Matplotlib log scale tick label number formatting

Matplotlib log scale tick label number formatting

When working with a logarithmic scale in Matplotlib, you might want to customize the formatting of tick labels to display numbers in a more readable and meaningful way. Matplotlib allows you to format tick labels using the ScalarFormatter and FuncFormatter classes.

Here's an example of how you can format tick labels for a logarithmic scale using Matplotlib:

import numpy as np import matplotlib.pyplot as plt from matplotlib.ticker import ScalarFormatter, FuncFormatter # Generate some example data x = np.linspace(1, 100, 100) y = np.exp(x) # Create a plot with a logarithmic y-axis fig, ax = plt.subplots() ax.semilogy(x, y) # Use ScalarFormatter for scientific notation ax.yaxis.set_major_formatter(ScalarFormatter()) # Define a custom function to format tick labels def log_tick_formatter(val, pos): if val >= 1: return f'$10^{int(np.log10(val))}$' else: return f'$10^{{-{abs(int(np.log10(val)))}}}$' # Apply the custom formatter ax.yaxis.set_major_formatter(FuncFormatter(log_tick_formatter)) # Set axis labels and title ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_title('Logarithmic Scale with Custom Tick Labels') plt.tight_layout() plt.show()

In this example, we create a logarithmic y-axis using ax.semilogy(). We then use ScalarFormatter() to format tick labels in scientific notation. Additionally, we define a custom formatting function log_tick_formatter() using FuncFormatter. This function takes a value (val) and a position (pos) and returns a formatted string for the tick label.

The custom formatter ensures that tick labels are displayed in the format "10^x" or "10^-x" based on the exponent of the value. You can modify the formatting logic in the log_tick_formatter function to suit your specific requirements.

Adjust the formatting as needed to achieve the desired appearance for your plot's tick labels on a logarithmic scale.

Examples

  1. "Matplotlib log scale tick label number formatting"

    • Description: This query aims to find methods to format tick labels on a logarithmic scale in Matplotlib.
    import matplotlib.pyplot as plt import numpy as np # Generating data x = np.linspace(1, 10, 100) y = np.exp(x) # Plotting data with logarithmic scale on y-axis plt.plot(x, y) plt.yscale('log') # Formatting tick labels on y-axis plt.gca().yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: '{:.0e}'.format(x))) plt.show()

  2. "Matplotlib log scale scientific notation tick labels"

    • Description: This query looks for ways to display tick labels in scientific notation on a logarithmic scale in Matplotlib.
    import matplotlib.pyplot as plt import numpy as np # Generating data x = np.linspace(1, 10, 100) y = np.exp(x) # Plotting data with logarithmic scale on y-axis plt.plot(x, y) plt.yscale('log') # Formatting tick labels on y-axis in scientific notation plt.gca().yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: '{:.1e}'.format(x))) plt.show()

  3. "Matplotlib log scale tick label precision"

    • Description: This query seeks methods to control the precision of tick labels on a logarithmic scale in Matplotlib.
    import matplotlib.pyplot as plt import numpy as np # Generating data x = np.linspace(1, 10, 100) y = np.exp(x) # Plotting data with logarithmic scale on y-axis plt.plot(x, y) plt.yscale('log') # Formatting tick labels on y-axis with specific precision plt.gca().yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: '{:.2f}'.format(x))) plt.show()

  4. "Matplotlib log scale tick labels without scientific notation"

    • Description: This query aims to display tick labels without scientific notation on a logarithmic scale in Matplotlib.
    import matplotlib.pyplot as plt import numpy as np # Generating data x = np.linspace(1, 10, 100) y = np.exp(x) # Plotting data with logarithmic scale on y-axis plt.plot(x, y) plt.yscale('log') # Formatting tick labels on y-axis without scientific notation plt.gca().yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: '{:g}'.format(x))) plt.show()

  5. "Matplotlib log scale tick labels with specific format"

    • Description: This query looks for ways to specify a custom format for tick labels on a logarithmic scale in Matplotlib.
    import matplotlib.pyplot as plt import numpy as np # Generating data x = np.linspace(1, 10, 100) y = np.exp(x) # Plotting data with logarithmic scale on y-axis plt.plot(x, y) plt.yscale('log') # Formatting tick labels on y-axis with a specific format plt.gca().yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: '${:.0f}'.format(x))) plt.show()

  6. "Matplotlib log scale tick labels in engineering notation"

    • Description: This query seeks methods to display tick labels in engineering notation on a logarithmic scale in Matplotlib.
    import matplotlib.pyplot as plt import numpy as np # Generating data x = np.linspace(1, 10, 100) y = np.exp(x) # Plotting data with logarithmic scale on y-axis plt.plot(x, y) plt.yscale('log') # Formatting tick labels on y-axis in engineering notation plt.gca().yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: '{:.1e}'.format(x))) plt.show()

  7. "Matplotlib log scale tick labels with comma separators"

    • Description: This query aims to display tick labels with comma separators on a logarithmic scale in Matplotlib.
    import matplotlib.pyplot as plt import numpy as np import matplotlib.ticker as ticker # Generating data x = np.linspace(1, 10, 100) y = np.exp(x) # Plotting data with logarithmic scale on y-axis plt.plot(x, y) plt.yscale('log') # Formatting tick labels on y-axis with comma separators formatter = ticker.FuncFormatter(lambda x, _: '{:,.0f}'.format(x)) plt.gca().yaxis.set_major_formatter(formatter) plt.show()

  8. "Matplotlib log scale tick labels with percentage format"

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