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    In Matplotlib, the equivalent of MATLAB's hold on command is achieved by simply calling the plot function multiple times before calling show. This allows you to plot multiple graphs on the same figure without clearing the previous plots.

    Example

    import numpy as np
    import matplotlib.pyplot as plt

    x = np.linspace(0, 2 * np.pi, 100)
    y1 = np.sin(x)
    y2 = np.cos(x)
    y3 = np.tan(x)

    plt.plot(x, y1, 'g', label='sin(x)')
    plt.plot(x, y2, 'r', label='cos(x)')
    plt.plot(x, y3, 'b', label='tan(x)')

    plt.xlabel('x')
    plt.ylabel('Function Value')
    plt.legend()
    plt.show()

    In this example, we plot the sine, cosine, and tangent functions on the same figure. The plot function is called three times before show, which displays all three plots on the same grid12.

    Important Considerations

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  3. Python equivalent to 'hold on' in Matlab - Stack Overflow

     
  4. MATLAB Hold On Command in Python - AskPython

    Oct 16, 2023 · To plot multiple graphs on a single grid in Python as an equivalent to MATLAB’s Hold On command, you can use the Matplotlib library. Import Matplotlib and define your data points. Then use plt.plot() for each graph you …

  5. Python's Alternative to 'hold on' in Matlab: Python 3 …

    While Python does not have a direct equivalent to ‘hold on,’ there are alternative approaches that can achieve similar results. One common method is to use the ‘plt.figure()’ function to create a new figure and then use ‘plt.plot()’ to add plots …

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  11. What does the matplotlib `hold` keyword argument do?

    When hold is False, the current axes and figure will be cleared on the next plot command. The value of hold determines if future plots are drawn over the previous one (s), or if the figure is cleared before drawing.

  12. How to Use the Python Equivalent of MATLAB's Hold …

    To plot multiple graphs on a single grid in Python as an equivalent to MATLAB’s Hold On command, you can use the Matplotlib library. Import Matplotlib and define your data points. Then use plt.plot() for each graph you want to plot.

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