fig = plt.figure(figsize=(10, 7)): Initializes a Matplotlib figure.

 ax = fig.add_subplot(111, projection="3d"): Creates a 3D plot area (ax).

 

Plot Heat Distribution as a 3D Surface

ax.plot_surface(X, Y, Z, cmap="hot", edgecolor="none")

plot_surface(X, Y, Z): Creates a 3D surface plot.

cmap="hot": Uses the "hot" color map, where:

Red & yellow = High heat

Black & dark orange = Low heat

edgecolor="none": Removes edges to make the plot smooth.

 

Customize Labels and Titles

ax.set_xlabel("X Axis")

ax.set_ylabel("Y Axis")

ax.set_zlabel("Heat Intensity")

ax.set_title("Heatwave Mirage - 3D Heat Diffusion Simulation")

Adds labels for X, Y, and Z axes.

Sets the plot title.

 Remove Grid Ticks for a Clean Look

ax.set_xticks([])

ax.set_yticks([])

ax.set_zticks([])

Hides grid ticks for a smoother visualization.

 

Display the Final Heatwave Mirage

plt.show()

Displays the 3D plot.