jan/opencl_fdtd
2
2
Fork 1
Code Issues Pull Requests Releases Wiki Activity

convert docstring to cleaner style

Browse Source
This commit is contained in:
Jan Petykiewicz 2021-07-11 17:06:32 -07:00
parent bbd33844b3
commit 292fde05d5
1 changed files with 29 additions and 32 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

37
opencl_fdtd/simulation.py
View File

@ -23,7 +23,7 @@ jinja_env = jinja2.Environment(loader=jinja2.PackageLoader(__name__, 'kernels'))
class Simulation(object):
"""
r"""
Constructs and holds the basic FDTD operations and related fields
After constructing this object, call the (update_E, update_H, update_S) members
@ -91,9 +91,10 @@ class Simulation(object):
"""
Initialize the simulation.
:param epsilon: List containing [eps_r,xx, eps_r,yy, eps_r,zz], where each element is a Yee-shifted ndarray
Args:
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 pmls: List of dicts with keys:
pmls: List of dicts with keys:
'axis': One of 'x', 'y', 'z'.
'direction': One of 'n', 'p'.
'thickness': Number of layers, default 8.
@ -102,28 +103,24 @@ class Simulation(object):
'ln_R_per_layer': Desired (ln(R) / thickness) value. Default -1.6.
'm': Polynomial grading exponent. Default 3.5.
'ma': Exponent for alpha. Default 1.
:param bloch_boundaries: List of dicts with keys:
bloch_boundaries: List of dicts with keys:
'axis': One of 'x', 'y', 'z'.
'real': Real part of bloch phase factor (i.e. real(exp(i * phase)))
'imag': Imaginary part of bloch phase factor (i.e. imag(exp(i * phase)))
:param dt: Time step. Default is min(dxes) * .99/sqrt(3).
:param initial_fields: Dict with optional keys ('E', 'H', 'F', 'G') containing initial values for the
dt: Time step. Default is min(dxes) * .99/sqrt(3).
initial_fields: Dict with optional keys ('E', 'H', 'F', 'G') containing initial values for the
specified fields (default is 0 everywhere). Fields have 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.
:param do_poynting: If true, enables calculation of the poynting vector, S.
context: pyOpenCL context. If not given, pyopencl.create_some_context(False) is called.
queue: pyOpenCL command queue. If not given, pyopencl.CommandQueue(context) is called.
float_type: numpy.float32 or numpy.float64. Default numpy.float32.
do_poynting: If true, enables calculation of the poynting vector, S.
Poynting vector calculation adds the following computational burdens:
****INACCURATE, TODO FIXME*****
* During update_H, ~6 extra additions/cell are performed in order to spatially
average E and temporally average H. These quantities are multiplied
(6 multiplications/cell) and then stored (6 writes/cell, cache-friendly).
* update_S performs a discrete cross product using the precalculated products
from update_H. This is not nice to the cache and similar to e.g. update_E
in complexity.
* GPU memory requirements are approximately doubled, since S and the intermediate
products must be stored.
:param do_poynting_halves: TODO DOCUMENT
* During update_H, ~6 extra additions/cell are performed in order to temporally
sum H. The results are then multiplied by E (6 multiplications/cell) and
then stored (6 writes/cell, cache-friendly). The E-field components are
reused from the H-field update and do not require additional H
* GPU memory requirements increase by 50% (for storing S)
do_poynting_halves: TODO DOCUMENT
"""
if initial_fields is None:
initial_fields = {}