## distributed under the License is distributed on an "AS IS" BASIS,
## WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
## See the License for the specific language governing permissions and
## limitations under the License.
__version__ = '0.1.0'
# import engine module
import pGadgetron as pMR
# import further modules
import os, numpy
import matplotlib.pyplot as plt
#%% GO TO MR FOLDER
os.chdir(pMR.examples_data_path('MR'))
#%% a definition of a Gaussian function
def gaussian(x, mu, sigma):
return numpy.exp(-numpy.power(x - mu, 2.) / (2 * numpy.power(sigma, 2.)))
#%% GO TO MR FOLDER AND LOAD RAW MR DATA
os.chdir(pMR.examples_data_path('MR'))
acq_data = pMR.AcquisitionData('simulated_MR_2D_cartesian.h5')
#%% GET SIZE OF K-SPACE DATA
# Get size of current k-space data as tuple
# (number of acquisitions, number of coils, number of samples)
kdim = acq_data.dimensions()
# import engine module objects
from pGadgetron import examples_data_path
from pGadgetron import existing_filepath
from pGadgetron import AcquisitionData
from pGadgetron import AcquisitionDataProcessor
from pGadgetron import Reconstructor
from pGadgetron import ISMRMRD_IMTYPE_MAGNITUDE
from pGadgetron import ImageDataProcessor
from pGadgetron import error
# process command-line options
data_file = args['--file']
data_path = args['--path']
if data_path is None:
data_path = examples_data_path('MR')
sigma = float(args['--sigma'])
show_plot = not args['--non-interactive']
def gaussian(x, mu, sigma):
return numpy.exp(-numpy.power(x - mu, 2.) / (2 * numpy.power(sigma, 2.)))
def main():
# Acquisitions will be read from this HDF file
input_file = existing_filepath(data_path, data_file)
acq_data = AcquisitionData(input_file)
# Get size of current k-space data as tuple