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https://github.com/smyalygames/FiniteVolumeGPU_HIP.git
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355 lines
9.7 KiB
Python
355 lines
9.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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This python module implements Cuda context handling
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Copyright (C) 2018 SINTEF ICT
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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"""
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from GPUSimulators.Simulator import BoundaryCondition
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import numpy as np
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import gc
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def getExtent(width, height, nx, ny, grid, index=None):
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if grid is not None:
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gx = grid.grid[0]
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gy = grid.grid[1]
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if index is not None:
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i, j = grid.getCoordinate(index)
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else:
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i, j = grid.getCoordinate()
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dx = (width / gx) / nx
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dy = (height / gy) / ny
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x0 = width*i/gx + 0.5*dx
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y0 = height*j/gy + 0.5*dy
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x1 = width*(i+1)/gx - 0.5*dx
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y1 = height*(j+1)/gy - 0.5*dx
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else:
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dx = width / nx
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dy = height / ny
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x0 = 0.5*dx
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y0 = 0.5*dy
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x1 = width-0.5*dx
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y1 = height-0.5*dy
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return [x0, x1, y0, y1, dx, dy]
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def downsample(highres_solution, x_factor, y_factor=None):
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if (y_factor == None):
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y_factor = x_factor
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assert(highres_solution.shape[1] % x_factor == 0)
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assert(highres_solution.shape[0] % y_factor == 0)
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if (x_factor*y_factor == 1):
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return highres_solution
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if (len(highres_solution.shape) == 1):
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highres_solution = highres_solution.reshape((1, highres_solution.size))
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nx = highres_solution.shape[1] / x_factor
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ny = highres_solution.shape[0] / y_factor
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return highres_solution.reshape([int(ny), int(y_factor), int(nx), int(x_factor)]).mean(3).mean(1)
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def bump(nx, ny, width, height,
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bump_size=None,
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ref_nx=None, ref_ny=None,
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x_center=0.5, y_center=0.5,
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h_ref=0.5, h_amp=0.1, u_ref=0.0, u_amp=0.1, v_ref=0.0, v_amp=0.1):
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if (ref_nx == None):
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ref_nx = nx
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assert(ref_nx >= nx)
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if (ref_ny == None):
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ref_ny = ny
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assert(ref_ny >= ny)
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if (bump_size == None):
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bump_size = width/5.0
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ref_dx = width / float(ref_nx)
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ref_dy = height / float(ref_ny)
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x_center = ref_dx*ref_nx*x_center
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y_center = ref_dy*ref_ny*y_center
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x = ref_dx*(np.arange(0, ref_nx, dtype=np.float32)+0.5) - x_center
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y = ref_dy*(np.arange(0, ref_ny, dtype=np.float32)+0.5) - y_center
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xv, yv = np.meshgrid(x, y, sparse=False, indexing='xy')
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r = np.sqrt(xv**2 + yv**2)
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xv = None
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yv = None
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gc.collect()
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#Generate highres then downsample
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#h_highres = 0.5 + 0.1*np.exp(-(xv**2/size + yv**2/size))
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h_highres = h_ref + h_amp*0.5*(1.0 + np.cos(np.pi*r/bump_size)) * (r < bump_size)
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h = downsample(h_highres, ref_nx/nx, ref_ny/ny)
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h_highres = None
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gc.collect()
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#hu_highres = 0.1*np.exp(-(xv**2/size + yv**2/size))
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u_highres = u_ref + u_amp*0.5*(1.0 + np.cos(np.pi*r/bump_size)) * (r < bump_size)
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hu = downsample(u_highres, ref_nx/nx, ref_ny/ny)*h
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u_highres = None
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gc.collect()
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#hu_highres = 0.1*np.exp(-(xv**2/size + yv**2/size))
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v_highres = v_ref + v_amp*0.5*(1.0 + np.cos(np.pi*r/bump_size)) * (r < bump_size)
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hv = downsample(v_highres, ref_nx/nx, ref_ny/ny)*h
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v_highres = None
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gc.collect()
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dx = width/nx
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dy = height/ny
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return h, hu, hv, dx, dy
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def genShockBubble(nx, ny, gamma, grid=None):
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"""
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Generate Shock-bubble interaction case for the Euler equations
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"""
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width = 4.0
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height = 1.0
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g = 0.0
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rho = np.ones((ny, nx), dtype=np.float32)
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u = np.zeros((ny, nx), dtype=np.float32)
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v = np.zeros((ny, nx), dtype=np.float32)
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E = np.zeros((ny, nx), dtype=np.float32)
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p = np.ones((ny, nx), dtype=np.float32)
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x0, x1, y0, y1, dx, dy = getExtent(width, height, nx, ny, grid)
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x = np.linspace(x0, x1, nx, dtype=np.float32)
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y = np.linspace(y0, y1, ny, dtype=np.float32)
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xv, yv = np.meshgrid(x, y, sparse=False, indexing='xy')
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#Bubble
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radius = 0.25
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x_center = 0.5
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y_center = 0.5
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bubble = np.sqrt((xv-x_center)**2+(yv-y_center)**2) <= radius
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rho = np.where(bubble, 0.1, rho)
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#Left boundary
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left = (xv < 0.1)
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rho = np.where(left, 3.81250, rho)
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u = np.where(left, 2.57669, u)
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#Energy
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p = np.where(left, 10.0, p)
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E = 0.5*rho*(u**2+v**2) + p/(gamma-1.0)
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bc = BoundaryCondition({
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'north': BoundaryCondition.Type.Reflective,
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'south': BoundaryCondition.Type.Reflective,
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'east': BoundaryCondition.Type.Periodic,
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'west': BoundaryCondition.Type.Periodic
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})
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#Construct simulator
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arguments = {
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'rho': rho, 'rho_u': rho*u, 'rho_v': rho*v, 'E': E,
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'nx': nx, 'ny': ny,
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'dx': dx, 'dy': dy,
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'g': g,
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'gamma': gamma,
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'boundary_conditions': bc
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}
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return arguments
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def genKelvinHelmholtz(nx, ny, gamma, roughness=0.125, grid=None, index=None):
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"""
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Roughness parameter in (0, 1.0] determines how "squiggly"
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the interface betweeen the zones is
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"""
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def genZones(nx, ny, n):
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"""
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Generates the zones of the two fluids of K-H
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"""
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zone = np.zeros((ny, nx), dtype=np.int32)
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def genSmoothRandom(nx, n):
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n = max(1, min(n, nx))
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if n == nx:
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return np.random.random(nx)-0.5
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else:
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from scipy.interpolate import interp1d
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#Control points and interpolator
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xp = np.linspace(0.0, 1.0, n)
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yp = np.random.random(n) - 0.5
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if (n == 1):
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kind = 'nearest'
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elif (n == 2):
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kind = 'linear'
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elif (n == 3):
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kind = 'quadratic'
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else:
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kind = 'cubic'
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f = interp1d(xp, yp, kind=kind)
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#Interpolation points
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x = np.linspace(0.0, 1.0, nx)
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return f(x)
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x0, x1, y0, y1, _, dy = getExtent(1.0, 1.0, nx, ny, grid, index)
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x = np.linspace(x0, x1, nx)
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y = np.linspace(y0, y1, ny)
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_, y = np.meshgrid(x, y)
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#print(y+a[0])
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a = genSmoothRandom(nx, n)*dy
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zone = np.where(y > 0.25+a, zone, 1)
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a = genSmoothRandom(nx, n)*dy
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zone = np.where(y < 0.75+a, zone, 1)
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return zone
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width = 2.0
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height = 1.0
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g = 0.0
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gamma = 1.4
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rho = np.empty((ny, nx), dtype=np.float32)
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u = np.empty((ny, nx), dtype=np.float32)
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v = np.zeros((ny, nx), dtype=np.float32)
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p = 2.5*np.ones((ny, nx), dtype=np.float32)
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#Generate the different zones
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zones = genZones(nx, ny, max(1, min(nx, int(nx*roughness))))
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#Zone 0
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zone0 = zones == 0
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rho = np.where(zone0, 1.0, rho)
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u = np.where(zone0, 0.5, u)
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#Zone 1
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zone1 = zones == 1
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rho = np.where(zone1, 2.0, rho)
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u = np.where(zone1, -0.5, u)
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E = 0.5*rho*(u**2+v**2) + p/(gamma-1.0)
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_, _, _, _, dx, dy = getExtent(width, height, nx, ny, grid, index)
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bc = BoundaryCondition({
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'north': BoundaryCondition.Type.Periodic,
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'south': BoundaryCondition.Type.Periodic,
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'east': BoundaryCondition.Type.Periodic,
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'west': BoundaryCondition.Type.Periodic
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})
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#Construct simulator
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arguments = {
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'rho': rho, 'rho_u': rho*u, 'rho_v': rho*v, 'E': E,
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'nx': nx, 'ny': ny,
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'dx': dx, 'dy': dy,
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'g': g,
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'gamma': gamma,
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'boundary_conditions': bc
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}
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return arguments
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def genRayleighTaylor(nx, ny, gamma, version=0, grid=None):
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"""
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Generates Rayleigh-Taylor instability case
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"""
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width = 0.5
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height = 1.5
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g = 0.1
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rho = np.zeros((ny, nx), dtype=np.float32)
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u = np.zeros((ny, nx), dtype=np.float32)
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v = np.zeros((ny, nx), dtype=np.float32)
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p = np.zeros((ny, nx), dtype=np.float32)
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x0, x1, y0, y1, dx, dy = getExtent(width, height, nx, ny, grid)
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x = np.linspace(x0, x1, nx, dtype=np.float32)-width*0.5
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y = np.linspace(y0, y1, ny, dtype=np.float32)-height*0.5
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xv, yv = np.meshgrid(x, y, sparse=False, indexing='xy')
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#This gives a squigly interfact
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if (version == 0):
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y_threshold = 0.01*np.cos(2*np.pi*np.abs(x)/0.5)
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rho = np.where(yv <= y_threshold, 1.0, rho)
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rho = np.where(yv > y_threshold, 2.0, rho)
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elif (version == 1):
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rho = np.where(yv <= 0.0, 1.0, rho)
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rho = np.where(yv > 0.0, 2.0, rho)
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v = 0.01*(1.0 + np.cos(2*np.pi*xv/0.5))/4
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else:
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assert False, "Invalid version"
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p = 2.5 - rho*g*yv
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E = 0.5*rho*(u**2+v**2) + p/(gamma-1.0)
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bc = BoundaryCondition({
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'north': BoundaryCondition.Type.Reflective,
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'south': BoundaryCondition.Type.Reflective,
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'east': BoundaryCondition.Type.Reflective,
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'west': BoundaryCondition.Type.Reflective
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})
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#Construct simulator
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arguments = {
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'rho': rho, 'rho_u': rho*u, 'rho_v': rho*v, 'E': E,
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'nx': nx, 'ny': ny,
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'dx': dx, 'dy': dy,
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'g': g,
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'gamma': gamma,
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'boundary_conditions': bc
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}
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return arguments |