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187 lines
6.5 KiB
Python
187 lines
6.5 KiB
Python
# -*- coding: utf-8 -*-
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"""
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This python module implements the Forward Backward Linear numerical
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scheme for the shallow water equations, described in
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L. P. Røed, "Documentation of simple ocean models for use in ensemble
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predictions", Met no report 2012/3 and 2012/5 .
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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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import pyopencl as cl #OpenCL in Python
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from SWESimulators import Common
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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 FBL:
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"""
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Initialization routine
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H: Water depth incl ghost cells, (nx+2)*(ny+2) cells
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eta0: Initial deviation from mean sea level incl ghost cells, (nx+2)*(ny+2) cells
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hu0: Initial momentum along x-axis incl ghost cells, (nx+1)*(ny+2) cells
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hv0: Initial momentum along y-axis incl ghost cells, (nx+2)*(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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f: Coriolis parameter (1.2e-4 s^1)
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r: Bottom friction coefficient (2.4e-3 m/s)
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wind_stress: Wind stress parameters
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"""
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def __init__(self, \
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cl_ctx, \
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H, eta0, hu0, hv0, \
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nx, ny, \
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dx, dy, dt, \
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g, f, r, \
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wind_stress=Common.WindStressParams(), \
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block_width=16, block_height=16):
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self.cl_ctx = cl_ctx
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#Create an OpenCL command queue
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self.cl_queue = cl.CommandQueue(self.cl_ctx)
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#Get kernels
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self.u_kernel = Common.get_kernel(self.cl_ctx, "FBL_U_kernel.opencl", block_width, block_height)
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self.v_kernel = Common.get_kernel(self.cl_ctx, "FBL_V_kernel.opencl", block_width, block_height)
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self.eta_kernel = Common.get_kernel(self.cl_ctx, "FBL_eta_kernel.opencl", block_width, block_height)
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#Create data by uploading to device
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ghost_cells_x = 0
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ghost_cells_y = 0
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self.H = Common.OpenCLArray2D(self.cl_ctx, nx, ny, ghost_cells_x, ghost_cells_y, H)
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self.cl_data = Common.SWEDataArkawaC(self.cl_ctx, nx, ny, ghost_cells_x, ghost_cells_y, eta0, hu0, hv0)
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#Save input parameters
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#Notice that we need to specify them in the correct dataformat for the
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#OpenCL kernel
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self.nx = np.int32(nx)
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self.ny = np.int32(ny)
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self.dx = np.float32(dx)
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self.dy = np.float32(dy)
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self.dt = np.float32(dt)
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self.g = np.float32(g)
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self.f = np.float32(f)
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self.r = np.float32(r)
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self.wind_stress = wind_stress
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#Initialize time
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self.t = np.float32(0.0)
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#Compute kernel launch parameters
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self.local_size = (8, 8) # WARNING::: MUST MATCH defines of block_width/height in kernels!
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self.global_size = ( \
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int(np.ceil(self.nx / float(self.local_size[0])) * self.local_size[0]), \
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int(np.ceil(self.ny / float(self.local_size[1])) * self.local_size[1]) \
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)
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def __str__(self):
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return "Forward Backward Linear"
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"""
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Function which steps n timesteps
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"""
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def step(self, t_end=0.0):
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n = int(t_end / self.dt + 1)
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for i in range(0, n):
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local_dt = np.float32(min(self.dt, t_end-i*self.dt))
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if (local_dt <= 0.0):
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break
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self.u_kernel.computeUKernel(self.cl_queue, self.global_size, self.local_size, \
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self.nx, self.ny, \
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self.dx, self.dy, local_dt, \
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self.g, self.f, self.r, \
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self.H.data, self.H.pitch, \
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self.cl_data.hu0.data, self.cl_data.hu0.pitch, \
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self.cl_data.hv0.data, self.cl_data.hv0.pitch, \
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self.cl_data.h0.data, self.cl_data.h0.pitch, \
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self.wind_stress.type, \
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self.wind_stress.tau0, self.wind_stress.rho, self.wind_stress.alpha, self.wind_stress.xm, self.wind_stress.Rc, \
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self.wind_stress.x0, self.wind_stress.y0, \
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self.wind_stress.u0, self.wind_stress.v0, \
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self.t)
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self.v_kernel.computeVKernel(self.cl_queue, self.global_size, self.local_size, \
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self.nx, self.ny, \
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self.dx, self.dy, local_dt, \
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self.g, self.f, self.r, \
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self.H.data, self.H.pitch, \
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self.cl_data.hu0.data, self.cl_data.hu0.pitch, \
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self.cl_data.hv0.data, self.cl_data.hv0.pitch, \
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self.cl_data.h0.data, self.cl_data.h0.pitch, \
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self.wind_stress.type, \
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self.wind_stress.tau0, self.wind_stress.rho, self.wind_stress.alpha, self.wind_stress.xm, self.wind_stress.Rc, \
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self.wind_stress.x0, self.wind_stress.y0, \
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self.wind_stress.u0, self.wind_stress.v0, \
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self.t)
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self.eta_kernel.computeEtaKernel(self.cl_queue, self.global_size, self.local_size, \
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self.nx, self.ny, \
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self.dx, self.dy, local_dt, \
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self.g, self.f, self.r, \
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self.H.data, self.H.pitch, \
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self.cl_data.hu0.data, self.cl_data.hu0.pitch, \
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self.cl_data.hv0.data, self.cl_data.hv0.pitch, \
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self.cl_data.h0.data, self.cl_data.h0.pitch)
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self.t += local_dt
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return self.t
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def download(self):
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return self.cl_data.download(self.cl_queue)
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