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# -*- coding: utf-8 -*-
#
# Copyright (C) 2015,20016 Thorsten Liebig (Thorsten.Liebig@gmx.de)
#
# 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 os
import numpy as np
import h5py
from openEMS import _nf2ff
from openEMS import utilities
class nf2ff:
"""
Create an nf2ff recording box. The nf2ff can either record in time-domain
or frequency-domain. Further more certain directions and boundary condition
mirroring can be enabled/disabled.
:param name: str -- Name for this recording box.
:param start/stop: (3,) array -- Box start/stop coordinates.
:param directions: (6,) bool array -- Enable/Disables directions.
:param mirror: (6,) int array -- 0 (Off), 1 (PEC) or 2 (PMC) boundary mirroring
:param frequency: array like -- List of frequencies (FD-domain recording)
"""
def __init__(self, CSX, name, start, stop, **kw):
self.CSX = CSX
self.name = name
self.start = start
self.stop = stop
self.freq = None
self.theta = None
self.phi = None
self.center = None
self.directions = [True]*6 # all directions by default
if 'directions' in kw:
self.directions = kw['directions']
del kw['directions']
assert len(self.directions)==6
self.mirror = [0]*6
if 'mirror' in kw:
self.mirror = kw['mirror']
del kw['mirror']
assert len(self.mirror)==6
self.dump_type = 0 # default Et/Ht
self.dump_mode = 1 # default cell interpolated
self.freq = None # broadband recording by defualt
if 'frequency' in kw:
self.freq = kw['frequency']
del kw['frequency']
self.dump_type = 10 # Ef/Hf
if np.isscalar(self.freq):
self.freq = [self.freq]
self.e_file = '{}_E'.format(self.name)
self.h_file = '{}_H'.format(self.name)
self.e_dump = CSX.AddDump(self.e_file, dump_type=self.dump_type , dump_mode=self.dump_mode, file_type=1, **kw)
self.h_dump = CSX.AddDump(self.h_file, dump_type=self.dump_type+1, dump_mode=self.dump_mode, file_type=1, **kw)
if self.freq is not None:
self.e_dump.SetFrequency(self.freq)
self.h_dump.SetFrequency(self.freq)
# print(self.directions)
for ny in range(3):
pos = 2*ny
if self.directions[pos]:
l_start = np.array(start)
l_stop = np.array(stop)
l_stop[ny] = l_start[ny]
self.e_dump.AddBox(l_start, l_stop)
self.h_dump.AddBox(l_start, l_stop)
if self.directions[pos+1]:
l_start = np.array(start)
l_stop = np.array(stop)
l_start[ny] = l_stop[ny]
self.e_dump.AddBox(l_start, l_stop)
self.h_dump.AddBox(l_start, l_stop)
def CalcNF2FF(self, sim_path, freq, theta, phi, radius=1, center=[0,0,0], outfile=None, read_cached=False, verbose=0):
""" CalcNF2FF(sim_path, freq, theta, phi, center=[0,0,0], outfile=None, read_cached=True, verbose=0):
Calculate the far-field after the simulation is done.
:param sim_path: str -- Simulation path
:param freq: array like -- list of frequency for transformation
:param theta/phi: array like -- Theta/Phi angles to calculate the far-field
:param radius: float -- Radius to calculate the far-field (default is 1m)
:param center: (3,) array -- phase center, must be inside the recording box
:param outfile: str -- File to save results in. (defaults to recording name)
:param read_cached: bool -- enable/disable read already existing results (default off)
:param verbose: int -- set verbose level (default 0)
:returns: nf2ff_results class instance
"""
if np.isscalar(freq):
freq = [freq]
self.freq = freq
if np.isscalar(theta):
theta = [theta]
self.theta = theta
if np.isscalar(phi):
phi = [phi]
self.phi = phi
self.center = center
if outfile is None:
fn = os.path.join(sim_path, self.name + '.h5')
else:
fn = os.path.join(sim_path, outfile)
if not read_cached or not os.path.exists(fn):
nfc = _nf2ff._nf2ff(self.freq, np.deg2rad(theta), np.deg2rad(phi), center, verbose=verbose)
for ny in range(3):
nfc.SetMirror(self.mirror[2*ny] , ny, self.start[ny])
nfc.SetMirror(self.mirror[2*ny+1], ny, self.stop[ny])
nfc.SetRadius(radius)
for n in range(6):
fn_e = os.path.join(sim_path, self.e_file + '_{}.h5'.format(n))
fn_h = os.path.join(sim_path, self.h_file + '_{}.h5'.format(n))
if os.path.exists(fn_e) and os.path.exists(fn_h):
assert nfc.AnalyseFile(fn_e, fn_h)
nfc.Write2HDF5(fn)
result = nf2ff_results(fn)
if result.phi is not None:
assert np.abs((result.r-radius)/radius)<1e-6, 'Radius does not match. Did you read an invalid chached result? Try "read_cached=False"'
assert utilities.Check_Array_Equal(np.rad2deg(result.theta), self.theta, 1e-4), 'Theta array does not match. Did you read an invalid chached result? Try "read_cached=False"'
assert utilities.Check_Array_Equal(np.rad2deg(result.phi), self.phi, 1e-4), 'Phi array does not match. Did you read an invalid chached result? Try "read_cached=False"'
assert utilities.Check_Array_Equal(result.freq, self.freq, 1e-6, relative=True), 'Frequency array does not match. Did you read an invalid chached result? Try "read_cached=False"'
return result
class nf2ff_results:
"""
nf2ff result class containing all results obtained by the nf2ff calculation.
Usueally returned from nf2ff.CalcNF2FF
Available attributes:
* `fn` : file name
* `theta`: theta angles
* `phi` : phi angles
* `r` : radius
* `freq` : frequencies
* `Dmax` : directivity over frequency
* `Prad` : total radiated power over frequency
* `E_theta` : theta component of electric field over frequency/theta/phi
* `E_phi` : phi component of electric field over frequency/theta/phi
* `E_norm` : abs component of electric field over frequency/theta/phi
* `E_cprh` : theta component of electric field over frequency/theta/phi
* `E_cplh` : theta component of electric field over frequency/theta/phi
* `P_rad` : radiated power (S) over frequency/theta/phi
"""
def __init__(self, fn):
self.fn = fn
h5_file = h5py.File(fn, 'r')
mesh_grp = h5_file['Mesh']
self.phi = np.array(mesh_grp['phi'])
self.theta = np.array(mesh_grp['theta'])
self.r = np.array(mesh_grp['r'])
data = h5_file['nf2ff']
self.freq = np.array(data.attrs['Frequency'])
self.Dmax = np.array(data.attrs['Dmax'])
self.Prad = np.array(data.attrs['Prad'])
THETA, PHI = np.meshgrid(self.theta, self.phi, indexing='ij')
cos_phi = np.cos(PHI)
sin_phi = np.sin(PHI)
self.E_theta = []
self.E_phi = []
self.P_rad = []
self.E_norm = []
self.E_cprh = []
self.E_cplh = []
for n in range(len(self.freq)):
E_theta = np.array(h5_file['/nf2ff/E_theta/FD/f{}_real'.format(n)]) + 1j*np.array(h5_file['/nf2ff/E_theta/FD/f{}_imag'.format(n)])
E_theta = np.swapaxes(E_theta, 0, 1)
E_phi = np.array(h5_file['/nf2ff/E_phi/FD/f{}_real'.format(n)]) + 1j*np.array(h5_file['/nf2ff/E_phi/FD/f{}_imag'.format(n)])
E_phi = np.swapaxes(E_phi, 0, 1)
self.P_rad .append(np.swapaxes(np.array(h5_file['/nf2ff/P_rad/FD/f{}'.format(n)]), 0, 1))
self.E_theta.append(E_theta)
self.E_phi .append(E_phi)
self.E_norm .append(np.sqrt(np.abs(E_theta)**2 + np.abs(E_phi)**2))
self.E_cprh .append((cos_phi+1j*sin_phi) * (E_theta+1j*E_phi)/np.sqrt(2.0))
self.E_cplh .append((cos_phi-1j*sin_phi) * (E_theta-1j*E_phi)/np.sqrt(2.0))
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