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https://gitee.com/sunhf/gprMax.git
已同步 2025-08-08 07:24:19 +08:00
106 行
3.6 KiB
Python
106 行
3.6 KiB
Python
# Copyright (C) 2015-2023: The University of Edinburgh, United Kingdom
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# Authors: Craig Warren, Antonis Giannopoulos, and John Hartley
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#
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# This file is part of gprMax.
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#
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# gprMax 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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#
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# gprMax 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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#
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# You should have received a copy of the GNU General Public License
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# along with gprMax. If not, see <http://www.gnu.org/licenses/>.
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import numpy as np
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import gprMax.config as config
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class Rx:
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"""Receiver output points."""
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allowableoutputs = ["Ex", "Ey", "Ez", "Hx", "Hy", "Hz", "Ix", "Iy", "Iz"]
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defaultoutputs = allowableoutputs[:-3]
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allowableoutputs_dev = allowableoutputs[:-3]
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def __init__(self):
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self.ID = None
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self.outputs = {}
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self.xcoord = None
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self.ycoord = None
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self.zcoord = None
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self.xcoordorigin = None
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self.ycoordorigin = None
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self.zcoordorigin = None
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def htod_rx_arrays(G, queue=None):
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"""Initialise arrays on compute device for receiver coordinates and to store field
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components for receivers.
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Args:
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G: FDTDGrid class describing a grid in a model.
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queue: pyopencl queue.
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Returns:
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rxcoords_dev: int array of receiver coordinates on compute device.
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rxs_dev: float array of receiver data on compute device - rows are field
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components; columns are iterations; pages are receivers.
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"""
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# Array to store receiver coordinates on compute device
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rxcoords = np.zeros((len(G.rxs), 3), dtype=np.int32)
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for i, rx in enumerate(G.rxs):
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rxcoords[i, 0] = rx.xcoord
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rxcoords[i, 1] = rx.ycoord
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rxcoords[i, 2] = rx.zcoord
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# Array to store field components for receivers on compute device -
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# rows are field components; columns are iterations; pages are receivers
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rxs = np.zeros(
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(len(Rx.allowableoutputs_dev), G.iterations, len(G.rxs)), dtype=config.sim_config.dtypes["float_or_double"]
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)
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# Copy arrays to compute device
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if config.sim_config.general["solver"] == "cuda":
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import pycuda.gpuarray as gpuarray
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rxcoords_dev = gpuarray.to_gpu(rxcoords)
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rxs_dev = gpuarray.to_gpu(rxs)
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elif config.sim_config.general["solver"] == "opencl":
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import pyopencl.array as clarray
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rxcoords_dev = clarray.to_device(queue, rxcoords)
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rxs_dev = clarray.to_device(queue, rxs)
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return rxcoords_dev, rxs_dev
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def dtoh_rx_array(rxs_dev, rxcoords_dev, G):
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"""Copy output from receivers array used on compute device back to receiver
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objects.
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Args:
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rxcoords_dev: int array of receiver coordinates on compute device.
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rxs_dev: float array of receiver data on compute device - rows are field
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components; columns are iterations; pages are receivers.
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G: FDTDGrid class describing a grid in a model.
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"""
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for rx in G.rxs:
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for rxd in range(len(G.rxs)):
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if (
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rx.xcoord == rxcoords_dev[rxd, 0]
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and rx.ycoord == rxcoords_dev[rxd, 1]
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and rx.zcoord == rxcoords_dev[rxd, 2]
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):
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for output in rx.outputs.keys():
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rx.outputs[output] = rxs_dev[Rx.allowableoutputs_dev.index(output), :, rxd]
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