Rocky Mountain Ellipse¶
Rocky Mountain Ellipse (RME) is a software package designed to provide an explicit digital record of the metrological traceability of a measurement result. In other words, RME will allows users to build a record that describes how a measurement result can be related to a reference through a documented unbroken chain of calibrations, each contributing to the measurement uncertainty. To show the traceability of measurements, RME provides a flexible, explicit system to organize and annotate scientific data and data analysis workflows.Because measurement uncertainty is closely related to traceability, RME allows users to track how the uncertainty of a measurement results derives from other measurements by providing tools to facilitate measurement uncertainty propagation (linear finite-difference and Monte-Carlo) through arbitrary Python functions. The system is compatible with the BIPM Guide to the expression of uncertainty in measurement (GUM). RME is intended to be part of a FAIR software ecosystem that will facilitate re-use of code and data. This vision includes an online archive that could eventually store records of NIST’s entire traceability chain, and beyond. As part of that vision, this package focuses on the development of three core utilities:
RMEMeas and RMEProp for correlated uncertainty propagation using XArray.
AnnotatedArray to define xarray.DataArray structure specifications.
GroupSaveable for serializing heirarchical objects to HDF5.
Please see the documentation.
Note
RMEllipse is still in development. We expect to make changes that will break backward compatibility. Also, there are known bugs that we have not fixed yet. Specifically, we plan to re-write the Monte-Carlo uncertainty propagation algorithm in RMEProp. Please check back for updates. When we increment the version to 1.0, we expect that that version will be stable.
Installation¶
Install with pip
pip install rmellipse
Developer Tools¶
It is assumed you have the following programs installed on your computer.
uv for package management
git bash or similar terminal emulator to run shell scripts if you are on windows.
Clone the repo and run, from the root directory:
uv sync
This will generate the virtual environment for the package.
Install git pre-commit:
uv run pre-commit install
Running Local Tests¶
In a bash terminal, run:
tools/test.sh
tools/test.sh open
This should execute all the defined tests with pytest. In addition, the open command will open a webpage with detailed reports about code coverage.
Building Local Documentation¶
Clean the local documentation build (this needs to be run sometimes if you are modifying the documentation and it gets into a broken state). It will reset the build directories and the next call to build it will be completely from scratch.
tools/docs.sh clean
To build a copy of the current state of the documentation with your changes run:
tools/docs.sh html
To build the full documentation with tagged versions and the most recent stable and development changes (this takes a while and is usually only run as part of the release jobs) run:
tools/docs.sh html-multiversioned
To open the documentation (you may have to call open in a new console) run
tools/docs.sh serve
tools/docs.sh open
This will serve a local copy of the documentation on your local host, and the open command will launch your default web browser directly to that page. Currently, this web page is on port 8000.
Code Profiling¶
If you are writing a test script, you can run it in a code profile from the cloned directory. This will open a webpage to navigate the statistics of your tests script once it complete.
tools/profile.sh <path/to/script.py>
Important
In accordance with Guidance for NIST Researchers’ Use of AI Tools v1.0, the use of AI tools are disclosed. These code and documentation changes were created with the assistance of AI tool (ChatGPT Sol 5.6), developed by OpenAI. The AI tool was used, in accordance with the author’s instructions, to search, edit, modify, test, and document this codebase, as reflected in the diff(s) under this pull request. All content has been reviewed to ensure accuracy and originality.
Acknowledgements¶
The development of RMEllipse is partially funded through the CHIPS Metrology program. Our goal is to use it to disseminate RF calibration and uncertainty analysis techniques to monitor RF power delivered to plasma etching and deposition tools used in semiconductor manufacturing.