bool:
- for d_id in darts_list:
- if isValidAction(m, d_id, 4)[0]:
+ # Vรฉrification que tous les angles sont supรฉrieurs ร 5ยฐ
+ if angle_A <= 5 or angle_B <= 5 or angle_C <= 5:
return False
- return True
\ No newline at end of file
+ return True
+
+ def isTruncated(self, darts_list) -> bool:
+ for d_id in darts_list:
+ if self.isValidAction(d_id, 4)[0]: # if on action is valid, it means it's valid topologically and geometrically, so no need to verify the two
+ return False
+ return True
+
+
+ # def is_star_vertex(self, n1:Node, new_coordinates, plot=False):
+ # #plot_mesh(self.mesh)
+ #
+ # # Retrieve all neighboring vertices in order
+ # d = n1.get_dart()
+ # d2 = d.get_beta(2)
+ # n_start = d2.get_node() #First neighbour to retrieve
+ #
+ # adj_nodes = [n_start]
+ # nodes_coord = [[n_start.x(), n_start.y()]]
+ #
+ # d = d2.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ #
+ # # As long as we haven't returned to the first neighbor, we keep searching.
+ # # This works because the collapse action is restricted to inner darts that are not connected to a boundary node.
+ # # Therefore, we are guaranteed to find the first vertex by following the beta1 and beta2 relations.
+ #
+ # while n != n_start:
+ # adj_nodes.append(n)
+ # nodes_coord.append([n.x(), n.y()])
+ # d = d2.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ #
+ # nodes_coord = np.array(nodes_coord)
+ #
+ # # Create a Polygon with shapely package
+ # poly = Polygon(nodes_coord)
+ # # Create the point for wich we want to check star property
+ # point_v = Point(new_coordinates)
+ #
+ # if plot :
+ # plt.figure(figsize=(6, 6))
+ # # Polygone
+ # x, y = poly.exterior.xy
+ # plt.fill(x, y, alpha=0.3, edgecolor='red', facecolor='lightcoral',
+ # label='Polygon formed par by neighbours vertices')
+ #
+ # # Voisins
+ # plt.scatter(nodes_coord[:, 0], nodes_coord[:, 1], color='blue', zorder=5, label='Neighbours')
+ #
+ # # Sommet testรฉ
+ # plt.scatter(new_coordinates[0], new_coordinates[1], color='green', s=100, zorder=5, label='Vertex to test')
+ #
+ # plt.legend()
+ # plt.gca().set_aspect('equal')
+ # plt.show()
+ #
+ # # If polygon is convexe
+ # if poly.is_valid and poly.is_simple and poly.convex_hull.equals(poly):
+ # return True
+ # p_before = None
+ # # Si concave : vรฉrifier visibilitรฉ
+ # for p in poly.exterior.coords[:-1]:
+ # full_seg = LineString([new_coordinates, p])
+ # new_seg_end = full_seg.interpolate(full_seg.length - 1e-5)
+ # seg = LineString([new_coordinates, new_seg_end])
+ # if not poly.contains_properly(seg):
+ # return False
+ # elif seg.crosses(poly.boundary):
+ # return False
+ # elif seg.touches(poly.boundary):
+ # return False
+ # elif p_before is not None: # test coolinearity of two vectors
+ # v1 = new_coordinates[0]-p[0], new_coordinates[1]-p[1]
+ # v2 = new_coordinates[0]-p_before[0], new_coordinates[1]-p_before[1]
+ #
+ # det = v1[0] * v2[1] - v1[1] * v2[0]
+ # if -1e-5 < det < 1e-5:
+ # return False
+ # p_before = p
+ # return Truedef is_star_vertex2(self, n1:Node, n2:Node, v):
+ #plot_mesh(self.mesh)
+ #
+ # adj_nodes = []
+ # nodes_coord = []
+ # d = n1.get_dart()
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # while n != n2:
+ # adj_nodes.append(n)
+ # nodes_coord.append([n.x(), n.y()])
+ # d = d2.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # d = d.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # while n != n1:
+ # if n not in adj_nodes:
+ # adj_nodes.append(n)
+ # nodes_coord.append([n.x(), n.y()])
+ # d = d2.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # d = d.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # while n != n2:
+ # if n not in adj_nodes:
+ # adj_nodes.append(n)
+ # nodes_coord.append([n.x(), n.y()])
+ # d = d2.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ #
+ # nodes_coord = np.array(nodes_coord)
+ #
+ # # Crรฉer le polygone
+ # poly = Polygon(nodes_coord)
+ # point_v = Point(v)
+ #
+ # # Vรฉrifier si polygone est convexe
+ # if poly.is_valid and poly.is_simple and poly.convex_hull.equals(poly):
+ # return True
+ #
+ # # Si concave : vรฉrifier visibilitรฉ
+ # for p in poly.exterior.coords[:-1]:
+ # seg = LineString([v, p])
+ # if not poly.contains(seg):
+ # # plt.figure(figsize=(6, 6))
+ # # # Polygone
+ # # x, y = poly.exterior.xy
+ # # plt.fill(x, y, alpha=0.3, edgecolor='red', facecolor='lightcoral',
+ # # label='Polygon formed par by neighbours vertices')
+ # #
+ # # # Voisins
+ # # plt.scatter(nodes_coord[:, 0], nodes_coord[:, 1], color='blue', zorder=5, label='Neighbours')
+ # #
+ # # # Sommet testรฉ
+ # # plt.scatter(v[0], v[1], color='green', s=100, zorder=5, label='Vertex to test')
+ # #
+ # # plt.legend()
+ # # plt.gca().set_aspect('equal')
+ # # plt.show()
+ # return False
+ # return True
+
+ # def is_star_vertex2(self, n1:Node, n2:Node, v):
+ # #plot_mesh(self.mesh)
+ #
+ # adj_nodes = []
+ # nodes_coord = []
+ # d = n1.get_dart()
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # while n != n2:
+ # adj_nodes.append(n)
+ # nodes_coord.append([n.x(), n.y()])
+ # d = d2.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # d = d.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # while n != n1:
+ # if n not in adj_nodes:
+ # adj_nodes.append(n)
+ # nodes_coord.append([n.x(), n.y()])
+ # d = d2.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # d = d.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ # while n != n2:
+ # if n not in adj_nodes:
+ # adj_nodes.append(n)
+ # nodes_coord.append([n.x(), n.y()])
+ # d = d2.get_beta(1)
+ # d2 = d.get_beta(2)
+ # n = d2.get_node()
+ #
+ # nodes_coord = np.array(nodes_coord)
+ #
+ # # Crรฉer le polygone
+ # poly = Polygon(nodes_coord)
+ # point_v = Point(v)
+ #
+ # # Vรฉrifier si polygone est convexe
+ # if poly.is_valid and poly.is_simple and poly.convex_hull.equals(poly):
+ # return True
+ #
+ # # Si concave : vรฉrifier visibilitรฉ
+ # for p in poly.exterior.coords[:-1]:
+ # seg = LineString([v, p])
+ # if not poly.contains(seg):
+ # # plt.figure(figsize=(6, 6))
+ # # # Polygone
+ # # x, y = poly.exterior.xy
+ # # plt.fill(x, y, alpha=0.3, edgecolor='red', facecolor='lightcoral',
+ # # label='Polygon formed par by neighbours vertices')
+ # #
+ # # # Voisins
+ # # plt.scatter(nodes_coord[:, 0], nodes_coord[:, 1], color='blue', zorder=5, label='Neighbours')
+ # #
+ # # # Sommet testรฉ
+ # # plt.scatter(v[0], v[1], color='green', s=100, zorder=5, label='Vertex to test')
+ # #
+ # # plt.legend()
+ # # plt.gca().set_aspect('equal')
+ # # plt.show()
+ # return False
+ # return True
+
+ # def find_star_vertex2(self, n1:Node, n2:Node) -> (float, float):
+ # adj_nodes = []
+ # nodes_coord = []
+ # for d_info in self.mesh.active_darts():
+ # if d_info[3] == n1.id or d_info[3] == n2.id:
+ # d2 = Dart(self.mesh, d_info[2])
+ # if d2 is not None:
+ # n = d2.get_node()
+ # adj_nodes.append(n)
+ # nodes_coord.append([n.x(), n.y()])
+ # else:
+ # raise ValueError("Collapse action may not be done near boundary")
+ # nodes_coord = np.array(nodes_coord)
+ #
+ # # Ordonner les voisins autour de v
+ # vectors = nodes_coord - v
+ # angles = np.arctan2(vectors[:, 1], vectors[:, 0])
+ # order = np.argsort(angles)
+ # neighbors_ordered = nodes_coord[order]
+ #
+ # hull = ConvexHull(nodes_coord)
+ # delaunay = Delaunay(nodes_coord)
+ # plt.plot(nodes_coord[:, 0], nodes_coord[:, 1], 'o')
+ #
+ # for simplex in hull.simplices:
+ # plt.plot(nodes_coord[simplex, 0], nodes_coord[simplex, 1], 'k-')
+ # plt.plot(nodes_coord[hull.vertices, 0], nodes_coord[hull.vertices, 1], 'r--', lw=2)
+ # plt.plot(nodes_coord[hull.vertices[0], 0], nodes_coord[hull.vertices[0], 1], 'ro')
+ # plt.show()
+ #
+ # _ = scipy.spatial.delaunay_plot_2d(delaunay)
+ # plt.show()
+ #
+ # mid = np.array([(n1.x() + n2.x()) / 2, (n1.y() + n2.y()) / 2])
+ # is_star_vertex = delaunay.find_simplex(mid) >=0
+ #
+ # # Calcul des angles des voisins autour de v
+ # vectors = nodes_coord - mid
+ # angles = np.arctan2(vectors[:, 1], vectors[:, 0])
+ # order = np.argsort(angles)
+ # neighbors_ordered = nodes_coord[order]
+ #
+ # # Construire le polygone
+ # poly = Polygon(neighbors_ordered)
+ #
+ # # Vรฉrifier si v est ร l'intรฉrieur ou sur la frontiรจre
+ # point_v = Point(mid)
+ # is_star = poly.contains(point_v) or poly.touches(point_v)
+ #
+ # plt.figure(figsize=(6, 6))
+ # # Polygone
+ # x, y = poly.exterior.xy
+ # plt.fill(x, y, alpha=0.3, edgecolor='red', facecolor='lightcoral', label='Polygone formรฉ par les voisins')
+ #
+ # # Voisins
+ # plt.scatter(nodes_coord[:, 0], nodes_coord[:, 1], color='blue', zorder=5, label='Voisins')
+ #
+ # # Sommet testรฉ
+ # plt.scatter(mid[0], mid[1], color='green', s=100, zorder=5, label='Sommet testรฉ')
+ #
+ # plt.legend()
+ # plt.gca().set_aspect('equal')
+ # plt.title(f"Le sommet est-il รฉtoilรฉ ? {is_star}")
+ # plt.show()
+ #
+ # if is_star:
+ # return mid
+ # elif poly.contains(Point(n1.x(), n1.y())) or poly.touches(Point(n1.x(), n1.y())):
+ # return n1.x(), n1.y()
+ # elif poly.contains(Point(n2.x(), n2.y())) or poly.touches(Point(n2.x(), n2.y())):
+ # return n2.x(), n2.y()
+ # else:
+ # plot_mesh(self.mesh)
+ # raise ValueError("No star vertex was found")
diff --git a/mesh_model/mesh_struct/mesh.py b/mesh_model/mesh_struct/mesh.py
index 01b8bb4..86da604 100644
--- a/mesh_model/mesh_struct/mesh.py
+++ b/mesh_model/mesh_struct/mesh.py
@@ -13,13 +13,14 @@
class Mesh:
def __init__(self, nodes=[], faces=[]):
"""
- Vertices are stored in a numpy array containing coordinates (x,y, dart id)
+ Vertices are stored in a numpy array containing coordinates (x,y, dart id, ideal adjacency, vertex score)
Faces are stored in a numpy array of simple (dart ids)
- Darts are stored in a numpy array, where each dart is a 5-tuple (dart id, beta_1, beta_2, vertex_id, face_id)
+ Darts are stored in a numpy array, where each dart is a 5-tuple (dart id, beta_1, beta_2, vertex_id, face_id, geo_quality)
+ Ideal adjacency, vertex scores and geometric quality are not defined here. You must use Mesh analysis class to define them
"""
- self.nodes = numpy.empty((0, 3))
+ self.nodes = numpy.empty((0, 5), dtype=float)
self.faces = numpy.empty(0, dtype=int)
- self.dart_info = numpy.empty((0, 5), dtype=int)
+ self.dart_info = numpy.empty((0, 6), dtype=int)
self.first_free_dart = 0
self.first_free_node = 0
self.first_free_face = 0
@@ -61,19 +62,20 @@ def nb_faces(self) -> int:
def add_node(self, x: float, y: float) -> Node:
"""
Add a vertex in the mesh, this node is not connected to a dart here
+ The ideal adjacency and vertex score are not defined here
:param x: X coordinate
:param y: Y coordinate
:return: the created node
"""
if len(self.nodes) <= self.first_free_node:
- self.nodes = numpy.append(self.nodes, [[x, y, -1]], axis=0)
+ self.nodes = numpy.append(self.nodes, [[x, y, -1, -1, -99]], axis=0)
self.first_free_node += 1
return Node(self, len(self.nodes) - 1)
elif self.first_free_node >= 0:
n_id = int(self.first_free_node)
if isinstance(n_id, int):
self.first_free_node = abs(self.nodes[n_id, 2] + 1)
- self.nodes[n_id] = [x, y, -1]
+ self.nodes[n_id] = [x, y, -1, -1, -99]
else:
print(n_id)
print(type(n_id))
@@ -272,17 +274,18 @@ def set_face_beta2(self, f: Face, darts: list[Dart]) -> None:
df_current = df_current.get_beta(1)
end = (df_current.id == f.get_dart().id)
- def add_dart(self, a1: int = -1, a2: int = -1, v: int = -1, f: int = -1) -> Dart:
+ def add_dart(self, a1: int = -1, a2: int = -1, v: int = -1, f: int = -1, q: int = -99) -> Dart:
"""
This function add a dart in the mesh. It must not be used directly
:param a1: dart index to connect by alpha1
:param a2: dart index to connect by alpha2
:param v: vertex index this dart point to
:param f: face to connect
+ :param q: geometric quality around the dart
:return: the created dart
"""
if len(self.dart_info) <= self.first_free_dart:
- self.dart_info = numpy.append(self.dart_info, [[len(self.dart_info), a1, a2, v, f]], axis=0)
+ self.dart_info = numpy.append(self.dart_info, [[len(self.dart_info), a1, a2, v, f, q]], axis=0)
self.first_free_dart += 1
return Dart(self, len(self.dart_info) - 1)
elif len(self.dart_info) > self.first_free_dart:
@@ -308,7 +311,16 @@ def del_dart(self, d: Dart):
"""
self.dart_info[d.id][0] = -self.first_free_dart - 1
self.first_free_dart = d.id
+ d.active = False
+ def is_dart_active(self, d: Dart) -> bool:
+ """Check if the dart has been deleted"""
+ if d is None:
+ return False
+ elif self.dart_info[d.id,0] < 0:
+ return False
+ elif self.dart_info[d.id,0] >=0 :
+ return True
def set_beta2(self, dart: Dart) -> None:
"""
@@ -405,6 +417,8 @@ def find_parallel_darts(self, d: Dart) -> list[Dart]:
return parallel_darts
+
+
def inverseQuad(A: Node, B: Node, C: Node, D: Node):
u1 = numpy.array([B.x() - A.x(), B.y() - A.y()]) # vect(AB)
u2 = numpy.array([C.x() - B.x(), C.y() - B.y()]) # vect(BC)
diff --git a/mesh_model/mesh_struct/mesh_elements.py b/mesh_model/mesh_struct/mesh_elements.py
index ac68310..a1b12e2 100644
--- a/mesh_model/mesh_struct/mesh_elements.py
+++ b/mesh_model/mesh_struct/mesh_elements.py
@@ -44,6 +44,9 @@ def get_beta(self, i: int) -> Dart:
raise ValueError("Wrong alpha dimension")
if self.mesh.dart_info[self.id, i] == -1:
return None
+ d2_id = self.mesh.dart_info[self.id, i]
+ if self.mesh.dart_info[d2_id, 0] <0 :
+ raise ValueError("Dart deleted")
return Dart(self.mesh, self.mesh.dart_info[self.id, i])
@@ -96,6 +99,36 @@ def set_face(self, face: Face) -> None:
"""
self.mesh.dart_info[self.id, 4] = face.id
+ def get_quality(self) -> int:
+ """
+ Get the geometric quality around a given dart.
+
+ :return: the geometric quality around the dart.
+ :raises ValueError: if there is no quality dimension
+ """
+ dart_quality = self.mesh.dart_info[self.id, 5]
+ if dart_quality == -99:
+ raise ValueError("No quality dimension")
+ return dart_quality
+
+ def set_quality(self, quality: int) -> None:
+ """
+ Set the geometric quality around a given dart. Automatically set the same quality for the twin dart
+ The quality is a parameter used to determine whether applying an operation to the dart would flip a face.
+
+ * For triangular meshes:
+ The dart's surrounding quality is determined by analyzing the quadrilateral formed by the two adjacent triangles.
+ The configuration is classified as convex, crossed, or concave.
+
+ * For quadrilateral meshes:
+ The dart's surrounding quality is determined based on whether the associated node forms a "star-shaped" (รฉtoilรฉ) configuration.
+ :param quality: calculated quality
+ """
+
+ d2_id = self.mesh.dart_info[self.id, 2]
+ self.mesh.dart_info[self.id, 5] = quality
+ if d2_id >=0: # inner dart
+ self.mesh.dart_info[d2_id, 5] = quality
class Node:
_mesh_type: type = None
@@ -175,6 +208,42 @@ def set_xy(self, x: float, y: float) -> None:
self.set_x(x)
self.set_y(y)
+ def set_ideal_adjacency(self, i: int) -> None:
+ """
+ Set the ideal adjacency of this node.
+ :param i: calculated ideal adjacency
+ """
+ self.mesh.nodes[self.id,3] = i
+
+ def get_ideal_adjacency(self) -> int:
+ """
+ Get the ideal adjacency of this node.
+ :return: ideal adjacency
+ :raises ValueError: if there is no ideal adjacency
+ """
+ ideal_adjacency = self.mesh.nodes[self.id,3]
+ if ideal_adjacency == -1:
+ raise ValueError("No ideal adjacency")
+ return ideal_adjacency
+
+ def set_score(self, s: int) -> None:
+ """
+ Set the score of a node.
+ :param s: calculated score
+ """
+ self.mesh.nodes[self.id,4] = s
+
+ def get_score(self) -> int:
+ """
+ Get the score of this node.
+ :return: score
+ :raises ValueError: if there is no score defined
+ """
+ score = self.mesh.nodes[self.id,4]
+ if score == -99:
+ raise ValueError("No score")
+ return score
+
class Face:
_mesh_type: type = None
diff --git a/mesh_model/random_quadmesh.py b/mesh_model/random_quadmesh.py
index 66a39cf..12fbbb0 100644
--- a/mesh_model/random_quadmesh.py
+++ b/mesh_model/random_quadmesh.py
@@ -4,7 +4,7 @@
from mesh_model.mesh_struct.mesh_elements import Dart
from mesh_model.mesh_struct.mesh import Mesh
-from mesh_model.mesh_analysis.quadmesh_analysis import isValidAction
+from mesh_model.mesh_analysis.quadmesh_analysis import QuadMeshOldAnalysis
from environment.actions.quadrangular_actions import flip_edge_cntcw_ids, split_edge_ids, collapse_edge_ids
from mesh_model.reader import read_gmsh
@@ -32,6 +32,7 @@ def mesh_shuffle(mesh: Mesh, num_nodes) -> Mesh:
nb_action_max = int(num_nodes)
nb_action = 0
active_darts_list = mesh.active_darts()
+ m_analysis = QuadMeshOldAnalysis(mesh)
i = 0
while i < nb_action_max:
action_type = np.random.randint(0, 3)
@@ -41,17 +42,17 @@ def mesh_shuffle(mesh: Mesh, num_nodes) -> Mesh:
i1 = dart.get_node()
i2 = (dart.get_beta(1)).get_node()
#plot_mesh(mesh)
- if action_type == 0 and isValidAction(mesh, d_id, action_type)[0]:
- flip_edge_cntcw_ids(mesh, i1.id, i2.id)
+ if action_type == 0 and m_analysis.isValidAction(d_id, action_type)[0]:
+ flip_edge_cntcw_ids(m_analysis, i1.id, i2.id)
nb_action += 1
- elif action_type == 1: # and isValidAction(mesh, d_id, action_type)[0]
- split_edge_ids(mesh, i1.id, i2.id)
+ elif action_type == 1 and m_analysis.isValidAction(d_id, action_type)[0]:
+ split_edge_ids(m_analysis, i1.id, i2.id)
nb_action += 1
- elif action_type == 2 and isValidAction(mesh, d_id, action_type)[0]:
- collapse_edge_ids(mesh, i1.id, i2.id)
+ elif action_type == 2 and m_analysis.isValidAction(d_id, action_type)[0]:
+ collapse_edge_ids(m_analysis, i1.id, i2.id)
nb_action += 1
- elif action_type == 3 and isValidAction(mesh, d_id, action_type)[0]:
- collapse_edge_ids(mesh, i1.id, i2.id)
+ elif action_type == 3 and m_analysis.isValidAction(d_id, action_type)[0]:
+ collapse_edge_ids(m_analysis, i1.id, i2.id)
nb_action += 1
i += 1
active_darts_list = mesh.active_darts()
diff --git a/mesh_model/random_trimesh.py b/mesh_model/random_trimesh.py
index db17a34..86a3834 100644
--- a/mesh_model/random_trimesh.py
+++ b/mesh_model/random_trimesh.py
@@ -1,10 +1,10 @@
from __future__ import annotations
import numpy as np
+from mesh_model.mesh_analysis.global_mesh_analysis import NodeAnalysis
from mesh_model.mesh_struct.mesh_elements import Dart, Node
from mesh_model.mesh_struct.mesh import Mesh
-from mesh_model.mesh_analysis.trimesh_analysis import find_opposite_node, isValidAction
-from mesh_model.mesh_analysis.global_mesh_analysis import node_in_mesh
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshQualityAnalysis
from environment.actions.triangular_actions import flip_edge_ids, split_edge_ids, collapse_edge_ids
@@ -18,6 +18,7 @@ def regular_mesh(num_nodes_max: int) -> Mesh:
nodes = [[0.0, 0.0], [1.0, 0.0], [0.5, 0.87]]
faces = [[0, 1, 2]]
mesh = Mesh(nodes, faces)
+ m_analysis = TriMeshQualityAnalysis(mesh)
num_nodes = 3
dart_id = 0
@@ -28,10 +29,10 @@ def regular_mesh(num_nodes_max: int) -> Mesh:
A = d.get_node()
d1 = d.get_beta(1)
B = d1.get_node()
- x_C, y_C = find_opposite_node(d)
+ x_C, y_C = m_analysis.find_opposite_node(d)
# Search if the node C already exist in the actual mesh
- found, n_id = node_in_mesh(mesh, x_C, y_C)
+ found, n_id = m_analysis.node_in_mesh( x_C, y_C)
if found and d.get_beta(2) is None:
C = Node(mesh, n_id)
@@ -46,6 +47,9 @@ def regular_mesh(num_nodes_max: int) -> Mesh:
dart_id += 1
mesh.set_twin_pointers()
+ m_analysis.set_adjacency()
+ m_analysis.set_scores()
+ m_analysis.set_geometric_quality()
return mesh
@@ -80,11 +84,12 @@ def mesh_shuffle_flip(mesh: Mesh) -> Mesh:
"""
nb_flip = len(mesh.dart_info)
nb_nodes = len(mesh.nodes)
+ m_analysis = TriMeshQualityAnalysis(mesh)
for i in range(nb_flip):
i1 = np.random.randint(nb_nodes)
i2 = np.random.randint(nb_nodes)
if i1 != i2:
- flip_edge_ids(mesh, i1, i2)
+ flip_edge_ids(m_analysis, i1, i2)
return mesh
def mesh_shuffle(mesh: Mesh, num_nodes) -> Mesh:
@@ -94,25 +99,26 @@ def mesh_shuffle(mesh: Mesh, num_nodes) -> Mesh:
:param num_nodes: number nodes of the mesh
:return: a mesh with randomly flipped darts.
"""
- nb_action_max = int(num_nodes)
+ nb_action_max = 3
nb_action = 0
active_darts_list = mesh.active_darts()
+ m_analysis = TriMeshQualityAnalysis(mesh)
i = 0
- while i < nb_action_max:
+ while nb_action < nb_action_max:
action_type = np.random.randint(0, 3)
d_id = np.random.randint(len(active_darts_list))
d_id = active_darts_list[d_id][0]
dart = Dart(mesh, d_id)
i1 = dart.get_node()
i2 = ((dart.get_beta(1)).get_beta(1)).get_node()
- if action_type == 0 and isValidAction(mesh, d_id, action_type)[0]:
- flip_edge_ids(mesh, i1.id, i2.id)
+ if action_type == 0 and m_analysis.isValidAction(d_id, action_type)[0]:
+ flip_edge_ids(m_analysis, i1.id, i2.id)
nb_action += 1
- elif action_type == 1 and isValidAction(mesh, d_id, action_type)[0]:
- split_edge_ids(mesh, i1.id, i2.id)
+ elif action_type == 1 and m_analysis.isValidAction(d_id, action_type)[0]:
+ split_edge_ids(m_analysis, i1.id, i2.id)
nb_action += 1
- elif action_type == 2 and isValidAction(mesh, d_id, action_type)[0]:
- collapse_edge_ids(mesh, i1.id, i2.id)
+ elif action_type == 2 and m_analysis.isValidAction(d_id, action_type)[0]:
+ collapse_edge_ids(m_analysis, i1.id, i2.id)
nb_action += 1
i += 1
active_darts_list = mesh.active_darts()
diff --git a/model_RL/PPO_model_pers.py b/model_RL/PPO_model_pers.py
index f2b860b..f390cb9 100644
--- a/model_RL/PPO_model_pers.py
+++ b/model_RL/PPO_model_pers.py
@@ -1,4 +1,3 @@
-from mesh_model.mesh_analysis.global_mesh_analysis import global_score
import copy
import random
from tqdm import tqdm
@@ -7,7 +6,6 @@
import torch.nn as nn
from torch.optim import Adam
from torch.distributions import Categorical
-from mesh_model.mesh_analysis.quadmesh_analysis import isValidAction
class NaNExceptionActor(Exception):
@@ -19,16 +17,17 @@ class NaNExceptionCritic(Exception):
class Actor(nn.Module):
- def __init__(self, env, input_dim, output_dim, lr=0.0001, eps=0):
+ def __init__(self, env, input_dim, n_actions, n_darts_observed, lr=0.0001, eps=0):
super(Actor, self).__init__()
self.fc1 = nn.Linear(input_dim, 64)
self.fc2 = nn.Linear(64, 64)
- self.fc3 = nn.Linear(64, output_dim)
+ self.fc3 = nn.Linear(64, n_actions*n_darts_observed)
self.softmax = nn.Softmax(dim=-1)
self.gamma = 0.9
self.optimizer = Adam(self.parameters(), lr=lr, weight_decay=0.01)
self.env = env
self.eps = eps
+ self.n_actions = n_actions
def reset(self, env=None):
self.fc1.reset_parameters()
@@ -37,6 +36,7 @@ def reset(self, env=None):
self.optimizer = Adam(self.parameters(), lr=self.optimizer.defaults['lr'], weight_decay=self.optimizer.defaults['weight_decay'])
def select_action(self, observation, info):
+ ma = info["mesh_analysis"]
if np.random.rand() < self.eps:
action = self.env.sample() # random choice of an action
dart_id = self.env.darts_selected[action[1]]
@@ -44,7 +44,7 @@ def select_action(self, observation, info):
total_actions_possible = np.prod(self.env.action_space.nvec)
prob = 1/total_actions_possible
i = 0
- while not isValidAction(self.env.mesh, dart_id, action_type):
+ while not ma.isValidAction(dart_id, action_type):
if i > 15:
return None, None
action = self.env.sample()
@@ -58,11 +58,11 @@ def select_action(self, observation, info):
action = dist.sample()
action = action.tolist()
prob = pmf[action]
- action_dart = int(action/4)
- action_type = action % 4
+ action_dart = int(action/self.n_actions)
+ action_type = action % self.n_actions
dart_id = info["darts_selected"][action_dart]
i = 0
- while not isValidAction(info["mesh"], dart_id, action_type):
+ while not ma.isValidAction(dart_id, action_type):
if i > 15:
return None, None
pmf = self.forward(obs)
@@ -70,8 +70,8 @@ def select_action(self, observation, info):
action = dist.sample()
action = action.tolist()
prob = pmf[action]
- action_dart = int(action/4)
- action_type = action % 4
+ action_dart = int(action/self.n_actions)
+ action_type = action % self.n_actions
dart_id = info["darts_selected"][action_dart]
i += 1
action_list = [action, dart_id, action_type]
@@ -137,10 +137,11 @@ def learn(self, critic_loss):
class PPO:
- def __init__(self, env, obs_size, max_steps, lr, gamma, nb_iterations, nb_episodes_per_iteration, nb_epochs, batch_size):
+ def __init__(self, env, obs_size, n_actions, n_darts_observed, max_steps, lr, gamma, nb_iterations, nb_episodes_per_iteration, nb_epochs, batch_size):
self.env = env
self.max_steps = max_steps
- self.actor = Actor(self.env, obs_size, 4*10, lr=lr)
+ self.n_actions =n_actions
+ self.actor = Actor(self.env, obs_size, n_actions, n_darts_observed, lr=lr)
self.critic = Critic(obs_size, lr=lr)
self.lr = lr
self.gamma = gamma
@@ -166,7 +167,7 @@ def train(self, dataset):
critic_loss = []
actor_loss = []
self.critic.optimizer.zero_grad()
- for _, (s, o, a, r, G, old_prob, next_o, done) in enumerate(batch, 1):
+ for _, (ma, o, a, r, G, old_prob, next_o, done) in enumerate(batch, 1):
o = torch.tensor(o.flatten(), dtype=torch.float32)
next_o = torch.tensor(next_o.flatten(), dtype=torch.float32)
value = self.critic(o)
@@ -174,7 +175,7 @@ def train(self, dataset):
log_prob = torch.log(pmf[a[0]])
next_value = torch.tensor(0.0, dtype=torch.float32) if done else self.critic(next_o)
delta = r + 0.9 * next_value - value
- _, st, ideal_s, _ = global_score(s) # Comparaison ร l'รฉtat s et pas s+1 ?
+ _, st, ideal_s, _ = ma.global_score() # Comparaison ร l'รฉtat s et pas s+1 ?
if st == ideal_s:
continue
advantage = 1 if done else G / (st - ideal_s)
@@ -226,13 +227,13 @@ def learn(self, writer):
done = False
step = 0
while step < self.max_steps:
- state = copy.deepcopy(info["mesh"])
+ ma = copy.deepcopy(info["mesh_analysis"])
obs = next_obs
action, prob = self.actor.select_action(obs, info)
if action is None:
wins.append(0)
break
- gym_action = [action[2],int(action[0]/4)]
+ gym_action = [action[2],int(action[0]/self.n_actions)]
next_obs, reward, terminated, truncated, info = self.env.step(gym_action)
ep_reward += reward
ep_mesh_reward += info["mesh_reward"]
@@ -241,13 +242,13 @@ def learn(self, writer):
if terminated:
if truncated:
wins.append(0)
- trajectory.append((state, obs, action, reward, G, prob, next_obs, done))
+ trajectory.append((ma, obs, action, reward, G, prob, next_obs, done))
else:
wins.append(1)
done = True
- trajectory.append((state, obs, action, reward, G, prob, next_obs, done))
+ trajectory.append((ma, obs, action, reward, G, prob, next_obs, done))
break
- trajectory.append((state, obs, action, reward, G, prob, next_obs, done))
+ trajectory.append((ma, obs, action, reward, G, prob, next_obs, done))
step += 1
if len(trajectory) != 0:
rewards.append(ep_reward)
@@ -275,4 +276,4 @@ def learn(self, writer):
print("NaN Exception on Critic Network")
return None, None, None, None
- return self.actor, rewards, wins, len_ep, info["observation_registry"]
+ return self.actor, rewards, wins, len_ep, None
diff --git a/model_RL/evaluate_model.py b/model_RL/evaluate_model.py
index 1f002ed..f6984be 100644
--- a/model_RL/evaluate_model.py
+++ b/model_RL/evaluate_model.py
@@ -1,19 +1,19 @@
-from numpy import ndarray
-
-from environment.trimesh_env import TriMesh
-from mesh_model.mesh_analysis.global_mesh_analysis import global_score
-from mesh_model.mesh_struct.mesh import Mesh
import numpy as np
import copy
+
from tqdm import tqdm
+from environment.old_files.trimesh_env import TriMesh
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshOldAnalysis
+from mesh_model.mesh_struct.mesh import Mesh
+
def testPolicy(
policy,
n_eval_episodes: int,
dataset: list[Mesh],
max_steps: int
-) -> tuple[ndarray, ndarray, ndarray, list[Mesh]]:
+) -> tuple[np.ndarray, np.ndarray, np.ndarray, list[Mesh]]:
"""
Tests policy on each mesh of a dataset with n_eval_episodes.
:param policy: the policy to test
@@ -60,7 +60,9 @@ def isBetterPolicy(actual_best_policy, policy_to_test):
def isBetterMesh(best_mesh, actual_mesh):
- if best_mesh is None or global_score(best_mesh)[1] > global_score(actual_mesh)[1]:
+ ma1 = TriMeshOldAnalysis(best_mesh)
+ ma2 = TriMeshOldAnalysis(actual_mesh)
+ if best_mesh is None or ma1.global_score()[1] > ma2.global_score()[1]:
return True
else:
return False
diff --git a/model_RL/AC_model.py b/model_RL/old_files/AC_model.py
similarity index 96%
rename from model_RL/AC_model.py
rename to model_RL/old_files/AC_model.py
index f48582f..615dd18 100644
--- a/model_RL/AC_model.py
+++ b/model_RL/old_files/AC_model.py
@@ -1,6 +1,6 @@
import torch
from tqdm import tqdm
-from model_RL.utilities.actor_critic_networks import NaNExceptionActor, NaNExceptionCritic, Actor, Critic
+from model_RL.old_files.utilities import NaNExceptionActor, NaNExceptionCritic, Actor, Critic
class AC:
diff --git a/model_RL/PPO_model.py b/model_RL/old_files/PPO_model.py
similarity index 98%
rename from model_RL/PPO_model.py
rename to model_RL/old_files/PPO_model.py
index a6dc568..ecbe9dd 100644
--- a/model_RL/PPO_model.py
+++ b/model_RL/old_files/PPO_model.py
@@ -2,7 +2,7 @@
Old version of PPO for triangular environement
"""
-from model_RL.utilities.actor_critic_networks import NaNExceptionActor, NaNExceptionCritic, Actor, Critic
+from model_RL.old_files.utilities import NaNExceptionActor, NaNExceptionCritic, Actor, Critic
from mesh_model.mesh_analysis.global_mesh_analysis import global_score
import copy
import torch
diff --git a/model_RL/SAC_model.py b/model_RL/old_files/SAC_model.py
similarity index 97%
rename from model_RL/SAC_model.py
rename to model_RL/old_files/SAC_model.py
index eff6636..62212f4 100644
--- a/model_RL/SAC_model.py
+++ b/model_RL/old_files/SAC_model.py
@@ -1,4 +1,4 @@
-from model_RL.utilities.actor_critic_networks import NaNExceptionActor, NaNExceptionCritic, Actor, Critic
+from model_RL.old_files.utilities import NaNExceptionActor, NaNExceptionCritic, Actor, Critic
import torch
import random
diff --git a/model_RL/parameters/ppo_config.json b/model_RL/old_files/ppo_config.json
similarity index 59%
rename from model_RL/parameters/ppo_config.json
rename to model_RL/old_files/ppo_config.json
index 1b844e5..299000f 100644
--- a/model_RL/parameters/ppo_config.json
+++ b/model_RL/old_files/ppo_config.json
@@ -5,7 +5,7 @@
"batch_size": 64,
"learning_rate": 0.0001,
"gamma": 0.9,
- "verbose": 1,
- "tensorboard_log": "training/results/quad/",
- "total_timesteps": 80000
+ "verbose": 2,
+ "tensorboard_log": "training/results/tri/",
+ "total_timesteps": 20000
}
diff --git a/model_RL/utilities/actor_critic_networks.py b/model_RL/old_files/utilities/actor_critic_networks.py
similarity index 100%
rename from model_RL/utilities/actor_critic_networks.py
rename to model_RL/old_files/utilities/actor_critic_networks.py
diff --git a/model_RL/utilities/nnPolicy.py b/model_RL/old_files/utilities/nnPolicy.py
similarity index 100%
rename from model_RL/utilities/nnPolicy.py
rename to model_RL/old_files/utilities/nnPolicy.py
diff --git a/model_RL/utilities/__init__.py b/model_RL/utilities/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/test_modules/test_actions.py b/test_modules/test_actions.py
index b2fcad6..c21de43 100644
--- a/test_modules/test_actions.py
+++ b/test_modules/test_actions.py
@@ -1,5 +1,7 @@
import unittest
+import scipy
import mesh_model.mesh_struct.mesh as mesh
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshQualityAnalysis
from mesh_model.mesh_struct.mesh_elements import Dart, Node
from mesh_model.random_trimesh import regular_mesh
from environment.actions.triangular_actions import split_edge, flip_edge, collapse_edge
@@ -31,7 +33,10 @@ def test_flip(self):
d1.set_beta(2, d2)
d2.set_beta(2, d1)
- flip_edge(cmap, n00, n11)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ done = flip_edge(m_analysis, n00, n11)
+
+ self.assertTrue(done[0])
self.assertEqual(2, cmap.nb_faces())
self.assertEqual(4, cmap.nb_nodes())
@@ -45,69 +50,78 @@ def test_split(self):
t1 = cmap.add_triangle(n00, n10, n11)
t2 = cmap.add_triangle(n00, n11, n01)
- split_edge(cmap, n00, n11)
+ cmap.set_twin_pointers()
+ m_analysis = TriMeshQualityAnalysis(cmap)
+
+ done = split_edge(m_analysis, n00, n11)
+ n_new = Node(cmap, 4)
+
+ self.assertTrue(done[0])
d1 = t1.get_dart()
- # d1 goes from n00 to n10
- self.assertEqual(d1.get_node(), n00)
+ # d1 goes from nnew to n10
+ self.assertEqual(d1.get_node(), n_new)
d1 = d1.get_beta(1).get_beta(1)
# now d1 goes from n11 to n00
self.assertEqual(d1.get_node(), n11)
d2 = t2.get_dart() # goes from n00 to n11
self.assertEqual(d2.get_node(), n00)
- # We sew on both directions
- d1.set_beta(2, d2)
- d2.set_beta(2, d1)
+ self.assertEqual(4, cmap.nb_faces())
+ self.assertEqual(5, cmap.nb_nodes())
def test_collapse(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]
faces = [[0, 1, 2], [0, 2, 3]]
cmap = mesh.Mesh(nodes, faces)
- plot_mesh(cmap)
n00 = Node(cmap, 0)
n11 = Node(cmap, 2)
- split_edge(cmap, n00, n11)
- plot_mesh(cmap)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+
+ split_edge(m_analysis, n00, n11)
n5 = Node(cmap, 4)
- valid, _, _ = collapse_edge(cmap, n00, n5)
- d1_to_test = Dart(cmap, 7)
- d2_to_test = Dart(cmap, 0)
+ split_edge(m_analysis, n11, n5)
+ n6 = Node(cmap, 5)
+ plot_mesh(cmap)
+ #Collapse not possible
+ valid, _, _ = collapse_edge(m_analysis, n11, n6)
self.assertEqual(valid, False)
- # Test possible collapse
- cmap = regular_mesh(16)
- d = Dart(cmap, 0)
- n0 = d.get_node()
- n1 = d.get_beta(1).get_node()
- valid, _, _ = collapse_edge(cmap, n0, n1)
+
+ # Collapse possible
+ valid, _, _ = collapse_edge(m_analysis, n6, n5)
self.assertEqual(valid, True)
+ plot_mesh(cmap)
+
def test_split_collapse_split(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]
faces = [[0, 1, 2], [0, 2, 3]]
cmap = mesh.Mesh(nodes, faces)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+
n0 = Node(cmap, 0)
n1 = Node(cmap, 1)
n2 = Node(cmap, 2)
n3 = Node(cmap, 3)
- split_edge(cmap, n0, n2)
+ split_edge(m_analysis, n0, n2)
n4 = Node(cmap, 4)
- collapse_edge(cmap, n0, n4)
- split_edge(cmap, n0, n2)
+ collapse_edge(m_analysis, n0, n4)
+ split_edge(m_analysis, n0, n2)
n5 = Node(cmap, 5)
- collapse_edge(cmap, n0, n5)
- split_edge(cmap, n4, n2)
- collapse_edge(cmap, n4, n5)
- collapse_edge(cmap, n2, n4)
- split_edge(cmap, n0, n2)
- split_edge(cmap, n0, n4)
- split_edge(cmap, n4, n3)
- split_edge(cmap, n4, n1)
- split_edge(cmap, n5, n1)
+ collapse_edge(m_analysis, n0, n5)
+ split_edge(m_analysis, n4, n2)
+ collapse_edge(m_analysis, n4, n5)
+ collapse_edge(m_analysis, n2, n4)
+ split_edge(m_analysis, n0, n2)
+ split_edge(m_analysis, n0, n4)
+ split_edge(m_analysis, n4, n3)
+ split_edge(m_analysis, n4, n1)
+ split_edge(m_analysis, n5, n1)
n7 = Node(cmap, 7)
n8 = Node(cmap, 8)
- collapse_edge(cmap, n7, n8)
- collapse_edge(cmap, n5, n7)
-
+ collapse_edge(m_analysis, n7, n8)
+ collapse_edge(m_analysis, n5, n7)
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file
diff --git a/test_modules/test_actions_quad.py b/test_modules/test_actions_quad.py
index fdc1903..24469d6 100644
--- a/test_modules/test_actions_quad.py
+++ b/test_modules/test_actions_quad.py
@@ -1,9 +1,9 @@
import unittest
import os
import mesh_model.mesh_struct.mesh as mesh
-from mesh_model.mesh_analysis.global_mesh_analysis import global_score
from mesh_model.mesh_struct.mesh_elements import Dart, Node
from mesh_model.random_quadmesh import random_mesh
+from mesh_model.mesh_analysis.quadmesh_analysis import QuadMeshOldAnalysis
from environment.actions.quadrangular_actions import flip_edge_cntcw, flip_edge_cw, split_edge, collapse_edge, cleanup_edge
from view.mesh_plotter.mesh_plots import plot_mesh
from mesh_model.reader import read_gmsh
@@ -24,6 +24,7 @@ def test_flip(self):
q1 = cmap.add_quad(n11, n10, n20, n21)
q2 = cmap.add_quad(n10, n11, n01, n00)
cmap.set_twin_pointers()
+ ma = QuadMeshOldAnalysis(cmap)
plot_mesh(cmap)
d0 = q1.get_dart()
@@ -34,11 +35,12 @@ def test_flip(self):
self.assertEqual(d2.get_node(), n10)
- self.assertEqual(flip_edge_cntcw(cmap, n11, n10), (True,True,True))
+ self.assertEqual(flip_edge_cntcw(ma, n11, n10), (True,True,True))
self.assertEqual(2, cmap.nb_faces())
self.assertEqual(6, cmap.nb_nodes())
plot_mesh(cmap)
- self.assertFalse(flip_edge_cntcw(cmap, n11, n10)[0])
+ self.assertFalse(flip_edge_cntcw(ma, n11, n10)[0])
+ self.assertEqual(flip_edge_cw(ma, n01, n20), (True, True, True))
def test_split(self):
cmap = mesh.Mesh()
@@ -57,14 +59,15 @@ def test_split(self):
q3 = cmap.add_quad(n11, n21, n22, n12)
q4 = cmap.add_quad(n01, n11, n12, n02)
cmap.set_twin_pointers()
+ ma = QuadMeshOldAnalysis(cmap)
plot_mesh(cmap)
found, d = cmap.find_inner_edge(n11, n21)
self.assertTrue(found)
- self.assertEqual(split_edge(cmap, n11, n21), (True,True,True))
+ self.assertEqual(split_edge(ma, n11, n21), (True,True,True))
self.assertEqual(10, cmap.nb_nodes())
self.assertEqual(5, cmap.nb_faces())
plot_mesh(cmap)
- self.assertFalse(split_edge(cmap, n20, n21)[0])
+ self.assertFalse(split_edge(ma, n20, n21)[0])
def test_collapse(self):
cmap = mesh.Mesh()
@@ -88,12 +91,13 @@ def test_collapse(self):
plot_mesh(cmap)
found, d = cmap.find_inner_edge(n151, n12)
self.assertTrue(found)
+ ma = QuadMeshOldAnalysis(cmap)
plot_mesh(cmap)
- self.assertEqual(collapse_edge(cmap, n151, n12), (True, True, True))
+ self.assertEqual(collapse_edge(ma, n151, n12), (True, True, True))
self.assertEqual(9, cmap.nb_nodes())
self.assertEqual(4, cmap.nb_faces())
plot_mesh(cmap)
- self.assertFalse(split_edge(cmap, n20, n21)[0])
+ self.assertFalse(split_edge(ma, n20, n21)[0])
def test_cleanup(self):
cmap = mesh.Mesh()
@@ -114,10 +118,11 @@ def test_cleanup(self):
q4 = cmap.add_quad(n01, n051, n12, n02)
q5 = cmap.add_quad(n051, n10, n151, n12)
cmap.set_twin_pointers()
+ ma = QuadMeshOldAnalysis(cmap)
plot_mesh(cmap)
found, d = cmap.find_inner_edge(n151, n12)
self.assertTrue(found)
- self.assertEqual(cleanup_edge(cmap, n151, n21), (True, True, True))
+ self.assertEqual(cleanup_edge(ma, n151, n21), (True, True, True))
self.assertEqual(7, cmap.nb_nodes())
self.assertEqual(3, cmap.nb_faces())
plot_mesh(cmap)
@@ -126,16 +131,17 @@ def test_cleanup(self):
def test_actions(self):
filename = os.path.join(TESTFILE_FOLDER, 't1_quad.msh')
cmap = read_gmsh(filename)
+ ma = QuadMeshOldAnalysis(cmap)
plot_mesh(cmap)
d = Dart(cmap, 14)
n1= d.get_node()
n2 = (d.get_beta(1)).get_node()
- self.assertEqual(collapse_edge(cmap, n1, n2), (True,True,True))
+ self.assertEqual(collapse_edge(ma, n1, n2), (True,True,True))
plot_mesh(cmap)
d = Dart(cmap, 32)
n1 = d.get_node()
n2 = (d.get_beta(1)).get_node()
- self.assertEqual(flip_edge_cntcw(cmap, n1, n2), (True,True,True))
+ self.assertEqual(flip_edge_cntcw(ma, n1, n2), (True,True,True))
plot_mesh(cmap)
@@ -151,100 +157,103 @@ def test_split_collapse_split(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]
faces = [[0, 1, 2], [0, 2, 3]]
cmap = mesh.Mesh(nodes, faces)
+ ma = QuadMeshOldAnalysis(cmap)
n0 = Node(cmap, 0)
n1 = Node(cmap, 1)
n2 = Node(cmap, 2)
n3 = Node(cmap, 3)
- split_edge(cmap, n0, n2)
+ split_edge(ma, n0, n2)
n4 = Node(cmap, 4)
- collapse_edge(cmap, n0, n4)
- split_edge(cmap, n0, n2)
+ collapse_edge(ma, n0, n4)
+ split_edge(ma, n0, n2)
n5 = Node(cmap, 5)
- collapse_edge(cmap, n0, n5)
- split_edge(cmap, n4, n2)
- collapse_edge(cmap, n4, n5)
- collapse_edge(cmap, n2, n4)
- split_edge(cmap, n0, n2)
- split_edge(cmap, n0, n4)
- split_edge(cmap, n4, n3)
- split_edge(cmap, n4, n1)
- split_edge(cmap, n5, n1)
+ collapse_edge(ma, n0, n5)
+ split_edge(ma, n4, n2)
+ collapse_edge(ma, n4, n5)
+ collapse_edge(ma, n2, n4)
+ split_edge(ma, n0, n2)
+ split_edge(ma, n0, n4)
+ split_edge(ma, n4, n3)
+ split_edge(ma, n4, n1)
+ split_edge(ma, n5, n1)
n7 = Node(cmap, 7)
n8 = Node(cmap, 8)
- collapse_edge(cmap, n7, n8)
- collapse_edge(cmap, n5, n7)
+ collapse_edge(ma, n7, n8)
+ collapse_edge(ma, n5, n7)
def test_simple_mesh(self):
filename = os.path.join(TESTFILE_FOLDER, 'simple_quad.msh')
cmap = read_gmsh(filename)
+ ma = QuadMeshOldAnalysis(cmap)
self.assertEqual(6, cmap.nb_faces())
self.assertEqual(11, cmap.nb_nodes())
#Collapse node 10 (0.67,0.67) from edge 10-6
- collapse_edge(cmap, Node(cmap, 10), Node(cmap, 6))
+ collapse_edge(ma, Node(cmap, 10), Node(cmap, 6))
self.assertEqual(5, cmap.nb_faces())
self.assertEqual(10, cmap.nb_nodes())
self.assertTrue(Node(cmap,10).get_dart().id < 0)
plot_mesh(cmap)
#Flip edge 5-3
self.assertTrue(cmap.find_inner_edge(Node(cmap, 5), Node(cmap, 3))[0])
- flip_edge_cntcw(cmap, Node(cmap, 5), Node(cmap, 3))
+ flip_edge_cntcw(ma, Node(cmap, 5), Node(cmap, 3))
self.assertFalse(cmap.find_inner_edge(Node(cmap, 5), Node(cmap, 3))[0])
plot_mesh(cmap)
#Collapse node 9 (0.33, 0.33) from edge 9-4
- collapse_edge(cmap, Node(cmap, 9), Node(cmap, 4))
+ collapse_edge(ma, Node(cmap, 9), Node(cmap, 4))
self.assertEqual(4, cmap.nb_faces())
self.assertEqual(9, cmap.nb_nodes())
self.assertTrue(Node(cmap, 9).get_dart().id < 0)
plot_mesh(cmap)
#Flip edge 7-1
self.assertTrue(cmap.find_inner_edge(Node(cmap, 7), Node(cmap, 1))[0])
- flip_edge_cntcw(cmap, Node(cmap, 7), Node(cmap, 1))
+ flip_edge_cntcw(ma, Node(cmap, 7), Node(cmap, 1))
self.assertFalse(cmap.find_inner_edge(Node(cmap, 7), Node(cmap, 1))[0])
plot_mesh(cmap)
#Flip edge 3-8
self.assertTrue(cmap.find_inner_edge(Node(cmap, 3), Node(cmap, 8))[0])
- flip_edge_cntcw(cmap, Node(cmap, 3), Node(cmap, 8))
+ flip_edge_cntcw(ma, Node(cmap, 3), Node(cmap, 8))
self.assertFalse(cmap.find_inner_edge(Node(cmap, 3), Node(cmap, 8))[0])
plot_mesh(cmap)
#Flip edge 1-8
self.assertTrue(cmap.find_inner_edge(Node(cmap, 1), Node(cmap, 8))[0])
- flip_edge_cntcw(cmap, Node(cmap, 1), Node(cmap, 8))
+ flip_edge_cntcw(ma, Node(cmap, 1), Node(cmap, 8))
self.assertFalse(cmap.find_inner_edge(Node(cmap, 1), Node(cmap, 8))[0])
plot_mesh(cmap)
#Split edge 2-7 and create new node n9 at coordinate (0.5, 0.75)
- split_edge(cmap, Node(cmap, 2), Node(cmap, 7))
+ split_edge(ma, Node(cmap, 2), Node(cmap, 7))
self.assertEqual(5, cmap.nb_faces())
self.assertEqual(10, cmap.nb_nodes())
self.assertTrue(Node(cmap, 9).get_dart().id > 0)
plot_mesh(cmap)
# Split edge 0-5 and create new node n10 at coordinate (0.5, 0.25)
- split_edge(cmap, Node(cmap, 0), Node(cmap, 5))
+ split_edge(ma, Node(cmap, 0), Node(cmap, 5))
self.assertEqual(6, cmap.nb_faces())
self.assertEqual(11, cmap.nb_nodes())
self.assertTrue(Node(cmap, 10).get_dart().id > 0)
plot_mesh(cmap)
# Flip edge 0-8
self.assertTrue(cmap.find_inner_edge(Node(cmap, 0), Node(cmap, 8))[0])
- flip_edge_cw(cmap, Node(cmap, 0), Node(cmap, 8))
+ flip_edge_cw(ma, Node(cmap, 0), Node(cmap, 8))
self.assertFalse(cmap.find_inner_edge(Node(cmap, 0), Node(cmap, 8))[0])
plot_mesh(cmap)
# Collapse node 8 (0.5, 0.5) from edge 8-10
- collapse_edge(cmap, Node(cmap, 8), Node(cmap, 10))
+ collapse_edge(ma, Node(cmap, 8), Node(cmap, 10))
self.assertEqual(5, cmap.nb_faces())
self.assertEqual(10, cmap.nb_nodes())
self.assertTrue(Node(cmap, 8).get_dart().id < 0)
# Collapse node 10 (0.5, 0.25) from edge 10-5
- collapse_edge(cmap, Node(cmap, 10), Node(cmap, 5))
+ collapse_edge(ma, Node(cmap, 10), Node(cmap, 5))
self.assertEqual(4, cmap.nb_faces())
self.assertEqual(9, cmap.nb_nodes())
self.assertTrue(Node(cmap, 10).get_dart().id < 0)
plot_mesh(cmap)
- self.assertEqual(global_score(cmap)[1], 0)
-
+ self.assertEqual(ma.global_score()[1], 0)
+if __name__ == '__main__':
+ unittest.main()
diff --git a/test_modules/test_global_mesh_analysis.py b/test_modules/test_global_mesh_analysis.py
new file mode 100644
index 0000000..58ef84a
--- /dev/null
+++ b/test_modules/test_global_mesh_analysis.py
@@ -0,0 +1,33 @@
+import math
+import unittest
+import os
+
+from mesh_model.mesh_struct.mesh import Mesh
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshQualityAnalysis, TriMeshOldAnalysis
+from mesh_model.reader import read_gmsh
+from view.mesh_plotter.mesh_plots import plot_mesh
+
+TESTFILE_FOLDER = os.path.join(os.path.dirname(__file__), '../mesh_files/')
+
+class TestGlobalMeshAnalysis(unittest.TestCase):
+
+ def test_angle_by_coord(self):
+ filename = os.path.join(TESTFILE_FOLDER, 't1_quad.msh')
+ cmap = read_gmsh(filename)
+ m_analysis = TriMeshOldAnalysis(cmap)
+ self.assertEqual(m_analysis.get_angle_by_coord(1,0,0,0,0,1), 90)
+ self.assertEqual(m_analysis.get_angle_by_coord(-1,0,0,0,1,0), 180)
+
+ def test_angle_from_sides(self):
+ filename = os.path.join(TESTFILE_FOLDER, 't1_quad.msh')
+ cmap = read_gmsh(filename)
+ m_analysis = TriMeshOldAnalysis(cmap)
+ self.assertAlmostEquals(math.degrees(m_analysis.angle_from_sides(1,1,1)), 60)
+ self.assertAlmostEquals(math.degrees(m_analysis.angle_from_sides(0.00000001, 1, 1)), 0)
+ self.assertAlmostEquals(math.degrees(m_analysis.angle_from_sides(1, 0.5, 0.5)), 180)
+
+ with self.assertRaises(ValueError):
+ m_analysis.angle_from_sides(1.1, 0.5, 0.5)
+
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file
diff --git a/test_modules/test_quadrangular_mesh_analysis.py b/test_modules/test_quadrangular_mesh_analysis.py
index aea10de..ff4a41b 100644
--- a/test_modules/test_quadrangular_mesh_analysis.py
+++ b/test_modules/test_quadrangular_mesh_analysis.py
@@ -3,77 +3,89 @@
from mesh_model.mesh_struct.mesh import Mesh
from mesh_model.mesh_struct.mesh_elements import Dart
-import mesh_model.mesh_analysis.global_mesh_analysis as GMA
-import mesh_model.mesh_analysis.quadmesh_analysis as QMA
-from environment.actions.triangular_actions import split_edge_ids
+from mesh_model.mesh_analysis.quadmesh_analysis import QuadMeshOldAnalysis
+from environment.actions.quadrangular_actions import split_edge_ids, flip_edge_cw_ids
from view.mesh_plotter.mesh_plots import plot_mesh
from mesh_model.reader import read_gmsh
TESTFILE_FOLDER = os.path.join(os.path.dirname(__file__), '../mesh_files/')
-class TestMeshAnalysis(unittest.TestCase):
+class TestMeshOldAnalysis(unittest.TestCase):
def test_mesh_regular_score(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [2.0, 0.0], [0.0, 1.0], [1.0, 1.0], [2.0, 1.0], [0.0, 2.0], [1.0, 2.0], [2.0, 2.0], [3.0, 3.0]]
faces = [[0, 1, 4, 3], [1, 2, 5, 4], [3, 4, 7, 6], [4, 5, 8, 7]]
cmap = Mesh(nodes,faces)
- nodes_score, mesh_score, mesh_ideal_score, adjacency = GMA.global_score(cmap)
+ qma = QuadMeshOldAnalysis(cmap)
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = qma.global_score()
self.assertEqual((0,0), (mesh_score, mesh_ideal_score) )
def test_mesh_with_irregularities(self):
filename = os.path.join(TESTFILE_FOLDER, 't1_quad.msh')
cmap = read_gmsh(filename)
- nodes_score, mesh_score, mesh_ideal_score, adjacency = GMA.global_score(cmap)
+ qma = QuadMeshOldAnalysis(cmap)
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = qma.global_score()
self.assertIsNot((0, 0), (mesh_score,mesh_ideal_score) )
def test_is_valid_action(self):
filename = os.path.join(TESTFILE_FOLDER, 't1_quad.msh')
cmap = read_gmsh(filename)
+ qma = QuadMeshOldAnalysis(cmap)
#Boundary dart
- self.assertEqual(QMA.isValidAction(cmap, 20, 0), (False, True))
+ self.assertEqual(qma.isValidAction(20, 0), (False, True))
- # Flip test
- self.assertEqual(QMA.isValidAction(cmap, 3, 0), (True, True))
- self.assertEqual(QMA.isValidAction(cmap, 27, 0), (False, True))
+ # Flip Clockwise test
+ self.assertEqual(qma.isValidAction(3, 0), (True, True))
+ self.assertEqual(qma.isValidAction(27, 0), (False, True))
+
+ # Flip Counterclockwise test
+ self.assertEqual(qma.isValidAction(3, 1), (True, True))
+ self.assertEqual(qma.isValidAction(27, 1), (False, True))
#Split test
- self.assertEqual(QMA.isValidAction(cmap, 0, 1), (True, True))
- self.assertEqual(QMA.isValidAction(cmap, 27, 1), (False, True))
+ self.assertEqual(qma.isValidAction(0, 2), (True, True))
+ self.assertEqual(qma.isValidAction(27, 2), (False, True))
#Collapse test
- self.assertEqual(QMA.isValidAction(cmap, 0, 2), (True, True))
+ self.assertEqual(qma.isValidAction(0, 3), (True, True))
plot_mesh(cmap)
- self.assertEqual(QMA.isValidAction(cmap, 27, 2), (False, True))
+ self.assertEqual(qma.isValidAction(27, 3), (False, True))
+
+ #Cleanup test action id = 4
#All action test
- self.assertEqual(QMA.isValidAction(cmap, 27, 3), (False, True))
- self.assertEqual(QMA.isValidAction(cmap, 9, 3), (True, True))
+ self.assertEqual(qma.isValidAction(27, 5), (False, True))
+ flip_edge_cw_ids(qma,13,37)
+ self.assertEqual(qma.isValidAction(66, 5), (False, False))
+ self.assertEqual(qma.isValidAction(9, 5), (True, True))
#One action test
- self.assertEqual(QMA.isValidAction(cmap, 0, 4), (True, True))
- self.assertEqual(QMA.isValidAction(cmap, 9, 4), (True, True))
- self.assertEqual(QMA.isValidAction(cmap, 27, 4), (False, True))
+ self.assertEqual(qma.isValidAction(0, 6), (True, True))
+ self.assertEqual(qma.isValidAction(9, 6), (True, True))
+ self.assertEqual(qma.isValidAction(27, 6), (False, True))
#Invalid action
with self.assertRaises(ValueError):
- QMA.isValidAction(cmap, 0, 7)
+ qma.isValidAction(0, 7)
def test_isTruncated(self):
filename = os.path.join(TESTFILE_FOLDER, 't1_quad.msh')
cmap = read_gmsh(filename)
+ qma = QuadMeshOldAnalysis(cmap)
darts_list = []
for d_info in cmap.active_darts():
darts_list.append(d_info[0])
- self.assertFalse(QMA.isTruncated(cmap, darts_list))
+ self.assertFalse(qma.isTruncated(darts_list))
nodes = [[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
faces = [[0, 1, 3, 2]]
cmap = Mesh(nodes, faces)
+ qma = QuadMeshOldAnalysis(cmap)
darts_list = []
for d_info in cmap.active_darts():
darts_list.append(d_info[0])
- self.assertTrue(QMA.isTruncated(cmap, darts_list))
+ self.assertTrue(qma.isTruncated(darts_list))
if __name__ == '__main__':
unittest.main()
diff --git a/test_modules/test_triangular_mesh_analysis.py b/test_modules/test_triangular_mesh_analysis.py
index 8eeff64..8dd1fc3 100644
--- a/test_modules/test_triangular_mesh_analysis.py
+++ b/test_modules/test_triangular_mesh_analysis.py
@@ -1,20 +1,19 @@
import unittest
from mesh_model.mesh_struct.mesh import Mesh
-from mesh_model.mesh_struct.mesh_elements import Dart
-import mesh_model.mesh_analysis.global_mesh_analysis as GMA
-import mesh_model.mesh_analysis.trimesh_analysis as TMA
-import mesh_model.mesh_analysis.quadmesh_analysis as QMA
+from mesh_model.mesh_struct.mesh_elements import Dart, Node
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshQualityAnalysis, TriMeshOldAnalysis
from environment.actions.triangular_actions import split_edge_ids
from view.mesh_plotter.mesh_plots import plot_mesh
-class TestMeshAnalysis(unittest.TestCase):
+class TestMeshQualityAnalysis(unittest.TestCase):
def test_mesh_regular_score(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [0.5, 1], [-0.5, 1.0], [0.0, 2.0], [-1.0,0.0],[-0.5,-1.0],[0.0,-2.0], [0.5,-1.0]]
faces = [[0, 1, 2], [0, 2, 3], [3, 2, 4], [3, 5, 0], [0, 5, 6], [0, 6, 8], [6, 7, 8], [0, 8, 1]]
cmap = Mesh(nodes,faces)
- nodes_score, mesh_score, mesh_ideal_score, adjacency = GMA.global_score(cmap)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = m_analysis.global_score()
self.assertEqual((0,0), (mesh_score, mesh_ideal_score) )
def test_mesh_with_irregularities(self):
@@ -25,34 +24,38 @@ def test_mesh_with_irregularities(self):
[3, 4, 5], [3, 5, 6], [3, 6, 7], [7, 6, 8], [7, 8, 9], [7, 9, 10], [10, 9, 11], [10, 11, 12],
[14, 12, 13], [14, 13, 15], [1, 14, 15], [1, 15, 16], [1, 16, 17], [1, 17, 2], [2, 17, 18], [2, 18, 4]]
cmap = Mesh(nodes, faces)
- nodes_score, mesh_score, mesh_ideal_score, adjacency = GMA.global_score(cmap)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = m_analysis.global_score()
self.assertEqual((6, -2), (mesh_score,mesh_ideal_score) )
def test_mesh_bad_score(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
cmap = Mesh(nodes, faces)
- nodes_score, mesh_score, mesh_ideal_score, adjacency = GMA.global_score(cmap)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = m_analysis.global_score()
self.assertEqual((3, 1), (mesh_score, mesh_ideal_score))
def test_split_score(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
cmap = Mesh(nodes, faces)
- split_edge_ids(cmap, 0, 2)
- split_edge_ids(cmap, 1, 2) # split impossible
- nodes_score, mesh_score, mesh_ideal_score, adjacency = GMA.global_score(cmap)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ split_edge_ids(m_analysis, 0, 2)
+ split_edge_ids(m_analysis, 1, 4) # split impossible
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = m_analysis.global_score()
self.assertEqual((3, 1), (mesh_score, mesh_ideal_score))
def test_find_template_opposite_node_not_found(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
cmap = Mesh(nodes, faces)
+ m_analysis = TriMeshQualityAnalysis(cmap)
dart_to_test = Dart(cmap, 0)
- node = TMA.find_template_opposite_node(dart_to_test)
+ node = m_analysis.find_template_opposite_node(dart_to_test)
self.assertEqual(node, None)
dart_to_test = Dart(cmap, 2)
- node = TMA.find_template_opposite_node(dart_to_test)
+ node = m_analysis.find_template_opposite_node(dart_to_test)
self.assertEqual(node, 3)
def test_is_valid_action(self):
@@ -63,102 +66,320 @@ def test_is_valid_action(self):
[3, 4, 5], [3, 5, 6], [3, 6, 7], [7, 6, 8], [7, 8, 9], [7, 9, 10], [10, 9, 11], [10, 11, 12],
[14, 12, 13], [14, 13, 15], [1, 14, 15], [1, 15, 16], [1, 16, 17], [1, 17, 2], [2, 17, 18], [2, 18, 4]]
cmap = Mesh(nodes, faces)
- split_edge_ids(cmap, 0, 1)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ split_edge_ids(m_analysis, 0, 1)
#Boundary dart
- self.assertEqual(TMA.isValidAction(cmap, 25, 0), (False, True))
+ self.assertEqual(m_analysis.isValidAction(25, 0), (False, True))
# Flip test
- self.assertEqual(TMA.isValidAction(cmap, 3, 0), (True, True))
- self.assertEqual(TMA.isValidAction(cmap, 0, 0), (False, True))
+ self.assertEqual(m_analysis.isValidAction(3, 0), (True, True))
+ self.assertEqual(m_analysis.isValidAction(0, 0), (True, False))
#Split test
- self.assertEqual(TMA.isValidAction(cmap, 0, 1), (True, True))
- split_edge_ids(cmap, 1, 19)
- split_edge_ids(cmap, 1, 20)
- self.assertEqual(TMA.isValidAction(cmap, 20, 1), (True, False))
- split_edge_ids(cmap, 0, 19)
- split_edge_ids(cmap, 0, 22)
- split_edge_ids(cmap, 0, 23)
- self.assertEqual(TMA.isValidAction(cmap, 20, 1), (False, True))
+ self.assertEqual(m_analysis.isValidAction(0, 1), (True, True))
+ split_edge_ids(m_analysis, 1, 19)
+ split_edge_ids(m_analysis, 1, 20)
+ plot_mesh(m_analysis.mesh)
+ self.assertEqual(m_analysis.isValidAction(20, 1), (True, True))
+ split_edge_ids(m_analysis, 0, 19)
+ split_edge_ids(m_analysis, 0, 22)
+ split_edge_ids(m_analysis, 0, 23)
+ plot_mesh(m_analysis.mesh)
+ self.assertEqual(m_analysis.isValidAction(20, 1), (False, True)) #node n2 and n14 degree are >= 10
#Collapse test
- self.assertEqual(TMA.isValidAction(cmap, 20, 2), (True, True))
+ self.assertEqual(m_analysis.isValidAction(20, 2), (True, True))
+ self.assertEqual(m_analysis.isValidAction(2, 2), (False, False))
+
+ #All action test
+ self.assertEqual(m_analysis.isValidAction(2, 3), (False, False))
+ self.assertEqual(m_analysis.isValidAction(26, 3), (False, False))
+ self.assertEqual(m_analysis.isValidAction(9, 3), (True, True))
+
+ #One action test
+ self.assertEqual(m_analysis.isValidAction(0, 4), (True, True))
+ self.assertEqual(m_analysis.isValidAction(9, 4), (True, True))
+ self.assertEqual(m_analysis.isValidAction(46, 4), (False, True))
+
+ def test_isFlipOk(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
+ cmap = Mesh(nodes, faces)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ dart_to_test = Dart(cmap, 0)
+ self.assertFalse(m_analysis.isFlipOk(dart_to_test)[0])
+ dart_to_test = Dart(cmap, 2)
+ self.assertTrue(m_analysis.isFlipOk(dart_to_test)[0])
+
+ def test_isSplitOk(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
+ cmap = Mesh(nodes, faces)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ dart_to_test = Dart(cmap, 0)
+ self.assertEqual(m_analysis.isSplitOk(dart_to_test), (False, True))
+ dart_to_test = Dart(cmap, 2)
+ self.assertEqual(m_analysis.isSplitOk(dart_to_test), (True, True))
+
+ def test_isCollapseOk(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
+ cmap = Mesh(nodes, faces)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ dart_to_test = Dart(cmap, 0)
+ self.assertFalse(m_analysis.isCollapseOk(dart_to_test)[0])
+ dart_to_test = Dart(cmap, 2)
+ self.assertFalse(m_analysis.isCollapseOk(dart_to_test)[0])
+
+ split_edge_ids(m_analysis, 0, 2)
+ split_edge_ids(m_analysis, 0, 5)
+ dart_to_test = Dart(cmap, 12)
+ self.assertTrue(m_analysis.isCollapseOk(dart_to_test)[0])
+
+ def test_isTruncated(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0]]
+ faces = [[0, 1, 2]]
+ cmap = Mesh(nodes, faces)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ darts_list = []
+ for d_info in cmap.active_darts():
+ darts_list.append(d_info[0])
+ self.assertTrue(m_analysis.isTruncated(darts_list))
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
+ cmap = Mesh(nodes, faces)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ darts_list = []
+ for d_info in cmap.active_darts():
+ darts_list.append(d_info[0])
+ self.assertFalse(m_analysis.isTruncated(darts_list))
+
+ def test_get_geometric_quality(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2], [0, 1, 4], [0, 4, 1]]
+ cmap = Mesh(nodes, faces)
plot_mesh(cmap)
- self.assertEqual(TMA.isValidAction(cmap, 2, 2), (False, True))
+ m_analysis = TriMeshQualityAnalysis(cmap)
+
+ # Half flat
+ d_to_test = Dart(cmap, 0)
+ self.assertEqual(m_analysis.get_dart_geometric_quality(d_to_test), 4)
+
+ # Full flat
+ d_to_test = Dart(cmap, 11)
+ self.assertEqual(m_analysis.get_dart_geometric_quality(d_to_test), 6)
+
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]
+ faces = [[0, 1, 2], [2, 1, 3]]
+ cmap = Mesh(nodes, faces)
+ plot_mesh(cmap)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+
+ # Crossed
+ d_to_test = Dart(cmap, 1)
+ self.assertEqual(m_analysis.get_dart_geometric_quality(d_to_test), 3)
+
+ def test_find_star_vertex(self):
+ # Polygon with ker
+ nodes = [[0.0, 0.0], [1.0, 1.0], [1.0, -1.0], [0.0, -2.0], [-1.0, 0.0], [-0.5, 0.5], [-0.25, -0.25]]
+ faces = [[0, 2, 1], [0, 3, 2], [0, 4, 3], [0, 5, 4], [0, 1, 5]]
+ cmap = Mesh(nodes, faces)
+ plot_mesh(cmap)
+ m_analysis = TriMeshQualityAnalysis(cmap)
+ n_to_test = Node(cmap, 0)
+ self.assertTrue(m_analysis.find_star_vertex(n_to_test)[0])
+
+
+class TestMeshOldAnalysis(unittest.TestCase):
+
+ def test_mesh_regular_score(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [0.5, 1], [-0.5, 1.0], [0.0, 2.0], [-1.0,0.0],[-0.5,-1.0],[0.0,-2.0], [0.5,-1.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [3, 2, 4], [3, 5, 0], [0, 5, 6], [0, 6, 8], [6, 7, 8], [0, 8, 1]]
+ cmap = Mesh(nodes,faces)
+ tma = TriMeshOldAnalysis(cmap)
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = tma.global_score()
+ self.assertEqual((0,0), (mesh_score, mesh_ideal_score) )
+
+ def test_mesh_with_irregularities(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [0.5, 1], [-0.5, 1.0], [0.0, 2.0], [-1.0, 2.0], [-2.0, 1.0], [-1.0, 0.0],
+ [-2.0, 0.0], [-2.0, -1.0], [-0.5, -1.0], [-1.0, -2.0], [0.0, -2.0], [1.0, -2.0],
+ [0.5, -1.0], [2.0, -1.0], [2.0, 0.0], [2.0, 1.0], [1.0, 2.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [3, 2, 4], [7, 0, 3], [7, 10, 0], [10, 14, 0], [0, 14, 1], [10, 12, 14],
+ [3, 4, 5], [3, 5, 6], [3, 6, 7], [7, 6, 8], [7, 8, 9], [7, 9, 10], [10, 9, 11], [10, 11, 12],
+ [14, 12, 13], [14, 13, 15], [1, 14, 15], [1, 15, 16], [1, 16, 17], [1, 17, 2], [2, 17, 18], [2, 18, 4]]
+ cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = tma.global_score()
+ self.assertEqual((6, -2), (mesh_score,mesh_ideal_score) )
+
+ def test_mesh_bad_score(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
+ cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = tma.global_score()
+ self.assertEqual((3, 1), (mesh_score, mesh_ideal_score))
+
+ def test_split_score(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
+ cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
+ split_edge_ids(tma, 0, 2)
+ split_edge_ids(tma, 1, 2) # split impossible
+ nodes_score, mesh_score, mesh_ideal_score, adjacency = tma.global_score()
+ self.assertEqual((3, 1), (mesh_score, mesh_ideal_score))
+
+ def test_find_template_opposite_node_not_found(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
+ cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
+ dart_to_test = Dart(cmap, 0)
+ node = tma.find_template_opposite_node(dart_to_test)
+ self.assertEqual(node, None)
+ dart_to_test = Dart(cmap, 2)
+ node = tma.find_template_opposite_node(dart_to_test)
+ self.assertEqual(node, 3)
+
+ def test_is_valid_action(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [0.5, 1], [-0.5, 1.0], [0.0, 2.0], [-1.0, 2.0], [-2.0, 1.0], [-1.0, 0.0],
+ [-2.0, 0.0], [-2.0, -1.0], [-0.5, -1.0], [-1.0, -2.0], [0.0, -2.0], [1.0, -2.0],
+ [0.5, -1.0], [2.0, -1.0], [2.0, 0.0], [2.0, 1.0], [1.0, 2.0]]
+ faces = [[0, 1, 2], [0, 2, 3], [3, 2, 4], [7, 0, 3], [7, 10, 0], [10, 14, 0], [0, 14, 1], [10, 12, 14],
+ [3, 4, 5], [3, 5, 6], [3, 6, 7], [7, 6, 8], [7, 8, 9], [7, 9, 10], [10, 9, 11], [10, 11, 12],
+ [14, 12, 13], [14, 13, 15], [1, 14, 15], [1, 15, 16], [1, 16, 17], [1, 17, 2], [2, 17, 18], [2, 18, 4]]
+ cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
+ split_edge_ids(tma, 0, 1)
+
+ #Boundary dart
+ self.assertEqual(tma.isValidAction( 25, 0), (False, True))
+
+ # Flip test
+ self.assertEqual(tma.isValidAction( 3, 0), (True, True))
+ self.assertEqual(tma.isValidAction(0, 0), (False, True))
+
+ #Split test
+ self.assertEqual(tma.isValidAction(0, 1), (True, True))
+ split_edge_ids(tma, 1, 19)
+ split_edge_ids(tma, 1, 20)
+ self.assertEqual(tma.isValidAction(20, 1), (True, False))
+ split_edge_ids(tma, 0, 19)
+ split_edge_ids(tma, 0, 22)
+ split_edge_ids(tma, 0, 23)
+ self.assertEqual(tma.isValidAction(20, 1), (False, True))
+
+ #Collapse test
+ self.assertEqual(tma.isValidAction(20, 2), (True, True))
+ plot_mesh(cmap)
+ self.assertEqual(tma.isValidAction(2, 2), (False, True))
#All action test
- self.assertEqual(TMA.isValidAction(cmap, 2, 3), (False, False))
- self.assertEqual(TMA.isValidAction(cmap, 26, 3), (False, False))
- self.assertEqual(TMA.isValidAction(cmap, 9, 3), (True, True))
+ self.assertEqual(tma.isValidAction(2, 3), (False, False))
+ self.assertEqual(tma.isValidAction(26, 3), (False, False))
+ self.assertEqual(tma.isValidAction(9, 3), (True, True))
#One action test
- self.assertEqual(TMA.isValidAction(cmap, 0, 4), (True, True))
- self.assertEqual(TMA.isValidAction(cmap, 9, 4), (True, True))
- self.assertEqual(TMA.isValidAction(cmap, 94, 4), (False, False))
+ self.assertEqual(tma.isValidAction(0, 4), (True, True))
+ self.assertEqual(tma.isValidAction(9, 4), (True, True))
+ self.assertEqual(tma.isValidAction(94, 4), (False, False))
def test_isFlipOk(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
plot_mesh(cmap)
dart_to_test = Dart(cmap, 0)
- self.assertFalse(TMA.isFlipOk(dart_to_test)[0])
+ self.assertFalse(tma.isFlipOk(dart_to_test)[0])
dart_to_test = Dart(cmap, 2)
- self.assertTrue(TMA.isFlipOk(dart_to_test))
+ self.assertTrue(tma.isFlipOk(dart_to_test))
def test_isSplitOk(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
plot_mesh(cmap)
dart_to_test = Dart(cmap, 0)
- self.assertEqual(TMA.isSplitOk(dart_to_test), (False, True))
+ self.assertEqual(tma.isSplitOk(dart_to_test), (False, True))
dart_to_test = Dart(cmap, 2)
- self.assertEqual(TMA.isSplitOk(dart_to_test), (True, True))
+ self.assertEqual(tma.isSplitOk(dart_to_test), (True, True))
def test_isCollapseOk(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
plot_mesh(cmap)
dart_to_test = Dart(cmap, 0)
- self.assertFalse(TMA.isCollapseOk(dart_to_test)[0])
+ self.assertFalse(tma.isCollapseOk(dart_to_test)[0])
dart_to_test = Dart(cmap, 2)
- self.assertFalse(TMA.isCollapseOk(dart_to_test)[0])
+ self.assertFalse(tma.isCollapseOk(dart_to_test)[0])
+ split_edge_ids(tma,2,1)
+ split_edge_ids(tma, 1, 5)
+ dart_to_test = Dart(cmap, 17)
+ self.assertTrue(tma.isCollapseOk(dart_to_test)[0])
def test_valid_triangle(self):
+ nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0]]
+ faces = [[0, 1, 2]]
+ cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
+
# test Lmax invalid
vect_AB = (5.0, 0.0)
vect_AC = (2.5, 5.0)
vect_BC = (-2.5, 5.0)
- self.assertFalse(TMA.valid_triangle(vect_AB, vect_AC, vect_BC))
+ self.assertFalse(tma.valid_triangle(vect_AB, vect_AC, vect_BC))
# test invalid angles
vect_AB = (3.0, 0.0)
vect_AC = (1.5, 0.05)
vect_BC = (-1.5, 0.05)
- self.assertFalse(TMA.valid_triangle(vect_AB, vect_AC, vect_BC))
+ self.assertFalse(tma.valid_triangle(vect_AB, vect_AC, vect_BC))
# test valid triangle
vect_AB = (3.0, 0.0)
vect_AC = (1.5, 3.0)
vect_BC = (-1.5, 3.0)
- self.assertTrue(TMA.valid_triangle(vect_AB, vect_AC, vect_BC))
+ self.assertTrue(tma.valid_triangle(vect_AB, vect_AC, vect_BC))
def test_isTruncated(self):
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0]]
faces = [[0, 1, 2]]
cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
darts_list = []
for d_info in cmap.active_darts():
darts_list.append(d_info[0])
- self.assertTrue(TMA.isTruncated(cmap, darts_list))
+ self.assertTrue(tma.isTruncated(darts_list))
nodes = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0], [2.0, 0.0]]
faces = [[0, 1, 2], [0, 2, 3], [1, 4, 2]]
cmap = Mesh(nodes, faces)
+ tma = TriMeshOldAnalysis(cmap)
darts_list = []
for d_info in cmap.active_darts():
darts_list.append(d_info[0])
- self.assertFalse(TMA.isTruncated(cmap, darts_list))
+ self.assertFalse(tma.isTruncated(darts_list))
if __name__ == '__main__':
unittest.main()
+
+
+ # def test_valid_triangle(self):
+ # # test Lmax invalid
+ # vect_AB = (5.0, 0.0)
+ # vect_AC = (2.5, 5.0)
+ # vect_BC = (-2.5, 5.0)
+ # self.assertFalse(m_analysis.valid_triangle(vect_AB, vect_AC, vect_BC))
+ # # test invalid angles
+ # vect_AB = (3.0, 0.0)
+ # vect_AC = (1.5, 0.05)
+ # vect_BC = (-1.5, 0.05)
+ # self.assertFalse(m_analysis.valid_triangle(vect_AB, vect_AC, vect_BC))
+ # # test valid triangle
+ # vect_AB = (3.0, 0.0)
+ # vect_AC = (1.5, 3.0)
+ # vect_BC = (-1.5, 3.0)
+ # self.assertTrue(m_analysis.valid_triangle(vect_AB, vect_AC, vect_BC))
diff --git a/training/config_PPO_SB3.yaml b/training/config/quadmesh_config_PPO_SB3.yaml
similarity index 76%
rename from training/config_PPO_SB3.yaml
rename to training/config/quadmesh_config_PPO_SB3.yaml
index 254798b..9a1d4d4 100644
--- a/training/config_PPO_SB3.yaml
+++ b/training/config/quadmesh_config_PPO_SB3.yaml
@@ -1,5 +1,5 @@
project_name : "Quadmesh"
-experiment_name : "test"
+experiment_name : "TEST"
description : ""
total_timesteps : 10000
@@ -7,7 +7,9 @@ total_timesteps : 10000
paths:
log_dir : "training/results/quad-sb3/"
policy_saving_dir : "training/policy_saved/quad-sb3/"
- wandb_model_saving_dir : "training/wandb_models/"
+ wandb_model_saving_dir : "training/wandb_models/quad-sb3/"
+ episode_recording_dir: "training/results/quad-sb3/episode_recording/"
+ observation_counts_dir: "training/results/quad-sb3/observation_counts/"
dataset:
evaluation_mesh_file_path : "mesh_files/simple_quad.msh"
@@ -27,6 +29,7 @@ env:
reward_function : 0 # 0 if basics, 1 if penalize, 2 otherwise
render_mode : null
obs_count : true
+ analysis_type : "old"
ppo:
policy : MlpPolicy
@@ -46,9 +49,9 @@ eval:
n_darts_selected: 10
deep: 12
obs_size: 120
- render_mode: "human"
+ render_mode: null
action_restriction: false
- with_degree_observation: false
+ with_quality_observation: false
metrics:
diff --git a/training/config_PPO_perso.yaml b/training/config/quadmesh_config_PPO_perso.yaml
similarity index 68%
rename from training/config_PPO_perso.yaml
rename to training/config/quadmesh_config_PPO_perso.yaml
index 5e946dc..3b374ed 100644
--- a/training/config_PPO_perso.yaml
+++ b/training/config/quadmesh_config_PPO_perso.yaml
@@ -1,11 +1,13 @@
project_name : "Quadmesh"
-experiment_name : "random_basic_quad_test_config-TEST"
+experiment_name : "TEST"
description : ""
paths:
log_dir : "training/results/quad-perso/"
policy_saving_dir : "training/policy_saved/quad-perso/"
- wandb_model_saving_dir : "training/wandb_models/"
+ wandb_model_saving_dir : "training/wandb_models/quad-perso/"
+ episode_recording_dir: "training/results/quad-perso/episode_recording/"
+ observation_counts_dir: "training/results/quad-perso/observation_counts/"
dataset:
evaluation_mesh_file_path : "mesh_files/simple_quad.msh"
@@ -24,10 +26,12 @@ env:
reward_function : 0 # 0 if basics, 1 if penalize, 2 otherwise
render_mode: null
obs_count: true
+ analysis_type : "old"
ppo:
- n_iterations : 5
- n_episodes_per_iteration : 50
+ n_actions : 4
+ n_iterations : 2
+ n_episodes_per_iteration : 20
n_epochs : 5
batch_size: 64
learning_rate : 0.0001
diff --git a/training/exploit.py b/training/exploit.py
deleted file mode 100644
index 8f02119..0000000
--- a/training/exploit.py
+++ /dev/null
@@ -1,31 +0,0 @@
-import mesh_model.random_trimesh as TM
-import torch
-from environment.trimesh_env import TriMesh
-from model_RL.utilities.actor_critic_networks import Actor
-
-from view.mesh_plotter.create_plots import plot_test_results
-from view.mesh_plotter.mesh_plots import plot_dataset
-
-from model_RL.evaluate_model import testPolicy
-
-LOCAL_MESH_FEAT = 0
-
-
-def exploit():
- mesh_size = 12
- feature = LOCAL_MESH_FEAT
-
- dataset = [TM.random_mesh(30) for _ in range(9)]
- plot_dataset(dataset)
-
- env = TriMesh(None, mesh_size, max_steps=60, feat=feature)
-
-
- actor = Actor(env, 30, 15, lr=0.0001)
- actor.load_state_dict(torch.load('policy_saved/actor_network.pth'))
-
- avg_steps, avg_wins, avg_rewards, final_meshes = testPolicy(actor, 30, dataset, 100)
-
- if avg_steps is not None:
- plot_test_results(avg_rewards, avg_wins, avg_steps)
- plot_dataset(final_meshes)
diff --git a/training/exploit_PPO_perso.py b/training/exploit_PPO_perso.py
index 7355785..275bee7 100644
--- a/training/exploit_PPO_perso.py
+++ b/training/exploit_PPO_perso.py
@@ -1,36 +1,42 @@
-from numpy import ndarray
-
-import gymnasium as gym
import json
import torch
+import copy
+import numpy as np
+import gymnasium as gym
+import yaml
+
+from tqdm import tqdm
+from numpy import ndarray
from torch.distributions import Categorical
-from model_RL.PPO_model_pers import Actor
-from mesh_model.mesh_analysis.global_mesh_analysis import global_score
+from mesh_model.mesh_analysis.quadmesh_analysis import QuadMeshOldAnalysis
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshOldAnalysis, TriMeshQualityAnalysis
+from mesh_model.mesh_struct.mesh_elements import Dart
from mesh_model.mesh_struct.mesh import Mesh
from mesh_model.reader import read_gmsh
+from model_RL.PPO_model_pers import Actor
+
from view.mesh_plotter.create_plots import plot_test_results
from view.mesh_plotter.mesh_plots import plot_dataset
from environment.actions.smoothing import smoothing_mean
-import mesh_model.random_quadmesh as QM
+
from environment.gymnasium_envs.quadmesh_env.envs.quadmesh import QuadMeshEnv
-import numpy as np
-import copy
-from tqdm import tqdm
+from environment.gymnasium_envs.trimesh_full_env.envs.trimesh import TriMeshEnvFull
+import mesh_model.random_quadmesh as QM
def testPolicy(
actor,
n_eval_episodes: int,
- env_config,
+ config,
dataset: list[Mesh]
) -> tuple[ndarray, ndarray, ndarray, ndarray, list[Mesh]]:
"""
Tests policy on each mesh of a dataset with n_eval_episodes.
- :param policy: the policy to test
+ :param actor: the policy to test
:param n_eval_episodes: number of evaluation episodes on each mesh
+ :param config: configuration
:param dataset: list of mesh objects
- :param max_steps: max steps to evaluate
:return: average length of evaluation episodes, number of wins,average reward per mesh, dataset with the modified meshes
"""
print('Testing policy')
@@ -42,14 +48,15 @@ def testPolicy(
for i, mesh in tqdm(enumerate(dataset, 1)):
best_mesh = mesh
env = gym.make(
- env_config["env_name"],
- max_episode_steps=30,
- mesh = mesh,
- n_darts_selected=env_config["n_darts_selected"],
- deep= env_config["deep"],
- action_restriction=env_config["action_restriction"],
- with_degree_obs=env_config["with_degree_observation"],
- render_mode="human"
+ config["env"]["env_id"],
+ max_episode_steps=config["env"]["max_episode_steps"],
+ mesh=mesh,
+ #mesh_size = 30,
+ n_darts_selected=config["env"]["n_darts_selected"],
+ deep=config["env"]["deep"],
+ action_restriction=config["env"]["action_restriction"],
+ with_quality_obs=config["env"]["with_quality_observation"],
+ render_mode=config["env"]["render_mode"],
)
for _ in range(n_eval_episodes):
terminated = False
@@ -63,8 +70,8 @@ def testPolicy(
dist = Categorical(pmf)
action = dist.sample()
action = action.tolist()
- action_dart = int(action / 4)
- action_type = action % 4
+ action_dart = int(action / config["ppo"]["n_actions"])
+ action_type = action % config["ppo"]["n_actions"]
gymnasium_action = [action_type, action_dart]
if action is None:
env.terminal = True
@@ -74,7 +81,7 @@ def testPolicy(
ep_length += 1
if terminated:
nb_wins[i-1] += 1
- if isBetterMesh(best_mesh, info['mesh']):
+ if isBetterMesh(best_mesh, info['mesh'], config["env"]["analysis_type"]):
best_mesh = copy.deepcopy(info['mesh'])
avg_length[i-1] += ep_length
avg_mesh_rewards[i-1] += ep_mesh_rewards
@@ -90,8 +97,27 @@ def isBetterPolicy(actual_best_policy, policy_to_test):
if actual_best_policy is None:
return True
-def isBetterMesh(best_mesh, actual_mesh):
- if best_mesh is None or global_score(best_mesh)[1] > global_score(actual_mesh)[1]:
+def isBetterMesh(best_mesh, actual_mesh, analysis_type):
+ tri = False
+ for d_info in actual_mesh.dart_info:
+ if d_info[0]>=0:
+ d = Dart(actual_mesh, d_info[0])
+ if d == ((d.get_beta(1)).get_beta(1)).get_beta(1):
+ tri = True
+ else:
+ tri = False
+ break
+ if tri:
+ if analysis_type == "old":
+ ma_best_mesh = TriMeshOldAnalysis(best_mesh)
+ ma_actual_mesh = TriMeshOldAnalysis(actual_mesh)
+ else:
+ ma_best_mesh = TriMeshQualityAnalysis(best_mesh)
+ ma_actual_mesh = TriMeshQualityAnalysis(actual_mesh)
+ else:
+ ma_best_mesh = QuadMeshOldAnalysis(best_mesh)
+ ma_actual_mesh = QuadMeshOldAnalysis(actual_mesh)
+ if best_mesh is None or ma_best_mesh.global_score()[1] > ma_actual_mesh.global_score()[1]:
return True
else:
return False
@@ -99,28 +125,29 @@ def isBetterMesh(best_mesh, actual_mesh):
if __name__ == '__main__':
-
#Create a dataset of 9 meshes
- mesh = read_gmsh("../mesh_files/medium_quad.msh")
+ mesh = read_gmsh("../mesh_files/t1_tri.msh")
dataset = [mesh for _ in range(9)]
- with open("../environment/environment_config.json", "r") as f:
- env_config = json.load(f)
+ with open("../training/config/trimesh_config_PPO_perso.yaml", "r") as f:
+ config = yaml.safe_load(f)
plot_dataset(dataset)
env = gym.make(
- env_config["env_name"],
+ config["env"]["env_id"],
+ max_episode_steps=config["env"]["max_episode_steps"],
mesh=mesh,
- max_episode_steps=env_config["max_episode_steps"],
- n_darts_selected=env_config["n_darts_selected"],
- deep=env_config["deep"],
- action_restriction=env_config["action_restriction"],
- with_degree_obs=env_config["with_degree_observation"]
+ # mesh_size = 30,
+ n_darts_selected=config["env"]["n_darts_selected"],
+ deep=config["env"]["deep"],
+ action_restriction=config["env"]["action_restriction"],
+ with_quality_obs=config["env"]["with_quality_observation"],
+ render_mode=config["env"]["render_mode"],
)
#Load the model
- actor = Actor(env, 10*8, 4*10, lr=0.0001)
- actor.load_state_dict(torch.load('policy_saved/quad-perso/medium_quad_perso-2.pth'))
- avg_steps, avg_wins, avg_rewards, normalized_return, final_meshes = testPolicy(actor, 15, env_config, dataset)
+ actor = Actor(env, config["env"]["obs_size"], config["ppo"]["n_actions"], n_darts_observed=config["env"]["n_darts_selected"], lr=0.0001)
+ actor.load_state_dict(torch.load('policy_saved/tri-perso/TEST-Exploit.pth'))
+ avg_steps, avg_wins, avg_rewards, normalized_return, final_meshes = testPolicy(actor, 15, config, dataset)
plot_test_results(avg_rewards, avg_wins, avg_steps, normalized_return)
plot_dataset(final_meshes)
diff --git a/training/exploit_SB3_policy.py b/training/exploit_SB3_policy.py
index 132f234..15ebcf2 100644
--- a/training/exploit_SB3_policy.py
+++ b/training/exploit_SB3_policy.py
@@ -1,5 +1,5 @@
import copy
-import json
+import yaml
import gymnasium as gym
import numpy as np
@@ -8,15 +8,23 @@
from numpy import ndarray
from stable_baselines3 import PPO
-from mesh_model.mesh_analysis.global_mesh_analysis import global_score
+from environment.actions.triangular_actions import flip_edge
+from mesh_model.mesh_analysis.global_mesh_analysis import GlobalMeshAnalysis
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshOldAnalysis
+from mesh_model.mesh_analysis.quadmesh_analysis import QuadMeshOldAnalysis
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshQualityAnalysis
from mesh_model.mesh_struct.mesh import Mesh
+from mesh_model.mesh_struct.mesh_elements import Dart
+from mesh_model.random_trimesh import random_mesh, regular_mesh
+from environment.actions.triangular_actions import flip_edge_ids, split_edge_ids
from mesh_model.reader import read_gmsh
from view.mesh_plotter.create_plots import plot_test_results
-from view.mesh_plotter.mesh_plots import plot_dataset
+from view.mesh_plotter.mesh_plots import plot_dataset, plot_mesh
from environment.actions.smoothing import smoothing_mean
-import mesh_model.random_quadmesh as QM
-from environment.gymnasium_envs.quadmesh_env.envs.quadmesh import QuadMeshEnv
+from environment.gymnasium_envs import trimesh_full_env
+
+
def testPolicy(
model,
@@ -42,12 +50,13 @@ def testPolicy(
best_mesh = mesh
env = gym.make(
config["eval"]["eval_env_id"],
- max_episode_steps=20,
+ max_episode_steps=config["eval"]["max_episode_steps"],
mesh = mesh,
+ #mesh_size = 30,
n_darts_selected=config["eval"]["n_darts_selected"],
deep= config["eval"]["deep"],
action_restriction=config["eval"]["action_restriction"],
- with_degree_obs=config["eval"]["with_degree_observation"],
+ with_degree_obs=config["eval"]["with_quality_observation"],
render_mode = config["eval"]["render_mode"],
)
for _ in range(n_eval_episodes):
@@ -66,7 +75,7 @@ def testPolicy(
ep_length += 1
if terminated:
nb_wins[i-1] += 1
- if isBetterMesh(best_mesh, info['mesh']):
+ if isBetterMesh(best_mesh, info['mesh'], config["env"]["analysis_type"]):
best_mesh = copy.deepcopy(info['mesh'])
avg_length[i-1] += ep_length
avg_mesh_rewards[i-1] += ep_mesh_rewards
@@ -82,25 +91,50 @@ def isBetterPolicy(actual_best_policy, policy_to_test):
if actual_best_policy is None:
return True
-def isBetterMesh(best_mesh, actual_mesh):
- if best_mesh is None or global_score(best_mesh)[1] > global_score(actual_mesh)[1]:
+def isBetterMesh(best_mesh, actual_mesh, analysis_type):
+ tri = False
+ for d_info in actual_mesh.dart_info:
+ if d_info[0]>=0:
+ d = Dart(actual_mesh, d_info[0])
+ if d == ((d.get_beta(1)).get_beta(1)).get_beta(1):
+ tri = True
+ else:
+ tri = False
+ break
+ if tri:
+ if analysis_type == "old":
+ ma_best_mesh = TriMeshOldAnalysis(best_mesh)
+ ma_actual_mesh = TriMeshOldAnalysis(actual_mesh)
+ else:
+ ma_best_mesh = TriMeshQualityAnalysis(best_mesh)
+ ma_actual_mesh = TriMeshQualityAnalysis(actual_mesh)
+ else:
+ ma_best_mesh = QuadMeshOldAnalysis(best_mesh)
+ ma_actual_mesh = QuadMeshOldAnalysis(actual_mesh)
+ if best_mesh is None or ma_best_mesh.global_score()[1] > ma_actual_mesh.global_score()[1]:
return True
else:
return False
if __name__ == '__main__':
-
#Create a dataset of 9 meshes
- mesh = read_gmsh("../mesh_files/medium_quad.msh")
- dataset = [mesh for _ in range(9)]
- with open("../environment/environment_config.json", "r") as f:
- env_config = json.load(f)
+ mesh = read_gmsh("../mesh_files/tri-star.msh")
+ # ma = TriMeshQualityAnalysis(mesh)
+ # split_edge_ids(ma, 5, 2)
+ # split_edge_ids(ma, 2, 10)
+ # flip_edge_ids(ma, 3,7)
+ # #plot_mesh(mesh)
+
+ dataset = [mesh for _ in range(1)]
+ # PARAMETERS CONFIGURATION
+ with open("../training/config/trimesh_config_PPO_SB3.yaml", "r") as f:
+ config = yaml.safe_load(f)
plot_dataset(dataset)
#Load the model
- model = PPO.load("policy_saved/quad/4-actions-quad-simple-PPO43.zip")
- avg_steps, avg_wins, avg_rewards, avg_normalized_return, final_meshes = testPolicy(model, 1, env_config, dataset)
+ model = PPO.load("policy_saved/tri-sb3/PPO_SB3_tri-delaunay-v0.zip")
+ avg_steps, avg_wins, avg_rewards, avg_normalized_return, final_meshes = testPolicy(model, 1, config, dataset)
plot_test_results(avg_rewards, avg_wins, avg_steps, avg_normalized_return)
plot_dataset(final_meshes)
diff --git a/training/exploit_trimesh.py b/training/exploit_trimesh.py
index b8c323f..4cd2c80 100644
--- a/training/exploit_trimesh.py
+++ b/training/exploit_trimesh.py
@@ -2,8 +2,8 @@
import torch
import json
import gymnasium as gym
-from environment.trimesh_env import TriMesh
-from model_RL.utilities.actor_critic_networks import Actor
+from environment.old_files.trimesh_env import TriMesh
+from model_RL.old_files.utilities import Actor
from mesh_model.reader import read_gmsh
from view.mesh_plotter.create_plots import plot_test_results
from view.mesh_plotter.mesh_plots import plot_dataset
@@ -39,7 +39,7 @@ def exploit():
#Create a dataset of 9 meshes
dataset = [mesh for _ in range(9)]
- with open("../environment/environment_config.json", "r") as f:
+ with open("../environment/old_files/environment_config.json", "r") as f:
env_config = json.load(f)
plot_dataset(dataset)
diff --git a/training/results/trimesh_results/FLIP/PPO_10/events.out.tfevents.1735828642.UN00315924-UNAL.dam.intra.cea.fr.292560.0 b/training/results/0-trimesh_results/FLIP/PPO_10/events.out.tfevents.1735828642.UN00315924-UNAL.dam.intra.cea.fr.292560.0
similarity index 100%
rename from training/results/trimesh_results/FLIP/PPO_10/events.out.tfevents.1735828642.UN00315924-UNAL.dam.intra.cea.fr.292560.0
rename to training/results/0-trimesh_results/FLIP/PPO_10/events.out.tfevents.1735828642.UN00315924-UNAL.dam.intra.cea.fr.292560.0
diff --git a/training/results/trimesh_results/FLIP/PPO_9/events.out.tfevents.1735828526.UN00315924-UNAL.dam.intra.cea.fr.291743.0 b/training/results/0-trimesh_results/FLIP/PPO_9/events.out.tfevents.1735828526.UN00315924-UNAL.dam.intra.cea.fr.291743.0
similarity index 100%
rename from training/results/trimesh_results/FLIP/PPO_9/events.out.tfevents.1735828526.UN00315924-UNAL.dam.intra.cea.fr.291743.0
rename to training/results/0-trimesh_results/FLIP/PPO_9/events.out.tfevents.1735828526.UN00315924-UNAL.dam.intra.cea.fr.291743.0
diff --git a/training/results/trimesh_results/e1/PPO_restricted-v0/events.out.tfevents.1734431836.UN00315924-UNAL.dam.intra.cea.fr.757470.0 b/training/results/0-trimesh_results/e1/PPO_restricted-v0/events.out.tfevents.1734431836.UN00315924-UNAL.dam.intra.cea.fr.757470.0
similarity index 100%
rename from training/results/trimesh_results/e1/PPO_restricted-v0/events.out.tfevents.1734431836.UN00315924-UNAL.dam.intra.cea.fr.757470.0
rename to training/results/0-trimesh_results/e1/PPO_restricted-v0/events.out.tfevents.1734431836.UN00315924-UNAL.dam.intra.cea.fr.757470.0
diff --git a/training/results/trimesh_results/e1/PPO_restricted-v1/events.out.tfevents.1734514338.UN00315924-UNAL.dam.intra.cea.fr.70489.0 b/training/results/0-trimesh_results/e1/PPO_restricted-v1/events.out.tfevents.1734514338.UN00315924-UNAL.dam.intra.cea.fr.70489.0
similarity index 100%
rename from training/results/trimesh_results/e1/PPO_restricted-v1/events.out.tfevents.1734514338.UN00315924-UNAL.dam.intra.cea.fr.70489.0
rename to training/results/0-trimesh_results/e1/PPO_restricted-v1/events.out.tfevents.1734514338.UN00315924-UNAL.dam.intra.cea.fr.70489.0
diff --git a/training/results/trimesh_results/e1/PPO_restricted-v2/events.out.tfevents.1734517568.UN00315924-UNAL.dam.intra.cea.fr.83005.0 b/training/results/0-trimesh_results/e1/PPO_restricted-v2/events.out.tfevents.1734517568.UN00315924-UNAL.dam.intra.cea.fr.83005.0
similarity index 100%
rename from training/results/trimesh_results/e1/PPO_restricted-v2/events.out.tfevents.1734517568.UN00315924-UNAL.dam.intra.cea.fr.83005.0
rename to training/results/0-trimesh_results/e1/PPO_restricted-v2/events.out.tfevents.1734517568.UN00315924-UNAL.dam.intra.cea.fr.83005.0
diff --git a/training/results/trimesh_results/e1/PPO_unrestricted-v0/events.out.tfevents.1734431823.UN00315924-UNAL.dam.intra.cea.fr.757302.0 b/training/results/0-trimesh_results/e1/PPO_unrestricted-v0/events.out.tfevents.1734431823.UN00315924-UNAL.dam.intra.cea.fr.757302.0
similarity index 100%
rename from training/results/trimesh_results/e1/PPO_unrestricted-v0/events.out.tfevents.1734431823.UN00315924-UNAL.dam.intra.cea.fr.757302.0
rename to training/results/0-trimesh_results/e1/PPO_unrestricted-v0/events.out.tfevents.1734431823.UN00315924-UNAL.dam.intra.cea.fr.757302.0
diff --git a/training/results/trimesh_results/e1/PPO_unrestricted-v1/events.out.tfevents.1734513709.UN00315924-UNAL.dam.intra.cea.fr.67221.0 b/training/results/0-trimesh_results/e1/PPO_unrestricted-v1/events.out.tfevents.1734513709.UN00315924-UNAL.dam.intra.cea.fr.67221.0
similarity index 100%
rename from training/results/trimesh_results/e1/PPO_unrestricted-v1/events.out.tfevents.1734513709.UN00315924-UNAL.dam.intra.cea.fr.67221.0
rename to training/results/0-trimesh_results/e1/PPO_unrestricted-v1/events.out.tfevents.1734513709.UN00315924-UNAL.dam.intra.cea.fr.67221.0
diff --git a/training/results/trimesh_results/e1/PPO_unrestricted-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0 b/training/results/0-trimesh_results/e1/PPO_unrestricted-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
similarity index 100%
rename from training/results/trimesh_results/e1/PPO_unrestricted-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
rename to training/results/0-trimesh_results/e1/PPO_unrestricted-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
diff --git a/training/results/trimesh_results/e2/PPO_10-v0/events.out.tfevents.1734446254.UN00315924-UNAL.dam.intra.cea.fr.817111.0 b/training/results/0-trimesh_results/e2/PPO_10-v0/events.out.tfevents.1734446254.UN00315924-UNAL.dam.intra.cea.fr.817111.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_10-v0/events.out.tfevents.1734446254.UN00315924-UNAL.dam.intra.cea.fr.817111.0
rename to training/results/0-trimesh_results/e2/PPO_10-v0/events.out.tfevents.1734446254.UN00315924-UNAL.dam.intra.cea.fr.817111.0
diff --git a/training/results/trimesh_results/e2/PPO_10-v1/events.out.tfevents.1734553188.UN00315924-UNAL.dam.intra.cea.fr.173728.0 b/training/results/0-trimesh_results/e2/PPO_10-v1/events.out.tfevents.1734553188.UN00315924-UNAL.dam.intra.cea.fr.173728.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_10-v1/events.out.tfevents.1734553188.UN00315924-UNAL.dam.intra.cea.fr.173728.0
rename to training/results/0-trimesh_results/e2/PPO_10-v1/events.out.tfevents.1734553188.UN00315924-UNAL.dam.intra.cea.fr.173728.0
diff --git a/training/results/trimesh_results/e2/PPO_20-v0/events.out.tfevents.1734432461.UN00315924-UNAL.dam.intra.cea.fr.760588.0 b/training/results/0-trimesh_results/e2/PPO_20-v0/events.out.tfevents.1734432461.UN00315924-UNAL.dam.intra.cea.fr.760588.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_20-v0/events.out.tfevents.1734432461.UN00315924-UNAL.dam.intra.cea.fr.760588.0
rename to training/results/0-trimesh_results/e2/PPO_20-v0/events.out.tfevents.1734432461.UN00315924-UNAL.dam.intra.cea.fr.760588.0
diff --git a/training/results/trimesh_results/e2/PPO_20-v1/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0 b/training/results/0-trimesh_results/e2/PPO_20-v1/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_20-v1/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
rename to training/results/0-trimesh_results/e2/PPO_20-v1/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
diff --git a/training/results/trimesh_results/e2/PPO_30-v/events.out.tfevents.1734555115.UN00315924-UNAL.dam.intra.cea.fr.181453.0 b/training/results/0-trimesh_results/e2/PPO_30-v/events.out.tfevents.1734555115.UN00315924-UNAL.dam.intra.cea.fr.181453.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_30-v/events.out.tfevents.1734555115.UN00315924-UNAL.dam.intra.cea.fr.181453.0
rename to training/results/0-trimesh_results/e2/PPO_30-v/events.out.tfevents.1734555115.UN00315924-UNAL.dam.intra.cea.fr.181453.0
diff --git a/training/results/trimesh_results/e2/PPO_30-v0/events.out.tfevents.1734435261.UN00315924-UNAL.dam.intra.cea.fr.775239.0 b/training/results/0-trimesh_results/e2/PPO_30-v0/events.out.tfevents.1734435261.UN00315924-UNAL.dam.intra.cea.fr.775239.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_30-v0/events.out.tfevents.1734435261.UN00315924-UNAL.dam.intra.cea.fr.775239.0
rename to training/results/0-trimesh_results/e2/PPO_30-v0/events.out.tfevents.1734435261.UN00315924-UNAL.dam.intra.cea.fr.775239.0
diff --git a/training/results/trimesh_results/e2/PPO_30-v1/events.out.tfevents.1734559178.UN00315924-UNAL.dam.intra.cea.fr.195914.0 b/training/results/0-trimesh_results/e2/PPO_30-v1/events.out.tfevents.1734559178.UN00315924-UNAL.dam.intra.cea.fr.195914.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_30-v1/events.out.tfevents.1734559178.UN00315924-UNAL.dam.intra.cea.fr.195914.0
rename to training/results/0-trimesh_results/e2/PPO_30-v1/events.out.tfevents.1734559178.UN00315924-UNAL.dam.intra.cea.fr.195914.0
diff --git a/training/results/trimesh_results/e2/PPO_5-v0/events.out.tfevents.1734432449.UN00315924-UNAL.dam.intra.cea.fr.760459.0 b/training/results/0-trimesh_results/e2/PPO_5-v0/events.out.tfevents.1734432449.UN00315924-UNAL.dam.intra.cea.fr.760459.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_5-v0/events.out.tfevents.1734432449.UN00315924-UNAL.dam.intra.cea.fr.760459.0
rename to training/results/0-trimesh_results/e2/PPO_5-v0/events.out.tfevents.1734432449.UN00315924-UNAL.dam.intra.cea.fr.760459.0
diff --git a/training/results/trimesh_results/e2/PPO_5-v1/events.out.tfevents.1734552568.UN00315924-UNAL.dam.intra.cea.fr.170760.0 b/training/results/0-trimesh_results/e2/PPO_5-v1/events.out.tfevents.1734552568.UN00315924-UNAL.dam.intra.cea.fr.170760.0
similarity index 100%
rename from training/results/trimesh_results/e2/PPO_5-v1/events.out.tfevents.1734552568.UN00315924-UNAL.dam.intra.cea.fr.170760.0
rename to training/results/0-trimesh_results/e2/PPO_5-v1/events.out.tfevents.1734552568.UN00315924-UNAL.dam.intra.cea.fr.170760.0
diff --git a/training/results/trimesh_results/e3/PPO_8_deep3-v1/events.out.tfevents.1734611428.UN00315924-UNAL.dam.intra.cea.fr.278749.0 b/training/results/0-trimesh_results/e3/PPO_8_deep3-v1/events.out.tfevents.1734611428.UN00315924-UNAL.dam.intra.cea.fr.278749.0
similarity index 100%
rename from training/results/trimesh_results/e3/PPO_8_deep3-v1/events.out.tfevents.1734611428.UN00315924-UNAL.dam.intra.cea.fr.278749.0
rename to training/results/0-trimesh_results/e3/PPO_8_deep3-v1/events.out.tfevents.1734611428.UN00315924-UNAL.dam.intra.cea.fr.278749.0
diff --git a/training/results/trimesh_results/e3/PPO_deep12-v0/events.out.tfevents.1734598832.UN00315924-UNAL.dam.intra.cea.fr.221925.0 b/training/results/0-trimesh_results/e3/PPO_deep12-v0/events.out.tfevents.1734598832.UN00315924-UNAL.dam.intra.cea.fr.221925.0
similarity index 100%
rename from training/results/trimesh_results/e3/PPO_deep12-v0/events.out.tfevents.1734598832.UN00315924-UNAL.dam.intra.cea.fr.221925.0
rename to training/results/0-trimesh_results/e3/PPO_deep12-v0/events.out.tfevents.1734598832.UN00315924-UNAL.dam.intra.cea.fr.221925.0
diff --git a/training/results/trimesh_results/e3/PPO_deep12-v1/events.out.tfevents.1734606176.UN00315924-UNAL.dam.intra.cea.fr.253849.0 b/training/results/0-trimesh_results/e3/PPO_deep12-v1/events.out.tfevents.1734606176.UN00315924-UNAL.dam.intra.cea.fr.253849.0
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diff --git a/training/results/trimesh_results/e3/PPO_deep3-v0/events.out.tfevents.1734559585.UN00315924-UNAL.dam.intra.cea.fr.197662.0 b/training/results/0-trimesh_results/e3/PPO_deep3-v0/events.out.tfevents.1734559585.UN00315924-UNAL.dam.intra.cea.fr.197662.0
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diff --git a/training/results/trimesh_results/e3/PPO_deep3-v1/events.out.tfevents.1734606200.UN00315924-UNAL.dam.intra.cea.fr.254037.0 b/training/results/0-trimesh_results/e3/PPO_deep3-v1/events.out.tfevents.1734606200.UN00315924-UNAL.dam.intra.cea.fr.254037.0
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diff --git a/training/results/trimesh_results/e3/PPO_deep3-v2/events.out.tfevents.1734618832.UN00315924-UNAL.dam.intra.cea.fr.310315.0 b/training/results/0-trimesh_results/e3/PPO_deep3-v2/events.out.tfevents.1734618832.UN00315924-UNAL.dam.intra.cea.fr.310315.0
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diff --git a/training/results/trimesh_results/e3/PPO_deep6-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0 b/training/results/0-trimesh_results/e3/PPO_deep6-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
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diff --git a/training/results/trimesh_results/e4/PPO_no_deg-v0/events.out.tfevents.1735664190.UN00315924-UNAL.dam.intra.cea.fr.16322.0 b/training/results/0-trimesh_results/e4/PPO_no_deg-v0/events.out.tfevents.1735664190.UN00315924-UNAL.dam.intra.cea.fr.16322.0
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diff --git a/training/results/trimesh_results/e5/PPO_4/events.out.tfevents.1735770299.UN00315924-UNAL.dam.intra.cea.fr.132277.0 b/training/results/0-trimesh_results/e5/PPO_4/events.out.tfevents.1735770299.UN00315924-UNAL.dam.intra.cea.fr.132277.0
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diff --git a/training/results/trimesh_results/efull/PPO_10-v0/events.out.tfevents.1734446254.UN00315924-UNAL.dam.intra.cea.fr.817111.0 b/training/results/0-trimesh_results/efull/PPO_10-v0/events.out.tfevents.1734446254.UN00315924-UNAL.dam.intra.cea.fr.817111.0
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diff --git a/training/results/trimesh_results/efull/PPO_8_deep3-v1/events.out.tfevents.1734611428.UN00315924-UNAL.dam.intra.cea.fr.278749.0 b/training/results/0-trimesh_results/efull/PPO_8_deep3-v1/events.out.tfevents.1734611428.UN00315924-UNAL.dam.intra.cea.fr.278749.0
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rename to training/results/0-trimesh_results/efull/PPO_8_deep3-v1/events.out.tfevents.1734611428.UN00315924-UNAL.dam.intra.cea.fr.278749.0
diff --git a/training/results/trimesh_results/efull/PPO_deep12-v0/events.out.tfevents.1734598832.UN00315924-UNAL.dam.intra.cea.fr.221925.0 b/training/results/0-trimesh_results/efull/PPO_deep12-v0/events.out.tfevents.1734598832.UN00315924-UNAL.dam.intra.cea.fr.221925.0
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diff --git a/training/results/trimesh_results/efull/PPO_deep12-v1/events.out.tfevents.1734606176.UN00315924-UNAL.dam.intra.cea.fr.253849.0 b/training/results/0-trimesh_results/efull/PPO_deep12-v1/events.out.tfevents.1734606176.UN00315924-UNAL.dam.intra.cea.fr.253849.0
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diff --git a/training/results/trimesh_results/efull/PPO_deep3-v0/events.out.tfevents.1734559585.UN00315924-UNAL.dam.intra.cea.fr.197662.0 b/training/results/0-trimesh_results/efull/PPO_deep3-v0/events.out.tfevents.1734559585.UN00315924-UNAL.dam.intra.cea.fr.197662.0
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diff --git a/training/results/trimesh_results/efull/PPO_deep3-v1/events.out.tfevents.1734606200.UN00315924-UNAL.dam.intra.cea.fr.254037.0 b/training/results/0-trimesh_results/efull/PPO_deep3-v1/events.out.tfevents.1734606200.UN00315924-UNAL.dam.intra.cea.fr.254037.0
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diff --git a/training/results/trimesh_results/efull/PPO_deep3-v2/events.out.tfevents.1734618832.UN00315924-UNAL.dam.intra.cea.fr.310315.0 b/training/results/0-trimesh_results/efull/PPO_deep3-v2/events.out.tfevents.1734618832.UN00315924-UNAL.dam.intra.cea.fr.310315.0
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diff --git a/training/results/trimesh_results/efull/PPO_deep6-v0/events.out.tfevents.1734598818.UN00315924-UNAL.dam.intra.cea.fr.221824.0 b/training/results/0-trimesh_results/efull/PPO_deep6-v0/events.out.tfevents.1734598818.UN00315924-UNAL.dam.intra.cea.fr.221824.0
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diff --git a/training/results/trimesh_results/efull/PPO_deep6-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0 b/training/results/0-trimesh_results/efull/PPO_deep6-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
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diff --git a/training/results/trimesh_results/efull/PPO_l30-v0/events.out.tfevents.1735812367.UN00315924-UNAL.dam.intra.cea.fr.228874.0 b/training/results/0-trimesh_results/efull/PPO_l30-v0/events.out.tfevents.1735812367.UN00315924-UNAL.dam.intra.cea.fr.228874.0
similarity index 100%
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diff --git a/training/results/trimesh_results/efull/PPO_l50-v0/events.out.tfevents.1735812393.UN00315924-UNAL.dam.intra.cea.fr.229064.0 b/training/results/0-trimesh_results/efull/PPO_l50-v0/events.out.tfevents.1735812393.UN00315924-UNAL.dam.intra.cea.fr.229064.0
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diff --git a/training/results/trimesh_results/efull/PPO_l50-v1/events.out.tfevents.1735818955.UN00315924-UNAL.dam.intra.cea.fr.253446.0 b/training/results/0-trimesh_results/efull/PPO_l50-v1/events.out.tfevents.1735818955.UN00315924-UNAL.dam.intra.cea.fr.253446.0
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diff --git a/training/results/trimesh_results/efull/PPO_m16-v0/events.out.tfevents.1735664190.UN00315924-UNAL.dam.intra.cea.fr.16322.0 b/training/results/0-trimesh_results/efull/PPO_m16-v0/events.out.tfevents.1735664190.UN00315924-UNAL.dam.intra.cea.fr.16322.0
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diff --git a/training/results/trimesh_results/efull/PPO_m16-v1/events.out.tfevents.1735739679.UN00315924-UNAL.dam.intra.cea.fr.49745.0 b/training/results/0-trimesh_results/efull/PPO_m16-v1/events.out.tfevents.1735739679.UN00315924-UNAL.dam.intra.cea.fr.49745.0
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diff --git a/training/results/trimesh_results/efull/PPO_m25-v0/events.out.tfevents.1735744674.UN00315924-UNAL.dam.intra.cea.fr.63182.0 b/training/results/0-trimesh_results/efull/PPO_m25-v0/events.out.tfevents.1735744674.UN00315924-UNAL.dam.intra.cea.fr.63182.0
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diff --git a/training/results/trimesh_results/efull/PPO_m25-v1/events.out.tfevents.1735761690.UN00315924-UNAL.dam.intra.cea.fr.109198.0 b/training/results/0-trimesh_results/efull/PPO_m25-v1/events.out.tfevents.1735761690.UN00315924-UNAL.dam.intra.cea.fr.109198.0
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diff --git a/training/results/trimesh_results/efull/PPO_m40-v0/events.out.tfevents.1735744703.UN00315924-UNAL.dam.intra.cea.fr.63292.0 b/training/results/0-trimesh_results/efull/PPO_m40-v0/events.out.tfevents.1735744703.UN00315924-UNAL.dam.intra.cea.fr.63292.0
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diff --git a/training/results/trimesh_results/efull/PPO_no_deg-v0/events.out.tfevents.1735664190.UN00315924-UNAL.dam.intra.cea.fr.16322.0 b/training/results/0-trimesh_results/efull/PPO_no_deg-v0/events.out.tfevents.1735664190.UN00315924-UNAL.dam.intra.cea.fr.16322.0
similarity index 100%
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diff --git a/training/results/trimesh_results/efull/PPO_no_deg-v1/events.out.tfevents.1735739679.UN00315924-UNAL.dam.intra.cea.fr.49745.0 b/training/results/0-trimesh_results/efull/PPO_no_deg-v1/events.out.tfevents.1735739679.UN00315924-UNAL.dam.intra.cea.fr.49745.0
similarity index 100%
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diff --git a/training/results/trimesh_results/efull/PPO_restricted-v0/events.out.tfevents.1734431836.UN00315924-UNAL.dam.intra.cea.fr.757470.0 b/training/results/0-trimesh_results/efull/PPO_restricted-v0/events.out.tfevents.1734431836.UN00315924-UNAL.dam.intra.cea.fr.757470.0
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diff --git a/training/results/trimesh_results/efull/PPO_restricted-v1/events.out.tfevents.1734514338.UN00315924-UNAL.dam.intra.cea.fr.70489.0 b/training/results/0-trimesh_results/efull/PPO_restricted-v1/events.out.tfevents.1734514338.UN00315924-UNAL.dam.intra.cea.fr.70489.0
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diff --git a/training/results/trimesh_results/efull/PPO_restricted-v2/events.out.tfevents.1734517568.UN00315924-UNAL.dam.intra.cea.fr.83005.0 b/training/results/0-trimesh_results/efull/PPO_restricted-v2/events.out.tfevents.1734517568.UN00315924-UNAL.dam.intra.cea.fr.83005.0
similarity index 100%
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diff --git a/training/results/trimesh_results/efull/PPO_unrestricted-v0/events.out.tfevents.1734431823.UN00315924-UNAL.dam.intra.cea.fr.757302.0 b/training/results/0-trimesh_results/efull/PPO_unrestricted-v0/events.out.tfevents.1734431823.UN00315924-UNAL.dam.intra.cea.fr.757302.0
similarity index 100%
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diff --git a/training/results/trimesh_results/efull/PPO_unrestricted-v1/events.out.tfevents.1734513709.UN00315924-UNAL.dam.intra.cea.fr.67221.0 b/training/results/0-trimesh_results/efull/PPO_unrestricted-v1/events.out.tfevents.1734513709.UN00315924-UNAL.dam.intra.cea.fr.67221.0
similarity index 100%
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diff --git a/training/results/trimesh_results/efull/PPO_unrestricted-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0 b/training/results/0-trimesh_results/efull/PPO_unrestricted-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
similarity index 100%
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rename to training/results/0-trimesh_results/efull/PPO_unrestricted-v2/events.out.tfevents.1734516617.UN00315924-UNAL.dam.intra.cea.fr.79025.0
diff --git a/training/results/trimesh_results/efull/PPO_with_deg-v0/events.out.tfevents.1735663450.UN00315924-UNAL.dam.intra.cea.fr.13339.0 b/training/results/0-trimesh_results/efull/PPO_with_deg-v0/events.out.tfevents.1735663450.UN00315924-UNAL.dam.intra.cea.fr.13339.0
similarity index 100%
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rename to training/results/0-trimesh_results/efull/PPO_with_deg-v0/events.out.tfevents.1735663450.UN00315924-UNAL.dam.intra.cea.fr.13339.0
diff --git a/training/results/trimesh_results/efull/PPO_with_deg-v1/events.out.tfevents.1735670821.UN00315924-UNAL.dam.intra.cea.fr.37218.0 b/training/results/0-trimesh_results/efull/PPO_with_deg-v1/events.out.tfevents.1735670821.UN00315924-UNAL.dam.intra.cea.fr.37218.0
similarity index 100%
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rename to training/results/0-trimesh_results/efull/PPO_with_deg-v1/events.out.tfevents.1735670821.UN00315924-UNAL.dam.intra.cea.fr.37218.0
diff --git a/training/results/trimesh_results/final/PPO_1/events.out.tfevents.1735901763.UN00315924-UNAL.dam.intra.cea.fr.608011.0 b/training/results/0-trimesh_results/final/PPO_1/events.out.tfevents.1735901763.UN00315924-UNAL.dam.intra.cea.fr.608011.0
similarity index 100%
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diff --git a/training/results/trimesh_results/final/PPO_2/events.out.tfevents.1735901862.UN00315924-UNAL.dam.intra.cea.fr.608834.0 b/training/results/0-trimesh_results/final/PPO_2/events.out.tfevents.1735901862.UN00315924-UNAL.dam.intra.cea.fr.608834.0
similarity index 100%
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diff --git a/training/results/trimesh_results/final/PPO_3/events.out.tfevents.1738140564.UN00315924-UNAL.dam.intra.cea.fr.233861.0 b/training/results/0-trimesh_results/final/PPO_3/events.out.tfevents.1738140564.UN00315924-UNAL.dam.intra.cea.fr.233861.0
similarity index 100%
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diff --git a/training/results/trimesh_results/final/PPO_4/events.out.tfevents.1738157639.UN00315924-UNAL.dam.intra.cea.fr.304319.0 b/training/results/0-trimesh_results/final/PPO_4/events.out.tfevents.1738157639.UN00315924-UNAL.dam.intra.cea.fr.304319.0
similarity index 100%
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rename to training/results/0-trimesh_results/final/PPO_4/events.out.tfevents.1738157639.UN00315924-UNAL.dam.intra.cea.fr.304319.0
diff --git a/training/results/trimesh_results/test/PPO_1/events.out.tfevents.1736411485.UN00315924-UNAL.dam.intra.cea.fr.1486540.0 b/training/results/0-trimesh_results/test/PPO_1/events.out.tfevents.1736411485.UN00315924-UNAL.dam.intra.cea.fr.1486540.0
similarity index 100%
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diff --git a/training/results/files_csv/curve_smoothing.py b/training/results/files_csv/curve_smoothing.py
index 28c9e8e..02913f5 100644
--- a/training/results/files_csv/curve_smoothing.py
+++ b/training/results/files_csv/curve_smoothing.py
@@ -1,9 +1,9 @@
import pandas as pd
-df = pd.read_csv("PPO_22.csv")
+df = pd.read_csv("medium_quad_perso.csv")
if 'Value' in df.columns:
alpha =0.1
df["Smoothed"]=df["Value"].ewm(alpha=alpha, adjust=False).mean()
- df.to_csv("PPO_SB3_fixed_quad.csv",index=False)
\ No newline at end of file
+ df.to_csv("medium_quad_perso.csv",index=False)
\ No newline at end of file
diff --git a/training/train_quadmesh.py b/training/train_quadmesh.py
index 6e76a28..deb6915 100644
--- a/training/train_quadmesh.py
+++ b/training/train_quadmesh.py
@@ -1,30 +1,23 @@
from __future__ import annotations
-import wandb
-import time
-import yaml
-import os
import random
import torch
+import yaml
+import os
+import time
+import wandb
-import numpy as np
-import gymnasium as gym
import matplotlib.pyplot as plt
+import gymnasium as gym
+import numpy as np
from torch.utils.tensorboard import SummaryWriter
#Internal import
from environment.gymnasium_envs import quadmesh_env
-
-from mesh_model.random_quadmesh import random_mesh
from mesh_model.reader import read_gmsh
from model_RL.PPO_model_pers import PPO
-from model_RL.evaluate_model import testPolicy
-
-from view.mesh_plotter.create_plots import plot_training_results, plot_test_results
-from view.mesh_plotter.mesh_plots import plot_dataset
-
def log_init(log_writer, config):
@@ -61,9 +54,11 @@ def log_end(log_writer, config, obs_registry):
if __name__ == '__main__':
# PARAMETERS CONFIGURATION
- with open("training/config_PPO_perso.yaml", "r") as f:
+ with open("training/config/quadmesh_config_PPO_perso.yaml", "r") as f:
config = yaml.safe_load(f)
+ experiment_name = config["experiment_name"]
+
# Create log dir
log_dir = config["paths"]["log_dir"]
os.makedirs(log_dir, exist_ok=True)
@@ -100,6 +95,8 @@ def log_end(log_writer, config, obs_registry):
model = PPO(
env=env,
obs_size= config["env"]["obs_size"],
+ n_actions=config["ppo"]["n_actions"],
+ n_darts_observed=config["env"]["n_darts_selected"],
max_steps=config["env"]["max_episode_steps"],
lr=config["ppo"]["learning_rate"],
gamma=config["ppo"]["gamma"],
diff --git a/training/train_quadmesh_SB3.py b/training/train_quadmesh_SB3.py
index e7d6dae..0c0ed66 100644
--- a/training/train_quadmesh_SB3.py
+++ b/training/train_quadmesh_SB3.py
@@ -8,8 +8,8 @@
import wandb
import matplotlib.pyplot as plt
-import numpy as np
import gymnasium as gym
+import numpy as np
from stable_baselines3 import PPO
@@ -231,7 +231,7 @@ def _on_training_end(self) -> None:
if __name__ == '__main__':
# PARAMETERS CONFIGURATION
- with open("training/config_PPO_SB3.yaml", "r") as f:
+ with open("training/config/quadmesh_config_PPO_SB3.yaml", "r") as f:
config = yaml.safe_load(f)
experiment_name = config["experiment_name"]
diff --git a/training/train_trimesh-flip_SB3.py b/training/train_trimesh-flip_SB3.py
index 82f6cb7..6de2032 100644
--- a/training/train_trimesh-flip_SB3.py
+++ b/training/train_trimesh-flip_SB3.py
@@ -94,9 +94,9 @@ def _on_training_end(self) -> None:
self.logger.dump(step=0)
-with open("../model_RL/parameters/ppo_config.json", "r") as f:
+with open("../model_RL/old_files/ppo_config.json", "r") as f:
ppo_config = json.load(f)
-with open("../environment/environment_config.json", "r") as f:
+with open("../environment/old_files/environment_config.json", "r") as f:
env_config = json.load(f)
# Create log dir
diff --git a/training/train_trimesh.py b/training/train_trimesh.py
index 0d67e81..0516259 100644
--- a/training/train_trimesh.py
+++ b/training/train_trimesh.py
@@ -1,43 +1,100 @@
-import mesh_model.random_trimesh as TM
+from __future__ import annotations
+
+import random
import torch
-from environment.trimesh_env import TriMesh
+import os
+import time
+import yaml
+import wandb
+
+import gymnasium as gym
+import numpy as np
+
+from torch.utils.tensorboard import SummaryWriter
+from stable_baselines3.common.env_checker import check_env
+
+#Internal import
+from environment.gymnasium_envs import trimesh_full_env
+from model_RL.PPO_model_pers import PPO
+
+
+def log_init(log_writer, config):
+ log_writer.add_text("Description", config["description"])
+ log_writer.add_hparams(hparam_dict=config["env"], metric_dict=config["metrics"], run_name=config["experiment_name"])
+
+
+if __name__ == '__main__':
+
+ # PARAMETERS CONFIGURATION
+ with open("training/config/trimesh_config_PPO_perso.yaml", "r") as f:
+ config = yaml.safe_load(f)
-from view.mesh_plotter.create_plots import plot_training_results, plot_test_results
-from view.mesh_plotter.mesh_plots import plot_dataset
+ experiment_name = config["experiment_name"]
-from model_RL.evaluate_model import testPolicy
+ # Create log dir
+ log_dir = config["paths"]["log_dir"]
+ os.makedirs(log_dir, exist_ok=True)
-from model_RL.PPO_model import PPO
-#from model_RL.SAC_model import SAC
-#from model_RL.AC_model import AC
+ wandb.tensorboard.patch(root_logdir=log_dir)
+ wandb.init(
+ project="Trimesh-learning",
+ name=experiment_name,
+ config=config,
+ sync_tensorboard=True,
+ save_code=True
+ )
-LOCAL_MESH_FEAT = 0
+ # SEEDING
+ seed = config["seed"]
+ random.seed(seed)
+ np.random.seed(seed)
+ torch.manual_seed(seed)
+ torch.backends.cudnn.deterministic = True
+ # Create the environment
+ env = gym.make(
+ config["env"]["env_id"],
+ # mesh=read_gmsh(config["dataset"]["evaluation_mesh_file_path"]),
+ mesh_size=config["env"]["mesh_size"],
+ max_episode_steps=config["env"]["max_episode_steps"],
+ n_darts_selected=config["env"]["n_darts_selected"],
+ deep=config["env"]["deep"],
+ action_restriction=config["env"]["action_restriction"],
+ with_quality_obs=config["env"]["with_quality_observation"],
+ render_mode=config["env"]["render_mode"],
+ analysis_type=config["env"]["analysis_type"],
+ )
-def train():
- mesh_size = 30
- lr = 0.0001
- gamma = 0.9
- feature = LOCAL_MESH_FEAT
+ check_env(env, warn=True)
- dataset = [TM.random_mesh(30) for _ in range(9)]
- plot_dataset(dataset)
+ model = PPO(
+ env=env,
+ obs_size= config["env"]["obs_size"],
+ n_actions=config["ppo"]["n_actions"],
+ n_darts_observed=config["env"]["n_darts_selected"],
+ max_steps=config["env"]["max_episode_steps"],
+ lr=config["ppo"]["learning_rate"],
+ gamma=config["ppo"]["gamma"],
+ nb_iterations=config["ppo"]["n_iterations"],
+ nb_episodes_per_iteration=config["ppo"]["n_episodes_per_iteration"],
+ nb_epochs=config["ppo"]["n_epochs"],
+ batch_size=config["ppo"]["batch_size"],
+ )
- env = TriMesh(None, mesh_size, max_steps=80, feat=feature)
+ writer = SummaryWriter(log_dir + config["experiment_name"])
+ log_init(writer, config)
- # Choix de la politique Actor Critic
- # actor = Actor(env, 30, 5, lr=0.0001)
- # critic = Critic(30, lr=0.0001)
- # policy = NNPolicy(env, 30, 64,5, 0.9, lr=0.0001)
+ # LEARNING
+ start_time = time.perf_counter()
+ print("-----------Starting learning-----------")
- model = PPO(env, lr, gamma, nb_iterations=3, nb_episodes_per_iteration=10, nb_epochs=2, batch_size=8)
- actor, rewards, wins, steps = model.train()
- if rewards is not None:
- plot_training_results(rewards, wins, steps)
+ actor, rewards, wins, steps, obs_registry = model.learn(writer)
- # torch.save(actor.state_dict(), 'policy_saved/actor_network.pth')
- avg_steps, avg_wins, avg_rewards, final_meshes = testPolicy(actor, 5, dataset, 60)
+ end_time = time.perf_counter()
+ print("-----------Learning ended------------")
+ print(f"Temps d'apprentissage : {end_time - start_time:.4} s")
- if rewards is not None:
- plot_test_results(avg_rewards, avg_wins, avg_steps, avg_rewards)
- plot_dataset(final_meshes)
+ # SAVING POLICY
+ torch.save(actor.state_dict(), config["paths"]["policy_saving_dir"]+config["experiment_name"]+".pth")
+ writer.close()
+ wandb.finish()
\ No newline at end of file
diff --git a/training/train_trimesh_SB3.py b/training/train_trimesh_SB3.py
index 1dc3bf0..b836c07 100644
--- a/training/train_trimesh_SB3.py
+++ b/training/train_trimesh_SB3.py
@@ -1,18 +1,75 @@
from __future__ import annotations
+import random
+import torch
import os
-import json
+import time
+import yaml
+import wandb
-import mesh_model.random_trimesh as TM
-from view.mesh_plotter.mesh_plots import dataset_plt
-from training.exploit_SB3_policy import testPolicy
+import gymnasium as gym
+import numpy as np
+
+from copy import deepcopy
from stable_baselines3 import PPO
from stable_baselines3.common.env_checker import check_env
from stable_baselines3.common.callbacks import BaseCallback
-from stable_baselines3.common.logger import Figure
+from stable_baselines3.common.logger import Figure, HParam
+
+from wandb.integration.sb3 import WandbCallback
+
+from environment.actions.smoothing import smoothing_mean
+from mesh_model.reader import read_gmsh
+from view.mesh_plotter.mesh_plots import dataset_plt, plot_mesh
+from training.exploit_SB3_policy import testPolicy
+
from environment.gymnasium_envs import trimesh_full_env
-import gymnasium as gym
+import mesh_model.random_trimesh as TM
+
+
+class HParamCallback(BaseCallback):
+ """
+ Saves the hyperparameters and metrics at the start of the training, and logs them to TensorBoard.
+ """
+
+ def _on_training_start(self) -> None:
+ hparam_dict = {
+ "algorithm": self.model.__class__.__name__,
+ "experiment": experiment_name,
+ "description": config["description"],
+ "learning rate": self.model.learning_rate,
+ "gamma": self.model.gamma,
+ "batch_size": config["ppo"]["batch_size"],
+ "epochs": config["ppo"]["n_epochs"],
+ "clip_range": config["ppo"]["clip_range"],
+ "training_meshes": config["dataset"]["training_mesh_file_path"],
+ "evaluation_meshes": config["dataset"]["evaluation_mesh_file_path"],
+ "max_steps": config["env"]["max_episode_steps"],
+ "max_timesteps": config["total_timesteps"],
+ "deep": config["env"]["deep"],
+ "with_quality": config["env"]["with_quality_observation"],
+ "nb_darts_selected": config["env"]["n_darts_selected"],
+ "reward_mode": config["env"]["reward_function"],
+
+
+ }
+ # define the metrics that will appear in the `HPARAMS` Tensorboard tab by referencing their tag
+ # Tensorbaord will find & display metrics from the `SCALARS` tab
+ metric_dict = {
+ "normalized_return": 0,
+ "rollout/ep_len_mean": 0.0,
+ "rollout/ep_rew_mean": 0.0
+ }
+ self.logger.record(
+ "hparams",
+ HParam(hparam_dict, metric_dict),
+ exclude=("stdout", "log", "json", "csv"),
+ )
+
+ def _on_step(self) -> bool:
+ return True
+
class TensorboardCallback(BaseCallback):
"""
@@ -40,14 +97,6 @@ def __init__(self, model, verbose=0):
self.final_distance = 0
self.normalized_return = 0
- def _on_training_start(self) -> None:
- """
- Record PPO parameters and environment configuration at the training start.
- """
- self.logger.record("parameters/ppo", f"{json.dumps(ppo_config, indent=4)}")
- self.logger.record("parameters/env", f"{json.dumps(env_config, indent=4)}")
- self.logger.dump(step=0)
-
def _on_step(self) -> bool:
"""
Record different learning variables to monitor
@@ -65,6 +114,7 @@ def _on_step(self) -> bool:
self.actions_info["nb_invalid_split"] += self.locals["infos"][0].get("invalid_split", 0.0)
self.actions_info["nb_invalid_collapse"] += self.locals["infos"][0].get("invalid_collapse", 0.0)
+ self.final_distance = self.locals["infos"][0].get("distance", 0.0)
self.mesh_reward += self.locals["infos"][0].get("mesh_reward", 0.0)
# When the episode is over
@@ -73,20 +123,26 @@ def _on_step(self) -> bool:
mesh_ideal_reward = self.locals["infos"][0].get("mesh_ideal_rewards", 0.0) # maximum achievable reward
if mesh_ideal_reward > 0:
self.normalized_return = self.mesh_reward/ mesh_ideal_reward
+ if self.normalized_return > 1:
+ plot_mesh(self.locals["infos"][0].get("mesh"))
+ smoothed_m = deepcopy(self.locals["infos"][0].get("mesh"))
+ smoothing_mean(smoothed_m)
+ plot_mesh(smoothed_m)
+ raise ValueError("normalized return above 1 imposssible")
else:
self.normalized_return = 0
- self.final_distance = self.locals["infos"][0].get("distance", 0.0)
+
self.logger.record("final_distance", self.final_distance)
- self.logger.record("valid_actions", self.actions_info["episode_valid_actions"]*100/self.current_episode_length if self.current_episode_length > 0 else 0)
+ self.logger.record("valid_actions (%)", self.actions_info["episode_valid_actions"]*100/self.current_episode_length if self.current_episode_length > 0 else 0)
self.logger.record("n_invalid_topo", self.actions_info["episode_invalid_topo"])
self.logger.record("n_invalid_geo", self.actions_info["episode_invalid_geo"])
self.logger.record("nb_flip", self.actions_info["nb_flip"])
self.logger.record("nb_split", self.actions_info["nb_split"])
self.logger.record("nb_collapse", self.actions_info["nb_collapse"])
- self.logger.record("invalid_flip", self.actions_info["nb_invalid_flip"]*100/self.actions_info["nb_flip"] if self.actions_info["nb_flip"] > 0 else 0)
- self.logger.record("invalid_split", self.actions_info["nb_invalid_split"]*100/self.actions_info["nb_split"] if self.actions_info["nb_split"] > 0 else 0)
- self.logger.record("invalid_collapse", self.actions_info["nb_invalid_collapse"]*100/self.actions_info["nb_collapse"]if self.actions_info["nb_collapse"] > 0 else 0)
+ self.logger.record("invalid_flip (%)", self.actions_info["nb_invalid_flip"]*100/self.actions_info["nb_flip"] if self.actions_info["nb_flip"] > 0 else 0)
+ self.logger.record("invalid_split (%)", self.actions_info["nb_invalid_split"]*100/self.actions_info["nb_split"] if self.actions_info["nb_split"] > 0 else 0)
+ self.logger.record("invalid_collapse (%)", self.actions_info["nb_invalid_collapse"]*100/self.actions_info["nb_collapse"]if self.actions_info["nb_collapse"] > 0 else 0)
self.logger.record("episode_mesh_reward", self.mesh_reward)
self.logger.record("episode_reward", self.current_episode_reward)
@@ -111,50 +167,82 @@ def _on_training_end(self) -> None:
"""
Records policy evaluation results : before and after dataset images
"""
- dataset = [TM.random_mesh(30) for _ in range(9)] # dataset of 9 meshes of size 30
+ print("-------- Testing Policy ---------")
+ dataset = [TM.random_mesh(30) for _ in range(4)] # dataset of 9 meshes of size 30
before = dataset_plt(dataset) # plot the datasat as image
- length, wins, rewards, normalized_return, final_meshes = testPolicy(self.model, 10, env_config, dataset) # test model policy on the dataset
+ length, wins, rewards, normalized_return, final_meshes = testPolicy(self.model, 5, config, dataset) # test model policy on the dataset
after = dataset_plt(final_meshes)
self.logger.record("figures/before", Figure(before, close=True), exclude=("stdout", "log"))
self.logger.record("figures/after", Figure(after, close=True), exclude=("stdout", "log"))
self.logger.dump(step=0)
-
-with open("../model_RL/parameters/ppo_config.json", "r") as f:
- ppo_config = json.load(f)
-with open("../environment/environment_config.json", "r") as f:
- env_config = json.load(f)
-
-# Create log dir
-log_dir = ppo_config["tensorboard_log"]
-os.makedirs(log_dir, exist_ok=True)
-
-# Create the environment
-env = gym.make(
- env_config["env_name"],
- mesh_size=env_config["mesh_size"],
- max_episode_steps=env_config["max_episode_steps"],
- n_darts_selected=env_config["n_darts_selected"],
- deep= env_config["deep"],
- action_restriction=env_config["action_restriction"],
- with_degree_obs=env_config["with_degree_observation"]
-)
-
-check_env(env, warn=True)
-
-model = PPO(
- policy=ppo_config["policy"],
- env=env,
- n_steps=ppo_config["n_steps"],
- n_epochs=ppo_config["n_epochs"],
- batch_size=ppo_config["batch_size"],
- learning_rate=ppo_config["learning_rate"],
- gamma=ppo_config["gamma"],
- verbose=ppo_config["verbose"],
- tensorboard_log=log_dir
-)
-
-print("-----------Starting learning-----------")
-model.learn(total_timesteps=ppo_config["total_timesteps"], callback=TensorboardCallback(model))
-print("-----------Learning ended------------")
-model.save("policy_saved/test/test-PPO-4")
\ No newline at end of file
+if __name__ == '__main__':
+
+ # PARAMETERS CONFIGURATION
+ with open("training/config/trimesh_config_PPO_SB3.yaml", "r") as f:
+ config = yaml.safe_load(f)
+
+ experiment_name = config["experiment_name"]
+
+ # SEEDING
+ seed = config["seed"]
+ random.seed(seed)
+ np.random.seed(seed)
+ torch.manual_seed(seed)
+ torch.backends.cudnn.deterministic = True
+
+ # # WANDB
+ # run = wandb.init(
+ # project="Trimesh-learning",
+ # name=experiment_name,
+ # sync_tensorboard=True, # auto-upload sb3's tensorboard metrics
+ # save_code=True, # optional
+ # )
+ # Create tensorboard log dir
+ log_dir = config["paths"]["log_dir"]
+ os.makedirs(log_dir, exist_ok=True)
+
+ #training_mesh = read_gmsh(config["dataset"]["training_mesh_file_path"])
+ # Create the environment
+ env = gym.make(
+ config["env"]["env_id"],
+ #mesh=training_mesh,
+ mesh_size = config["env"]["mesh_size"],
+ max_episode_steps=config["env"]["max_episode_steps"],
+ n_darts_selected=config["env"]["n_darts_selected"],
+ deep=config["env"]["deep"],
+ action_restriction=config["env"]["action_restriction"],
+ with_quality_obs=config["env"]["with_quality_observation"],
+ render_mode=config["env"]["render_mode"],
+ analysis_type=config["env"]["analysis_type"],
+ )
+
+ check_env(env, warn=True)
+
+ model = PPO(
+ policy=config["ppo"]["policy"],
+ env=env,
+ n_steps=config["ppo"]["n_steps"],
+ n_epochs=config["ppo"]["n_epochs"],
+ batch_size=config["ppo"]["batch_size"],
+ learning_rate=config["ppo"]["learning_rate"],
+ gamma=config["ppo"]["gamma"],
+ verbose=1,
+ tensorboard_log=log_dir
+ )
+
+ start_time = time.perf_counter()
+ print("-----------Starting learning-----------")
+ model.learn(
+ total_timesteps=config["total_timesteps"],
+ tb_log_name=config["experiment_name"],
+ callback=[HParamCallback(),
+
+ TensorboardCallback(model)],
+ progress_bar=True
+ )
+ end_time = time.perf_counter()
+ print("-----------Learning ended------------")
+ print(f"Temps d'apprentissage : {end_time - start_time:.4} s")
+ model.save(config["paths"]["policy_saving_dir"] + config["experiment_name"])
+ # run.finish()
\ No newline at end of file
diff --git a/view/graph.py b/view/graph.py
index 46e95ac..343d7e4 100644
--- a/view/graph.py
+++ b/view/graph.py
@@ -1,6 +1,7 @@
import pygame
import sys
from pygame import math
+import warnings
edge_color_normal = pygame.Color(30, 30, 30) # Dark Grey
vertex_color_normal = pygame.Color(255, 0, 0) # Red
@@ -123,11 +124,14 @@ def create_vertex(self, id: int, x: int, y: int, n_value) -> int:
return len(self.vertices) - 1
def create_edge(self, i1: int, i2: int) -> int:
+ n1, n2 = None, None
for v in self.vertices:
if v.idx == i1:
n1 = v
elif v.idx == i2:
n2 = v
+ if n1 is None or n2 is None:
+ warnings.warn("try to create an edge between nodes not found")
self.add_edge(Edge(n1, n2))
return len(self.edges) - 1
diff --git a/view/mesh_plotter/mesh_plots.py b/view/mesh_plotter/mesh_plots.py
index 5a79718..584e345 100644
--- a/view/mesh_plotter/mesh_plots.py
+++ b/view/mesh_plotter/mesh_plots.py
@@ -11,7 +11,8 @@ def plot_mesh(mesh: Mesh) -> None:
Plot a mesh using matplotlib
:param mesh: a Mesh
"""
- _, _ = plt.subplots()
+ fig, ax = plt.subplots(figsize=(15, 15))
+
subplot_mesh(mesh)
plt.show(block=True)
@@ -43,8 +44,37 @@ def subplot_mesh(mesh: Mesh) -> None:
n1 = d1.get_node()
n2 = d2.get_node()
n3 = d3.get_node()
+
+ # Nodes coordinates
+ p1 = np.array([n1.x(), n1.y()])
+ p2 = np.array([n2.x(), n2.y()])
+ p3 = np.array([n3.x(), n3.y()])
+
polygon = np.array([(n1.x(), n1.y()), (n2.x(), n2.y()), (n3.x(), n3.y()), (n1.x(), n1.y())])
plt.plot(polygon[:, 0], polygon[:, 1], 'k-')
+
+ # Plot darts ID
+ mid1 = (p1 + p2) / 2
+ mid2 = (p2 + p3) / 2
+ mid3 = (p3 + p1) / 2
+
+ centroid = (p1 + p2 + p3) / 3
+
+ pos1 = mid1 +0.2* (centroid - mid1)
+ pos2 = mid2 +0.2* (centroid - mid2)
+ pos3 = mid3 +0.2* (centroid - mid3)
+
+ plt.text(*pos1, f"{d1.id}", color='blue', fontsize=10, ha='center', va='center')
+ plt.text(*pos2, f"{d2.id}", color='blue', fontsize=10, ha='center', va='center')
+ plt.text(*pos3, f"{d3.id}", color='blue', fontsize=10, ha='center', va='center')
+
+ # Plot nodes ID
+ n_id =0
+ for n_info in mesh.nodes:
+ if n_info[2] >=0:
+ plt.text(n_info[0] + 0.03, n_info[1] - 0.02, f"{n_id}", fontsize=12, color='red', ha='right', va='top')
+ n_id+=1
+
elif quad:
for dart_id in faces:
d1 = Dart(mesh, dart_id)
* **triangular quad:** This configuration should be avoided, as it results in the creation of a degenerate (flat) triangle. As illustrated in the figures below, flipping dart 0 leads to a flattened face between nodes 2, 0, and 7.
- *
+
@@ -51,6 +51,54 @@ However, in some configurations, collapse action can also lead to problematic co
* **Adjacency too high :** When nodes A already has an adjacency higher than 10, collapse is not possible.
* **Configuration who tends to imply edge reversal**: To detect these situations, we look a the type of darts in the surrounding. When there are some darts with concave surrounding, collapse action can lead to edge reversal.
-
-
\ No newline at end of file
+
+
+The **flip** action can be decomposed as follows:
+
+* Check whether the dart `d` exists.
+* Update the **beta1** relations.
+* Update the links from nodes `n1` and `n2`, if they were previously linked to the flipped dart.
+* Update the links from faces `F1` and `F2`, if they were previously linked to the flipped dart.
+* Update the node links for `d` and `d2`.
+* Update the face links depending on the orientation (darts which change of face):
+ * If **counterclockwise**: update links for `d1` and `d21`.
+ * If **clockwise**: update links for `d2111` and `d111`.
+* Update the scores of the nodes.
+
+## Split
+
+
+
+The **split** action can be decomposed as follows:
+
+* Check whether the dart `d` exists.
+* Create a new node **n10** in the middle of [n1,n2]
+* Update node links of `d` and `d21`, they are now linked to `n10`
+* Create a new face with yellow darts
+* Update the **beta2** relations (`d1112`, `d111`,`d212`, `d21`).
+* Update the scores of the nodes.
+
+## Collapse
+
+
+
+The **collapse** action can be decomposed as follows:
+
+* Check whether the dart `d` exists.
+* Save the score of node `n1` for later computation.
+* If `n3` is not on the boundary, move its coordinates to the midpoint between `n3` and `n1`.
+* Check if nodes `n2` and `n4` are linked to the dart being deleted. If so, reassign their links to existing darts (node `n3` will be checked later).
+* Delete the face associated with `d`, along with its related darts.
+* Reassign all darts previously linked to `n1` so they now point to `n3`.
+* Link the dart associated with `n3` to an existing node.
+* Update the **beta2** relations (`d2`/`d12`, `d112`/`d1112`).
+* Recalculate the scores of the affected nodes.
diff --git a/docs/img/actions/collapse_quad.png b/docs/img/actions/collapse_quad.png
new file mode 100644
index 0000000..6909cf6
Binary files /dev/null and b/docs/img/actions/collapse_quad.png differ
diff --git a/docs/img/actions/flip_quad.png b/docs/img/actions/flip_quad.png
new file mode 100644
index 0000000..936ee2e
Binary files /dev/null and b/docs/img/actions/flip_quad.png differ
diff --git a/docs/img/actions/split_quad.png b/docs/img/actions/split_quad.png
new file mode 100644
index 0000000..2279194
Binary files /dev/null and b/docs/img/actions/split_quad.png differ
diff --git a/docs/tests/actions.md b/docs/tests/actions.md
new file mode 100644
index 0000000..04d36bf
--- /dev/null
+++ b/docs/tests/actions.md
@@ -0,0 +1,38 @@
+# Actions tests
+
+## Triangular actions
+
+### Flip
+
+We want to ensure that **flip** operations are performed correctly.
+Consider the following mesh:
+
+
+
+If we flip the dart between nodes **n0** and **n3**, we should obtain the following mesh:
+
+
+
+### Split
+
+We want to ensure that **split** operations are performed correctly.
+Consider the following mesh:
+
+
+
+If we split the dart between nodes **n0** and **n3**, we add a node **n5** on the middle of the edge and two faces are created.
+We should obtain the following mesh:
+
+
+
+### Collapse
+
+We want to ensure that **split** operations are performed correctly.
+Consider the following mesh:
+
+
+
+Here we can't collapse the dart between nodes **n5** and **n2** because n2 is on boundary. However we can collapse the edge between **n4** and **n5**.
+We should obtain the following mesh:
+
+
\ No newline at end of file
diff --git a/docs/tests/img/tri_collapse_after.png b/docs/tests/img/tri_collapse_after.png
new file mode 100644
index 0000000..9b0ca5c
Binary files /dev/null and b/docs/tests/img/tri_collapse_after.png differ
diff --git a/docs/tests/img/tri_collapse_before.png b/docs/tests/img/tri_collapse_before.png
new file mode 100644
index 0000000..48f3289
Binary files /dev/null and b/docs/tests/img/tri_collapse_before.png differ
diff --git a/docs/tests/img/tri_flip_after.png b/docs/tests/img/tri_flip_after.png
new file mode 100644
index 0000000..33cec2e
Binary files /dev/null and b/docs/tests/img/tri_flip_after.png differ
diff --git a/docs/tests/img/tri_flip_before.png b/docs/tests/img/tri_flip_before.png
new file mode 100644
index 0000000..8ae9e65
Binary files /dev/null and b/docs/tests/img/tri_flip_before.png differ
diff --git a/docs/tests/img/tri_split_after.png b/docs/tests/img/tri_split_after.png
new file mode 100644
index 0000000..df8768a
Binary files /dev/null and b/docs/tests/img/tri_split_after.png differ
diff --git a/docs/tests/img/tri_split_before.png b/docs/tests/img/tri_split_before.png
new file mode 100644
index 0000000..8ae9e65
Binary files /dev/null and b/docs/tests/img/tri_split_before.png differ
diff --git a/environment/actions/quadrangular_actions.py b/environment/actions/quadrangular_actions.py
index d1716bf..14efd5a 100644
--- a/environment/actions/quadrangular_actions.py
+++ b/environment/actions/quadrangular_actions.py
@@ -1,26 +1,37 @@
from __future__ import annotations
+from copy import deepcopy
+
+from mesh_model.mesh_analysis.global_mesh_analysis import NodeAnalysis
from mesh_model.mesh_struct.mesh import Mesh
from mesh_model.mesh_struct.mesh_elements import Node
-from mesh_model.mesh_analysis.global_mesh_analysis import adjacent_darts, degree, mesh_check, on_boundary
-from mesh_model.mesh_analysis.quadmesh_analysis import isFlipCCWOk, isFlipCWOk, isCollapseOk, isSplitOk, isCleanupOk
+from mesh_model.reader import read_gmsh
+from view.mesh_plotter.mesh_plots import plot_mesh
+"""
+Quadrangular actions performed on meshes.
-def flip_edge_cntcw_ids(mesh: Mesh, id1: int, id2: int) -> True:
- return flip_edge_cntcw(mesh, Node(mesh, id1), Node(mesh, id2))
+Each function returns three Booleans:
+ * action_validity: If the action has been performed.
+ * topo: if the action is topologically valid
+ * geo: if the action is geometrically valid
+"""
-def flip_edge_cntcw(mesh: Mesh, n1: Node, n2: Node) -> (True, True, True):
- found, d = mesh.find_inner_edge(n1, n2)
+def flip_edge_cntcw_ids(mesh_analysis, id1: int, id2: int) -> (True, True, True):
+ return flip_edge_cntcw(mesh_analysis, Node(mesh_analysis.mesh, id1), Node(mesh_analysis.mesh, id2))
+
+def flip_edge_cntcw(mesh_analysis, n1: Node, n2: Node) -> (True, True, True):
+ found, d = mesh_analysis.mesh.find_inner_edge(n1, n2)
if found:
- topo, geo = isFlipCCWOk(d)
+ topo, geo = mesh_analysis.isFlipCCWOk(d)
if not geo or not topo:
return False, topo, geo
else:
return False, False, False
- d2, d1, d11, d111, d21, d211, d2111, n1, n2, n3, n4, n5, n6 = mesh.active_quadrangles(d)
+ d2, d1, d11, d111, d21, d211, d2111, n1, n2, n3, n4, n5, n6 = mesh_analysis.mesh.active_quadrangles(d)
f1 = d.get_face()
f2 = d2.get_face()
@@ -33,7 +44,7 @@ def flip_edge_cntcw(mesh: Mesh, n1: Node, n2: Node) -> (True, True, True):
d2111.set_beta(1, d1)
d1.set_beta(1, d2)
-
+ #Update nodes links
if n1.get_dart().id == d.id:
n1.set_dart(d21)
if n2.get_dart().id == d2.id:
@@ -41,7 +52,6 @@ def flip_edge_cntcw(mesh: Mesh, n1: Node, n2: Node) -> (True, True, True):
if f1.get_dart().id == d1.id:
f1.set_dart(d)
-
if f2.get_dart().id == d21.id:
f2.set_dart(d2)
@@ -50,23 +60,28 @@ def flip_edge_cntcw(mesh: Mesh, n1: Node, n2: Node) -> (True, True, True):
d21.set_face(f1)
d1.set_face(f2)
- return True, topo, geo
+ # update nodes scores
+ n1.set_score(n1.get_score() + 1)
+ n2.set_score(n2.get_score() + 1)
+ n3.set_score(n3.get_score() - 1)
+ n5.set_score(n5.get_score() - 1)
-def flip_edge_cw_ids(mesh: Mesh, id1: int, id2: int) -> True:
- return flip_edge_cw(mesh, Node(mesh, id1), Node(mesh, id2))
+ return True, topo, geo
+def flip_edge_cw_ids(mesh_analysis, id1: int, id2: int) -> (True, True, True):
+ return flip_edge_cw(mesh_analysis, Node(mesh_analysis.mesh, id1), Node(mesh_analysis.mesh, id2))
-def flip_edge_cw(mesh: Mesh, n1: Node, n2: Node) -> (True, True, True):
- found, d = mesh.find_inner_edge(n1, n2)
+def flip_edge_cw(mesh_analysis, n1: Node, n2: Node) -> (True, True, True):
+ found, d = mesh_analysis.mesh.find_inner_edge(n1, n2)
if found:
- topo, geo = isFlipCWOk(d)
+ topo, geo = mesh_analysis.isFlipCWOk(d)
if not geo or not topo:
return False, topo, geo
else:
return False, False, False
- d2, d1, d11, d111, d21, d211, d2111, n1, n2, n3, n4, n5, n6 = mesh.active_quadrangles(d)
+ d2, d1, d11, d111, d21, d211, d2111, n1, n2, n3, n4, n5, n6 = mesh_analysis.mesh.active_quadrangles(d)
f1 = d.get_face()
f2 = d2.get_face()
@@ -97,51 +112,64 @@ def flip_edge_cw(mesh: Mesh, n1: Node, n2: Node) -> (True, True, True):
d2111.set_face(f1)
d111.set_face(f2)
- return True, topo, geo
-
+ # update nodes scores
+ n1.set_score(n1.get_score() + 1)
+ n2.set_score(n2.get_score() + 1)
+ n4.set_score(n3.get_score() - 1)
+ n6.set_score(n5.get_score() - 1)
-def split_edge_ids(mesh: Mesh, id1: int, id2: int) -> True:
- return split_edge(mesh, Node(mesh, id1), Node(mesh, id2))
+ return True, topo, geo
+def split_edge_ids(mesh_analysis, id1: int, id2: int) -> (True, True, True):
+ return split_edge(mesh_analysis, Node(mesh_analysis.mesh, id1), Node(mesh_analysis.mesh, id2))
-def split_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
- found, d = mesh.find_inner_edge(n1, n2)
+def split_edge(mesh_analysis, n1: Node, n2: Node) -> (True, True, True):
+ mesh_before = deepcopy(mesh_analysis.mesh)
+ found, d = mesh_analysis.mesh.find_inner_edge(n1, n2)
if found:
- topo, geo = isSplitOk(d)
+ topo, geo = mesh_analysis.isSplitOk(d)
if not geo or not topo:
return False, topo, geo
else:
return False, True, False
- d2, d1, d11, d111, d21, d211, d2111, n1, n2, n3, n4, n5, n6 = mesh.active_quadrangles(d)
+ d2, d1, d11, d111, d21, d211, d2111, n1, n2, n3, n4, n5, n6 = mesh_analysis.mesh.active_quadrangles(d)
d1112 = d111.get_beta(2)
d212 = d21.get_beta(2)
# create a new node in the middle of [n1, n2]
- N10 = mesh.add_node((n1.x() + n2.x()) / 2, (n1.y() + n2.y()) / 2)
+ N10 = mesh_analysis.mesh.add_node((n1.x() + n2.x()) / 2, (n1.y() + n2.y()) / 2)
# modify existing triangles
d.set_node(N10)
d21.set_node(N10)
# create a new quadrangle
- f5 = mesh.add_quad(n1, n5, N10, n4)
+ f5 = mesh_analysis.mesh.add_quad(n1, n5, N10, n4)
# update beta2 relations
- mesh.set_face_beta2(f5,[d111,d1112,d21,d212])
+ mesh_analysis.mesh.set_face_beta2(f5,[d111,d1112,d21,d212])
+
+ # update nodes scores
+ n1.set_score(n1.get_score() + 1)
+ n3.set_score(n3.get_score() - 1)
+ n4.set_score(n4.get_score() - 1)
+ N10.set_score(1) # new nodes have an adjacency of 3, wich means a score of 1
+ N10.set_ideal_adjacency(4) # the inner vertices of quadrangular meshes have an ideal adjacency of 4
return True, topo, geo
-def collapse_edge_ids(mesh: Mesh, id1: int, id2: int) -> True:
- return collapse_edge(mesh, Node(mesh, id1), Node(mesh, id2))
+def collapse_edge_ids(mesh_analysis, id1: int, id2: int) -> (True, True, True):
+ return collapse_edge(mesh_analysis, Node(mesh_analysis.mesh, id1), Node(mesh_analysis.mesh, id2))
-def collapse_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
+def collapse_edge(mesh_analysis, n1: Node, n2: Node) -> (True, True, True):
+ mesh = mesh_analysis.mesh
found, d = mesh.find_inner_edge(n1, n2)
if found:
- topo, geo = isCollapseOk(d)
+ topo, geo = mesh_analysis.isCollapseOk(d)
if not geo or not topo:
return False, topo, geo
else:
@@ -149,27 +177,50 @@ def collapse_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
d2, d1, d11, d111, d21, d211, d2111, n1, n2, n3, n4, n5, n6 = mesh.active_quadrangles(d)
+ n1_score = n1.get_score()
+
d1112 = d111.get_beta(2)
d12 = d1.get_beta(2)
d112 = d11.get_beta(2)
+ n3_analysis = NodeAnalysis(n3)
# Move n3 node in the middle of [n3, n1]
- if not on_boundary(n3):
+ if not n3_analysis.on_boundary():
n3.set_xy((n3.x() + n1.x()) / 2, (n1.y() + n3.y()) / 2)
- #Delete the face F5
+ # Check if nodes n2 and n4 are not linked to deleted dart (n3 will be checked after)
+ if n2.get_dart() == d1:
+ if mesh.is_dart_active(d2):
+ n2.set_dart(d2)
+ else:
+ n2.set_dart(d12.get_beta(1))
+ if n4.get_dart() == d111:
+ if mesh.is_dart_active(d112):
+ n4.set_dart(d112)
+ else:
+ n4.set_dart(d1112.get_beta(1))
+
+ # Delete the face F5
f5 = d.get_face()
- mesh.del_quad(d, d1, d11, d111, f5)
+ mesh_analysis.mesh.del_quad(d, d1, d11, d111, f5)
n_from = n1
n_to = n3
- adj_darts = adjacent_darts(n_from)
+
+ n_from_analysis = NodeAnalysis(n_from)
+ adj_darts = n_from_analysis.adjacent_darts()
for d in adj_darts:
if d.get_node() == n_from:
d.set_node(n_to)
- mesh.del_node(n_from)
+ # Change n3 dart association
+ for d in adj_darts:
+ if d.get_node() == n_to:
+ n_to.set_dart(d)
+ break
+
+ mesh_analysis.mesh.del_node(n_from)
#Update beta2 relations
if d2 is not None:
@@ -184,22 +235,27 @@ def collapse_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
if d112 is not None:
d112.set_beta(2, d1112)
- return mesh_check(mesh), topo, geo
+ # update nodes scores
+ n2.set_score(n1.get_score() + 1)
+ n4.set_score(n2.get_score() + 1)
+ n3.set_score(n3.get_score() + n1_score - 2)
+ return mesh_analysis.mesh_check(), topo, geo
-def cleanup_edge_ids(mesh: Mesh, id1: int, id2: int) -> True:
- return cleanup_edge(mesh, Node(mesh, id1), Node(mesh, id2))
-def cleanup_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
- found, d = mesh.find_inner_edge(n1, n2)
+def cleanup_edge_ids(mesh_analysis, id1: int, id2: int) -> (True, True, True):
+ return cleanup_edge(mesh_analysis.mesh, Node(mesh_analysis.mesh, id1), Node(mesh_analysis.mesh, id2))
+
+def cleanup_edge(mesh_analysis, n1: Node, n2: Node) -> (True, True, True):
+ found, d = mesh_analysis.mesh.find_inner_edge(n1, n2)
if found:
- topo, geo = isCleanupOk(d)
+ topo, geo = mesh_analysis.isCleanupOk(d)
if not geo or not topo:
return False, topo, geo
else:
return False, False, False
- parallel_darts = mesh.find_parallel_darts(d)
+ parallel_darts = mesh_analysis.mesh.find_parallel_darts(d)
last_dart = parallel_darts[-1]
ld1 = last_dart.get_beta(1)
@@ -207,8 +263,9 @@ def cleanup_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
ld111 = ld11.get_beta(1)
last_node = ld111.get_node()
node_to = ld11.get_node()
- adj_darts = adjacent_darts(last_node)
- mesh.del_node(last_node)
+ na_last_node = NodeAnalysis(last_node)
+ adj_darts = na_last_node.adjacent_darts()
+ mesh_analysis.mesh.del_node(last_node)
for da in adj_darts:
if da.get_node() == last_node:
@@ -231,15 +288,15 @@ def cleanup_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
if d12 is not None:
d12.set_beta(2, d1112)
- mesh.del_quad(d, d1, d11, d111, f)
-
- adj_darts = adjacent_darts(n_from)
+ mesh_analysis.mesh.del_quad(d, d1, d11, d111, f)
+ na_nfrom = NodeAnalysis(n_from)
+ adj_darts = na_nfrom.adjacent_darts()
for d in adj_darts:
if d.get_node() == n_from:
d.set_node(n_to)
- mesh.del_node(n_from)
+ mesh_analysis.mesh.del_node(n_from)
- return mesh_check(mesh), topo, geo
+ return mesh_analysis.mesh_check(), topo, geo
diff --git a/environment/actions/smoothing.py b/environment/actions/smoothing.py
index 9b5f431..3c1dc42 100644
--- a/environment/actions/smoothing.py
+++ b/environment/actions/smoothing.py
@@ -2,7 +2,9 @@
from mesh_model.mesh_struct.mesh import Mesh
from mesh_model.mesh_struct.mesh_elements import Node
-from mesh_model.mesh_analysis.global_mesh_analysis import adjacent_darts, on_boundary
+from mesh_model.mesh_analysis.global_mesh_analysis import NodeAnalysis
+from view.mesh_plotter.mesh_plots import plot_mesh
+
def smoothing_mean(mesh: Mesh) -> True:
for i in range (20):
@@ -10,8 +12,9 @@ def smoothing_mean(mesh: Mesh) -> True:
for i, n_info in enumerate (mesh.nodes, start=0):
if n_info[2] >=0:
node_to_smooth = Node(mesh, i)
- if not on_boundary(node_to_smooth):
- list_darts = adjacent_darts(node_to_smooth)
+ na = NodeAnalysis(node_to_smooth)
+ if not na.on_boundary():
+ list_darts = na.adjacent_darts()
sum_x = 0.0
sum_y = 0.0
nb_nodes = 0.0
@@ -21,4 +24,7 @@ def smoothing_mean(mesh: Mesh) -> True:
sum_x += n.x()
sum_y += n.y()
nb_nodes += 1
+ if nb_nodes == 0:
+ plot_mesh(mesh)
+ raise ValueError("Isolated vertex ")
node_to_smooth.set_xy(sum_x/nb_nodes, sum_y/nb_nodes)
\ No newline at end of file
diff --git a/environment/actions/triangular_actions.py b/environment/actions/triangular_actions.py
index bb7a357..a7fb79e 100644
--- a/environment/actions/triangular_actions.py
+++ b/environment/actions/triangular_actions.py
@@ -1,25 +1,44 @@
from __future__ import annotations
-from mesh_model.mesh_struct.mesh import Mesh
-from mesh_model.mesh_struct.mesh_elements import Node
-from mesh_model.mesh_analysis.global_mesh_analysis import mesh_check
-from mesh_model.mesh_analysis.trimesh_analysis import isFlipOk, isCollapseOk, isSplitOk
+import copy
+import numpy as np
+from mesh_model.mesh_analysis.global_mesh_analysis import NodeAnalysis
+from mesh_model.mesh_struct.mesh_elements import Node, Dart
+from view.mesh_plotter.mesh_plots import plot_mesh
+"""
+Triangular actions performed on meshes.
+Each function returns three Booleans:
+ * action_validity: If the action has been performed.
+ * topo: if the action is topologically valid
+ * geo: if the action is geometrically valid
+"""
-def flip_edge_ids(mesh: Mesh, id1: int, id2: int) -> True:
- return flip_edge(mesh, Node(mesh, id1), Node(mesh, id2))
+def flip_edge_ids(mesh_analysis, id1: int, id2: int) -> True:
+ return flip_edge(mesh_analysis, Node(mesh_analysis.mesh, id1), Node(mesh_analysis.mesh, id2))
-def flip_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
- found, d = mesh.find_inner_edge(n1, n2)
+def flip_edge(mesh_analysis, n1: Node, n2: Node) -> True:
+ """
+ When a dart is flipped, beta2 relationships are not affected, only beta1.
+ :param mesh_analysis: mesh analysis object from the mesh to modify
+ :param n1: first node of the edge to be flipped
+ :param n2: second node of the edge to be flipped
+ :return: valid_action : True if valid, false otherwise ; topo: true if topologically valid, false otherwise ; geo : true if geometrically valid, false otherwise
+ """
+ valid_action = True
+ found, d = mesh_analysis.mesh.find_inner_edge(n1, n2)
+ mesh_before = copy.deepcopy(mesh_analysis.mesh)
+
if found:
- topo, geo = isFlipOk(d)
+ topo, geo = mesh_analysis.isFlipOk(d)
if not geo or not topo:
return False, topo, geo
else:
- return False, False, False
+ return False, False, True # the geometrical criteria is True because if the dart is not found, it means it's a boundary dart and a topological criteria
- d2, d1, d11, d21, d211, n1, n2, n3, n4 = mesh.active_triangles(d)
+
+ d2, d1, d11, d21, d211, n1, n2, n3, n4 = mesh_analysis.mesh.active_triangles(d)
f1 = d.get_face()
f2 = d2.get_face()
@@ -38,7 +57,6 @@ def flip_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
if f1.get_dart().id == d11.id:
f1.set_dart(d)
-
if f2.get_dart().id == d211.id:
f2.set_dart(d2)
@@ -46,27 +64,44 @@ def flip_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
d2.set_node(n4)
d211.set_face(f1)
d11.set_face(f2)
- return True, topo, geo
+ #Update dart quality and nodes scores
+ d.set_quality(mesh_analysis.get_dart_geometric_quality(d)) # updates d and d2
+ d1.set_quality(mesh_analysis.get_dart_geometric_quality(d1)) # updates d1 and d12
+ d11.set_quality(mesh_analysis.get_dart_geometric_quality(d11)) # updates d11 and d112
+ d21.set_quality(mesh_analysis.get_dart_geometric_quality(d21)) # updates d21 and d212
+ d211.set_quality(mesh_analysis.get_dart_geometric_quality(d211)) # updates d211 and d2112
-def split_edge_ids(mesh: Mesh, id1: int, id2: int) -> True:
- return split_edge(mesh, Node(mesh, id1), Node(mesh, id2))
+ n1.set_score(n1.get_score() + 1) # an edge is removed from vertex n1
+ n2.set_score(n2.get_score() + 1) # an edge is removed from vertex n2
+ n3.set_score(n3.get_score() - 1) # an edge is added to vertex n3
+ n4.set_score(n4.get_score() - 1) # an edge is added to vertex n4
+ after_check = check_mesh(mesh_analysis, mesh_before)
+ if not after_check:
+ raise ValueError("Some checks are missing")
-def split_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
- found, d = mesh.find_inner_edge(n1, n2)
+ return valid_action, topo, geo
+
+def split_edge_ids(mesh_analysis, id1: int, id2: int) -> True:
+ return split_edge(mesh_analysis, Node(mesh_analysis.mesh, id1), Node(mesh_analysis.mesh, id2))
+
+
+def split_edge(mesh_analysis, n1: Node, n2: Node) -> True:
+ found, d = mesh_analysis.mesh.find_inner_edge(n1, n2)
+ mesh_before = copy.deepcopy(mesh_analysis.mesh)
if found:
- topo, geo = isSplitOk(d)
+ topo, geo = mesh_analysis.isSplitOk(d)
if not geo or not topo:
return False, topo, geo
else:
- return False, True, False
+ return False, False, True # the geometrical criteria is True because if the dart is not found, it means it's a boundary dart
- d2, d1, _, d21, _, n1, n2, n3, n4 = mesh.active_triangles(d)
+ d2, d1, d11, d21, d211, n1, n2, n3, n4 = mesh_analysis.mesh.active_triangles(d)
- # create a new node in the middle of [n1, n2]
- N5 = mesh.add_node((n1.x() + n2.x()) / 2, (n1.y() + n2.y()) / 2)
+ # Create a new node in the middle of [n1, n2]
+ N5 = mesh_analysis.mesh.add_node((n1.x() + n2.x()) / 2, (n1.y() + n2.y()) / 2)
# modify existing triangles
d1.set_node(N5)
@@ -75,86 +110,292 @@ def split_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
d2.set_beta(1, d21)
# create 2 new triangles
- F3 = mesh.add_triangle(n2, n3, N5)
- F4 = mesh.add_triangle(N5, n1, n4)
+ F3 = mesh_analysis.mesh.add_triangle(n2, n3, N5)
+ F4 = mesh_analysis.mesh.add_triangle(N5, n1, n4)
# update beta2 relations
- mesh.set_face_beta2(F3, [d1, d2])
- d2b2 = d2.get_beta(2)
- d2b21 = d2b2.get_beta(1)
- mesh.set_beta2(d2b21)
- mesh.set_face_beta2(F4, [d, d21])
- db2 = d.get_beta(2)
- db21 = db2.get_beta(1)
- mesh.set_beta2(db21)
+ mesh_analysis.mesh.set_face_beta2(F3, [d1, d2, d1.get_beta(2)])
+ mesh_analysis.mesh.set_face_beta2(F4, [d, d21, d21.get_beta(2)])
+
+ #update nodes scores
+ n3.set_score(n3.get_score() - 1)
+ n4.set_score(n4.get_score() - 1)
+ N5.set_score(2) # new nodes have an adjacency of 4, wich means a score of 2
+ N5.set_ideal_adjacency(6) # the inner vertices of triangular meshes have an ideal adjacency of 6
+
+ #update darts quality
+ d.set_quality(mesh_analysis.get_dart_geometric_quality(d)) # d and d twin update
+ d1.set_quality(mesh_analysis.get_dart_geometric_quality(d1)) # d1 and d12 update
+ d11.set_quality(mesh_analysis.get_dart_geometric_quality(d11)) # d11 and d112 update
+ d2.set_quality(mesh_analysis.get_dart_geometric_quality(d2)) # d2 and d22 update (d and d2 are no longer twin darts)
+ d21.set_quality(mesh_analysis.get_dart_geometric_quality(d21)) # d21 and d212 update
+ d211.set_quality(mesh_analysis.get_dart_geometric_quality(d211)) # d211 and d2112 update
+
+ #f3 face
+ d22f3 = d2.get_beta(2)
+ d221f3 = d22f3.get_beta(1)
+ d221f3.set_quality(mesh_analysis.get_dart_geometric_quality(d221f3))
+
+ #f4 face
+ d2f4 = d.get_beta(2)
+ d21f4 = d2f4.get_beta(1)
+ d21f4.set_quality(mesh_analysis.get_dart_geometric_quality(d21f4))
+
+ after_check = check_mesh(mesh_analysis, mesh_before)
+ if not after_check:
+ raise ValueError("Some checks are missing")
return True, topo, geo
-def collapse_edge_ids(mesh: Mesh, id1: int, id2: int) -> True:
- return collapse_edge(mesh, Node(mesh, id1), Node(mesh, id2))
+def collapse_edge_ids(mesh_analysis, id1: int, id2: int) -> True:
+ return collapse_edge(mesh_analysis, Node(mesh_analysis.mesh, id1), Node(mesh_analysis.mesh, id2))
-def collapse_edge(mesh: Mesh, n1: Node, n2: Node) -> True:
+def collapse_edge(mesh_analysis, n1: Node, n2: Node) -> True:
+ mesh = mesh_analysis.mesh
+ mesh_before = copy.deepcopy(mesh)
found, d = mesh.find_inner_edge(n1, n2)
+
if found:
- topo, geo = isCollapseOk(d)
+ topo, geo = mesh_analysis.isCollapseOk(d)
if not geo or not topo:
return False, topo, geo
else:
- return False, False, False
+ return False, False, True # the geometrical criteria is True because if the dart is not found, it means it's a boundary dart
+
+ d2, d1, d11, d21, d211, n1, n2, n3, n4 = mesh.active_triangles(d)
+
+ d212 = d21.get_beta(2) # T1
+ d2112 = d211.get_beta(2) # T2
+ d12 = d1.get_beta(2) # T3
+ if not mesh.is_dart_active(d12):
+ print("error")
+ d112 = d11.get_beta(2) # T4
+ # Delete the darts around selected dart
+ mesh_analysis.mesh.del_adj_triangles(d)
+
+ #Check if nodes n3 and n4 are not linked to deleted dart
+
+ if n3.get_dart().id == d11.id:
+ if mesh.is_dart_active(d12):
+ n3.set_dart(d12)
+ else:
+ n3.set_dart(d112.get_beta(1))
+ if n4.get_dart().id == d211.id:
+ if mesh.is_dart_active(d212):
+ n4.set_dart(d212)
+ else:
+ n4.set_dart(d2112.get_beta(1))
+ if n1.get_dart().id == d.id or n1.get_dart().id == d21.id:
+ if mesh.is_dart_active(d112):
+ n1.set_dart(d112)
+ else:
+ n1.set_dart(d2112)
+
+ #update beta2 relations
+ if mesh.is_dart_active(d112):
+ d112.set_beta(2, d12)
+ if mesh.is_dart_active(d12):
+ d12.set_beta(2, d112)
- _, d1, d11, d21, d211, n1, n2, _, _ = mesh.active_triangles(d)
+ if mesh.is_dart_active(d212):
+ d212.set_beta(2, d2112)
+ if mesh.is_dart_active(d2112):
+ d2112.set_beta(2, d212)
- d212 = d21.get_beta(2) #T1
- d2112 = d211.get_beta(2) #T2
- d12 = d1.get_beta(2) #T3
- d112 = d11.get_beta(2) #T4
+ n2_score = n2.get_score()
+ n2x = n2.x()
+ n2y =n2.y()
+ mid = np.array([(n1.x() + n2x) / 2, (n1.y() + n2y) / 2])
+ near_n1 = np.array([(n1.x() * 0.9 + n2x * 0.1), (n1.y() * 0.9 + n2y * 0.1)])
+ near_n2 = np.array([(n1.x() * 0.1 + n2x * 0.9), (n1.y() * 0.1 + n2y * 0.9)])
+ #delete n2 node
+ mesh_analysis.mesh.del_node(n2)
- #Delete the darts around selected dart
- mesh.del_adj_triangles(d)
+ # update nodes scores
+ n1.set_score(n1.get_score() + n2_score - 2) # node n1 becomes the union of nodes n1 and n2
+ n3.set_score(n3.get_score() + 1) # an edge is removed from vertex n3
+ n4.set_score(n4.get_score() + 1) # an edge is removed from vertex n4
- #Move n1 node in the middle of [n1, n2]
- n1.set_xy((n1.x() + n2.x()) / 2, (n1.y() + n2.y()) / 2)
+ # d12.set_quality(mesh_analysis.get_dart_geometric_quality(d12))
+ # d212.set_quality(mesh_analysis.get_dart_geometric_quality(d212, mesh_before))
- #Update node relations
- if d12 is not None:
+ # Update node relations
+ i = 0
+ if mesh.is_dart_active(d12):
d121 = d12.get_beta(1)
d121.set_node(n1)
ds = d121
+ ds1 = ds.get_beta(1)
while ds is not None and ds != d2112:
+ i += 1
d2s = ds.get_beta(2)
- if d2s is None:
+ if not mesh.is_dart_active(d2s):
ds = d2112
- while ds is not None:
+ while mesh.is_dart_active(ds):
+ i += 1
ds.set_node(n1)
ds1 = ds.get_beta(1)
ds11 = ds1.get_beta(1)
ds = ds11.get_beta(2)
+ if i > 30:
+ i = 0
+ raise ValueError("Potential infinite loop in action collapse")
else:
ds = d2s.get_beta(1)
ds.set_node(n1)
- """
- elif d12 is None and d2112 is not None:
- d2112.set_node(n1)
- ds = (d2112.get_beta(1)).get_beta(1)
- ds2 = ds.get_beta(2)
- while ds2 is not None:
- ds2.set_node(n1)
- ds = (ds2.get_beta(1)).get_beta(1)
- ds2 = ds.get_beta(2)
- """
- #update beta2 relations
- if d112 is not None:
- d112.set_beta(2, d12)
- if d12 is not None:
- d12.set_beta(2, d112)
-
- if d212 is not None:
- d212.set_beta(2, d2112)
- if d2112 is not None:
- d2112.set_beta(2, d212)
-
- #delete n2 node
- mesh.del_node(n2)
+ ds1 = ds.get_beta(1)
+ if i > 30:
+ i = 0
+ raise ValueError("Potential infinite loop in action collapse")
+
+ found, new_x, new_y = mesh_analysis.find_star_vertex(n1)
+ if found:
+ n1.set_xy(new_x, new_y)
+ else:
+ # plot_mesh(mesh_before)
+ # plot_mesh(mesh_analysis.mesh)
+ mesh_analysis.find_star_vertex(n1, plot=True)
+ raise ValueError("No star vertex found")
+
+ # if mesh_analysis.is_star_vertex(n1, mid):
+ # n1.set_xy(mid[0], mid[1])
+ # elif mesh_analysis.is_star_vertex(n1, near_n1):
+ # n1.set_xy(near_n1[0], near_n1[1])
+ # elif mesh_analysis.is_star_vertex(n1, near_n2):
+ # n1.set_xy(near_n2[0], near_n2[1])
+ # elif mesh_analysis.is_star_vertex(n1, np.array([n1.x(), n1.y()])):
+ # pass
+ # elif mesh_analysis.is_star_vertex(n1, np.array([n2x, n2y])):
+ # n1.set_xy(n2x, n2y)
+ # else:
+ # plot_mesh(mesh_before)
+ # plot_mesh(mesh_analysis.mesh)
+ # mesh_analysis.is_star_vertex(n1, np.array([n1.x(), n1.y()]), True)
+ # raise ValueError("No star vertex found")
+
+ # Update dart quality
+ n1_analysis = NodeAnalysis(n1)
+ adj_darts = n1_analysis.adjacent_darts()
+ d_updated = []
+ for _d in adj_darts:
+ _d2 = _d.get_beta(2)
+ _d1 = _d.get_beta(1)
+ _d12 = _d1.get_beta(2)
+ _d11 = _d1.get_beta(1)
+ _d112 = _d11.get_beta(2)
+ # if d2, d12 or d112 is None, dart quality is -1 and was not modified by collapse action
+ if _d2 is not None and _d2.id not in d_updated:
+ _d.set_quality(mesh_analysis.get_dart_geometric_quality(_d, mesh_before))
+ d_updated.append(_d.id)
+ if _d12 is not None and _d12.id not in d_updated:
+ _d1.set_quality(mesh_analysis.get_dart_geometric_quality(_d1, mesh_before))
+ d_updated.append(_d1.id)
+ if _d112 is not None and _d112.id not in d_updated:
+ _d11.set_quality(mesh_analysis.get_dart_geometric_quality(_d11))
+ d_updated.append(_d11.id)
+
+ after_check = check_mesh(mesh_analysis, mesh_before)
+ if not after_check:
+ # mesh_analysis.is_star_vertex(n1, np.array([n1.x(), n1.y()]), True)
+ raise ValueError("Some checks are missing")
+ return True, topo, geo
- return mesh_check(mesh), topo, geo
+def check_mesh(mesh_analysis, m=None) -> bool:
+ for dart_info in mesh_analysis.mesh.active_darts():
+ #Check beta2 relation
+ d = dart_info[0]
+ d2 = dart_info[2]
+ # if associated twin dart no longer exist
+ if d2 >= 0 and mesh_analysis.mesh.dart_info[d2, 0] < 0:
+ return False
+ # if beta2 relation is not symetrical
+ elif d2 >= 0 and mesh_analysis.mesh.dart_info[d2, 2] != d:
+ return False
+
+ # null dart
+ elif d2>=0 and mesh_analysis.mesh.dart_info[d2, 3] == mesh_analysis.mesh.dart_info[d, 3]:
+ return False
+ #if adjacent face is the same
+ elif d2>=0 and mesh_analysis.mesh.dart_info[d2, 4] == mesh_analysis.mesh.dart_info[d, 4]:
+ return False
+
+
+ d1 = mesh_analysis.mesh.dart_info[d,1]
+ d11 = mesh_analysis.mesh.dart_info[d1,1]
+
+ #Check beta1
+ if mesh_analysis.mesh.dart_info[d11,1]!=d :
+ return False
+ #check if the quality is the same for twin darts
+ if d2>=0 and mesh_analysis.mesh.dart_info[d2,5] != mesh_analysis.mesh.dart_info[d, 5]:
+ plot_mesh(mesh_analysis.mesh)
+ return False
+ d = Dart(mesh_analysis.mesh, d)
+ if d2 >= 0 :
+ d2, d1, d11, d21, d211, n1, n2, n3, n4 = mesh_analysis.mesh.active_triangles(d)
+ if len(set([n1.id, n2.id, n3.id, n4.id])) < 4 and d.get_quality() != 3: # not flat faces
+ plot_mesh(m)
+ plot_mesh(mesh_analysis.mesh)
+ return False
+ if dart_info[5] != mesh_analysis.get_dart_geometric_quality(d):
+ plot_mesh(m)
+ plot_mesh(mesh_analysis.mesh)
+ return False
+ if dart_info[5] not in [-1,0,1,2]:
+ plot_mesh(m)
+ plot_mesh(mesh_analysis.mesh)
+ return False
+ return True
+
+#
+# def check_mesh_debug(mesh_analysis, mesh_before=None)->True:
+# for dart_info in mesh_analysis.mesh.active_darts():
+# #Check beta2 relation
+# d = dart_info[0]
+# d2 = dart_info[2]
+# # if associated twin dart no longer exist
+# if d2 >= 0 and mesh_analysis.mesh.dart_info[d2, 0] < 0:
+# plot_mesh(mesh_analysis.mesh)
+# if mesh_before is not None:
+# plot_mesh(mesh_before)
+# raise ValueError("error beta2")
+# # if beta2 relation is not symetrical
+# elif d2 >= 0 and mesh_analysis.mesh.dart_info[d2, 2] != d:
+# plot_mesh(mesh_analysis.mesh)
+# if mesh_before is not None:
+# plot_mesh(mesh_before)
+# raise ValueError("error beta2")
+# # null dart
+# elif d2>=0 and mesh_analysis.mesh.dart_info[d2, 3] == mesh_analysis.mesh.dart_info[d, 3]:
+# plot_mesh(mesh_analysis.mesh)
+# if mesh_before is not None:
+# plot_mesh(mesh_before)
+# raise ValueError("same node for twin darts")
+# #if adjacent face is the same
+# elif d2>=0 and mesh_analysis.mesh.dart_info[d2, 4] == mesh_analysis.mesh.dart_info[d, 4]:
+# plot_mesh(mesh_analysis.mesh)
+# if mesh_before is not None:
+# plot_mesh(mesh_before)
+# raise ValueError("same adjacent face")
+#
+#
+# d1 = mesh_analysis.mesh.dart_info[d,1]
+# d11 = mesh_analysis.mesh.dart_info[d1,1]
+#
+# #Check beta1
+# if mesh_analysis.mesh.dart_info[d11,1]!=d :
+# plot_mesh(mesh_analysis.mesh)
+# if mesh_before is not None:
+# plot_mesh(mesh_before)
+# raise ValueError("error beta1")
+#
+# if d2 >= 0 :
+# d = Dart(mesh_analysis.mesh, d)
+# d2, d1, d11, d21, d211, n1, n2, n3, n4 = mesh_analysis.mesh.active_triangles(d)
+#
+# if len(set([n1.id, n2.id, n3.id, n4.id])) < 4:
+# plot_mesh(mesh_analysis.mesh)
+# if mesh_before is not None:
+# plot_mesh(mesh_before)
+# raise ValueError("same traingle for two faces")
\ No newline at end of file
diff --git a/environment/gymnasium_envs/quadmesh_env/envs/mesh_conv.py b/environment/gymnasium_envs/quadmesh_env/envs/mesh_conv.py
index d6f4130..961d49a 100644
--- a/environment/gymnasium_envs/quadmesh_env/envs/mesh_conv.py
+++ b/environment/gymnasium_envs/quadmesh_env/envs/mesh_conv.py
@@ -1,23 +1,23 @@
import numpy as np
-from mesh_model.mesh_analysis.quadmesh_analysis import isValidAction
+from mesh_model.mesh_analysis.quadmesh_analysis import QuadMeshOldAnalysis
from mesh_model.mesh_struct.mesh_elements import Dart
from mesh_model.mesh_struct.mesh import Mesh
-def get_x(state: Mesh, n_darts_selected: int, deep :int, degree: bool, restricted:bool, nodes_scores: list[int], nodes_adjacency: list[int]):
- mesh = state
+def get_x(m_analysis, n_darts_selected: int, deep :int, degree: bool, restricted:bool, nodes_scores: list[int], nodes_adjacency: list[int]):
+ mesh = m_analysis.mesh
if degree:
deep = int(deep / 2)
- template, darts_id = get_template_boundary(mesh, deep, nodes_scores, nodes_adjacency)
+ template, darts_id = get_template_boundary(m_analysis, deep)
else:
- template, darts_id = get_template(mesh, deep, nodes_scores)
+ template, darts_id = get_template(m_analysis, deep)
if restricted:
darts_to_delete = []
darts_id = []
for i, d_info in enumerate(mesh.active_darts()):
d_id = d_info[0]
- if d_info[2] == -1 or not isValidAction(mesh, d_info[0], 4)[0]: # test the validity of all action type
+ if d_info[2] == -1 or not m_analysis.isValidAction(d_info[0], 4)[0]: # test the validity of all action type
darts_to_delete.append(i)
else:
darts_id.append(d_id)
@@ -31,17 +31,17 @@ def get_x(state: Mesh, n_darts_selected: int, deep :int, degree: bool, restricte
return X, np.array(valid_dart_ids)
-def get_template(mesh: Mesh, deep: int, nodes_scores):
- size = len(mesh.dart_info)
+def get_template(m_analysis, deep: int):
+ size = len(m_analysis.mesh.dart_info)
template = np.zeros((size, deep), dtype=np.int64)
dart_ids = []
n_darts = 0
- for d_info in mesh.active_darts():
+ for d_info in m_analysis.mesh.active_darts():
n_darts += 1
d_id = d_info[0]
dart_ids.append(d_id)
- d = Dart(mesh, d_id)
+ d = Dart(m_analysis.mesh, d_id)
A = d.get_node()
d1 = d.get_beta(1)
B = d1.get_node()
@@ -51,10 +51,10 @@ def get_template(mesh: Mesh, deep: int, nodes_scores):
D = d111.get_node()
# Template niveau 1
- template[n_darts - 1, 0] = nodes_scores[A.id]
- template[n_darts - 1, 1] = nodes_scores[B.id]
- template[n_darts - 1, 2] = nodes_scores[C.id]
- template[n_darts - 1, 3] = nodes_scores[D.id]
+ template[n_darts - 1, 0] = A.get_score()
+ template[n_darts - 1, 1] = B.get_score()
+ template[n_darts - 1, 2] = C.get_score()
+ template[n_darts - 1, 3] = D.get_score()
E = [A,B,C,D]
@@ -76,9 +76,9 @@ def get_template(mesh: Mesh, deep: int, nodes_scores):
F.append(df111)
N1, N2 = df11.get_node(), df111.get_node()
E.append(N1)
- template[n_darts-1, len(E)-1] = nodes_scores[N1.id]
+ template[n_darts-1, len(E)-1] = N1.get_score()
E.append(N2)
- template[n_darts - 1, len(E)-1] = nodes_scores[N2.id]
+ template[n_darts - 1, len(E)-1] = N2.get_score()
else:
E.extend([None,None])
#template[n_darts - 1, len(E) - 1] = -500 # dummy vertices are assigned to -500
@@ -88,17 +88,18 @@ def get_template(mesh: Mesh, deep: int, nodes_scores):
return template, dart_ids
-def get_template_deg(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
- size = len(mesh.dart_info)
+
+def get_template_boundary(m_analysis, deep: int):
+ size = len(m_analysis.mesh.dart_info)
template = np.zeros((size, deep*2), dtype=np.int64)
dart_ids = []
n_darts = 0
- for d_info in mesh.active_darts():
+ for d_info in m_analysis.mesh.active_darts():
n_darts += 1
d_id = d_info[0]
dart_ids.append(d_id)
- d = Dart(mesh, d_id)
+ d = Dart(m_analysis.mesh, d_id)
A = d.get_node()
d1 = d.get_beta(1)
B = d1.get_node()
@@ -108,14 +109,14 @@ def get_template_deg(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
D = d111.get_node()
# Template niveau 1
- template[n_darts - 1, 0] = nodes_scores[A.id]
- template[n_darts - 1, deep] = nodes_adjacency[A.id]
- template[n_darts - 1, 1] = nodes_scores[B.id]
- template[n_darts - 1, deep+1] = nodes_adjacency[B.id]
- template[n_darts - 1, 2] = nodes_scores[C.id]
- template[n_darts - 1, deep+2] = nodes_adjacency[C.id]
- template[n_darts - 1, 3] = nodes_scores[D.id]
- template[n_darts - 1, deep + 3] = nodes_adjacency[D.id]
+ template[n_darts - 1, 0] = A.get_score()
+ template[n_darts - 1, deep] = 1
+ template[n_darts - 1, 1] = B.get_score()
+ template[n_darts - 1, deep+1] = 1
+ template[n_darts - 1, 2] = C.get_score()
+ template[n_darts - 1, deep+2] = 1
+ template[n_darts - 1, 3] = D.get_score()
+ template[n_darts - 1, deep + 3] = 1
E = [A, B, C, D]
deep_captured = len(E)
@@ -136,11 +137,11 @@ def get_template_deg(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
F.append(df111)
N1, N2 = df11.get_node(), df111.get_node()
E.append(N1)
- template[n_darts-1, len(E)-1] = nodes_scores[N1.id]
- template[n_darts-1, deep + len(E)-1] = nodes_adjacency[N1.id]
+ template[n_darts-1, len(E)-1] = N1.get_score()
+ template[n_darts-1, deep + len(E)-1] = 1
E.append(N2)
- template[n_darts - 1, len(E)-1] = nodes_scores[N2.id]
- template[n_darts - 1, deep + len(E)-1] = nodes_adjacency[N2.id]
+ template[n_darts - 1, len(E)-1] = N2.get_score()
+ template[n_darts - 1, deep + len(E)-1] = 1
else:
E.extend([None,None])
#template[n_darts - 1, len(E) - 1] = -500 # dummy vertices are assigned to -500
@@ -149,17 +150,18 @@ def get_template_deg(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
template = template[:n_darts, :]
return template, dart_ids
-def get_template_boundary(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
- size = len(mesh.dart_info)
+
+def get_template_deg(m_analysis, deep: int, nodes_scores, nodes_adjacency):
+ size = len(m_analysis.mesh.dart_info)
template = np.zeros((size, deep*2), dtype=np.int64)
dart_ids = []
n_darts = 0
- for d_info in mesh.active_darts():
+ for d_info in m_analysis.mesh.active_darts():
n_darts += 1
d_id = d_info[0]
dart_ids.append(d_id)
- d = Dart(mesh, d_id)
+ d = Dart(m_analysis.mesh, d_id)
A = d.get_node()
d1 = d.get_beta(1)
B = d1.get_node()
@@ -169,14 +171,14 @@ def get_template_boundary(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
D = d111.get_node()
# Template niveau 1
- template[n_darts - 1, 0] = nodes_scores[A.id]
- template[n_darts - 1, deep] = 1
- template[n_darts - 1, 1] = nodes_scores[B.id]
- template[n_darts - 1, deep+1] = 1
- template[n_darts - 1, 2] = nodes_scores[C.id]
- template[n_darts - 1, deep+2] = 1
- template[n_darts - 1, 3] = nodes_scores[D.id]
- template[n_darts - 1, deep + 3] = 1
+ template[n_darts - 1, 0] = A.get_score()
+ template[n_darts - 1, deep] = nodes_adjacency[A.id]
+ template[n_darts - 1, 1] = B.get_score()
+ template[n_darts - 1, deep+1] = nodes_adjacency[B.id]
+ template[n_darts - 1, 2] = C.get_score()
+ template[n_darts - 1, deep+2] = nodes_adjacency[C.id]
+ template[n_darts - 1, 3] = D.get_score()
+ template[n_darts - 1, deep + 3] = nodes_adjacency[D.id]
E = [A, B, C, D]
deep_captured = len(E)
@@ -197,11 +199,11 @@ def get_template_boundary(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
F.append(df111)
N1, N2 = df11.get_node(), df111.get_node()
E.append(N1)
- template[n_darts-1, len(E)-1] = nodes_scores[N1.id]
- template[n_darts-1, deep + len(E)-1] = 1
+ template[n_darts-1, len(E)-1] = N1.get_score()
+ template[n_darts-1, deep + len(E)-1] = nodes_adjacency[N1.id]
E.append(N2)
- template[n_darts - 1, len(E)-1] = nodes_scores[N2.id]
- template[n_darts - 1, deep + len(E)-1] = 1
+ template[n_darts - 1, len(E)-1] = N2.get_score()
+ template[n_darts - 1, deep + len(E)-1] = nodes_adjacency[N2.id]
else:
E.extend([None,None])
#template[n_darts - 1, len(E) - 1] = -500 # dummy vertices are assigned to -500
diff --git a/environment/gymnasium_envs/quadmesh_env/envs/quadmesh.py b/environment/gymnasium_envs/quadmesh_env/envs/quadmesh.py
index 3be7753..2937045 100644
--- a/environment/gymnasium_envs/quadmesh_env/envs/quadmesh.py
+++ b/environment/gymnasium_envs/quadmesh_env/envs/quadmesh.py
@@ -1,4 +1,3 @@
-
import copy
import pygame
import imageio
@@ -13,8 +12,7 @@
from mesh_model.random_quadmesh import random_mesh
from mesh_model.mesh_struct.mesh_elements import Dart
-from mesh_model.mesh_analysis.global_mesh_analysis import global_score
-from mesh_model.mesh_analysis.quadmesh_analysis import isTruncated
+from mesh_model.mesh_analysis.quadmesh_analysis import QuadMeshOldAnalysis
from environment.gymnasium_envs.quadmesh_env.envs.mesh_conv import get_x
from environment.actions.quadrangular_actions import flip_edge_cntcw, flip_edge_cw, split_edge, collapse_edge, cleanup_edge
from environment.observation_register import ObservationRegistry
@@ -70,10 +68,10 @@ def __init__(
else :
self.config = {"mesh": None}
self.mesh = random_mesh()
-
+ self.mesh_analysis = QuadMeshOldAnalysis(self.mesh)
#self.mesh_size = len(self.mesh.nodes)
#self.nb_darts = len(self.mesh.dart_info)
- self._nodes_scores, self._mesh_score, self._ideal_score, self._nodes_adjacency = global_score(self.mesh)
+ self._nodes_scores, self._mesh_score, self._ideal_score, self._nodes_adjacency = self.mesh_analysis.global_score()
self._ideal_rewards = (self._mesh_score - self._ideal_score)*10 #arbitrary factor of 10 for rewards
self.next_mesh_score = 0
self.n_darts_selected = n_darts_selected
@@ -115,8 +113,8 @@ def __init__(
# Observation and action spaces
self.observation_space = gym.spaces.Box(
- low=-6, # nodes min degree : -6
- high=2, # nodes max degree : 2
+ low=-8, # nodes min degree : -6
+ high=4, # nodes max degree : 2
shape=(self.n_darts_selected, deep),
dtype=np.int64
)
@@ -125,8 +123,6 @@ def __init__(
# We have 4 actions, flip clockwise, flip counterclockwise, split, collapse
self.action_space = gym.spaces.MultiDiscrete([4, self.n_darts_selected])
-
-
def reset(self, seed=None, options=None):
# We need the following line to seed self.np_random
super().reset(seed=seed)
@@ -136,8 +132,10 @@ def reset(self, seed=None, options=None):
self.mesh = copy.deepcopy(self.config["mesh"])
else:
self.mesh = random_mesh()
+
+ self.mesh_analysis = QuadMeshOldAnalysis(self.mesh)
#self.nb_darts = len(self.mesh.dart_info)
- self._nodes_scores, self._mesh_score, self._ideal_score, self._nodes_adjacency = global_score(self.mesh)
+ self._nodes_scores, self._mesh_score, self._ideal_score, self._nodes_adjacency = self.mesh_analysis.global_score()
self._ideal_rewards = (self._mesh_score - self._ideal_score) * 10
self.nb_invalid_actions = 0
self.close()
@@ -161,9 +159,8 @@ def reset(self, seed=None, options=None):
return self.observation, info
-
def _get_obs(self):
- irregularities, darts_list = get_x(self.mesh, self.n_darts_selected, self.deep, self.degree_observation, self.restricted, self._nodes_scores, self._nodes_adjacency)
+ irregularities, darts_list = get_x(self.mesh_analysis, self.n_darts_selected, self.deep, self.degree_observation, self.restricted, self._nodes_scores, self._nodes_adjacency)
self.darts_selected = darts_list
return irregularities
@@ -187,6 +184,7 @@ def _get_info(self, terminated, valid_act, action, mesh_reward):
"invalid_collapse": 1.0 if action[0]==Actions.COLLAPSE.value and not valid_action else 0.0,
"invalid_cleanup": 1.0 if action[0]==Actions.CLEANUP.value and not valid_action else 0.0,
"mesh" : self.mesh,
+ "mesh_analysis" : self.mesh_analysis,
"darts_selected" : self.darts_selected,
"observation_registry" : self.observation_registry if self.observation_count else None,
}
@@ -209,19 +207,19 @@ def step(self, action: np.ndarray):
valid_action, valid_topo, valid_geo = False, False, False
if action[0] == Actions.FLIP_CW.value:
self.actions_info["n_flip_cw"] += 1
- valid_action, valid_topo, valid_geo = flip_edge_cw(self.mesh, n1, n2)
+ valid_action, valid_topo, valid_geo = flip_edge_cw(self.mesh_analysis, n1, n2)
elif action[0] == Actions.FLIP_CNTCW.value:
self.actions_info["n_flip_cntcw"] += 1
- valid_action, valid_topo, valid_geo = flip_edge_cntcw(self.mesh, n1, n2)
+ valid_action, valid_topo, valid_geo = flip_edge_cntcw(self.mesh_analysis, n1, n2)
elif action[0] == Actions.SPLIT.value:
self.actions_info["n_split"] += 1
- valid_action, valid_topo, valid_geo = split_edge(self.mesh, n1, n2)
+ valid_action, valid_topo, valid_geo = split_edge(self.mesh_analysis, n1, n2)
elif action[0] == Actions.COLLAPSE.value:
self.actions_info["n_collapse"] += 1
- valid_action, valid_topo, valid_geo = collapse_edge(self.mesh, n1, n2)
+ valid_action, valid_topo, valid_geo = collapse_edge(self.mesh_analysis, n1, n2)
elif action[0] == Actions.CLEANUP.value:
self.actions_info["n_cleanup"] += 1
- valid_action, valid_topo, valid_geo = cleanup_edge(self.mesh, n1, n2)
+ valid_action, valid_topo, valid_geo = cleanup_edge(self.mesh_analysis, n1, n2)
else:
raise ValueError("Action not defined")
@@ -230,7 +228,7 @@ def step(self, action: np.ndarray):
if valid_action:
# An episode is done if the actual score is the same as the ideal
- next_nodes_score, self.next_mesh_score, _, next_nodes_adjacency = global_score(self.mesh)
+ next_nodes_score, self.next_mesh_score, _, next_nodes_adjacency = self.mesh_analysis.global_score()
terminated = np.array_equal(self._ideal_score, self.next_mesh_score)
if terminated:
mesh_reward = (self._mesh_score - self.next_mesh_score)*10
@@ -254,7 +252,7 @@ def step(self, action: np.ndarray):
else:
raise ValueError("Invalid action")
if self.nb_invalid_actions > 10 :
- truncated = isTruncated(self.mesh, self.darts_selected)
+ truncated = self.mesh_analysis.isTruncated(self.darts_selected)
else:
truncated = False
valid_act = valid_action, valid_topo, valid_geo
@@ -271,7 +269,6 @@ def step(self, action: np.ndarray):
return self.observation, reward, terminated, truncated, info
-
def _render_frame(self):
if self.render_mode == "human" and self.window is None:
pygame.init()
diff --git a/environment/gymnasium_envs/quadmesh_env/wrappers/__init__.py b/environment/gymnasium_envs/quadmesh_env/wrappers/__init__.py
index c1fc21e..1a77df7 100644
--- a/environment/gymnasium_envs/quadmesh_env/wrappers/__init__.py
+++ b/environment/gymnasium_envs/quadmesh_env/wrappers/__init__.py
@@ -1,4 +1,4 @@
-from trimesh_env.wrappers.clip_reward import ClipReward
-from trimesh_env.wrappers.discrete_actions import DiscreteActions
-from trimesh_env.wrappers.reacher_weighted_reward import ReacherRewardWrapper
-from trimesh_env.wrappers.relative_position import RelativePosition
+from environment.gymnasium_envs.quadmesh_env.wrappers.clip_reward import ClipReward
+from environment.gymnasium_envs.quadmesh_env.wrappers.discrete_actions import DiscreteActions
+from environment.gymnasium_envs.quadmesh_env.wrappers.reacher_weighted_reward import ReacherRewardWrapper
+from environment.gymnasium_envs.quadmesh_env.wrappers.relative_position import RelativePosition
diff --git a/environment/gymnasium_envs/trimesh_full_env/__init__.py b/environment/gymnasium_envs/trimesh_full_env/__init__.py
index 063182b..76685b6 100644
--- a/environment/gymnasium_envs/trimesh_full_env/__init__.py
+++ b/environment/gymnasium_envs/trimesh_full_env/__init__.py
@@ -5,5 +5,5 @@
id="Trimesh-v0",
entry_point="environment.gymnasium_envs.trimesh_full_env.envs:TriMeshEnvFull",
max_episode_steps=100,
- kwargs={"mesh": None, "mesh_size": 30, "n_darts_selected": 20, "deep": 6, "with_degree_obs": True, "action_restriction": False},
+ kwargs={"mesh": None, "mesh_size": 7, "n_darts_selected": 7, "deep": 6, "with_quality_obs": True, "action_restriction": False},
)
diff --git a/environment/gymnasium_envs/trimesh_full_env/envs/mesh_conv.py b/environment/gymnasium_envs/trimesh_full_env/envs/mesh_conv.py
index e6cc4e4..27616dd 100644
--- a/environment/gymnasium_envs/trimesh_full_env/envs/mesh_conv.py
+++ b/environment/gymnasium_envs/trimesh_full_env/envs/mesh_conv.py
@@ -1,22 +1,21 @@
import numpy as np
-from mesh_model.mesh_analysis.trimesh_analysis import isValidAction, find_template_opposite_node
-from mesh_model.mesh_struct.mesh_elements import Dart
+from mesh_model.mesh_struct.mesh_elements import Dart, Node
from mesh_model.mesh_struct.mesh import Mesh
-def get_x(state: Mesh, n_darts_selected: int, deep :int, degree: bool, restricted:bool, nodes_scores: list[int], nodes_adjacency: list[int]):
- mesh = state
- if degree:
- template, darts_id = get_template_deg(mesh, deep, nodes_scores, nodes_adjacency)
+def get_x(m_analysis, n_darts_selected: int, deep :int, quality: bool, restricted:bool, nodes_scores: list[int], nodes_adjacency: list[int]):
+ mesh = m_analysis.mesh
+ if quality:
+ template, darts_id = get_template_with_quality(m_analysis, deep)
else:
- template, darts_id = get_template(mesh, deep, nodes_scores)
+ template, darts_id = get_template(m_analysis, deep, nodes_scores)
if restricted:
darts_to_delete = []
darts_id = []
for i, d_info in enumerate(mesh.active_darts()):
d_id = d_info[0]
- if d_info[2] == -1 or not isValidAction(mesh, d_info[0], 4)[0]: # test the validity of all action type
+ if d_info[2] == -1 or not m_analysis.isValidAction(d_info[0], 4)[0]: # test the validity of all action type
darts_to_delete.append(i)
else:
darts_id.append(d_id)
@@ -30,17 +29,17 @@ def get_x(state: Mesh, n_darts_selected: int, deep :int, degree: bool, restricte
return X, np.array(valid_dart_ids)
-def get_template(mesh: Mesh, deep: int, nodes_scores):
- size = len(mesh.dart_info)
+def get_template(m_analysis, deep: int, nodes_scores):
+ size = len(m_analysis.mesh.dart_info)
template = np.zeros((size, deep), dtype=np.int64)
dart_ids = []
n_darts = 0
- for d_info in mesh.active_darts():
+ for d_info in m_analysis.mesh.active_darts():
n_darts += 1
d_id = d_info[0]
dart_ids.append(d_id)
- d = Dart(mesh, d_id)
+ d = Dart(m_analysis.mesh, d_id)
A = d.get_node()
d1 = d.get_beta(1)
B = d1.get_node()
@@ -48,68 +47,81 @@ def get_template(mesh: Mesh, deep: int, nodes_scores):
C = d11.get_node()
# Template niveau 1
- template[n_darts - 1, 0] = nodes_scores[C.id]
- template[n_darts - 1, 1] = nodes_scores[A.id]
- template[n_darts - 1, 2] = nodes_scores[B.id]
+ template[n_darts - 1, 0] = C.get_score()
+ template[n_darts - 1, 1] = A.get_score()
+ template[n_darts - 1, 2] = B.get_score()
if deep>3:
# template niveau 2 deep = 6
- n_id = find_template_opposite_node(d)
+ n_id = m_analysis.find_template_opposite_node(d)
if n_id is not None:
- template[n_darts - 1, 3] = nodes_scores[n_id]
- n_id = find_template_opposite_node(d1)
+ template[n_darts - 1, 3] = n_id.get_score()
+ n_id = m_analysis.find_template_opposite_node(d1)
if n_id is not None:
- template[n_darts - 1, 4] = nodes_scores[n_id]
- n_id = find_template_opposite_node(d11)
+ template[n_darts - 1, 4] = n_id.get_score()
+ n_id = m_analysis.find_template_opposite_node(d11)
if n_id is not None:
- template[n_darts - 1, 5] = nodes_scores[n_id]
+ template[n_darts - 1, 5] = n_id.get_score()
if deep>6:
# template niveau 3 - deep = 12
- d2, d1, d11, d21, d211, n1, n2, n3, n4 = mesh.active_triangles(d)
+ d2, d1, d11, d21, d211, n1, n2, n3, n4 = m_analysis.mesh.active_triangles(d)
#Triangle F2
- n_id = find_template_opposite_node(d21)
+ n_id = m_analysis.find_template_opposite_node(d21)
if n_id is not None:
- template[n_darts - 1, 6] = nodes_scores[n_id]
- n_id = find_template_opposite_node(d211)
+ template[n_darts - 1, 6] = n_id.get_score()
+ n_id = m_analysis.find_template_opposite_node(d211)
if n_id is not None:
- template[n_darts - 1, 7] = nodes_scores[n_id]
+ template[n_darts - 1, 7] = n_id.get_score()
# Triangle T3
d12 = d1.get_beta(2)
d121 = d12.get_beta(1)
d1211 = d121.get_beta(1)
- n_id = find_template_opposite_node(d121)
+ n_id = m_analysis.find_template_opposite_node(d121)
if n_id is not None:
- template[n_darts - 1, 8] = nodes_scores[n_id]
- n_id = find_template_opposite_node(d1211)
+ template[n_darts - 1, 8] = n_id.get_score()
+ n_id = m_analysis.find_template_opposite_node(d1211)
if n_id is not None:
- template[n_darts - 1, 9] = nodes_scores[n_id]
+ template[n_darts - 1, 9] = n_id.get_score()
# Triangle T4
d112 = d11.get_beta(2)
d1121 = d112.get_beta(1)
d11211 = d1121.get_beta(1)
- n_id = find_template_opposite_node(d1121)
+ n_id = m_analysis.find_template_opposite_node(d1121)
if n_id is not None:
- template[n_darts - 1, 10] = nodes_scores[n_id]
- n_id = find_template_opposite_node(d11211)
+ template[n_darts - 1, 10] = n_id.get_score()
+ n_id = m_analysis.find_template_opposite_node(d11211)
if n_id is not None:
- template[n_darts - 1, 11] = nodes_scores[n_id]
+ template[n_darts - 1, 11] = n_id.get_score()
template = template[:n_darts, :]
return template, dart_ids
-def get_template_deg(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
- size = len(mesh.dart_info)
+def get_template_with_quality(m_analysis, deep: int):
+ """
+ Create a template matrix representing the entire mesh, composed of:
+
+ * Node scores: i.e. the difference between ideal adjacency and actual adjacency.
+ * Dart surrounding quality: a measure of the geometric quality around each dart.
+
+ Each column in the matrix corresponds to the local surrounding of a dart,
+ including the scores of its surrounding nodes and its associated quality.
+
+ :param m_analysis: mesh to analyze
+ :param deep: observation deep (how many nodes observed on each dart surrounding)
+ :return: template matrix
+ """
+ size = len(m_analysis.mesh.dart_info)
template = np.zeros((size, deep*2), dtype=np.int64)
dart_ids = []
n_darts = 0
- for d_info in mesh.active_darts():
+ for d_info in m_analysis.mesh.active_darts():
n_darts += 1
d_id = d_info[0]
dart_ids.append(d_id)
- d = Dart(mesh, d_id)
+ d = Dart(m_analysis.mesh, d_id)
A = d.get_node()
d1 = d.get_beta(1)
B = d1.get_node()
@@ -117,67 +129,76 @@ def get_template_deg(mesh: Mesh, deep: int, nodes_scores, nodes_adjacency):
C = d11.get_node()
# Template niveau 1
- template[n_darts - 1, 0] = nodes_scores[C.id]
- template[n_darts - 1, deep] = nodes_adjacency[C.id]
- template[n_darts - 1, 1] = nodes_scores[A.id]
- template[n_darts - 1, deep+1] = nodes_adjacency[A.id]
- template[n_darts - 1, 2] = nodes_scores[B.id]
- template[n_darts - 1, deep+2] = nodes_adjacency[B.id]
+ template[n_darts - 1, 0] = C.get_score()
+ template[n_darts - 1, deep] = d.get_quality()
+ template[n_darts - 1, 1] = A.get_score()
+ template[n_darts - 1, deep+1] = d1.get_quality()
+ template[n_darts - 1, 2] = B.get_score()
+ template[n_darts - 1, deep+2] = d11.get_quality()
if deep>3:
# template niveau 2
- n_id = find_template_opposite_node(d)
+ n_id = m_analysis.find_template_opposite_node(d)
if n_id is not None:
- template[n_darts - 1, 3] = nodes_scores[n_id]
- template[n_darts - 1, deep+3] = nodes_adjacency[n_id]
- n_id = find_template_opposite_node(d1)
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+3] = d.get_quality() #quality around dart d is equivalent to quality around dart d2
+ n_id = m_analysis.find_template_opposite_node(d1)
if n_id is not None:
- template[n_darts - 1, 4] = nodes_scores[n_id]
- template[n_darts - 1, deep+4] = nodes_adjacency[n_id]
- n_id = find_template_opposite_node(d11)
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+4] = d1.get_quality()
+ n_id = m_analysis.find_template_opposite_node(d11)
if n_id is not None:
- template[n_darts - 1, 5] = nodes_scores[n_id]
- template[n_darts - 1, deep+5] = nodes_adjacency[n_id]
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+5] = d11.get_quality()
if deep>6:
# template niveau 3 - deep = 12
if d.get_beta(2) is not None:
- d2, d1, d11, d21, d211, n1, n2, n3, n4 = mesh.active_triangles(d)
+ d2, d1, d11, d21, d211, n1, n2, n3, n4 = m_analysis.mesh.active_triangles(d)
#Triangle F2
- n_id = find_template_opposite_node(d21)
+ n_id = m_analysis.find_template_opposite_node(d21)
if n_id is not None:
- template[n_darts - 1, 6] = nodes_scores[n_id]
- template[n_darts - 1, deep+6] = nodes_adjacency[n_id]
- n_id = find_template_opposite_node(d211)
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+6] = d21.get_quality()
+ n_id = m_analysis.find_template_opposite_node(d211)
if n_id is not None:
- template[n_darts - 1, 7] = nodes_scores[n_id]
- template[n_darts - 1, deep+7] = nodes_adjacency[n_id]
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+7] = d211.get_quality()
# Triangle T3
d12 = d1.get_beta(2)
if d12 is not None:
d121 = d12.get_beta(1)
d1211 = d121.get_beta(1)
- n_id = find_template_opposite_node(d121)
+ n_id = m_analysis.find_template_opposite_node(d121)
if n_id is not None:
- template[n_darts - 1, 8] = nodes_scores[n_id]
- template[n_darts - 1, deep+8] = nodes_adjacency[n_id]
- n_id = find_template_opposite_node(d1211)
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+8] = d121.get_quality()
+ n_id = m_analysis.find_template_opposite_node(d1211)
if n_id is not None:
- template[n_darts - 1, 9] = nodes_scores[n_id]
- template[n_darts - 1, deep+9] = nodes_adjacency[n_id]
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+9] = d1211.get_quality()
# Triangle T4
d112 = d11.get_beta(2)
if d112 is not None:
d1121 = d112.get_beta(1)
d11211 = d1121.get_beta(1)
- n_id = find_template_opposite_node(d1121)
+ n_id = m_analysis.find_template_opposite_node(d1121)
if n_id is not None:
- template[n_darts - 1, 10] = nodes_scores[n_id]
- template[n_darts - 1, deep+10] = nodes_adjacency[n_id]
- n_id = find_template_opposite_node(d11211)
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+10] = d1121.get_quality()
+ n_id = m_analysis.find_template_opposite_node(d11211)
if n_id is not None:
- template[n_darts - 1, 11] = nodes_scores[n_id]
- template[n_darts - 1, deep+11] = nodes_adjacency[n_id]
+ n = Node(m_analysis.mesh, n_id)
+ template[n_darts - 1, 3] = n.get_score()
+ template[n_darts - 1, deep+11] = d11211.get_quality()
template = template[:n_darts, :]
return template, dart_ids
\ No newline at end of file
diff --git a/environment/gymnasium_envs/trimesh_full_env/envs/trimesh.py b/environment/gymnasium_envs/trimesh_full_env/envs/trimesh.py
index 6658c69..b097e05 100644
--- a/environment/gymnasium_envs/trimesh_full_env/envs/trimesh.py
+++ b/environment/gymnasium_envs/trimesh_full_env/envs/trimesh.py
@@ -1,19 +1,31 @@
-from enum import Enum
-import gymnasium as gym
-from gymnasium import spaces
+import copy
import pygame
+import imageio
+import sys
+import os
+
import numpy as np
+import gymnasium as gym
+
+from copy import deepcopy
+from enum import Enum
+
+from gymnasium import spaces
+from pygame.locals import *
+
from mesh_model.random_trimesh import random_mesh
from mesh_model.mesh_struct.mesh_elements import Dart
-from mesh_model.mesh_analysis.global_mesh_analysis import global_score
-from mesh_model.mesh_analysis.trimesh_analysis import isTruncated
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshQualityAnalysis, TriMeshOldAnalysis
from environment.gymnasium_envs.trimesh_full_env.envs.mesh_conv import get_x
-from environment.actions.triangular_actions import flip_edge, split_edge, collapse_edge
-
-from view.window import Game
+from environment.actions.triangular_actions import flip_edge, split_edge, collapse_edge, check_mesh
+from view.mesh_plotter.mesh_plots import plot_mesh
+from view.window import window_data, graph
from mesh_display import MeshDisplay
+#from view.window import Game
+#from mesh_display import MeshDisplay
+
class Actions(Enum):
FLIP = 0
@@ -24,27 +36,59 @@ class Actions(Enum):
class TriMeshEnvFull(gym.Env):
metadata = {"render_modes": ["human", "rgb_array"], "render_fps": 60}
- def __init__(self, mesh=None, mesh_size=16, n_darts_selected=20, deep=6, with_degree_obs=True, action_restriction=False, render_mode=None):
- self.mesh = mesh if mesh is not None else random_mesh(mesh_size)
- self.mesh_size = len(self.mesh.nodes)
- self.nb_darts = len(self.mesh.dart_info)
- self._nodes_scores, self._mesh_score, self._ideal_score, self._nodes_adjacency = global_score(self.mesh)
+ def __init__(
+ self,
+ mesh=None,
+ mesh_size=9,
+ max_episode_steps=20,
+ n_darts_selected=7,
+ deep=6,
+ with_quality_obs=False,
+ action_restriction=False,
+ render_mode=None,
+ analysis_type = "quality"
+ ) -> None:
+
+ assert render_mode is None or render_mode in self.metadata["render_modes"]
+ self.render_mode = render_mode
+
+ # If a mesh has been entered, it is used, otherwise a random mesh is generated.
+ if mesh is not None:
+ self.config = {"mesh": mesh}
+ self.mesh = copy.deepcopy(mesh)
+ self.mesh_size = 0
+ else:
+ self.config = {"mesh": None}
+ self.mesh_size = mesh_size
+ self.mesh = random_mesh(mesh_size)
+ self.analysis_type = analysis_type
+ self.m_analysis = TriMeshQualityAnalysis(self.mesh) if self.analysis_type == "quality" else TriMeshOldAnalysis(self.mesh)
+ self._nodes_scores, self._mesh_score, self._ideal_score, self._nodes_adjacency = self.m_analysis.global_score()
self._ideal_rewards = (self._mesh_score - self._ideal_score)*10
self.next_mesh_score = 0
self.deep = deep
self.n_darts_selected = n_darts_selected
self.restricted = action_restriction
- self.degree_observation = with_degree_obs
+ self.quality_observation = with_quality_obs
self.window_size = 512 # The size of the PyGame window
self.g = None
self.nb_invalid_actions = 0
self.darts_selected = [] # darts id observed
- deep = self.deep*2 if self.degree_observation else deep
+ self.episode_count = 0
+ self.ep_len = 0
+ self.darts_selected = []
+ self.max_steps = max_episode_steps
+
+ self.actions_info = {
+ "n_flip": 0,
+ "n_split": 0,
+ "n_collapse": 0,
+ }
self.observation_space = spaces.Box(
low=-15, # nodes min degree : 15
high=15, # nodes max degree : 15
- shape=(self.n_darts_selected, self.deep * 2 if self.degree_observation else self.deep),
+ shape=(self.n_darts_selected, self.deep * 2 if self.quality_observation else self.deep),
dtype=np.int64
)
@@ -53,9 +97,6 @@ def __init__(self, mesh=None, mesh_size=16, n_darts_selected=20, deep=6, with_de
# We have 3 action, flip, split, collapse
self.action_space = spaces.MultiDiscrete([3, self.n_darts_selected])
- assert render_mode is None or render_mode in self.metadata["render_modes"]
- self.render_mode = render_mode
-
"""
If human-rendering is used, `self.window` will be a reference
to the window that we draw to. `self.clock` will be a clock that is used
@@ -63,37 +104,63 @@ def __init__(self, mesh=None, mesh_size=16, n_darts_selected=20, deep=6, with_de
human-mode. They will remain `None` until human-mode is used for the
first time.
"""
- self.window = None
- self.clock = None
+ # Render
+ if self.render_mode == "human":
+ self.mesh_disp = MeshDisplay(self.mesh)
+ self.graph = graph.Graph(self.mesh_disp.get_nodes_coordinates(), self.mesh_disp.get_edges(),
+ self.mesh_disp.get_scores())
+ self.win_data = window_data()
+ self.window_size = 512 # The size of the PyGame window
+ self.window = None
+ self.clock = None
+
+ self.recording = False
+ self.frames = []
+ self._render_frame()
def reset(self, seed=None, options=None):
# We need the following line to seed self.np_random
super().reset(seed=seed)
if options is not None:
self.mesh = options['mesh']
+ elif self.config["mesh"] is not None:
+ self.mesh = copy.deepcopy(self.config["mesh"])
else:
self.mesh = random_mesh(self.mesh_size)
- self.nb_darts = len(self.mesh.dart_info)
- self._nodes_scores, self._mesh_score, self._ideal_score, self._nodes_adjacency = global_score(self.mesh)
+
+ self.m_analysis = TriMeshQualityAnalysis(self.mesh) if self.analysis_type=="quality" else TriMeshOldAnalysis(self.mesh)
+ self._nodes_scores, self._mesh_score, self._ideal_score, self._nodes_adjacency = self.m_analysis.global_score()
self._ideal_rewards = (self._mesh_score - self._ideal_score) * 10
self.nb_invalid_actions = 0
+ self.ep_len = 0
self.close()
self.observation = self._get_obs()
info = self._get_info(terminated=False,valid_act=(None,None,None), action=(None,None), mesh_reward=None)
+ self.actions_info = {
+ "n_flip": 0,
+ "n_split": 0,
+ "n_collapse": 0,
+ }
+
if self.render_mode == "human":
+ self.recording = True
self._render_frame()
+ else:
+ self.recording = False
return self.observation, info
def _get_obs(self):
- irregularities, darts_list = get_x(self.mesh, self.n_darts_selected, self.deep, self.degree_observation, self.restricted, self._nodes_scores, self._nodes_adjacency)
+ irregularities, darts_list = get_x(self.m_analysis, self.n_darts_selected, self.deep, self.quality_observation, self.restricted, self._nodes_scores, self._nodes_adjacency)
self.darts_selected = darts_list
return irregularities
def _get_info(self, terminated, valid_act, action, mesh_reward):
valid_action, valid_topo, valid_geo = valid_act
+ if self._mesh_score - self._ideal_score <0:
+ raise ValueError("score impossible")
return {
"distance": self._mesh_score - self._ideal_score,
"mesh_reward" : mesh_reward,
@@ -108,7 +175,9 @@ def _get_info(self, terminated, valid_act, action, mesh_reward):
"invalid_flip": 1.0 if action[0]==Actions.FLIP.value and not valid_action else 0.0,
"invalid_split": 1.0 if action[0]==Actions.SPLIT.value and not valid_action else 0.0,
"invalid_collapse": 1.0 if action[0]==Actions.COLLAPSE.value and not valid_action else 0.0,
- "mesh" : self.mesh,
+ "mesh" : self.m_analysis.mesh,
+ "mesh_analysis": self.m_analysis,
+ "darts_selected": self.darts_selected,
}
def _action_to_dart_id(self, action: np.ndarray) -> int:
@@ -120,45 +189,50 @@ def _action_to_dart_id(self, action: np.ndarray) -> int:
return self.darts_selected[int(action[1])]
def step(self, action: np.ndarray):
+ self.ep_len+=1
dart_id = self._action_to_dart_id(action)
d = Dart(self.mesh, dart_id)
d1 = d.get_beta(1)
n1 = d.get_node()
n2 = d1.get_node()
valid_action, valid_topo, valid_geo = False, False, False
-
+ # before_mesh = deepcopy(self.mesh)
if action[0] == Actions.FLIP.value:
- valid_action, valid_topo, valid_geo = flip_edge(self.mesh, n1, n2)
+ valid_action, valid_topo, valid_geo = flip_edge(self.m_analysis, n1, n2)
+ self.actions_info["n_flip"] += 1
elif action[0] == Actions.SPLIT.value:
- valid_action, valid_topo, valid_geo = split_edge(self.mesh, n1, n2)
+ valid_action, valid_topo, valid_geo = split_edge(self.m_analysis, n1, n2)
+ self.actions_info["n_split"] += 1
elif action[0] == Actions.COLLAPSE.value:
- valid_action, valid_topo, valid_geo = collapse_edge(self.mesh, n1, n2)
+ valid_action, valid_topo, valid_geo = collapse_edge(self.m_analysis, n1, n2)
+ self.actions_info["n_collapse"] += 1
else:
raise ValueError("Action not defined")
if valid_action:
+ next_nodes_score, self.next_mesh_score, _, next_nodes_adjacency = self.m_analysis.global_score()
# An episode is done if the actual score is the same as the ideal
- next_nodes_score, self.next_mesh_score, _, next_nodes_adjacency = global_score(self.mesh)
terminated = np.array_equal(self._ideal_score, self.next_mesh_score)
mesh_reward = (self._mesh_score - self.next_mesh_score)*10
+ # if mesh_reward == 10: # it should be impossible to improve only one irregularity
+ # b_mesh_analysis = TriMeshTopoAnalysis(before_mesh)
+ # plot_mesh(before_mesh)
+ # plot_mesh(self.mesh)
+ # bool1 = check_mesh(b_mesh_analysis)
+ # bool2 = check_mesh(self.m_analysis)
reward = mesh_reward
self._nodes_scores, self._mesh_score, self._nodes_adjacency = next_nodes_score, self.next_mesh_score, next_nodes_adjacency
self.observation = self._get_obs()
self.nb_invalid_actions = 0
- elif not valid_topo:
+ elif not valid_topo or not valid_geo:
reward = -10
mesh_reward = 0
terminated = False
self.nb_invalid_actions += 1
- elif not valid_geo:
- mesh_reward = 0
- terminated = False
- reward = 0
- self.nb_invalid_actions += 1
else:
raise ValueError("Invalid action")
if self.nb_invalid_actions > 10 :
- truncated = isTruncated(self.mesh, self.darts_selected)
+ truncated = self.m_analysis.isTruncated(self.darts_selected)
else:
truncated = False
valid_act = valid_action, valid_topo, valid_geo
@@ -166,30 +240,91 @@ def step(self, action: np.ndarray):
if self.render_mode == "human":
self._render_frame()
+ #Saving episode rendering as gif
+ if terminated or self.ep_len>= self.max_steps:
+ if self.recording and self.frames:
+ base_path = f"training/episode_recording/del/episode_star_{self.episode_count}"
+ filename = base_path + ".gif"
+ index = 1
+ while os.path.exists(filename):
+ filename = f"{base_path}_{index}.gif"
+ index += 1
- return self.observation, reward, terminated, truncated, info
+ imageio.mimsave(filename, self.frames, fps=1)
+ print("Image recorded")
+ self.episode_count +=1
- def render(self):
- if self.render_mode == "human":
- return self._render_frame()
+ return self.observation, reward, terminated, truncated, info
def _render_frame(self):
- if self.g is None and self.render_mode == "human":
- mesh_disp = MeshDisplay(self.mesh)
- self.g = Game(self.mesh, mesh_disp)
- self.window = True
- self.g.control_events()
- self.g.window.fill((255, 255, 255))
- self.g.draw()
- pygame.display.flip()
- if self.clock is None and self.render_mode == "human":
+ if self.render_mode == "human" and self.window is None:
+ pygame.init()
+ pygame.display.init()
+ self.window = pygame.display.set_mode(self.win_data.size, self.win_data.options)
+ pygame.display.set_caption('QuadMesh')
+ self.window.fill((255, 255, 255))
+ self.font = pygame.font.SysFont(None, self.win_data.font_size)
self.clock = pygame.time.Clock()
- if self.render_mode == "human":
- self.g.mesh_disp = MeshDisplay(self.mesh)
- self.g.control_events()
+ self.clock.tick(60)
+ self.win_data.scene_xmin, self.win_data.scene_ymin, self.win_data.scene_xmax, self.win_data.scene_ymax = self.graph.bounding_box()
+ self.win_data.scene_center = pygame.math.Vector2((self.win_data.scene_xmax + self.win_data.scene_xmin) / 2.0,
+ (self.win_data.scene_ymax + self.win_data.scene_ymin) / 2.0)
+
+ pygame.event.pump()
+ self.window.fill((255, 255, 255)) # white
+ for event in pygame.event.get():
+ if event.type == QUIT:
+ pygame.quit()
+ sys.exit()
+
+ if event.type == VIDEORESIZE or event.type == VIDEOEXPOSE: # handles window minimising/maximising
+ x, y = self.window.get_size()
+ text_margin = 200
+ self.win_data.center.x = (x - text_margin) / 2
+ self.win_data.center.y = y / 2
+ ratio = float(x - text_margin) / float(self.win_data.scene_xmax - self.win_data.scene_xmin)
+ ratio_y = float(y) / float(self.win_data.scene_ymax - self.win_data.scene_ymin)
+ if ratio_y < ratio:
+ ratio = ratio_y
+
+ self.win_data.node_size = max(ratio / 100, 10)
+ self.win_data.stretch = 0.75 * ratio
+
+ self.window.fill((255, 255, 255))
+ pygame.display.flip()
+
+ self.graph.clear()
+ self.mesh_disp = MeshDisplay(self.mesh)
+ self.graph.update(self.mesh_disp.get_nodes_coordinates(), self.mesh_disp.get_edges(),
+ self.mesh_disp.get_scores())
+
+ #Draw mesh
+ for e in self.graph.edges:
+ e.draw(self.window, self.win_data)
+ for n in self.graph.vertices:
+ n.draw(self.window, self.font, self.win_data)
+
+ #Print action type
+ if hasattr(self, 'actions_info'):
+ x = self.window.get_width() - 150
+ y_start = 100
+ line_spacing = 25
+
+ for i, (action_name, count) in enumerate(self.actions_info.items()):
+ text = f"{action_name}: {count}"
+ text_surface = self.font.render(text, True, (0, 0, 0))
+ self.window.blit(text_surface, (x, y_start + i * line_spacing))
+
+ self.clock.tick(60)
+ pygame.time.delay(1200)
+ pygame.display.flip()
+ if self.recording:
+ pixels = pygame.surfarray.array3d(pygame.display.get_surface())
+ frame = pixels.transpose([1,0,2])
+ self.frames.append(frame)
def close(self):
- if self.window is not None:
+ if self.render_mode=="human" and self.window is not None:
pygame.display.quit()
pygame.quit()
- self.g = None
+ self.window = None
diff --git a/environment/environment_config.json b/environment/old_files/environment_config.json
similarity index 51%
rename from environment/environment_config.json
rename to environment/old_files/environment_config.json
index 8ee4646..db6e82a 100644
--- a/environment/environment_config.json
+++ b/environment/old_files/environment_config.json
@@ -1,9 +1,9 @@
{
- "env_name": "Quadmesh-v0",
- "mesh_size": 16,
+ "env_name": "Trimesh-v0",
+ "mesh_size": 10,
"max_episode_steps": 20,
- "n_darts_selected": 10,
- "deep": 8,
+ "n_darts_selected": 11,
+ "deep": 6,
"action_restriction": false,
"with_degree_observation": false
}
\ No newline at end of file
diff --git a/environment/eval_environment_config.json b/environment/old_files/eval_environment_config.json
similarity index 100%
rename from environment/eval_environment_config.json
rename to environment/old_files/eval_environment_config.json
diff --git a/environment/trimesh_env.py b/environment/old_files/trimesh_env.py
similarity index 100%
rename from environment/trimesh_env.py
rename to environment/old_files/trimesh_env.py
diff --git a/mesh_display.py b/mesh_display.py
index 0d21e38..6b816df 100644
--- a/mesh_display.py
+++ b/mesh_display.py
@@ -1,5 +1,5 @@
from mesh_model.mesh_struct.mesh import Mesh
-from mesh_model.mesh_analysis.global_mesh_analysis import global_score
+from mesh_model.mesh_analysis.global_mesh_analysis import GlobalMeshAnalysis
class MeshDisplay:
@@ -35,5 +35,6 @@ def get_scores(self):
Calculates the irregularities of each node and the real and ideal score of the mesh
:return: a list of three elements (nodes_score, mesh_score, ideal_mesh_score)
"""
- nodes_score, mesh_score, ideal_mesh_score, adjacency = global_score(self.mesh)
+ ma = GlobalMeshAnalysis(self.mesh)
+ nodes_score, mesh_score, ideal_mesh_score, adjacency = ma.global_score()
return [nodes_score, mesh_score, ideal_mesh_score]
diff --git a/mesh_files/tri-delaunay.msh b/mesh_files/tri-delaunay.msh
new file mode 100644
index 0000000..9497d75
--- /dev/null
+++ b/mesh_files/tri-delaunay.msh
@@ -0,0 +1,125 @@
+$MeshFormat
+4.1 0 8
+$EndMeshFormat
+$Entities
+4 4 1 0
+2 3 0 0 0
+3 1 2 0 0
+4 1 -2 0 0
+6 -1 0 0 0
+1 -1 0 0 1 2 0 0 2 3 -6
+2 -1 -2 0 1 0 0 0 2 6 -4
+3 1 -2 0 3 0 0 0 2 4 -2
+4 1 0 0 3 2 0 0 2 2 -3
+1 -1 -2 0 3 2 0 0 4 1 2 3 4
+$EndEntities
+$Nodes
+9 21 1 21
+0 2 0 1
+1
+3 0 0
+0 3 0 1
+2
+1 2 0
+0 4 0 1
+3
+1 -2 0
+0 6 0 1
+4
+-1 0 0
+1 1 0 2
+5
+6
+0.3333333333351847 1.333333333335185 0
+-0.3333333333310193 0.6666666666689807 0
+1 2 0 2
+7
+8
+-0.3333333333350901 -0.6666666666649099 0
+0.3333333333315289 -1.333333333331529 0
+1 3 0 2
+9
+10
+1.666666666666666 -1.333333333333334 0
+2.333333333332406 -0.6666666666675944 0
+1 4 0 2
+11
+12
+2.333333333336016 0.6666666666639838 0
+1.666666666669397 1.333333333330603 0
+2 1 0 9
+13
+14
+15
+16
+17
+18
+19
+20
+21
+1.000000000000195 -2.053357484044227e-13 0
+1.833333333333501 -4.514097429197325e-13 0
+0.1666666666669092 5.088429677603714e-13 0
+1.000000000000573 0.8333333333331049 0
+0.9999999999997741 -0.8333333333337288 0
+1.65476190476127 -0.6547619047618515 0
+0.3452380952395821 0.6547619047612705 0
+0.3452380952388717 -0.6547619047606879 0
+1.654761904761082 0.6547619047601926 0
+$EndNodes
+$Elements
+9 44 1 44
+0 2 15 1
+1 1
+0 3 15 1
+2 2
+0 4 15 1
+3 3
+0 6 15 1
+4 4
+1 1 1 3
+5 2 5
+6 5 6
+7 6 4
+1 2 1 3
+8 4 7
+9 7 8
+10 8 3
+1 3 1 3
+11 3 9
+12 9 10
+13 10 1
+1 4 1 3
+14 1 11
+15 11 12
+16 12 2
+2 1 2 28
+17 1 11 14
+18 10 1 14
+19 6 4 15
+20 12 2 16
+21 2 5 16
+22 4 7 15
+23 3 9 17
+24 8 3 17
+25 14 13 18
+26 15 13 19
+27 13 16 19
+28 13 17 18
+29 13 15 20
+30 13 14 21
+31 16 13 21
+32 17 13 20
+33 11 12 21
+34 7 8 20
+35 5 6 19
+36 9 10 18
+37 14 11 21
+38 16 5 19
+39 15 7 20
+40 10 14 18
+41 17 9 18
+42 6 15 19
+43 12 16 21
+44 8 17 20
+$EndElements
diff --git a/mesh_files/tri-easy.msh b/mesh_files/tri-easy.msh
new file mode 100644
index 0000000..04b605a
--- /dev/null
+++ b/mesh_files/tri-easy.msh
@@ -0,0 +1,109 @@
+$MeshFormat
+4.1 0 8
+$EndMeshFormat
+$Entities
+4 4 1 0
+2 2 0 0 0
+3 1 2 0 0
+4 1 -2 0 0
+6 0 0 0 0
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diff --git a/mesh_files/tri-medium.msh b/mesh_files/tri-medium.msh
new file mode 100644
index 0000000..bbf4f17
--- /dev/null
+++ b/mesh_files/tri-medium.msh
@@ -0,0 +1,93 @@
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+$EndMeshFormat
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diff --git a/mesh_files/tri-star.msh b/mesh_files/tri-star.msh
new file mode 100644
index 0000000..4c4791e
--- /dev/null
+++ b/mesh_files/tri-star.msh
@@ -0,0 +1,73 @@
+$MeshFormat
+4.1 0 8
+$EndMeshFormat
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+$EndEntities
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+$EndElements
diff --git a/mesh_model/mesh_analysis/global_mesh_analysis.py b/mesh_model/mesh_analysis/global_mesh_analysis.py
index 3553c6d..ab3eea6 100644
--- a/mesh_model/mesh_analysis/global_mesh_analysis.py
+++ b/mesh_model/mesh_analysis/global_mesh_analysis.py
@@ -1,301 +1,297 @@
-from math import sqrt, degrees, acos
import numpy as np
+from math import sqrt, degrees, acos, atan2
+from abc import ABC, abstractmethod
from mesh_model.mesh_struct.mesh_elements import Dart, Node, Face
from mesh_model.mesh_struct.mesh import Mesh
from view.mesh_plotter.mesh_plots import plot_mesh
-def global_score(m: Mesh):
- """
- Calculate the overall mesh score. The mesh cannot achieve a better score than the ideal one.
- And the current score is the mesh score.
- :param m: the mesh to be analyzed
- :return: 4 return: a list of the nodes score, the current mesh score and the ideal mesh score, and the adjacency
- """
- mesh_ideal_score = 0
- mesh_score = 0
- nodes_score = []
- nodes_adjacency = []
- for i in range(len(m.nodes)):
- if m.nodes[i, 2] >= 0:
- n_id = i
- node = Node(m, n_id)
- n_score, adjacency= score_calculation(node)
- nodes_score.append(n_score)
- nodes_adjacency.append(adjacency)
- mesh_ideal_score += n_score
- mesh_score += abs(n_score)
- else:
- nodes_score.append(0)
- nodes_adjacency.append(6)
- return nodes_score, mesh_score, mesh_ideal_score, nodes_adjacency
-
+class NodeAnalysis:
+ def __init__(self, n: Node):
+ self.n = n
+
+ def score_calculation(self) -> int:
+ """
+ Function to calculate the irregularity of a node in the mesh.
+ :param n: a node in the mesh.
+ :return: the irregularity of the node
+ :raises ValueError: if the node is associated to no dart
+ """
+
+ d = self.n.get_dart()
+ if d.mesh.dart_info[d.id,0] < 0:
+ raise ValueError("No existing dart")
+
+ adjacency = self.degree()
+ ideal_adjacency =self.n.get_ideal_adjacency()
+
+ return ideal_adjacency - adjacency
+
+ def get_angle(self, d1: Dart, d2: Dart) -> float:
+ """
+ Function to calculate the angle of the boundary at the node n.
+ The angle is named ABC and node self.n is at point A.
+ :param d1: the first boundary dart.
+ :param d2: the second boundary dart.
+ :return: the angle (degrees)
+ """
+ if d1.get_node() == self.n:
+ A = self.n
+ B = d1.get_beta(1).get_node()
+ C = d2.get_node()
-def score_calculation(n: Node) -> (int, int):
- """
- Function to calculate the irregularity of a node in the mesh.
- :param n: a node in the mesh.
- :return: the irregularity of the node
- """
- adjacency = degree(n)
- # Check if the mesh is triangular or quad
- d = n.get_dart()
- if d.id <0:
- raise ValueError("No existing dart")
- d1 = d.get_beta(1)
- d11 = d1.get_beta(1)
- d111 = d11.get_beta(1)
- triangular = (d111.id == d.id)
- if on_boundary(n):
- angle = get_boundary_angle(n)
- if triangular:
- ideal_adjacency = max(round(angle/60)+1, 2)
else:
- ideal_adjacency = max(round(angle/90)+1, 2)
- elif triangular:
- ideal_adjacency = 360/60
- else:
- ideal_adjacency = 360/90
+ A = self.n
+ B = d2.get_beta(1).get_node()
+ C = d1.get_node()
+ if d2.get_node() != A:
+ raise ValueError("Angle error")
- return ideal_adjacency-adjacency, adjacency
+ vect_AB = (B.x() - A.x(), B.y() - A.y())
+ vect_AC = (C.x() - A.x(), C.y() - A.y())
-def get_angle(d1: Dart, d2: Dart, n: Node) -> float:
- """
- Function to calculate the angle of the boundary at the node n.
- The angle is named ABC and node n is at point A.
- :param d1: the first boundary dart.
- :param d2: the second boundary dart.
- :param n: the boundary node
- :return: the angle (degrees)
- """
- if d1.get_node() == n:
- A = n
- B = d1.get_beta(1).get_node()
- C = d2.get_node()
-
- else:
- A = n
- B = d2.get_beta(1).get_node()
- C = d1.get_node()
- if d2.get_node() != A:
- raise ValueError("Angle error")
+ dot = vect_AB[0] * vect_AC[0] + vect_AB[1] * vect_AC[1]
- vect_AB = (B.x() - A.x(), B.y() - A.y())
- vect_AC = (C.x() - A.x(), C.y() - A.y())
- dist_AB = sqrt(vect_AB[0]**2 + vect_AB[1]**2)
- dist_AC = sqrt(vect_AC[0]**2 + vect_AC[1]**2)
- cos_theta = np.dot(vect_AB, vect_AC)/(dist_AB*dist_AC)
- cos_theta = np.clip(cos_theta, -1, 1)
- angle = np.arccos(cos_theta)
- if np.isnan(angle):
- plot_mesh(n.mesh)
- raise ValueError("Angle error")
- return degrees(angle)
-
-def angle_from_sides(a, b, c):
- # Calculate angle A, with a the opposite side and b and c the adjacent sides
- cosA = (b**2 + c**2 - a**2) / (2 * b * c)
- if 1 <= cosA < 1.01:
- cosA = 1
- elif -1.01 <= cosA < -1:
- cosA = -1
- elif cosA > 1.01 or cosA < -1.01:
- raise ValueError("Math domain error : cos>1.01")
- return acos(cosA)
-
-def get_angle_by_coord(x1: float, y1: float, x2: float, y2: float, x3:float, y3:float) -> float:
- BAx, BAy = x1 - x2, y1 - y2
- BCx, BCy = x3 - x2, y3 - y2
-
- cos_ABC = (BAx * BCx + BAy * BCy) / (sqrt(BAx ** 2 + BAy ** 2) * sqrt(BCx ** 2 + BCy ** 2))
- cos_ABC = np.clip(cos_ABC, -1, 1)
- rad = acos(cos_ABC)
- deg = degrees(rad)
- return deg
-
-def get_boundary_angle(n: Node) -> float:
- """
- Calculate the boundary angle of a node in the mesh.
- :param n: a boundary node
- :return: the boundary angle (degrees)
- """
- adj_darts_list = adjacent_darts(n)
- boundary_darts = []
- for d in adj_darts_list:
- d_twin = d.get_beta(2)
- if d_twin is None:
- boundary_darts.append(d)
- if len(boundary_darts) > 7:
- raise ValueError("Boundary error")
- angle = get_angle(boundary_darts[0], boundary_darts[1], n)
- return angle
-
-
-def on_boundary(n: Node) -> bool:
- """
- Test if the node n is on boundary.
- :param n: a node in the mesh.
- :return: True if the node n is on boundary, False otherwise.
- """
- adj_darts_list = adjacent_darts(n)
- for d in adj_darts_list:
- d_twin = d.get_beta(2)
- if d_twin is None:
- return True
- return False
+ # cross product
+ cross = vect_AB[0] * vect_AC[1] - vect_AB[1] * vect_AC[0]
+ angle_rad = atan2(cross, dot)
+ angle = degrees(angle_rad) % 360
+ if np.isnan(angle):
+ raise ValueError("Angle error")
+ return angle
+
+ def get_boundary_angle(self) -> float:
+ """
+ Calculate the boundary angle of a node in the mesh.
+ :return: the boundary angle (degrees)
+ """
+ adj_darts_list = self.adjacent_darts()
+ boundary_darts = []
+ for d in adj_darts_list:
+ d_twin = d.get_beta(2)
+ if d_twin is None:
+ boundary_darts.append(d)
+ #if len(boundary_darts) > 2 : # or len(boundary_darts) < 2
+ #plot_mesh(self.n.mesh)
+ #raise ValueError("Boundary error")
+ angle = self.get_angle(boundary_darts[0], boundary_darts[1])
+ return angle
+
+ def on_boundary(self) -> bool:
+ """
+ Test if the node self.n is on boundary.
+ :return: True if the node n is on boundary, False otherwise.
+ """
+ adj_darts_list = self.adjacent_darts()
+ for d in adj_darts_list:
+ d_twin = d.get_beta(2)
+ if d_twin is None:
+ return True
+ return False
-def adjacent_darts(n: Node) -> list[Dart]:
- """
- Function that retrieve the adjacent darts of node n.
- :param n: a node in the mesh.
- :return: the list of adjacent darts
- """
- adj_darts = []
- for d_info in n.mesh.active_darts():
- d = Dart(n.mesh, d_info[0])
- d_nfrom = d.get_node()
- d_nto = d.get_beta(1)
- if d_nfrom == n and d not in adj_darts:
- adj_darts.append(d)
- if d_nto.get_node() == n and d not in adj_darts:
- adj_darts.append(d)
- return adj_darts
-
-def adjacent_faces_id(n: Node) -> list[int]:
- adj_darts = adjacent_darts(n)
- adj_faces = []
- for d in adj_darts:
- f = d.get_face()
- if f.id not in adj_faces:
- adj_faces.append(f.id)
- return adj_faces
-
-
-def degree(n: Node) -> int:
- """
- Function to calculate the degree of a node in the mesh.
- :param n: a node in the mesh.
- :return: the degree of the node
- """
- adj_darts_list = adjacent_darts(n)
- adjacency = 0
- b = on_boundary(n)
- boundary_darts = []
- for d in adj_darts_list:
- d_twin = d.get_beta(2)
- if d_twin is None and b:
- adjacency += 1
- boundary_darts.append(d)
+ def adjacent_darts(self) -> list[Dart]:
+ """
+ Function that retrieve the adjacent darts of node n.
+ :return: the list of adjacent darts
+ """
+ adj_darts = []
+ m = self.n.mesh
+ for d_info in m.active_darts():
+ d = Dart(m, d_info[0])
+ d_nfrom = d.get_node()
+ d_nto = d.get_beta(1)
+ if d_nfrom == self.n and d not in adj_darts:
+ adj_darts.append(d)
+ if d_nto.get_node() == self.n and d not in adj_darts:
+ adj_darts.append(d)
+ return adj_darts
+
+ def adjacent_faces_id(self) -> list[int]:
+ adj_darts = self.adjacent_darts()
+ adj_faces = []
+ for d in adj_darts:
+ f = d.get_face()
+ if f.id not in adj_faces:
+ adj_faces.append(f.id)
+ return adj_faces
+
+ def degree(self) -> int:
+ """
+ Function to calculate the degree of a node in the mesh.
+ :return: the degree of the node
+ """
+ adj_darts_list = self.adjacent_darts()
+ adjacency = 0
+ b = self.on_boundary()
+ boundary_darts = []
+ for d in adj_darts_list:
+ d_twin = d.get_beta(2)
+ if d_twin is None and b:
+ adjacency += 1
+ boundary_darts.append(d)
+ else:
+ adjacency += 0.5
+ if adjacency != int(adjacency):
+ raise ValueError("Adjacency error")
+ return adjacency
+
+ def test_degree(self) -> bool:
+ """
+ Verify that the degree of a vertex is lower than 10
+ :return: True if the degree is lower than 10, False otherwise
+ """
+ if self.degree() >= 10:
+ return False
else:
- adjacency += 0.5
- if adjacency != int(adjacency):
- raise ValueError("Adjacency error")
- return adjacency
-
-
-def get_boundary_darts(m: Mesh) -> list[Dart]:
- """
- Find all boundary darts
- :param m: a mesh
- :return: a list of all boundary darts
- """
- boundary_darts = []
- for d_info in m.active_darts():
- d = Dart(m, d_info[0])
- d_twin = d.get_beta(2)
- if d_twin is None:
- boundary_darts.append(d)
- return boundary_darts
-
-
-def node_in_mesh(mesh: Mesh, x: float, y: float) -> (bool, int):
- """
- Search if the node of coordinate (x, y) is inside the mesh.
- :param mesh: the mesh to work with
- :param x: X coordinate
- :param y: Y coordinate
- :return: a boolean indicating if the node is inside the mesh and the id of the node if it is.
- """
- n_id = 0
- for n in mesh.nodes:
- if n[2] >= 0 :
- if abs(x - n[0]) <= 0.1 and abs(y - n[1]) <= 0.1:
- return True, n_id
- n_id += 1
- return False, None
+ return True
-def test_degree(n: Node) -> bool:
+class GlobalMeshAnalysis(ABC):
"""
- Verify that the degree of a vertex is lower than 10
- :param n: a Node
- :return: True if the degree is lower than 10, False otherwise
+ The base of mesh analysis
+ :param mesh: A mesh to analise
"""
- if degree(n) >= 10:
- return False
- else:
+ def __init__(self, mesh: Mesh) -> None:
+ self.mesh = mesh
+
+ def set_adjacency(self):
+ pass
+
+ def set_scores(self):
+ pass
+
+ def set_geometric_quality(self):
+ pass
+
+ def get_dart_geometric_quality(self, d: Dart) -> int:
+ pass
+
+ def global_score(self):
+ """
+ Calculate the overall mesh score. The mesh cannot achieve a better score than the ideal one.
+ And the current score is the mesh score.
+ :return: 4 return: a list of the nodes score, the current mesh score and the ideal mesh score, and the adjacency
+ """
+ mesh_ideal_score = 0
+ mesh_score = 0
+ nodes_score = []
+ nodes_adjacency = []
+ for i in range(len(self.mesh.nodes)):
+ if self.mesh.nodes[i, 2] >= 0:
+ n_id = i
+ node = Node(self.mesh, n_id)
+ n_a = NodeAnalysis(node)
+ n_score = n_a.score_calculation()
+ nodes_score.append(n_score)
+ nodes_adjacency.append(n_a.degree())
+ mesh_ideal_score += n_score
+ mesh_score += abs(n_score)
+ else:
+ nodes_score.append(0)
+ nodes_adjacency.append(6)
+ return nodes_score, mesh_score, mesh_ideal_score, nodes_adjacency
+
+ def get_boundary_darts(self) -> list[Dart]:
+ """
+ Find all boundary darts
+ :return: a list of all boundary darts
+ """
+ boundary_darts = []
+ for d_info in self.mesh.active_darts():
+ d = Dart(self.mesh, d_info[0])
+ d_twin = d.get_beta(2)
+ if d_twin is None:
+ boundary_darts.append(d)
+ return boundary_darts
+
+ def node_in_mesh(self, x: float, y: float) -> (bool, int):
+ """
+ Search if the node of coordinate (x, y) is inside the mesh.
+ :param x: X coordinate
+ :param y: Y coordinate
+ :return: a boolean indicating if the node is inside the mesh and the id of the node if it is.
+ """
+ n_id = 0
+ for n in self.mesh.nodes:
+ if n[2] >= 0:
+ if abs(x - n[0]) <= 0.1 and abs(y - n[1]) <= 0.1:
+ return True, n_id
+ n_id += 1
+ return False, None
+
+ def check_beta2_relation(self) -> bool:
+ for dart_info in self.mesh.active_darts():
+ d = dart_info[0]
+ d2 = dart_info[2]
+ if d2 >= 0 and self.mesh.dart_info[d2, 0] < 0:
+ raise ValueError("error beta2")
+ elif d2 >= 0 and self.mesh.dart_info[d2, 2] != d:
+ raise ValueError("error beta2")
return True
+ def check_double(self) -> bool:
+ for dart_info in self.mesh.active_darts():
+ d = Dart(self.mesh, dart_info[0])
+ d2 = Dart(self.mesh, dart_info[2]) if dart_info[2] >= 0 else None
+ n1 = dart_info[3]
+ if d2 is None:
+ d1 = d.get_beta(1)
+ n2 = d1.get_node().id
+ else:
+ n2 = d2.get_node().id
+ for dart_info2 in self.mesh.active_darts():
+ ds = Dart(self.mesh, dart_info2[0])
+ ds2 = Dart(self.mesh, dart_info2[2]) if dart_info2[2] >= 0 else None
+ if d != ds and d != ds2:
+ ns1 = dart_info2[3]
+ if ds2 is None:
+ ds1 = ds.get_beta(1)
+ ns2 = ds1.get_node().id
+ else:
+ ns2 = ds2.get_node().id
+
+ if n1 == ns1 and n2 == ns2:
+ plot_mesh(self.mesh)
+ raise ValueError("double error")
+ elif n2 == ns1 and n1 == ns2:
+ plot_mesh(self.mesh)
+ raise ValueError("double error")
+ return True
-def check_beta2_relation(mesh: Mesh) -> bool:
- for dart_info in mesh.active_darts():
- d = dart_info[0]
- d2 = dart_info[2]
- if d2 >= 0 and mesh.dart_info[d2, 0] < 0:
- raise ValueError("error beta2")
- elif d2 >= 0 and mesh.dart_info[d2, 2] != d:
- raise ValueError("error beta2")
- return True
-
-
-def check_double(mesh: Mesh) -> bool:
- for dart_info in mesh.active_darts():
- d = Dart(mesh, dart_info[0])
- d2 = Dart(mesh, dart_info[2]) if dart_info[2] >= 0 else None
- n1 = dart_info[3]
- if d2 is None:
- d1 = d.get_beta(1)
- n2 = d1.get_node().id
- else:
- n2 = d2.get_node().id
- for dart_info2 in mesh.active_darts():
- ds = Dart(mesh, dart_info2[0])
- ds2 = Dart(mesh, dart_info2[2]) if dart_info2[2] >= 0 else None
- if d != ds and d != ds2:
- ns1 = dart_info2[3]
- if ds2 is None:
- ds1 = ds.get_beta(1)
- ns2 = ds1.get_node().id
- else:
- ns2 = ds2.get_node().id
-
- if n1 == ns1 and n2 == ns2:
- plot_mesh(mesh)
- raise ValueError("double error")
- elif n2 == ns1 and n1 == ns2:
- plot_mesh(mesh)
- raise ValueError("double error")
- return True
-
-
-def mesh_check(mesh: Mesh) -> bool:
- return check_double(mesh) and check_beta2_relation(mesh)
-
-
-"""
-def get_boundary_nodes(m: Mesh) -> list[Node]:
- #
- Find all boundary nodes
- :param m: a mesh
- :return: a list of all boundary nodes
- #
- boundary_nodes = []
- for n_id in range(0, len(m.nodes)):
- if m.nodes[n_id, 2] >= 0:
- n = Node(m, n_id)
- if on_boundary(n):
- boundary_nodes.append(n)
- return boundary_nodes
-"""
\ No newline at end of file
+ def mesh_check(self) -> bool:
+ return self.check_double() and self.check_beta2_relation()
+
+ def angle_from_sides(self, a, b, c):
+ # Calculate angle A, with a the opposite side and b and c the adjacent sides
+ cosA = (b ** 2 + c ** 2 - a ** 2) / (2 * b * c)
+ if 1 <= cosA < 1.01:
+ cosA = 1
+ elif -1.01 <= cosA < -1:
+ cosA = -1
+ elif cosA > 1.01 or cosA < -1.01:
+ raise ValueError("Math domain error : cos>1.01")
+ return acos(cosA)
+
+ def get_angle_by_coord(self, x1: float, y1: float, x2: float, y2: float, x3: float, y3: float) -> float:
+ BAx, BAy = x1 - x2, y1 - y2
+ BCx, BCy = x3 - x2, y3 - y2
+
+ cos_ABC = (BAx * BCx + BAy * BCy) / (sqrt(BAx ** 2 + BAy ** 2) * sqrt(BCx ** 2 + BCy ** 2))
+ cos_ABC = np.clip(cos_ABC, -1, 1)
+ rad = acos(cos_ABC)
+ deg = degrees(rad)
+ return deg
+
+ def cross_product(self, vect_AB, vect_AC):
+ """ Return the cross product between AB et AC.
+ 0 means A, B and C are coolinear
+ > 0 mean A, B and C are "sens des aiguilles d'une montre"
+ < 0 sens inverse
+ """
+ val = vect_AB[0] * vect_AC[1] - vect_AB[1] * vect_AC[0]
+ return val
+
+ def signe(self, a: int):
+ pass
\ No newline at end of file
diff --git a/mesh_model/mesh_analysis/old_files/old_mesh_analysis.py b/mesh_model/mesh_analysis/old_files/old_mesh_analysis.py
new file mode 100644
index 0000000..a152d4b
--- /dev/null
+++ b/mesh_model/mesh_analysis/old_files/old_mesh_analysis.py
@@ -0,0 +1,273 @@
+from mesh_model.mesh_analysis.trimesh_analysis import TriMeshAnalysis
+from mesh_model.mesh_analysis.global_mesh_analysis import NodeAnalysis
+from mesh_model.mesh_struct.mesh import Mesh
+from mesh_model.mesh_struct.mesh_elements import Dart, Face
+from math import sqrt, degrees
+
+FLIP = 0
+SPLIT = 1
+COLLAPSE = 2
+TEST_ALL = 3
+ONE_VALID = 4
+
+
+class TriMeshOldAnalysis(TriMeshAnalysis):
+ """
+ Triangular mesh analysis with geometrical criteria
+ """
+
+ def __init__(self, mesh: Mesh):
+ super().__init__(mesh=mesh)
+
+ def isValidAction(self, dart_id: int, action: int) -> (bool, bool):
+ d = Dart(self.mesh, dart_id)
+ boundary_darts = self.get_boundary_darts()
+ if d in boundary_darts:
+ return False, True
+ elif action == FLIP:
+ return self.isFlipOk(d)
+ elif action == SPLIT:
+ return self.isSplitOk(d)
+ elif action == COLLAPSE:
+ return self.isCollapseOk(d)
+ elif action == TEST_ALL:
+ topo, geo = self.isFlipOk(d)
+ if not (topo and geo):
+ return False, False
+ topo, geo = self.isSplitOk(d)
+ if not (topo and geo):
+ return False, False
+ topo, geo = self.isCollapseOk(d)
+ if not (topo and geo):
+ return False, False
+ elif topo and geo:
+ return True, True
+ elif action == ONE_VALID:
+ topo_flip, geo_flip = self.isFlipOk(d)
+ if (topo_flip and geo_flip):
+ return True, True
+ topo_split, geo_split = self.isSplitOk(d)
+ if (topo_split and geo_split):
+ return True, True
+ topo_collapse, geo_collapse = self.isCollapseOk(d)
+ if (topo_collapse and geo_collapse):
+ return True, True
+ return False, False
+ else:
+ raise ValueError("No valid action")
+
+ def isFlipOk(self, d: Dart) -> (bool, bool):
+ topo = True
+ geo = True
+ # if d is on boundary, flip is not possible
+ if d.get_beta(2) is None:
+ topo = False
+ return topo, geo
+ else:
+ _, _, _, _, _, A, B, C, D = self.mesh.active_triangles(d)
+
+ nA_analysis = NodeAnalysis(A)
+ nB_analysis = NodeAnalysis(B)
+
+ if not nA_analysis.test_degree() or not nB_analysis.test_degree():
+ topo = False
+ return topo, geo
+
+ # Check angle at d limits to avoid edge reversal
+ angle_B = self.get_angle_by_coord(A.x(), A.y(), B.x(), B.y(), C.x(), C.y()) + self.get_angle_by_coord(A.x(),
+ A.y(),
+ B.x(),
+ B.y(),
+ D.x(),
+ D.y())
+ angle_A = self.get_angle_by_coord(B.x(), B.y(), A.x(), A.y(), C.x(), C.y()) + self.get_angle_by_coord(B.x(),
+ B.y(),
+ A.x(),
+ A.y(),
+ D.x(),
+ D.y())
+ if angle_B >= 180 or angle_A >= 180:
+ topo = False
+ return topo, geo
+
+ # Check if new triangle will be valid
+
+ # Triangle ACD
+ vect_AC = (C.x() - A.x(), C.y() - A.y())
+ vect_AD = (D.x() - A.x(), D.y() - A.y())
+ vect_DC = (C.x() - D.x(), C.y() - D.y())
+
+ # Triangle CBD
+ vect_BC = (C.x() - B.x(), C.y() - B.y())
+ vect_BD = (D.x() - B.x(), D.y() - B.y())
+
+ if not self.valid_triangle(vect_AC, vect_AD, vect_DC) or not self.valid_triangle(vect_BC, vect_BD, vect_DC):
+ geo = False
+ return topo, geo
+
+ return topo, geo
+
+ def isSplitOk(self, d: Dart) -> (bool, bool):
+ topo = True
+ geo = True
+ if d.get_beta(2) is None:
+ topo = False
+ return topo, geo
+ else:
+ _, _, _, _, _, A, B, C, D = self.mesh.active_triangles(d)
+
+ nC_analysis = NodeAnalysis(C)
+ nD_analysis = NodeAnalysis(D)
+
+ if not nC_analysis.test_degree() or not nD_analysis.test_degree():
+ topo = False
+ return topo, geo
+
+ newNode_x, newNode_y = (A.x() + B.x()) / 2, (A.y() + B.y()) / 2
+
+ # Check if new triangle will be valid
+
+ # Triangle AEC
+ vect_AC = (C.x() - A.x(), C.y() - A.y())
+ vect_AE = (newNode_x - A.x(), newNode_y - A.y())
+ vect_EC = (C.x() - newNode_x, C.y() - newNode_y)
+ if not self.valid_triangle(vect_AE, vect_AC, vect_EC):
+ geo = False
+ return topo, geo
+
+ # Triangle ADE
+ vect_AD = (D.x() - A.x(), D.y() - A.y())
+ vect_ED = (D.x() - newNode_x, D.y() - newNode_y)
+ if not self.valid_triangle(vect_AD, vect_AE, vect_ED):
+ geo = False
+ return topo, geo
+
+ # Triangle BCE
+ vect_BC = (C.x() - B.x(), C.y() - B.y())
+ vect_BE = (newNode_x - B.x(), newNode_y - B.y())
+ vect_EC = (C.x() - newNode_x, C.y() - newNode_y)
+ if not self.valid_triangle(vect_BC, vect_BE, vect_EC):
+ geo = False
+ return topo, geo
+
+ # Triangle BDE
+ vect_BD = (D.x() - B.x(), D.y() - B.y())
+ vect_ED = (D.x() - newNode_x, D.y() - newNode_y)
+ if not self.valid_triangle(vect_BD, vect_BE, vect_ED):
+ geo = False
+ return topo, geo
+
+ return topo, geo
+
+ def isCollapseOk(self, d: Dart) -> (bool, bool):
+ topo = True
+ geo = True
+ if d.get_beta(2) is None:
+ topo = False
+ return topo, geo
+ else:
+ _, d1, d11, d21, d211, n1, n2, _, _ = self.mesh.active_triangles(d)
+
+ d112 = d11.get_beta(2)
+ d12 = d1.get_beta(2)
+
+ d212 = d21.get_beta(2)
+ d2112 = d211.get_beta(2)
+
+ newNode_x, newNode_y = (n1.x() + n2.x()) / 2, (n1.y() + n2.y()) / 2
+
+ n1_analysis = NodeAnalysis(n1)
+ n2_analysis = NodeAnalysis(n2)
+
+ if d112 is None or d12 is None or d2112 is None or d212 is None:
+ topo = False
+ return topo, geo
+ elif n1_analysis.on_boundary() or n2_analysis.on_boundary():
+ topo = False
+ return topo, geo
+ elif not n1_analysis.test_degree():
+ topo = False
+ return topo, geo
+ else:
+ # search for all adjacent faces to n1 and n2
+ if d12 is None and d2112 is None:
+ adj_faces_n1 = self.get_adjacent_faces(n1, d212, d112)
+ return topo, self.valid_faces_changes(adj_faces_n1, n1.id, newNode_x, newNode_y)
+ elif d212 is None and d112 is None:
+ adj_faces_n2 = self.get_adjacent_faces(n2, d12, d2112)
+ return topo, self.valid_faces_changes(adj_faces_n2, n2.id, newNode_x, newNode_y)
+ else:
+ adj_faces_n1 = self.get_adjacent_faces(n1, d212, d112)
+ adj_faces_n2 = self.get_adjacent_faces(n2, d12, d2112)
+ if not self.valid_faces_changes(adj_faces_n1, n1.id, newNode_x,
+ newNode_y) or not self.valid_faces_changes(adj_faces_n2, n2.id,
+ newNode_x, newNode_y):
+ geo = False
+ return topo, geo
+ else:
+ return topo, geo
+
+ def valid_faces_changes(self, faces: list[Face], n_id: int, new_x: float, new_y: float) -> bool:
+ """
+ Check the orientation of triangles adjacent to node n = Node(mesh, n_id) if the latter is moved to coordinates new_x, new_y.
+ Also checks that no triangle will become flat
+ :param faces: adjacents faces to node of id n_id
+ :param n_id: node id
+ :param new_x: new x coordinate
+ :param new_y: new y coordinate
+ :return: True if valid, False otherwise
+ """
+ for f in faces:
+ _, _, _, A, B, C = f.get_surrounding_triangle()
+ if A.id == n_id:
+ vect_AB = (B.x() - new_x, B.y() - new_y)
+ vect_AC = (C.x() - new_x, C.y() - new_y)
+ vect_BC = (C.x() - B.x(), C.y() - B.y())
+ elif B.id == n_id:
+ vect_AB = (new_x - A.x(), new_y - A.y())
+ vect_AC = (C.x() - A.x(), C.y() - A.y())
+ vect_BC = (C.x() - new_x, C.y() - new_y)
+ elif C.id == n_id:
+ vect_AB = (B.x() - A.x(), B.y() - A.y())
+ vect_AC = (new_x - A.x(), new_y - A.y())
+ vect_BC = (new_x - B.x(), new_y - B.y())
+ else:
+ print("Non-adjacent face error")
+ continue
+
+ cross_product = vect_AB[0] * vect_AC[1] - vect_AB[1] * vect_AC[0]
+
+ if cross_product <= 0:
+ return False # One face is not correctly oriented or is flat
+ elif not self.valid_triangle(vect_AB, vect_AC, vect_BC):
+ return False
+ return True
+
+ def valid_triangle(self, vect_AB, vect_AC, vect_BC) -> bool:
+ dist_AB = sqrt(vect_AB[0] ** 2 + vect_AB[1] ** 2)
+ dist_AC = sqrt(vect_AC[0] ** 2 + vect_AC[1] ** 2)
+ dist_BC = sqrt(vect_BC[0] ** 2 + vect_BC[1] ** 2)
+ target_mesh_size = 1
+
+ L_max = max(dist_AB, dist_AC, dist_BC)
+
+ if target_mesh_size / 2 * sqrt(2) < L_max and L_max < target_mesh_size * 3 * sqrt(2): # 0.35