def single_dipole_search(electrode_potential, leadfield, mesh_file, elements_to_consider=[1002]):
from forward.mesh import read_mesh, get_closest_element_to_point
from nipype import logging
iflogger = logging.getLogger('interface')
geo_file = op.abspath("search_points.geo")
data_name = "leadfield"
lf_data_file = h5py.File(leadfield, "r")
lf_data = lf_data_file.get(data_name)
leadfield_matrix = lf_data.value
_, lf_name, _ = split_filename(leadfield)
bounds = (0,leadfield_matrix.shape[0]/3)
mesh_data, _, _, _ = read_mesh(mesh_file, elements_to_consider)
centroids = []
element_ids = []
for poly in mesh_data:
element_ids.append(poly["element_id"])
centroids.append(poly["centroid"])
p0, bounds = random_initial_guess(centroids)
#p0 = np.array([0,0,60])
mw = {}
args = (leadfield_matrix, electrode_potential, centroids, element_ids)
mw['args'] = args
#mw['bounds'] = bounds
#res = so.basinhopping(calculate_element_cost, p0, T=0.01, stepsize = 3, minimizer_kwargs=mw, disp=True, niter_success=20)
# Perform downhill search, minimizing cost function
xopt, fopt, n_iter, funcalls, _, allvecs = so.fmin(calculate_element_cost, p0, ftol=0.00000001, args=(leadfield_matrix, electrode_potential, centroids, element_ids), xtol = 1, disp=True, full_output=True, retall=True)
write_search_points(allvecs, geo_file)
# Need to minimize cost by changing values of orientation and magnitude:
_, element_idx, centroid, element_data, lf_idx = get_closest_element_to_point(mesh_file, elements_to_consider, np.array([xopt]))
L = np.transpose(leadfield_matrix[lf_idx * 3:lf_idx * 3 + 3])
V = electrode_potential
qopt, _, _, _ = np.linalg.lstsq(L, V)
return xopt, qopt, element_data, geo_file
def rewrite_mesh_from_binary_mask(mask_file,
mesh_file,
mesh_id,
new_phys_id=1015):
# Takes about 8 minutes
import numpy as np
import nibabel as nb
import os.path as op
from forward.mesh import read_mesh
from nipype import logging
iflogger = logging.getLogger('interface')
mask_img = nb.load(mask_file)
mask_data = mask_img.get_data()
mask_affine = mask_img.get_affine()
mask_header = mask_img.get_header()
#tensor_data = np.flipud(tensor_image.get_data())
# Define various constants
elements_to_consider = [1002] #Use only white matter
vx, vy, vz = mask_header.get_zooms()[0:3]
max_x, max_y, max_z = np.shape(mask_data)[0:3]
halfx, halfy, halfz = np.array((vx * max_x, vy * max_y, vz * max_z)) / 2.0
mesh_data, _, _, _ = read_mesh(mesh_file, elements_to_consider)
elem_list = []
for idx, poly in enumerate(mesh_data):
i = np.round((poly['centroid'][0] + halfx) / vx).astype(int)
j = np.round((poly['centroid'][1] + halfy) / vy).astype(int)
k = np.round((poly['centroid'][2] + halfz) / vz).astype(int)
if mask_data[i, j, k]:
elem_list.append(poly['element_id'])
#iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
new_elem_id = new_phys_id + 2000
out_file = swap_element_ids(mesh_file, elem_list, new_elem_id, new_phys_id)
print('Writing binary masked mesh file to %s' % out_file)
return out_file
def rewrite_mesh_from_binary_mask(mask_file, mesh_file, mesh_id, new_phys_id=1015):
# Takes about 8 minutes
import numpy as np
import nibabel as nb
import os.path as op
from forward.mesh import read_mesh
from nipype import logging
iflogger = logging.getLogger('interface')
mask_img = nb.load(mask_file)
mask_data = mask_img.get_data()
mask_affine = mask_img.get_affine()
mask_header = mask_img.get_header()
#tensor_data = np.flipud(tensor_image.get_data())
# Define various constants
elements_to_consider = [1002] #Use only white matter
vx, vy, vz = mask_header.get_zooms()[0:3]
max_x, max_y, max_z = np.shape(mask_data)[0:3]
halfx, halfy, halfz = np.array((vx*max_x, vy*max_y, vz*max_z))/2.0
mesh_data, _, _, _ = read_mesh(mesh_file, elements_to_consider)
elem_list = []
for idx, poly in enumerate(mesh_data):
i = np.round((poly['centroid'][0]+halfx)/vx).astype(int)
j = np.round((poly['centroid'][1]+halfy)/vy).astype(int)
k = np.round((poly['centroid'][2]+halfz)/vz).astype(int)
if mask_data[i,j,k]:
elem_list.append(poly['element_id'])
#iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
new_elem_id = new_phys_id+2000
out_file = swap_element_ids(mesh_file, elem_list, new_elem_id, new_phys_id)
print('Writing binary masked mesh file to %s' % out_file)
return out_file
def include_gmsh_tensor_elements(mesh_file, tensor_file, mask_file, mask_threshold=0.5, lower_triangular=True):
import numpy as np
import nibabel as nb
from nipype.utils.filemanip import split_filename
import os.path as op
from forward.mesh import read_mesh
from nipype import logging
import shutil
iflogger = logging.getLogger("interface")
# Load 4D (6 volume upper or lower triangular) conductivity tensor image
tensor_image = nb.load(tensor_file)
tensor_data = np.flipud(tensor_image.get_data())
# Correct the tensors after flipping in the X direction
tensor_data[:, :, :, 1] *= -1
if lower_triangular:
tensor_data[:, :, :, 3] *= -1
else:
tensor_data[:, :, :, 2] *= -1
# Load mask (usually fractional anisotropy) image
mask_image = nb.load(mask_file)
mask_data = np.flipud(mask_image.get_data())
header = tensor_image.get_header()
# Make sure the files share the same (3D) dimensions before continuing
assert np.shape(tensor_data)[0:3] == np.shape(mask_data)[0:3]
# Define various constants
elements_to_consider = [1001] # Use only white matter
vx, vy, vz = header.get_zooms()[0:3]
max_x, max_y, max_z = np.shape(tensor_data)[0:3]
halfx, halfy, halfz = np.array((vx * max_x, vy * max_y, vz * max_z)) / 2.0
mesh_data, _, _, _ = read_mesh(mesh_file, elements_to_consider)
# Create the output mesh file
path, name, ext = split_filename(mesh_file)
out_file = op.abspath(name + "_cond.msh")
iflogger.info("Copying current mesh file to %s" % out_file)
shutil.copyfile(mesh_file, out_file)
f = open(out_file, "a") # Append to the end of the file
iflogger.info("Appending Conductivity tensors to %s" % out_file)
# Write the tag information to the file:
num_polygons = len(mesh_data)
f.write("$ElementData\n")
str_tag = '"Conductivity"'
timestep = 0.0001
f.write("1\n") # Num String tags
f.write(str_tag + "\n")
f.write("1\n") # Num Real tags
f.write("%f\n" % timestep)
# Three integer tags: timestep, num field components, num elements
f.write("3\n") # Three int tags
f.write("0\n") # Time step index
f.write("9\n") # Num field components
# Get the centroid of all white matter elements
# Find out which voxel they lie inside
iflogger.info("Getting tensor for each element")
# ipdb.set_trace()
nonzero = 0
elem_list = []
if lower_triangular:
for idx, poly in enumerate(mesh_data):
i = np.round((poly["centroid"][0] + halfx) / vx).astype(int)
j = np.round((poly["centroid"][1] + halfy) / vy).astype(int)
k = np.round((poly["centroid"][2] + halfz) / vz).astype(int)
T = tensor_data[i, j, k]
if not (all(T == 0) and mask_data[i, j, k] >= mask_threshold):
elementdata_str = "%d %e %e %e %e %e %e %e %e %e\n" % (
poly["element_id"],
T[0],
T[1],
T[3],
T[1],
T[2],
T[4],
T[3],
T[4],
T[5],
)
elem_list.append(elementdata_str)
nonzero += 1
# iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
else:
for idx, poly in enumerate(mesh_data):
i = np.round((poly["centroid"][0] + halfx) / vx).astype(int)
j = np.round((poly["centroid"][1] + halfy) / vy).astype(int)
k = np.round((poly["centroid"][2] + halfz) / vz).astype(int)
T = tensor_data[i, j, k]
if not (all(T == 0) and mask_data[i, j, k] >= mask_threshold):
elementdata_str = "%d %e %e %e %e %e %e %e %e %e\n" % (
poly["element_id"],
T[0],
T[1],
T[2],
T[1],
T[3],
T[4],
T[2],
T[4],
T[5],
)
elem_list.append(elementdata_str)
nonzero += 1
# iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
f.write("%d\n" % nonzero) # Num nonzero field components
for elementdata_str in elem_list:
f.write(elementdata_str)
f.write("$EndElementData\n")
f.write("$ElementData\n")
str_tag = '"FA"'
timestep = 0.0002
f.write("1\n") # Num String tags
f.write(str_tag + "\n")
f.write("1\n") # Num Real tags
f.write("%f\n" % timestep)
# Three integer tags: timestep, num field components, num elements
f.write("3\n") # Three int tags
f.write("1\n") # Time step index
f.write("1\n") # Num field components
# Get the centroid of all white matter elements
# Find out which voxel they lie inside
iflogger.info("Writing FA for each element")
# ipdb.set_trace()
nonzero = 0
elem_list = []
for idx, poly in enumerate(mesh_data):
i = np.round((poly["centroid"][0] + halfx) / vx).astype(int)
j = np.round((poly["centroid"][1] + halfy) / vy).astype(int)
k = np.round((poly["centroid"][2] + halfz) / vz).astype(int)
if mask_data[i, j, k] > 0:
elementdata_str = "%d %e\n" % (poly["element_id"], mask_data[i, j, k])
elem_list.append(elementdata_str)
nonzero += 1
# iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
f.write("%d\n" % nonzero) # Num nonzero field components
for elementdata_str in elem_list:
f.write(elementdata_str)
f.write("$EndElementData\n")
f.close()
iflogger.info("Finished writing to %s" % out_file)
return out_file
import numpy as np
from forward.mesh import read_mesh
n_electrodes = 42
elem_to_consider = [1000, 1002, 1003, 1004]
elem_to_consider.extend(range(5000, 5000+n_electrodes))
mesh_data, nodes, elem, labels = read_mesh('4shell_elec.msh', elem_to_consider)
np.savetxt('nodes.txt', nodes)
np.savetxt('elem.txt', elem)
np.savetxt('labels.txt', labels)
def cost_function_mapping(potential, leadfield, mesh_file, mesh_id):
import os.path as op
import numpy as np
import h5py
import shutil
from forward.mesh import read_mesh
from nipype.utils.filemanip import split_filename
from nipype import logging
iflogger = logging.getLogger('interface')
data_name = "leadfield"
lf_data_file = h5py.File(leadfield, "r")
lf_data = lf_data_file.get(data_name)
leadfield_matrix = lf_data.value
_, lf_name, _ = split_filename(leadfield)
V = np.load(potential)
# ---- Resave the mesh with the cost function as element data ---- #
mesh_data, _, _, _ = read_mesh(mesh_file, [mesh_id])
# Create the output mesh file
path, name, ext = split_filename(mesh_file)
cost_mesh_file = op.abspath(name + "_cost.msh")
iflogger.info('Copying current mesh file to %s' % cost_mesh_file)
shutil.copyfile(mesh_file, cost_mesh_file)
f = open(cost_mesh_file,'a') #Append to the end of the file
iflogger.info('Appending cost function scalars to %s' % cost_mesh_file)
# Write the tag information to the file:
f.write('$ElementData\n')
str_tag = '"Cost function %s"' % (leadfield)
timestep = 0.0001
f.write('1\n') #Num String tags
f.write(str_tag + '\n')
f.write('1\n') #Num Real tags
f.write('%f\n' % timestep)
#Three integer tags: timestep, num field components, num elements
f.write('3\n') #Three int tags
f.write('0\n') #Time step index
f.write('1\n') #Num field components
elem_list = []
elem_idx_list = []
cost_list = []
assert(len(mesh_data)*3 == leadfield_matrix.shape[0])
for lf_idx, poly in enumerate(mesh_data):
L = np.transpose(leadfield_matrix[lf_idx * 3:lf_idx * 3 + 3])
I = np.eye(len(V))
Linv = np.linalg.pinv(L)
val = np.dot(V.T, I - np.dot(L,Linv))
R = np.dot(val,V)
cost = np.linalg.norm(R)
#cost = np.sqrt(R / np.linalg.norm(V))
cost_list.append(cost)
elem_idx_list.append(poly["element_id"])
elementdata_str = ('%d %e\n' % (poly["element_id"], cost))
elem_list.append(elementdata_str)
#iflogger.info("%3.3f%%" % (float(lf_idx)/num_polygons*100.0))
import ipdb
ipdb.set_trace()
minidx = cost_list.index(np.min(cost_list))
maxidx = cost_list.index(np.max(cost_list))
print(elem_idx_list[minidx], elem_idx_list[maxidx])
f.write('%d\n' % len(mesh_data)) #Num nonzero field components
for elementdata_str in elem_list:
f.write(elementdata_str)
f.write('$EndElementData\n')
f.close()
iflogger.info("Finished writing to %s" % cost_mesh_file)
cost_geo_file = ""
return cost_mesh_file, cost_geo_file
def cost_function_mapping(potential, leadfield, mesh_file, mesh_id):
import os.path as op
import numpy as np
import h5py
import shutil
from forward.mesh import read_mesh
from nipype.utils.filemanip import split_filename
from nipype import logging
iflogger = logging.getLogger('interface')
data_name = "leadfield"
lf_data_file = h5py.File(leadfield, "r")
lf_data = lf_data_file.get(data_name)
leadfield_matrix = lf_data.value
_, lf_name, _ = split_filename(leadfield)
V = np.load(potential)
# ---- Resave the mesh with the cost function as element data ---- #
mesh_data, _, _, _ = read_mesh(mesh_file, [mesh_id])
# Create the output mesh file
path, name, ext = split_filename(mesh_file)
cost_mesh_file = op.abspath(name + "_cost.msh")
iflogger.info('Copying current mesh file to %s' % cost_mesh_file)
shutil.copyfile(mesh_file, cost_mesh_file)
f = open(cost_mesh_file, 'a') #Append to the end of the file
iflogger.info('Appending cost function scalars to %s' % cost_mesh_file)
# Write the tag information to the file:
f.write('$ElementData\n')
str_tag = '"Cost function %s"' % (leadfield)
timestep = 0.0001
f.write('1\n') #Num String tags
f.write(str_tag + '\n')
f.write('1\n') #Num Real tags
f.write('%f\n' % timestep)
#Three integer tags: timestep, num field components, num elements
f.write('3\n') #Three int tags
f.write('0\n') #Time step index
f.write('1\n') #Num field components
elem_list = []
elem_idx_list = []
cost_list = []
assert (len(mesh_data) * 3 == leadfield_matrix.shape[0])
for lf_idx, poly in enumerate(mesh_data):
L = np.transpose(leadfield_matrix[lf_idx * 3:lf_idx * 3 + 3])
I = np.eye(len(V))
Linv = np.linalg.pinv(L)
val = np.dot(V.T, I - np.dot(L, Linv))
R = np.dot(val, V)
cost = np.linalg.norm(R)
#cost = np.sqrt(R / np.linalg.norm(V))
cost_list.append(cost)
elem_idx_list.append(poly["element_id"])
elementdata_str = ('%d %e\n' % (poly["element_id"], cost))
elem_list.append(elementdata_str)
#iflogger.info("%3.3f%%" % (float(lf_idx)/num_polygons*100.0))
import ipdb
ipdb.set_trace()
minidx = cost_list.index(np.min(cost_list))
maxidx = cost_list.index(np.max(cost_list))
print(elem_idx_list[minidx], elem_idx_list[maxidx])
f.write('%d\n' % len(mesh_data)) #Num nonzero field components
for elementdata_str in elem_list:
f.write(elementdata_str)
f.write('$EndElementData\n')
f.close()
iflogger.info("Finished writing to %s" % cost_mesh_file)
cost_geo_file = ""
return cost_mesh_file, cost_geo_file
import numpy as np
from forward.mesh import read_mesh
n_electrodes = 42
elem_to_consider = [1000, 1002, 1003, 1004]
elem_to_consider.extend(range(5000, 5000 + n_electrodes))
mesh_data, nodes, elem, labels = read_mesh('4shell_elec.msh', elem_to_consider)
np.savetxt('nodes.txt', nodes)
np.savetxt('elem.txt', elem)
np.savetxt('labels.txt', labels)
def compare_leadfields(leadfield1, leadfield2, mesh_file, write_mesh=True):
'''
Compares two leadfield matrices and outputs the difference as
scalars attached to a mesh file. The mesh file must have the
same number of elements as the leadfield's second dimension
FEM reciprocity leadfield is M x N where M is the number of sensors
and N is the number of elements. Mesh file must have N elements.
e.g. isotropic white matter conductivity
vs. anisotropic conductivity from estimated diffusion tensors
'''
import os.path as op
import h5py
import numpy as np
import shutil
from forward.mesh import read_mesh
from nipype.utils.filemanip import split_filename
from nipype import logging
iflogger = logging.getLogger('interface')
data_name = "leadfield"
print("Reading leadfield 1: %s" % leadfield1)
lf1_data_file = h5py.File(leadfield1, "r")
lf1_data = lf1_data_file.get(data_name)
leadfield_matrix1 = lf1_data.value
print("Reading leadfield 2: %s" % leadfield2)
lf2_data_file = h5py.File(leadfield2, "r")
lf2_data = lf2_data_file.get(data_name)
leadfield_matrix2 = lf2_data.value
path, name, ext = split_filename(mesh_file)
if write_mesh:
# Electric field elements are only saved in the gray matter
#elements_to_consider = [1001] #For Sphere
elements_to_consider = [1002] #For head models
mesh_data, _, _, _ = read_mesh(mesh_file, elements_to_consider)
# Create the output mesh file
rms_mesh_file = op.abspath(name + "_rmse.msh")
iflogger.info('Copying current mesh file to %s' % rms_mesh_file)
shutil.copyfile(mesh_file, rms_mesh_file)
f = open(rms_mesh_file,'a') #Append to the end of the file
iflogger.info('Appending root mean squared error scalars to %s' % rms_mesh_file)
else:
rms_mesh_file = None
out_rms_hdf5_file_x = op.abspath(name + "_rmse_x.hdf5")
out_rms_hdf5_file_y = op.abspath(name + "_rmse_y.hdf5")
out_rms_hdf5_file_z = op.abspath(name + "_rmse_z.hdf5")
out_rms_hdf5_file_avg = op.abspath(name + "_rmse_avg.hdf5")
rms_hdf5_file_x = h5py.File(out_rms_hdf5_file_x, "w")
rms_hdf5_file_y = h5py.File(out_rms_hdf5_file_y, "w")
rms_hdf5_file_z = h5py.File(out_rms_hdf5_file_z, "w")
rms_hdf5_file_avg = h5py.File(out_rms_hdf5_file_avg, "w")
# Write the tag information to the file:
if write_mesh:
num_polygons = len(mesh_data)
_, name1, _ = split_filename(leadfield1)
_, name2, _ = split_filename(leadfield2)
#For testing
#noise = np.random.normal(0,1,leadfield_matrix2.shape)
#leadfield_matrix2 = leadfield_matrix2 + noise
# Reshape the leadfields so they are M x 3 x N vectors (x, y, z direction of electric field)
leadfield_mesh1 = np.reshape(leadfield_matrix1, (leadfield_matrix1.shape[0]/3,3,leadfield_matrix1.shape[1]))
leadfield_mesh2 = np.reshape(leadfield_matrix2, (leadfield_matrix2.shape[0]/3,3,leadfield_matrix2.shape[1]))
#Check that the dimensions are appropriate
try:
if write_mesh:
assert(len(mesh_data) == leadfield_mesh1.shape[0] == leadfield_mesh2.shape[0])
else:
assert(leadfield_mesh1.shape[0] == leadfield_mesh2.shape[0])
except AssertionError:
iflogger.error("Lead fields could not be compared because the " \
"number of elements in the files do not match")
if write_mesh:
iflogger.error("Elements in %s: %d" % (mesh_file, len(mesh_data)))
iflogger.error("Elements in leadfield 1 %s: %d" % (leadfield1, leadfield_mesh1.shape[0]))
iflogger.error("Elements in leadfield 2 %s: %d" % (leadfield2, leadfield_mesh2.shape[0]))
raise Exception
# Get the mean squared difference between electric field vectors by sensor and element
diff = leadfield_mesh2 - leadfield_mesh1
# Gets the norm of the difference for X, Y, and Z directions
norm_x_diff = np.linalg.norm(diff[:,0,:],axis=1)
norm_y_diff = np.linalg.norm(diff[:,1,:],axis=1)
norm_z_diff = np.linalg.norm(diff[:,2,:],axis=1)
norm_lf1_x = np.linalg.norm(leadfield_mesh1[:,0,:], axis=1)
norm_lf1_y = np.linalg.norm(leadfield_mesh1[:,1,:], axis=1)
norm_lf1_z = np.linalg.norm(leadfield_mesh1[:,2,:], axis=1)
rmse_x = norm_x_diff / norm_lf1_x
rmse_y = norm_y_diff / norm_lf1_y
rmse_z = norm_z_diff / norm_lf1_z
rmse = (rmse_x + rmse_y + rmse_z) / 3.
assert(leadfield_mesh2.shape[0] == rmse.shape[0])
if write_mesh:
rmse_avg_list = []
rmse_x_list = []
rmse_y_list = []
rmse_z_list = []
for idx, poly in enumerate(mesh_data):
rmse_avg_str = ('%d %e \n' % (poly["element_id"], rmse[idx]))
rmse_avg_list.append(rmse_avg_str)
rmse_x_str = ('%d %e \n' % (poly["element_id"], rmse_x[idx]))
rmse_x_list.append(rmse_x_str)
rmse_y_str = ('%d %e \n' % (poly["element_id"], rmse_y[idx]))
rmse_y_list.append(rmse_y_str)
rmse_z_str = ('%d %e \n' % (poly["element_id"], rmse_z[idx]))
rmse_z_list.append(rmse_z_str)
iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
# ----- Average RMSE ----- #
f.write('$ElementData\n')
str_tag = '"Average Root Mean Squared Error"'
timestep = 0.0001
f.write('1\n') #Num String tags
f.write(str_tag + '\n')
f.write('1\n') #Num Real tags
f.write('%f\n' % timestep)
#Three integer tags: timestep, num field components, num elements
f.write('3\n') #Three int tags
f.write('0\n') #Time step index
f.write('1\n') #Num field components
f.write('%d\n' % len(mesh_data)) #Num nonzero field components
for elementdata_str in rmse_avg_list:
f.write(elementdata_str)
f.write('$EndElementData\n')
# ----- RMSE X ----- #
f.write('$ElementData\n')
str_tag = '"Root Mean Squared Error X-direction"'
timestep = 0.0002
f.write('1\n') #Num String tags
f.write(str_tag + '\n')
f.write('1\n') #Num Real tags
f.write('%f\n' % timestep)
#Three integer tags: timestep, num field components, num elements
f.write('3\n') #Three int tags
f.write('0\n') #Time step index
f.write('1\n') #Num field components
f.write('%d\n' % len(mesh_data)) #Num nonzero field components
for elementdata_str in rmse_x_list:
f.write(elementdata_str)
f.write('$EndElementData\n')
# ----- RMSE X ----- #
f.write('$ElementData\n')
str_tag = '"Root Mean Squared Error Y-direction"'
timestep = 0.0003
f.write('1\n') #Num String tags
f.write(str_tag + '\n')
f.write('1\n') #Num Real tags
f.write('%f\n' % timestep)
#Three integer tags: timestep, num field components, num elements
f.write('3\n') #Three int tags
f.write('0\n') #Time step index
f.write('1\n') #Num field components
f.write('%d\n' % len(mesh_data)) #Num nonzero field components
for elementdata_str in rmse_y_list:
f.write(elementdata_str)
f.write('$EndElementData\n')
# ----- RMSE X ----- #
f.write('$ElementData\n')
str_tag = '"Root Mean Squared Error Z-direction"'
timestep = 0.0004
f.write('1\n') #Num String tags
f.write(str_tag + '\n')
f.write('1\n') #Num Real tags
f.write('%f\n' % timestep)
#Three integer tags: timestep, num field components, num elements
f.write('3\n') #Three int tags
f.write('0\n') #Time step index
f.write('1\n') #Num field components
f.write('%d\n' % len(mesh_data)) #Num nonzero field components
for elementdata_str in rmse_z_list:
f.write(elementdata_str)
f.write('$EndElementData\n')
f.close()
iflogger.info("Finished writing to %s" % rms_mesh_file)
## Save RMSE data to an HDF5 file
dset_x = rms_hdf5_file_x.create_dataset("rmse_x", data=rmse_x)
dset_x[...] = rmse_x
dset_y = rms_hdf5_file_y.create_dataset("rmse_y", data=rmse_y)
dset_y[...] = rmse_y
dset_z = rms_hdf5_file_z.create_dataset("rmse_z", data=rmse_z)
dset_z[...] = rmse_z
dset = rms_hdf5_file_avg.create_dataset("rmse_avg", data=rmse)
dset[...] = rmse
rms_hdf5_file_x.close()
rms_hdf5_file_y.close()
rms_hdf5_file_z.close()
rms_hdf5_file_avg.close()
print("Saved RMSE-X matrix as %s" % out_rms_hdf5_file_x)
print("Saved RMSE-Y matrix as %s" % out_rms_hdf5_file_y)
print("Saved RMSE-Z matrix as %s" % out_rms_hdf5_file_z)
print("Saved RMSE-Avg matrix as %s" % out_rms_hdf5_file_avg)
###
return rms_mesh_file, out_rms_hdf5_file_avg, out_rms_hdf5_file_x, out_rms_hdf5_file_y, out_rms_hdf5_file_z
def compare_leadfields(leadfield1, leadfield2, mesh_file, write_mesh=True):
"""
Compares two leadfield matrices and outputs the difference as
scalars attached to a mesh file. The mesh file must have the
same number of elements as the leadfield's second dimension
FEM reciprocity leadfield is M x N where M is the number of sensors
and N is the number of elements. Mesh file must have N elements.
e.g. isotropic white matter conductivity
vs. anisotropic conductivity from estimated diffusion tensors
"""
import os.path as op
import h5py
import numpy as np
import shutil
from forward.mesh import read_mesh
from nipype.utils.filemanip import split_filename
from nipype import logging
iflogger = logging.getLogger("interface")
data_name = "leadfield"
print("Reading leadfield 1: %s" % leadfield1)
lf1_data_file = h5py.File(leadfield1, "r")
lf1_data = lf1_data_file.get(data_name)
leadfield_matrix1 = lf1_data.value
print("Reading leadfield 2: %s" % leadfield2)
lf2_data_file = h5py.File(leadfield2, "r")
lf2_data = lf2_data_file.get(data_name)
leadfield_matrix2 = lf2_data.value
path, name, ext = split_filename(mesh_file)
if write_mesh:
# Electric field elements are only saved in the gray matter
# elements_to_consider = [1001] #For Sphere
elements_to_consider = [1002] # For head models
mesh_data, _, _, _ = read_mesh(mesh_file, elements_to_consider)
# Create the output mesh file
rms_mesh_file = op.abspath(name + "_rmse.msh")
iflogger.info("Copying current mesh file to %s" % rms_mesh_file)
shutil.copyfile(mesh_file, rms_mesh_file)
f = open(rms_mesh_file, "a") # Append to the end of the file
iflogger.info("Appending root mean squared error scalars to %s" % rms_mesh_file)
else:
rms_mesh_file = None
out_rms_hdf5_file_x = op.abspath(name + "_rmse_x.hdf5")
out_rms_hdf5_file_y = op.abspath(name + "_rmse_y.hdf5")
out_rms_hdf5_file_z = op.abspath(name + "_rmse_z.hdf5")
out_rms_hdf5_file_avg = op.abspath(name + "_rmse_avg.hdf5")
rms_hdf5_file_x = h5py.File(out_rms_hdf5_file_x, "w")
rms_hdf5_file_y = h5py.File(out_rms_hdf5_file_y, "w")
rms_hdf5_file_z = h5py.File(out_rms_hdf5_file_z, "w")
rms_hdf5_file_avg = h5py.File(out_rms_hdf5_file_avg, "w")
# Write the tag information to the file:
if write_mesh:
num_polygons = len(mesh_data)
_, name1, _ = split_filename(leadfield1)
_, name2, _ = split_filename(leadfield2)
# For testing
# noise = np.random.normal(0,1,leadfield_matrix2.shape)
# leadfield_matrix2 = leadfield_matrix2 + noise
# Reshape the leadfields so they are M x 3 x N vectors (x, y, z direction of electric field)
leadfield_mesh1 = np.reshape(leadfield_matrix1, (leadfield_matrix1.shape[0] / 3, 3, leadfield_matrix1.shape[1]))
leadfield_mesh2 = np.reshape(leadfield_matrix2, (leadfield_matrix2.shape[0] / 3, 3, leadfield_matrix2.shape[1]))
# Check that the dimensions are appropriate
try:
if write_mesh:
assert len(mesh_data) == leadfield_mesh1.shape[0] == leadfield_mesh2.shape[0]
else:
assert leadfield_mesh1.shape[0] == leadfield_mesh2.shape[0]
except AssertionError:
iflogger.error("Lead fields could not be compared because the " "number of elements in the files do not match")
if write_mesh:
iflogger.error("Elements in %s: %d" % (mesh_file, len(mesh_data)))
iflogger.error("Elements in leadfield 1 %s: %d" % (leadfield1, leadfield_mesh1.shape[0]))
iflogger.error("Elements in leadfield 2 %s: %d" % (leadfield2, leadfield_mesh2.shape[0]))
raise Exception
# Get the mean squared difference between electric field vectors by sensor and element
diff = leadfield_mesh2 - leadfield_mesh1
# Gets the norm of the difference for X, Y, and Z directions
norm_x_diff = np.linalg.norm(diff[:, 0, :], axis=1)
norm_y_diff = np.linalg.norm(diff[:, 1, :], axis=1)
norm_z_diff = np.linalg.norm(diff[:, 2, :], axis=1)
norm_lf1_x = np.linalg.norm(leadfield_mesh1[:, 0, :], axis=1)
norm_lf1_y = np.linalg.norm(leadfield_mesh1[:, 1, :], axis=1)
norm_lf1_z = np.linalg.norm(leadfield_mesh1[:, 2, :], axis=1)
rmse_x = norm_x_diff / norm_lf1_x
rmse_y = norm_y_diff / norm_lf1_y
rmse_z = norm_z_diff / norm_lf1_z
rmse = (rmse_x + rmse_y + rmse_z) / 3.0
assert leadfield_mesh2.shape[0] == rmse.shape[0]
if write_mesh:
rmse_avg_list = []
rmse_x_list = []
rmse_y_list = []
rmse_z_list = []
for idx, poly in enumerate(mesh_data):
rmse_avg_str = "%d %e \n" % (poly["element_id"], rmse[idx])
rmse_avg_list.append(rmse_avg_str)
rmse_x_str = "%d %e \n" % (poly["element_id"], rmse_x[idx])
rmse_x_list.append(rmse_x_str)
rmse_y_str = "%d %e \n" % (poly["element_id"], rmse_y[idx])
rmse_y_list.append(rmse_y_str)
rmse_z_str = "%d %e \n" % (poly["element_id"], rmse_z[idx])
rmse_z_list.append(rmse_z_str)
iflogger.info("%3.3f%%" % (float(idx) / num_polygons * 100.0))
# ----- Average RMSE ----- #
f.write("$ElementData\n")
str_tag = '"Average Root Mean Squared Error"'
timestep = 0.0001
f.write("1\n") # Num String tags
f.write(str_tag + "\n")
f.write("1\n") # Num Real tags
f.write("%f\n" % timestep)
# Three integer tags: timestep, num field components, num elements
f.write("3\n") # Three int tags
f.write("0\n") # Time step index
f.write("1\n") # Num field components
f.write("%d\n" % len(mesh_data)) # Num nonzero field components
for elementdata_str in rmse_avg_list:
f.write(elementdata_str)
f.write("$EndElementData\n")
# ----- RMSE X ----- #
f.write("$ElementData\n")
str_tag = '"Root Mean Squared Error X-direction"'
timestep = 0.0002
f.write("1\n") # Num String tags
f.write(str_tag + "\n")
f.write("1\n") # Num Real tags
f.write("%f\n" % timestep)
# Three integer tags: timestep, num field components, num elements
f.write("3\n") # Three int tags
f.write("0\n") # Time step index
f.write("1\n") # Num field components
f.write("%d\n" % len(mesh_data)) # Num nonzero field components
for elementdata_str in rmse_x_list:
f.write(elementdata_str)
f.write("$EndElementData\n")
# ----- RMSE X ----- #
f.write("$ElementData\n")
str_tag = '"Root Mean Squared Error Y-direction"'
timestep = 0.0003
f.write("1\n") # Num String tags
f.write(str_tag + "\n")
f.write("1\n") # Num Real tags
f.write("%f\n" % timestep)
# Three integer tags: timestep, num field components, num elements
f.write("3\n") # Three int tags
f.write("0\n") # Time step index
f.write("1\n") # Num field components
f.write("%d\n" % len(mesh_data)) # Num nonzero field components
for elementdata_str in rmse_y_list:
f.write(elementdata_str)
f.write("$EndElementData\n")
# ----- RMSE X ----- #
f.write("$ElementData\n")
str_tag = '"Root Mean Squared Error Z-direction"'
timestep = 0.0004
f.write("1\n") # Num String tags
f.write(str_tag + "\n")
f.write("1\n") # Num Real tags
f.write("%f\n" % timestep)
# Three integer tags: timestep, num field components, num elements
f.write("3\n") # Three int tags
f.write("0\n") # Time step index
f.write("1\n") # Num field components
f.write("%d\n" % len(mesh_data)) # Num nonzero field components
for elementdata_str in rmse_z_list:
f.write(elementdata_str)
f.write("$EndElementData\n")
f.close()
iflogger.info("Finished writing to %s" % rms_mesh_file)
## Save RMSE data to an HDF5 file
dset_x = rms_hdf5_file_x.create_dataset("rmse_x", data=rmse_x)
dset_x[...] = rmse_x
dset_y = rms_hdf5_file_y.create_dataset("rmse_y", data=rmse_y)
dset_y[...] = rmse_y
dset_z = rms_hdf5_file_z.create_dataset("rmse_z", data=rmse_z)
dset_z[...] = rmse_z
dset = rms_hdf5_file_avg.create_dataset("rmse_avg", data=rmse)
dset[...] = rmse
rms_hdf5_file_x.close()
rms_hdf5_file_y.close()
rms_hdf5_file_z.close()
rms_hdf5_file_avg.close()
print("Saved RMSE-X matrix as %s" % out_rms_hdf5_file_x)
print("Saved RMSE-Y matrix as %s" % out_rms_hdf5_file_y)
print("Saved RMSE-Z matrix as %s" % out_rms_hdf5_file_z)
print("Saved RMSE-Avg matrix as %s" % out_rms_hdf5_file_avg)
###
return rms_mesh_file, out_rms_hdf5_file_avg, out_rms_hdf5_file_x, out_rms_hdf5_file_y, out_rms_hdf5_file_z
def include_gmsh_tensor_elements(mesh_file,
tensor_file,
mask_file,
mask_threshold=0.5,
lower_triangular=True):
import numpy as np
import nibabel as nb
from nipype.utils.filemanip import split_filename
import os.path as op
from forward.mesh import read_mesh
from nipype import logging
import shutil
iflogger = logging.getLogger('interface')
# Load 4D (6 volume upper or lower triangular) conductivity tensor image
tensor_image = nb.load(tensor_file)
tensor_data = np.flipud(tensor_image.get_data())
# Correct the tensors after flipping in the X direction
tensor_data[:, :, :, 1] *= -1
if lower_triangular:
tensor_data[:, :, :, 3] *= -1
else:
tensor_data[:, :, :, 2] *= -1
# Load mask (usually fractional anisotropy) image
mask_image = nb.load(mask_file)
mask_data = np.flipud(mask_image.get_data())
header = tensor_image.get_header()
# Make sure the files share the same (3D) dimensions before continuing
assert (np.shape(tensor_data)[0:3] == np.shape(mask_data)[0:3])
# Define various constants
elements_to_consider = [1001] #Use only white matter
vx, vy, vz = header.get_zooms()[0:3]
max_x, max_y, max_z = np.shape(tensor_data)[0:3]
halfx, halfy, halfz = np.array((vx * max_x, vy * max_y, vz * max_z)) / 2.0
mesh_data, _, _, _ = read_mesh(mesh_file, elements_to_consider)
# Create the output mesh file
path, name, ext = split_filename(mesh_file)
out_file = op.abspath(name + "_cond.msh")
iflogger.info('Copying current mesh file to %s' % out_file)
shutil.copyfile(mesh_file, out_file)
f = open(out_file, 'a') #Append to the end of the file
iflogger.info('Appending Conductivity tensors to %s' % out_file)
# Write the tag information to the file:
num_polygons = len(mesh_data)
f.write('$ElementData\n')
str_tag = '"Conductivity"'
timestep = 0.0001
f.write('1\n') #Num String tags
f.write(str_tag + '\n')
f.write('1\n') #Num Real tags
f.write('%f\n' % timestep)
#Three integer tags: timestep, num field components, num elements
f.write('3\n') #Three int tags
f.write('0\n') #Time step index
f.write('9\n') #Num field components
# Get the centroid of all white matter elements
# Find out which voxel they lie inside
iflogger.info("Getting tensor for each element")
#ipdb.set_trace()
nonzero = 0
elem_list = []
if lower_triangular:
for idx, poly in enumerate(mesh_data):
i = np.round((poly['centroid'][0] + halfx) / vx).astype(int)
j = np.round((poly['centroid'][1] + halfy) / vy).astype(int)
k = np.round((poly['centroid'][2] + halfz) / vz).astype(int)
T = tensor_data[i, j, k]
if not (all(T == 0) and mask_data[i, j, k] >= mask_threshold):
elementdata_str = ('%d %e %e %e %e %e %e %e %e %e\n' %
(poly["element_id"], T[0], T[1], T[3], T[1],
T[2], T[4], T[3], T[4], T[5]))
elem_list.append(elementdata_str)
nonzero += 1
#iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
else:
for idx, poly in enumerate(mesh_data):
i = np.round((poly['centroid'][0] + halfx) / vx).astype(int)
j = np.round((poly['centroid'][1] + halfy) / vy).astype(int)
k = np.round((poly['centroid'][2] + halfz) / vz).astype(int)
T = tensor_data[i, j, k]
if not (all(T == 0) and mask_data[i, j, k] >= mask_threshold):
elementdata_str = ('%d %e %e %e %e %e %e %e %e %e\n' %
(poly["element_id"], T[0], T[1], T[2], T[1],
T[3], T[4], T[2], T[4], T[5]))
elem_list.append(elementdata_str)
nonzero += 1
#iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
f.write('%d\n' % nonzero) #Num nonzero field components
for elementdata_str in elem_list:
f.write(elementdata_str)
f.write('$EndElementData\n')
f.write('$ElementData\n')
str_tag = '"FA"'
timestep = 0.0002
f.write('1\n') #Num String tags
f.write(str_tag + '\n')
f.write('1\n') #Num Real tags
f.write('%f\n' % timestep)
#Three integer tags: timestep, num field components, num elements
f.write('3\n') #Three int tags
f.write('1\n') #Time step index
f.write('1\n') #Num field components
# Get the centroid of all white matter elements
# Find out which voxel they lie inside
iflogger.info("Writing FA for each element")
#ipdb.set_trace()
nonzero = 0
elem_list = []
for idx, poly in enumerate(mesh_data):
i = np.round((poly['centroid'][0] + halfx) / vx).astype(int)
j = np.round((poly['centroid'][1] + halfy) / vy).astype(int)
k = np.round((poly['centroid'][2] + halfz) / vz).astype(int)
if mask_data[i, j, k] > 0:
elementdata_str = ('%d %e\n' %
(poly["element_id"], mask_data[i, j, k]))
elem_list.append(elementdata_str)
nonzero += 1
#iflogger.info("%3.3f%%" % (float(idx)/num_polygons*100.0))
f.write('%d\n' % nonzero) #Num nonzero field components
for elementdata_str in elem_list:
f.write(elementdata_str)
f.write('$EndElementData\n')
f.close()
iflogger.info("Finished writing to %s" % out_file)
return out_file