Finite rect lat constant driving far field "ccd"
Former-commit-id: 69fc0ebe1eba8701743d6883f877e5df70f4477d
This commit is contained in:
Marek Nečada
parent
5f729d28a7
commit
ac6e94065a
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@ -11,6 +11,10 @@ ap.add_argument("-o", "--output", type=str, required=False, help='output path (i
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ap.add_argument("-O", "--plot-out", type=str, required=False, help="path to plot output (optional)")
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ap.add_argument("-P", "--plot", action='store_true', help="if -p not given, plot to a default path")
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ap.add_argument("-g", "--save-gradually", action='store_true', help="saves the partial result after computing each irrep")
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ap.add_argument("-S", "--symmetry-adapted", default=None, help="Use a symmetry-adapted basis of a given point group instead of individual spherical harmonics")
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ap.add_argument("-d", "--ccd-distance", type=float, default=math.nan, help='Far-field "CCD" distance from the sample')
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ap.add_argument("-D", "--ccd-size", type=float, default=math.nan, help='Far-field "CCD" width and heighth')
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ap.add_argument("-R", "--ccd-resolution", type=int, default=101, help='Far-field "CCD" resolution')
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#ap.add_argument("--irrep", type=str, default="none", help="Irrep subspace (irrep index from 0 to 7, irrep label, or 'none' for no irrep decomposition")
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@ -41,6 +45,20 @@ from qpms import FinitePointGroup, ScatteringSystem, BesselType, eV, hbar
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from qpms.symmetries import point_group_info
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eh = eV/hbar
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def cleanarray(a, atol=1e-10, copy=True):
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a = np.array(a, copy=copy)
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sieve = abs(a.real) < atol
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a[sieve] = 1j * a[sieve].imag
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sieve = abs(a.imag) < atol
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a[sieve] = a[sieve].real
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return a
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def nicerot(a, atol=1e-10, copy=True): #gives array a "nice" phase
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a = np.array(a, copy=copy)
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i = np.argmax(abs(a))
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a = a / a[i] * abs(a[i])
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return a
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dbgmsg_enable(DebugFlags.INTEGRATION)
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#Particle positions
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@ -67,13 +85,30 @@ outfile_tmp = defaultprefix + ".tmp" if a.output is None else a.output + ".tmp"
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nelem = len(bspec)
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phases = np.exp(1j*np.dot(ss.positions[:,:2], np.array(a.wavevector)))
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driving_full = np.zeros((nelem, ss.fecv_size),dtype=complex)
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for y in range(nelem):
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if a.symmetry_adapted is not None:
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ss1, ssw1 = ScatteringSystem.create(particles=[Particle((0,0,0), ap.tmgen, bspec)], medium=medium, omega=omega,
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sym=FinitePointGroup(point_group_info[a.symmetry_adapted]))
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fvcs1 = np.empty((nelem, nelem), dtype=complex)
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y = 0
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iris1 = []
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for iri1 in range(ss1.nirreps):
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for j in range(ss1.saecv_sizes[iri1]):
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pvc1 = np.zeros((ss1.saecv_sizes[iri1],), dtype=complex)
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fvcs1[y] = ss1.unpack_vector(pvc1, iri1)
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fvcs1[y] = cleanarray(nicerot(fvcs1[y], copy=False), copy=False)
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driving_full[y] = (phases[:, None] * fvcs1[y][None,:]).flatten()
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y += 1
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iris1.append(iri1)
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iris1 = np.array(iris1)
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else:
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for y in range(nelem):
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driving_full[y,y::nelem] = phases
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scattered_full = np.zeros((nelem, ss.fecv_size),dtype=complex)
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scattered_ir = [None for iri in range(ss.nirreps)]
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ir_contained = np.ones((nelem, ss.nirreps), dtype=bool)
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for iri in range(ss.nirreps):
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logging.info("processing irrep %d/%d" % (iri, ss.nirreps))
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@ -84,14 +119,17 @@ for iri in range(ss.nirreps):
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#translation_matrix = ss.translation_matrix_packed(wavenumber, iri, BesselType.REGULAR) + np.eye(ss.saecv_sizes[iri])
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#logging.info("auxillary translation matrix created")
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scattered_ir[iri] = np.empty((nelem, ss.saecv_sizes[iri]), dtype=complex)
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scattered_ir_unpacked = np.empty((nelem, ss.fecv_size), dtype=complex)
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scattered_ir[iri] = np.zeros((nelem, ss.saecv_sizes[iri]), dtype=complex)
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scattered_ir_unpacked = np.zeros((nelem, ss.fecv_size), dtype=complex)
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for y in range(nelem):
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ã = driving_full[y]
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ãi = cleanarray(ss.pack_vector(ã, iri), copy=False)
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if np.all(ãi == 0):
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ir_contained[y, iri] = False
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continue
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Tã = ssw.apply_Tmatrices_full(ã)
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Tãi = ss.pack_vector(Tã, iri)
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ãi = ss.pack_vector(ã, iri)
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fi = LU(Tãi)
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scattered_ir[iri][y] = fi
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scattered_ir_unpacked[y] = ss.unpack_vector(fi, iri)
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@ -106,6 +144,21 @@ for iri in range(ss.nirreps):
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)
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logging.info("partial results saved to %s"%iriout)
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t, l, m = bspec.tlm()
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if not math.isnan(a.ccd_distance):
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logging.info("Computing the far fields")
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ccd_size = (20 * a.ccd_distance / (max(Nx*px, Ny*py) * ssw.wavenumber.real)) if math.isnan(a.ccd_size) else a.ccd_size
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ccd_x = np.linspace(-ccd_size/2, ccd_size/2, a.ccd_resolution)
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ccd_y = np.linspace(-ccd_size/2, ccd_size/2, a.ccd_resolution)
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ccd_grid = np.meshgrid(ccd_x, ccd_y, (a.ccd_distance,), indexing='ij')
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ccd_points = np.stack(ccd_grid, axis=-1).squeeze(axis=-2)
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print(ccd_points.shape)
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ccd_fields = np.empty((nelem,) + ccd_points.shape, dtype=complex)
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for y in range(nelem):
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ccd_fields[y] = ssw.scattered_E(scattered_full[y], ccd_points, btyp=BesselType.HANKEL_PLUS)
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print(ccd_fields.shape)
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logging.info("Far fields done")
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outfile = defaultprefix + ".npz" if a.output is None else a.output
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np.savez(outfile, meta=vars(a),
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@ -113,6 +166,14 @@ np.savez(outfile, meta=vars(a),
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positions = ss.positions[:,:2],
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scattered_ir_packed = scattered_ir,
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scattered_full = scattered_full,
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ir_contained = ir_contained,
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t=t, l=l, m=m,
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iris1 = iris1 if (a.symmetry_adapted is not None) else None,
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irnames1 = ss1.irrep_names if (a.symmetry_adapted is not None) else None,
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fvcs1 = fvcs1 if (a.symmetry_adapted is not None) else None,
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#ccd_size = ccd_size if not math.isnan(a.ccd_distance) else None,
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ccd_points = ccd_points if not math.isnan(a.ccd_distance) else None,
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ccd_fields = ccd_fields if not math.isnan(a.ccd_distance) else None,
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)
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logging.info("Saved to %s" % outfile)
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@ -141,17 +202,30 @@ if a.plot or (a.plot_out is not None):
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from matplotlib import pyplot as plt, cm
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t, l, m = bspec.tlm()
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phasecm = cm.twilight
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pmcm = cm.bwr
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abscm = cm.plasma
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fig, axes = plt.subplots(nelem, 12, figsize=(figscale*12, figscale*nelem))
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for yp in range(0,3):
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fig, axes = plt.subplots(nelem, 12 if math.isnan(a.ccd_distance) else 15, figsize=(figscale*(12 if math.isnan(a.ccd_distance) else 15), figscale*nelem))
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for yp in range(0,3): # TODO xy-dipoles instead?
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axes[0,4*yp+0].set_title("abs / %s,%d,%+d"%('E' if t[yp]==2 else 'M', l[yp], m[yp],))
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axes[0,4*yp+1].set_title("arg / %s,%d,%+d"%('E' if t[yp]==2 else 'M', l[yp], m[yp],))
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axes[0,4*yp+2].set_title("Fabs / %s,%d,%+d"%('E' if t[yp]==2 else 'M', l[yp], m[yp],))
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axes[0,4*yp+3].set_title("Farg / %s,%d,%+d"%('E' if t[yp]==2 else 'M', l[yp], m[yp],))
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if not math.isnan(a.ccd_distance):
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axes[0,12].set_title("$E_{xy}$ @ $z = %g; \phi$" % a.ccd_distance)
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axes[0,13].set_title("$E_{xy}$ @ $z = %g; \phi + \pi/2$" % a.ccd_distance)
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axes[0,14].set_title("$E_{z}$ @ $z = %g$" % a.ccd_distance)
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for y in range(nelem):
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axes[y,0].set_ylabel("%s,%d,%+d"%('E' if t[y]==2 else 'M', l[y], m[y],))
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fulvec = scattered_full[y]
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if a.symmetry_adapted is not None:
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driving_nonzero_y = [j for j in range(nelem) if abs(fvcs1[y,j]) > 1e-5]
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driving_descr = ss1.irrep_names[iris1[y]].join((str(fvcs[y,j]) +
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"(%s, %d, %+d) " % (("E" if t[j] == 2 else "M"), l[j], m[j]) for j in
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driving_nonzero_y)) # TODO shorten the complex number precision
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else:
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driving_descr = "%s,%d,%+d"%('E' if t[y]==2 else 'M', l[y], m[y],)
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axes[y,0].set_ylabel(driving_descr)
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vecgrid = fullvec2grid(fulvec)
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vecgrid_ff = np.fft.fftshift(np.fft.fft2(vecgrid, axes=(0,1)),axes=(0,1))
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lemax = np.amax(abs(vecgrid))
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@ -165,7 +239,21 @@ if a.plot or (a.plot_out is not None):
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else:
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for c in range(0,4):
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axes[y,yp*4+c].tick_params(bottom=False, left=False, labelbottom=False, labelleft=False)
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if not math.isnan(a.ccd_distance):
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fxye=(-ccd_size/2, ccd_size/2, -ccd_size/2, ccd_size/2)
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e2vmax = np.amax(np.linalg.norm(ccd_fields[y], axis=-1)**2)
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print(np.sum(abs(ccd_fields[y,...,:2].real)**2).shape)
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axes[y, 12].imshow(np.sum(abs(ccd_fields[y,...,:2].real)**2, axis=-1),
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origin="lower",vmax=e2vmax, extent=fxye, cmap=abscm)
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axes[y, 12].streamplot(ccd_points[...,1], ccd_points[...,0],
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ccd_fields[y,...,1].real, ccd_fields[y,...,0].real)
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axes[y, 13].imshow(np.sum(abs(ccd_fields[y,...,:2].imag)**2, axis=-1) ,
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origin="lower",vmax=e2vmax, extent=fxye, cmap=abscm)
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axes[y, 13].streamplot(ccd_points[...,1], ccd_points[...,0],
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ccd_fields[y,...,1].imag, ccd_fields[y,...,0].imag)
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zplot = abs(ccd_fields[y,...,2])**2
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axes[y, 14].imshow(zplot, origin='lower', extent=fxye, cmap=abscm)
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axes[y, 14].text(0.5, 0.5, '%g' % np.amax(zplot)/e2vmax, horizontalalignment='center', verticalalignment='center', transform=axes[y,14].transAxes)
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plotfile = defaultprefix + ".pdf" if a.plot_out is None else a.plot_out
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fig.savefig(plotfile)
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