Code Explanation:
Import Required Libraries
import numpy as np
import matplotlib.pyplot as plt
numpy (np) is used for numerical operations and generating data points.
matplotlib.pyplot (plt) is used for visualization.
Generate X-Axis Values
x = np.linspace(0, 10, 400)
np.linspace(0, 10, 400) creates 400 evenly spaced points between 0 and 10.
This ensures a smooth wave curve instead of a jagged one.
Define Two Wave Functions
y1 = np.sin(2 * np.pi * x)
y2 = np.sin(2 * np.pi * x + np.pi/2)
y1 = sin(2πx): A standard sine wave.
y2 = sin(2πx + π/2): A phase-shifted sine wave (shifted by π/2).
This means y2 leads y1 by 90 degrees, so the two waves are out of sync.
Create the Figure and Plot the Waves
plt.figure(figsize=(8, 5))
Creates a figure with an 8×5 inch size, ensuring a properly scaled plot.
plt.plot(x, y1, label="Wave 1 (sin)", color="royalblue", linewidth=2)
plt.plot(x, y2, label="Wave 2 (sin + π/2)", color="crimson", linestyle="--", linewidth=2)
plt.plot(x, y1, ...): Plots the first sine wave (y1) in royal blue.
plt.plot(x, y2, ...): Plots the second sine wave (y2) in crimson with a dashed (--) line style.
linewidth=2: Makes the lines thicker for better visibility.
label="...": Adds labels for the legend.
Customize the Plot
plt.title("Dual Wave Pattern", fontsize=14, fontweight="bold")
Adds a bold title with a font size of 14.
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
Labels the X-axis and Y-axis.
plt.grid(True, linestyle="--", alpha=0.6)
Adds a grid to improve readability.
Dashed grid lines (--) with a slight transparency (alpha=0.6).
plt.legend()
Displays a legend to distinguish the two waves.
Show the Plot
plt.show()
Displays the final sine wave plot.


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