diff --git a/setup.py b/setup.py
index c3859050d9fc15c8215e3e376d93ff10eb1afc2e..d931be3256f3ecda443507168e36776230c01f4e 100644
--- a/setup.py
+++ b/setup.py
@@ -47,6 +47,11 @@ setup_kwds = dict(
'wallMeshImageSignal = gnomon_package_tissueimagemesh.algorithm.cellImageQuantification.wallMeshImageSignal',
'wallMeshSignalPolarities = gnomon_package_tissueimagemesh.algorithm.cellImageQuantification.wallMeshSignalPolarities',
],
+ 'meshFilter': [
+ 'surfaceCellMeshDecimation = gnomon_package_tissueimagemesh.algorithm.meshFilter.surfaceCellMeshDecimation',
+ 'surfaceCellMeshFlipOptimization = gnomon_package_tissueimagemesh.algorithm.meshFilter.surfaceCellMeshFlipOptimization',
+ 'surfaceMeshCellProjection = gnomon_package_tissueimagemesh.algorithm.meshFilter.surfaceMeshCellProjection'
+ ],
'meshFromImage': [
'imageSurfaceMesh = gnomon_package_tissueimagemesh.algorithm.meshFromImage.imageSurfaceMesh',
'segmentationSurfaceMesh = gnomon_package_tissueimagemesh.algorithm.meshFromImage.segmentationSurfaceMesh',
diff --git a/src/gnomon_package_tissueimagemesh/algorithm/cellImageQuantification/surfaceMeshCellProperty.py b/src/gnomon_package_tissueimagemesh/algorithm/cellImageQuantification/surfaceMeshCellProperty.py
index 147c5d800d5e8fa37bb8a92f682f8c3cb92971cc..91e5fb406db58f88aa44225f814e8b1459cf8be6 100644
--- a/src/gnomon_package_tissueimagemesh/algorithm/cellImageQuantification/surfaceMeshCellProperty.py
+++ b/src/gnomon_package_tissueimagemesh/algorithm/cellImageQuantification/surfaceMeshCellProperty.py
@@ -66,8 +66,8 @@ class surfaceMeshCellProperty(gnomonAbstractCellImageQuantification):
out_tissue.walls.image = out_tissue
cell_labels = out_tissue.cell_ids()
- if surface_topomesh.has_wisp_property('cell', 0, is_computed=True):
- vertex_cells = surface_topomesh.wisp_property('cell', 0).values(list(surface_topomesh.wisps(0)))
+ if surface_topomesh.has_wisp_property('label', 0, is_computed=True):
+ vertex_cells = surface_topomesh.wisp_property('label', 0).values(list(surface_topomesh.wisps(0)))
else:
if 'surface_center' in out_tissue.cells.feature_names():
cell_surface_centers = out_tissue.cells.feature('surface_center')
@@ -79,7 +79,7 @@ class surfaceMeshCellProperty(gnomonAbstractCellImageQuantification):
vertex_cell_distances = np.linalg.norm(vertex_points[:, np.newaxis] - cell_centers[np.newaxis], axis=-1)
vertex_cells = cell_labels[np.argmin(vertex_cell_distances, axis=-1)]
- surface_topomesh.update_wisp_property('cell', 0, dict(zip(surface_topomesh.wisps(0), vertex_cells)))
+ surface_topomesh.update_wisp_property('label', 0, dict(zip(surface_topomesh.wisps(0), vertex_cells)))
surface_topomesh.update_wisp_property('label', 0, dict(zip(surface_topomesh.wisps(0), vertex_cells%256)))
for property_name in self['attribute_names']:
diff --git a/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/__init__.py b/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceCellMeshDecimation.py b/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceCellMeshDecimation.py
new file mode 100644
index 0000000000000000000000000000000000000000..46d972aebdd3c25f778c50384690eaa189ff9f58
--- /dev/null
+++ b/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceCellMeshDecimation.py
@@ -0,0 +1,91 @@
+# {# gnomon, plugin.imports
+# do not modify, any code after the gnomon tag will be overwritten
+from dtkcore import d_bool, d_real
+
+import gnomon.core
+
+from gnomon.utils import algorithmPlugin
+from gnomon.utils.decorators import meshInput, meshOutput
+# #}
+# add your imports before the next gnomon tag
+
+from copy import deepcopy
+
+import numpy as np
+import scipy.ndimage as nd
+
+from cellcomplex.property_topomesh.analysis import compute_topomesh_property, compute_topomesh_vertex_property_from_faces
+from cellcomplex.property_topomesh.topological_operations import topomesh_collapse_edge
+from cellcomplex.property_topomesh.extraction import clean_topomesh_properties
+
+from cellcomplex.utils import array_dict
+
+# {# gnomon, plugin.class
+# do not modify, any code after the gnomon tag will be overwritten
+@algorithmPlugin(version='0.1.0', coreversion='0.81.0', name="Surface Cell Projection")
+@meshInput(attr='in_surface_topomesh', data_plugin='gnomonMeshDataPropertyTopomesh')
+@meshOutput(attr='surface_topomesh', data_plugin='gnomonMeshDataPropertyTopomesh')
+class surfaceCellMeshDecimation(gnomon.core.gnomonAbstractMeshFilter):
+ """Decimate tissue mesh to keep one vertex per cell label
+
+ """
+
+ def __init__(self):
+ super().__init__()
+
+ self._parameters = {}
+
+ # self.seg_img = {}
+ self.in_surface_topomesh = {}
+ self.surface_topomesh = {}
+
+ def run(self):
+ self.surface_topomesh = {}
+ for time in self.in_surface_topomesh.keys():
+ surface_topomesh = deepcopy(self.in_surface_topomesh[time])
+ # #}
+ # implement the run method
+
+ edges = np.array(list(surface_topomesh.wisps(1)))
+ edge_vertices = surface_topomesh.wisp_property('vertices', 1).values(edges)
+ edge_vertex_cells = surface_topomesh.wisp_property('label', 0).values(edge_vertices)
+
+ inner_edges = edges[edge_vertex_cells[:, 1] == edge_vertex_cells[:, 0]]
+ inner_edge_lengths = surface_topomesh.wisp_property('length', 1).values(inner_edges)
+
+ inner_edges = inner_edges[np.argsort(inner_edge_lengths)]
+ collapsed_edges = inner_edges
+
+ iteration = 0
+ while len(collapsed_edges)>0:
+ collapsed_edges = []
+ affected_edges = set()
+ for e in inner_edges:
+ if not e in affected_edges:
+ neighbor_edges = set(surface_topomesh.border_neighbors(1, e))
+ collapsed = topomesh_collapse_edge(surface_topomesh, e)
+ if collapsed:
+ collapsed_edges += [e]
+ affected_edges |= set(neighbor_edges)
+ iteration += 1
+ print(f"Collapsed {len(collapsed_edges)} edges")
+
+ clean_topomesh_properties(surface_topomesh)
+ compute_topomesh_property(surface_topomesh, 'vertices', 1)
+ compute_topomesh_property(surface_topomesh, 'length', 1)
+
+ edges = np.array(list(surface_topomesh.wisps(1)))
+ edge_vertices = surface_topomesh.wisp_property('vertices', 1).values(edges)
+ edge_vertex_cells = surface_topomesh.wisp_property('label', 0).values(edge_vertices)
+
+ inner_edges = edges[edge_vertex_cells[:, 1] == edge_vertex_cells[:, 0]]
+ inner_edge_lengths = surface_topomesh.wisp_property('length', 1).values(inner_edges)
+
+ inner_edges = inner_edges[np.argsort(inner_edge_lengths)]
+
+ compute_topomesh_property(surface_topomesh, 'borders', 2)
+ compute_topomesh_property(surface_topomesh, 'vertices', 2)
+ compute_topomesh_property(surface_topomesh, 'oriented_vertices', 2)
+ compute_topomesh_property(surface_topomesh, 'oriented_borders', 3)
+
+ self.surface_topomesh[time] = surface_topomesh
diff --git a/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceCellMeshFlipOptimization.py b/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceCellMeshFlipOptimization.py
new file mode 100644
index 0000000000000000000000000000000000000000..0d27e5baad2157835e8609dbbe3a640843df8dd5
--- /dev/null
+++ b/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceCellMeshFlipOptimization.py
@@ -0,0 +1,82 @@
+# {# gnomon, plugin.imports
+# do not modify, any code after the gnomon tag will be overwritten
+from dtkcore import d_int, d_real
+
+import gnomon.core
+
+from gnomon.utils import algorithmPlugin
+from gnomon.utils.decorators import cellImageInput, meshInput, meshOutput
+# #}
+# add your imports before the next gnomon tag
+
+from copy import deepcopy
+
+import numpy as np
+
+from cellcomplex.property_topomesh.optimization import property_topomesh_edge_flip_optimization
+
+
+# {# gnomon, plugin.class
+# do not modify, any code after the gnomon tag will be overwritten
+@algorithmPlugin(version='0.1.0', coreversion='0.72.0', name="Cell Mesh Flip Optimization")
+@cellImageInput("seg_img", data_plugin="gnomonCellImageDataTissueImage")
+@meshInput(attr='in_surface_topomesh', data_plugin='gnomonMeshDataPropertyTopomesh')
+@meshOutput(attr='surface_topomesh', data_plugin='gnomonMeshDataPropertyTopomesh')
+class surfaceCellMeshFlipOptimization(gnomon.core.gnomonAbstractMeshFilter):
+ """Perform edge flips to get closer to the image cell ajacencies
+
+ """
+
+ def __init__(self):
+ super().__init__()
+
+ self._parameters = {}
+ self._parameters['iterations'] = d_int("Iterations", 3, 0, 5, "The number of iterations to perform in the edge flip process")
+ self._parameters['regularization'] = d_real("Regularization Weight", 0, 0, 1, 2, "The weight associated to the regularization energy term")
+
+ self.seg_img = {}
+ self.in_surface_topomesh = {}
+ self.surface_topomesh = {}
+
+ def run(self):
+ self.surface_topomesh = {}
+ for time in self.in_surface_topomesh.keys():
+ surface_topomesh = deepcopy(self.in_surface_topomesh[time])
+ # #}
+ # implement the run method
+
+ if self['iterations']>0:
+ vertex_cells = surface_topomesh.wisp_property('label', 0)
+ unique_cells = np.unique(vertex_cells.values())
+ cell_vertices = {c: [] for c in unique_cells}
+ for v, c in vertex_cells.items():
+ cell_vertices[c] += [v]
+
+ seg_img = self.seg_img[time]
+ image_cell_edges = np.array([w for w in seg_img.wall_ids()])
+ image_edges = []
+ for c1, c2 in image_cell_edges:
+ if c1 in cell_vertices and c2 in cell_vertices:
+ image_edges += [
+ (v1, v2)
+ for v1 in cell_vertices[c1] for v2 in cell_vertices[c2]
+ ]
+ image_edges += [
+ (v2, v1)
+ for v1 in cell_vertices[c1] for v2 in cell_vertices[c2]
+ ]
+ image_edges = np.array(image_edges)
+
+ omega_energies = {'image': 1}
+ if self['regularization'] > 0:
+ omega_energies.update({'regularization': self['regularization']})
+
+ property_topomesh_edge_flip_optimization(
+ surface_topomesh,
+ iterations=self['iterations'],
+ omega_energies=omega_energies,
+ simulated_annealing=False,
+ image_edges=image_edges
+ )
+
+ self.surface_topomesh[time] = surface_topomesh
diff --git a/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceMeshCellProjection.py b/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceMeshCellProjection.py
new file mode 100644
index 0000000000000000000000000000000000000000..dcb60ad84ebdf507dbc05b8931968669c30cdb3b
--- /dev/null
+++ b/src/gnomon_package_tissueimagemesh/algorithm/meshFilter/surfaceMeshCellProjection.py
@@ -0,0 +1,59 @@
+# {# gnomon, plugin.imports
+# do not modify, any code after the gnomon tag will be overwritten
+from dtkcore import d_bool, d_real, d_inliststring
+
+import gnomon.core
+
+from gnomon.utils import algorithmPlugin
+from gnomon.utils.decorators import cellImageInput, meshInput, meshOutput
+# #}
+# add your imports before the next gnomon tag
+
+from copy import deepcopy
+
+from timagetk_geometry.image_surface.tissue_image_mesh import surface_vertex_normal_sampling_label_projection, surface_vertex_remove_isolated_labels
+
+
+# {# gnomon, plugin.class
+# do not modify, any code after the gnomon tag will be overwritten
+@algorithmPlugin(version='0.1.0', coreversion='0.72.0', name="Surface Cell Projection")
+@cellImageInput("seg_img", data_plugin="gnomonCellImageDataTissueImage")
+@meshInput(attr='in_surface_topomesh', data_plugin='gnomonMeshDataPropertyTopomesh')
+@meshOutput(attr='surface_topomesh', data_plugin='gnomonMeshDataPropertyTopomesh')
+class surfaceMeshCellProjection(gnomon.core.gnomonAbstractMeshFilter):
+ """Project cell labels on surface mesh using normals
+
+ """
+
+ def __init__(self):
+ super().__init__()
+
+ self._parameters = {}
+ self._parameters['sampling_depth'] = d_real("Sampling depth", 3., 0., 10., 1, "Depth up to which to sample the segmented image")
+ self._parameters['method'] = d_inliststring("Method", "median", ["most", "first", "median"], "Method used to choose the selected label")
+ self._parameters['remove_isolated_labels'] = d_bool("Remove isolated labels",True, "Whether to remove labels that have no identical neighbor")
+
+ self.seg_img = {}
+ self.in_surface_topomesh = {}
+ self.surface_topomesh = {}
+
+ def run(self):
+ self.surface_topomesh = {}
+ for time in self.in_surface_topomesh.keys():
+ surface_topomesh = deepcopy(self.in_surface_topomesh[time])
+ # #}
+ # implement the run method
+
+ seg_img = self.seg_img[time]
+
+ surface_vertex_normal_sampling_label_projection(
+ surface_topomesh,
+ seg_img,
+ sampling_depth=self['sampling_depth'],
+ method=self['method']
+ )
+
+ if self['remove_isolated_labels']:
+ surface_vertex_remove_isolated_labels(surface_topomesh)
+
+ self.surface_topomesh[time] = surface_topomesh
diff --git a/src/gnomon_package_tissueimagemesh/algorithm/pointCloudQuantification/surfaceMeshProperty.py b/src/gnomon_package_tissueimagemesh/algorithm/pointCloudQuantification/surfaceMeshProperty.py
index 343c692c0be1a65b498c0059b3d7d87b572d4ed6..6b11aa64912e8df474d9744c16d89b2128e62dd9 100644
--- a/src/gnomon_package_tissueimagemesh/algorithm/pointCloudQuantification/surfaceMeshProperty.py
+++ b/src/gnomon_package_tissueimagemesh/algorithm/pointCloudQuantification/surfaceMeshProperty.py
@@ -58,8 +58,8 @@ class surfaceMeshProperty(gnomonAbstractPointCloudQuantification):
out_df = deepcopy(df)
cell_labels = df['label'].values
- if surface_topomesh.has_wisp_property('cell', 0, is_computed=True):
- vertex_cells = surface_topomesh.wisp_property('cell', 0).values(list(surface_topomesh.wisps(0)))
+ if surface_topomesh.has_wisp_property('label', 0, is_computed=True):
+ vertex_cells = surface_topomesh.wisp_property('label', 0).values(list(surface_topomesh.wisps(0)))
else:
cell_centers = df[['center_'+dim for dim in 'xyz']].values
@@ -67,7 +67,7 @@ class surfaceMeshProperty(gnomonAbstractPointCloudQuantification):
vertex_cell_distances = np.linalg.norm(vertex_points[:, np.newaxis] - cell_centers[np.newaxis], axis=-1)
vertex_cells = cell_labels[np.argmin(vertex_cell_distances, axis=-1)]
- surface_topomesh.update_wisp_property('cell', 0, dict(zip(surface_topomesh.wisps(0), vertex_cells)))
+ surface_topomesh.update_wisp_property('label', 0, dict(zip(surface_topomesh.wisps(0), vertex_cells)))
surface_topomesh.update_wisp_property('label', 0, dict(zip(surface_topomesh.wisps(0), vertex_cells%256)))
for property_name in self['attribute_names']: