Matplotlib 简明教程

\documentclass{article}
\begin{document}
\section{Introduction}
This is a simple LaTeX document.
\subsection{Subsection}
Some text in a subsection.
\end{document}

import numpy as np
from matplotlib import pyplot as plt
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
x = np.linspace(-10, 10, 100)
y = np.exp(x)
plt.plot(x, y, color='red', label="$y=e^{x}$")
plt.legend(loc='upper right')
plt.show()

import numpy as np
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
x = np.linspace(1, 10, 1000)
y = np.sin(x)
plt.plot(x, y, label=r'$\sin (x)$', c="red", lw=2)
plt.legend()
plt.show()

import numpy as np
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
x = np.linspace(1, 10, 1000)
y = np.sin(x)
plt.plot(x, y, label=r'$\sin (x)$', c="red", lw=2)
plt.legend(r'αiπ+1=0')
plt.show()

import matplotlib.pyplot as plt
equation = r'$x = \frac{{-b \pm \sqrt{{b^2 - 4ac}}}}{{2a}}$'
plt.text(0.5, 0.5, equation, fontsize=12, ha='center')
plt.axis('off')
plt.show()

$$
   f(x) = \int_{a}^{b} g(x) \, dx
$$

\begin{equation}
   f(x) = \int_{a}^{b} g(x) \, dx
   \end{equation}

import matplotlib.pyplot as plt
import matplotlib as mpl
equation = r'$(\alpha + \beta = \gamma \times \delta)$'
plt.figure(figsize=(6, 3))
plt.text(0.5, 0.5, equation, fontsize=12, ha='center', va='center')
plt.axis('off')
plt.show()

import matplotlib.pyplot as plt
import matplotlib as mpl
equation = r'The fraction is $\frac{3}{4}$'
plt.figure(figsize=(6, 3))
plt.text(0.5, 0.5, equation, fontsize=12, ha='center', va='center')
plt.axis('off')
plt.show()

\[
\begin{array}{ccc}
1 & 2 & 3 \\
4 & 5 & 6 \\
7 & 8 & 9 \\
\end{array}
\]

\[
\begin{matrix}
1 & 2 & 3 \\
4 & 5 & 6 \\
7 & 8 & 9 \\
\end{matrix}
\]

\[
\begin{array}{ccc}
1 & 222 & 3 \\
4 & 55555 & 6 \\
7 & 888 & 999999 \\
\end{array}
\]

\begin{bmatrix}
1 & 2 \\
3 & 4
\end{bmatrix}

import matplotlib.pyplot as plt

# LaTeX code for the bold text
bold_text = r'$\sin(\theta), \log(x), \lim_{x \to \infty} f(x)$'

# Create a figure and display the bold text
plt.figure(figsize=(6, 3))
plt.text(0.5, 0.5, bold_text, fontsize=12, ha='center', va='center')
plt.axis('off')
plt.show()

from matplotlib import pyplot as plt
plt.rcParams["figure.figsize"] = [7.00, 3.50]
plt.rcParams["figure.autolayout"] = True
plt.subplot(211)
plt.text(0.4, 0.4, r'$\sum_{n=1}^{\infty}\; \frac{-e^{i\pi}}{2^n}!\left[a^2+\delta ^2- \frac{\pi}{2} \right ]$', fontsize=16, color='r')
plt.title("With thick space")
plt.subplot(212)
plt.text(0.4, 0.4, r'$\sum_{n=1}^{\infty}\! \frac{-e^{i\pi}}{2^n}!\left[a^2+\delta ^2- \frac{\pi}{2} \right ]$', fontsize=16, color='r')
plt.title("With thin space")
plt.show()

\textbf{Bold Text}

\textit{Italic Text}

\underline{Underlined Text}

import matplotlib.pyplot as plt
# Create a simple plot
x = [1, 2, 3, 4]
y = [2, 5, 7, 10]
plt.plot(x, y, marker='o', linestyle='-')

# Add an annotation with LaTeX text formatting
plt.annotate(r'\textbf{Max Value}',
   xy=(x[y.index(max(y))], max(y)),
   xytext=(2.5, 8),
   arrowprops=dict(facecolor='black', shrink=0.05),
   fontsize=12,
   color='blue',
   bbox=dict(boxstyle='round,pad=0.3', edgecolor='blue', facecolor='lightblue'))

# Set axis labels and title
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Example Plot with LaTeX Annotation')

# Show the plot
plt.show()

\mathbf{Bold Text}

\textit{Italic Text}

\textsf{Sans-serif Text}

\texttt{Typewriter Text}

import matplotlib.pyplot as plt

# Generating some data points
x = [1, 2, 3, 4]
y = [2, 5, 7, 10]
plt.plot(x, y, 'o-', label='Data')

# Annotating a point with a subscript and a superscript
plt.annotate(r'$\mathrm{Point}_{\mathrm{max}}^{(4, 10)}$',
   xy=(x[y.index(max(y))], max(y)),
   xytext=(3, 8),
   arrowprops=dict(facecolor='black', arrowstyle='->'),
   fontsize=12,
   color='red')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Example Plot with Annotation')
plt.legend()
plt.show()

import matplotlib.pyplot as plt
import matplotlib as mpl
equation = r'$x_i^2$ denotes $x$ raised to the power of $i$ squared.'
plt.figure(figsize=(6, 3))
plt.text(0.5, 0.5, equation, fontsize=12, ha='center', va='center')
plt.axis('off')
plt.show()

import matplotlib.pyplot as plt
import matplotlib as mpl
equation = r'$x_{i_j}^{2k}$ represents a nested subscript and superscript.'
plt.figure(figsize=(6, 3))
plt.text(0.5, 0.5, equation, fontsize=12, ha='center', va='center')
plt.axis('off')
plt.show()

import matplotlib.pyplot as plt
import matplotlib as mpl
equation = r'$x_{i}^{2}$'
plt.figure(figsize=(6, 3))
plt.text(0.5, 0.5, equation, fontsize=12, ha='center', va='center')
plt.axis('off')
plt.show()

import matplotlib.pyplot as plt

# Generating some data points
x = [1, 2, 3, 4]
y = [2, 5, 7, 10]
plt.plot(x, y, 'o-', label='Data')

# Annotating a point with combined text and math in LaTeX
plt.annotate(r'$\frac{dx}{dt} = \alpha \cdot x(t) + \beta$ is the differential equation',
   xy=(x[2], y[2]),
   xytext=(2, 6),
   arrowprops=dict(facecolor='black', arrowstyle='->'),
   fontsize=12,
   color='blue')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Example Plot with Annotation by Latex')
plt.legend()
plt.show()

\textcolor{color_name}{text}

import matplotlib.pyplot as plt

# Generating some data points
x = [1, 2, 3, 4]
y = [2, 5, 7, 10]
plt.plot(x, y, 'o-', label='Data')

# Annotating a point with different text color and font style
plt.annotate(r'\mathbf{\textcolor{red}{Max value:}} \ \textit{\textcolor{blue}{y_{\text{max}} = 10}}',
   xy=(x[y.index(max(y))], max(y)),
   xytext=(3, 8),
   arrowprops=dict(facecolor='black', arrowstyle='->'),
   fontsize=12)
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Example Plot with Annotation of color and font style')
plt.legend()
plt.show()

import numpy as np
from matplotlib import pyplot as plt, font_manager as fm
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
plt.rcParams["font.fantasy"] = "Comic Sans MS"
x = np.array([1, 2, 3, 4])
y = np.exp(x)
ax1 = plt.subplot()
ax1.set_xticks(x)
ax1.set_yticks(y)
ax1.plot(x, y, c="red")
ax1.set_xticklabels([r"$\bf{one}$", r"$\bf{two}$", r"$\bf{three}$",
   r"$\bf{four}$"], rotation=45)
ax1.set_yticklabels([r"$\bf{:.2f}$".format(y[0]), r"$\bf{:.2f}$".format(y[1]),
   r"$\bf{:.2f}$".format(y[2]), r"$\bf{:.2f}$".format(y[3])], rotation=45)
plt.tight_layout()
plt.show()

import numpy as np
from matplotlib import pyplot as plt

# Set the figures size
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# x and y data points
x = np.linspace(-5, 5, 100)
y = x**3/3

# Plot the data points
plt.plot(x, y)

# Fill the area between the curve
plt.fill_between(x, y)

# LaTex representation
plt.title("$area=\int_a^b{x^2dx}$=83.3")

# Display the plot
plt.show()

import numpy as np
from matplotlib import pyplot as plt

# Set the figures size
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# x and y data points
x = np.linspace(-5, 5, 100)
y = x**3/3

# Plot the data points
plt.plot(x, y)

# Fill the area between the curve
plt.fill_between(x, y)

# LaTex representation
plt.title("$area=\int_a^b{x^2dx}$=83.3")

# Display the plot
plt.show()

pdflatex your_file.tex

import matplotlib.pyplot as plt

# Sample data
x = [1, 2, 3, 4]
y = [2, 5, 7, 10]
plt.plot(x, y, 'o-', label='Data')

# Annotating a point with LaTeX-rendered text
plt.annotate(r'$\sum_{i=1}^{4} y_i$',   # LaTeX expression within the annotation
   xy=(x[2], y[2]),           # Coordinates of the annotation point
   xytext=(2.5, 6),           # Text position
   arrowprops=dict(facecolor='black', arrowstyle='->'),
   fontsize=12,
   color='green')

# Labeling axes and title
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Plot with LaTeX rendering in Annotation')
plt.legend()
plt.show()

import matplotlib.pyplot as plt

# Generating some data points
x = [1, 2, 3, 4]
y = [2, 5, 7, 10]
plt.plot(x, y, 'o-', label='Data')

# Annotating a point with LaTeX rendering
plt.annotate(r'\textbf{Max Value}',
   xy=(x[y.index(max(y))], max(y)),
   xytext=(2.5, 8),
   arrowprops=dict(facecolor='black', shrink=0.05),
   fontsize=12,
   color='white',
   bbox=dict(boxstyle='round,pad=0.3', edgecolor='red', facecolor='green'))
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Example Plot with LaTeX Annotation')
plt.legend()
plt.show()

import numpy as np
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = [7.00, 3.50]
plt.rcParams["figure.autolayout"] = True
x = np.array([1, 2, 3, 4])
y = np.exp(x)
ax1 = plt.subplot()
ax1.set_xticks(x)
ax1.set_yticks(y)
ax1.plot(x, y, c="red")
ax1.set_xticklabels([r"$\bf{one}$", r"$\bf{two}$", r"$\bf{three}$", r"$\bf{four}$"], rotation=45)
ax1.set_yticklabels([r"$\bf{:.2f}$".format(y[0]), r"$\bf{:.2f}$".format(y[1]),
   r"$\bf{:.2f}$".format(y[2]), r"$\bf{:.2f}$".format(y[3])], rotation=45)
plt.tight_layout()
plt.show()