Bruker native formats¶

A separate, dependency-free reader opens Bruker EPR native files directly, without converting to CSV first. It is numpy-only (no Qt, no extra packages) and hardware-agnostic, so it works for any Bruker trace — CW spectra, T1/T2 relaxation, ESEEM, DEER, etc.

import atomize.general_modules.bruker_opener as bruker

reader = bruker.Bruker_Opener()
data = reader.open('my_measurement.DSC')

Two format families are supported:

BES3T — Xepr / Elexsys (.DSC ASCII descriptor + .DTA binary, plus optional .XGF/.YGF companions for non-linear axes). The modern pulse-EPR format; complex datasets (IKKF=CPLX) carry quadrature data and map onto an I/Q pair.
ESP / WinEPR — older EMX (.par ASCII + .spc binary). WinEPR (PC) is little-endian float32; ESP (workstation) is big-endian int32. Mostly CW.

Functions¶

Bruker_Opener()¶

reader = bruker.Bruker_Opener()

Creates the reader. All methods below are called on it.

open(path)¶

data = reader.open(path)    # -> dict

Opens a Bruker file and dispatches on the extension: .dsc/.dta/.xgf/.ygf → read_bes3t(); .par/.spc → read_winepr(). You may pass either member of a pair (the descriptor or the binary) — the companion file is found automatically. Raises ValueError for an unrecognized extension.

The returned dict:

Key	Description
`format`	`'BES3T'` or `'ESP/WinEPR'`
`ndim`	`1` or `2`
`x`	The X (within-trace) abscissa array
`x_name`, `x_unit`	X axis name and unit (from the descriptor)
`y`	The Y (indirect) abscissa array (2D only)
`y_name`, `y_unit`	Y axis name and unit
`complex`	`True` if the data carry quadrature (I/Q)
`data`	Raw shaped array — `(nx,)` for 1D, `(ny, nx)` for 2D; complex when applicable
`channels`	`[(label, ndarray), …]`: `[('real', …), ('imag', …)]` for complex data, else `[('intensity', …)]`
`params`	The parsed descriptor as a `{key: value}` dict

channels is the convenient form the Data Treatment tools register; data is the raw array for direct numerical work.

read_bes3t(path) / read_winepr(path)¶

data = reader.read_bes3t(path)     # BES3T (.DSC/.DTA)
data = reader.read_winepr(path)    # ESP/WinEPR (.par/.spc)

The per-format readers behind open(); both return the same dict described above. Call them directly when you already know the format, otherwise prefer open().

import atomize.general_modules.bruker_opener as bruker
import atomize.general_modules.general_functions as general

reader = bruker.Bruker_Opener()
res = reader.open('echo_decay.DSC')
if res['complex']:
    re = dict(res['channels'])['real']
    general.plot_1d('Bruker', res['x'], re, xname='Time', xscale=res['x_unit'])