nrv.fmod.FEM.fenics_utils

Description

NeuRon Virtualizer, large scale modeling of Peripheral Nervous System with random stimulation waveforms

`f_material`()	a class for conductive material wh
`FEMParameters`([D, mesh_file, data])	Class gathering parameters of a FEM FEniCS simulation.
`FEMResults`([mesh_file, domain, elem, V, ...])	Result of a FEMSimulation.
`FEMSimulation`([D, mesh_file, mesh, data, ...])	Class usefull to solve the Static/Quasi-Static electrical current problem using FEM with FEniCSx algorithms (https://fenicsproject.org).
`fenics_material`([mat])	A class of materials better suited to FEM resolution with fenics.
`layered_material`([mat_in, mat_lay, alpha_lay])	a class for conductive material wh

`is_f_mat`(mat)	check if an object is a fenics_material, return True if yes, else False
`mat_from_interp`(X, Y[, kind, dx, ...])	Return a fenics material with a conductivity space function define as the `nrv_interp` of X and Y
`mat_from_csv`(fname, **kwargs)	Return a fenics material with a conductivity space function define as the `nrv_interp` from the value of a .csv file
`load_f_material`([X])	Return fenics material from an object X
`is_sim_res`(result)	check if an object is a FEMResults, return True if yes, else False
`save_sim_res_list`(sim_res_list, fname[, dt])	save a list of SimResults in a .bp folder which can be open with PrarView
`read_gmsh`(mesh[, comm, rank, gdim])	Given a mesh_file or a MeshCreator returns mesh cell_tags and facet_tags (see dolfinx.io.gmshio.model_to_mesh for more details) NB: copy of dolfinx.io.gmshio.read_from_msh verbose from gmsh
`domain_from_meshfile`(mesh_file)	return only the domain from mesh_file
`V_from_meshfile`(mesh_file[, elem])
`closest_point_in_mesh`(mesh, point, tree, ...)
`is_lay_mat`(mat)	check if an object is a fenics_material, return True if yes, else False
`get_sig_ap`(sig_in, sig_lay, alpha_lay)