def setUp(self):
self.config = GadgetronConfig()
path = 'mr_utils/test_data/tests/gadgetron/client/'
file = 'grappa_test_data.h5'
load_test_data(path, [file], do_return=False)
self.filename = '%s/%s' % (path, file)
def epi():
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('NoiseAdjust')
config.add_gadget('ReconX', 'EPIReconXGadget')
config.add_gadget('EPICorr')
config.add_gadget('FFTX', dll='gadgetron_epi')
config.add_gadget('AccTrig',
'AcquisitionAccumulateTriggerGadget',
props=[('trigger_dimension', 'repetition'),
('sorting_dimension', 'slice')])
config.add_gadget('Buff',
'BucketToBufferGadget',
props=[('N_dimension', ''), ('S_dimension', ''),
('split_slices', 'true'),
('ignore_segment', 'true')])
config.add_gadget('FFT')
config.add_gadget('Combine')
config.add_gadget('Extract')
config.add_gadget('AutoScale')
config.add_gadget('FloatToShort', 'FloatToUShortGadget')
config.add_gadget('ImageFinish')
return (config)
def distributed_image_default():
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1022', 'MRIImageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_writer('1008', 'GadgetIsmrmrdAcquisitionMessageWriter')
config.add_gadget('RemoveROOversampling')
config.add_gadget('AccTrig',
'AcquisitionAccumulateTriggerGadget',
props=[('trigger_dimension', 'repetition'),
('sorting_dimension', 'slice')])
config.add_gadget('Buff',
'BucketToBufferGadget',
props=[('N_dimension', ''), ('S_dimension', ''),
('split_slices', 'true')])
config.add_gadget('SimpleRecon')
config.add_gadget('ImageArraySplit')
config.add_gadget('Distribute',
'IsmrmrdImageDistributeGadget',
dll='gadgetron_distributed',
props=[('parallel_dimension', 'repetition'),
('use_this_node_for_compute', 'true'),
('single_package_mode', 'true')])
config.add_gadget('Extract')
config.add_gadget('Collect', dll='gadgetron_distributed')
config.add_gadget('ImageSort', props=[('sorting_dimension', 'repetition')])
config.add_gadget('ImageFinish')
return (config)
def setUp(self):
self.config = GadgetronConfig()
self.filename = GadgetronClient.grappa_input_filename()
class GadgetronConfigTestCase(unittest.TestCase):
def setUp(self):
self.config = GadgetronConfig()
self.filename = GadgetronClient.grappa_input_filename()
def test_create_xml(self):
self.config.add_reader(1008,'GadgetIsmrmrdAcquisitionMessageReader')
self.config.add_writer(1004,'MRIImageWriterCPLX')
self.config.add_writer(1005,'MRIImageWriterFLOAT')
self.config.add_writer(1006,'MRIImageWriterUSHORT')
self.config.add_gadget('Acc','AccumulatorGadget')
self.config.add_gadget('FFT')
self.config.add_gadget('Extract')
self.config.add_gadget('ImageFinishFLOAT','ImageFinishGadgetFLOAT')
# self.config.print()
def test_create_default_config(self):
config = configs.default()
truth = GadgetronTestConfig.default_config()
res = len(main.diff_texts(truth.encode(),config.tostring().encode()))
self.assertTrue(res == 0)
def test_use_default_config(self):
# Give the filename of raw data to the client
filename = GadgetronClient.raw_input_filename()
# Send gadgetron the local default configuration file
config = configs.default()
# print(config)
# data,header = client(filename,config_local=config.get_filename())
data,header = client(filename,config_local=config.tostring())
# Make sure the output is the same as when h5 is given
true_output_data = GadgetronClient.true_output_data()
self.assertTrue(np.allclose(data,true_output_data))
def test_use_grappa_cpu_config(self):
config = configs.grappa_cpu()
data,header = client(self.filename,config_local=config.tostring())
data_true,header_true = client(self.filename,config='grappa_cpu.xml')
self.assertTrue(np.allclose(data,data_true))
def test_use_grappa_float_cpu_config(self):
config = configs.grappa_float_cpu()
data,header = client(self.filename,config_local=config.tostring())
data_true,header_true = client(self.filename,config='grappa_float_cpu.xml')
self.assertTrue(np.allclose(data,data_true))
def test_use_grappa_unoptimized_cpu_config(self):
config = configs.grappa_unoptimized_cpu()
data,header = client(self.filename,config_local=config.tostring())
data_true,header_true = client(self.filename,config='grappa_unoptimized.xml')
self.assertTrue(np.allclose(data,data_true))
def test_use_grappa_unoptimized_float_cpu_config(self):
config = configs.grappa_unoptimized_float_cpu()
data,header = client(self.filename,config_local=config.tostring())
data_true,header_true = client(self.filename,config='grappa_unoptimized_float.xml')
self.assertTrue(np.allclose(data,data_true))
def test_use_distributed_default_config(self):
config = configs.distributed_default()
data,header = client(self.filename,config_local=config.tostring())
data_true,header_true = client(self.filename,config='distributed_default.xml')
self.assertTrue(np.allclose(data,data_true))
def test_use_distributed_image_default_config(self):
config = configs.distributed_image_default()
data,header = client(self.filename,config_local=config.tostring())
data_true,header_true = client(self.filename,config='distributed_image_default.xml')
self.assertTrue(np.allclose(data,data_true))
data = '%s/%s' % (path, file)
# Look at the data to make sure we got what we got
with h5py.File(data, 'r') as f:
coil_images = f['dataset']['coil_images']
coil_images = coil_images['real'] + 1j * coil_images['imag']
# R = 2
tmp = np.fft.fft2(coil_images)
tmp[..., ::2, :] = 0
aliased = np.fft.ifft2(tmp)
view(aliased, montage_axis=0)
# Make the config
num_coils = 16
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('NoiseAdjust')
config.add_gadget('CoilReduction', props=[('coils_out', str(num_coils))])
# RO asymmetric echo handling
config.add_gadget('AsymmetricEcho', 'AsymmetricEchoAdjustROGadget')
config.add_gadget('RemoveROOversampling')
config.add_gadget('Grappa',
props=[
('target_coils', str(num_coils)),
('use_gpu', 'false'),
('uncombined_channels',
','.join(str(x) for x in range(num_coils))),
])
def python_short():
# pylint: disable=C0301
'''python_short.xml
Generates [2]_.
References
==========
.. [2] https://github.com/gadgetron/gadgetron/blob/master/gadgets/python/config/python_short.xml
'''
# pylint: enable=C0301
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('RemoveOversamplingPython',
'PythonGadget',
props=[
('python_path', '/home/myuser/scripts/python'),
('python_module', 'remove_2x_oversampling'),
('python_class', 'Remove2xOversampling'),
])
config.add_gadget('AccReconPython',
'PythonGadget',
props=[
('python_path', '/home/myuser/scripts/python'),
('python_module', 'accumulate_and_recon'),
('python_class', 'AccumulateAndRecon'),
])
config.add_gadget('CoilCombinePython',
'PythonGadget',
props=[
('python_path', '/home/myuser/scripts/python'),
('python_module', 'rms_coil_combine'),
('python_class', 'RMSCoilCombine'),
])
config.add_gadget('Extract')
config.add_gadget('AutoScale')
config.add_gadget('FloatToShort', 'FloatToUShortGadget')
config.add_gadget('ImageFinish')
return config
def grappa_float_cpu():
config = GadgetronConfig()
config.add_reader('1008','GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026','GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022','MRIImageWriter')
config.add_gadget('NoiseAdjust')
config.add_gadget('PCA','PCACoilGadget')
config.add_gadget('CoilReduction',props=[
('coils_out','16')
])
config.add_gadget('AsymmetricEcho','AsymmetricEchoAdjustROGadget') # RO asymmetric echo handling
config.add_gadget('RemoveROOversampling')
config.add_gadget('Grappa',props=[
('target_coils','8'),
('use_gpu','false')
])
config.add_gadget('GrappaUnmixing')
config.add_gadget('Extract')
config.add_gadget('ImageFinish')
return(config)
def grappa_unoptimized_float_cpu():
# pylint: disable=C0301
'''Generates grappa_unoptimized_float_cpu.xml.
Generates [4]_.
References
==========
.. [4] https://github.com/gadgetron/gadgetron/blob/master/gadgets/grappa/config/grappa_unoptimized_float.xml
'''
# pylint: enable=C0301
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('RemoveROOversampling')
config.add_gadget('Grappa',
props=[('target_coils', '8'), ('use_gpu', 'false')])
config.add_gadget('GrappaUnmixing')
config.add_gadget('Extract')
config.add_gadget('ImageFinish')
return config
def default():
config = GadgetronConfig()
config.add_reader('1008','GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026','GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022','MRIImageWriter')
config.add_gadget('RemoveROOversampling')
config.add_gadget('AccTrig','AcquisitionAccumulateTriggerGadget',props=[
('trigger_dimension','repetition'),
('sorting_dimension','slice')
])
config.add_gadget('Buff','BucketToBufferGadget',props=[
('N_dimension',''),
('S_dimension',''),
('split_slices','true')
])
config.add_gadget('SimpleRecon')
config.add_gadget('ImageArraySplit')
config.add_gadget('Extract')
config.add_gadget('ImageFinish')
return(config)
def grappa_cpu():
# pylint: disable=C0301
'''Generates grappa_cpu.xml.
Generates [1]_.
References
==========
.. [1] https://github.com/gadgetron/gadgetron/blob/master/gadgets/grappa/config/grappa_cpu.xml
'''
# pylint: enable=C0301
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('NoiseAdjust')
config.add_gadget('PCA', 'PCACoilGadget')
config.add_gadget('CoilReduction', props=[('coils_out', '16')])
# RO asymmetric echo handling
config.add_gadget('AsymmetricEcho', 'AsymmetricEchoAdjustROGadget')
config.add_gadget('RemoveROOversampling')
config.add_gadget('Grappa',
props=[('target_coils', '8'), ('use_gpu', 'false')])
config.add_gadget('GrappaUnmixing')
config.add_gadget('Extract')
config.add_gadget('AutoScale')
config.add_gadget('FloatToShort', 'FloatToUShortGadget')
config.add_gadget('ImageFinish')
return config
from mr_utils.test_data import load_test_data
from mr_utils.definitions import ROOT_DIR
from mr_utils import view
if __name__ == '__main__':
# Load in a numerical phantom to play around with
path = 'mr_utils/test_data/tests/gadgetron/client/'
file = 'input.h5'
load_test_data(path, [file], do_return=False)
data = '%s/%s' % (path, file)
# Make a config
script_dir = 'tmp/'
default_dir = ''
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('RemoveOversamplingPython',
'PythonGadget',
props=[
('python_path', default_dir),
('python_module', 'remove_2x_oversampling'),
('python_class', 'Remove2xOversampling'),
])
config.add_gadget('AccReconPython',
'PythonGadget',
props=[
('python_path', default_dir),
('python_module', 'accumulate_and_recon'),
def distributed_default():
# pylint: disable=C0301
'''Generates distributed_default.xml.
Generates [1]_.
References
==========
.. [1] https://github.com/gadgetron/gadgetron/blob/master/gadgets/distributed/config/distributed_default.xml
'''
# pylint: enable=C0301
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1022', 'MRIImageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_writer('1008', 'GadgetIsmrmrdAcquisitionMessageWriter')
config.add_gadget('Distribute',
'IsmrmrdAcquisitionDistributeGadget',
dll='gadgetron_distributed',
props=[('parallel_dimension', 'repetition'),
('use_this_node_for_compute', 'true')])
config.add_gadget('RemoveROOversampling')
config.add_gadget('AccTrig',
'AcquisitionAccumulateTriggerGadget',
props=[('trigger_dimension', 'repetition'),
('sorting_dimension', 'slice')])
config.add_gadget('Buff',
'BucketToBufferGadget',
props=[('N_dimension', ''), ('S_dimension', ''),
('split_slices', 'true')])
config.add_gadget('SimpleRecon')
config.add_gadget('ImageArraySplit')
config.add_gadget('Collect', dll='gadgetron_distributed')
config.add_gadget('Extract')
config.add_gadget('Sort',
'ImageSortGadget',
props=[('sorting_dimension', 'repetition')])
config.add_gadget('ImageFinish')
return config
'''Example of how to programmatically generate a config file.'''
from mr_utils.gadgetron import GadgetronConfig
if __name__ == '__main__':
config = GadgetronConfig()
config.add_reader(1008, 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_writer(1004, 'MRIImageWriterCPLX')
config.add_writer(1005, 'MRIImageWriterFLOAT')
config.add_writer(1006, 'MRIImageWriterUSHORT')
config.add_gadget('Acc', 'AccumulatorGadget')
config.add_gadget('FFT')
config.add_gadget('Extract')
config.add_gadget('ImageFinishFLOAT', 'ImageFinishGadgetFLOAT')
print(config.tostring())
def epi_gtplus_grappa():
'''GT Plus configuration file for general 2D epi reconstruction.'''
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('NoiseAdjust')
config.add_gadget('ReconX', 'EPIReconXGadget')
config.add_gadget('EPICorr')
config.add_gadget('FFTX', dll='gadgetron_epi')
config.add_gadget('Acc',
'GtPlusAccumulatorWorkOrderTriggerGadget',
props=[('verboseMode', 'false'),
('noacceleration_triggerDim1', 'DIM_Repetition'),
('noacceleration_triggerDim2', 'DIM_NONE'),
('noacceleration_numOfKSpace_triggerDim1', '1'),
('separate_triggerDim1', 'DIM_Repetition'),
('separate_triggerDim2', 'DIM_NONE'),
('separate_numOfKSpace_triggerDim1', '1'),
('other_kspace_matching_Dim', 'DIM_Repetition')])
# Recon computation for 2DT cases
config.add_gadget(
'Recon',
'GtPlusRecon2DTGadget',
props=[
# kspace data
('dim_4th', 'DIM_Contrast'),
('dim_5th', 'DIM_Slice'),
# ork flow
('workOrder_ShareDim', 'DIM_Repetition'),
# o accelaration mode
('no_acceleration_averageall_ref', 'true'),
('no_acceleration_ref_numOfModes', '0'),
('no_acceleration_same_combinationcoeff_allS', 'false'),
('no_acceleration_whichS_combinationcoeff', '0'),
# separate mode
('separate_averageall_ref', 'true'),
('separate_ref_numOfModes', '0'),
('separate_fullres_coilmap', 'false'),
('separate_same_combinationcoeff_allS', 'false'),
('separate_whichS_combinationcoeff', '0'),
# coil compression
('same_coil_compression_coeff_allS', 'false'),
('downstream_coil_compression', 'false'),
('coil_compression_thres', '-1'),
('coil_compression_num_modesKept', '-1'),
# parameters for coil map estimation
('coil_map_algorithm', 'ISMRMRD_SOUHEIL'),
('csm_kSize', '7'),
('csm_powermethod_num', '3'),
('csm_true_3D', 'false'),
('csm_iter_num', '5'),
('csm_iter_thres', '0.001'),
# algorithm
('recon_algorithm', 'ISMRMRD_GRAPPA'),
('recon_kspace_needed', 'false'),
('recon_auto_parameters', 'true'),
# parameters for ISMRMRD_GRAPPA
('grappa_kSize_RO', '5'),
('grappa_kSize_E1', '4'),
('grappa_kSize_E2', '4'),
('grappa_reg_lamda', '0.0005'),
('grappa_calib_over_determine_ratio', '0'),
# parameters for scaling and image sending
('min_intensity_value', '64'),
('max_intensity_value', '4095'),
('scalingFactor', '-1.0'),
('use_constant_scalingFactor', 'false'),
# parameters for kspace filter, image data
('filterRO', 'Gaussian'),
('filterRO_sigma', '1.0'),
('filterRO_width', '0.15'),
('filterE1', 'Gaussian'),
('filterE1_sigma', '1.0'),
('filterE1_width', '0.15'),
('filterE2', 'Gaussian'),
('filterE2_sigma', '1.0'),
('filterE2_width', '0.15'),
# parameters for kspace filter, ref data
('filterRefRO', 'Hanning'),
('filterRefRO_sigma', '1.5'),
('filterRefRO_width', '0.15'),
('filterRefE1', 'Hanning'),
('filterRefE1_sigma', '1.5'),
('filterRefE1_width', '0.15'),
('filterRefE2', 'Hanning'),
('filterRefE2_sigma', '1.5'),
('filterRefE2_width', '0.15'),
# parameters for debug and timing
('debugFolder', ''),
('debugFolder2', ''),
('cloudNodeFile', 'myCloud_2DT.txt'),
('performTiming', 'true'),
('verboseMode', 'false'),
# parameters for system acquisition
('timeStampResolution', '0.0025'),
# parameters for recon job split
('job_split_by_S', 'false'),
('job_num_of_N', '32'),
('job_max_Megabytes', '10240'),
('job_overlap', '2'),
('job_perform_on_control_node', 'true')
])
config.add_gadget('ComplexToFloatAttrib', 'ComplexToFloatGadget')
config.add_gadget('FloatToShortAttrib', 'FloatToUShortGadget')
config.add_gadget('ImageFinish')
return (config)
def default():
# pylint: disable=C0301
'''Default config file, default.xml.
Generates [1]_.
References
==========
.. [1] https://github.com/gadgetron/gadgetron/blob/master/gadgets/mri_core/config/default.xml
'''
# pylint: enable=C0301
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('RemoveROOversampling')
config.add_gadget('AccTrig',
'AcquisitionAccumulateTriggerGadget',
props=[('trigger_dimension', 'repetition'),
('sorting_dimension', 'slice')])
config.add_gadget('Buff',
'BucketToBufferGadget',
props=[('N_dimension', ''), ('S_dimension', ''),
('split_slices', 'true')])
config.add_gadget('SimpleRecon')
config.add_gadget('ImageArraySplit')
config.add_gadget('Extract')
config.add_gadget('ImageFinish')
return config
def generic_cartesian_grappa():
config = GadgetronConfig()
config.add_reader('1008','GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026','GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022','MRIImageWriter')
config.add_gadget('NoiseAdjust')
config.add_gadget('AsymmetricEcho','AsymmetricEchoAdjustROGadget')
config.add_gadget('RemoveROOversampling')
config.add_gadget('AccTrig','AcquisitionAccumulateTriggerGadget',props=[
('trigger_dimension',''),
('sorting_dimension','')
])
config.add_gadget('BucketToBuffer',props=[
('N_dimension','contrast'),
('S_dimension','average'),
('split_slices','false'),
('ignore_segment','true'),
('verbose','true')
])
config.add_gadget('PrepRef','GenericReconCartesianReferencePrepGadget',props=[
('debug_folder',''),
('perform_timing','true'),
('verbose','true'),
('average_all_ref_N','true'),
('average_all_ref_S','true'),
('prepare_ref_always','true')
])
config.add_gadget('CoilCompression','GenericReconEigenChannelGadget',props=[
('debug_folder',''),
('perform_timing','true'),
('verbose','true'),
('average_all_ref_N','true'),
('average_all_ref_S','true'),
('upstream_coil_compression','true'),
('upstream_coil_compression_thres','0.002'),
('upstream_coil_compression_num_modesKept','0')
])
config.add_gadget('Recon','GenericReconCartesianGrappaGadget',props=[
('image_series','0'),
('coil_map_algorithm','Inati'),
('downstream_coil_compression','true'),
('downstream_coil_compression_thres','0.01'),
('downstream_coil_compression_num_modesKept','0'),
('debug_folder',''),
('perform_timing','true'),
('verbose','true'),
('send_out_gfactor','false')
])
config.add_gadget('PartialFourierHandling','GenericReconPartialFourierHandlingFilterGadget',props=[
('debug_folder',''),
('perform_timing','false'),
('verbose','false'),
('skip_processing_meta_field','Skip_processing_after_recon'),
('partial_fourier_filter_RO_width','0.15'),
('partial_fourier_filter_E1_width','0.15'),
('partial_fourier_filter_E2_width','0.15'),
('partial_fourier_filter_densityComp','false')
])
config.add_gadget('KSpaceFilter','GenericReconKSpaceFilteringGadget',props=[
('debug_folder',''),
('perform_timing','false'),
('verbose','false'),
('skip_processing_meta_field','Skip_processing_after_recon'),
('filterRO','Gaussian'),
('filterRO_sigma','1.0'),
('filterRO_width','0.15'),
('filterE1','Gaussian'),
('filterE1_sigma','1.0'),
('filterE1_width','0.15'),
('filterE2','Gaussian'),
('filterE2_sigma','1.0'),
('filterE2_width','0.15'),
])
config.add_gadget('FOVAdjustment','GenericReconFieldOfViewAdjustmentGadget',props=[
('debug_folder',''),
('perform_timing','false'),
('verbose','false')
])
config.add_gadget('Scaling','GenericReconImageArrayScalingGadget',props=[
('perform_timing','false'),
('verbose','false'),
('min_intensity_value','64'),
('max_intensity_value','4095'),
('scalingFactor','10.0'),
('use_constant_scalingFactor','true'),
('auto_scaling_only_once','true'),
('scalingFactor_dedicated','100.0')
])
config.add_gadget('ImageArraySplit')
config.add_gadget('ComplexToFloatAttrib','ComplexToFloatGadget')
config.add_gadget('FloatToShortAttrib','FloatToUShortGadget',props=[
('max_intensity','32767'),
('min_intensity','0'),
('intensity_offset','0')
])
config.add_gadget('ImageFinish')
return(config)
def test_gadgetron_grappa_coil_output(self):
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('RemoveROOversampling')
config.add_gadget('Grappa',
props=[('target_coils', '8'), ('use_gpu', 'false'),
('uncombined_channels',
'1,2,3,4,5,6,7,8,9,10,11,12')])
config.add_gadget('GrappaUnmixing')
config.add_gadget('Extract',
props=[('extract_magnitude', 'false')('extract_real',
'true'),
('extract_imag', 'true')])
config.add_gadget('ImageFinish')
data, header = client(self.filename, config_local=config.tostring())
data = data[0, ...] + 1j * data[1, ...]
view(data, montage_axis=0)
def grappa_unoptimized_float_cpu():
config = GadgetronConfig()
config.add_reader('1008','GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026','GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022','MRIImageWriter')
config.add_gadget('RemoveROOversampling')
config.add_gadget('Grappa',props=[
('target_coils','8'),
('use_gpu','false')
])
config.add_gadget('GrappaUnmixing')
config.add_gadget('Extract')
config.add_gadget('ImageFinish')
return(config)
def epi():
# pylint: disable=C0301
'''Generates epi.xml.
Generates [1]_.
References
==========
.. [1] https://github.com/gadgetron/gadgetron/blob/master/gadgets/epi/epi.xml
'''
# pylint: enable=C0301
config = GadgetronConfig()
config.add_reader('1008', 'GadgetIsmrmrdAcquisitionMessageReader')
config.add_reader('1026', 'GadgetIsmrmrdWaveformMessageReader')
config.add_writer('1022', 'MRIImageWriter')
config.add_gadget('NoiseAdjust')
config.add_gadget('ReconX', 'EPIReconXGadget')
config.add_gadget('EPICorr')
config.add_gadget('FFTX', dll='gadgetron_epi')
config.add_gadget('AccTrig',
'AcquisitionAccumulateTriggerGadget',
props=[('trigger_dimension', 'repetition'),
('sorting_dimension', 'slice')])
config.add_gadget('Buff',
'BucketToBufferGadget',
props=[('N_dimension', ''), ('S_dimension', ''),
('split_slices', 'true'),
('ignore_segment', 'true')])
config.add_gadget('FFT')
config.add_gadget('Combine')
config.add_gadget('Extract')
config.add_gadget('AutoScale')
config.add_gadget('FloatToShort', 'FloatToUShortGadget')
config.add_gadget('ImageFinish')
return config