Python-based tools for simple navigation calculations.

See http://slott56.github.io/navtools/.

The NavTools distribution includes the following.

• navtools. The Python code which gets installed.
• igrf11coeffs.txt. Data used to compute magnetic deviation. This is from http://www.ngdc.noaa.gov/IAGA/vmod/igrf11coeffs.txt
• docs. The RST-formatted documentation files.

Clone the Git repository (or download the .zip archive).

git clone https://github.com/slott56/navtools

Run the setup.py to install the package.

python setup.py install

For details, see http://slott56.github.io/navtools/installation.html. This is not available in PyPI, so a simple python -m pip install navtools isn't supported.

There are several applications that process .gpx or .csv files:

• Route Planning. Computes a schedule for arrival at the various waypoints. This, in turn, can be used to build a float plan to share with others.
• Track Analysis. Annotates a historical log with distance and speed.
• OpenCPN Conversion. Transforms an OpenCPN route planning table into more useful content for spreadsheet use and float plan creation.
• Waypoint Merge. Determines the differences among waypoints from multiple sources.

These provide a number of navigation planning and analysis capabilities. These are not intended for use while sailing, however, that is better done by tools like OpenCPN, iNavX, and chartplotters.

While there is a lot of file processing, the essence of route planning is thinking and tinkering the speeds, destinations, departure times, and the like. While a spreadsheet is useful, Jupyter Lab is -- perhaps -- much better.

The idea is to create Notebook with the plan details. In some cases, you may even want to create the seed for a data collection log book that can be updated with details of the actual voyage.

You'll need to start JupyterLab with the navtools directory on the Python path.

• Install navtools.
• PYTHONPATH=/path/to/navtools jupyter lab to start the lab with the extra path setting. Often this becomes PYTHONPATH=$(pwd) jupyter lab if you change to the navtools checkout.

It's best to create a unique notebook for each specific voyage. When this involves multiple legs, then there may be multiple float plans generated from a single notebook source document.

There are two publication options for the plan details.

1. A cell of the notebook creates a Markdown file with boilerplate and itinerary for a specific plan. This is processed through pandoc. This is a pleasant approach because other formats (like plain text) can be made from the Markdown source.

   pandoc --from markdown+pipe_tables "plan.md" -o "plan.pdf"

2. A separate notebook is built from boilerplate and itinerary. This is processed through NBConvert.

   jupyter nbconvert "plan.ipynb" --to pdf --no-input

The results are similar, and are small PDF's that can be shared widely.

cd docs
make html

The development environment relies on PlantUML to create the diagrams. See https://plantuml.com.

The Sphinx-PlantUML plugin is used to transform .. uml:: markup into a diagram.

• Use conda to install graphviz, as well as installing the plantuml-markdown tools. and the Sphinx-PlantUML extension. The markdown_py application can create an HTML draft of a Markdown doc. It needs to be installed separately, if this is needed.

  conda install graphviz
  python -m pip install plantuml-markdown sphinxcontrib-plantuml

• Older PlantUML versions require a GRAPHVIZ_DOT environment variable to name the conda virtual environment where graphviz was installed. The macOS and Linux users can update ~/.zshrc or ~/.bashrc file, depending on which shell is in use. Windows users should set their system environment variables.
• It may be necessary to create a plantuml shell script in /usr/local/bin. See https://github.com/mikitex70/plantuml-markdown for details on installation. This may be done automatically by the plantuml-markdown installation. If not, it needs to be added.

A tool like https://pypi.org/project/py2puml/ can be used to create PlantUML text from the source code.

Additionally, plantuml can also be incorporated into a markdown processing plug-in used by the PyCharm IDE. The plugin depends on graphviz.

• Add the Markdown tool to PyCharm.
• In the preferences for Markdown, install and enable PlantUML.

While this can be useful for documents created with Markdown, this project's documentation is in RST.