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توضیحات

Electromagnetic Finite Difference Frequency Domain Solver

ویژگی	مقدار
سیستم عامل	-
نام فایل	fdfdpy-0.1.2
نام	fdfdpy
نسخه کتابخانه	0.1.2
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Tyler Hughes, Momchil Minkov, Ian Williamson
ایمیل نویسنده	tylerwhughes91@gmail.com
آدرس صفحه اصلی	https://github.com/fancompute/fdfdpy
آدرس اینترنتی	https://pypi.org/project/fdfdpy/
مجوز	-

![](img/dipole_dielectric_field.png) # fdfdpy This is a pure Python implementation of the finite difference frequency domain (FDFD) method. It makes use of scipy, numpy, matplotlib, and the MKL Pardiso solver. fdfdpy currently supports 2D geometries ## Installation python setup.py install ## Structure ### Initialization The `Fdfd` class is initialized as simulation = Fdfd(omega, eps_r, dl, NPML, pol, L0) - `omega` : the angular frequency in units of` 2 pi / seconds` - `eps_r` : a numpy array specifying the relative permittivity distribution - `dl` : the spatial grid size in units of `L0` - `NPML` : defines number of PML grids `[# on x borders, # on y borders]` - `pol` : polarization, one of `{'Hz','Ez'}` where `z` is the transverse field. - `L0` : simulation length scale, default is 1e-6 meters (one micron) Creating a new Fdfd object solves for: - `xrange` : defines spatial domain in x [left-most position, right-most position] in units of `L0` - `yrange` : defines spatial domain in y [bottom-most position, top-most position] in units of `L0` - `A` : the Maxwell operator, which is used later to solve for the E&M fields. - `derivs` : dictionary storing the derivative operators. It also creates a relative permeability, `mu_r`, as `numpy.ones(eps_r.shape)` and a source `src` as `numpy.zeros(eps_r.shape)`. ### Adding sources is exciting! Sources can be added to the simulation either by manually editing the 2D src array inside of the simulation object, simulation.src[10,20:30] = 1 or by adding modal sources, which are defined as planes within the 2D domain which launch a mode in their normal direction. Modal source definitions can be added to the simulation by simulation.add_mode(neff, direction, center, width) simulation.setup_modes() - `neff` : defines the effective index of the mode; this will be used as the eigenvalue guess - `direction` : defines the normal direction of the plane, should be either 'x' or 'y' - `center` : defines the center coordinates for the plane in cell coordinates [xc, yc] - `width` : defines the width of the plane in number of cells Note that `simulation.setup_modes()` must always be called after adding mode(s) in order to populate `simulation.src`. ### Solving for the electromagnetic fields Now, we have everything we need to solve the system for the electromagnetic fields, by running fields = simulation.solve_fields(timing=False) `simulation.src` is proportional to either the `Jz` or `Mz` source term, depending on whether `pol` is set to `'Ez'` or `'Hz'`, respectively. `fields` is a tuple containing `(Ex, Ey, Hz)` or `(Hx, Hy, Ez)` depending on the polarization. ### Setting a new permittivity If you want to change the permittivity distribution, you may run simulation.reset_eps(new_eps) And this will reconstruct the system matrix and store it in `FDFD`. Note that `simulation.setup_modes()` should also be called if the permittivity changed within the plane of any of the modal sources. ### Plotting Primary fields (Hz/Ez) can be visualized using the included helper functions: simulation.plt_re(outline=True, cbar=True) simulation.plt_abs(outline=True, cbar=True) These optionally outline the permittivity with contours and can be supplied with a matplotlib axis handle to plot into. ### Requirements - numpy - scipy - matplotlib To load the MKL solver: git submodule update --init --recursive ### To Do #### Whenever - [x] Modal source. - [x] More dope plotting methods. - [ ] xrange, yrange labels on plots. - [ ] set modal source amplitude (and normalization) - [ ] Add ability to run local jupyter notebooks running FDFD on parallel from hera. - [ ] Save the factorization of `A` in the `Fdfd` object to be reused later if one has the same `A` but a different `b`. - [ ] Allow the source term to have `(Jx, Jy, Jz, Mx, My, Mz)`, which would be useful for adjoint stuff where the source is not necessarily along the `z` direction. - [ ] Clean up imports (e.g. `import numpy as np` to `from numpy import abs, zeros, ...`)

نحوه نصب

نصب پکیج whl fdfdpy-0.1.2:

pip install fdfdpy-0.1.2.whl

نصب پکیج tar.gz fdfdpy-0.1.2:

pip install fdfdpy-0.1.2.tar.gz