("HDF5", "*.h5")])
if file_path.endswith('npz'):
kwarg = {'fieldname': 'amp'}
else:
kwarg = {}
obj, extension = util.load_file(file_path, **kwarg)
if extension == '.h5':
comment = comment + '_mode'
if phasing_shape is None:
phasing_shape = obj.shape
if upsampling_factor > 1:
obj, _ = fu.upsample(array=obj,
upsampling_factor=upsampling_factor,
debugging=debug)
print(f'Upsampled object shape = {obj.shape}')
voxel_size = [vox / upsampling_factor for vox in voxel_size]
comment += f'_ups{upsampling_factor}'
######################
# define the support #
######################
obj = abs(obj)
min_obj = obj[np.nonzero(obj)].min()
obj = obj / min_obj # normalize to the non-zero min to avoid dividing by small numbers
obj[obj == 0] = min_offset # avoid dividing by 0
support = np.zeros(obj.shape)
support[obj >= isosurface_threshold * obj.max()] = 1
support[support == 0] = min_offset
convert_grey=True,
cmap='gray',
debug=False)
else:
obj, _ = util.load_file(file_path)
obj = abs(obj)
ndim = obj.ndim
if isinstance(voxel_size, Real):
voxel_size = (voxel_size, ) * ndim
print(f'Object shape = {obj.shape}, voxel size = {voxel_size}')
if upsampling_factor > 1:
obj, voxel_size = fu.upsample(array=obj,
upsampling_factor=upsampling_factor,
voxelsizes=voxel_size,
title='modulus',
debugging=debug)
print(
f'Upsampled object shape = {obj.shape}, upsampled voxel size = {voxel_size}'
)
else:
valid.valid_container(voxel_size,
container_types=(list, tuple, np.ndarray),
length=ndim,
item_types=Real,
min_excluded=0,
name='angular_profile')
#########################
# check some parameters #
plt.ion()
root = tk.Tk()
root.withdraw()
file_path = filedialog.askopenfilename(initialdir=datadir, filetypes=[("NPZ", "*.npz")])
npzfile = np.load(file_path)
amp = npzfile['amp']
amp = amp / amp.max()
nz, ny, nx = amp.shape
print("Initial data size: (", nz, ',', ny, ',', nx, ')')
strain = npzfile['strain']
#################
# upsample data #
#################
if upsampling_factor > 1:
amp, voxel_size = fu.upsample(array=amp, upsampling_factor=upsampling_factor, voxelsizes=voxel_size,
debugging=debug)
strain, _ = fu.upsample(array=strain, upsampling_factor=upsampling_factor, voxelsizes=voxel_size,
debugging=debug)
nz, ny, nx = amp.shape
print("Upsampled data size: (", nz, ',', ny, ',', nx, ')')
print("New voxel sizes: ", voxel_size)
#####################################################################
# Use marching cubes to obtain the surface mesh of these ellipsoids #
#####################################################################
vertices_old, faces, _, _ = measure.marching_cubes_lewiner(amp, level=support_threshold, step_size=1)
nb_vertices = vertices_old.shape[0]
# vertices is a list of 3d coordinates of all vertices points
# faces is a list of facets defined by the indices of 3 vertices
# from scipy.io import savemat
plt.ion()
root = tk.Tk()
root.withdraw()
file_path = filedialog.askopenfilename(initialdir=datadir, filetypes=[("NPZ", "*.npz")])
npzfile = np.load(file_path)
amp = npzfile['amp']
amp = amp / amp.max()
nz, ny, nx = amp.shape
print("Initial data size: (", nz, ',', ny, ',', nx, ')')
strain = npzfile['strain']
#################
# upsample data #
#################
if upsampling_factor > 1:
amp, _ = fu.upsample(array=amp, upsampling_factor=upsampling_factor, voxelsizes=voxel_size,
title='modulus', debugging=debug)
strain, voxel_size = fu.upsample(array=strain, upsampling_factor=upsampling_factor, voxelsizes=voxel_size,
title='strain', debugging=debug)
nz, ny, nx = amp.shape
print("Upsampled data size: (", nz, ',', ny, ',', nx, ')')
print("New voxel sizes: ", voxel_size)
#####################################################################
# Use marching cubes to obtain the surface mesh of these ellipsoids #
#####################################################################
vertices_old, faces, _, _ = measure.marching_cubes_lewiner(amp, level=support_threshold, allow_degenerate=False,
step_size=1)
# vertices_old is a list of 3d coordinates of all vertices points
# faces is a list of facets defined by the indices of 3 vertices_old
# from scipy.io import savemat