Anton's Digital Garden

PyPlot

3 min read

Plot of values for 

import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4])
plt.ylabel('some numbers')
plt.show()

Plot and coordinates

import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
plt.show()

Use numpy

import matplotlib.pyplot as plt
import numpy as np
# evenly sampled time at 200ms intervals
t = np.arange(0., 5., 0.2)
 
# red dashes, blue squares and green triangles
plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')
plt.show()

Plotting with keyword string

data = {'a': np.arange(50),
        'c': np.random.randint(0, 50, 50),
        'd': np.random.randn(50)}
data['b'] = data['a'] + 10 * np.random.randn(50)
data['d'] = np.abs(data['d']) * 100
 
plt.scatter('a', 'b', c='c', s='d', data=data)
plt.xlabel('entry a')
plt.ylabel('entry b')
plt.show()

SVG export

import matplotlib.pyplot as plt
import numpy as np
 
# Generate some data
x = np.linspace(0, 10, 100)
y = np.sin(x)
 
# Create the plot
plt.figure(figsize=(8, 4))
plt.plot(x, y)
plt.title('Sine Wave')
plt.xlabel('X axis')
plt.ylabel('Y axis')
 
# Save the plot as SVG
plt.rcParams['svg.fonttype'] = 'none'
plt.savefig(@vault_path + '/attachments/sine_wave_plot.svg', format='svg', dpi=300, bbox_inches='tight', transparent=True)
plt.show()
plt.close()

sine_wave_plot.svg

Showcase

import numpy as np
import matplotlib.pyplot as plt
 
# Set up the figure with a wide aspect ratio
plt.figure(figsize=(8, 4))
 
# Generate data
x = np.linspace(-2*np.pi, 2*np.pi, 200)
y1 = np.sin(x)
y2 = np.cos(x)
 
# Plot the data
plt.plot(x, y1, color='#ff7f0e', label=r'$\sin(x)$')  # Using hex color
plt.plot(x, y2, color='royalblue', label=r'$\cos(x)$')  # Using named color
 
# Set the title with LaTeX
plt.title(r'Comparison of $\sin(x)$ and $\cos(x)$', fontsize=16)
 
# Set x and y labels with LaTeX
plt.xlabel(r'$x$ (radians)', fontsize=12)
plt.ylabel(r'$f(x)$', fontsize=12)
 
# Add a grid
plt.grid(True, linestyle='--', alpha=0.7)
 
# Add a legend
plt.legend(fontsize=10)
 
# Add text annotation with LaTeX
plt.text(0, 0.5, r'$f(x) = \sin(x)$ or $\cos(x)$', 
         fontsize=12, ha='center', va='center', 
         bbox=dict(facecolor='white', edgecolor='gray', alpha=0.8))
 
# Customize the plot area
plt.xlim(-2*np.pi, 2*np.pi)
plt.ylim(-1.5, 1.5)
 
# Add custom ticks with LaTeX
plt.xticks([-2*np.pi, -np.pi, 0, np.pi, 2*np.pi],
           [r'$-2\pi$', r'$-\pi$', r'$0$', r'$\pi$', r'$2\pi$'])
 
# Adjust layout and save as SVG with transparent background
plt.tight_layout()
plt.gcf().set_facecolor('none')
plt.savefig(@vault_path + '/attachments/pyplot_features_demo.svg', format='svg', transparent=True)
 
# Show the plot
plt.show()

pyplot_features_demo.svg

import numpy as np
import matplotlib.pyplot as plt
 
# Enable LaTeX rendering
plt.rcParams['text.usetex'] = True
plt.rcParams['font.family'] = 'serif'
 
# Create data
x = np.linspace(-2*np.pi, 2*np.pi, 100)
y = np.sin(x)
 
# Create the plot
plt.figure(figsize=(6, 3))
plt.plot(x, y)
plt.title(r'$f(x) = \sin(x)$')
plt.xlabel(r'$x$')
plt.ylabel(r'$y$')
 
# Add a text box with a more complex equation
plt.text(0, 0.5, r'$\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}$', 
         fontsize=14, bbox=dict(facecolor='white', alpha=0.8))
 
plt.grid(True)
plt.savefig(@vault_path + '/attachments/latex_plot.svg', format='svg', transparent=True)
plt.show()

latex_plot.svg

Better SVG rendering

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