def write_surface_with_LUTs(File, Points, Faces, Maps):
"""Like write_scalars in io_vtk but no writing of vertices
"""
print "writing sulci into VTK file:", File
Fp = open(File,'w')
io_vtk.write_header(Fp)
io_vtk.write_points(Fp, Points)
io_vtk.write_faces(Fp, Faces)
if len(Maps) > 0:
# Make sure that LUTs is a list of lists
Count = 0
for LUT_name, LUT in Maps.iteritems():
if Count == 0 :
io_vtk.write_scalars(Fp, LUT, LUT_name)
else:
io_vtk.write_scalars(Fp, LUT, LUT_name, begin_scalars=False)
Count += 1
Fp.close()
return None
fundus_indices = [x for i,x in enumerate(border_indices)
if np.unique(border_label_tuples[i]).tolist()
in label_pairs]
# Store the points as sulcus IDs in the fundus IDs array
label_boundary_fundi[fundus_indices] = isulcus + 1
# Construct a distance matrix
print('Construct a boundary-to-fundus distance matrix...')
distances, distance_matrix = compute_fundus_distances(label_boundary_fundi,
fundi, folds, points, n_fundi)
# Compute mean distances for each fundus
fundus_mean_distances = np.zeros(n_fundi)
fundus_std_distances = np.zeros(n_fundi)
for ifundus in range(n_fundi):
fundus_distances = distance_matrix[:, ifundus]
fundus_distances = [x for x in fundus_distances if x != -1]
fundus_mean_distances[ifundus] = np.mean(fundus_distances)
fundus_std_distances[ifundus] = np.std(fundus_distances)
print('Fundus mean distances')
print(fundus_mean_distances)
print('Fundus standard deviations of distances')
print(fundus_std_distances)
# Write resulting fundus-label boundary distances to VTK file
print('Write distances to a VTK file for visualization...')
write_scalars('evaluate_fundi.vtk', points, range(npoints), faces,
[distances], ['fundus-label boundary distances'])
def rewrite_scalars(input_vtk, output_vtk, new_scalars,
new_scalar_names=['scalars'], filter_scalars=[],
background_value=-1):
"""
Load VTK format file and save a subset of scalars into a new file.
Parameters
----------
input_vtk : string
input VTK file name
output_vtk : string
output VTK file name
new_scalars : list of lists of floats (or single list or array of floats)
each list (lookup table) contains new values to assign to the vertices
new_scalar_names : string or list of strings
each element is the new name for a lookup table
filter_scalars : list or numpy array (optional)
scalar values used to filter faces (foreground values retained)
background_value : integer
background value
Returns
-------
output_vtk : string
output VTK file name
Examples
--------
>>> # Write vtk file with curvature values on sulci
>>> import os
>>> from mindboggle.utils.io_vtk import read_scalars, rewrite_scalars
>>> path = os.environ['MINDBOGGLE_DATA']
>>> input_vtk = os.path.join(path, 'arno', 'shapes', 'lh.pial.mean_curvature.vtk')
>>> sulci_file = os.path.join(path, 'arno', 'features', 'sulci.vtk')
>>> output_vtk = 'rewrite_scalars.vtk'
>>> curvs, name = read_scalars(input_vtk, True,True)
>>> sulci, name = read_scalars(sulci_file)
>>> new_scalars = [curvs, sulci]
>>> new_scalar_names = ['curvs', 'sulci']
>>> filter_scalars = sulci
>>> background_value = -1
>>> #
>>> rewrite_scalars(input_vtk, output_vtk, new_scalars, new_scalar_names, filter_scalars, background_value)
>>> #
>>> # View:
>>> from mindboggle.utils.plots import plot_surfaces
>>> plot_surfaces('rewrite_scalars.vtk')
"""
import os
import numpy as np
from mindboggle.utils.mesh import remove_faces
from mindboggle.utils.io_vtk import write_header, write_points, \
write_vertices, write_faces, write_scalars, read_vtk, scalars_checker
# Convert numpy arrays to lists
if isinstance(new_scalars, np.ndarray):
new_scalars = new_scalars.tolist()
if isinstance(filter_scalars, np.ndarray):
filter_scalars = filter_scalars.tolist()
# Output VTK file to current working directory
output_vtk = os.path.join(os.getcwd(), output_vtk)
# Load VTK file
faces, lines, indices, points, npoints, scalars, name, \
input_vtk = read_vtk(input_vtk)
# Find indices to foreground values
if filter_scalars:
indices_keep = [i for i,x in enumerate(filter_scalars)
if x != background_value]
indices_remove = [i for i,x in enumerate(filter_scalars)
if x == background_value]
# Remove surface faces whose three vertices are not all in indices
faces = remove_faces(faces, indices_keep)
# Write VTK file
Fp = open(output_vtk,'w')
write_header(Fp)
write_points(Fp, points)
if indices:
write_vertices(Fp, indices)
if faces:
write_faces(Fp, faces)
if new_scalars:
new_scalars, new_scalar_names = scalars_checker(new_scalars,
new_scalar_names)
# scalars_checker() returns a list of lists for scalars:
for i, new_scalar_list in enumerate(new_scalars):
if filter_scalars:
for iremove in indices_remove:
new_scalar_list[iremove] = background_value
if np.ndim(new_scalar_list) == 1:
scalar_type = type(new_scalar_list[0]).__name__
elif np.ndim(new_scalar_list) == 2:
scalar_type = type(new_scalar_list[0][0]).__name__
else:
print("Undefined scalar type!")
if i == 0:
new_scalar_name = new_scalar_names[0]
write_scalars(Fp, new_scalar_list, new_scalar_name,
begin_scalars=True,
scalar_type=scalar_type)
else:
if len(new_scalar_names) < i + 1:
new_scalar_name = new_scalar_names[0]
else:
new_scalar_name = new_scalar_names[i]
write_scalars(Fp, new_scalar_list, new_scalar_name,
begin_scalars=False,
scalar_type=scalar_type)
else:
print('Error: new_scalars is empty')
exit()
Fp.close()
if not os.path.exists(output_vtk):
raise(IOError(output_vtk + " not found"))
return output_vtk
def write_vtk(output_vtk, points, indices=[], lines=[], faces=[],
scalars=[], scalar_names=['scalars'], scalar_type='float'):
"""
Save lists of scalars into the lookup table of a VTK-format file.
Scalar definition includes specification of a lookup table.
The definition of a lookup table is optional. If not specified,
the default VTK table will be used (and tableName should be "default").
SCALARS dataName dataType numComp
LOOKUP_TABLE tableName
Parameters
----------
output_vtk : string
path of the output VTK file
points : list of 3-tuples of floats
each element has 3 numbers representing the coordinates of the points
indices : list of integers
indices of vertices
lines : list of 2-tuples of integers
Each element is an edge on the mesh, consisting of 2 integers
representing the 2 vertices of the edge
faces : list of 3-tuples of integers
indices to the three vertices of a face on the mesh
scalars : list of floats, or list of lists of floats;
each list (lookup table) contains values assigned to the vertices
scalar_names : string or list of strings
each element is the name of a scalar list (lookup table)
scalar_type : string
type of scalars ('float' or 'int')
Examples
--------
>>> # Toy example
>>> import random, os
>>> from mindboggle.utils.io_vtk import write_vtk
>>> from mindboggle.utils.plots import plot_surfaces
>>> points = [[random.random() for i in [1,2,3]] for j in range(4)]
>>> indices = [1,2,3,0]
>>> lines = [[1,2],[3,4]]
>>> faces = [[1,2,3],[0,1,3]]
>>> scalars = [[random.random() for i in range(4)] for j in [1,2]]
>>> scalar_names = ['curv','depth']
>>> output_vtk = 'write_vtk.vtk'
>>> scalar_type = 'float'
>>> write_vtk(output_vtk, points, indices, lines, faces, scalars, scalar_names, scalar_type)
>>> # View:
>>> plot_surfaces(output_vtk)
>>> #
>>> # Write vtk file with curvature values and view:
>>> import os
>>> from mindboggle.utils.io_vtk import read_vtk, write_vtk
>>> from mindboggle.utils.plots import plot_surfaces
>>> path = os.environ['MINDBOGGLE_DATA']
>>> input_vtk = os.path.join(path, 'arno', 'shapes', 'lh.pial.mean_curvature.vtk')
>>> faces, lines, indices, points, npoints, scalars, scalar_names, input_vtk = read_vtk(input_vtk)
>>> output_vtk = 'write_vtk.vtk'
>>> scalar_type = 'float'
>>> write_vtk(output_vtk, points, indices, lines, faces, scalars, scalar_names, scalar_type)
>>> # View:
>>> plot_surfaces(output_vtk)
"""
import os
import numpy as np
from mindboggle.utils.io_vtk import write_header, write_points, \
write_vertices, write_faces, write_scalars, scalars_checker
# Convert numpy arrays to lists
if isinstance(faces, np.ndarray):
faces = faces.tolist()
if isinstance(points, np.ndarray):
points = points.tolist()
output_vtk = os.path.join(os.getcwd(), output_vtk)
Fp = open(output_vtk,'w')
write_header(Fp)
write_points(Fp, points)
if indices:
write_vertices(Fp, indices)
if lines:
for i in range(0,len(lines)):
lines[i] = [lines[i][0], lines[i][1]]
write_faces(Fp, lines) # write_faces can write either lines or faces
if faces:
write_faces(Fp, faces)
scalars, scalar_names = scalars_checker(scalars, scalar_names)
if len(scalars):
for i, scalar_list in enumerate(scalars):
if i == 0:
scalar_name = scalar_names[i]
write_scalars(Fp, scalar_list, scalar_name,
begin_scalars=True, scalar_type=scalar_type)
else:
if len(scalar_names) < i + 1:
scalar_name = scalar_names[0]
else:
scalar_name = scalar_names[i]
write_scalars(Fp, scalar_list, scalar_name,
begin_scalars=False, scalar_type=scalar_type)
Fp.close()
if not os.path.exists(output_vtk):
raise(IOError(output_vtk + " not found"))
return output_vtk
def rewrite_scalars(input_vtk, output_vtk, new_scalars,
new_scalar_names=['scalars'], filter_scalars=[]):
"""
Load VTK format file and save a subset of scalars into a new file.
Parameters
----------
input_vtk : string
input VTK file name
output_vtk : string
output VTK file name
new_scalars : list of lists of floats (or single list or array of floats)
each list (lookup table) contains new values to assign to the vertices
new_scalar_names : string or list of strings
each element is the new name for a lookup table
filter_scalars : list or numpy array (optional)
scalar values used to filter faces (values > -1 retained)
Returns
-------
output_vtk : string
output VTK file name
Examples
--------
>>> # Write vtk file with curvature values on sulci
>>> import os
>>> from mindboggle.utils.io_vtk import read_scalars, rewrite_scalars
>>> path = os.environ['MINDBOGGLE_DATA']
>>> curv_file = os.path.join(path, 'arno', 'shapes', 'lh.pial.mean_curvature.vtk')
>>> curvs, name = read_scalars(curv_file, True,True)
>>> sulci_file = os.path.join(path, 'arno', 'features', 'sulci.vtk')
>>> sulci, name = read_scalars(sulci_file)
>>> #
>>> rewrite_scalars(curv_file, 'rewrite_scalars.vtk',
>>> [curvs, sulci], ['curvs', 'sulci'], sulci)
>>> #
>>> # View:
>>> from mindboggle.utils.plots import plot_vtk
>>> plot_vtk('rewrite_scalars.vtk')
"""
import os
import numpy as np
from mindboggle.utils.mesh import remove_faces
from mindboggle.utils.io_vtk import write_header, write_points, \
write_vertices, write_faces, write_scalars, read_vtk, \
scalars_checker
# Convert numpy arrays to lists
if isinstance(new_scalars, np.ndarray):
new_scalars = new_scalars.tolist()
if isinstance(filter_scalars, np.ndarray):
filter_scalars = filter_scalars.tolist()
# Output VTK file to current working directory
output_vtk = os.path.join(os.getcwd(), output_vtk)
# Load VTK file
faces, lines, indices, points, npoints, scalars, name, input_vtk = read_vtk(input_vtk)
# Find indices to nonzero values
indices = range(npoints)
if filter_scalars:
indices_filter = [i for i,x in enumerate(filter_scalars) if x > -1]
indices_remove = [i for i,x in enumerate(filter_scalars) if x == -1]
# Remove surface mesh faces whose three vertices are not all in indices
faces = remove_faces(faces, indices_filter)
# Write VTK file
Fp = open(output_vtk,'w')
write_header(Fp)
write_points(Fp, points)
if indices:
write_vertices(Fp, indices)
if faces:
write_faces(Fp, faces)
if new_scalars:
new_scalars, new_scalar_names = scalars_checker(new_scalars, new_scalar_names)
for i, new_scalar_list in enumerate(new_scalars):
if filter_scalars:
for iremove in indices_remove:
new_scalar_list[iremove] = -1
if i == 0:
new_scalar_name = new_scalar_names[0]
write_scalars(Fp, new_scalar_list, new_scalar_name)
else:
if len(new_scalar_names) < i + 1:
new_scalar_name = new_scalar_names[0]
else:
new_scalar_name = new_scalar_names[i]
write_scalars(Fp, new_scalar_list, new_scalar_name, begin_scalars=False)
else:
print('Error: new_scalars is empty')
exit()
Fp.close()
return output_vtk
def write_vtk(output_vtk, points, indices=[], lines=[], faces=[],
scalars=[], scalar_names=['scalars']):
"""
Save lists of scalars into the lookup table of a VTK-format file.
Scalar definition includes specification of a lookup table.
The definition of a lookup table is optional. If not specified,
the default VTK table will be used (and tableName should be "default").
SCALARS dataName dataType numComp
LOOKUP_TABLE tableName
Parameters
----------
output_vtk : string
path of the output VTK file
points : list of 3-tuples of floats
each element has 3 numbers representing the coordinates of the points
indices : list of integers
indices of vertices, default=[]
lines : list of 2-tuples of integers
Each element is an edge on the mesh, consisting of 2 integers
representing the 2 vertices of the edge
default=[]
faces : list of 3-tuples of integers
indices to the three vertices of a face on the mesh, default=[]
scalars : list of, or list of lists of, floats (or single list of floats)
each list (lookup table) contains values assigned to the vertices, default=[]
scalar_names : string or list of strings
each element is the name of a lookup table, default=['scalars']
if only one string is given for this field, the program will convert
it into a list of only this string.
Notes
--------
If you do not have all 7 parameters, it's safer to use syntax like
...``indices=indices, faces=faces``... (as in Toy example)
than syntax like ...``indices, faces``... alone to
ensure that your variables are aligned with their orders
in parameter definition.
Examples
--------
>>> # Toy example
>>> import random, os
>>> from mindboggle.utils.io_vtk import write_vtk
>>> from mindboggle.utils.plots import plot_vtk
>>> points = [[random.random() for i in [1,2,3]] for j in range(4)]
>>> indices = [1,2,3,0]
>>> lines = [[1,2],[3,4]]
>>> faces = [[1,2,3],[0,1,3]]
>>> scalar_names = ['curv','depth']
>>> scalars = [[random.random() for i in range(4)] for j in [1,2]]
>>> #
>>> write_vtk('write_vtk.vtk', points,
>>> indices, lines, faces, scalars, scalar_names)
>>> #
>>> # View:
>>> plot_vtk('write_vtk.vtk')
>>> #
>>> # Write vtk file with curvature values on sulci and view:
>>> from mindboggle.utils.io_vtk import read_vtk, write_vtk
>>> path = os.environ['MINDBOGGLE_DATA']
>>> input_vtk = os.path.join(path, 'arno', 'shapes', 'lh.pial.mean_curvature.vtk')
>>> faces, lines, indices, points, npoints, curvs, name, input_vtk = read_vtk(input_vtk)
>>> write_vtk('write_vtk.vtk', points, [], [], faces, curvs, 'curvatures')
>>> plot_vtk('write_vtk.vtk')
"""
import os
from mindboggle.utils.io_vtk import write_header, write_points, \
write_vertices, write_faces, write_scalars, \
scalars_checker
output_vtk = os.path.join(os.getcwd(), output_vtk)
Fp = open(output_vtk,'w')
write_header(Fp)
write_points(Fp, points)
if indices:
write_vertices(Fp, indices)
if lines:
for i in range(0,len(lines)):
lines[i] = [lines[i][0], lines[i][1]]
write_faces(Fp, lines) # write_faces can write either lines or faces
if faces:
write_faces(Fp, faces)
scalars, scalar_names = scalars_checker(scalars, scalar_names)
if len(scalars):
for i, scalar_list in enumerate(scalars):
if i == 0:
scalar_name = scalar_names[i]
write_scalars(Fp, scalar_list, scalar_name)
else:
if len(scalar_names) < i + 1:
scalar_name = scalar_names[0]
else:
scalar_name = scalar_names[i]
write_scalars(Fp, scalar_list, scalar_name, begin_scalars=False)
Fp.close()
return output_vtk