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Implement projected surface area calculation function in util.shape

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This commit is contained in:
Dion Moult
2023-10-06 13:04:34 +11:00
parent c34a9c52d0
commit eb836436b9
1 changed files with 24 additions and 6 deletions
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src/ifcopenshell-python/ifcopenshell/util/shape.py
+24 -6
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@@ -188,7 +188,10 @@ def get_area(geometry):
return get_area_vf(vertices, faces)
def get_side_area(geometry, axis="Y"):
def get_side_area(geometry, axis="Y", direction=None):
if direction is None:
direction = {"X": (1.0, 0.0, 0.0), "Y": (0.0, 1.0, 0.0), "Z": (0.0, 0.0, 1.0)}[axis]
verts = geometry.verts
faces = geometry.faces
vertices = np.array([[verts[i], verts[i + 1], verts[i + 2]] for i in range(0, len(verts), 3)])
@@ -201,15 +204,21 @@ def get_side_area(geometry, axis="Y"):
# Normalize the normal vectors
triangle_normals = triangle_normals / np.linalg.norm(triangle_normals, axis=1)[:, np.newaxis]
direction = np.array(direction) / np.linalg.norm(direction)
# Find the faces with a normal vector pointing in the desired +Y normal direction
axis = {"X": 0, "Y": 1, "Z": 2}[axis]
filtered_face_indices = np.where(triangle_normals[:, axis] > tol)[0]
# normal_tol < 0 is pointing away, = 0 is perpendicular, and > 0 is pointing towards.
normal_tol = 0.01 # Close to perpendicular, but with a fuzz for numerical tolerance
dot_products = np.dot(triangle_normals, direction)
filtered_face_indices = np.where(dot_products > normal_tol)[0]
filtered_faces = faces[filtered_face_indices]
return get_area_vf(vertices, filtered_faces)
def get_footprint_area(geometry):
def get_footprint_area(geometry, axis="Z", direction=None):
if direction is None:
direction = {"X": (1.0, 0.0, 0.0), "Y": (0.0, 1.0, 0.0), "Z": (0.0, 0.0, 1.0)}[axis]
verts = geometry.verts
faces = geometry.faces
vertices = np.array([[verts[i], verts[i + 1], verts[i + 2]] for i in range(0, len(verts), 3)])
@@ -222,10 +231,19 @@ def get_footprint_area(geometry):
# Normalize the normal vectors
triangle_normals = triangle_normals / np.linalg.norm(triangle_normals, axis=1)[:, np.newaxis]
direction = np.array(direction) / np.linalg.norm(direction)
# Find the faces with a normal vector pointing in the desired +Z normal direction
filtered_face_indices = np.where(triangle_normals[:, 2] > tol)[0]
# Find the faces with a normal vector pointing in the desired direction using dot product
# normal_tol < 0 is pointing away, = 0 is perpendicular, and > 0 is pointing towards.
normal_tol = 0.01 # Close to perpendicular, but with a fuzz for numerical tolerance
dot_products = np.dot(triangle_normals, direction)
filtered_face_indices = np.where(dot_products > normal_tol)[0]
filtered_faces = faces[filtered_face_indices]
# Flatten vertices along the direction
for idx in range(len(vertices)):
vertices[idx] = vertices[idx] - np.dot(vertices[idx], direction) * direction
return get_area_vf(vertices, filtered_faces)