Matplotlib Logo Creation

Introduction

This lab will guide you through the process of creating the Firefox logo using Python's Matplotlib library.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

Import Required Libraries

We will first import all the required libraries for this project, which include re, matplotlib.pyplot, numpy, matplotlib.patches, and matplotlib.path.

import re
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.patches as patches
from matplotlib.path import Path

Define the Firefox Logo Path

We will define the path of the Firefox logo using SVG path data.

firefox = "M28.4,22.469c0.479-0.964,0.851-1.991,1.095-3.066c0.953-3.661,0.666-6.854,0.666-6.854l-0.327,2.104c0,0-0.469-3.896-1.044-5.353c-0.881-2.231-1.273-2.214-1.274-2.21c0.542,1.379,0.494,2.169,0.483,2.288c-0.01-0.016-0.019-0.032-0.027-0.047c-0.131-0.324-0.797-1.819-2.225-2.878c-2.502-2.481-5.943-4.014-9.745-4.015c-4.056,0-7.705,1.745-10.238,4.525C5.444,6.5,5.183,5.938,5.159,5.317c0,0-0.002,0.002-0.006,0.005c0-0.011-0.003-0.021-0.003-0.031c0,0-1.61,1.247-1.436,4.612c-0.299,0.574-0.56,1.172-0.777,1.791c-0.375,0.817-0.75,2.004-1.059,3.746c0,0,0.133-0.422,0.399-0.988c-0.064,0.482-0.103,0.971-0.116,1.467c-0.09,0.845-0.118,1.865-0.039,3.088c0,0,0.032-0.406,0.136-1.021c0.834,6.854,6.667,12.165,13.743,12.165l0,0c1.86,0,3.636-0.37,5.256-1.036C24.938,27.771,27.116,25.196,28.4,22.469zM16.002,3.356c2.446,0,4.73,0.68,6.68,1.86c-2.274-0.528-3.433-0.261-3.423-0.248c0.013,0.015,3.384,0.589,3.981,1.411c0,0-1.431,0-2.856,0.41c-0.065,0.019,5.242,0.663,6.327,5.966c0,0-0.582-1.213-1.301-1.42c0.473,1.439,0.351,4.17-0.1,5.528c-0.058,0.174-0.118-0.755-1.004-1.155c0.284,2.037-0.018,5.268-1.432,6.158c-0.109,0.07,0.887-3.189,0.201-1.93c-4.093,6.276-8.959,2.539-10.934,1.208c1.585,0.388,3.267,0.108,4.242-0.559c0.982-0.672,1.564-1.162,2.087-1.047c0.522,0.117,0.87-0.407,0.464-0.872c-0.405-0.466-1.392-1.105-2.725-0.757c-0.94,0.247-2.107,1.287-3.886,0.233c-1.518-0.899-1.507-1.63-1.507-2.095c0-0.366,0.257-0.88,0.734-1.028c0.58,0.062,1.044,0.214,1.537,0.466c0.005-0.135,0.006-0.315-0.001-0.519c0.039-0.077,0.015-0.311-0.047-0.596c-0.036-0.287-0.097-0.582-0.19-0.851c0.01-0.002,0.017-0.007,0.021-0.021c0.076-0.344,2.147-1.544,2.299-1.659c0.153-0.114,0.55-0.378,0.506-1.183c-0.015-0.265-0.058-0.294-2.232-0.286c-0.917,0.003-1.425-0.894-1.589-1.245c0.222-1.231,0.863-2.11,1.919-2.704c0.02-0.011,0.015-0.021-0.008-0.027c0.219-0.127-2.524-0.006-3.76,1.604C9.674,8.045,9.219,7.95,8.71,7.95c-0.638,0-1.139,0.07-1.603,0.187c-0.05,0.013-0.122,0.011-0.208-0.001C6.769,8.04,6.575,7.88,6.365,7.672c0.161-0.18,0.324-0.356,0.495-0.526C9.201,4.804,12.43,3.357,16.002,3.356z"  ## noqa

Parse SVG Path Data

We will use the svg_parse function to parse the SVG path data into vertices and codes that can be used by Matplotlib.

def svg_parse(path):
    commands = {'M': (Path.MOVETO,),
                'L': (Path.LINETO,),
                'Q': (Path.CURVE3,)*2,
                'C': (Path.CURVE4,)*3,
                'Z': (Path.CLOSEPOLY,)}
    vertices = []
    codes = []
    cmd_values = re.split("([A-Za-z])", path)[1:]  ## Split over commands.
    for cmd, values in zip(cmd_values[::2], cmd_values[1::2]):
        ## Numbers are separated either by commas, or by +/- signs (but not at
        ## the beginning of the string).
        points = ([*map(float, re.split(",|(?<!^)(?=[+-])", values))] if values
                  else [(0., 0.)])  ## Only for "z/Z" (CLOSEPOLY).
        points = np.reshape(points, (-1, 2))
        if cmd.islower():
            points += vertices[-1][-1]
        codes.extend(commands[cmd.upper()])
        vertices.append(points)
    return np.array(codes), np.concatenate(vertices)

## Parse the Firefox logo path data
codes, verts = svg_parse(firefox)
path = Path(verts, codes)

Create the Plot

We will now create the plot using Matplotlib by adding two PathPatch objects to the plot. One will be an orange filled shape, while the other will be a white outline.

## Set the plot limits
xmin, ymin = verts.min(axis=0) - 1
xmax, ymax = verts.max(axis=0) + 1

## Create the plot
fig = plt.figure(figsize=(5, 5), facecolor="0.75")  ## gray background
ax = fig.add_axes([0, 0, 1, 1], frameon=False, aspect=1,
                  xlim=(xmin, xmax),  ## centering
                  ylim=(ymax, ymin),  ## centering, upside down
                  xticks=[], yticks=[])  ## no ticks

## Add the white outline
ax.add_patch(patches.PathPatch(path, facecolor='none', edgecolor='w', lw=6))

## Add the orange shape
ax.add_patch(patches.PathPatch(path, facecolor='orange', edgecolor='k', lw=2))

## Display the plot
plt.show()

Summary

In this lab, we learned how to use Matplotlib to create a plot of the Firefox logo. We parsed the SVG path data using a custom function and created the plot using PathPatch objects. This lab provides a good introduction to the capabilities of Matplotlib for creating complex shapes and designs.