Loading Data

SpinLab can import data from a wide range of spectrometer formats. The universal entry point is the sl.load() function — in most cases it detects the file format automatically from the file extension or directory contents.

import spinlab as sl
data = sl.load("path/to/my/data")

The result is always a The SpinData Object ready for processing.

Automatic Format Detection

SpinLab inspects the file extension (or the contents of a directory) to determine the format. The table below shows which formats are detected automatically:

Spectrometer / Software	Extension / Indicator	Format string
Bruker Xepr / Elexsys (BES3T)	`.DSC`, `.DTA`, `.YGF`	`"xepr"`
Bruker WinEPR / ESP	`.par`, `.spc`	`"winepr"`
Bruker TopSpin (raw)	directory with `acqus`	`"topspin"`
Bruker TopSpin (processed)	directory with `procs`	`"topspin pdata"`
Varian / Agilent VnmrJ	`.fid` directory	`"vnmrj"`
JEOL Delta	`.jdf`	`"delta"`
Magritek Prospa	`.1d`, `.2d`, `.3d`, `.4d`	`"prospa"`
FeMi SpecMan4EPR	`.d01`, `.exp`	`"specman"`
Tecmag TNMR	`.tnt`	`"tnmr"`
RS2D	`.xml`, `.dat`	`"rs2d"`
VNA (S-parameters)	`.s1p`, `.s2p`	`"vna"`
SpinLab HDF5	`.h5`	`"h5"`
CSV	(use `sl.load_csv` directly)	—

If autodetection fails, pass the format explicitly:

data = sl.load("path/to/data", data_format="topspin")

Format-by-Format Examples

Bruker Xepr / Elexsys (BES3T)

Point sl.load() at the .DTA or .DSC file. Axis files (.XGF, .YGF, .ZGF) are loaded automatically if present:

data = sl.load("experiment/1D_CW.DTA")
print(data)

Bruker WinEPR / ESP

Pass the .par or .spc file:

data = sl.load("spectrum.par")

Bruker TopSpin (raw FID / SER)

Pass the experiment directory (the folder containing acqus). SpinLab reads the fid or ser binary file and applies the acquisition parameters automatically:

data = sl.load("path/to/topspin/1/")

Bruker TopSpin (processed pdata)

Pass the pdata/1 subdirectory (the folder containing procs):

data = sl.load("path/to/topspin/1/pdata/1/")

Varian / Agilent VnmrJ

Pass the .fid directory:

data = sl.load("experiment.fid/")

JEOL Delta

Pass the .jdf file:

data = sl.load("spectrum.jdf")

Magritek Prospa

Pass the .1d (or .2d, .3d, .4d) file:

data = sl.load("experiment.1d")

FeMi SpecMan4EPR

Pass the .d01 or .exp file:

data = sl.load("experiment.d01")

CSV Files

CSV files are not handled by sl.load() — use sl.load_csv() directly. By default it expects columns: time (col 0), real (col 1), imaginary (col 2):

data = sl.load_csv(
    "data.csv",
    tcol=0,      # column index for the time/x axis
    real=1,      # column index for real part
    imag=2,      # column index for imaginary part
    skiprows=1,  # skip one header row
    delimiter=","
)

SpinLab HDF5 (`.h5`)

HDF5 is SpinLab's own storage format (see Saving Data). Load it exactly like any other file:

data = sl.load("experiment.h5")

If the .h5 file contains multiple datasets (saved as a dictionary), a Python dictionary of SpinData objects is returned:

workspace = sl.load("workspace.h5")
data_nmr = workspace["nmr"]
data_epr = workspace["epr"]

Loading Multiple Files

Pass a list of paths together with a dim name and a coord array to concatenate several files along a new dimension in one step. This is useful for, e.g., a power series or a time series:

import numpy as np

paths  = ["power_1mW.DTA", "power_5mW.DTA", "power_10mW.DTA"]
powers = np.array([1e-3, 5e-3, 10e-3])   # in Watts

data = sl.load(paths, dim="power", coord=powers)
print(data.dims)    # ['B0', 'power']
print(data.shape)   # (2250, 3)

The individual spectra are stacked along the new "power" dimension. The coord array must have the same length as the list of paths.

Saving Data

Use sl.save() to write a SpinData object to an HDF5 file. HDF5 preserves the full object — values, axes, all attributes, and the processing audit log:

sl.save(data, "processed_data.h5")

To save multiple datasets in a single file, pass a dictionary:

workspace = {"nmr": data_nmr, "epr": data_epr}
sl.save(workspace, "workspace.h5")

Note

By default sl.save() will raise an error if the file already exists. Pass overwrite=True to allow overwriting:

sl.save(data, "processed_data.h5", overwrite=True)