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Grid generator

Project description

FDGrid : Finite difference grid generator

Grid generator

Introducing FDGrid

FDGrid provides some tools to create regular, adaptative or curvilinear 2D grids. FDGrid has been designed to work with nsfds2 but can also be used alone. FDGrid provides tool to:

  • Generate 2D meshes : x and z coordinates
  • Subdivide the grid into Subdomain objects used by nsfds2

FDGrid provides 3 main types of objects to create meshes:

  • Mesh(): Create a regular mesh

  • AdaptativeMesh(): Create a mesh that is adapted around obstacles and close to the boundaries

  • CurvilinearMesh(): Create a mesh using curvilinear coordinates

FDGrid provides two main objects to create computation domains and/or sets of obstacles:

  • Domain() : Container for Subdomain objects

  • Subdomain() : Subdivision of the grid

Requirements and installation

Requirements

  • python > 3.7
  • matplotlib > 3.0
  • numpy > 1.1
  • scipy > 1.1
  • ofdlib2 > 0.8

Installation

python setup.py install

or

pip install fdgrid

Classical use

Create set of obstacles

Domain and Subdomain objects can be used to create sets of obstacles.

  • Use Subdomain to create an obstacle:

    • First argument is a list of coordinates as [left, bottom, right, top]
    • Second argument is the boundary conditions [(R)igid, (A)bsorbing, (Z)impedance]
  • Use Domain to gather all Subdomain objects:

    • First argument is the shape of the grid (tuple)
    • Keyword argument data is a list of Subdomain objects

For instance:

from fdgrid import mesh, templates
from fdgrid.domains import Subdomain, Domain

def custom_obstacles(nx, nz):

    geo = [Subdomain([30, 20, 40, 40], 'RRRR'),
           Subdomain([60, 20, 70, 40], 'RRRR'),
           Subdomain([90, 20, 100, 40], 'RRRR')]

    return Domain((nx, nz), data=geo)

nx, nz = 128, 64
dx, dz = 1., 1.
ix0, iz0 = 0, 0
bc = 'ARAR'

mesh2 = mesh.Mesh((nx, nz), (dx, dz), (ix0, iz0), obstacles=custom_obstacles(nx, nz), bc=bc)
mesh2.plot_grid(pml=True)

domains

Simple adaptative mesh example

from fdgrid import mesh, templates, domains


shape = (512, 256)	# Dimensions of the grid
steps = (1, 1)		# grid steps
ix0, iz0 = 0, 0		# grid origin
bc = 'RRRR' 		# Boundary conditions : left, bottom, right, top.
			# Can be (R)igid, (A)bsorbing, (P)eriodic, (Z)impedance

# Set up obstacles in the grid with a template
obstacles = templates.testcase1(*shape)

# Generate AdaptativeMesh object
msh = mesh.AdaptativeMesh(shape, steps, (ix0, iz0), obstacles=obstacles, bc=bc)

# Show
msh.plot_grid(N=8)

adaptative mesh

Simple curvilinear mesh example

from fdgrid import mesh, templates
import numpy as np

shape = (256, 256)       # Dimensions of the grid
steps = (1e-4, 1e-4)     # grid steps
origin = (128, 0)        # grid origin
bc = 'RRRR'              # Boundary conditions : left, bottom, right, top.
                         # Can be (R)igid, (A)bsorbing, (P)eriodic, (Z)impedance

# Set up obstacles in the grid with a template
obstacles = templates.helmholtz_double(nx, nz)

# Setup curvilinear transformation
def curv(xn, zn):
    f = 5*dx
    xp = xn.copy()
    zp = zn + np.exp(-np.linspace(0, 10, zn.shape[1]))*np.sin(2*np.pi*f*xn/xn.max()/2)
    return xp, zp

# Generate CurvilinearMesh object
msh = mesh.CurvilinearMesh(shape, steps, origin, obstacles=obstacles, bc=bc, fcurvxz=curv)

# Show physical grid
msh.plot_physical()

curvilinear mesh

Project details


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