├── .github └── workflows │ └── python-test.yml ├── LICENSE ├── README.md ├── examples ├── 0_annulus │ └── driver.py ├── 1_supersonic │ └── driver.py ├── 2_ringleb │ └── driver.py ├── 3_blobs │ └── driver.py ├── 4_annulus_acoustics │ └── driver.py ├── 5_circles │ └── driver.py ├── 6_channel │ └── driver.py ├── 7_doublemach │ └── driver.py ├── 8_argrun │ └── driver.py └── README.md ├── images ├── aligned.png ├── annulus.png ├── annulus_zoom.png ├── blobs.png ├── gridgen.png ├── ringleb.png ├── ringleb_zoom.png ├── split.png └── tunneled.png ├── pygrid2d ├── PyGrid2D.py ├── __init__.py ├── annulus.py ├── annulus_acoustics.py ├── bisection.py ├── blobs.py ├── channel.py ├── circles.py ├── domain.py ├── doublemach.py ├── output.py ├── plot_mesh.py ├── ringleb.py └── supersonic.py ├── setup.py └── tests ├── data ├── annulus_10_10_q1.ply ├── annulus_20_20_q2.ply ├── annulus_30_30_q3.ply ├── annulus_40_40_q4.ply ├── annulus_50_50_q5.ply ├── ringleb_10_10_q1.ply ├── ringleb_20_20_q2.ply ├── ringleb_30_30_q3.ply ├── ringleb_40_40_q4.ply ├── supersonic_10_10_q1.ply ├── supersonic_20_20_q2.ply ├── supersonic_30_30_q3.ply ├── supersonic_40_40_q4.ply └── supersonic_50_50_q5.ply └── test_PyGrid.py /.github/workflows/python-test.yml: -------------------------------------------------------------------------------- 1 | # This is a basic workflow to help you get started with Actions 2 | 3 | name: CI 4 | 5 | # Controls when the workflow will run 6 | on: 7 | # Triggers the workflow on push or pull request events but only for the main branch 8 | push: 9 | branches: [ main ] 10 | pull_request: 11 | branches: [ main ] 12 | 13 | # Allows you to run this workflow manually from the Actions tab 14 | workflow_dispatch: 15 | 16 | # A workflow run is made up of one or more jobs that can run sequentially or in parallel 17 | jobs: 18 | # This workflow contains a single job called "build" 19 | build: 20 | # The type of runner that the job will run on 21 | runs-on: ubuntu-latest 22 | 23 | # Steps represent a sequence of tasks that will be executed as part of the job 24 | steps: 25 | # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it 26 | - uses: actions/checkout@v2 27 | 28 | # Runs a set of commands using the runners shell 29 | - name: install 30 | run: | 31 | echo test, and deploy your project. 32 | pip install . 33 | 34 | - name: ls -l again 35 | run: | 36 | ls -l 37 | pwd 38 | 39 | - name: run test 40 | run: | 41 | cd tests 42 | ls -l 43 | pytest . 44 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2021 andrewgiuliani 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # PyGrid2D 2 | 3 | 4 | ![CI](https://github.com/andrewgiuliani/PyGrid-2D/workflows/CI/badge.svg) 5 | 6 | 7 | 8 | This is a short Python code that generates two dimensional high order embedded boundary grids. The code is fast, with most operations fully vectorized in Numpy. There are a number of domains already implemented from [1], that include an annulus domain as well as the domain used in Ringleb flow. 9 |

10 | annulus               11 | annulus 12 |

13 |

High order embedded boundary annulus (left) and Ringleb (right) domains. Each curved boundary segment has q+1 boundary points (red dots), where q = 3.

14 | 15 | 16 | ## Installation 17 | To install, navigate to the cloned github repository, and call 18 | ``` 19 | pip install -e . 20 | ``` 21 | 22 | ## Goal 23 | The goal of this work is to provide an easy to install, high order cut cell grid generator for simple boundary geometries that have a functional representation. PyGrid assumes that each cut cell has only one or two, possibly curved, edges associated to the embedded boundary. 24 | 25 |

26 | annulus               27 | annulus 28 |

29 |

Zooms onto cut cells of the annulus and Ringleb meshes. Cut cells can have either one (left) or two curved edges (right). Cut cells with two curved edges can occur on sharp corners of the embedded boundary.

30 | 31 | The code supports complex curved embedded boundaries (illustrated below), provided that it has a functional representation. We do not allow split or tunneled cells for ease of code development. This mesh generator does not handle mesh degeneracies, nor can it handle all types of cut cells, see the section entitled The sharp bits below for more information on the codes limitations. 32 | 33 |

34 | blobs 35 |

36 |

Complex curved embedded boundaries are also supported. Here we embedded five `blobs' and request three interpolation points per cut cell edge ().

37 | 38 | 39 | ## How does it work? 40 | 1. The user provides a function, `in_domain`, that maps a spatial coordinate (x,y) to 1 if the point lies inside the domain or 0 if it does not. Using this function, the regular grid points that lie in and out of the domain are determined. For example, this is done in the figure below on the Ringleb domain. The regular grid points that lie in the domain are shown in orange, while the regular grid points that are outside the domain are shown in black. 41 | 42 | 2. When a regular grid point that lies outside the domain is adjacent another that is inside the domain, this means that between these two points, the embedded boundary crosses a Cartesian grid line. Using the method of bisection, the precise point of intersection is computed. On the Ringleb domain below, these points are plotted in red. Right now, the code assumes that the boundary does not cross the grid line more than once. 43 | 44 | 3. After these intersection points are computed, the cut cells are assembled. 45 | 46 | 4. If the user requests curved edges, then additional vertices that are approximately uniformly spaced (in arclength) along the embedded boundary are computed. For circular embedded boundaries, we have explicit formulae to accomplish this. Again, this is done using the method of bisection. 47 | 48 | 5. The cut cells are then written to file in the `.ply` format. See here for more information http://paulbourke.net/dataformats/ply/. 49 | 50 |

51 | annulus 52 |

53 |

Regular grid points that lie inside and outside the domain are respectively orange and black, computed in step 1. Irregular grid points on the embedded boundary are red, computed in step 2.

54 | 55 | ## 🌲🌳  Into the weeds on curved edges 56 | If curved boundaries are requested, the code computes interpolation points that are equispaced in arclength (for circular boundaries) and approximately equispaced in arclength using the method of bisection otherwise. The approach for non-circular boundaries relies on a one-dimensional parametrization of the boundary . 57 | Say that a cut cell's curved edge is defined by the set of points . 58 | In order to find additional interpolation points along the boundary, define the function 59 | 60 | 61 | 62 | for some on . This function is zero when maps to a point, , that is exactly units away from . 63 | 64 | Note that and . Provided that is monotonically increasing on , will only have a single root in , which can be found using the method of bisection. Therefore, when the user requests interpolation points along the boundary, the code finds the roots of when . These additional boundary points, along with the edge endpoints and , form a set of edge interpolation points. 65 | 66 | Note that this is not a fully robust approach to determining interpolation points on the embedded boundary and is only appropriate when the boundary is sufficiently well-resolved. 67 | 68 | ## 🔪  The sharp bits 69 | This code only handles cut cells on which the boundary enters and leaves on different faces. Additionally, it cannot deal with tunnelled and split cells. It may be added in the future, and of course in 3D for real geometries this would be necessary. 70 |

71 | split               72 | tunneled 73 |

74 |

On the left, the annulus domain is removed from the background grid, creating split cut cells. On the right, the complement of the annulus is removed from the background grid, creating tunnelled cut cells.

75 | 76 | Additionally, the code does not robustly (or gracefully) handle mesh degeneracies. For example, if the embedded geometry lies directly on a Cartesian grid line cell, the code will produce erroneous output and may, or may not output an error. 77 | 78 |

79 | aligned 80 |

81 |

A square domain (black lines) is removed from the background grid (blue lines), where the domain is perfectly aligned with the Cartesian grid lines.

82 | 83 | We do not support the above scenarios for code simplicity, however, they must be addressed when moving to three dimensions and complex engineering geometries. This is the reason that the dimensions of some of the background grids in [1] are slighly perturbed from round numbers, as we aimed to avoid any of the above scenarios. 84 | 85 | ## 🏗  Grid generation 86 | 87 | Of the many examples included here, the script in `./examples/8_argrun/driver.py` accepts command line arguments, which are explained below: 88 | 89 | 90 | -Nx 91 | number of cells on the grid in the x-direction 92 | 93 | -Ny 94 | number of cells on the grid in the y-direction 95 | 96 | -fbody 97 | the ID of the embedded boundary to be used. 98 | * `0`: quarter annulus, for the supersonic vortex problem, 99 | * `1`: annulus for rotating pulse problem, 100 | * `2`: Ringleb, 101 | * `3`: random blobs. 102 | * `4`: annulus for acoustics problem, 103 | * `5`: circular obstacles, 104 | * `6`: channel, 105 | * `7`: double Mach. 106 | 107 | -plot 108 | display the generated cut cell grid 109 | 110 | -q 111 | add curved edges on the cut cells with q+1 interpolation points with the embedded boundary 112 | 113 | For example, the Ringleb domain can be generated and plotted by calling 114 | ``` 115 | ./examples/8_argrun/driver.py -Nx 10 -Ny 10 -fbody 2 -q 3 -plot 116 | ``` 117 | 118 | ## Contact 119 | For help running the code, or any other questions, send me an email at 120 | `giuliani AT cims DOT nyu DOT edu` 121 | 122 | ## Citing 123 | If you find this code useful in your work, you can cite it with 124 | 125 | Giuliani, Andrew. "A two-dimensional stabilized discontinuous Galerkin method on curvilinear embedded boundary grids". [https://arxiv.org/abs/2102.01857](https://arxiv.org/abs/2102.01857) 126 | 127 | ## 📓  License 128 | [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) 129 | 130 | 131 | 132 | ## References 133 | [1] Giuliani, Andrew. "A two-dimensional stabilized discontinuous Galerkin method on curvilinear embedded boundary grids". [https://arxiv.org/abs/2102.01857](https://arxiv.org/abs/2102.01857) 134 | 135 | -------------------------------------------------------------------------------- /examples/0_annulus/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import pygrid2d as pg2d 3 | 4 | Nx = 25 5 | Ny = 25 6 | plot_flag = True 7 | q = 5 # q = 5 means the mesh generator will compute 6 points on the embedded boundary, resulting in a degree 5 polynomial boundary interpolant 8 | bid = 0 # bodyID = 0 means annulus domain 9 | 10 | vertices, cell_list, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 11 | pg2d.output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q) 12 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 13 | -------------------------------------------------------------------------------- /examples/1_supersonic/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import pygrid2d as pg2d 3 | 4 | Nx = 25 5 | Ny = 25 6 | plot_flag = True 7 | q = 5 # q = 5 means the mesh generator will compute 6 points on the embedded boundary, resulting in a degree 5 polynomial boundary interpolant 8 | bid = 1 # bodyID = 1 means supersonic domain 9 | 10 | vertices, cell_list, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 11 | pg2d.output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q) 12 | pg2d.output_nor(vertices, mesh_data, face_data, domain, Nx, Ny, q) 13 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 14 | -------------------------------------------------------------------------------- /examples/2_ringleb/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import pygrid2d as pg2d 3 | 4 | Nx = 25 5 | Ny = 25 6 | plot_flag = True 7 | q = 5 # q = 5 means the mesh generator will compute 6 points on the embedded boundary, resulting in a degree 5 polynomial boundary interpolant 8 | bid = 2 # bodyID = 2 means Ringleb domain 9 | 10 | vertices, cell_list, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 11 | pg2d.output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q) 12 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 13 | -------------------------------------------------------------------------------- /examples/3_blobs/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import pygrid2d as pg2d 3 | 4 | Nx = 26 5 | Ny = 26 6 | plot_flag = True 7 | q = 5 # q = 5 means the mesh generator will compute 6 points on the embedded boundary, resulting in a degree 5 polynomial boundary interpolant 8 | bid = 3 # bodyID = 3 means blob domain 9 | 10 | vertices, cell_list, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 11 | pg2d.output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q) 12 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 13 | -------------------------------------------------------------------------------- /examples/4_annulus_acoustics/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import pygrid2d as pg2d 3 | 4 | Nx = 26 5 | Ny = 26 6 | plot_flag = True 7 | q = 5 # q = 5 means the mesh generator will compute 6 points on the embedded boundary, resulting in a degree 5 polynomial boundary interpolant 8 | bid = 4 # bodyID = 4 means the acoustics annulus domain 9 | 10 | vertices, cell_list, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 11 | pg2d.output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q) 12 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 13 | 14 | -------------------------------------------------------------------------------- /examples/5_circles/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import pygrid2d as pg2d 3 | 4 | Nx = 26 5 | Ny = 26 6 | plot_flag = True 7 | q = 5 # q = 5 means the mesh generator will compute 6 points on the embedded boundary, resulting in a degree 5 polynomial boundary interpolant 8 | bid = 5 # bodyID = 5 means domain of circular obstacles 9 | 10 | 11 | vertices, cell_list, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 12 | pg2d.output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q) 13 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 14 | -------------------------------------------------------------------------------- /examples/6_channel/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import pygrid2d as pg2d 3 | 4 | Nx = 26 5 | Ny = 26 6 | plot_flag = True 7 | q = 5 # q = 5 means the mesh generator will compute 6 points on the embedded boundary, resulting in a degree 5 polynomial boundary interpolant 8 | bid = 6 # bodyID = 6 means channel domain 9 | 10 | vertices, cell_list, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 11 | pg2d.output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q) 12 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 13 | -------------------------------------------------------------------------------- /examples/7_doublemach/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import pygrid2d as pg2d 3 | 4 | Nx = 26 5 | Ny = 26 6 | plot_flag = True 7 | q = 5 # q = 5 means the mesh generator will compute 6 points on the embedded boundary, resulting in a degree 5 polynomial boundary interpolant 8 | bid = 7 # bodyID = 7 means double Mach domain 9 | 10 | vertices, cell_list, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 11 | pg2d.output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q) 12 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 13 | -------------------------------------------------------------------------------- /examples/8_argrun/driver.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import argparse 3 | import pygrid2d as pg2d 4 | 5 | ## this driver lets you generate grids using the command line. For example: 6 | ## ./driver.py -Nx 10 -Ny 10 -fbody 2 -q 3 -plot 7 | ## generates a 10x10 grid on the Ringleb flow domain (fbody=2) with 4 interpolation points 8 | ## along the curved boundary, and plots it. You can 9 | ## avoid plotting by removing the -plot command line option: 10 | ## ./driver.py -Nx 10 -Ny 10 -fbody 2 -q 3 11 | 12 | 13 | 14 | 15 | parser = argparse.ArgumentParser() 16 | parser.add_argument("-Nx", "--Nx", type=int, help="number of elements in x-direction") 17 | parser.add_argument("-Ny", "--Ny", type=int, help="number of elements in y-direction") 18 | parser.add_argument("-fbody","--fbody", type=int, help="geometry type") 19 | parser.add_argument("-plot","--PLOT", action='store_true', help="plot") 20 | parser.add_argument("-q","--Q", type = int, default = 1, help="q is the degree of the curved boundary") 21 | args = parser.parse_args() 22 | Nx = args.Nx 23 | Ny = args.Ny 24 | plot_flag = args.PLOT 25 | q = args.Q 26 | bid = args.fbody 27 | 28 | vertices, cell_list, domain = pg2d.PyGrid2D(Nx, Ny, plot_flag, q, bid) 29 | pg2d.output_ply(vertices, cell_list, domain, Nx, Ny, q) 30 | -------------------------------------------------------------------------------- /examples/README.md: -------------------------------------------------------------------------------- 1 | ## 🧪   Examples 2 | 3 | This folder contains a number of examples to generate grids: 4 | - `0_annulus` 5 | - `1_supersonic` 6 | - `2_ringleb` 7 | - `3_blobs` 8 | - `4_annulus_acoustics` 9 | - `5_circles` 10 | - `6_channel` 11 | - `7_doublemach` 12 | - `8_argrun` 13 | 14 | For all of the above examples, there is a driver script that can be executed by calling `./driver.py`. The final driver script in `8_argrun` can be called to generate grids from command line input. 15 | -------------------------------------------------------------------------------- /images/aligned.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andrewgiuliani/PyGrid2D/05a5580c1525ed30bd0b4211227467a9ef63ccbc/images/aligned.png -------------------------------------------------------------------------------- /images/annulus.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andrewgiuliani/PyGrid2D/05a5580c1525ed30bd0b4211227467a9ef63ccbc/images/annulus.png -------------------------------------------------------------------------------- /images/annulus_zoom.png: -------------------------------------------------------------------------------- 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https://raw.githubusercontent.com/andrewgiuliani/PyGrid2D/05a5580c1525ed30bd0b4211227467a9ef63ccbc/images/ringleb.png -------------------------------------------------------------------------------- /images/ringleb_zoom.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andrewgiuliani/PyGrid2D/05a5580c1525ed30bd0b4211227467a9ef63ccbc/images/ringleb_zoom.png -------------------------------------------------------------------------------- /images/split.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andrewgiuliani/PyGrid2D/05a5580c1525ed30bd0b4211227467a9ef63ccbc/images/split.png -------------------------------------------------------------------------------- /images/tunneled.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andrewgiuliani/PyGrid2D/05a5580c1525ed30bd0b4211227467a9ef63ccbc/images/tunneled.png -------------------------------------------------------------------------------- /pygrid2d/PyGrid2D.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import sys 3 | import argparse 4 | from .bisection import * 5 | from .plot_mesh import * 6 | from .output import * 7 | from .domain import Domain 8 | from .ringleb import Ringleb 9 | from .annulus import Annulus 10 | from .annulus_acoustics import Annulus_acoustics 11 | from .supersonic import Supersonic 12 | from .blobs import Blobs 13 | from .circles import Circles 14 | from .channel import Channel 15 | from .doublemach import DoubleMach 16 | from rich.console import Console 17 | from rich.table import Column, Table 18 | 19 | def PyGrid2D(Nx, Ny, plot_flag, q, bid): 20 | 21 | console = Console() 22 | 23 | if bid == 0: 24 | domain = Annulus() 25 | elif bid == 1: 26 | domain = Supersonic() 27 | elif bid == 2: 28 | domain = Ringleb() 29 | elif bid == 3: 30 | domain = Blobs() 31 | elif bid == 4: 32 | domain = Annulus_acoustics() 33 | elif bid == 5: 34 | domain = Circles() 35 | elif bid == 6: 36 | domain = Channel() 37 | elif bid == 7: 38 | domain = DoubleMach() 39 | else: 40 | quit() 41 | 42 | 43 | dom = np.array([domain.left, domain.bottom, domain.right, domain.top]) 44 | console.print("Embedded grid input", style="bold red") 45 | table = Table(show_header = False) 46 | table.add_column("Name", style="dim", width=15) 47 | table.add_column("Value",justify="right") 48 | table.add_row("(Nx,Ny)", '({},{})'.format(Nx,Ny)) 49 | table.add_row("Domain", '[{},{}] x [{},{}]'.format(dom[0],dom[2], dom[1], dom[3] )) 50 | table.add_row("Grid geometry", domain.name ) 51 | console.print(table) 52 | 53 | 54 | 55 | console.print("Generating the grid...", style="bold blue") 56 | X = np.linspace(dom[0], dom[2], Nx+1) 57 | Y = np.linspace(dom[1], dom[3], Ny+1) 58 | XX,YY = np.meshgrid(X,Y) 59 | XX = np.transpose(XX) 60 | YY = np.transpose(YY) 61 | 62 | 63 | vert_in = domain.in_domain(XX,YY) 64 | idx_vert_in = np.where(vert_in) 65 | num = vert_in[0:-1,0:-1] + vert_in[0:-1,1:] + vert_in[1:,0:-1] + vert_in[1:,1:] 66 | irr = np.equal(num,4).astype(int) 67 | 68 | 69 | cuts = np.logical_and(np.greater(num , 0) , np.less(num, 4) ).astype(int) 70 | num_cuts = np.sum(cuts) 71 | 72 | # grid of booleans that say if horizontal or vertical faces have irregular intersections 73 | # h_bool[0][0] is TRUE ==> cell 0 has a bottom irreg 74 | # h_bool[0][1] is TRUE ==> cell 0 has a top irreg 75 | h_bool = np.logical_xor(vert_in[0:-1,:],vert_in[1:,:]) 76 | v_bool = np.logical_xor(vert_in[:,0:-1],vert_in[:,1:]) 77 | h_idx = np.where( h_bool ) 78 | v_idx = np.where( v_bool ) 79 | 80 | console.print("Computing the x-intersections...", style="bold blue") 81 | xh1 = XX[h_idx[0] , h_idx[1]] 82 | xh2 = XX[h_idx[0]+1, h_idx[1]] 83 | xh = bisection(xh1, xh2, lambda xin : (domain.in_domain(xin,YY[h_idx])-0.5) ) 84 | 85 | console.print("Computing the y-intersections...", style="bold blue") 86 | yv1 = YY[v_idx] 87 | yv2 = YY[v_idx[0], v_idx[1]+1] 88 | yv = bisection(yv1, yv2, lambda yin : (domain.in_domain(XX[v_idx],yin)-0.5) ) 89 | 90 | whole_idx = np.where(irr) 91 | cut_idx = np.where(cuts) 92 | 93 | 94 | has_bot = h_bool[ cut_idx[0] , cut_idx[1] ] 95 | has_top = h_bool[ cut_idx[0] , cut_idx[1]+1] 96 | has_left = v_bool[ cut_idx[0] , cut_idx[1] ] 97 | has_right= v_bool[ cut_idx[0]+1, cut_idx[1] ] 98 | 99 | 100 | # make grid of irregular vertex indices 101 | h_vert_idx = np.cumsum(np.ravel(h_bool)).reshape(h_bool.shape)-1 102 | v_vert_idx = np.cumsum(np.ravel(v_bool)).reshape(v_bool.shape)-1 + (h_vert_idx[-1,-1]+1) 103 | 104 | num_regular_vertices = np.sum(vert_in) 105 | num_vertices = np.sum(vert_in) + xh.size + yv.size 106 | 107 | # assemble all the vertices in the grid 108 | v1 = whole_idx 109 | v2 = (v1[0]+1, v1[1] ) 110 | v3 = (v1[0]+1, v1[1]+1) 111 | v4 = (v1[0] , v1[1]+1) 112 | 113 | # grid of indices assigned to Cartesian vertices 114 | vertex_idx = np.cumsum(np.ravel(vert_in)).reshape(Nx+1,Ny+1)-1 115 | 116 | # compress out the unused Cartesian vertices 117 | regular_vertices = np.hstack( ( 118 | np.compress(np.ravel(vert_in).astype(bool),np.ravel(XX))[:,None], 119 | np.compress(np.ravel(vert_in).astype(bool),np.ravel(YY))[:,None] 120 | ) ) 121 | vertices = np.vstack( ( 122 | regular_vertices, 123 | np.hstack((xh[:,None], YY[h_idx][:,None] )), 124 | np.hstack((XX[v_idx][:,None], yv[:,None])) 125 | ) ) 126 | 127 | 128 | 129 | 130 | 131 | 132 | 133 | 134 | 135 | # assemble the whole cells 136 | cells_whole = np.hstack( ( 137 | vertex_idx[v1][:,None], 138 | vertex_idx[v2][:,None], 139 | vertex_idx[v3][:,None], 140 | vertex_idx[v4][:,None] 141 | ) ) 142 | 143 | 144 | 145 | # assemble the cut cells 146 | h_vert_idx = h_vert_idx + np.sum(vert_in) 147 | v_vert_idx = v_vert_idx + np.sum(vert_in) 148 | 149 | v1 = cut_idx 150 | v2 = (v1[0]+1, v1[1] ) 151 | v3 = (v1[0]+1, v1[1]+1) 152 | v4 = (v1[0] , v1[1]+1) 153 | 154 | v1_idx = np.where( vert_in[v1][:,None], vertex_idx[v1][:,None], -np.ones((num_cuts,1)).astype(int) ) 155 | v12_idx = np.where(has_bot,h_vert_idx[v1],-np.ones(num_cuts) )[:,None] 156 | 157 | v2_idx = np.where( vert_in[v2][:,None], vertex_idx[v2][:,None], -np.ones((num_cuts,1)).astype(int) ) 158 | v23_idx = np.where(has_right,v_vert_idx[v2],-np.ones(num_cuts) )[:,None] 159 | 160 | v3_idx = np.where( vert_in[v3][:,None], vertex_idx[v3][:,None], -np.ones((num_cuts,1)).astype(int) ) 161 | v34_idx = np.where(has_top,h_vert_idx[v4],-np.ones(num_cuts) )[:,None] 162 | 163 | v4_idx = np.where( vert_in[v4][:,None], vertex_idx[v4][:,None], -np.ones((num_cuts,1)).astype(int) ) 164 | v41_idx = np.where(has_left,v_vert_idx[v1],-np.ones(num_cuts) )[:,None] 165 | 166 | cut_vertices = np.hstack( ( v1_idx,v12_idx,v2_idx,v23_idx,v3_idx,v34_idx,v4_idx,v41_idx) ).astype(int) 167 | cut_nv = np.sum( cut_vertices != -1, axis = 1) 168 | 169 | 170 | 171 | 172 | 173 | console.print("Shifting the cut cell vertices...", style="bold blue") 174 | 175 | s_idx = np.argsort(cut_nv) 176 | cut_nv = cut_nv[s_idx] 177 | cut_vertices = cut_vertices[s_idx,:] 178 | cut_idx = (cut_idx[0][s_idx], cut_idx[1][s_idx]) 179 | 180 | irreg_edges = np.zeros( ( num_cuts, 2 ) ).astype(int) 181 | 182 | 183 | 184 | min_nv = np.min(cut_nv) 185 | max_nv = np.max(cut_nv) 186 | cut_cells = [np.array([]) for vv in np.arange(min_nv,max_nv+1)] 187 | cell_list_idx = [ () for vv in np.arange(min_nv,max_nv+1)] 188 | 189 | count = 0 190 | for nv in np.arange(min_nv,max_nv+1): 191 | idx = np.where(cut_nv == nv)[0] 192 | cells_nv = np.ravel(cut_vertices[idx,:]) 193 | 194 | pos_vals = cells_nv > -1 195 | cell_nv = np.compress(pos_vals, cells_nv).reshape((-1,nv)) 196 | 197 | # this is another shift to make sure first and last vertices are edge vertices 198 | cont = 1 199 | while cont: 200 | shift = cell_nv[:,0] < regular_vertices.shape[0] 201 | cell_nv[shift,:] = np.roll(cell_nv[shift,:],1,axis=1) 202 | cont = np.sum(shift) > 0 203 | shift = cell_nv[:,-1] < regular_vertices.shape[0] 204 | cell_nv[shift,:] = np.roll(cell_nv[shift,:],-1,axis=1) 205 | 206 | 207 | cut_cells[nv-min_nv] = cell_nv 208 | cell_list_idx[nv-min_nv] = (cut_idx[0][idx], cut_idx[1][idx]) 209 | irreg_edges[count:count+cell_nv.shape[0],:] = cell_nv[:,(0,-1)] 210 | count = count + cell_nv.shape[0] 211 | 212 | cell_list = [cells_whole] + cut_cells 213 | vertex_count = [4] + list(np.arange(min_nv,max_nv+1)) 214 | cell_ij = [whole_idx] + cell_list_idx 215 | ncf = [0] + [1] * len(cut_cells) 216 | 217 | 218 | console.print("Computing the curved and corner boundaries...", style="bold blue") 219 | corners_flag = domain.is_corner(irreg_edges, vertices) 220 | num_corners = np.sum(corners_flag) 221 | regular_idx = np.where(np.logical_not(corners_flag))[0] 222 | corner_idx = np.where(corners_flag)[0] 223 | 224 | corner_cell_ij = [ () ] * len(cell_list) 225 | corner_cell_list = [np.array([])] * len(cell_list) 226 | corner_cut_nv = cut_nv[corner_idx] 227 | corner_vertex_count = [ v for v in vertex_count] 228 | # remove the corner cells 229 | for c in range(1,len(cell_list)): 230 | idx = np.where( cut_nv == vertex_count[c] )[0] 231 | 232 | keep = np.where(np.logical_not(corners_flag[idx]))[0] 233 | cidx = np.where(corners_flag[idx])[0] 234 | 235 | corner_cell_list[c] = cell_list[c][cidx, :] 236 | corner_cell_ij[c] = (cell_ij[c][0][cidx],cell_ij[c][1][cidx]) 237 | 238 | 239 | cell_list[c] = cell_list[c][keep, :] 240 | cell_ij[c] = (cell_ij[c][0][keep],cell_ij[c][1][keep]) 241 | 242 | cut_nv = cut_nv[regular_idx] 243 | 244 | 245 | if q > 1: 246 | # compute regular high order edges 247 | new_vertices, new_cells = domain.compute_curved(irreg_edges[regular_idx,:], vertices,q) 248 | shift = vertices.shape[0] 249 | new_cells = new_cells + shift 250 | vertices = np.vstack( (vertices, new_vertices) ) 251 | for c in range(1,len(cell_list)): 252 | idx = np.where( cut_nv == vertex_count[c] )[0] 253 | cell_list[c] = np.hstack( (cell_list[c], new_cells[idx,:]) ) 254 | vertex_count[c] = vertex_count[c] + q-1 255 | 256 | 257 | 258 | 259 | 260 | if np.sum(corners_flag) > 0 : 261 | # deal with the corners 262 | 263 | 264 | new_vertices, new_cells = domain.compute_corner(irreg_edges[corner_idx,:], vertices,q) 265 | shift = vertices.shape[0] 266 | new_cells = new_cells + shift 267 | vertices = np.vstack( (vertices, new_vertices) ) 268 | 269 | count = 0 270 | for c in range(1,len(corner_cell_list)): 271 | if corner_cell_list[c].size == 0 : 272 | continue 273 | 274 | idx = corner_cell_list[c].shape[0] 275 | corner_cell_list[c] = np.hstack( (corner_cell_list[c], new_cells[count:count + idx,:]) ) 276 | corner_vertex_count[c] = corner_cell_list[c].shape[1] 277 | count = count + idx 278 | 279 | # append corner bins 280 | cell_list = cell_list + corner_cell_list 281 | vertex_count = vertex_count + corner_vertex_count 282 | cell_ij = cell_ij + corner_cell_ij 283 | ncf = ncf + len(corner_cell_list) * [2] 284 | 285 | 286 | # cell_list - bins of cells 287 | # vertex_count - number of vertices of cells in each bin 288 | # ncf - number of irregular faces associated to cells in each bin 289 | mesh_data = [] 290 | for bin_idx, (c, num_curved_faces) in enumerate(zip(cell_list, ncf)): 291 | cut = bin_idx!=0 292 | for idx in range(c.shape[0]): 293 | faces = [] 294 | 295 | if num_curved_faces == 0: 296 | for vidx in range(c.shape[1]): 297 | v1 = c[idx,vidx] 298 | v2 = c[idx,(vidx+1)%4] 299 | faces.append([v1,v2]) 300 | else: 301 | num_extra = (q-1)*num_curved_faces+(num_curved_faces-1) 302 | final_vidx = c.shape[1]-num_extra 303 | 304 | for vidx in range(final_vidx-1): 305 | v1 = c[idx,vidx] 306 | v2 = c[idx,vidx+1] 307 | faces.append([v1, v2]) 308 | 309 | vertices_extra = list(c[idx,final_vidx-1:]) + [c[idx,0]] 310 | v1 = 0 311 | v2 =q+1 312 | for fidx in range(num_curved_faces): 313 | faces.append( vertices_extra[v1:v2] ) 314 | v1 = v2-1 315 | v2 = v1 + q+1 316 | mesh_data.append({'vertices': c[idx,:], 'num_curved_faces': num_curved_faces, 'faces':faces, 'cut':cut}) 317 | 318 | # order cells by number of faces 319 | face_number = [len(cell['faces']) for cell in mesh_data] 320 | elem_order = np.argsort(face_number) 321 | mesh_data = [mesh_data[idx] for idx in elem_order] 322 | for idx,elem in enumerate(mesh_data): 323 | elem['idx'] = idx 324 | 325 | face_hash = {} 326 | for elem in mesh_data: 327 | for f in elem['faces']: 328 | fkey = tuple(np.sort(f)) 329 | if fkey not in face_hash: 330 | face_hash[fkey] = {'lr':[elem['idx'], -1], 'vertices':f, 'cut':elem['cut']} 331 | else: 332 | face_hash[fkey]['lr'][1] = elem['idx'] 333 | prev_cut = face_hash[fkey]['cut'] 334 | face_hash[fkey]['cut'] = elem['cut'] if prev_cut==0 else prev_cut 335 | 336 | for f in face_hash: 337 | if face_hash[f]['lr'][1] > -1: 338 | continue 339 | x = vertices[f, 0] 340 | y = vertices[f, 1] 341 | bc = domain.vertex2bc(x,y) # returns zero if vertex is a member of multiple or no EBs 342 | final_bc = np.min(bc) # 0 or a negative number 343 | assert final_bc != 0 344 | face_hash[f]['lr'][1] = final_bc 345 | 346 | 347 | face_data = [] 348 | for f in face_hash: 349 | face_data.append(face_hash[f]) 350 | 351 | vertex_number = [len(face['vertices']) for face in face_data] 352 | face_order = np.argsort(vertex_number) 353 | face_data = [face_data[idx] for idx in face_order] 354 | for idx, f in enumerate(face_data): 355 | f['idx'] = idx 356 | 357 | for elem in mesh_data: 358 | elem['fidx'] = np.zeros((len(elem['faces']),)) 359 | for idx, f in enumerate(elem['faces']): 360 | fkey = tuple(np.sort(f)) 361 | elem['fidx'][idx] = face_hash[fkey]['idx'] 362 | 363 | 364 | 365 | 366 | 367 | 368 | 369 | # compute mesh stats 370 | def PolyArea(x,y): 371 | return 0.5*np.abs(np.sum(x * np.roll(y,1,axis=1),axis = 1)-np.sum(y * np.roll(x,1,axis=1), axis = 1)) 372 | area = np.zeros((0,1)) 373 | for cells,nv,ij in zip(cell_list, vertex_count, cell_ij): 374 | if cells.size == 0: 375 | continue 376 | 377 | xcoord = vertices[np.ravel(cells),0].reshape( (cells.shape[0], nv) ) 378 | ycoord = vertices[np.ravel(cells),1].reshape( (cells.shape[0], nv) ) 379 | 380 | in1 = xcoord >= XX[ij][:,None] 381 | in2 = xcoord <= XX[ij[0]+1, ij[1]][:,None] 382 | in3 = ycoord >= YY[ij][:,None] 383 | in4 = ycoord <= YY[ij[0], ij[1]+1][:,None] 384 | 385 | all_in = np.logical_and(in1,in2) 386 | all_in = np.logical_and(all_in,in3) 387 | all_in = np.logical_and(all_in, in4) 388 | any_out = np.logical_not(all_in) 389 | num_out = np.sum(any_out) 390 | 391 | if num_out > 0: 392 | print("There are some geomtrical vertices that lie outside a Cartesian cell") 393 | quit() 394 | 395 | ar = PolyArea(xcoord,ycoord) 396 | area = np.vstack( (area,ar[:,None]) ) 397 | 398 | 399 | 400 | 401 | 402 | reg_vol = area[0] 403 | min_vol_frac = np.min(area) / reg_vol 404 | str_whole = str(cells_whole.shape[0]) 405 | str_cut = str(num_cuts) 406 | str_tot = str(cells_whole.shape[0]+num_cuts) 407 | str_min_vol = '%.8e' % min_vol_frac[0] 408 | 409 | 410 | console.print("Embedded grid metadata", style="bold red") 411 | table = Table(show_header = False) 412 | table.add_column("Name", style="dim", width=15) 413 | table.add_column("Value",justify="right") 414 | table.add_row("whole cells", str_whole) 415 | table.add_row("cut cells", str_cut ) 416 | table.add_row("total cells", str_tot ) 417 | table.add_row("min. vol. frac.", str_min_vol ) 418 | console.print(table) 419 | 420 | # reorder vertices counterclockwise 421 | if plot_flag: 422 | console.print("Plotting...", style="bold blue") 423 | plot_mesh(vertices,cell_list,vertex_count, dom, num_regular_vertices) 424 | 425 | return vertices, cell_list, domain, mesh_data, face_data 426 | -------------------------------------------------------------------------------- /pygrid2d/__init__.py: -------------------------------------------------------------------------------- 1 | from .PyGrid2D import * 2 | -------------------------------------------------------------------------------- /pygrid2d/annulus.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from .domain import Domain 3 | 4 | class Annulus(Domain): 5 | 6 | name = 'annulus' 7 | left = 0 8 | right = 3.0001 9 | bottom = 0 10 | top = 3.0001 11 | R1 = 0.75 12 | R2 = 1.25 13 | sx = 1.5 14 | sy = 1.5 15 | 16 | 17 | def in_domain(self, X,Y): 18 | R = np.sqrt( (X-self.sx)**2. + (Y-self.sy)**2 ) 19 | bval = np.logical_and( np.less_equal(self.R1 , R) , np.less_equal(R , self.R2) ) 20 | return bval.astype(int) 21 | 22 | def bc(self,x,y): 23 | r = np.sqrt( (x-self.sx)**2. + (y-self.sy)**2.) 24 | r1 = -1*(np.abs(r-self.R1) < 1e-14) 25 | r2 = -2*(np.abs(r-self.R2) < 1e-14) 26 | 27 | sanity_check = np.logical_not(np.logical_xor(r1,r2)) 28 | num_wrong = np.sum(sanity_check) 29 | 30 | if(num_wrong > 0): 31 | print("DUPLICATE BOUNDARY CONDITIONS\n") 32 | quit() 33 | 34 | return r1+r2 35 | 36 | def bc_id(self, bid): 37 | return bid 38 | 39 | def vertex2bc(self, x, y): 40 | r = np.sqrt( (x-self.sx)**2. + (y-self.sy)**2.) 41 | r1 = -1*(np.abs(r-self.R1) < 1e-14) 42 | r2 = -1*(np.abs(r-self.R2) < 1e-14) 43 | bc = r1+r2 44 | 45 | decided = np.where(np.logical_xor(r1, r2)) 46 | out = np.zeros(x.shape) 47 | out[decided] = bc[decided] 48 | return out 49 | 50 | 51 | 52 | 53 | def curved_points(self,wgt,X1,Y1,X2,Y2): 54 | bc1 = self.bc(X1,Y1) 55 | bc2 = self.bc(X2,Y2) 56 | sanity_check = np.logical_not( np.equal(bc1,bc2) ) 57 | num_wrong = np.sum(sanity_check) 58 | if(num_wrong > 0): 59 | print("not the same\n") 60 | quit() 61 | 62 | radii = np.where(np.equal(bc1, -1) , self.R1, self.R2) 63 | angle1 = np.arctan2( Y1-self.sy, X1-self.sx ) 64 | angle2 = np.arctan2( Y2-self.sy, X2-self.sx ) 65 | 66 | 67 | idx_jump = np.where(angle2-angle1 > np.pi ) 68 | angle1[idx_jump] = angle1[idx_jump] + 2.* np.pi 69 | idx_jump = np.where(angle2-angle1 < -np.pi ) 70 | angle2[idx_jump] = angle2[idx_jump] + 2.* np.pi 71 | 72 | 73 | angles = wgt[None,:]*angle1[:,None] + (1.-wgt[None,:])*angle2[:,None] 74 | 75 | 76 | points = np.zeros( (angles.shape[0], angles.shape[1], 2) ) 77 | points[:,:,0] = radii[:,None] * np.cos(angles)+self.sx 78 | points[:,:,1] = radii[:,None] * np.sin(angles)+self.sy 79 | return points 80 | 81 | -------------------------------------------------------------------------------- /pygrid2d/annulus_acoustics.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from .domain import Domain 3 | 4 | class Annulus_acoustics(Domain): 5 | 6 | name = 'annulus_acoustics' 7 | left = 0. 8 | right = 21. 9 | bottom = 0. 10 | top = 21. 11 | R1 = 0.5 12 | R2 = 10. 13 | sx = 10.5 14 | sy = 10.5 15 | 16 | 17 | def in_domain(self, X,Y): 18 | R = np.sqrt( (X-self.sx)**2. + (Y-self.sy)**2 ) 19 | bval = np.logical_and( np.less_equal(self.R1 , R) , np.less_equal(R , self.R2) ) 20 | return bval.astype(int) 21 | 22 | def bc(self,x,y): 23 | r = np.sqrt( (x-self.sx)**2. + (y-self.sy)**2.) 24 | r1 = -1*(np.abs(r-self.R1) < 1e-14) 25 | r2 = -2*(np.abs(r-self.R2) < 1e-14) 26 | 27 | sanity_check = np.logical_not(np.logical_xor(r1,r2)) 28 | num_wrong = np.sum(sanity_check) 29 | 30 | if(num_wrong > 0): 31 | print("DUPLICATE BOUNDARY CONDITIONS\n") 32 | quit() 33 | 34 | return r1+r2 35 | 36 | def bc_id(self, bid): 37 | return bid 38 | 39 | def vertex2bc(self, x, y): 40 | r = np.sqrt( (x-self.sx)**2. + (y-self.sy)**2.) 41 | r1 = -1*(np.abs(r-self.R1) < 1e-14) 42 | r2 = -1*(np.abs(r-self.R2) < 1e-14) 43 | bc = r1+r2 44 | 45 | decided = np.where(np.logical_xor(r1, r2)) 46 | out = np.zeros(x.shape) 47 | out[decided] = bc[decided] 48 | return out 49 | 50 | 51 | 52 | 53 | def curved_points(self,wgt,X1,Y1,X2,Y2): 54 | bc1 = self.bc(X1,Y1) 55 | bc2 = self.bc(X2,Y2) 56 | sanity_check = np.logical_not( np.equal(bc1,bc2) ) 57 | num_wrong = np.sum(sanity_check) 58 | if(num_wrong > 0): 59 | print("not the same\n") 60 | quit() 61 | 62 | radii = np.where(np.equal(bc1, -1) , self.R1, self.R2) 63 | angle1 = np.arctan2( Y1-self.sy, X1-self.sx ) 64 | angle2 = np.arctan2( Y2-self.sy, X2-self.sx ) 65 | 66 | 67 | idx_jump = np.where(angle2-angle1 > np.pi ) 68 | angle1[idx_jump] = angle1[idx_jump] + 2.* np.pi 69 | idx_jump = np.where(angle2-angle1 < -np.pi ) 70 | angle2[idx_jump] = angle2[idx_jump] + 2.* np.pi 71 | 72 | 73 | angles = wgt[None,:]*angle1[:,None] + (1.-wgt[None,:])*angle2[:,None] 74 | 75 | 76 | points = np.zeros( (angles.shape[0], angles.shape[1], 2) ) 77 | points[:,:,0] = radii[:,None] * np.cos(angles)+self.sx 78 | points[:,:,1] = radii[:,None] * np.sin(angles)+self.sy 79 | return points 80 | 81 | -------------------------------------------------------------------------------- /pygrid2d/bisection.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | def bisection(a,b,func): 3 | # you only need 55 iterations to get to machine precision 4 | max_step = 55 5 | 6 | init_diff = np.abs(a-b) 7 | 8 | for step in range(max_step): 9 | c = (a + b)/2.0 10 | fa = func(a) 11 | fc = func(c) 12 | fb = func(b) 13 | 14 | a = np.where( np.sign(fc) == np.sign(fa), c, a ) 15 | b = np.where( np.sign(fc) == np.sign(fb), c, b ) 16 | 17 | if init_diff.size > 0: 18 | max_res = np.max(init_diff)/2.**max_step 19 | if max_res > 1e-15: 20 | print("BISECTION NOT CONVERGED {}\n".format(max_res)) 21 | quit() 22 | 23 | return c 24 | -------------------------------------------------------------------------------- /pygrid2d/blobs.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from .domain import Domain 3 | from .bisection import * 4 | 5 | class Blobs(Domain): 6 | name = 'blobs' 7 | left = 0 8 | right = 20. 9 | bottom = 0 10 | top = 20. 11 | num_blobs = 5 12 | num_modes = 7 13 | sx = 10 14 | sy = 10 15 | def __init__(self): 16 | 17 | self.num_blobs = 5 18 | theta = np.linspace( 0, 2 * np.pi, self.num_blobs+1)[:,None] 19 | theta = theta[:-1]-3*np.pi/2 20 | Ro = 5 21 | self.centroids = np.hstack( (Ro * np.cos(theta)+self.sx, Ro*np.sin(theta)+self.sy ) ) 22 | 23 | np.random.seed(1) 24 | self.modes_sin = (np.random.rand( self.num_blobs, self.num_modes )-0.5)*2. 25 | self.modes_cos = (np.random.rand( self.num_blobs, self.num_modes )-0.5)*2. 26 | print(self.modes_sin) 27 | print(self.modes_cos) 28 | 29 | scale = 1.2*np.array( range(1,self.num_modes+1) ) 30 | scale[0] = 1 31 | self.modes_sin[:,0] = 2 32 | self.modes_cos[:,0] = 2 33 | self.modes_sin = self.modes_sin / scale 34 | self.modes_cos = self.modes_cos / scale 35 | 36 | 37 | def in_domain(self, X,Y): 38 | Xp = X.ravel() 39 | Yp = Y.ravel() 40 | R = np.sqrt( (Xp[:,None] - self.centroids[:,0])**2 + (Yp[:,None] - self.centroids[:,1])**2) 41 | theta = np.arctan2(Yp[:,None] - self.centroids[:,1], Xp[:,None] - self.centroids[:,0]) 42 | 43 | ntheta = np.array( range(self.num_modes) )[None,None,:] * theta[:,:,None] 44 | R_blob = np.sum(self.modes_sin[None,:,:] * np.sin(ntheta) + self.modes_cos[None,:,:] * np.cos(ntheta), axis = 2) 45 | 46 | bval = np.logical_not(np.sum(R <= R_blob, axis = 1) > 0) 47 | return bval.astype(int).reshape( X.shape ) 48 | 49 | def bc(self,x,y): 50 | Xp = x.ravel() 51 | Yp = y.ravel() 52 | R = np.sqrt( (Xp[:,None] - self.centroids[:,0])**2 + (Yp[:,None] - self.centroids[:,1])**2) 53 | theta = np.arctan2(Yp[:,None] - self.centroids[:,1], Xp[:,None] - self.centroids[:,0]) 54 | 55 | 56 | ntheta = np.array( range(self.num_modes) )[None,None,:] * theta[:,:,None] 57 | R_blob = np.sum(self.modes_sin[None,:,:] * np.sin(ntheta) + self.modes_cos[None,:,:] * np.cos(ntheta), axis = 2) 58 | 59 | rdiff = np.sqrt( (Xp[:,None]-self.centroids[:,0])**2. + (Yp[:,None]-self.centroids[:,1])**2.)-R_blob 60 | idx = -np.where(rdiff < 1e-14)[1]-1 61 | 62 | return idx 63 | def bc_id(self,bid): 64 | return -1 65 | 66 | def vertex2bc(self,x,y): 67 | Xp = x.ravel() 68 | Yp = y.ravel() 69 | R = np.sqrt( (Xp[:,None] - self.centroids[:,0])**2 + (Yp[:,None] - self.centroids[:,1])**2) 70 | theta = np.arctan2(Yp[:,None] - self.centroids[:,1], Xp[:,None] - self.centroids[:,0]) 71 | 72 | 73 | ntheta = np.array( range(self.num_modes) )[None,None,:] * theta[:,:,None] 74 | R_blob = np.sum(self.modes_sin[None,:,:] * np.sin(ntheta) + self.modes_cos[None,:,:] * np.cos(ntheta), axis = 2) 75 | 76 | rdiff = np.sqrt( (Xp[:,None]-self.centroids[:,0])**2. + (Yp[:,None]-self.centroids[:,1])**2.)-R_blob 77 | decided = np.where(rdiff < 1e-14)[0] 78 | 79 | 80 | out = np.zeros(x.shape) 81 | out[decided] = -1 82 | 83 | if decided.size == 0: 84 | out[:] = -2 85 | return out 86 | 87 | 88 | 89 | def target_ratio(self, wgt, idx,R1, angle1, angle2, R3, angle3) : 90 | X1,Y1 = R1 * np.cos(angle1), R1* np.sin(angle1) 91 | 92 | ntheta = np.array( range(self.num_modes) )[None,:] * angle2[:,None] 93 | R2 = np.sum(self.modes_sin[idx,:] * np.sin(ntheta) + self.modes_cos[idx,:] * np.cos(ntheta), axis = 1) 94 | X2,Y2 = R2 * np.cos(angle2), R2 * np.sin(angle2) 95 | 96 | X3,Y3 = R3 * np.cos(angle3), R3 * np.sin(angle3) 97 | 98 | 99 | l1 = np.sqrt( (X3-X2)**2. + (Y3-Y2)**2. ) 100 | l3 = np.sqrt( (X3-X1)**2. + (Y3-Y1)**2. ) 101 | 102 | return l1/l3 - wgt 103 | 104 | def curved_points(self,wgt,X1,Y1,X2,Y2): 105 | idx = -self.bc(X1,Y1) - 1 106 | 107 | R1 = np.sqrt( (X1 - self.centroids[idx,0])**2 + (Y1 - self.centroids[idx,1])**2) 108 | R2 = np.sqrt( (X2 - self.centroids[idx,0])**2 + (Y2 - self.centroids[idx,1])**2) 109 | angle1 = np.arctan2(Y1 - self.centroids[idx,1], X1 - self.centroids[idx,0]) 110 | angle2 = np.arctan2(Y2 - self.centroids[idx,1], X2 - self.centroids[idx,0]) 111 | 112 | 113 | idx_jump = np.where(angle2-angle1 > np.pi ) 114 | angle1[idx_jump] = angle1[idx_jump] + 2.* np.pi 115 | idx_jump = np.where(angle2-angle1 < -np.pi ) 116 | angle2[idx_jump] = angle2[idx_jump] + 2.* np.pi 117 | 118 | 119 | points = np.zeros( (X1.shape[0], wgt.size, 2) ) 120 | for qq in range(wgt.size): 121 | angle3 = bisection( angle1, angle2, lambda qin : self.target_ratio(wgt[qq], idx,R1, angle1, qin, R2, angle2) ) 122 | 123 | ntheta = np.array( range(self.num_modes) )[None,:] * angle3[:,None] 124 | R3 = np.sum(self.modes_sin[idx,:] * np.sin(ntheta) + self.modes_cos[idx,:] * np.cos(ntheta), axis = 1) 125 | X3,Y3 = R3 * np.cos(angle3)+self.centroids[idx,0], R3 * np.sin(angle3) + self.centroids[idx,1] 126 | 127 | points[:,qq,0] = X3 128 | points[:,qq,1] = Y3 129 | 130 | 131 | 132 | return points 133 | 134 | 135 | -------------------------------------------------------------------------------- /pygrid2d/channel.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from .domain import Domain 3 | 4 | class Channel(Domain): 5 | name = 'channel' 6 | left = 0 7 | right = 5. 8 | bottom = 0 9 | top = 5. 10 | num_blobs = 5 11 | 12 | 13 | def __init__(self): 14 | self.x1 = 6*5/30 + 0.5*5/30 15 | self.y1 = 0 16 | self.s1 = 1. 17 | 18 | self.x2 = 0 19 | self.y2 = 6*5/30 + 0.5*5/30 20 | self.s2 = 1. 21 | 22 | 23 | 24 | def in_domain(self, X,Y): 25 | Xp = X.ravel() 26 | Yp = Y.ravel() 27 | d1 = -self.s1 * (Xp-self.x1) + (Yp-self.y1) 28 | d2 = -self.s2 * (Xp-self.x2) + (Yp-self.y2) 29 | bval = np.logical_and( d1 > 0 , d2 < 0 ) 30 | return bval.astype(int).reshape( X.shape ) 31 | 32 | def bc(self,x,y): 33 | idx = -np.ones( (x.size) ).astype(int) 34 | return idx 35 | def bc_id(self,bid): 36 | return bid[0] 37 | 38 | 39 | def vertex2bc(self, x, y): 40 | d1 = -self.s1 * (x-self.x1) + (y-self.y1) 41 | d2 = -self.s2 * (x-self.x2) + (y-self.y2) 42 | 43 | r1 = -1*(np.abs(d1)<1e-14) 44 | r2 = -1*(np.abs(d2)<1e-14) 45 | left = -2*(np.abs(x-self.left)<1e-14) 46 | right = -2*(np.abs(x-self.right)<1e-14) 47 | top = -2*(np.abs(y-self.top)<1e-14) 48 | bot = -2*(np.abs(y-self.bottom)<1e-14) 49 | bc = r1+r2+top+bot+left+right 50 | 51 | decided = np.where(np.logical_xor(np.logical_xor(np.logical_xor(np.logical_xor(np.logical_xor(r1, r2), top), bot), left), right)) 52 | out = np.zeros(x.shape) 53 | out[decided] = bc[decided] 54 | return out 55 | 56 | 57 | 58 | 59 | 60 | def curved_points(self,wgt,X1,Y1,X2,Y2): 61 | points = np.zeros( (X1.shape[0], wgt.size, 2) ) 62 | points[:,:,0] = wgt[None,:]*X1[:,None] + (1.-wgt[None,:])*X2[:,None] 63 | points[:,:,1] = wgt[None,:]*Y1[:,None] + (1.-wgt[None,:])*Y2[:,None] 64 | return points 65 | -------------------------------------------------------------------------------- /pygrid2d/circles.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from .domain import Domain 3 | 4 | class Circles(Domain): 5 | name = 'circles' 6 | left = 0 7 | right = 20. 8 | bottom = 0 9 | top = 20. 10 | sx = 10 11 | sy = 10 12 | num_blobs = 5 13 | 14 | def __init__(self): 15 | theta = np.linspace( 0, 2 * np.pi, self.num_blobs+1)[:,None] 16 | theta = theta[:-1]-3*np.pi/2 17 | Ro = 5 18 | self.centroids = np.hstack( (Ro * np.cos(theta)+self.sx, Ro*np.sin(theta)+self.sy ) ) 19 | self.num_blobs = self.centroids.shape[0] 20 | self.Ri = 2*np.ones ((1,self.num_blobs) ) 21 | 22 | 23 | def in_domain(self, X,Y): 24 | Xp = X.ravel() 25 | Yp = Y.ravel() 26 | R = np.sqrt( (Xp[:,None] - self.centroids[None,:,0])**2 + (Yp[:,None] - self.centroids[None,:,1])**2) 27 | theta = np.arctan2(Yp[:,None] - self.centroids[:,1], Xp[:,None] - self.centroids[:,0]) 28 | 29 | bval = np.logical_not(np.sum(R <= self.Ri, axis = 1) > 0) 30 | return bval.astype(int).reshape( X.shape ) 31 | 32 | def bc(self,x,y): 33 | Xp = x.ravel() 34 | Yp = y.ravel() 35 | 36 | rdiff = np.sqrt( (Xp[:,None]-self.centroids[:,0])**2. + (Yp[:,None]-self.centroids[:,1])**2.)-self.Ri 37 | bools = rdiff < 1e-14 38 | idx = -np.where(rdiff < 1e-14)[1]-1 39 | return idx 40 | def bc_id(self,bid): 41 | return bid[0] 42 | 43 | 44 | 45 | def vertex2bc(self,x,y): 46 | Xp = x.ravel() 47 | Yp = y.ravel() 48 | 49 | rdiff = np.sqrt( (Xp[:,None]-self.centroids[:,0])**2. + (Yp[:,None]-self.centroids[:,1])**2.)-self.Ri 50 | bools = rdiff < 1e-14 51 | decided = np.where(rdiff < 1e-14)[0] 52 | 53 | out = np.zeros(x.shape) 54 | out[decided] = -1 55 | 56 | if decided.size == 0: 57 | out[:] = -2 58 | return out 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | def curved_points(self,wgt,X1,Y1,X2,Y2): 68 | idx = -self.bc(X1,Y1) - 1 69 | 70 | radii = self.Ri[ 0, idx ] 71 | angle1 = np.arctan2( Y1-self.centroids[idx,1], X1-self.centroids[idx,0] ) 72 | angle2 = np.arctan2( Y2-self.centroids[idx,1], X2-self.centroids[idx,0] ) 73 | 74 | 75 | idx_jump = np.where(angle2-angle1 > np.pi ) 76 | angle1[idx_jump] = angle1[idx_jump] + 2.* np.pi 77 | idx_jump = np.where(angle2-angle1 < -np.pi ) 78 | angle2[idx_jump] = angle2[idx_jump] + 2.* np.pi 79 | 80 | 81 | angles = wgt[None,:]*angle1[:,None] + (1.-wgt[None,:])*angle2[:,None] 82 | 83 | 84 | points = np.zeros( (angles.shape[0], angles.shape[1], 2) ) 85 | points[:,:,0] = radii[:,None] * np.cos(angles)+self.centroids[idx,0][:,None] 86 | points[:,:,1] = radii[:,None] * np.sin(angles)+self.centroids[idx,1][:,None] 87 | 88 | return points 89 | 90 | 91 | 92 | 93 | -------------------------------------------------------------------------------- /pygrid2d/domain.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | class Domain: 3 | 4 | def is_corner(self, irreg_edges, vertices): 5 | X1 = vertices[irreg_edges[:,0], 0] 6 | Y1 = vertices[irreg_edges[:,0], 1] 7 | X2 = vertices[irreg_edges[:,1], 0] 8 | Y2 = vertices[irreg_edges[:,1], 1] 9 | 10 | 11 | bc1 = self.bc(X1,Y1) 12 | bc2 = self.bc(X2,Y2) 13 | vals = np.logical_not(np.equal(bc1,bc2) ) 14 | return vals 15 | 16 | def compute_curved(self, edges,vertices, q): 17 | 18 | 19 | wgt = np.linspace(0.,1.,q+1) 20 | wgt = wgt[1:-1] 21 | X1 = vertices[edges[:,0],0] 22 | Y1 = vertices[edges[:,0],1] 23 | X2 = vertices[edges[:,1],0] 24 | Y2 = vertices[edges[:,1],1] 25 | extra_vertices=self.curved_points(wgt,X1,Y1,X2,Y2) 26 | 27 | out_vertices = extra_vertices.reshape( (-1, 2) ) 28 | out_cells = np.arange(wgt.size * X1.size).reshape( (-1, wgt.size) ) 29 | return out_vertices,out_cells 30 | 31 | 32 | def compute_corner(self, edges, vertices, q): 33 | 34 | X1 = vertices[edges[:,0], 0] 35 | Y1 = vertices[edges[:,0], 1] 36 | X2 = vertices[edges[:,1], 0] 37 | Y2 = vertices[edges[:,1], 1] 38 | bc1 = self.bc(X1,Y1) 39 | bc2 = self.bc(X2,Y2) 40 | sanity_check = np.equal(bc1,bc2) 41 | num_wrong = np.sum(sanity_check) 42 | if(num_wrong > 0): 43 | print("not the same\n") 44 | quit() 45 | num_corners = edges.shape[0] 46 | new_corner_coord = self.get_corner_coord(bc1,bc2) 47 | 48 | wgt = np.linspace(0.,1.,q+1) 49 | wgt1 = wgt[:-1] 50 | wgt2 = wgt[1:-1] 51 | extra_vertices1=self.curved_points(wgt1, X1,Y1,new_corner_coord[:,0],new_corner_coord[:,1]) 52 | extra_vertices2=self.curved_points(wgt2, X2,Y2,new_corner_coord[:,0],new_corner_coord[:,1]) 53 | extra_vertices1[:,:,0] = np.fliplr(extra_vertices1[:,:,0]) 54 | extra_vertices1[:,:,1] = np.fliplr(extra_vertices1[:,:,1]) 55 | # extra_vertices2[:,:,0] = np.fliplr(extra_vertices2[:,:,0]) 56 | # extra_vertices2[:,:,1] = np.fliplr(extra_vertices2[:,:,1]) 57 | 58 | extra_vertices1 = extra_vertices1.reshape( (-1,2) ) 59 | extra_vertices2 = extra_vertices2.reshape( (-1,2) ) 60 | extra_vertices = np.vstack( (extra_vertices1, extra_vertices2) ) 61 | 62 | extra_cells1 = np.arange( 0, X1.shape[0] * q ).reshape( (-1, q ) ) 63 | extra_cells2 = np.zeros( (extra_cells1.shape[0],0) ).astype(int) 64 | if q > 1: 65 | extra_cells2 = np.arange( 0, X1.shape[0] * (q-1) ).reshape( (-1, q-1 ) ) + np.max(extra_cells1)+1 66 | extra_cells = np.fliplr(np.hstack( ( extra_cells1, extra_cells2) )) 67 | 68 | return extra_vertices, extra_cells 69 | -------------------------------------------------------------------------------- /pygrid2d/doublemach.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from .domain import Domain 3 | 4 | class DoubleMach(Domain): 5 | name = 'doublemach' 6 | 7 | def __init__(self): 8 | self.left = 0 9 | self.right = 2.5 10 | self.bottom = 0 11 | self.top = 1.75 12 | self.corner_x = 1./6. 13 | self.corner_y = 1e-10 14 | 15 | def in_domain(self, X,Y): 16 | dist_from_wedge = (X - self.corner_x) * np.sin(30*np.pi/180) + (Y - self.corner_y) * -np.cos(30 * np.pi/180) 17 | bval1 = np.less_equal(dist_from_wedge, 0) 18 | bval2 = np.less_equal(self.corner_y, Y) 19 | bval = np.logical_and(bval1, bval2) 20 | return bval.astype(int) 21 | 22 | def bc_id(self,bid): 23 | return bid 24 | 25 | 26 | 27 | def vertex2bc(self, x, y): 28 | dist_from_wedge = (x - self.corner_x) * np.sin(30*np.pi/180) + (y - self.corner_y) * -np.cos(30 * np.pi/180) 29 | bval1 = -1*np.less_equal(-dist_from_wedge, 1e-14) 30 | bval2 = -1*np.less_equal(y, self.corner_y+1e-14) 31 | left = -2*(np.abs(x-self.left)<1e-14) 32 | right = -2*(np.abs(x-self.right)<1e-14) 33 | top = -2*(np.abs(y-self.top)<1e-14) 34 | 35 | bc = bval1+bval2+left+top+right 36 | 37 | decided = np.where(np.logical_xor(np.logical_xor(np.logical_xor(np.logical_xor(bval1, bval2), left), right), top)) 38 | out = np.zeros(x.shape) 39 | out[decided] = bc[decided] 40 | return out 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | def bc(self,x,y): 49 | dist_from_wedge = (x - self.corner_x) * np.sin(30*np.pi/180) + (y - self.corner_y) * -np.cos(30 * np.pi/180) 50 | bc_out = -1*(np.abs(y-self.corner_y) < 1e-13) - 2 * (np.abs(dist_from_wedge) < 1e-13) 51 | return bc_out.astype(int) 52 | 53 | def curved_points(self,wgt,X1,Y1,X2,Y2): 54 | points = np.zeros( (X1.shape[0], wgt.size, 2) ) 55 | points[:,:,0] = wgt[None,:]*X1[:,None] + (1.-wgt[None,:])*X2[:,None] 56 | points[:,:,1] = wgt[None,:]*Y1[:,None] + (1.-wgt[None,:])*Y2[:,None] 57 | return points 58 | 59 | def get_corner_coord(self,bc1, bc2): 60 | return np.array([self.corner_x, self.corner_y]).reshape((-1,2)) 61 | 62 | -------------------------------------------------------------------------------- /pygrid2d/output.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def output_nor(vertices, mesh_data, face_data, domain, Nx, Ny, q): 4 | assert q == 1 5 | 6 | f = open(domain.name+"_"+str(Nx)+"_"+str(Ny)+"_q" + str(q)+".nor", 'w') 7 | num_faces = len(face_data) 8 | nor = np.zeros((num_faces,3)) 9 | count = 0 10 | for face in face_data: 11 | v = face['vertices'] 12 | x = np.zeros((2,)) 13 | y = np.zeros((2,)) 14 | for i in range(2): 15 | x[i] = vertices[v[i],0] 16 | y[i] = vertices[v[i],1] 17 | dx = x[1]-x[0] 18 | dy = y[1]-y[0] 19 | nn = np.sqrt(dx**2 + dy**2) 20 | nor[count,0] = dy/nn 21 | nor[count,1] = -dx/nn 22 | count+=1 23 | np.savetxt(f,nor) 24 | f.close() 25 | 26 | def output_ply(vertices, cells, domain, Nx, Ny, q): 27 | f = open(domain.name+"_"+str(Nx)+"_"+str(Ny)+"_q" + str(q)+".ply", 'w') 28 | f.write("ply\n") 29 | f.write("format ascii 1.0\n") 30 | f.write("comment this file is a " +str(Nx)+"x"+str(Ny)+" " + domain.name + "\n") 31 | f.write("element vertex " + str(vertices.shape[0]) + "\n") 32 | f.write("property float x\n") 33 | f.write("property float y\n") 34 | tot_count = 0 35 | for c in cells: 36 | tot_count = tot_count + c.shape[0] 37 | 38 | f.write("element face " + str(tot_count) +"\n") 39 | f.write("end_header\n") 40 | np.savetxt(f,vertices) 41 | for c in cells: 42 | np.savetxt(f,c,fmt='%i') 43 | 44 | f.close() 45 | 46 | def output_unstructured(vertices, mesh_data, face_data, domain, Nx, Ny, q): 47 | tot_elem = len(mesh_data) 48 | tot_face = len(face_data) 49 | 50 | f = open(domain.name+"_"+str(Nx)+"_"+str(Ny)+"_q" + str(q)+".unstr", 'w') 51 | f.write("vertices " + str(vertices.shape[0]) + "\n") 52 | np.savetxt(f,vertices) 53 | 54 | f.write("cells " + str(tot_elem) + "\n") 55 | for c in mesh_data: 56 | cdata = np.concatenate( ([c['cut']], c['fidx']) ) 57 | np.savetxt(f, cdata.reshape((1,-1)), fmt='%i') 58 | 59 | f.write("faces " + str(tot_face) + "\n") 60 | for face in face_data: 61 | fdata = np.concatenate( ([face['cut']], face['vertices']) ) 62 | np.savetxt(f, fdata.reshape((1,-1)), fmt='%i') 63 | 64 | f.write("faces left right " + str(tot_face) + "\n") 65 | for face in face_data: 66 | np.savetxt(f, np.array(face['lr']).reshape((1,-1)), fmt='%i') 67 | 68 | 69 | 70 | def output_ag(vertices, cells, cells_ij, nv, ncf, domain, Nx, Ny, q, vertex_idx, vert_in): 71 | 72 | irr = -np.ones( (Nx, Ny) ).astype(int) 73 | irr[cells_ij[0]] = 1 74 | 75 | irr_num = 2 76 | for c in range(1, len(cells_ij)): 77 | if len(cells_ij[c]) > 0: 78 | irr[cells_ij[c]] = np.arange( cells_ij[c][0].size ) + irr_num 79 | irr_num = irr_num + cells_ij[c][0].size 80 | 81 | f = open(domain.name + "_" + str(Nx) + "x" + str(Ny)+"_q"+str(q)+".dat","w") 82 | f.write(str(Nx) + " " + str(Ny) + "\n") 83 | f.write("{:.16E} {:.16E} {:.16E} {:.16E}\n".format(domain.left, domain.bottom, domain.right, domain.top)) 84 | f.write("{:.16E} {:.16E}\n".format( (domain.right - domain.left) / Nx, (domain.top - domain.bottom) / Ny ) ) 85 | np.savetxt(f, irr, fmt = '%i') 86 | f.write("{}\n{}\n{}\n".format(4,0,q) ) 87 | f.write("{}\n".format( 0 ) ) 88 | f.write("{} {}\n".format( -1,-1 )) 89 | dx = (domain.right - domain.left) / Nx 90 | dy = (domain.top - domain.bottom) / Ny 91 | np.savetxt(f, np.array([ [0,0], [0,dy], [dx,dy],[dx,0] ]) , fmt = '%.16E') 92 | 93 | # compute side data 94 | hb_list = [None]*len(cells) 95 | ht_list = [None]*len(cells) 96 | vl_list = [None]*len(cells) 97 | vr_list = [None]*len(cells) 98 | tot_cell_count = 0 99 | for cid1 in range( 1, len(cells) ): 100 | c = cells[cid1] 101 | v = nv[cid1] 102 | tot_cell_count = tot_cell_count + c.shape[0] 103 | if c.shape[0] == 0: 104 | continue 105 | 106 | ij = cells_ij[cid1] 107 | 108 | v1 = ij 109 | v2 = (v1[0]+1, v1[1] ) 110 | v3 = (v1[0]+1, v1[1]+1) 111 | v4 = (v1[0] , v1[1]+1) 112 | 113 | 114 | where_v1 = np.where( np.logical_and(vertex_idx[v1][:,None] == c, vert_in[v1][:,None]) ) 115 | where_v2 = np.where( np.logical_and(vertex_idx[v2][:,None] == c, vert_in[v2][:,None]) ) 116 | where_v3 = np.where( np.logical_and(vertex_idx[v3][:,None] == c, vert_in[v3][:,None]) ) 117 | where_v4 = np.where( np.logical_and(vertex_idx[v4][:,None] == c, vert_in[v4][:,None]) ) 118 | 119 | idx_v1 = -np.ones(c.shape[0]).astype(int) 120 | idx_v2 = -np.ones(c.shape[0]).astype(int) 121 | idx_v3 = -np.ones(c.shape[0]).astype(int) 122 | idx_v4 = -np.ones(c.shape[0]).astype(int) 123 | 124 | idx_v1[where_v1[0]] = where_v1[1] 125 | idx_v2[where_v2[0]] = where_v2[1] 126 | idx_v3[where_v3[0]] = where_v3[1] 127 | idx_v4[where_v4[0]] = where_v4[1] 128 | 129 | hb = np.where( np.logical_and(idx_v1 > -1, idx_v2 > -1) , idx_v1, -1) 130 | hb = np.where( np.logical_and(idx_v1 > -1, idx_v2 == -1) , idx_v1, hb) 131 | hb = np.where( np.logical_and(idx_v1 == -1, idx_v2 > -1) , idx_v2-1, hb) 132 | 133 | ht = np.where( np.logical_and(idx_v3 > -1, idx_v4 > -1) , idx_v3, -1) 134 | ht = np.where( np.logical_and(idx_v3 > -1, idx_v4 == -1) , idx_v3, ht) 135 | ht = np.where( np.logical_and(idx_v3 == -1, idx_v4 > -1) , idx_v4-1, ht) 136 | 137 | 138 | vl = np.where( np.logical_and(idx_v4 > -1, idx_v1 > -1) , idx_v4, -1) 139 | vl = np.where( np.logical_and(idx_v4 > -1, idx_v1 == -1) , idx_v4, vl) 140 | vl = np.where( np.logical_and(idx_v4 == -1, idx_v1 > -1) , idx_v1-1, vl) 141 | 142 | vr = np.where( np.logical_and(idx_v2 > -1, idx_v3 > -1) , idx_v2, -1) 143 | vr = np.where( np.logical_and(idx_v2 > -1, idx_v3 == -1) , idx_v2, vr) 144 | vr = np.where( np.logical_and(idx_v2 == -1, idx_v3 > -1) , idx_v3-1, vr) 145 | 146 | # hb_list[cid1] = hb 147 | # ht_list[cid1] = ht 148 | # vl_list[cid1] = vl 149 | # vr_list[cid1] = vr 150 | # need to flip the sides 151 | num = v - (ncf[cid1] * (q-1) + ncf[cid1] - 1) - 2 152 | hb_list[cid1] = np.where(hb>-1, num-hb, hb) 153 | ht_list[cid1] = np.where(ht>-1, num-ht, ht) 154 | vl_list[cid1] = np.where(vl>-1, num-vl, vl) 155 | vr_list[cid1] = np.where(vr>-1, num-vr, vr) 156 | 157 | 158 | 159 | for cid2 in range(c.shape[0]): 160 | X1 = vertices[c[cid2,0],0] 161 | Y1 = vertices[c[cid2,0],1] 162 | if ncf[cid1] == 1: 163 | X2 = vertices[c[cid2, -ncf[cid1] *(q-1) - 1 ],0] 164 | Y2 = vertices[c[cid2, -ncf[cid1] *(q-1) - 1 ],1] 165 | else: 166 | X2 = vertices[c[cid2, -ncf[cid1] *(q-1) - 1 -1 ],0] 167 | Y2 = vertices[c[cid2, -ncf[cid1] *(q-1) - 1 -1 ],1] 168 | 169 | bc1 = domain.bc(X1,Y1) 170 | bc2 = domain.bc(X2,Y2) 171 | bid1 = domain.bc_id(bc1) 172 | bid2 = domain.bc_id(bc2) 173 | f.write("{}\n{}\n{}\n".format(v - (ncf[cid1] * (q-1) + ncf[cid1] - 1), ncf[cid1] * (q-1) + ncf[cid1] - 1 , q)) 174 | f.write("{}\n".format( ncf[cid1] ) ) 175 | f.write("{} {}\n".format( bid1, bid2 )) 176 | cl = c[cid2,:] 177 | num = v - (ncf[cid1] * (q-1) + ncf[cid1] - 1) 178 | cl[:num] = np.flip(cl[:num]) 179 | cl[num:] = np.flip(cl[num:]) 180 | np.savetxt(f, vertices[cl,:], fmt = '%.16E') 181 | 182 | np.savetxt( f, np.array( [ 3, 2, 1, 0] ).reshape( (1,-1) ).astype(int) , fmt = "%i") 183 | for cid1 in range(1,len(cells)): 184 | c = cells[cid1] 185 | if c.shape[0] == 0: 186 | continue 187 | np.savetxt(f, np.hstack( (hb_list[cid1][:,None], 188 | vr_list[cid1][:,None], 189 | ht_list[cid1][:,None], 190 | vl_list[cid1][:,None] ) ) , fmt = '%i') 191 | 192 | f.close() 193 | 194 | 195 | # from matplotlib import collections as mc 196 | # from matplotlib.collections import LineCollection 197 | # import matplotlib.pyplot as plt 198 | # for cid1 in range(1, len(cells)): 199 | # c = cells[cid1] 200 | # v = nv[cid1] 201 | # if c.shape[0] == 0: 202 | # continue 203 | # 204 | # for cid2 in range(c.shape[0]): 205 | # XX = vertices[c[cid2,:],0] 206 | # YY = vertices[c[cid2,:],1] 207 | # XX = np.hstack( (XX, XX[0] ) ) 208 | # YY = np.hstack( (YY, YY[0] ) ) 209 | # 210 | # plt.plot(XX,YY) 211 | # if hb_list[cid1][cid2] > -1: 212 | # plt.scatter(np.mean(XX[hb_list[cid1][cid2]:hb_list[cid1][cid2]+2]), 213 | # np.mean(YY[hb_list[cid1][cid2]:hb_list[cid1][cid2]+2])+0.01, c = 'black',s=2) 214 | # if ht_list[cid1][cid2] > -1: 215 | # plt.scatter(np.mean(XX[ht_list[cid1][cid2]:ht_list[cid1][cid2]+2]), 216 | # np.mean(YY[ht_list[cid1][cid2]:ht_list[cid1][cid2]+2])-0.01, c = 'green', s=2) 217 | # if vl_list[cid1][cid2] > -1: 218 | # plt.scatter(np.mean(XX[vl_list[cid1][cid2]:vl_list[cid1][cid2]+2])+0.01, 219 | # np.mean(YY[vl_list[cid1][cid2]:vl_list[cid1][cid2]+2]), c = 'blue',s=2) 220 | # if vr_list[cid1][cid2] > -1: 221 | # plt.scatter(np.mean(XX[vr_list[cid1][cid2]:vr_list[cid1][cid2]+2])-0.01, 222 | # np.mean(YY[vr_list[cid1][cid2]:vr_list[cid1][cid2]+2]), c = 'purple', s=2) 223 | # plt.show() 224 | 225 | 226 | 227 | -------------------------------------------------------------------------------- /pygrid2d/plot_mesh.py: -------------------------------------------------------------------------------- 1 | from matplotlib import collections as mc 2 | from matplotlib.collections import LineCollection 3 | import numpy as np 4 | import matplotlib.pyplot as plt 5 | 6 | 7 | 8 | def plot_mesh(vertices, cell_list, vertex_counts, dom, regular_vertices): 9 | 10 | ax = plt.axes() 11 | ax.set_xlim(dom[0], dom[2]) 12 | ax.set_ylim(dom[1], dom[3]) 13 | 14 | for cells,nv in zip(cell_list,vertex_counts): 15 | if cells.size == 0: 16 | continue 17 | 18 | segs = np.zeros((cells.shape[0], nv+1, 2)) 19 | segs[:,0:nv,0] = vertices[np.ravel(cells),0].reshape( (cells.shape[0], nv) ) 20 | segs[:,0:nv,1] = vertices[np.ravel(cells),1].reshape( (cells.shape[0], nv) ) 21 | 22 | segs[:,nv,:] = segs[:,0,:] 23 | line_segments = LineCollection(segs, linestyle='solid', linewidth = 0.5) 24 | 25 | 26 | ax.add_collection(line_segments) 27 | ax.set_aspect('equal', 'box') 28 | 29 | plt.scatter(vertices[regular_vertices:,0], vertices[regular_vertices:,1], color = 'red', s = 1) 30 | plt.scatter(vertices[0:regular_vertices,0], vertices[0:regular_vertices,1], color = 'black', s = 1) 31 | plt.show() 32 | -------------------------------------------------------------------------------- /pygrid2d/ringleb.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from .domain import Domain 3 | from .bisection import * 4 | 5 | class Ringleb(Domain): 6 | gamma = 1.4 7 | gm1 = gamma - 1. 8 | kmin = 0.7 9 | kmax = 1.2 10 | qmin = 0.5 11 | sx = 1.5 12 | sy = 0 13 | name = 'ringleb' 14 | left = 0 15 | right = 2.75 16 | bottom = 0 17 | top = 2.75 18 | 19 | 20 | 21 | def compute_J(self,c): 22 | return 1. / c + 1. / (3. * c ** 3) + 1. / (5. * c ** 5) -.5 * np.log((1. + c) / (1. - c)) 23 | def compute_rho(self,c): 24 | return c ** (2. / self.gm1) 25 | def compute_q2(self,c): 26 | return 2. * (1. - c ** 2) / self.gm1 27 | 28 | def eqn(self,x, y, c): 29 | J = self.compute_J(c) 30 | rho = self.compute_rho(c) 31 | q2 = self.compute_q2(c) 32 | 33 | return (x - J / 2.) ** 2 + y ** 2 - 1. / (4. * rho ** 2 * q2 ** 2) 34 | 35 | def compute_c(self,x, y): 36 | clow =.5*np.ones(x.size) 37 | chigh = 0.9999*np.ones(x.size) 38 | 39 | c = bisection(clow, chigh, lambda cin : self.eqn(np.ravel(x),np.ravel(y),cin) ) 40 | return c.reshape(x.shape) 41 | 42 | def kq2xy(self, k, q): 43 | c = np.sqrt(2. + q**2 - self.gamma * q**2)/np.sqrt(2) 44 | J = self.compute_J(c) 45 | rho = self.compute_rho(c) 46 | q2 = q**2 47 | k2 = k**2 48 | 49 | x = (0.5/rho) * (1./q2 - 2./k**2.) + 0.5 * J + self.sx 50 | y = np.sqrt(1. - q2/k**2.)/(k * rho * q ) + self.sy 51 | return x,y 52 | 53 | def xy2kq(self,x,y): 54 | x = x - self.sx 55 | y = y - self.sy 56 | 57 | c = self.compute_c(x, y) 58 | J = self.compute_J(c) 59 | rho = self.compute_rho(c) 60 | q2 = self.compute_q2(c) 61 | 62 | q = np.sqrt(q2) 63 | k = np.sqrt(2. / (1. / q2 - 2. * rho * (x - J / 2.))) 64 | return k,q 65 | 66 | def in_domain(self,x,y): 67 | k,q = self.xy2kq(x,y) 68 | c1 = np.greater_equal(q,self.qmin) 69 | c2 = np.logical_and(np.less_equal(self.kmin, k), np.less_equal(k,self.kmax) ) 70 | return np.logical_and(c1,c2).astype(int) 71 | 72 | def bc_id(self, bid): 73 | if bid == -1 or bid == -2: 74 | return -1 75 | else: 76 | return -2 77 | 78 | # DEPRECATE THIS. 79 | def bc(self,x,y): 80 | k,q = self.xy2kq(x,y) 81 | dk_min = -1*(np.abs(k-self.kmin) < 1e-13) 82 | dk_max = -2*(np.abs(k-self.kmax) < 1e-13) 83 | dq_min = -3*(np.abs(q-self.qmin) < 1e-13) 84 | 85 | sanity_check = np.logical_not(np.logical_xor(np.logical_xor(dk_min, dk_max), dq_min)) 86 | num_wrong = np.sum(sanity_check) 87 | if(num_wrong > 0): 88 | print("DUPLICATE BOUNDARY CONDITIONS\n") 89 | quit() 90 | 91 | return dk_min+dk_max+dq_min 92 | 93 | # -1 reflecting, -2 is inflow/outflow 94 | def vertex2bc(self, x, y): 95 | k,q = self.xy2kq(x,y) 96 | dk_min = -1*(np.abs(k-self.kmin) < 1e-13) 97 | dk_max = -1*(np.abs(k-self.kmax) < 1e-13) 98 | dq_min = -2*(np.abs(q-self.qmin) < 1e-13) 99 | bot = -2*(np.abs(y) < 1e-13) 100 | bc = dk_min+dk_max+dq_min+bot 101 | decided = np.where(np.logical_xor(np.logical_xor(np.logical_xor(dk_min, dk_max), dq_min), bot)) 102 | 103 | out = np.zeros(x.shape) 104 | out[decided] = bc[decided] 105 | return out 106 | 107 | 108 | def target_ratio(self, wgt, k1, q1, k2, q2, k3, q3) : 109 | X1,Y1 = self.kq2xy(k1,q1) 110 | X2,Y2 = self.kq2xy(k2,q2) 111 | X3,Y3 = self.kq2xy(k3,q3) 112 | 113 | l1 = np.sqrt( (X3-X2)**2. + (Y3-Y2)**2. ) 114 | l3 = np.sqrt( (X3-X1)**2. + (Y3-Y1)**2. ) 115 | 116 | return l1/l3 - wgt 117 | 118 | 119 | def curved_points(self,wgt,X1,Y1,X2,Y2): 120 | bc1 = self.bc(X1,Y1) 121 | # bc2 = self.bc(X2,Y2) 122 | # sanity_check = np.logical_not( np.equal(bc1,bc2) ) 123 | # num_wrong = np.sum(sanity_check) 124 | # if(num_wrong > 0): 125 | # print("not the same\n") 126 | # quit() 127 | 128 | 129 | points = np.zeros( (X1.shape[0], wgt.size, 2) ) 130 | for qq in range(wgt.size): 131 | # boundary -1 132 | idx1 = np.where( bc1 == -1 )[0] 133 | k1,q1 = self.xy2kq(X1[idx1], Y1[idx1]) 134 | k3,q3 = self.xy2kq(X2[idx1], Y2[idx1]) 135 | q2 = bisection( q1, q3, lambda qin : self.target_ratio(wgt[qq], self.kmin, q1, 136 | self.kmin, qin, 137 | self.kmin, q3 ) ) 138 | x2,y2 = self.kq2xy(self.kmin,q2) 139 | points[idx1,qq,0] = x2 140 | points[idx1,qq,1] = y2 141 | 142 | # boundary -2 143 | idx2 = np.where( bc1 == -2)[0] 144 | k1,q1 = self.xy2kq(X1[idx2], Y1[idx2]) 145 | k3,q3 = self.xy2kq(X2[idx2], Y2[idx2]) 146 | q2 = bisection( q1, q3, lambda qin : self.target_ratio(wgt[qq], self.kmax, q1, 147 | self.kmax, qin, 148 | self.kmax, q3 ) ) 149 | 150 | x2,y2 = self.kq2xy(self.kmax,q2) 151 | points[idx2,qq,0] = x2 152 | points[idx2,qq,1] = y2 153 | 154 | 155 | # boundary -3 156 | idx3 = np.where( bc1 == -3)[0] 157 | k1,q1 = self.xy2kq(X1[idx3], Y1[idx3]) 158 | k3,q3 = self.xy2kq(X2[idx3], Y2[idx3]) 159 | k2 = bisection( k1, k3, lambda kin : self.target_ratio(wgt[qq], k1 , self.qmin, 160 | kin, self.qmin, 161 | k3 , self.qmin ) ) 162 | 163 | x2,y2 = self.kq2xy(k2,self.qmin) 164 | points[idx3,qq,0] = x2 165 | points[idx3,qq,1] = y2 166 | 167 | 168 | 169 | 170 | return points 171 | 172 | 173 | 174 | 175 | def get_corner_coord(self,bc1, bc2): 176 | k13,q13 = self.kq2xy(np.array([self.kmin]), np.array([self.qmin])) 177 | k23,q23 = self.kq2xy(np.array([self.kmax]), np.array([self.qmin])) 178 | 179 | corner13 = np.hstack( (k13,q13) ).reshape( (-1,2) ) 180 | corner23 = np.hstack( (k23,q23) ).reshape( (-1,2) ) 181 | 182 | corner_coords = np.zeros( (bc1.shape[0], 2) ) 183 | corner_coords[:,0] = np.where( np.logical_and(bc1 == -1,bc2 == -3) , corner13[:,0], corner23[:,0] ) 184 | corner_coords[:,1] = np.where( np.logical_and(bc1 == -1,bc2 == -3) , corner13[:,1], corner23[:,1] ) 185 | 186 | return corner_coords 187 | 188 | 189 | 190 | 191 | 192 | -------------------------------------------------------------------------------- /pygrid2d/supersonic.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from .domain import Domain 3 | 4 | class Supersonic(Domain): 5 | name = 'supersonic' 6 | left = 0 7 | right = 1.43 8 | bottom = 0 9 | top = 1.43 10 | R1 = 1. 11 | R2 = 1.384 12 | 13 | 14 | def in_domain(self, X,Y): 15 | 16 | R = np.sqrt( X**2 + Y**2) 17 | bval = np.logical_and( np.less_equal(self.R1 , R) , np.less_equal(R , self.R2) ) 18 | return bval.astype(int) 19 | def bc_id(self,bid): 20 | return bid 21 | def bc(self,x,y): 22 | r = np.sqrt(x**2. + y**2.) 23 | r1 = -1*(np.abs(r-self.R1) < 1e-14) 24 | r2 = -2*(np.abs(r-self.R2) < 1e-14) 25 | 26 | sanity_check = np.logical_not(np.logical_xor(r1,r2)) 27 | num_wrong = np.sum(sanity_check) 28 | if(num_wrong > 0): 29 | print("DUPLICATE BOUNDARY CONDITIONS\n") 30 | quit() 31 | 32 | return r1+r2 33 | 34 | # -1 reflecting, -2 is inflow/outflow 35 | def vertex2bc(self, x, y): 36 | r = np.sqrt(x**2. + y**2.) 37 | r1 = -1*(np.abs(r-self.R1) < 1e-14) 38 | r2 = -1*(np.abs(r-self.R2) < 1e-14) 39 | bot= -2*(np.abs(y < 1e-14)) 40 | left=-2*(np.abs(x < 1e-14)) 41 | bc = r1+r2+bot+left 42 | decided = np.where(np.logical_xor(np.logical_xor(np.logical_xor(r1, r2), bot), left)) 43 | out = np.zeros(x.shape) 44 | out[decided] = bc[decided] 45 | return out 46 | 47 | 48 | 49 | 50 | 51 | def curved_points(self,wgt,X1,Y1,X2,Y2): 52 | bc1 = self.bc(X1,Y1) 53 | bc2 = self.bc(X2,Y2) 54 | sanity_check = np.logical_not( np.equal(bc1,bc2) ) 55 | num_wrong = np.sum(sanity_check) 56 | if(num_wrong > 0): 57 | print("not the same\n") 58 | quit() 59 | 60 | radii = np.where(np.equal(bc1, -1) , self.R1, self.R2) 61 | angle1 = np.arctan2( Y1, X1 ) 62 | angle2 = np.arctan2( Y2, X2 ) 63 | angles = wgt[None,:]*angle1[:,None] + (1.-wgt[None,:])*angle2[:,None] 64 | 65 | points = np.zeros( (angles.shape[0], angles.shape[1], 2) ) 66 | points[:,:,0] = radii[:,None] * np.cos(angles) 67 | points[:,:,1] = radii[:,None] * np.sin(angles) 68 | return points 69 | 70 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | from setuptools import setup, Extension 2 | from setuptools.command.build_ext import build_ext 3 | import sys 4 | import os 5 | import setuptools 6 | 7 | __version__ = '0.0.1' 8 | 9 | setup( 10 | name='PyGrid2D', 11 | long_description='', 12 | install_requires=['numpy', 'scipy', 'argparse', 'matplotlib', 'pytest', 'rich'], 13 | packages = ["pygrid2d"], 14 | package_dir = {"pygrid2d": "pygrid2d"}, 15 | zip_safe=False, 16 | ) 17 | -------------------------------------------------------------------------------- /tests/data/annulus_10_10_q1.ply: -------------------------------------------------------------------------------- 1 | ply 2 | format ascii 1.0 3 | comment this file is a 10x10 annulus 4 | element vertex 92 5 | property float x 6 | property float y 7 | element face 64 8 | end_header 9 | 3.000099999999999989e-01 1.200039999999999996e+00 10 | 3.000099999999999989e-01 1.500049999999999883e+00 11 | 3.000099999999999989e-01 1.800059999999999993e+00 12 | 6.000199999999999978e-01 9.000299999999999967e-01 13 | 6.000199999999999978e-01 1.200039999999999996e+00 14 | 6.000199999999999978e-01 1.500049999999999883e+00 15 | 6.000199999999999978e-01 1.800059999999999993e+00 16 | 6.000199999999999978e-01 2.100070000000000103e+00 17 | 9.000299999999999967e-01 6.000199999999999978e-01 18 | 9.000299999999999967e-01 9.000299999999999967e-01 19 | 9.000299999999999967e-01 2.100070000000000103e+00 20 | 9.000299999999999967e-01 2.400079999999999991e+00 21 | 1.200039999999999996e+00 3.000099999999999989e-01 22 | 1.200039999999999996e+00 6.000199999999999978e-01 23 | 1.200039999999999996e+00 2.400079999999999991e+00 24 | 1.200039999999999996e+00 2.700089999999999879e+00 25 | 1.500049999999999883e+00 3.000099999999999989e-01 26 | 1.500049999999999883e+00 6.000199999999999978e-01 27 | 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709 | 84 94 95 85 710 | 85 95 96 86 711 | 86 96 97 87 712 | 87 97 98 88 713 | 88 98 99 89 714 | 89 99 100 90 715 | 90 100 101 91 716 | 93 102 103 94 717 | 94 103 104 95 718 | 95 104 105 96 719 | 96 105 106 97 720 | 97 106 107 98 721 | 98 107 108 99 722 | 99 108 109 100 723 | 100 109 110 101 724 | 102 112 113 103 725 | 103 113 114 104 726 | 104 114 115 105 727 | 105 115 116 106 728 | 106 116 117 107 729 | 107 117 118 108 730 | 108 118 119 109 731 | 111 121 122 112 732 | 112 122 123 113 733 | 113 123 124 114 734 | 114 124 125 115 735 | 115 125 126 116 736 | 116 126 127 117 737 | 117 127 128 118 738 | 118 128 129 119 739 | 120 131 132 121 740 | 121 132 133 122 741 | 122 133 134 123 742 | 123 134 135 124 743 | 124 135 136 125 744 | 125 136 137 126 745 | 126 137 138 127 746 | 127 138 139 128 747 | 130 141 142 131 748 | 131 142 143 132 749 | 132 143 144 133 750 | 133 144 145 134 751 | 134 145 146 135 752 | 135 146 147 136 753 | 136 147 148 137 754 | 137 148 149 138 755 | 138 149 150 139 756 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485 933 | 374 323 322 373 486 487 934 | 373 322 321 372 488 489 935 | 343 174 175 344 490 491 936 | 372 321 320 371 492 493 937 | 371 320 319 370 494 495 938 | 370 319 318 369 496 497 939 | 346 187 188 347 498 499 940 | 361 276 275 360 500 501 941 | 348 202 203 349 502 503 942 | 367 314 313 366 504 505 943 | 349 203 204 350 506 507 944 | 350 204 205 351 508 509 945 | 351 205 206 352 510 511 946 | 352 206 207 353 512 513 947 | 365 304 303 364 514 515 948 | 353 207 208 354 516 517 949 | 357 222 221 356 518 519 950 | 363 291 290 362 520 521 951 | 416 186 201 418 522 523 952 | 368 315 314 367 524 525 953 | 379 9 0 377 526 527 954 | 340 162 163 341 528 529 955 | 397 84 75 395 530 531 956 | 388 49 57 390 532 533 957 | 401 102 93 399 534 535 958 | 400 101 110 402 536 537 959 | 389 50 42 387 538 539 960 | 393 67 58 391 540 541 961 | 386 41 49 388 542 543 962 | 404 119 129 406 544 545 963 | 396 83 92 398 546 547 964 | 387 42 34 385 548 549 965 | 376 325 324 375 550 551 966 | 385 34 26 383 552 553 967 | 382 25 33 384 554 555 968 | 383 26 18 381 556 557 969 | 408 139 150 410 558 559 970 | 394 74 83 396 560 561 971 | 381 18 9 379 562 563 972 | 378 8 17 380 564 565 973 | 384 33 41 386 566 567 974 | 390 57 66 392 568 569 975 | 366 313 312 323 426 570 571 976 | 327 58 59 50 389 572 573 977 | 364 303 302 315 425 574 575 978 | 369 318 317 325 427 576 577 979 | 326 17 16 25 382 578 579 980 | 362 290 289 304 424 580 581 981 | 328 66 65 74 394 582 583 982 | 341 163 164 151 411 584 585 983 | 329 75 76 67 393 586 587 984 | 342 161 160 173 414 588 589 985 | 339 150 149 161 412 590 591 986 | 338 151 152 140 409 592 593 987 | 344 175 176 162 413 594 595 988 | 345 173 172 186 416 596 597 989 | 337 140 141 130 407 598 599 990 | 336 129 128 139 408 600 601 991 | 335 130 131 120 405 602 603 992 | 360 275 274 291 423 604 605 993 | 347 188 189 174 415 606 607 994 | 333 110 109 119 404 608 609 995 | 332 111 112 102 401 610 611 996 | 331 92 91 101 400 612 613 997 | 354 208 209 187 417 614 615 998 | 355 201 200 222 419 616 617 999 | 330 93 94 84 397 618 619 1000 | 356 221 220 241 420 620 621 1001 | 359 259 258 276 422 622 623 1002 | 334 120 121 111 403 624 625 1003 | 358 241 240 259 421 626 627 1004 | -------------------------------------------------------------------------------- /tests/test_PyGrid.py: -------------------------------------------------------------------------------- 1 | import pytest 2 | import numpy as np 3 | import pygrid2d as pg2d 4 | 5 | 6 | def load_vertices_elem(domain, Nx, Ny, q): 7 | f = open("./data/" + domain.name+"_"+str(Nx)+"_"+str(Ny)+"_q" + str(q)+".ply", 'r') 8 | line = f.readline() 9 | line = f.readline() 10 | line = f.readline() 11 | line = f.readline().split(" ") 12 | Nv = int(line[-1]) 13 | 14 | line = f.readline() 15 | line = f.readline() 16 | line = f.readline() 17 | line = f.readline() 18 | 19 | vertices = np.zeros( (Nv, 2) ) 20 | for v in range(Nv): 21 | line = f.readline().split(" ") 22 | line = [float(l.strip('\n')) for l in line] 23 | line = np.array(line) 24 | vertices[v,:] = line 25 | 26 | return vertices 27 | 28 | @pytest.mark.parametrize("Nx,Ny,q,bid", [ 29 | (10,10,1,0), 30 | (20,20,2,0), 31 | (30,30,3,0), 32 | (40,40,4,0), 33 | (50,50,5,0), 34 | (10,10,1,1), 35 | (20,20,2,1), 36 | (30,30,3,1), 37 | (40,40,4,1), 38 | (50,50,5,1), 39 | (10,10,1,2), 40 | (20,20,2,2), 41 | (30,30,3,2), 42 | (40,40,4,2) 43 | ]) 44 | def test_PyGrid(Nx, Ny, q, bid): 45 | vertices, elem, domain, mesh_data, face_data = pg2d.PyGrid2D(Nx, Ny, False, q, bid) 46 | vertices_loaded = load_vertices_elem(domain, Nx, Ny, q) 47 | 48 | err = np.linalg.norm(vertices - vertices_loaded) 49 | assert err < 1e-12 50 | --------------------------------------------------------------------------------