André R. Brodtkorb 4da6fd043d Added superclass
2018-08-09 15:14:50 +02:00

115 lines
3.8 KiB
Python

# -*- coding: utf-8 -*-
"""
This python module implements the Kurganov-Petrova numerical scheme
for the shallow water equations, described in
A. Kurganov & Guergana Petrova
A Second-Order Well-Balanced Positivity Preserving Central-Upwind
Scheme for the Saint-Venant System Communications in Mathematical
Sciences, 5 (2007), 133-160.
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 <http://www.gnu.org/licenses/>.
"""
#Import packages we need
import numpy as np
from SWESimulators import Simulator
"""
Class that solves the SW equations using the Forward-Backward linear scheme
"""
class KP07 (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)
r: Bottom friction coefficient (2.4e-3 m/s)
"""
def __init__(self, \
context, \
h0, hu0, hv0, \
nx, ny, \
dx, dy, dt, \
g, \
theta=1.3, r=0.0, \
block_width=16, block_height=16):
# Call super constructor
super().__init__(context, \
h0, hu0, hv0, \
nx, ny, \
2, 2, \
dx, dy, dt, \
g, \
block_width, block_height);
self.theta = np.float32(theta)
self.r = np.float32(r)
#Get kernels
self.module = context.get_kernel("KP07_kernel.cu", block_width, block_height)
self.kernel = self.module.get_function("KP07Kernel")
self.kernel.prepare("iiffffffiPiPiPiPiPiPi")
def __str__(self):
return "Kurganov-Petrova 2007"
def simulate(self, t_end):
return super().simulateRK(t_end, 2)
def substepRK(self, dt, substep):
self.kernel.prepared_async_call(self.global_size, self.local_size, self.stream, \
self.nx, self.ny, \
self.dx, self.dy, dt, \
self.g, \
self.theta, \
self.r, \
np.int32(substep), \
self.data.h0.data.gpudata, self.data.h0.pitch, \
self.data.hu0.data.gpudata, self.data.hu0.pitch, \
self.data.hv0.data.gpudata, self.data.hv0.pitch, \
self.data.h1.data.gpudata, self.data.h1.pitch, \
self.data.hu1.data.gpudata, self.data.hu1.pitch, \
self.data.hv1.data.gpudata, self.data.hv1.pitch)
self.data.swap()
def stepEuler(self, dt):
self.substepRK(dt, 0)
self.t += dt
def stepRK(self, dt, order):
if (order != 2):
raise NotImplementedError("Only second order implemented")
self.substepRK(dt, 0)
self.substepRK(dt, 1)
self.t += dt
def download(self):
return self.data.download(self.stream)