Source code for felupe.mesh._geometry

# -*- coding: utf-8 -*-
"""
This file is part of FElupe.

FElupe is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

FElupe is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with FElupe.  If not, see <http://www.gnu.org/licenses/>.
"""

import numpy as np

from ._line_rectangle_cube import cube_hexa, line_line, rectangle_quad
from ._mesh import Mesh
from ._tools import concatenate


[docs]class Line(Mesh): "A line shaped 1d-mesh with lines between ``a`` and ``b`` with ``n`` points." def __init__(self, a=0, b=1, n=2): self.a = a self.b = b self.n = n points, cells, cell_type = line_line(a, b, n) super().__init__(points, cells, cell_type)
[docs]class Rectangle(Mesh): """A rectangular 2d-mesh with quads between ``a`` and ``b`` with ``n`` points per axis.""" def __init__(self, a=(0, 0), b=(1, 1), n=(2, 2)): self.a = a self.b = b self.n = n points, cells, cell_type = rectangle_quad(a, b, n) super().__init__(points, cells, cell_type)
[docs]class Cube(Mesh): """A cube shaped 3d-mesh with hexahedrons between ``a`` and ``b`` with ``n`` points per axis.""" def __init__(self, a=(0, 0, 0), b=(1, 1, 1), n=(2, 2, 2)): self.a = a self.b = b self.n = n points, cells, cell_type = cube_hexa(a, b, n) super().__init__(points, cells, cell_type)
[docs]class Grid(Mesh): """A grid shaped 3d-mesh with hexahedrons. Basically a wrapper for :func:`numpy.meshgrid` with default ``indexing="ij"``.""" def __init__(self, *xi, indexing="ij", **kwargs): shape = np.array([len(x) for x in xi]) n = shape if len(shape) > 1 else shape[0] M = [None, line_line, rectangle_quad, cube_hexa][len(xi)] points, cells, cell_type = M(n=n) super().__init__(points, cells, cell_type) self.points = ( np.vstack( [g.T.ravel() for g in np.meshgrid(*xi, indexing=indexing, **kwargs)] ) .astype(float) .T )
[docs]class RectangleArbitraryOrderQuad(Mesh): """A rectangular 2d-mesh with arbitrary order quads between ``a`` and ``b`` with ``n`` points per axis.""" def __init__(self, a=(0, 0), b=(1, 1), order=2): yv, xv = np.meshgrid( np.linspace(a[1], b[1], order + 1), np.linspace(a[0], b[0], order + 1), indexing="ij", ) points = np.vstack((xv.flatten(), yv.flatten())).T # search vertices xmin = min(points[:, 0]) ymin = min(points[:, 1]) xmax = max(points[:, 0]) ymax = max(points[:, 1]) def search_vertice(p, x, y): return np.where(np.logical_and(p[:, 0] == x, p[:, 1] == y))[0][0] def search_edge(p, a, x): return np.where(p[:, a] == x)[0][1:-1] v1 = search_vertice(points, xmin, ymin) v2 = search_vertice(points, xmax, ymin) v3 = search_vertice(points, xmax, ymax) v4 = search_vertice(points, xmin, ymax) vertices = [v1, v2, v3, v4] mask1 = np.ones_like(points[:, 0], dtype=bool) mask1[vertices] = 0 # points_no_verts = points[mask1] e1 = search_edge(points, 1, ymin) e2 = search_edge(points, 0, xmax) e3 = search_edge(points, 1, ymax) e4 = search_edge(points, 0, xmin) edges = np.hstack((e1, e2, e3, e4)) mask2 = np.ones_like(points[:, 0], dtype=bool) mask2[np.hstack((vertices, edges))] = 0 # points_no_verts_edges = points[mask2] face = np.arange(len(points))[mask2] cells = np.hstack((vertices, edges, face)).reshape(1, -1) super().__init__(points, cells, cell_type="VTK_LAGRANGE_QUADRILATERAL")
[docs]class CubeArbitraryOrderHexahedron(Mesh): """A cube shaped 3d-mesh with arbitrary order hexahedrons between ``a`` and ``b`` with ``n`` points per axis.""" def __init__(self, a=(0, 0, 0), b=(1, 1, 1), order=2): zv, yv, xv = np.meshgrid( np.linspace(a[2], b[2], order + 1), np.linspace(a[1], b[1], order + 1), np.linspace(a[0], b[0], order + 1), indexing="ij", ) points = np.vstack((xv.flatten(), yv.flatten(), zv.flatten())).T # search vertices xmin = min(points[:, 0]) ymin = min(points[:, 1]) zmin = min(points[:, 2]) xmax = max(points[:, 0]) ymax = max(points[:, 1]) zmax = max(points[:, 2]) def search_vertice(p, x, y, z): return np.where( np.logical_and(np.logical_and(p[:, 0] == x, p[:, 1] == y), p[:, 2] == z) )[0][0] def search_edge(p, a, b, x, y): return np.where(np.logical_and(p[:, a] == x, p[:, b] == y))[0][1:-1] def search_face(p, a, x, vertices, edges): face = np.where(points[:, a] == x)[0] mask = np.zeros_like(p[:, 0], dtype=bool) mask[face] = 1 mask[np.hstack((vertices, edges))] = 0 return np.arange(len(p[:, 0]))[mask] v1 = search_vertice(points, xmin, ymin, zmin) v2 = search_vertice(points, xmax, ymin, zmin) v3 = search_vertice(points, xmax, ymax, zmin) v4 = search_vertice(points, xmin, ymax, zmin) v5 = search_vertice(points, xmin, ymin, zmax) v6 = search_vertice(points, xmax, ymin, zmax) v7 = search_vertice(points, xmax, ymax, zmax) v8 = search_vertice(points, xmin, ymax, zmax) vertices = [v1, v2, v3, v4, v5, v6, v7, v8] mask1 = np.ones_like(points[:, 0], dtype=bool) mask1[vertices] = 0 # points_no_verts = points[mask1] e1 = search_edge(points, 1, 2, ymin, zmin) e2 = search_edge(points, 0, 2, xmax, zmin) e3 = search_edge(points, 1, 2, ymax, zmin) e4 = search_edge(points, 0, 2, xmin, zmin) e5 = search_edge(points, 1, 2, ymin, zmax) e6 = search_edge(points, 0, 2, xmax, zmax) e7 = search_edge(points, 1, 2, ymax, zmax) e8 = search_edge(points, 0, 2, xmin, zmax) e9 = search_edge(points, 0, 1, xmin, ymin) e10 = search_edge(points, 0, 1, xmax, ymin) e11 = search_edge(points, 0, 1, xmin, ymax) e12 = search_edge(points, 0, 1, xmax, ymax) edges = np.hstack((e1, e2, e3, e4, e5, e6, e7, e8, e9, e10, e11, e12)) mask2 = np.ones_like(points[:, 0], dtype=bool) mask2[np.hstack((vertices, edges))] = 0 # points_no_verts_edges = points[mask2] f1 = search_face(points, 0, xmin, vertices, edges) f2 = search_face(points, 0, xmax, vertices, edges) f3 = search_face(points, 1, ymin, vertices, edges) f4 = search_face(points, 1, ymax, vertices, edges) f5 = search_face(points, 2, zmin, vertices, edges) f6 = search_face(points, 2, zmax, vertices, edges) faces = np.hstack((f1, f2, f3, f4, f5, f6)) mask3 = np.ones_like(points[:, 0], dtype=bool) mask3[np.hstack((vertices, edges, faces))] = 0 volume = np.arange(len(points))[mask3] cells = np.hstack((vertices, edges, faces, volume)).reshape(1, -1) super().__init__(points, cells, cell_type="VTK_LAGRANGE_HEXAHEDRON")
[docs]class Circle(Mesh): """A circular shaped 2d-mesh with quads and ``n`` points on the circumferential edge of a 45-degree section. 90-degree ``sections`` are placed at given angles in degree.""" def __init__( self, radius=1, centerpoint=[0, 0], n=2, sections=[0, 90, 180, 270], value=0.15, exponent=2, decimals=10, ): rect = Rectangle(b=(0.5, 0.5), n=(n, n)) right = rect.points[:, 0] == 0.5 rect = rect.add_runouts(values=[-value], axis=0, exponent=exponent) rect.points[:, 0] = rect.points[:, 1].reshape(n, n, order="F").ravel() line = Line(n=n) phi = np.linspace(np.pi / 4, 0, n) bottom = line.copy(points=rect.points[right][::-1]) top = line.copy(points=np.vstack([np.cos(phi), np.sin(phi)]).T) face = bottom.fill_between(top, n=n) quarter = concatenate([face, face.mirror(normal=[-1, 1]), rect]) circle = concatenate([quarter.rotate(alpha, 2) for alpha in sections]).sweep( decimals=decimals ) circle.points *= radius circle.points += np.array(centerpoint) super().__init__( points=circle.points, cells=circle.cells, cell_type=circle.cell_type )
[docs]class Triangle(Mesh): """A triangular shaped 2d-mesh with quads and ``n`` points at the edges of the three sub-quadrilaterals.""" def __init__( self, a=(0, 0), b=(1, 0), c=(0, 1), n=2, decimals=10, ): a = np.asarray(a) b = np.asarray(b) c = np.asarray(c) sections = [] centerpoint = (a + b + c) / 3 centerpoints = {"ab": (a + b) / 2, "bc": (b + c) / 2, "ac": (a + c) / 2} line = Line(n=n) # section (connected to point) a x1 = np.linspace(a[0], centerpoints["ac"][0], n) y1 = np.linspace(a[1], centerpoints["ac"][1], n) left = line.copy(points=np.vstack([x1, y1]).T) x2 = np.linspace(centerpoints["ab"][0], centerpoint[0], n) y2 = np.linspace(centerpoints["ab"][1], centerpoint[1], n) middle = line.copy(points=np.vstack([x2, y2]).T) sections.append(middle.fill_between(left, n=n)) # section (connected to point) b x3 = np.linspace(b[0], centerpoints["bc"][0], n) y3 = np.linspace(b[1], centerpoints["bc"][1], n) right = line.copy(points=np.vstack([x3, y3]).T) sections.append(right.fill_between(middle, n=n)) # section (connected to point) c x4 = np.linspace(centerpoints["ac"][0], c[0], n) y4 = np.linspace(centerpoints["ac"][1], c[1], n) top = line.copy(points=np.vstack([x4, y4]).T) x5 = np.linspace(centerpoint[0], centerpoints["bc"][0], n) y5 = np.linspace(centerpoint[1], centerpoints["bc"][1], n) bottom = line.copy(points=np.vstack([x5, y5]).T) sections.append(bottom.fill_between(top, n=n)) # combine sections triangle = concatenate(sections).sweep(decimals=decimals) super().__init__( points=triangle.points, cells=triangle.cells, cell_type=triangle.cell_type )