Think DSP: Digital Signal Processing in Python, by Allen B. Downey.

Related tags

MiscellaneousThinkDSP
Overview

ThinkDSP

LaTeX source and Python code for Think DSP: Digital Signal Processing in Python, by Allen B. Downey.

The premise of this book (and the other books in the Think X series) is that if you know how to program, you can use that skill to learn other things. I am writing this book because I think the conventional approach to digital signal processing is backward: most books (and the classes that use them) present the material bottom-up, starting with mathematical abstractions like phasors.

With a programming-based approach, I can go top-down, which means I can present the most important ideas right away. By the end of the first chapter, you can break down a sound into its harmonics, modify the harmonics, and generate new sounds.

Here's a notebook that previews what you will see in Chapter 1:

And if you want to see where were headed, here's a preview of Chapter 10:

Running the code

Most of the code for this book is in Jupyter notebooks. If you are not familiar with Jupyter, you can run a tutorial by clicking here. Then select "Try Classic Notebook". It will open a notebook with instructions for getting started.

To run the ThinkDSP code, you have several options:

Option 1: Run the notebooks on Google Colab.

Option 2: Run the notebooks on Binder.

Option 3: Use Conda to install the libraries you need and run the notebooks on your computer.

Option 4: Use poetry to install the libraries you need and run the notebooks on your computer.

The following sections explain these options in detail.

Note: I have heard from a few people who tried to run the code in Spyder. Apparently there were problems, so I don't recommend it.

Option 1: Run on Colab

I have recently updated most of the notebooks in this repository so they run on Colab.

You can open any of them by clicking on the links below. If you want to modify and save any of them, you can use Colab to save a copy in a Google Drive or your own GitHub repo, or on your computer.

Option 2: Run on Binder

To run the code for this book on Binder, press this button:

Binder

It takes a minute or so to start up, but then you should see the Jupyter home page with a list of files. Click on code to open the folder with the notebooks, then click on one of the notebooks (with the .ipynb extension).

Option 3: Install Python+Jupyter

First, download the files from this repository. If you are a Git user, you can run

git clone --depth 1 https://github.com/AllenDowney/ThinkDSP.git

Otherwise you can download this Zip file and unzip it. Either way, you should end up with a directory called ThinkDSP.

Now, if you don't already have Jupyter, I highly recommend installing Anaconda, which is a Python distribution that contains everything you need to run the ThinkDSP code. It is easy to install on Windows, Mac, and Linux, and because it does a user-level install, it will not interfere with other Python installations.

Information about installing Anaconda is here.

If you have the choice of Python 2 or 3, choose Python 3.

There are two ways to get the packages you need for ThinkDSP. You can install them by hand or create a Conda environment.

To install them by hand run

conda install jupyter numpy scipy pandas matplotlib seaborn

Or, to create a conda environment, run

cd ThinkDSP
conda env create -f environment.yml
conda activate ThinkDSP

Option 4: Use poetry to manage the project on your computer or notebook locally.

First, download the files from this repository. If you are a Git user, you can run

git clone --depth 1 https://github.com/AllenDowney/ThinkDSP.git

Then, assuming you have poetry installed on your machine, run

cd ThinkDSP
poetry install

to install the libraries you need in a virtual environment. To activate the environment, run

poetry shell

Then you can run Jupyter.

Run Jupyter

To start Jupyter, run:

jupyter notebook

Jupyter should launch your default browser or open a tab in an existing browser window. If not, the Jupyter server should print a URL you can use. For example, when I launch Jupyter, I get

~/ThinkComplexity2$ jupyter notebook
[I 10:03:20.115 NotebookApp] Serving notebooks from local directory: /home/downey/ThinkDSP
[I 10:03:20.115 NotebookApp] 0 active kernels
[I 10:03:20.115 NotebookApp] The Jupyter Notebook is running at: http://localhost:8888/
[I 10:03:20.115 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).

In this case, the URL is http://localhost:8888. When you start your server, you might get a different URL. Whatever it is, if you paste it into a browser, you should see a home page with a list of directories.

Click on code to open the folder with the notebooks, then click on one of the notebooks (with the .ipynb extension).

Select the cell with the import statements and press "Shift-Enter" to run the code in the cell. If it works and you get no error messages, you are all set.

If you get error messages about missing packages, you can install the packages you need using your package manager, or install Anaconda.

If you run into problems with these instructions, let me know and I will make corrections. Good luck!

Freesound

Special thanks to Freesound (http://freesound.org), which is the source of many of the sound samples I use in this book, and to the Freesound users who uploaded those sounds. I include some of their wave files in the GitHub repository for this book, using the original file names, so it should be easy to find their sources.

Unfortunately, most Freesound users don't make their real names available, so I can only thank them using their user names. Samples used in this book were contributed by Freesound users: iluppai, wcfl10, thirsk, docquesting, kleeb, landup, zippi1, themusicalnomad, bcjordan, rockwehrmann, marchascon7, jcveliz. Thank you all!

Here are links to the sources:

http://www.freesound.org/people/iluppai/sounds/100475/

http://www.freesound.org/people/wcfl10/sounds/105977/

http://www.freesound.org/people/Thirsk/sounds/120994/

http://www.freesound.org/people/ciccarelli/sounds/132736/

http://www.freesound.org/people/Kleeb/sounds/180960/

http://www.freesound.org/people/zippi1/sounds/18871/

http://www.freesound.org/people/themusicalnomad/sounds/253887/

http://www.freesound.org/people/bcjordan/sounds/28042/

http://www.freesound.org/people/rockwehrmann/sounds/72475/

http://www.freesound.org/people/marcgascon7/sounds/87778/

http://www.freesound.org/people/jcveliz/sounds/92002/

Owner
Allen Downey
Professor at Olin College, author of Think Python, Think Bayes, Think Stats, and other books. Blog author of Probably Overthinking It.
Allen Downey
MODSKIN-LOLPRO-updater: The mod is fkn 10y old and has'nt a self-updater

The mod is fkn 10y old and has'nt a self-updater. To use it just run the exec, wait some seconds, and it will run the new modsk

Shiro Amurha 3 Apr 23, 2022
使用京东cookie一键生成所有退会链接

JDMemberCloseLinks 本项目旨在使用京东cookie一键生成所有退会链接

hyzaw 68 Jun 10, 2022
Vaccine for STOP/DJVU ransomware, prevents encryption

STOP/DJVU Ransomware Vaccine Prevents STOP/DJVU Ransomware from encrypting your files. This tool does not prevent the infection itself. STOP ransomwar

Karsten Hahn 16 May 31, 2022
This is a working model for which I have used python.

Jarvis_voiceAssistance This is a working model for which I have used python. This model can: 1)Play a video or song on youtube. 2)Tell us time. 3)Tell

Hardik Jain 1 Jan 30, 2022
Shopping-card - Shopping Card Project With Python

Shopping Card Project this application was built to handle problems with saving

moein98 1 May 06, 2022
Find virtual hosts (vhosts) from IP addresses and hostnames

Features Enumerate vhosts from a list of IP addresses and domain names. Virtual Hosts are enumerated using the following process: Supplied domains are

3 Jul 09, 2022
Pre-commit hook for upgrading type hints

This is a pre-commit hook configured to automatically upgrade your type hints to the new native types implemented in PEP 585.

snok 54 Nov 14, 2022
An alternative site to emplea.do due to inconsistent service of the app.

feline a agile and fast alternative to emplea.do License: MIT Settings Moved to settings. Basic Commands Setting Up Your Users To create a normal user

Codetiger 8 Nov 10, 2021
A web UI for managing your 351ELEC device ROMs.

351ELEC WebUI A web UI for managing your 351ELEC device ROMs. Requirements Python 3 or Python 2.7 are required. If the ftfy package is installed, it w

Ben Phelps 5 Sep 26, 2022
Like Docker, but for Squeak. You know, for kids.

Squeaker Like Docker, but for Smalltalk images. You know, for kids. It's a small program that helps in automated derivation of configured Smalltalk im

Tony Garnock-Jones 14 Sep 11, 2022
36 key ergo split keyboard, designed around the Seeeduino Xiao platform

Slice36 Minimalist Split Keyboard 36 key ergo split keyboard, designed around the Seeeduino Xiao platform. Inspired by the Corne, Ferris, Ben Vallack'

54 Dec 21, 2022
A Kodi add-on for watching content hosted on PeerTube.

A Kodi add-on for watching content hosted on PeerTube. This add-on is under development so only basic features work, and you're welcome to improve it.

1 Dec 18, 2021
Superset custom path for python

It is a common requirement to have superset running under a base url, (https://mydomain.at/analytics/ instead of https://mydomain.at/). I created the

9 Dec 14, 2022
Herramienta para pentesting web.

iTell 🕴 ¡Tool con herramientas para pentesting web! Metodos ❣ DDoS Attacks Recon Active Recon (Vulns) Extras (Bypass CF, FTP && SSH Bruter) Respons

1 Jul 28, 2022
An OrpheusDL Tidal module

OrpheusDL - Tidal A Tidal module for the OrpheusDL modular archival music program Report Bug · Request Feature Table of content About OrpheusDL - Tida

Daniel 54 Dec 29, 2022
🍕 A small app with capabilities ordering food and listing them with pub/sub pattern

food-ordering A small app with capabilities ordering food and listing them. Prerequisites Docker Run Tests docker-compose run --rm web ./manage.py tes

Muhammet Mücahit 1 Jan 14, 2022
A collection of existing KGQA datasets in the form of the huggingface datasets library, aiming to provide an easy-to-use access to them.

KGQA Datasets Brief Introduction This repository is a collection of existing KGQA datasets in the form of the huggingface datasets library, aiming to

Semantic Systems research group 21 Jan 06, 2023
Find habits that genuinely increase your productivity

BiProductive Description This repository contains the application BiProductive, which analyzes the habits of the person, tests his productivity, and d

Rizvan Iskaliev 43 Jun 11, 2022
Check if Python package names are available on PyPI.

😻 isavailable Can I haz this Python package on PyPI? Check if Python package names are available on PyPI. Usage $ isavailable checks whether your des

Felipe S. S. Schneider 3 May 18, 2022
Generates images with semantic content from distribution A in the style of distribution B

A2B Generates images with semantic content from distribution A in the style of d

Richard Herbert 2 Dec 27, 2021