def test_cython_mapping(self):
set_up_parameters = {
'sigma_G': 0.0, # Below electrode
'sigma_T': 0.3, # Tissue
'sigma_S': 0.3, # Saline
'slice_thickness': 200.,
'steps': 20
}
xstart = np.array([100., 0, -100., -110])
xend = np.array([100., 0, -100., -110]) + 100.
ystart = np.array([100., 0, -100, 200.])
yend = np.array([100., 0, -100, 200]) + 100.
zstart = np.array([10, 0, -10, -50.])
zend = np.array([10, 0, -10, -50]) + 10.
xmid = xstart
ymid = ystart
zmid = zstart
elec_x = (np.arange(3) - 1) * 50.
elec_y = (np.arange(3) - 1) * 50.
#elec_x = np.array([0.])
#elec_y = np.array([0.])
elec_z = -set_up_parameters['slice_thickness'] / 2.
elec_r = 1
n_avrg_points = 100
ext_sim_dict = {
'elec_x': elec_x,
'elec_y': elec_y,
'elec_z': elec_z,
'include_elec': False,
'use_line_source': False,
'moi_steps': set_up_parameters['steps'],
'n_avrg_points': n_avrg_points,
'elec_radius': elec_r
}
moi = MoI(set_up_parameters=set_up_parameters)
mapping = moi.make_mapping_standalone(ext_sim_dict,
xstart=xstart,
ystart=ystart,
zstart=zstart,
xend=xend,
yend=yend,
zend=zend,
xmid=xmid,
ymid=ymid,
zmid=zmid)
mapping2 = moi.make_mapping_cython(ext_sim_dict,
xstart=xstart,
ystart=ystart,
zstart=zstart,
xend=xend,
yend=yend,
zend=zend,
xmid=xmid,
ymid=ymid,
zmid=zmid)
error = np.abs((mapping - mapping2) / mapping2)
self.assertLessEqual(np.max(error), 0.001)
def test_cython_mapping(self):
set_up_parameters = {
"sigma_G": 0.0, # Below electrode
"sigma_T": 0.3, # Tissue
"sigma_S": 0.3, # Saline
"slice_thickness": 200.0,
"steps": 20,
}
xstart = np.array([100.0, 0, -100.0, -110])
xend = np.array([100.0, 0, -100.0, -110]) + 100.0
ystart = np.array([100.0, 0, -100, 200.0])
yend = np.array([100.0, 0, -100, 200]) + 100.0
zstart = np.array([10, 0, -10, -50.0])
zend = np.array([10, 0, -10, -50]) + 10.0
xmid = xstart
ymid = ystart
zmid = zstart
elec_x = (np.arange(3) - 1) * 50.0
elec_y = (np.arange(3) - 1) * 50.0
# elec_x = np.array([0.])
# elec_y = np.array([0.])
elec_z = -set_up_parameters["slice_thickness"] / 2.0
elec_r = 1
n_avrg_points = 100
ext_sim_dict = {
"elec_x": elec_x,
"elec_y": elec_y,
"elec_z": elec_z,
"include_elec": False,
"use_line_source": False,
"moi_steps": set_up_parameters["steps"],
"n_avrg_points": n_avrg_points,
"elec_radius": elec_r,
}
moi = MoI(set_up_parameters=set_up_parameters)
mapping = moi.make_mapping_standalone(
ext_sim_dict,
xstart=xstart,
ystart=ystart,
zstart=zstart,
xend=xend,
yend=yend,
zend=zend,
xmid=xmid,
ymid=ymid,
zmid=zmid,
)
mapping2 = moi.make_mapping_cython(
ext_sim_dict,
xstart=xstart,
ystart=ystart,
zstart=zstart,
xend=xend,
yend=yend,
zend=zend,
xmid=xmid,
ymid=ymid,
zmid=zmid,
)
error = np.abs((mapping - mapping2) / mapping2)
self.assertLessEqual(np.max(error), 0.001)
def compute_electrodecoeffs(self):
'''
compute for each cell their corresponding mapping of compartment
membrane currents to each electrode contact point
'''
coefffile = os.path.join(self.savefolder, 'electrodecoeffs.h5')
moi = MoI(self.paramsMoI)
coeffs = []
if os.path.isfile(coefffile):
if MASTER_MODE:
print 'loading electrode mappings from file %s' % coefffile
f = h5py.File(coefffile, 'r')
allcoeffs = {}
for cellindex in range(self.POPULATION_SIZE):
allcoeffs.update({
cellindex : f['cell%.3i' % cellindex].value
})
f.close()
else:
allcoeffs = None
return COMM.bcast(allcoeffs, root=0)
else:
for cellindex in range(self.POPULATION_SIZE):
if divmod(cellindex, SIZE)[1] == RANK:
cell = self.cellsim(cellindex, return_just_cell=True)
mapping = moi.make_mapping_cython(self.paramsMapping,
xmid=cell.xmid,
ymid=cell.ymid,
zmid=cell.zmid,
xstart=cell.xstart,
ystart=cell.ystart,
zstart=cell.zstart,
xend=cell.xend,
yend=cell.yend,
zend=cell.zend,
morphology=cell.morphology)
coeffs.append({cellindex : mapping})
#sync MPI threads, communicate coefficients between ranks
COMM.Barrier()
coeffs = COMM.gather(coeffs, root=0)
if RANK == 0:
allcoeffs = {}
for i in range(SIZE):
for item in coeffs[i]:
allcoeffs.update(item)
#write mappings to HDF5
print 'writing electrode mappings to file %s' % coefffile
f = h5py.File(coefffile, 'a', compression='gzip')
for cellindex in range(self.POPULATION_SIZE):
f['cell%.3i' % cellindex] = allcoeffs[cellindex]
f.close()
else:
allcoeffs = None
return COMM.bcast(allcoeffs, root=0)
