pitchplots 1.4.2

A package containing representation tools for musical purposes

pitchplots

library plotting charts for different tonal representations

Getting Started

The program consist in the following files: functions.py, reader.py, modified_musicxml_parser.py, parser.py and static.py

Prerequisites

What things you need to install the software and how to install them

You will need python on your computer and the following libaries: matplotlib, pandas and numpy

note that if you are using anaconda, these libraries are already installed

Installing

You can download the pitchplots package on pypi with pip using the following command in the prompt:

python3 -m pip install pitchplots

or if you're using anaconda prompt

pip install pitchplots

Running the tests

you can first try to parse xml/musicScore xml files to csv or DataFrame, that is the Gymnopédie from Sati with:

import pitchplots.parser as ppp

# If no filepath is specified, will automatically charge data_example.mxl
df_data_example = ppp.xml_to_csv(save_csv=True)

then you can try the static module by passing csv files or Dataframe:

import pitchplots.static as pps

pps.tonnetz(df_data_example)

or

import pitchplots.static as pps

pps.circle('csv/data_example.csv')

to try the dynamic videos:

import pitchplots.dynamic as ppd

ppd.tonnetz_animation(df_data_example)

Authors

• Timothy Loayza, Fabian Moss

Use of magenta's code

The modified_musicxml_parser.py file is taken from the magenta project and has been modified. Therefore the modifications are listed in the magenta_musicxml_code_modifications.md file and there is the magenta_LICENSE.md.

License

This project is licensed under the MIT License - see the LICENSE.md file for details