commit 66d05ca8306d32edf8a0051fe00ecefe5bfbea68 Author: jan Date: Wed Mar 30 15:00:00 2016 -0700 Initial commit diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..9376de2 --- /dev/null +++ b/.gitignore @@ -0,0 +1,3 @@ +.idea/ +.pyc + diff --git a/README.md b/README.md new file mode 100644 index 0000000..15daefa --- /dev/null +++ b/README.md @@ -0,0 +1,34 @@ +# opencl-fdtd + +**opencl-fdtd** is a python package for running 3D time-domain electromagnetic +simulations on parallel compute hardware (mainly GPUs). + +**Performance** highly depends on what hardware you have available: +* A 395x345x73 cell simulation (~10 million points, 8-cell absorbing boundaries) + runs at around 42 iterations/sec. on my Nvidia GTX 580. +* On my laptop (Nvidia 940M) the same simulation achieves ~8 iterations/sec. +* An L3 photonic crystal cavity ringdown simulation (1550nm source, 40nm + discretization, 8000 steps) takes about 5 minutes on my laptop. + +**Capabilities** are currently pretty minimal: +* Absorbing boundaries (CPML) +* Conducting boundaries (PMC) +* Anisotropic media (eps_xx, eps_yy, eps_zz) +* Direct access to fields (eg., you can trivially add a soft or hard + current source with just sim.E[1] += sin(f0 * t), or save any portion + of a field to a file) + +## Installation + +**Requirements:** +* python 3 (written and tested with 3.5) +* numpy +* pyopencl +* h5py (for file output) +* [gridlock](https://mpxd.net/gogs/jan/gridlock) +* [masque](https://mpxd.net/gogs/jan/masque) + +You can install the requirements and their dependencies easily with +```bash +pip intall -r requirements.txt +``` \ No newline at end of file diff --git a/fdtd.py b/fdtd.py new file mode 100644 index 0000000..6c52c56 --- /dev/null +++ b/fdtd.py @@ -0,0 +1,164 @@ +""" +Example code for running an OpenCL FDTD simulation + +See main() for simulation setup. +""" + +import sys +import time + +import numpy +import h5py + +from fdtd.simulation import Simulation +from masque import Pattern, shapes +import gridlock +import pcgen + + +def perturbed_l3(a: float, radius: float, **kwargs) -> Pattern: + """ + Generate a masque.Pattern object containing a perturbed L3 cavity. + + :param a: Lattice constant. + :param radius: Hole radius, in units of a (lattice constant). + :param kwargs: Keyword arguments: + hole_dose, trench_dose, hole_layer, trench_layer: Shape properties for Pattern. + Defaults *_dose=1, hole_layer=0, trench_layer=1. + shifts_a, shifts_r: passed to pcgen.l3_shift; specifies lattice constant (1 - + multiplicative factor) and radius (multiplicative factor) for shifting + holes adjacent to the defect (same row). Defaults are 0.15 shift for + first hole, 0.075 shift for third hole, and no radius change. + xy_size: [x, y] number of mirror periods in each direction; total size is + 2 * n + 1 holes in each direction. Default [10, 10]. + perturbed_radius: radius of holes perturbed to form an upwards-driected beam + (multiplicative factor). Default 1.1. + trench width: Width of the undercut trenches. Default 1.2e3. + :return: masque.Pattern object containing the L3 design + """ + + default_args = {'hole_dose': 1, + 'trench_dose': 1, + 'hole_layer': 0, + 'trench_layer': 1, + 'shifts_a': (0.15, 0, 0.075), + 'shifts_r': (1.0, 1.0, 1.0), + 'xy_size': (10, 10), + 'perturbed_radius': 1.1, + 'trench_width': 1.2e3, + } + kwargs = {**default_args, **kwargs} + + xyr = pcgen.l3_shift_perturbed_defect(mirror_dims=kwargs['xy_size'], + perturbed_radius=kwargs['perturbed_radius'], + shifts_a=kwargs['shifts_a'], + shifts_r=kwargs['shifts_r']) + xyr *= a + xyr[:, 2] *= radius + + pat = Pattern() + pat.name = 'L3p-a{:g}r{:g}rp{:g}'.format(a, radius, kwargs['perturbed_radius']) + pat.shapes += [shapes.Circle(radius=r, offset=(x, y), + dose=kwargs['hole_dose'], + layer=kwargs['hole_layer']) + for x, y, r in xyr] + + maxes = numpy.max(numpy.fabs(xyr), axis=0) + pat.shapes += [shapes.Polygon.rectangle( + lx=(2 * maxes[0]), ly=kwargs['trench_width'], + offset=(0, s * (maxes[1] + a + kwargs['trench_width'] / 2)), + dose=kwargs['trench_dose'], layer=kwargs['trench_layer']) + for s in (-1, 1)] + return pat + + +def main(): + max_t = 8000 # number of timesteps + + dx = 40 # discretization (nm/cell) + pml_thickness = 8 # (number of cells) + + wl = 1550 # Excitation wavelength and fwhm + dwl = 200 + + # Device design parameters + xy_size = numpy.array([10, 10]) + a = 430 + r = 0.285 + th = 170 + + # refractive indices + n_slab = 3.408 # InGaAsP(80, 50) @ 1550nm + n_air = 1.0 # air + + # Half-dimensions of the simulation grid + xy_max = (xy_size + 1) * a * [1, numpy.sqrt(3)/2] + z_max = 1.6 * a + xyz_max = numpy.hstack((xy_max, z_max)) + pml_thickness * dx + + # Coordinates of the edges of the cells. The fdtd package can only do square grids at the moment. + half_edge_coords = [numpy.arange(dx/2, m + dx, step=dx) for m in xyz_max] + edge_coords = [numpy.hstack((-h[::-1], h)) for h in half_edge_coords] + + # #### Create the grid, mask, and draw the device #### + grid = gridlock.Grid(edge_coords, initial=n_air**2, num_grids=3) + grid.draw_slab(surface_normal=gridlock.Direction.z, + center=[0, 0, 0], + thickness=th, + eps=n_slab**2) + mask = perturbed_l3(a, r) + grid.draw_polygons(surface_normal=gridlock.Direction.z, + center=[0, 0, 0], + thickness=2 * th, + eps=n_air**2, + polygons=mask.as_polygons()) + + print(grid.shape) + # #### Create the simulation grid #### + sim = Simulation(grid.grids) + + # Conducting boundaries and pmls in every direction + c_args = [] + pml_args = [] + for d in (0, 1, 2): + for p in (-1, 1): + c_args += [{'direction': d, 'polarity': p}] + pml_args += [{'direction': d, 'polarity': p, 'epsilon_eff': n_slab**2}] + sim.init_conductors(c_args) + sim.init_cpml(pml_args) + + # Source parameters and function + w = 2 * numpy.pi * dx / wl + fwhm = dwl * w * w / (2 * numpy.pi * dx) + alpha = (fwhm ** 2) / 8 * numpy.log(2) + delay = 7/numpy.sqrt(2 * alpha) + field_source = lambda t: numpy.sin(w * (t * sim.dt - delay)) * \ + numpy.exp(-alpha * (t * sim.dt - delay)**2) + + # #### Run a bunch of iterations #### + # event = sim.whatever([prev_event]) indicates that sim.whatever should be queued immediately and run + # once prev_event is finished. + output_file = h5py.File('simulation_output.h5', 'w') + start = time.perf_counter() + for t in range(max_t): + event = sim.cpml_E([]) + sim.update_E([event]).wait() + + sim.E[1][tuple(grid.shape//2)] += field_source(t) + event = sim.conductor_E([]) + event = sim.cpml_H([event]) + event = sim.update_H([event]) + sim.conductor_H([event]).wait() + + print('iteration {}: average {} iterations per sec'.format(t, (t+1)/(time.perf_counter()-start))) + sys.stdout.flush() + + # Save field slices + if (t % 20 == 0 and (max_t - t < 1000 or t < 1000)) or t == max_t-1: + print('saving E-field') + for j, f in enumerate(sim.E): + a = f.get() + output_file['/E{}_t{}'.format('xyz'[j], t)] = a[:, :, round(a.shape[2]/2)] + +if __name__ == '__main__': + main() diff --git a/fdtd/__init__.py b/fdtd/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/fdtd/__pycache__/__init__.cpython-35.pyc b/fdtd/__pycache__/__init__.cpython-35.pyc new file mode 100644 index 0000000..c752ba6 Binary files /dev/null and b/fdtd/__pycache__/__init__.cpython-35.pyc differ diff --git a/fdtd/__pycache__/base.cpython-35.pyc b/fdtd/__pycache__/base.cpython-35.pyc new file mode 100644 index 0000000..9205bc6 Binary files /dev/null and b/fdtd/__pycache__/base.cpython-35.pyc differ diff --git a/fdtd/__pycache__/boundary.cpython-35.pyc b/fdtd/__pycache__/boundary.cpython-35.pyc new file mode 100644 index 0000000..e3e8912 Binary files /dev/null and b/fdtd/__pycache__/boundary.cpython-35.pyc differ diff --git a/fdtd/__pycache__/simulation.cpython-35.pyc b/fdtd/__pycache__/simulation.cpython-35.pyc new file mode 100644 index 0000000..cf43628 Binary files /dev/null and b/fdtd/__pycache__/simulation.cpython-35.pyc differ diff --git a/fdtd/base.py b/fdtd/base.py new file mode 100644 index 0000000..e05f416 --- /dev/null +++ b/fdtd/base.py @@ -0,0 +1,75 @@ +""" +Basic code snippets for opencl FDTD +""" + +from typing import List +import numpy + + +def shape_source(shape: List[int] or numpy.ndarray) -> str: + """ + Defines sx, sy, sz C constants specifying the shape of the grid in each of the 3 dimensions. + + :param shape: [sx, sy, sz] values. + :return: String containing C source. + """ + sxyz = """ +// Field sizes +const int sx = {shape[0]}; +const int sy = {shape[1]}; +const int sz = {shape[2]}; +""".format(shape=shape) + return sxyz + +# Defines dix, diy, diz constants used for stepping in the x, y, z directions in a linear array +# (ie, given Ex[i] referring to position (x, y, z), Ex[i+diy] will refer to position (x, y+1, z)) +dixyz_source = """ +// Convert offset in field xyz to linear index offset +const int dix = sz * sy; +const int diy = sz; +const int diz = 1; +""" + +# Given a linear index i and shape sx, sy, sz, defines x, y, and z as the 3D indices of the current element (i). +xyz_source = """ +// Convert linear index to field index (xyz) +const int x = i / (sz * sy); +const int y = (i - x * sz * sy) / sz; +const int z = (i - y * sz - x * sz * sy); +""" + +# Source code for updating the E field; maxes use of dixyz_source. +maxwell_E_source = """ +// E update equations +Ex[i] += dt / epsx[i] * ((Hz[i] - Hz[i-diy]) - (Hy[i] - Hy[i-diz])); +Ey[i] += dt / epsy[i] * ((Hx[i] - Hx[i-diz]) - (Hz[i] - Hz[i-dix])); +Ez[i] += dt / epsz[i] * ((Hy[i] - Hy[i-dix]) - (Hx[i] - Hx[i-diy])); +""" + +# Source code for updating the H field; maxes use of dixyz_source and assumes mu=0 +maxwell_H_source = """ +// H update equations +Hx[i] -= dt * ((Ez[i+diy] - Ez[i]) - (Ey[i+diz] - Ey[i])); +Hy[i] -= dt * ((Ex[i+diz] - Ex[i]) - (Ez[i+dix] - Ez[i])); +Hz[i] -= dt * ((Ey[i+dix] - Ey[i]) - (Ex[i+diy] - Ex[i])); +""" + + +def type_to_C(float_type: numpy.float32 or numpy.float64) -> str: + """ + Returns a string corresponding to the C equivalent of a numpy type. + Only works for float32 and float64. + + :param float_type: numpy.float32 or numpy.float64 + :return: string containing the corresponding C type (eg. 'double') + """ + if float_type == numpy.float32: + arg_type = 'float' + elif float_type == numpy.float64: + arg_type = 'double' + else: + raise Exception('Unsupported type') + return arg_type + + + diff --git a/fdtd/boundary.py b/fdtd/boundary.py new file mode 100644 index 0000000..0f01a37 --- /dev/null +++ b/fdtd/boundary.py @@ -0,0 +1,185 @@ +from typing import List, Dict +import numpy + + +def conductor(direction: int, + polarity: int, + ) -> List[str]: + """ + Create source code for conducting boundary conditions. + + :param direction: integer in range(3), corresponding to x,y,z. + :param polarity: -1 or 1, specifying eg. a -x or +x boundary. + :return: [E_source, H_source] source code for E and H boundary update steps. + """ + if direction not in range(3): + raise Exception('Invalid direction: {}'.format(direction)) + + if polarity not in (-1, 1): + raise Exception('Invalid polarity: {}'.format(polarity)) + + r = 'xyz'[direction] + uv = 'xyz'.replace(r, '') + + if polarity < 0: + bc_E = """ +if ({r} == 0) {{ + E{r}[i] = 0; + E{u}[i] = E{u}[i+di{r}]; + E{v}[i] = E{v}[i+di{r}]; +}} +""" + bc_H = """ +if ({r} == 0) {{ + H{r}[i] = H{r}[i+di{r}]; + H{u}[i] = 0; + H{v}[i] = 0; +}} +""" + + elif polarity > 0: + bc_E = """ +if ({r} == s{r} - 1) {{ + E{r}[i] = -E{r}[i-2*di{r}]; + E{u}[i] = +E{u}[i-di{r}]; + E{v}[i] = +E{v}[i-di{r}]; +}} else if ({r} == s{r} - 2) {{ + E{r}[i] = 0; +}} +""" + bc_H = """ +if ({r} == s{r} - 1) {{ + H{r}[i] = +H{r}[i-di{r}]; + H{u}[i] = -H{u}[i-2*di{r}]; + H{v}[i] = -H{v}[i-2*di{r}]; +}} else if ({r} == s{r} - 2) {{ + H{u}[i] = 0; + H{v}[i] = 0; +}} +""" + else: + raise Exception() + + replacements = {'r': r, 'u': uv[0], 'v': uv[1]} + return [s.format(**replacements) for s in (bc_E, bc_H)] + + +def cpml(direction: int, + polarity: int, + dt: float, + thickness: int=8, + epsilon_eff: float=1, + ) -> Dict: + """ + Generate source code for complex phase matched layer (cpml) absorbing boundaries. + These are not full boundary conditions and require a conducting boundary to be added + in the same direction as the pml. + + :param direction: integer in range(3), corresponding to x, y, z directions. + :param polarity: -1 or 1, corresponding to eg. -x or +x direction. + :param dt: timestep used by the simulation + :param thickness: Number of cells used by the pml (the grid is NOT expanded to add these cells). Default 8. + :param epsilon_eff: Effective epsilon_r of the pml layer. Default 1. + :return: Dict with entries 'E', 'H' (update equations for E and H) and 'psi_E', 'psi_H' (lists of str, + specifying the field names of the cpml fields used in the E and H update steps. Eg., + Psi_xn_Ex for the complex Ex component for the x- pml.) + """ + if direction not in range(3): + raise Exception('Invalid direction: {}'.format(direction)) + + if polarity not in (-1, 1): + raise Exception('Invalid polarity: {}'.format(polarity)) + + if thickness <= 2: + raise Exception('It would be wise to have a pml with 4+ cells of thickness') + + if epsilon_eff <= 0: + raise Exception('epsilon_eff must be positive') + + m = (3.5, 1) + sigma_max = 0.8 * (m[0] + 1) / numpy.sqrt(epsilon_eff) + alpha_max = 0 # TODO: Decide what to do about non-zero alpha + transverse = numpy.delete(range(3), direction) + + r = 'xyz'[direction] + np = 'nVp'[numpy.sign(polarity)+1] + uv = ['xyz'[i] for i in transverse] + + xE = numpy.arange(1, thickness+1, dtype=float)[::-1] + xH = numpy.arange(1, thickness+1, dtype=float)[::-1] + if polarity > 0: + xE -= 0.5 + elif polarity < 0: + xH -= 0.5 + + def par(x): + sigma = ((x / thickness) ** m[0]) * sigma_max + alpha = ((1 - x / thickness) ** m[1]) * alpha_max + p0 = numpy.exp(-(sigma + alpha) * dt) + p1 = sigma / (sigma + alpha) * (p0 - 1) + return p0, p1 + p0e, p1e = par(xE) + p0h, p1h = par(xH) + + vals = {'r': r, + 'u': uv[0], + 'v': uv[1], + 'np': np, + 'th': thickness, + 'p0e': ', '.join((str(x) for x in p0e)), + 'p1e': ', '.join((str(x) for x in p1e)), + 'p0h': ', '.join((str(x) for x in p0h)), + 'p1h': ', '.join((str(x) for x in p1h)), + 'se': '-+'[direction % 2], + 'sh': '+-'[direction % 2]} + + if polarity < 0: + bounds_if = """ +if ( 0 < {r} && {r} < {th} + 1 ) {{ + const int ir = {r} - 1; // index into pml parameters + const int ip = {v} + {u} * s{v} + ir * s{v} * s{u}; // linear index into Psi +""" + elif polarity > 0: + bounds_if = """ +if ( (s{r} - 1) > {r} && {r} > (s{r} - 1) - ({th} + 1) ) {{ + const int ir = (s{r} - 1) - ({r} + 1); // index into pml parameters + const int ip = {v} + {u} * s{v} + ir * s{v} * s{u}; // linear index into Psi +""" + else: + raise Exception('Bad polarity (=0)') + + code_E = """ + // pml parameters: + const float p0[{th}] = {{ {p0e} }}; + const float p1[{th}] = {{ {p1e} }}; + + Psi_{r}{np}_E{u}[ip] = p0[ir] * Psi_{r}{np}_E{u}[ip] + p1[ir] * (H{v}[i] - H{v}[i-di{r}]); + Psi_{r}{np}_E{v}[ip] = p0[ir] * Psi_{r}{np}_E{v}[ip] + p1[ir] * (H{u}[i] - H{u}[i-di{r}]); + + E{u}[i] {se}= dt / eps{u}[i] * Psi_{r}{np}_E{u}[ip]; + E{v}[i] {sh}= dt / eps{v}[i] * Psi_{r}{np}_E{v}[ip]; +}} +""" + code_H = """ + // pml parameters: + const float p0[{th}] = {{ {p0h} }}; + const float p1[{th}] = {{ {p1h} }}; + + Psi_{r}{np}_H{u}[ip] = p0[ir] * Psi_{r}{np}_H{u}[ip] + p1[ir] * (E{v}[i+di{r}] - E{v}[i]); + Psi_{r}{np}_H{v}[ip] = p0[ir] * Psi_{r}{np}_H{v}[ip] + p1[ir] * (E{u}[i+di{r}] - E{u}[i]); + + H{u}[i] {sh}= dt * Psi_{r}{np}_H{u}[ip]; + H{v}[i] {se}= dt * Psi_{r}{np}_H{v}[ip]; +}} +""" + + pml_data = { + 'E': (bounds_if + code_E).format(**vals), + 'H': (bounds_if + code_H).format(**vals), + 'psi_E': ['Psi_{r}{np}_E{u}'.format(**vals), + 'Psi_{r}{np}_E{v}'.format(**vals)], + 'psi_H': ['Psi_{r}{np}_H{u}'.format(**vals), + 'Psi_{r}{np}_H{v}'.format(**vals)], + } + + return pml_data diff --git a/fdtd/simulation.py b/fdtd/simulation.py new file mode 100644 index 0000000..57b0ce7 --- /dev/null +++ b/fdtd/simulation.py @@ -0,0 +1,207 @@ +""" +Class for constructing and holding the basic FDTD operations and fields +""" + +from typing import List, Dict, Callable +import numpy +import warnings + +import pyopencl +import pyopencl.array +from pyopencl.elementwise import ElementwiseKernel + +from . import boundary, base +from .base import type_to_C + + +class Simulation(object): + """ + Constructs and holds the basic FDTD operations and related fields + """ + E = None # type: List[pyopencl.array.Array] + H = None # type: List[pyopencl.array.Array] + eps = None # type: List[pyopencl.array.Array] + dt = None # type: float + + arg_type = None # type: numpy.float32 or numpy.float64 + + context = None # type: pyopencl.Context + queue = None # type: pyopencl.CommandQueue + + update_E = None # type: Callable[[],pyopencl.Event] + update_H = None # type: Callable[[],pyopencl.Event] + + conductor_E = None # type: Callable[[],pyopencl.Event] + conductor_H = None # type: Callable[[],pyopencl.Event] + + cpml_E = None # type: Callable[[],pyopencl.Event] + cpml_H = None # type: Callable[[],pyopencl.Event] + + cpml_psi_E = None # type: Dict[str, pyopencl.array.Array] + cpml_psi_H = None # type: Dict[str, pyopencl.array.Array] + + def __init__(self, + epsilon: List[numpy.ndarray], + dt: float=.99/numpy.sqrt(3), + initial_E: List[numpy.ndarray]=None, + initial_H: List[numpy.ndarray]=None, + context: pyopencl.Context=None, + queue: pyopencl.CommandQueue=None, + float_type: numpy.float32 or numpy.float64=numpy.float32): + """ + Initialize the simulation. + + :param epsilon: List containing [eps_r,xx, eps_r,yy, eps_r,zz], where each element is a Yee-shifted ndarray + spanning the simulation domain. Relative epsilon is used. + :param dt: Time step. Default is the Courant factor. + :param initial_E: Initial E-field (default is 0 everywhere). Same format as epsilon. + :param initial_H: Initial H-field (default is 0 everywhere). Same format as epsilon. + :param context: pyOpenCL context. If not given, pyopencl.create_some_context(False) is called. + :param queue: pyOpenCL command queue. If not given, pyopencl.CommandQueue(context) is called. + :param float_type: numpy.float32 or numpy.float64. Default numpy.float32. + """ + + if len(epsilon) != 3: + Exception('Epsilon must be a list with length of 3') + if not all((e.shape == epsilon[0].shape for e in epsilon[1:])): + Exception('All epsilon grids must have the same shape. Shapes are {}', [e.shape for e in epsilon]) + + if context is None: + self.context = pyopencl.create_some_context(False) + else: + self.context = context + + if queue is None: + self.queue = pyopencl.CommandQueue(self.context) + else: + self.queue = queue + + if dt > .99/numpy.sqrt(3): + warnings.warn('Warning: unstable dt: {}'.format(dt)) + elif dt <= 0: + raise Exception('Invalid dt: {}'.format(dt)) + else: + self.dt = dt + + self.arg_type = float_type + + self.eps = [pyopencl.array.to_device(self.queue, e.astype(float_type)) for e in epsilon] + + if initial_E is None: + self.E = [pyopencl.array.zeros_like(self.eps[0]) for _ in range(3)] + else: + if len(initial_E) != 3: + Exception('Initial_E must be a list of length 3') + if not all((E.shape == epsilon[0].shape for E in initial_E)): + Exception('Initial_E list elements must have same shape as epsilon elements') + self.E = [pyopencl.array.to_device(self.queue, E.astype(float_type)) for E in initial_E] + + if initial_H is None: + self.H = [pyopencl.array.zeros_like(self.eps[0]) for _ in range(3)] + else: + if len(initial_H) != 3: + Exception('Initial_H must be a list of length 3') + if not all((H.shape == epsilon[0].shape for H in initial_H)): + Exception('Initial_H list elements must have same shape as epsilon elements') + self.H = [pyopencl.array.to_device(self.queue, H.astype(float_type)) for H in initial_H] + + E_args = [type_to_C(self.arg_type) + ' *E' + c for c in 'xyz'] + H_args = [type_to_C(self.arg_type) + ' *H' + c for c in 'xyz'] + eps_args = [type_to_C(self.arg_type) + ' *eps' + c for c in 'xyz'] + dt_arg = [type_to_C(self.arg_type) + ' dt'] + + sxyz = base.shape_source(epsilon[0].shape) + E_source = sxyz + base.dixyz_source + base.maxwell_E_source + H_source = sxyz + base.dixyz_source + base.maxwell_H_source + + E_update = ElementwiseKernel(self.context, operation=E_source, + arguments=', '.join(E_args + H_args + dt_arg + eps_args)) + + H_update = ElementwiseKernel(self.context, operation=H_source, + arguments=', '.join(E_args + H_args + dt_arg)) + + self.update_E = lambda e: E_update(*self.E, *self.H, self.dt, *self.eps, wait_for=e) + self.update_H = lambda e: H_update(*self.E, *self.H, self.dt, wait_for=e) + + def init_cpml(self, pml_args: List[Dict]): + """ + Initialize absorbing layers (cpml: complex phase matched layer). PMLs are not actual + boundary conditions, so you should add a conducting boundary (.init_conductors()) for + all directions in which you add PMLs. + Allows use of self.cpml_E(events) and self.cpml_H(events). + All necessary additional fields are created on the opencl device. + + :param pml_args: A list containing dictionaries which are passed to .boundary.cpml(...). + The dt argument is set automatically, but the others must be passed in each entry + of pml_args. + """ + sxyz = base.shape_source(self.eps[0].shape) + + # Prepare per-iteration constants for later use + pml_E_source = sxyz + base.dixyz_source + base.xyz_source + pml_H_source = sxyz + base.dixyz_source + base.xyz_source + + psi_E = [] + psi_H = [] + psi_E_names = [] + psi_H_names = [] + for arg_set in pml_args: + pml_data = boundary.cpml(dt=self.dt, **arg_set) + + pml_E_source += pml_data['E'] + pml_H_source += pml_data['H'] + + ti = numpy.delete(range(3), arg_set['direction']) + trans = [self.eps[0].shape[i] for i in ti] + psi_shape = (8, trans[0], trans[1]) + + psi_E += [pyopencl.array.zeros(self.queue, psi_shape, dtype=self.arg_type) + for _ in pml_data['psi_E']] + psi_H += [pyopencl.array.zeros(self.queue, psi_shape, dtype=self.arg_type) + for _ in pml_data['psi_H']] + + psi_E_names += pml_data['psi_E'] + psi_H_names += pml_data['psi_H'] + + E_args = [type_to_C(self.arg_type) + ' *E' + c for c in 'xyz'] + H_args = [type_to_C(self.arg_type) + ' *H' + c for c in 'xyz'] + eps_args = [type_to_C(self.arg_type) + ' *eps' + c for c in 'xyz'] + dt_arg = [type_to_C(self.arg_type) + ' dt'] + arglist_E = [type_to_C(self.arg_type) + ' *' + psi for psi in psi_E_names] + arglist_H = [type_to_C(self.arg_type) + ' *' + psi for psi in psi_H_names] + pml_E_args = ', '.join(E_args + H_args + dt_arg + eps_args + arglist_E) + pml_H_args = ', '.join(E_args + H_args + dt_arg + arglist_H) + + pml_E = ElementwiseKernel(self.context, arguments=pml_E_args, operation=pml_E_source) + pml_H = ElementwiseKernel(self.context, arguments=pml_H_args, operation=pml_H_source) + + self.cpml_E = lambda e: pml_E(*self.E, *self.H, self.dt, *self.eps, *psi_E, wait_for=e) + self.cpml_H = lambda e: pml_H(*self.E, *self.H, self.dt, *psi_H, wait_for=e) + self.cmpl_psi_E = {k: v for k, v in zip(psi_E_names, psi_E)} + self.cmpl_psi_H = {k: v for k, v in zip(psi_H_names, psi_H)} + + def init_conductors(self, conductor_args: List[Dict]): + """ + Initialize reflecting boundary conditions. + Allows use of self.conductor_E(events) and self.conductor_H(events). + + :param conductor_args: List of dictionaries with which to call .boundary.conductor(...). + """ + + sxyz = base.shape_source(self.eps[0].shape) + + # Prepare per-iteration constants + bc_E_source = sxyz + base.dixyz_source + base.xyz_source + bc_H_source = sxyz + base.dixyz_source + base.xyz_source + for arg_set in conductor_args: + [e, h] = boundary.conductor(**arg_set) + bc_E_source += e + bc_H_source += h + + E_args = [type_to_C(self.arg_type) + ' *E' + c for c in 'xyz'] + H_args = [type_to_C(self.arg_type) + ' *H' + c for c in 'xyz'] + bc_E = ElementwiseKernel(self.context, arguments=E_args, operation=bc_E_source) + bc_H = ElementwiseKernel(self.context, arguments=H_args, operation=bc_H_source) + + self.conductor_E = lambda e: bc_E(*self.E, wait_for=e) + self.conductor_H = lambda e: bc_H(*self.H, wait_for=e) diff --git a/pcgen.py b/pcgen.py new file mode 100644 index 0000000..d61a793 --- /dev/null +++ b/pcgen.py @@ -0,0 +1,206 @@ +""" +Routines for creating normalized 2D lattices and common photonic crystal + cavity designs. +""" + +from typing import List + +import numpy + + +def triangular_lattice(dims: List[int], + asymmetrical: bool=False + ) -> numpy.ndarray: + """ + Return an ndarray of [[x0, y0], [x1, y1], ...] denoting lattice sites for + a triangular lattice in 2D. The lattice will be centered around (0, 0), + unless asymmetrical=True in which case there will be extra holes in the +x + direction. + + :param dims: Number of lattice sites in the [x, y] directions. + :param asymmetrical: If true, each row in x will contain the same number of + lattice sites. If false, the structure is symmetrical around (0, 0). + :return: [[x0, y0], [x1, 1], ...] denoting lattice sites. + """ + dims = numpy.array(dims, dtype=int) + + if asymmetrical: + k = 0 + else: + k = 1 + + positions = [] + for j in numpy.arange(dims[1]): + j_odd = j % 2 + x_offset = (j_odd * 0.5) - dims[0]/2 + y_offset = dims[1]/2 + xs = numpy.arange(dims[0] - k * j_odd) + x_offset + ys = numpy.full_like(xs, j * numpy.sqrt(3)/2 + y_offset) + positions += [numpy.vstack((xs, ys)).T] + xy = numpy.vstack(tuple(positions)) + return xy[xy[:, 0].argsort(), ] + + +def square_lattice(dims: List[int]) -> numpy.ndarray: + """ + Return an ndarray of [[x0, y0], [x1, y1], ...] denoting lattice sites for + a square lattice in 2D. The lattice will be centered around (0, 0). + + :param dims: Number of lattice sites in the [x, y] directions. + :return: [[x0, y0], [x1, 1], ...] denoting lattice sites. + """ + xs, ys = numpy.meshgrid(range(dims[0]), range(dims[1]), 'xy') + xs -= dims[0]/2 + ys -= dims[1]/2 + xy = numpy.vstack((xs.flatten(), ys.flatten())).T + return xy[xy[:, 0].argsort(), ] + +# ### Photonic crystal functions ### + + +def nanobeam_holes(a_defect: float, + num_defect_holes: int, + num_mirror_holes: int + ) -> numpy.ndarray: + """ + Returns a list of [[x0, r0], [x1, r1], ...] of nanobeam hole positions and radii. + Creates a region in which the lattice constant and radius are progressively + (linearly) altered over num_defect_holes holes until they reach the value + specified by a_defect, then symmetrically returned to a lattice constant and + radius of 1, which is repeated num_mirror_holes times on each side. + + :param a_defect: Minimum lattice constant for the defect, as a fraction of the + mirror lattice constant (ie., for no defect, a_defect = 1). + :param num_defect_holes: How many holes form the defect (per-side) + :param num_mirror_holes: How many holes form the mirror (per-side) + :return: Ndarray [[x0, r0], [x1, r1], ...] of nanobeam hole positions and radii. + """ + a_values = numpy.linspace(a_defect, 1, num_defect_holes, endpoint=False) + xs = a_values.cumsum() - (a_values[0] / 2) # Later mirroring makes center distance 2x as long + mirror_xs = numpy.arange(1, num_mirror_holes + 1) + xs[-1] + mirror_rs = numpy.ones_like(mirror_xs) + return numpy.vstack((numpy.hstack((-mirror_xs[::-1], -xs[::-1], xs, mirror_xs)), + numpy.hstack((mirror_rs[::-1], a_values[::-1], a_values, mirror_rs)))).T + + +def ln_defect(mirror_dims: List[int], defect_length: int) -> numpy.ndarray: + """ + N-hole defect in a triangular lattice. + + :param mirror_dims: [x, y] mirror lengths (number of holes). Total number of holes + is 2 * n + 1 in each direction. + :param defect_length: Length of defect. Should be an odd number. + :return: [[x0, y0], [x1, y1], ...] for all the holes + """ + if defect_length % 2 != 1: + raise Exception('defect_length must be odd!') + p = triangular_lattice([2 * d + 1 for d in mirror_dims]) + half_length = numpy.floor(defect_length / 2) + hole_nums = numpy.arange(-half_length, half_length + 1) + holes_to_keep = numpy.in1d(p[:, 0], hole_nums, invert=True) + return p[numpy.logical_or(holes_to_keep, p[:, 1] != 0), ] + + +def ln_shift_defect(mirror_dims: List[int], + defect_length: int, + shifts_a: List[float]=(0.15, 0, 0.075), + shifts_r: List[float]=(1, 1, 1) + ) -> numpy.ndarray: + """ + N-hole defect with shifted holes (intended to give the mode a gaussian profile + in real- and k-space so as to improve both Q and confinement). Holes along the + defect line are shifted and altered according to the shifts_* parameters. + + :param mirror_dims: [x, y] mirror lengths (number of holes). Total number of holes + is 2 * n + 1 in each direction. + :param defect_length: Length of defect. Should be an odd number. + :param shifts_a: Percentage of a to shift (1st, 2nd, 3rd,...) holes along the defect line + :param shifts_r: Factor to multiply the radius by. Should match length of shifts_a + :return: [[x0, y0, r0], [x1, y1, r1], ...] for all the holes + """ + if not hasattr(shifts_a, "__len__") and shifts_a is not None: + shifts_a = [shifts_a] + if not hasattr(shifts_r, "__len__") and shifts_r is not None: + shifts_r = [shifts_r] + + xy = ln_defect(mirror_dims, defect_length) + + # Add column for radius + xyr = numpy.hstack((xy, numpy.ones((xy.shape[0], 1)))) + + # Shift holes + # Expand shifts as necessary + n_shifted = max(len(shifts_a), len(shifts_r)) + + tmp_a = numpy.array(shifts_a) + shifts_a = numpy.ones((n_shifted, )) + shifts_a[:len(tmp_a)] = tmp_a + + tmp_r = numpy.array(shifts_r) + shifts_r = numpy.ones((n_shifted, )) + shifts_r[:len(tmp_r)] = tmp_r + + x_removed = numpy.floor(defect_length / 2) + + for ind in range(n_shifted): + for sign in (-1, 1): + x_val = sign * (x_removed + ind + 1) + which = numpy.logical_and(xyr[:, 0] == x_val, xyr[:, 1] == 0) + xyr[which, ] = (x_val + numpy.sign(x_val) * shifts_a[ind], 0, shifts_r[ind]) + + return xyr + + +def r6_defect(mirror_dims: List[int]) -> numpy.ndarray: + """ + R6 defect in a triangular lattice. + + :param mirror_dims: [x, y] mirror lengths (number of holes). Total number of holes + is 2 * n + 1 in each direction. + :return: [[x0, y0], [x1, y1], ...] specifying hole centers. + """ + xy = triangular_lattice([2 * d + 1 for d in mirror_dims]) + + rem_holes_plus = numpy.array([[1, 0], + [0.5, +numpy.sqrt(3)/2], + [0.5, -numpy.sqrt(3)/2]]) + rem_holes = numpy.vstack((rem_holes_plus, -rem_holes_plus)) + + for rem_xy in rem_holes: + xy = xy[(xy != rem_xy).any(axis=1), ] + + return xy + + +def l3_shift_perturbed_defect(mirror_dims: List[int], + perturbed_radius: float=1.1, + shifts_a: List[float]=(), + shifts_r: List[float]=() + ) -> numpy.ndarray: + """ + 3-hole defect with perturbed hole sizes intended to form an upwards-directed + beam. Can also include shifted holes along the defect line, intended + to give the mode a more gaussian profile to improve Q. + + :param mirror_dims: [x, y] mirror lengths (number of holes). Total number of holes + is 2 * n + 1 in each direction. + :param perturbed_radius: Amount to perturb the radius of the holes used for beam-forming + :param shifts_a: Percentage of a to shift (1st, 2nd, 3rd,...) holes along the defect line + :param shifts_r: Factor to multiply the radius by. Should match length of shifts_a + :return: [[x0, y0, r0], [x1, y1, r1], ...] for all the holes + """ + xyr = ln_shift_defect(mirror_dims, 3, shifts_a, shifts_r) + + abs_x, abs_y = (numpy.fabs(xyr[:, i]) for i in (0, 1)) + + # Sorted unique xs and ys + # Ignore row y=0 because it might have shifted holes + xs = numpy.unique(abs_x[abs_x != 0]) + ys = numpy.unique(abs_y) + + # which holes should be perturbed? (xs[[3, 7]], ys[1]) and (xs[[2, 6]], ys[2]) + perturbed_holes = ((xs[a], ys[b]) for a, b in ((3, 1), (7, 1), (2, 2), (6, 2))) + for row in xyr: + if numpy.fabs(row) in perturbed_holes: + row[2] = perturbed_radius + return xyr diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..6121670 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,6 @@ +numpy +h5py +pyopencl +-e git+https://mpxd.net/gogs/jan/float_raster.git@release#egg=float_raster +-e git+https://mpxd.net/gogs/jan/gridlock.git@release#egg=gridlock +-e git+https://mpxd.net/gogs/jan/masque.git@release#egg=masque