Responsive Navbar with Google Search
☰ Menu
Home
Python
LaTeX
GNUPlot
Arduino
Feedback
Contact Us
Plotting in Python: Stream plot to Visualize Flow Data
Plotting in Python
Basic Plot and formatting
Subplot, Multiplot
Colormaps in Plots
Bar Plot
Pie Chart
Histogram
Quiver plot to show Vector Fields
Stream plot to Visualize Flow Data
Polar, Parametric Plot
Contour Plot
3D Plot
Density Plot
Animated Plot
Miscellaneous
Stream plot to Visualize Flow Data: Program 1
2D Stream Plot
import numpy as np import matplotlib.pyplot as plt Y, X = np.mgrid[-3:3:100j, -3:3:100j] U = -1 - X**2 + Y V = 1 + X - Y**2 plt.streamplot(X, Y, U, V, color='blue') plt.title('Simple 2D Stream Plot') plt.xlabel('X-axis') plt.ylabel('Y-axis') plt.savefig('plot.png')
Run Code
Output 1
Stream plot to Visualize Flow Data: Program 2
Stream Plot with Varying Line Width
import numpy as np import matplotlib.pyplot as plt Y, X = np.mgrid[-3:3:100j, -3:3:100j] U = 1 - X**2 + Y V = 1 + X - Y**2 speed = np.sqrt(U**2 + V**2) # Speed as the magnitude of the velocity vector plt.streamplot(X, Y, U, V, color='green', linewidth=2*speed/speed.max()) plt.title('Stream Plot with Varying Line Width') plt.xlabel('X-axis') plt.ylabel('Y-axis') plt.savefig('plot.png')
Run Code
Output 2
Stream plot to Visualize Flow Data: Program 3
Stream Plot with Color Coding by Speed
import numpy as np import matplotlib.pyplot as plt Y, X = np.mgrid[-3:3:100j, -3:3:100j] U = 1 - X**2 + Y V = 1 + X - Y**2 speed = np.sqrt(U**2 + V**2) plt.streamplot(X, Y, U, V, color=speed, linewidth=1, cmap='autumn') plt.colorbar(label='Flow Speed') plt.title('Stream Plot with Color Coding by Speed') plt.xlabel('X-axis') plt.ylabel('Y-axis') plt.savefig('plot.png')
Run Code
Output 3
Stream plot to Visualize Flow Data: Program 4
Stream Plot with Custom Starting Points
import numpy as np import matplotlib.pyplot as plt Y, X = np.mgrid[-3:3:100j, -3:3:100j] U = 1 - X**2 + Y V = 1 + X - Y**2 start_points = np.array([[0, 0], [1, 1], [-1, -1], [2, -2]]) plt.streamplot(X, Y, U, V, start_points=start_points, color='purple') plt.scatter(start_points[:, 0], start_points[:, 1], color='red') # Mark starting points plt.title('Stream Plot with Custom Starting Points') plt.xlabel('X-axis') plt.ylabel('Y-axis') plt.savefig('plot.png')
Run Code
Output 4