brukerapi 0.2.4

Bruker API

brukerapi-python

A Python package providing I/O interface for Bruker data sets.

tl;dr

Install using pip:

pip install brukerapi

Load any data set:

from brukerapi.dataset import Dataset
dataset = Dataset('{path}/2dseq')    # create data set, works for fid, 2dseq, rawdata.x, ser
dataset.data                         # access data array
dataset.VisuCoreSize                 # get a value of a single parameter

Load an entire study:

from brukerapi.folders import Study
study = Study('{path_to_study_folder}')
dataset = study.get_dataset(exp_id='1', proc_id='1')

# get_dataset returns an empty dataset
# in order to load data into the data set, you can either use the context manager:

with dataset as d:
    d.data                         # access data array
    d.VisuCoreSize                 # get a value of a parameter

# or the load function
dataset.load()
dataset.data                       # access data array
dataset.VisuCoreSize               # get a value of a single parameter

Load a parametric file:

from brukerapi.jcampdx import JCAMPDX

parameters = JCAMPDX('path_to_scan/method')

TR = data.params["PVM_RepetitionTime"].value # This way
TR = data.get_value("PVM_RepetitionTime") # Or this way

Features

• I/O interface for fid data sets

• I/O interface for 2dseq data sets

• I/O interface for ser data sets

• I/O interface for rawdata data sets

• Random access for fid and 2dseq data sets

• Split operation implemented over 2dseq data sets

• Filter operation implemented over Bruker folders (allowing you to work with a subset of your study only)

Examples

• How to read a Bruker fid, 2dseq, rawdata, or ser file

• How to split slice packages of a 2dseq data set

• How to split FG_ECHO of a 2dseq data set

• How to split FG_ISA of a 2dseq data set

Documentation

Online documentation of the API is available at Read The Docs.

Install

Using pip:

pip install brukerapi

From source:

git clone https://github.com/isi-nmr/brukerapi-python.git
cd brukerapi-python
python setup.py build
python setup.py install

Testing

To ensure reliability, every commit to this repository is tested against the following, publicly available data sets:

• BrukerAPI test data set (Bruker ParaVision v5.1)

• BrukerAPI test data set (Bruker ParaVision v6.0.1)

• bruker2nifti_qa data set

Compatibility

The API was tested using various data sets obtained by ParaVision 5.1, 6.0.1 and 360. It it is compatible with the following data set types from individual ParaVision versions.

ParaVision v5.1

Compatible data set types:

• fid

• 2dseq

• rawdata.job0

• rawdata.Navigator

Compatible pulse sequences for fid data sets:

• FLASH.ppg

• MGE.ppg

• MSME.ppg

• RARE.ppg

• FAIR_RARE.ppg

• RAREVTR.ppg

• RAREst.ppg

• MDEFT.ppg

• FISP.ppg

• FLOWMAP.ppg

• DtiStandard.ppg

• EPI.ppg

• FAIR_EPI.ppg

• DtiEpi.ppg

• T1_EPI.ppg

• T2_EPI.ppg

• T2S_EPI.ppg

• SPIRAL.ppg

• DtiSpiral.ppg

• UTE.ppg

• UTE3D.ppg

• ZTE.ppg

• CSI.ppg

• FieldMap.ppg

• NSPECT.ppg

• PRESS.ppg

• STEAM.ppg

• igFLASH.ppg

ParaVision v6.0.1 and v7.0.0

Compatible data set types:

• fid

• 2dseq

• rawdata.job0

• rawdata.Navigator

Compatible pulse sequences for fid data sets:

• FLASH.ppg,

• FLASHAngio.ppg

• IgFLASH.ppg

• MGE.ppg

• MSME.ppg

• RARE.ppg

• FAIR_RARE.ppg

• RAREVTR.ppg

• RAREst.ppg

• MDEFT.ppg

• FISP.ppg

• FLOWMAP.ppg

• DtiStandard.ppg

• EPI.ppg

• FAIR_EPI.ppg

• CASL_EPI.ppg

• DtiEpi.ppg

• T1_EPI.ppg

• T2_EPI.ppg

• T2S_EPI.ppg

• SPIRAL.ppg

• DtiSpiral.ppg

• UTE.ppg

• UTE3D.ppg

• ZTE.ppg

• CSI.ppg

• FieldMap.ppg

• SINGLEPULSE.ppg

• NSPECT.ppg

• EPSI.ppg

• PRESS.ppg

• STEAM.ppg

• ISIS.ppg

• CPMG.ppg

• RfProfile.ppg

ParaVision 360 v1.1 v3.0-v3.7

Reading rawdata is supported only in a basic form, no reshaping into k-space is supported at the moment. Compatible data set types:

• 2dseq

• rawdata.job0

• rawdata.Navigator