This is a simple tool that constructs a calibration curve using known x and y values from standards, and backout the x value for an unknown based on its measured y signal.
Features
- Given x and y, creates calibration curve and finds linear portion and limits of linearity
- Given y of an unknown, interpolates to find x
- Computes interpolation error
Development requires Docker and Make on your host system. Everything else is taken care of inside the Docker container.
Spin up your container using the provided docker-compose.yml file and Makefile by running
make image. This creates an image with a correct git configuration for your user, which makes it
easy to release. All of the commands you should need to run are defined the Makefile as targets.
All of the targets except for image, are meant to be run inside the Docker container, but can be
run from the host machine by having -ext appended to them. For example, to run tests, you could
either call make test from a shell inside the container, or make test-ext from the host.
Dependencies are managed through the conda tool and defined in
environment.yml. All new dependencies must be specified with a version, for a reproducible build
environment.
All pull requests are run through the Travis CI process specified in .travis.yml and must pass
all tests before being accepted.
Deployment of tagged commits happens to PyPI automatically via Travis CI. To bump and deploy a new
version directly, you must have access to write to the master branch. Run make bump/[foo]-ext,
where [foo] is major, minor, or patch. Then git push origin --tags master. If
you do not have access to the master branch, do the same thing, but in a separate branch, and make
a pull request.