Exemple #1
0
def _load_dump(path):
    """
    Load binary Radia dump object
    :param path: (str) Path to the Radia dump file
    :return: (Radia object)
    """
    with open(path, 'rb') as ff:
        result = ff.read()
        solved_magnet = radia.UtiDmpPrs(result)
        return solved_magnet
Exemple #2
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def compute_fields(points_list, radia_object_id = None, field_component = 'bz'):

    m = len(points_list)
    k = m / size

    ## decompose the domain of the field calcaulation to the different processors and send the arrays
    if rank == 0:
        radia_object = rad.UtiDmp([radia_object_id], 'bin')

        for i in range(1, size):
            comm.send(radia_object, dest = i)

    else:
        radia_object = comm.recv(source = 0)

    device_id = rad.UtiDmpPrs(radia_object)

    ## convert the arrrays back into radia friendly format
    calc_points = np.asarray(points_list[rank::size])
    radia_points = np.ndarray.tolist(calc_points)

    # Compute the fields at the points specified 
    field_result = rad.Fld(device_id, field_component, radia_points)

    # construct arrays to gather points and field solution for plotting and analysis
    sendbuf = np.column_stack([calc_points, np.asarray(field_result)])
    row,col = sendbuf.shape

    recvbuf = None

    if rank == 0:
        recvbuf = np.empty([size, k+1, col])

    # Gather the arrays from the different processors
    comm.Gather(sendbuf, recvbuf, root = 0)

    # Return the field result
    if rank == 0:
        # clean up the data after collecting it
        data_out = recvbuf.reshape([size * (k + 1), col])
        bad_points = np.where((data_out > 1.0e20) + (data_out < -1.0e20) )

        data_out = np.delete(data_out, bad_points[0], axis = 0)

        # sort the data before returning, sort by x, then y, then z
        indices = np.lexsort((data_out[:,0], data_out[:,1], data_out[:,2]))
        data_out = [data_out[i,:]for i in indices]

        return np.asarray(data_out)

    else:
        return None
Exemple #3
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def load_bin(data):
    return radia.UtiDmpPrs(data)
Exemple #4
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rad.TrfOrnt(mag01, trf06)

#rad.ObjDrwOpenGL(mag01)

matNdFeB = rad.MatStd('NdFeB')
M = rad.MatMvsH(matNdFeB, 'M', [0,0,0])
print('NdFeB material index:', matNdFeB, ' Magnetization:', M)

matLin01 = rad.MatLin([0.1,0.2],1.1)
matLin02 = rad.MatLin([0.1,0.2],[0,0,1.1])
print('Linear material indexes:', matLin01, matLin02)

dmp = rad.UtiDmp([mag01, trf02], 'bin')
#print(dmp)

elemsRest = rad.UtiDmpPrs(dmp)
print('Indexes of restored elements:', elemsRest)
#rad.ObjDrwOpenGL(elemsRest[0])

print(rad.UtiDmp(elemsRest[0], 'asc'))
print(rad.UtiDmp(elemsRest[1], 'asc'))

#rad.UtiDel(elemsRest[0])
#print(rad.UtiDmp(elemsRest[0], 'asc'))

print(rad.UtiDmp(trf03, 'asc'))
rad.UtiDelAll()
print(rad.UtiDmp(trf03, 'asc'))


#cutMag = rad.ObjCutMag(mag, [0,0,50], [0,0,1], "Frame->Lab")