Skip to content

JupyterPhysSciLab/Documentation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

32 Commits
 
 
 
 
 
 

Repository files navigation

Jupyter Physical Science Lab Suite (JPSL)

Documentation for the Jupyter Physical Science Lab Suite of Packages.

Introduction | Try It | Quick Start | Packages | Packages being considerd | JPSL Project Repository | JPSL Documentation Repository | License

Introduction

The key goals of this suite of packages is to provide:

  1. an open source electronic laboratory notebook that is practical in physical science laboratories where data is collected by hand, from instrumentation and sensors;
  2. the ability to run on minimal hardware (things like the Raspberry Pi) to make it affordable for educational use;
  3. adaptability, allowing for use in a variety of teaching situations;
  4. GUI elements that allow students in introductory courses without programming experience to collect data and analyze it, while also facilitating scaffolding learning to write data analysis code/scripts in more advanced course;
  5. tools for instructors allowing them to create worksheets or more open-ended assignments (there is some potential feature overlap with nbgrader, but nbgrader tools are aimed more at math and programming assignments);
  6. ability to generate compact pdf formatted "reports" for grading;
  7. easy ways to have students analyze data while properly tracking units and what analysis was done, thus facilitating grading and trouble-shooting of student work.

There are two basic flavors of this suite of packages: student; and instructor. The instructor flavor includes tools for generating content in worksheets that students cannot edit. As well as ways to control what is displayed to the students and in the final version submitted for grading. The student version purposely leaves out the tools that allow unlocking of locked cells in a notebook, so that the instructor can include unchanging instructions, examples and questions.

Try it

You can try the parts of Jupyter Physical Science lab without installing anything. The packages can be run in the cloud. Links to do this are provided on the Github pages for each package. It is recommended that you start with JPSLInstructor, which includes all the supported packages.

Quick Start

  1. Install python on your machine, if necessary.
    1. Check current system python install by opening a command line terminal and issuing the command python3 --version. If it is >= 3. 7 you can use it. Otherwise, follow the next step to install a newer version.
    2. Get the installer for your computer from python.org. Follow the instructions for installing on your system.
  2. Install a tool for managing and using virtual environments. This allows you to have multiple independent sets (virtual environments) of python packages installed.
    1. I recommend you use this so that you can have both an "instructor" and "student" environment for testing.
    2. I personally like using pipenv. You can install it using the command pip3 --user install pipenv. On Windows you will probably have to do python3 -m pip --user install pipenv. See the website for more information.
  3. Set up an instructor work environment.
    1. Create a directory to contain your virtual environment and navigate into it (in *nix: cd path-to-directory).
    2. Create the empty virtual environment pipenv shell (on Windows python3 -m pipenv shell). This will create the environment, activate it and leave you inside it. WARNING: on Windows I have seen it move you to another directory. If it does this navigate back using the cd command.
    3. Still within the environment use pip to install the JPSLInstructor pseudo package pip install JPSLInstructor. This will take a while to run. There are a lot of packages to download and install.
    4. Example notebooks are not installed by pip. You should download the JPSLInstructor pseudo package as a zip file and extract the Examples folder into the directory for this virtual environment.
    5. To work with the software launch the jupyter notebook with the command jupyter lab (for the complex user interface) or juptyer notebook (for the simplified user interface). This will launch a local jupyter server on your machine and open a page connected to it in your web browser (Chrome and Firefox work best).
    6. Open an example notebook to try things.
    7. After quiting the Jupyter notebook server you can exit the virtual environment with the command exit.
  4. Set up a student work environment for testing.
    1. Create a directory to contain your virtual environment and navigate into it (in *nix: cd path-to-directory).
    2. Create the empty virtual environment pipenv shell. This will create the environment, activate it and leave you inside it.
    3. Still within the environment use pip to install the JPSLStudent pseudo package pip install JPSLStudent. This will take a while to run. There are a lot of packages to download and install.
    4. To work with the software launch the jupyter notebook with the command juptyer notebook (the simplified interface is recommended most use with students).
    5. Copy notebooks you want to see from a student perspective into this directory.
    6. After quiting the Jupyter notebook server you can exit the virtual environment with the command exit.

Packages

(Under active development, please try and send feedback)

The packages are available from PyPi (using pip for installation) or by installing from these repositories. The packages are broken up to allow using only the tools necessary.

  • jupyter-datainputtable provides tools for generating a GUI table into which data can be typed and the data will survive clearing of the cell outputs from a notebook.
  • jupyter-instructortools provides menu based tools for locking and unlocking text (Markdown) and code cells, inserting tables, some boilerplate language, etc.
  • jupyter-pandas-GUI provides jupyter widget based GUI code composers for tasks such as calculating a new column in a Pandas DataFrame, making a scatter or line plot from data in a DataFrame, or fitting data in a DataFrame.
  • JupyterPiDAQ provides tools for interactive data collection using A/D boards and visualization of that data, presently supports specific boards attached to Raspberry Pi 3B+ or above and sensors connected to Vernier LabQuest interfaces.
  • jupyterpidaq_menu provides a menu of useful commands for initiating data collections and analyzing data.
  • JPSL_Tools_Menu provides a convenience menu with access to documentation on the parts of the Jupyter Physical Science Lab and menu items to insert common initialization code, commands to activate each tool and control hiding of cells for printing.
  • Algebra_with_SymPy provides a definition for an equation with a lhs and a rhs. This tool applies operations to both sides of the equation simultaneously, just as students are taught to do when attempting to isolate (solve for) a variable. Thus the statement Equation/b yields a new equation Equation.lhs/b = Equation.rhs/b. This facilitates clearly documented symbolic algebraic manipulations and calculations with units included.
  • Pseudo Packages

Packages being considered

These are packages that are under development elsewhere, but might be included if there is interest:

  • DeltaSymbol allows adding a symbol in SymPy that displays as the typeset ΔX in Jupyter notbooks. Where ΔX is the common abbreviation for final(X) - initial (X).
  • jupyter-wysiwyg provides a what you see is what you get mode for Markdown/Richtext cells activated by clicking a button.
  • ipysketch. Tool for making and embedding sketches in a notebook.
  • ipysheet. Tool that provides a widgets based alternative to jupyter-datainputtable . To use, data persistence will have to be addressed.
  • WYSIWYGcell provides what you see is what you get text edit cells in Jupyter notebooks, but involves significant changes to the Jupyter notebook code, thus will either require providing a fully custom Jupyter notebook or monkey patching a current installation.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

Copyright - Jonathan Gutow, 2021 - 2024.