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
JHBuild is a tool designed to ease building collections of source packages, called “modules”.

JHBuild README JHBuild is a tool designed to ease building collections of source packages, called “modules”. JHBuild was originally written for buildi

GNOME Github Mirror 46 Nov 22, 2022
Python solutions to Codeforces problems

CodeForces This repository is dedicated to my Python solutions for CodeForces problems. Feel free to copy, contribute and/or comment. If you find any

Shukur Sabzaliev 15 Dec 20, 2022
Reso is a low-level circuit design language and simulator, inspired by things like Redstone, Conway's Game of Life, and Wireworld.

Reso Reso is a low-level circuit design language and simulator, inspired by things like Redstone, Conway's Game of Life, and Wireworld. What is Reso?

Lynn 287 Nov 26, 2022
A simple website-based resource monitor for slurm system.

Slurm Web A simple website-based resource monitor for slurm system. Screenshot Required python packages flask, colored, humanize, humanfriendly, beart

Tengda Han 17 Nov 29, 2022
Simple Python script I use to manage and build my Reflux themes.

Simple Python script I use to manage and build my Reflux themes. Built for personal use, but anyone can easily fork and tweak to suit thier needs.

Ire 3 Jan 25, 2022
Convert ldapdomaindump to Bloodhound

ldd2bh Usage usage: ldd2bh.py [-h] [-i INPUT_FOLDER] [-o OUTPUT_FOLDER] [-a] [-u] [-c] [-g] [-d] Convert ldapdomaindump to Bloodhoun

64 Oct 30, 2022
Hotpile: High Order Turing Machine Language Compiler

Hotpile: High Order Turing Machine Language Compiler Build and Run Requirements: Python 3.6+, bison, flex, and GCC installed. Needs to be run under UN

Jiang Weihao 4 Dec 29, 2021
Serverless demo showing users how they can capture (and obfuscate) their Lambda payloads in Datadog APM

Serverless-capture-lambda-payload-demo Serverless demo showing users how they can capture (and obfuscate) their Lambda payloads in Datadog APM This wi

Datadog, Inc. 1 Nov 02, 2021
AminoAutoRegFxck/AutoReg For AminoApps.com

AminoAutoRegFxck AminoAutoRegFxck/AutoReg For AminoApps.com Termux apt update -y apt upgrade -y pkg install python git clone https://github.com/LilZev

3 Jan 18, 2022
A data engineering project with Kafka, Spark Streaming, dbt, Docker, Airflow, Terraform, GCP and much more!

Streamify A data pipeline with Kafka, Spark Streaming, dbt, Docker, Airflow, Terraform, GCP and much more! Description Objective The project will stre

Ankur Chavda 206 Dec 30, 2022
An esoteric programming language that supports concurrency, regex, and web requests.

The Hofstadter Esoteric Programming Language Hofstadter's Law: It always takes longer than you expect, even when you take into account Hofstadter's La

Austin Henley 19 Dec 27, 2022
Custom Python code for calculating the Probability of Profit (POP) for options trading strategies using Monte Carlo Simulations.

Custom Python code for calculating the Probability of Profit (POP) for options trading strategies using Monte Carlo Simulations.

35 Nov 22, 2022
Objetivo: de forma colaborativa pasar de nodos de Dynamo a Python.

ITTI_Ed01_De-nodos-a-python ITTI. EXPERT TRAINING EN AUTOMATIZACIÓN DE PROCESOS BIM: OFFICIAL DE AUTODESK. Edición 1 Enlace al Master Enunciado: Traba

1 Jun 06, 2022
Suite of tools for retrieving USGS NWIS observations and evaluating National Water Model (NWM) data.

Documentation OWPHydroTools GitHub pages documentation Motivation We developed OWPHydroTools with data scientists in mind. We attempted to ensure the

36 Dec 11, 2022
A tool for fixing inconsistent timestamp metadata (atime, ctime, and mtime).

Mtime Fixer Mtime Fixer is a tool for fixing inconsistent timestamp metadata (atime, ctime, and mtime). Sometimes timestamp metadata of folders are in

Halit Şimşek 2 Jan 11, 2022
A Non profit app built on top of Frappe framework & ERPNext

Non Profit A Non profit app built on top of Frappe framework & ERPNext. People who change the world need the tools to do it! The Non Profit Modules of

Frappe 16 Nov 17, 2022
Tools Elit Adalah Sebuah Script Crack Yang Wajib Tap Yes...

Tools Elit Adalah Sebuah Script Crack Yang Wajib Tap Yes...

Risky [ Zero Tow ] 10 Apr 07, 2022
This code makes the logs provided by Fiddler proxy of the Google Analytics events coming from iOS more readable.

GA-beautifier-iOS This code makes the logs provided by Fiddler proxy of the Google Analytics events coming from iOS more readable. To run it, create a

Rafael Machado 3 Feb 02, 2022
Stopmagic gives you the power of creating amazing Stop Motion animations faster and easier than ever before.

Stopmagic gives you the power of creating amazing Stop Motion animations faster and easier than ever before. This project is maintained by Aldrin Mathew.

Aldrin's Art Factory 67 Dec 31, 2022
The code behind sqlfmt.com, a web UI for sqlfmt

The code behind sqlfmt.com, a web UI for sqlfmt

Ted Conbeer 2 Dec 14, 2022