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Read a Nanonis spectroscopy .dat file into a xarray Dataset

Project description

Xarray plugin to read Nanonis spectroscopy .dat files

pypi conda-forge pypi downloads license python ci pre-commit.ci status codecov SPEC 0 — Minimum Supported Dependencies ruff DOI

nanonis-xarray is a xarray plugin to read spectroscopy measurements saved in text format (.dat) by a Nanonis Mimea SPM control system from SPECS Surface Nano Analysis GmbH.

The data is read into a xarray.Dataset, where each measured channel (tunnelling current, AFM oscillation amplitude, …) is a xarray.DataArray with up to three dimensions:

  • The independent variable of the measurement, such as sample bias voltage or tip z position;
  • The sweep number, if the measurement has been repeated multiple times;
  • The sweep direction (forward or backward), if the independent variable has been swept in both directions.
>>> import xarray as xr

>>> data = xr.open_dataset("tests/data/z.dat")
>>> data.coords
Coordinates:
  * z_rel      (z_rel) float64 2kB [m] -2.1e-10 -2.065e-10 ... 4.865e-10 4.9e-10
  * sweep      (sweep) uint32 12B 1 2 3
  * direction  (direction) category 18B fw bw

pint-xarray is used to associate a physical unit to each channel, unless xr.open_dataset() is called with quantify_vars=False:

>>> data["current"].pint.units
<Unit('ampere')>

The header of the measurement is stored in the header nested dictionary:

>>> data.header["Z Spectroscopy"]["Number of sweeps"]
3
>>> data.header["Z Spectroscopy"]["backward sweep"]
True

Physical quantities are stored as pint.Quantity, timestamps as datetime.datetime, and paths as pathlib.Path:

>>> data.header["NanonisMain"]["RT Frequency"]
<Quantity(10000.0, 'hertz')>
>>> data.header["Date"]
datetime.datetime(2015, 3, 27, 11, 49, 5)

🚧 Work in progress 🚧

This library is under development: expect breaking changes. Nanonis binary formats (.sxm, .3ds) are currently not supported, and can be read by similar projects:

How to cite

Cite nanonis-xarray in your published work using the metadata in CITATION.cff. Specific DOIs and BibTeX entries for each released version can be found on Zenodo.

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