Metadata-Version: 1.1
Name: resonance
Version: 0.4.1
Summary: Learning mechanical vibrations through computation.
Home-page: https://github.com/moorepants/resonance/
Author: Jason K. Moore
Author-email: moorepants@gmail.com
License: CC-BY 4.0
Description: ========================================================================
        Resonance: Learning Mechanical Vibration Engineering Through Computation
        ========================================================================
        
        .. image:: https://img.shields.io/pypi/v/resonance.svg
           :target: http://pypi.org/project/resonance
        
        .. image:: https://readthedocs.org/projects/resonance/badge/?version=latest
           :target: http://resonance.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation Status
        
        .. image:: https://travis-ci.org/moorepants/resonance.svg?branch=master
           :target: https://travis-ci.org/moorepants/resonance
        
        Introduction
        ============
        
        This repository contains the interactive learning materials designed for the
        upper-level UC Davis engineering course on Mechanical Vibrations (ENG 122). The
        materials are designed with these ideas in mind:
        
        - That students can learn about mechanical vibrations engineering through
          "computational thinking" and "computational experimentation", i.e. actively
          interacting with a computer by writing code to simulate and analyze
          computational models and experimental data.
        - That the computer allows students to solve vibration engineering problems
          without knowing all of the mathematical theory a priori. This means that we
          can motivate students to dig deeper into the theory and by presenting it
          posteriori when the motivation is high. The students will be introduced to
          data analysis techniques to study vibrations before analytical techniques.
        - Students learn best by doing. The content is meant to used in class while the
          instructors act as a coach through the learning.
        - That each lesson should have a motivated real life example that drives the
          investigation.
        - Open access materials promote easy reuse, remixing, and dissemination.
        
        The current course website can be found at:
        
        https://moorepants.github.io/eng122/
        
        All of the Jupyter notebooks are rendered at:
        
        http://moorepants.github.io/resonance
        
        Learning Objectives
        ===================
        
        There are three broad learning objectives that we focus on in the course:
        
        1. Students will be able to analyze vibrational measurement data to draw
           conclusions about the measured system's vibrational nature and describe how
           the systems behaves vibrational.
        2. Students will be able to create simple mathematical and computational models
           of real vibrating systems that can be used to answer specific questions
           about the system by concisely demonstrating the vibrational phenomena.
        3. Students will be able to design a mechanical structure that has desirable
           vibrational behavior.
        
        Students that master these three core learning objectives will be well prepared
        to use mechanical vibration concepts, theories, and tools to solve engineering
        problems.
        
        For a more detailed topical outline with specific per-activity learning
        objectives see the `outline <outline.rst>`_.
        
        Assessment
        ==========
        
        The students will be assessed through a series of in- and out-of- class
        exercises that focus on individual lesson topics, two examinations, and on an
        individual open-ended vibration design project.
        
        Authors
        =======
        
        - Jason K. Moore, Faculty, Mechanical and Aerospace Engineering Department,
          University of California, Davis
        - Kenneth Lyons, Graduate Student, Mechanical and Aerospace Engineering
          Department, University of California, Davis
        
        License
        =======
        
        The contents of this repository are licensed under the CC-BY 4.0 license.
        
        Acknowledgements
        ================
        
        Much of this work has been made possible through the Undergraduate
        Instructional Innovation Program funds provided by the Association of American
        Universities (AAU) and Google which is administered by UC Davis's Center for
        Educational Effectiveness.
        
        This work is also made possible by the broad open source software stack that
        underpins the Scientific Python Ecosystem, in particular: Jupyter, NumPy,
        SymPy, SciPy, and matplotlib.
        
        Installation
        ============
        
        For users, you can create a conda environment called ``resonance`` by
        downloading the ``user-environment.yml`` file and typing the following at the
        command line::
        
           $ conda env create -f user-environment.yml
        
        This environment can be activated with::
        
           $ conda activate resonance
        
        To properly view the exercises you will need to enable the exercise2 notebook
        extension::
        
           (resonance)$ jupyter nbextension enable exercise2/main
        
        If you want to develop resonance, use the ``dev-environment.yml`` file::
        
           $ conda env create -f dev-environment.yml
           $ conda activate resonance-dev
        
        If you don't want to use our environments, you can use pip to install
        resonance::
        
           $ pip install resonance
        
Keywords: engineering vibrations mechanical
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Physics
