# -*- coding: utf-8 -*- """ This python module implements the Weighted average flux (WAF) described in E. Toro, Shock-Capturing methods for free-surface shallow flows, 2001 Copyright (C) 2016 SINTEF ICT This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . """ #Import packages we need import numpy as np from GPUSimulators import Simulator, Common """ Class that solves the SW equations using the Forward-Backward linear scheme """ class WAF (Simulator.BaseSimulator): """ Initialization routine h0: Water depth incl ghost cells, (nx+1)*(ny+1) cells hu0: Initial momentum along x-axis incl ghost cells, (nx+1)*(ny+1) cells hv0: Initial momentum along y-axis incl ghost cells, (nx+1)*(ny+1) cells nx: Number of cells along x-axis ny: Number of cells along y-axis dx: Grid cell spacing along x-axis (20 000 m) dy: Grid cell spacing along y-axis (20 000 m) dt: Size of each timestep (90 s) g: Gravitational accelleration (9.81 m/s^2) """ def __init__(self, \ context, \ h0, hu0, hv0, \ nx, ny, \ dx, dy, dt, \ g, \ block_width=16, block_height=16): # Call super constructor super().__init__(context, \ nx, ny, \ dx, dy, dt, \ g, \ block_width, block_height); #Get kernels self.kernel = context.get_prepared_kernel("WAF_kernel.cu", "WAFKernel", \ "iiffffiPiPiPiPiPiPi", \ BLOCK_WIDTH=self.local_size[0], \ BLOCK_HEIGHT=self.local_size[1]) #Create data by uploading to device self.u0 = Common.ArakawaA2D(self.stream, \ nx, ny, \ 2, 2, \ [h0, hu0, hv0]) self.u1 = Common.ArakawaA2D(self.stream, \ nx, ny, \ 2, 2, \ [None, None, None]) def __str__(self): return "Weighted average flux" def simulate(self, t_end): return super().simulateDimsplit(t_end) def stepEuler(self, dt): return self.stepDimsplitXY(dt) def stepDimsplitXY(self, dt): self.kernel.prepared_async_call(self.global_size, self.local_size, self.stream, \ self.nx, self.ny, \ self.dx, self.dy, dt, \ self.g, \ np.int32(0), \ self.u0[0].data.gpudata, self.u0[0].data.strides[0], \ self.u0[1].data.gpudata, self.u0[1].data.strides[0], \ self.u0[2].data.gpudata, self.u0[2].data.strides[0], \ self.u1[0].data.gpudata, self.u1[0].data.strides[0], \ self.u1[1].data.gpudata, self.u1[1].data.strides[0], \ self.u1[2].data.gpudata, self.u1[2].data.strides[0]) self.u0, self.u1 = self.u1, self.u0 self.t += dt def stepDimsplitYX(self, dt): self.kernel.prepared_async_call(self.global_size, self.local_size, self.stream, \ self.nx, self.ny, \ self.dx, self.dy, dt, \ self.g, \ np.int32(1), \ self.u0[0].data.gpudata, self.u0[0].data.strides[0], \ self.u0[1].data.gpudata, self.u0[1].data.strides[0], \ self.u0[2].data.gpudata, self.u0[2].data.strides[0], \ self.u1[0].data.gpudata, self.u1[0].data.strides[0], \ self.u1[1].data.gpudata, self.u1[1].data.strides[0], \ self.u1[2].data.gpudata, self.u1[2].data.strides[0]) self.u0, self.u1 = self.u1, self.u0 self.t += dt def download(self): return self.u0.download(self.stream)