How to load a fid file?

The Dataset constructor accepts both a path to directory containing a fid file, or a path to the fid file.

from brukerapi.dataset import Dataset

 dataset = Dataset('path_to_fid/')

 dataset = Dataset('path_to_fid/fid')

A Dataset object is primarily an interface to the data contained in the fid file.

data = dataset.data

Data is typically and n-dimensional array, the physical meaning of individual dimensions is stored in dim_type property.

>> dataset.dim_type
>> ['k_space_encode_step_0', 'k_space_encode_step_1', 'object', 'repetition', 'channel']

Dataset.data contains ordered raw k-space, not a reconstructed image. RARE/EPI line ordering is applied, while ramp-sampling regridding remains a downstream reconstruction step. Real-only AQ_mod=qf data stays real; quadrature acquisition modes are returned as complex arrays.

Use the explicit views in new code: dataset.raw is the decoded acquisition stream with axes (sample, shot, receiver); dataset.kspace is the same ordered k-space exposed through data for compatibility.

When an experiment has a reconstruction, its reco declaration is used to determine EPI continuous-train handling and odd-line reversal (RECO_inp_order=REV_ALT_ROWS). The conventional first reconstruction is used by default. Select another reconstruction explicitly when its input-order metadata is the one that corresponds to the data being read:

dataset = Dataset(
    'path/to/fid',
    reco_path='path/to/pdata/2/reco',
)

For a FID without a reconstruction, the reader falls back to the acquisition declaration and, where necessary, the pulse-program scheme inference. A RuntimeWarning is emitted if the selected reco and scheme inference disagree; the declared reconstruction value is used.

For custom pulse-program names the scheme is inferred from acquisition metadata. An explicit override is available when inference is ambiguous:

dataset = Dataset('path/to/fid', scheme_id='RADIAL')

Random-access mmap=True is currently supported for 2dseq only. Load a FID normally, then select the desired k-space array slice.

Known fid.spiral, fid.navFid, and fid.orig companions are loaded under dataset.fid_companions. They are auxiliary subdatasets rather than standalone primary datasets. TopSpin/NMR ser is not supported.

It is possible to directly access some of the most wanted measurement parameters.

>> dataset.TE
>> 3.0
>> dataset.TR
>> 15.0
>> dataset.flip_angle
>> 10.0

Both acqp and method files are used to construct a fid dataset. Any parameter stored in those files can also be accessed directly.

>> dataset.get_value('PVM_Matrix')
>> [192 192]
>> dataset.get_value('ACQ_dim_desc')
>> ['Spatial' 'Spatial']