Source code for nighres.surface.mesh_to_levelset

import os
import sys
import numpy as np
import nibabel as nb
import nighresjava
from import load_volume, save_volume, load_mesh_geometry, save_mesh_geometry
from ..utils import _output_dir_4saving, _fname_4saving,_check_available_memory

[docs]def mesh_to_levelset(surface_mesh, reference_image, save_data=False, overwrite=False, output_dir=None, file_name=None): """Mesh to levelset Creates a signed distance function from a triangulated mesh using pseudonormals. Parameters ---------- surface_mesh: mesh Mesh model of the surface reference_image: niimg Image of the dimensions and resolutions corresponding to the mesh save_data: bool, optional Save output data to file (default is False) overwrite: bool, optional Overwrite existing results (default is False) output_dir: str, optional Path to desired output directory, will be created if it doesn't exist file_name: str, optional Desired base name for output files with file extension (suffixes will be added) Returns ---------- dict Dictionary collecting outputs under the following keys (suffix of output files in brackets) * result (niimg): Levelset function representing the mesh (_m2l-lvl) Notes ---------- Ported from original Java module by Christine Tardif and Pierre-Louis Bazin. References ---------- """ print("\nMesh to Levelset") # make sure that saving related parameters are correct if save_data: output_dir = _output_dir_4saving(output_dir, surface_mesh) lvl_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=surface_mesh, suffix='m2l-lvl')) if overwrite is False \ and os.path.isfile(lvl_file) : print("skip computation (use existing results)") output = {'result': lvl_file} return output # start virtual machine if not running try: mem = _check_available_memory() nighresjava.initVM(initialheap=mem['init'], maxheap=mem['max']) except ValueError: pass # initiate class algorithm = nighresjava.SurfaceMeshToLevelsetPseudoNormals() # load the data mesh = load_mesh_geometry(surface_mesh) algorithm.setSurfacePoints(nighresjava.JArray('float')( (mesh['points'].flatten('C')).astype(float))) algorithm.setSurfaceTriangles(nighresjava.JArray('int')( (mesh['faces'].flatten('C')).astype(int).tolist())) ref_img = load_volume(reference_image) hdr = ref_img.header aff = ref_img.affine resolution = [x.item() for x in hdr.get_zooms()] dimensions = hdr.get_data_shape() algorithm.setResolutions(resolution[0], resolution[1], resolution[2]) algorithm.setDimensions(dimensions[0], dimensions[1], dimensions[2]) # execute class try: algorithm.execute() except: # if the Java module fails, reraise the error it throws print("\n The underlying Java code did not execute cleanly: ") print(sys.exc_info()[0]) raise return # collect outputs lvl_data = np.reshape(np.array(algorithm.getLevelsetImage(), dtype=np.float32), dimensions, 'F') # create the mesh dictionary header['cal_min'] = np.nanmin(lvl_data) header['cal_max'] = np.nanmax(lvl_data) lvl = nb.Nifti1Image(lvl_data, affine, header) if save_data: save_volume(lvl_file, lvl) return {'result': lvl_file} else: return {'result': lvl}