data_models/data_model_helpers.py
def export_convolutionfunction_to_hdf5(cf, filename):
    """ Export a ConvolutionFunction to HDF5 format

    :param cf:
    :param filename:
    :return:
    """
    
    if not isinstance(cf, collections.Iterable):
        cf = [cf]
    with h5py.File(filename, 'w') as f:
        f.attrs['number_data_models'] = len(cf)
        for i, m in enumerate(cf):
            assert isinstance(m, ConvolutionFunction)
            mf = f.create_group('ConvolutionFunction%d' % i)
            convert_convolutionfunction_to_hdf(m, mf)
        f.flush()
        f.close()
 Export a ConvolutionFunction to HDF5 format

    :param cf:
    :param filename:
    :return:
    
Export a ConvolutionFunction to HDF5 format
Export a ConvolutionFunction to HDF5 format
def export_convolutionfunction_to_hdf5(cf, filename):
    if not isinstance(cf, collections.Iterable):
        cf = [cf]
    with h5py.File(filename, 'w') as f:
        f.attrs['number_data_models'] = len(cf)
        for i, m in enumerate(cf):
            assert isinstance(m, ConvolutionFunction)
            mf = f.create_group('ConvolutionFunction%d' % i)
            convert_convolutionfunction_to_hdf(m, mf)
        f.flush()
        f.close()
def export_convolutionfunction_to_hdf5 ( cf , filename ) : if not isinstance ( cf , collections . Iterable ) : cf = [ cf ] with h5py . File ( filename , 'w' ) as f : f . attrs [ 'number_data_models' ] = len ( cf ) for i , m in enumerate ( cf ) : assert isinstance ( m , ConvolutionFunction ) mf = f . create_group ( 'ConvolutionFunction%d' % i ) convert_convolutionfunction_to_hdf ( m , mf ) f . flush ( ) f . close ( )
Export a ConvolutionFunction to HDF5 format
Export a ConvolutionFunction to HDF5 format
""" Export a ConvolutionFunction to HDF5 format

    :param cf:
    :param filename:
    :return:
    """
None
cf
None
filename
None