nanonis-xarray 0.1.6

Read a Nanonis spectroscopy .dat file into a xarray Dataset

Xarray plugin to read Nanonis spectroscopy .dat files

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 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) int64 24B 1 2 3
  * direction  (direction) object 16B 'bw' 'fw'

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 attrs nested dictionary:

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

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

>>> data.attrs["NanonisMain"]["RT Frequency"]
<Quantity(10000.0, 'hertz')>
>>> data.attrs["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:

• nanonispy2
• xarray-nanonis
• ... and many more.

How to cite

Cite nanonis-xarray in your published work using the metadata in CITATION.cff, or this general BibTeX entry:

@misc{Peronio_nanonis-xarray_2025,
title = {nanonis-xarray},
author = {Peronio, Angelo},
url = {https://github.com/angelo-peronio/nanonis-xarray},
doi = {10.5281/zenodo.17095214},
year = {2025},
month = {5}
}

Specific DOIs for each released version are listed on Zenodo, but are not included in CITATION.cff due to a limitation of Zenodo itself.