Materials data, with context

Open & extensible materials data file with in-built provenance

pip install vector-mtrl
go to appgo to code
.mtrlrun-0142.spaftir-009.sparun-003.spasamples.csvresults.xlsx.mtrlrun-0142.spaftir-009.sparun-003.spasamples.csvresults.xlsx

A file to bring it all together

Your lab. Connected.

Bring files from different instruments together—without changing the lab you already have.

A cursor carries files from any instrument onto one colour-shifting orb and they come back as one tableA cursor picks each file up from the pile (.spa, .csv, .txt, .tri, .xlsx) and carries it onto a translucent orb, setting it down on top of the orb. The file dissolves in as the orb's body slowly diffuses with its colour, then every file comes back out and settles, checked, in a pile beside where it started, and its clean table sheet joins the stack on the right.A cursor carries files from any instrument onto one colour-shifting orb and they come back as one tableA cursor picks each file up from the pile (.spa, .csv, .txt) and carries it onto a translucent orb, setting it down on top of the orb. The file dissolves in as the orb's body slowly diffuses with its colour, then every file comes back out and settles, checked, in a pile beside where it started, and its clean table sheet joins the stack below.

Provenance, built in.

Every processing step is recorded as it happens, so a result can be traced back to the instrument file it came from—and verified before use.

A pipeline edited over time, with every revision kept in its historyA pipeline is edited over time: raw data is smoothed, fitted and reported. A Smooth step is inserted before the fit, so the pre-processed data is what gets fitted, and a Baseline step is then added between the two and removed again, leaving Raw data, Smooth, Peak fit and Report. A git-style history beside it commits each revision, and removing Baseline leaves its commit on a dimmed branch marked reverted rather than erasing it.

Open and extensible by design.

Start with the core Python library and add what your workflow needs: separate packages for instrument input, resampling, exports and plots.