IO

Load & Save

spinlab.io.load.autodetect(test_path, verbose=False)

Automatically detect data format

Parameters:

test_path (str) -- Test directory
verbose (bool) -- If true, print output for debugging

Returns:

Data format as string

Return type:

str

spinlab.io.load.load(path, data_format=None, dim=None, coord=[], verbose=False, *args, **kwargs)

Import data from different spectrometer formats

Parameters:

path (str, list) -- Path to data directory or list of directories
data_format (str) -- format of spectrometer data to import (optional). Allowed values: "prospa", "topspin", "delta", "vnmrj", "tnmr", "specman", "xenon", "xepr", "winepr", "esp", "h5", "power", "vna", "cnsi_powers", "rs2d"
dim (str) -- If giving directories as list, name of dimension to concatenate data along
coord (numpy.ndarray) -- If giving directories as list, coordinates of new dimension
verbose (bool) -- If true, print debugging output
*args -- Additional positional arguments passed to the format-specific import function.
**kwargs -- Additional keyword arguments passed to the format-specific import function.

Returns:

Data object

Return type:

data (slData)

Examples

Load a data file

>>> data = sl.load('Path/To/File')

Load a list of files and concatenate down a new dimension called 't1' with coordinates

>>> data = sl.load(['1/data.1d','2/data.1d','3/data.1d'], dim = 't1', coord = np.r_[0.1,0.2,0.3])

spinlab.io.load.load_file(path, data_format=None, verbose=False, *args, **kwargs)

Import data from different spectrometer formats

Parameters:

path (str) -- Path to data directory or file
data_format (str) -- Format of spectrometer data to import (optional). Allowed values: "prospa", "topspin", "delta", "vnmrj", "tnmr", "specman", "xenon", "xepr", "winepr", "esp", "h5", "power", "vna", "cnsi_powers"
verbose (bool) -- If true, print additional debug outputs
*args -- Additional positional arguments passed to the format-specific import function.
**kwargs -- Additional keyword arguments passed to the format-specific import function.

Returns:

Data object

Return type:

data (slData)

spinlab.io.save.autodetect(test_name)

Detect the save format from the file extension.

Parameters:: test_name (str) -- File path or name including extension.
Returns:: Detected format string — "h5" for HDF5 or "mat" for MATLAB.
Return type:: str
Raises:: TypeError -- If the extension is not recognized.

spinlab.io.save.save(data_object, filename, save_type=None, *args, **kwargs)

Save data to h5 format

Parameters:

data_object (SpinData) -- sldata object to save
filename (str) -- name of file, must include extension .h5
save_type (str) -- Type of file to save (optional). Allowed values: "h5"

Returns:

none

spinlab.io.h5.load_h5(path, *args, **kwargs)

Returns Dictionary of slDataObjects

Parameters:: path (str) -- Path to h5 file
Returns:: workspace object with data
Return type:: sldata_collection

spinlab.io.h5.read_dict(sldata_group)

Read a plain Python dictionary from an HDF5 group.

Parameters:: sldata_group (h5py.Group) -- HDF5 group containing a serialized dictionary.
Returns:: Dictionary of attributes stored in the HDF5 group.
Return type:: dict

spinlab.io.h5.read_sldata(sldata_group)

Read a SpinData object from an HDF5 group.

Reconstructs a complete SpinData object including values, dimension labels, axis coordinates, experiment attributes, SpinLab attributes, and the processing audit log.

Parameters:: sldata_group (h5py.Group) -- HDF5 group containing a serialized SpinData object.
Returns:: Reconstructed data object.
Return type:: SpinData

spinlab.io.h5.save_h5(dataDict, path, overwrite=False)

Save workspace in .h5 format

Parameters:

dataDict (dict) -- sldata_collection object to save.
path (str) -- Path to save data
overwrite (bool) -- If True, h5 file can be overwritten. Otherwise, h5 file cannot be overwritten

spinlab.io.h5.write_dict(slDataGroup, slDataObject)

Writes dictionary to h5 file

Parameters:

slDataGroup (h5py.Group) -- h5 group to write attrs dictionary
slDataObject (SpinData) -- SpinData object to write

spinlab.io.h5.write_sldata(slDataGroup, slDataObject)

Takes file/group and writes slData object to it

Parameters:

slDataGroup -- h5 group to save data to
slDataObject -- sldata object to save in h5 format

spinlab.io.load_csv.load_csv(filename, tcol=0, real=1, imag=2, skiprows=0, maxrows=-1, convert_time=<function <lambda>>, convert_data=<function <lambda>>, **kwargs)

Load data from a CSV file

Parameters:

filename (str) -- String or path like file that is read
tcol (int) -- column index for time data (default=0), None = not applicable, will count from 0 to npoints and then apply covert_time!
real (int) -- column index for real part (default=1), None = not applicable, will be set to zero
imag (int) -- column index for imaginary part (default=2), None = not applicable, will be set to zero
skiprows (int) -- number of rows to skip at beginning (default=0)
maxrows (int) -- if this is larger than zero, read at most maxrows rows. (default: -1)
convert_time (callable) -- callable that converts the time strings to a number (default: replaces , with .)
convert_data (callable) -- callable that converts data to a number (default: replaces , with .)
delimiter (str) -- optional, sets the delimiter in the csv file (default ; )
dims (str,list) -- optional, sets name for dimension (default: ["t2"])
object (**kwargs are forwarded to csv.reader)

Returns:

Data object with values,coords and dim

Return type:

data (slData)

Examples

data=load_csv('csv_arrLNA_data.csv',imag=2,skiprows=1)

Bruker

Functions to import Bruker EPR data

spinlab.io.bes3t.import_bes3t(path)

Import Bruker BES3T data and return sldata object

Parameters:: path (str) -- Path to either .DSC or .DTA file
Returns:: SpinData object containing Bruker BES3T data
Return type:: bes3t_data (object)

spinlab.io.bes3t.load_dsc(path)

Import contents of .DSC file

Parameters:: path (str) -- Path to .DSC file
Returns:: dictionary of parameters
Return type:: attrs (dict)

spinlab.io.bes3t.load_dta(path_dta, path_xgf=None, path_ygf=None, path_zgf=None, attrs={})

Import data from .DTA file. Uses .DSC and .XGF, .YGF, or .ZGF files if they exist

Parameters:

path_dta (str) -- Path to .DTA file
path_xgf (str) -- path to .XGF file for 1D data with nonlinear axis, "none" otherwise
path_ygf (str) -- path to .YGF file for 2D data, "none" if 1D or linear y axis
path_zgf (str) -- path to .ZGF file for 3D data, "none" if 1D/2D or linear z axis
attrs (dict) -- dictionary of parameters

Returns:

Spectrum for 1D or spectra for 2D dims (list) : dimensions coords (ndarray) : coordinates for spectrum or spectra attrs (dict) : updated dictionary of parameters

Return type:

values (ndarray)

spinlab.io.bes3t.load_gf_files(path, axis_type='', axis_format='', axis_points=1, axis_min=1, axis_width=1, endian='')

Import data from .XGF, .YGF, or .ZGF files

Parameters:

path (str) -- Path to ._GF file
axis_type (str) -- linear or nonlinear
axis_format (str) -- format of file data
axis_points (int) -- number of points in axis
axis_min (float) -- minimum value of axis
axis_width (float) -- total width of axis
endian (float) -- endian of data

Returns:

axis coordinates

Return type:

coords (ndarray)

spinlab.io.winepr.import_winepr(path)

Import Bruker par/spc data and return SpinData object

Parameters:: path (str) -- Path to either .par or .spc file
Returns:: SpinData object containing Bruker par/spc data
Return type:: parspc_data (object)

spinlab.io.winepr.load_par(path)

Import contents of .par file

Parameters:: path (str) -- Path to .par file
Returns:: dictionary of parameters
Return type:: attrs (dict)

spinlab.io.winepr.load_spc(path, attrs)

Import data and axes of .spc file

Parameters:: path (str) -- Path to .spc file
Returns:: coordinates for spectrum or spectra values (ndarray) : data values attrs (dict) : updated dictionary of parameters dims (list) : dimension labels
Return type:: coords (ndarray)

spinlab.io.topspin.find_group_delay(attrs_dict)

Determine group delay from tables

Parameters:: attrs_dict (dict) -- dictionary of topspin acquisition parameters
Returns:: Group delay. Number of points FID is shifted by DSP. The ceiling of this number (group delay rounded up) is the number of points should be removed from the start of the FID.
Return type:: float

spinlab.io.topspin.import_topspin(path, assign_vdlist=False, remove_digital_filter=False, read_offset=False, verbose=False, **kwargs)

Import topspin data and return sldata object

Parameters:

path (str) -- Directory of data
assign_vdlist -- False, or the name of dimension to assign topspin vdlist
remove_digital_filter (bool) -- Option to remove group delay (see note below)
verbose (bool) -- Print additional output for troubleshooting

Note

The group delay is a consequence of the oversampling and digital filtering in Bruker spectrometers. For more details see these blog posts https://nmr-analysis.blogspot.com/2010/05/bruker-smiles.html and https://nmr-analysis.blogspot.com/2010/05/bruker-smiles.html

Returns:: topspin data
Return type:: sldata

spinlab.io.topspin.load_acqu(path, required_params=None, verbose=False)

Import topspin acqu or proc files

Parameters:

path (str) -- directory of acqu or proc file
required_params (list) -- Only return parameters given
verbose (bool) -- If true, print output for troubleshooting

Returns:

Dictionary of acquisition parameters

Return type:

dict

spinlab.io.topspin.load_bin(path, dtype='>i4')

Import Topspin Ser file

Parameters:

path (str) -- Directory of data
dtype (str) -- data format for import

Returns:

Data from ser file

Return type:

raw (np.ndarray)

spinlab.io.topspin.load_pdata(path, verbose=False)

Import TopSpin processed data

Parameters:

path (str) -- Directory of pdata
verbose (bool) -- If true, print output for troubleshooting

Returns:

Topspin processed data

Return type:

SpinData

spinlab.io.topspin.load_ser(path, dtype='>i4')

Deprecated. Use load_bin. Import Topspin Ser file

Parameters:

path (str) -- Directory of data
dtype (str) -- data format for import

Returns:

Data from ser file

Return type:

raw (np.ndarray)

spinlab.io.topspin.load_title(path='1', title_path='pdata/1', title_filename='title')

Import Topspin Experiment Title File

Parameters:

path (str) -- Directory of title
title_path (str) -- Path within experiment of title
title_filename (str) -- filename of title

Returns:

Contents of experiment title file

Return type:

str

spinlab.io.topspin.load_topspin_jcamp_dx(path, verbose=False)

Return the contents of topspin JCAMP-DX file as dictionary

Parameters:

path (str) -- Path to file
verbose (bool) -- If true, print output for troubleshooting

Returns:

Dictionary of JCAMP-DX file parameters

Return type:

dict

spinlab.io.topspin.topspin_vdlist(path)

Return topspin vdlist

Parameters:: path (str) -- Directory of data
Returns:: vdlist as numpy array
Return type:: numpy.ndarray

JEOL

spinlab.io.delta.import_delta(path, verbose=False)

Import Delta data and return SpinData object

Currently only 1D and 2D data sets are supported.

Parameters:: path (str) -- Path to .jdf file
Returns:: SpinData object containing Delta data
Return type:: sldata (SpinData)

spinlab.io.delta.import_delta_data(path, params={}, verbose=False)

Import spectrum or spectra of Delta data

Currently only 1D and 2D data sets are supported.

Parameters:

path (str) -- Path to .jdf file
params (dict) -- dictionary of parameters

Returns:

spectrum or spectra if >1D abscissa (list) : coordinates of axes dims (list) : axes names params (dict) : updated dictionary of parameters

Return type:

y_data (ndarray)

spinlab.io.delta.import_delta_pars(path, context_start)

Import parameter fields of Delta data

Parameters:

path (str) -- Path to .jdf file
context_start (int) -- the index where the context starts

Returns:

dictionary of parameter fields and values

Return type:

params (dict)

Varian / Agilent

spinlab.io.vnmrj.array_coords(attrs)

Return array dimension coords from parameters dictionary

Parameters:: attrs (dict) -- Dictionary of procpar parameters
Returns:: dim and coord for array
Return type:: tuple

spinlab.io.vnmrj.import_fid(path, filename='fid')

Import VnmrJ fid file

Parameters:

path (str) -- Directory of fid file
filename (str) -- Name of fid file. "fid" by default

Returns:

Array of data

Return type:

numpy.ndarray

spinlab.io.vnmrj.import_procpar(path, filename='procpar')

Import VnmrJ procpar parameters file

Parameters:: path (str) -- Directory of file
Returns:: Dictionary of procpar parameters
Return type:: dict

spinlab.io.vnmrj.import_vnmrj(path, fidFilename='fid', paramFilename='procpar')

Import VnmrJ Data

Parameters:

path (str) -- path to experiment folder
fidFilename (str) -- FID file name
paramFilename (str) -- process parameter filename

Returns:

data in sldata object

Return type:

sldata

Magritek

spinlab.io.prospa.import_csv(path, return_raw=False, is_complex=True)

Import Kea csv file

Parameters:: path (str) -- Path to csv file
Returns:: x(numpy.array): axes if return_raw = False data(numpy.array): Data in csv file
Return type:: tuple

spinlab.io.prospa.import_nd(path)

Import Kea binary 1d, 2d, 3d, 4d files

Parameters:: path (str) -- Path to file
Returns:: x (None, numpy.array): Axes if included in binary file, None otherwise data (numpy.array): Numpy array of data
Return type:: tuple

spinlab.io.prospa.import_par(path)

Import Kea parameters .par file

Parameters:: path (str) -- Path to parameters file
Returns:: Dictionary of Kea Parameters
Return type:: dict

spinlab.io.prospa.import_prospa(path, parameters_filename=None, experiment=None, verbose=False)

Import Kea data

Parameters:

path (str) -- Path to data
parameters_filename (str)
experiment (str) -- Prospa experiment, used when calculating coords from parameters
verbose (bool) -- If true, prints additional information for troubleshooting

Returns:

sldata object with Kea data

spinlab.io.prospa.prospa_coords(attrs, data_shape, experiment)

Generate coords from prospa acquisition parameters

Parameters:

attrs (dict) -- Dictionary of prospa acqusition parameters
data_shape (tuple) -- Shape of data

Returns:

dims and coords

Return type:

tuple

FeMi

spinlab.io.specman.analyze_attrs(attrs)

Analyze the attrs and add some important attrs to existing dictionary

Parameters:: attrs (dict) -- Dictionary of specman acqusition parameters
Returns:: The dictionary of specman acqusition parameters and added parameters
Return type:: attrs (dict)

spinlab.io.specman.calculate_specman_coords(attrs, old_coords, dims=None)

Generate coords from specman acquisition parameters

Parameters:

attrs (dict) -- Dictionary of specman acqusition parameters
dims (list) -- (Optional) a list of dims

Returns:

a calculated coords

Return type:

coords (list)

spinlab.io.specman.generate_dims(attrs)

Generate dims from specman acquisition parameters

Parameters:: attrs (dict) -- Dictionary of specman acqusition parameters
Returns:: a new dims
Return type:: dims (list)

spinlab.io.specman.import_specman(path, autodetect_coords: bool = True, autodetect_dims: bool = True, make_complex: bool = True, complex_dim: str = 'x')

Import SpecMan data and return SpinData object

SpinLab function to import SpecMan4EPR data (https://specman4epr.com/). The function returns a Spindata object with the spectral data.

The structure of the Spindata object can be complex and the variables saved by SpecMan depend on the individual spectrometer configuration. Therefore, the import function returns a numpy array with the dimension "x0", "x1", "x2", "x3", "x4". In any case, the dimension "x0" corresponds to the variables stored in the data file. The spectroscopic data is stored in "x1" to "x4", depending on how many dimensions were recorded. The import function will require a parser script to properly assign the spectroscopic data and proper coordinates.

Parameters:

path (str) -- Path to either .exp file
autodetect_coords (bool) -- Autodetect coords based on attrs
autodetect_dims (bool) -- Autodetect dims based on attrs
make_complex (bool) -- If True, will create a complex SpinData object if the data is complex
complex_dim (str) -- The dimension to use for complex data (default: 'x')

Returns:

SpinData object containing SpecMan EPR data

Return type:

data (SpinData)

spinlab.io.specman.load_specman_d01(path, attrs, verbose=False)

Import SpecMan d01 data file

SpinLab function to import the SpecMan d01 data file. The format of the SpecMan data file is described here:

Parameters:: path (str) -- Path to either .d01 or .exp file
Returns:: SpecMan data as numpy array params (dict): Dictionary with import updated parameters dictionary
Return type:: data (ndarray)

spinlab.io.specman.load_specman_exp(path)

Import SpecMan parameters

SpinLab function to read and import the SpecMan exp file. The .exp file is a text file that stores the experimental data, the pulse program, and other spectrometer configuration files.

Parameters:: path (str) -- Path to either .d01 or .exp file
Returns:: Dictionary of parameter fields and values (SpinLab attributes)
Return type:: attrs (dict)

Tecmag

spinlab.io.tnmr.import_tnmr(path, squeeze=True)

Import tnmr data and return SpinData object

Parameters:

path (str) -- Path to .jdf file
squeeze (bool) -- Automatically remove length 1 dimensions

Returns:

SpinData object containing tnmr data

Return type:

sldata (object)

spinlab.io.tnmr.import_tnmr_data(path)

Import spectrum or spectra of tnmr data

Parameters:: path (str) -- Path to .tnt file
Returns:: Spectrum or spectra if >1D abscissa (list): Coordinates of axes dims (list): Axes names
Return type:: data (ndarray)

RS2D

spinlab.io.rs2d.import_rs2d(path, datafile='data.dat', headerfile='header.xml', *args, **kwargs)

Import data from an RS2D file.

Accepts either the header.xml or data.dat file; the companion file is located automatically in the same directory.

Parameters:

path (str) -- Path to the header.xml or data.dat file.
datafile (str) -- Name of the binary data file. Default is "data.dat".
headerfile (str) -- Name of the XML header file. Default is "header.xml".
**kwargs -- Additional keyword arguments passed to the data reader (e.g. endianess, fmt, fmt_size).

Returns:

Imported data object with axes and acquisition parameters.

Return type:

SpinData

Other

spinlab.io.vna.get_sldata(values, coords, attrs, concat_dim=None)

Construct a SpinData object from VNA data arrays.

For 1D data (single S-parameter trace) a single SpinData is returned. For 2D data (multiple traces, e.g. all four S-parameters of an s2p file) the traces are concatenated along concat_dim.

Parameters:

values (numpy.ndarray) -- S-parameter data, 1D or 2D.
coords (numpy.ndarray) -- Frequency axis array.
attrs (dict) -- Acquisition attributes (format, center frequency, span).
concat_dim (str, optional) -- Name of the new dimension when concatenating multiple traces. Default is None.

Returns:

Data object containing the VNA measurement.

Return type:

SpinData

spinlab.io.vna.import_snp(path, *args, **kwargs): Import sNp file and return numpy array

spinlab.io.vna.import_vna(path, *args, **kwargs): Import VNA data and return sldata object

spinlab.io.cnsi.get_powers(path, power_file, experiment_list)

Split power readings files into array of power measurements equal in length to number of spectra in dataset

Parameters:

path (str) -- Path to base folder containing power file
power_file (str) -- filename, "power" or "t1_powers"
experiment_list (list) -- list of folder numbers of experiments corresponding to power_file

Returns:

list of power readings equal in length to experiment_list

Return type:

power_list (list)

spinlab.io.power.assign_power(dataDict, expNumList, powersList)

Given a dictionary of slData objects with key being folder string, return the data with power values assigned to a new axis dimension

Parameters:

dataDict (dict) -- dictionary of data objects
expNumList (list) -- List of experiment numbers
powersList (list) -- List of powers

Returns:

Data object with powers

Return type:

SpinData

spinlab.io.power.chop_power(t, p, threshold=0.1)

Use Derivative to chop Powers

Parameters:

t (numpy.ndarray) -- Array of time points
p (numpy.ndarray) -- Array of powers
threshold (float) -- Threshold to chop powers

Returns:

Array of average time values averagePowerArray: Array of average power values

Return type:

averageTimeArray

spinlab.io.power.import_power(path, filename='')

import powers file

Parameters:

path (str) -- Directory of powers
filename (str) -- filename of powers if given

Returns:

Array of time points p (numpy.ndarray): Array of powers

Return type:

t (numpy.ndarray)