Mountain Horizon Pattern using Python

 

import numpy as np

import matplotlib.pyplot as plt

num_layers = 7

x = np.linspace(0, 10, 500)

plt.figure(figsize=(8, 6))

for i in range(num_layers):

    y = 1.5 * np.sin(x + i * 0.5) + np.random.uniform(-0.2, 0.2, size=x.shape) + (i * 0.8)

    color = (0.2, 0.3, 0.5, 1 - i / (num_layers + 1))

    plt.fill_between(x, y, -5, color=color)

plt.axis('off')

plt.gca().set_aspect('auto', adjustable='box')

plt.title('Mountain Horizon Pattern', fontsize=14)

plt.show()

#source code --> clcoding.com

Code Explanation:

1. Importing Libraries

import numpy as np

import matplotlib.pyplot as plt

NumPy: Used for mathematical operations and to generate smooth x-values (np.linspace) and random noise (np.random.uniform).

Matplotlib: Used to plot and visualize the mountains using plt.fill_between().

 2. Parameters and Initialization

num_layers = 7

x = np.linspace(0, 10, 500)

plt.figure(figsize=(10, 6))

num_layers = 7: The number of mountain layers to be drawn, creating a sense of depth.

x = np.linspace(0, 10, 500):

Generates 500 points between 0 and 10 for the x-axis, ensuring smooth curves.

plt.figure(figsize=(10, 6)):

Creates a figure with a size of 10x6 inches, providing a wide, scenic view.

 3. Creating the Mountain Layers

for i in range(num_layers):

    y = 1.5 * np.sin(x + i * 0.5) + np.random.uniform(-0.2, 0.2, size=x.shape) + (i * 0.8)

for i in range(num_layers): A loop that generates each layer of mountains.

np.sin(x + i * 0.5):

A sine wave creates the smooth, wavy shape of the mountains.

The i * 0.5 adds a phase shift to differentiate the layers.

np.random.uniform(-0.2, 0.2, size=x.shape):

Adds small random variations (noise) to the wave, making the mountains look more natural and rugged.

(i * 0.8):

Gradually raises each subsequent layer, simulating mountains in the distance.

 4. Adding Color with Transparency

color = (0.2, 0.3, 0.5, 1 - i / (num_layers + 1))

Color: Uses an RGBA value where:

 Red (0.2), Green (0.3), and Blue (0.5) create a cool blue tone, like distant mountains.

Alpha (1 - i / (num_layers + 1)) controls transparency.

Closer mountains are darker and more opaque.

Distant mountains are lighter and more transparent, creating an atmospheric perspective.

 5. Plotting the Mountains

plt.fill_between(x, y, -5, color=color)

plt.fill_between():

Fills the area between the mountain curve (y) and the bottom of the plot (-5).

This creates the solid mountain silhouette.

 6. Adjusting the Plot

plt.axis('off')

plt.gca().set_aspect('auto', adjustable='box')

plt.title('Mountain Horizon Pattern', fontsize=14)

plt.show()

plt.axis('off'): Hides the axis for a clean, artistic look.

plt.gca().set_aspect('auto', adjustable='box'):

Ensures the aspect ratio adjusts naturally to fit the plot.

plt.title(): Adds a descriptive title.

plt.show(): Displays the final output.