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109 lines
4.0 KiB
Python
109 lines
4.0 KiB
Python
# -*- coding: utf-8 -*-
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"""
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This python module implements the Weighted average flux (WAF) described in
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E. Toro, Shock-Capturing methods for free-surface shallow flows, 2001
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Copyright (C) 2016 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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#Import packages we need
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import numpy as np
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from SWESimulators import Simulator
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"""
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Class that solves the SW equations using the Forward-Backward linear scheme
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"""
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class WAF (Simulator.BaseSimulator):
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"""
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Initialization routine
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h0: Water depth incl ghost cells, (nx+1)*(ny+1) cells
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hu0: Initial momentum along x-axis incl ghost cells, (nx+1)*(ny+1) cells
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hv0: Initial momentum along y-axis incl ghost cells, (nx+1)*(ny+1) cells
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nx: Number of cells along x-axis
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ny: Number of cells along y-axis
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dx: Grid cell spacing along x-axis (20 000 m)
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dy: Grid cell spacing along y-axis (20 000 m)
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dt: Size of each timestep (90 s)
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g: Gravitational accelleration (9.81 m/s^2)
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"""
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def __init__(self, \
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context, \
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h0, hu0, hv0, \
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nx, ny, \
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dx, dy, dt, \
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g, \
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block_width=16, block_height=16):
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# Call super constructor
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super().__init__(context, \
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h0, hu0, hv0, \
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nx, ny, \
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2, 2, \
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dx, dy, dt, \
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g, \
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block_width, block_height);
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#Get kernels
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self.kernel = context.get_prepared_kernel("WAF_kernel.cu", "WAFKernel", \
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"iiffffiPiPiPiPiPiPi", \
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BLOCK_WIDTH=block_width, \
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BLOCK_HEIGHT=block_height)
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def __str__(self):
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return "Weighted average flux"
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def simulate(self, t_end):
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return super().simulateDimsplit(t_end)
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def stepEuler(self, dt):
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return self.stepDimsplitXY(dt)
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def stepDimsplitXY(self, dt):
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self.kernel.prepared_async_call(self.global_size, self.local_size, self.stream, \
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self.nx, self.ny, \
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self.dx, self.dy, dt, \
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self.g, \
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np.int32(0), \
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self.data.h0.data.gpudata, self.data.h0.pitch, \
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self.data.hu0.data.gpudata, self.data.hu0.pitch, \
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self.data.hv0.data.gpudata, self.data.hv0.pitch, \
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self.data.h1.data.gpudata, self.data.h1.pitch, \
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self.data.hu1.data.gpudata, self.data.hu1.pitch, \
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self.data.hv1.data.gpudata, self.data.hv1.pitch)
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self.data.swap()
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self.t += dt
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def stepDimsplitYX(self, dt):
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self.kernel.prepared_async_call(self.global_size, self.local_size, self.stream, \
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self.nx, self.ny, \
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self.dx, self.dy, dt, \
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self.g, \
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np.int32(1), \
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self.data.h0.data.gpudata, self.data.h0.pitch, \
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self.data.hu0.data.gpudata, self.data.hu0.pitch, \
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self.data.hv0.data.gpudata, self.data.hv0.pitch, \
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self.data.h1.data.gpudata, self.data.h1.pitch, \
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self.data.hu1.data.gpudata, self.data.hu1.pitch, \
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self.data.hv1.data.gpudata, self.data.hv1.pitch)
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self.data.swap()
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self.t += dt
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