How can I format a float using matplotlib's LaTeX formatter?

To format a float using matplotlib's LaTeX formatter, you can embed mathematical expressions and formatted numbers directly in titles, labels, and text. This is particularly useful for scientific plots where you need to display equations with precise numerical values.

Basic LaTeX Float Formatting

You can format floats within LaTeX strings using Python's string formatting combined with matplotlib's LaTeX renderer ?

import numpy as np
import matplotlib.pyplot as plt

# Set figure parameters
plt.rcParams["figure.figsize"] = [8, 5]
plt.rcParams["figure.autolayout"] = True

# Calculate a float value
area_value = 83.333333
formatted_area = f"{area_value:.2f}"

# Create sample data
x = np.linspace(-5, 5, 100)
y = x**2

# Plot the data
plt.plot(x, y, 'b-', linewidth=2)
plt.fill_between(x, y, alpha=0.3)

# LaTeX formatting with float
plt.title(f"$\int_{{-5}}^{{5}} x^2 dx = {formatted_area}$", fontsize=14)
plt.xlabel("$x$")
plt.ylabel("$f(x) = x^2$")

plt.show()

Advanced Float Formatting in LaTeX

For more control over number formatting, you can use different precision and scientific notation ?

import numpy as np
import matplotlib.pyplot as plt

plt.rcParams["figure.figsize"] = [10, 6]
plt.rcParams["figure.autolayout"] = True

# Different float values
pi_value = np.pi
large_number = 1234567.89
small_number = 0.00012345

# Create subplots for different formatting examples
fig, axes = plt.subplots(2, 2, figsize=(10, 8))

# Example 1: Basic precision
x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)
axes[0,0].plot(x, y)
axes[0,0].set_title(f"$\sin(x)$, $\pi = {pi_value:.4f}$")

# Example 2: Scientific notation
axes[0,1].plot(x, y**2)
axes[0,1].set_title(f"$\sin^2(x)$, Large: ${large_number:.2e}$")

# Example 3: Small numbers
axes[1,0].plot(x, np.cos(x))
axes[1,0].set_title(f"$\cos(x)$, Small: ${small_number:.5f}$")

# Example 4: Percentage formatting
percentage = 0.8567
axes[1,1].plot(x, np.tan(x))
axes[1,1].set_title(f"$\tan(x)$, Rate: ${percentage:.1%}$")
axes[1,1].set_ylim(-2, 2)

plt.tight_layout()
plt.show()

Formatting Options

Dynamic LaTeX Formatting

You can also create functions to dynamically format floats based on their magnitude ?

import numpy as np
import matplotlib.pyplot as plt

def format_float_latex(value):
    """Format float for LaTeX based on magnitude"""
    if abs(value) >= 1000:
        return f"{value:.2e}"
    elif abs(value) >= 1:
        return f"{value:.3f}"
    else:
        return f"{value:.5f}"

# Sample calculation
x_data = np.linspace(0, 10, 50)
y_data = np.exp(x_data)

# Calculate statistics
mean_val = np.mean(y_data)
max_val = np.max(y_data)
min_val = np.min(y_data)

plt.figure(figsize=(10, 6))
plt.plot(x_data, y_data, 'r-', linewidth=2)

# Use dynamic formatting
title_text = f"$e^x$ function: Mean = ${format_float_latex(mean_val)}$, " + \
             f"Max = ${format_float_latex(max_val)}$"
plt.title(title_text, fontsize=12)
plt.xlabel("$x$")
plt.ylabel("$e^x$")
plt.grid(True, alpha=0.3)

plt.show()

Conclusion

Use f-string formatting combined with LaTeX syntax to display formatted floats in matplotlib. Choose appropriate precision (:.2f, :.2e) based on your data's magnitude and scientific context.