├── .gitignore
├── Dockerfile
├── LICENSE.md
├── README.md
├── environment.yml
├── epsilon
├── eAgFerreiraf.edb
├── eAgPalikSTDf.edb
├── eAlRakicSTDf.edb
├── eAuJCSTDf.edb
├── eAuPalikSTDf.edb
├── eAuWoolam.edb
├── eBK7HikariSTDf.edb
├── eBK7HoyaSTDf.edb
├── eBK7SchottSTDf.edb
├── eBK7SumitaSTDf.edb
├── eCoSTDf.edb
├── eCoWoolam.edb
├── eCrSopraSTDf.edb
├── eCrWoolam.edb
├── eCuPalikSTDf.edb
├── eFeArgonneSTDf.edb
├── eH2OHaleSTDf.edb
├── eHexaneSTDf.edb
├── eNixxPalikSTDf.edb
├── eSF10SchottSTDf.edb
├── eSiO2PalikSTDf.edb
├── eSiPalikSTDf.edb
├── eSilkSTDf.edb
├── eTiO2PalikSTDf.edb
├── eTiWoolam.edb
├── eVacuum.edb
├── eZero.edb
└── eagJCf.edb
├── examples
├── AuAg_dimer.ipynb
├── Au_dimer_scattering.ipynb
├── Chirality.ipynb
└── Stockman Silver Nanolens.ipynb
├── images
└── array.png
├── notebook_config.py
├── py_gmm
├── __init__.py
├── basicsubs.f90
├── datatypes.f90
├── f2py.sh
├── gmm_f2py_module.f90
├── gmmsubs.f90
├── kinds.f90
├── linear_solver.f90
├── local_field.f90
├── mat.py
├── operators.f90
├── shared_data.f90
├── sing_part.f90
└── vec_trans.f90
└── setup.py
/.gitignore:
--------------------------------------------------------------------------------
1 | *.mod
2 | *.o
3 | *.so
4 | py_gmm/tmp/**
5 | py_gmm/__pycache__/**
6 | *.pyf
7 | .ipynb_checkpoints/**
8 | examples/.ipynb_checkpoints/**
9 |
--------------------------------------------------------------------------------
/Dockerfile:
--------------------------------------------------------------------------------
1 | FROM jupyter/datascience-notebook:ubuntu-20.04
2 |
3 | ADD . $HOME/notebooks
4 |
5 | USER root
6 |
7 | RUN apt update
8 |
9 |
10 | RUN apt -y install liblapack-dev liblapack3 libopenblas-base libopenblas-dev gfortran
11 | RUN ln -s /opt/OpenBLAS/lib/libopenblas.so /usr/lib/libopenblas.so
12 |
13 | RUN chown -R $NB_USER:users $HOME/notebooks
14 |
15 | USER $NB_USER
16 |
17 | # WORKDIR $HOME/notebooks
18 |
19 | # RUN conda env create -n binder python=3.6
20 | # RUN pip install plotly
21 |
22 | # ENV PATH /home/main/anaconda2/envs/binder/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
23 |
24 | WORKDIR $HOME/notebooks/py_gmm
25 |
26 | # RUN /bin/bash -c "source activate binder && sh f2py.sh"
27 | RUN /bin/bash -c "sh f2py.sh"
28 |
29 | WORKDIR $HOME/notebooks
30 |
31 | # RUN /bin/bash -c "source activate binder && ipython kernelspec install-self --user"
32 |
--------------------------------------------------------------------------------
/LICENSE.md:
--------------------------------------------------------------------------------
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650 | Also add information on how to contact you by electronic and paper mail.
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668 |
669 | The GNU General Public License does not permit incorporating your program
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674 | .
675 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # py_gmm
2 |
3 | [](http://mybinder.org/repo/gevero/py_gmm)
4 |
5 |
6 |
7 | A Fortran 90 implementation of the **Generalized Multiparticle Mie** method. If you find py_gmm useful for generating results included in publications, please consider citing the following paper:
8 |
9 | Pellegrini G., Mattei G., Bello V. and Mazzoldi P. (2007) **Interacting metal nanoparticles: Optical properties from nanoparticle dimers to core-satellite systems** *Materials Science and Engineering: C 27:1347–1350*. [doi:10.1016/j.msec.2006.07.025](http://dx.doi.org/10.1016/j.msec.2006.07.025)
10 |
11 | ## Use it right away
12 |
13 | Do you want to try **py_gmm** without even installing it? Well, just click this badge [](http://mybinder.org/repo/gevero/py_gmm) or the one on top of the page! Then simply navigate to the **examples** folder and run one of the [Jupyter Notebooks](http://ipython.org/notebook.html). Modify the examples to suite your needs and run it! **Just one thing: please run only light calculations!!!**
14 |
15 | ## Use Docker
16 |
17 | Another option is to use docker. The instructions below are for linux, but should work on other platforms with minor [modifications](https://docs.docker.com/get-started/):
18 |
19 | 1. Install docker on your machine (do this, and the following, as root if using linux).
20 | 2. In the py_gmm base folder, the one that contains the Dockerfile, run `docker build --tag pygmm:1.0 .` to build the py_gmm image.
21 | 3. Run `docker run --publish 8888:8888 --detach --name pygmm pygmm:1.0` to start a container named **pygmm** and forward the 8888 port from the container to your machine. A jupyter server is already running inside the container.
22 | 4. Run `docker exec -it pygmm jupyter notebook list` to get the token that will give you access to the jupyter server.
23 |
24 | ## Installation the hard way
25 |
26 | Installing **py_gmm** should be fairly easy. First of all you need a python distribution on your system. The simplest thing to do, for any operating system (**Windows**, **OSX** or **Linux**), would be to install [Anaconda](https://store.continuum.io/cshop/anaconda/), a beautiful, free, and easy to use python distribution: the relevant installations instructions are found [here](http://docs.continuum.io/anaconda/install.html). Then you must also install The [Jupyter Notebook](http://ipython.org/notebook.html), which is already bundled in Anaconda.
27 |
28 | The second step would be installing a Fortran compiler. If you are not new to compilers, you're already covered here. If don't know much about compilers yet, my advice is to go for [gfortran](https://gcc.gnu.org/wiki/GFortran). While I strongly advise you to work under **Linux** (this code was developed under **Linux**), I will try to provide minimal informations for the installations under **WIndows** and **OSX**. Keep in mind that I never installed or tried my software under these platforms, so I offer no guarantee whatsoever. Nevertheless if you encounter any problem please open an **Issue** here on github and we'll try to work it out. Regarding installation on different platforms it goes as follows:
29 |
30 | * **Windows:** Get [MinGW](http://www.mingw.org/wiki/howto_install_the_mingw_gcc_compiler_suite) and follow the instructions to install **gfortran** on your system;
31 | * **OSX:** Get the right [gfortran](https://gcc.gnu.org/wiki/GFortranBinaries#MacOS) and if needed read the instructions [here](https://gcc.gnu.org/wiki/GFortranBinariesMacOS);
32 | * **Linux:** Install **gfortran** with the package manager of your own distro: it should be no trouble at all.
33 |
34 | The third step would be to get **py_gmm** itself. If you are familiar with [git](http://git-scm.com/) and [github](https://github.com/) you can simply clone the repository, otherwise just [download](https://github.com/gevero/py_gmm/archive/master.zip) the zipped version of the repo and unpack it wherever you like.
35 |
36 | Then we finally come to compiling: if you are under **Linux** or **OSX** `sh f2py.sh` should be sufficient to build everything. Under **Windows** try and change `f2py.sh` to `f2py.bat` and see what happens. If it does not work open an issue and we'll work it out.
37 |
38 | ## Usage
39 |
40 | The best thing to do for the moment is to start from the **.ipynb** files in the [examples](https://github.com/gevero/py_gmm/tree/master/examples) folder. You can load them in your local **Jupyter Notebook** instance: they should give you a fair idea about how to proceed for your calculations. Each function in the code features a detailed documentation easily accessible with the `Shift-Tab` tool-tip shortcut from the **Jupyter Notebook** interface.
41 |
--------------------------------------------------------------------------------
/environment.yml:
--------------------------------------------------------------------------------
1 | name: binder
2 | dependencies:
3 | - numpy
4 | - scipy
5 | - matplotlib
6 | - pip:
7 | - plotly
8 |
--------------------------------------------------------------------------------
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77 |
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--------------------------------------------------------------------------------
/epsilon/eCoWoolam.edb:
--------------------------------------------------------------------------------
1 | 2.119000000000000057e+02 -1.408000000000000584e+00 5.023200000000000109e+00
2 | 2.313000000000000114e+02 -1.336000000000000743e+00 5.497799999999999798e+00
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27 |
--------------------------------------------------------------------------------
/epsilon/eCrWoolam.edb:
--------------------------------------------------------------------------------
1 | 5.86E+28 4.00E-14 1.39E+06
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56 | 1.771000000000000000e+03 -1.516799999999999926e+01 4.483179999999999410e+01
57 |
--------------------------------------------------------------------------------
/epsilon/eSiO2PalikSTDf.edb:
--------------------------------------------------------------------------------
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--------------------------------------------------------------------------------
/epsilon/eTiWoolam.edb:
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/epsilon/eVacuum.edb:
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1803 |
--------------------------------------------------------------------------------
/epsilon/eZero.edb:
--------------------------------------------------------------------------------
1 | 5.86E+028 4.00E-014 1.39E+006
2 | 200 0 0
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1734 | 1932 0 0
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1742 | 1940 0 0
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1748 | 1946 0 0
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1751 | 1949 0 0
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1754 | 1952 0 0
1755 | 1953 0 0
1756 | 1954 0 0
1757 | 1955 0 0
1758 | 1956 0 0
1759 | 1957 0 0
1760 | 1958 0 0
1761 | 1959 0 0
1762 | 1960 0 0
1763 | 1961 0 0
1764 | 1962 0 0
1765 | 1963 0 0
1766 | 1964 0 0
1767 | 1965 0 0
1768 | 1966 0 0
1769 | 1967 0 0
1770 | 1968 0 0
1771 | 1969 0 0
1772 | 1970 0 0
1773 | 1971 0 0
1774 | 1972 0 0
1775 | 1973 0 0
1776 | 1974 0 0
1777 | 1975 0 0
1778 | 1976 0 0
1779 | 1977 0 0
1780 | 1978 0 0
1781 | 1979 0 0
1782 | 1980 0 0
1783 | 1981 0 0
1784 | 1982 0 0
1785 | 1983 0 0
1786 | 1984 0 0
1787 | 1985 0 0
1788 | 1986 0 0
1789 | 1987 0 0
1790 | 1988 0 0
1791 | 1989 0 0
1792 | 1990 0 0
1793 | 1991 0 0
1794 | 1992 0 0
1795 | 1993 0 0
1796 | 1994 0 0
1797 | 1995 0 0
1798 | 1996 0 0
1799 | 1997 0 0
1800 | 1998 0 0
1801 | 1999 0 0
1802 | 2000 0 0
1803 |
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/images/array.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/gevero/py_gmm/c6f84a58111ff03dcf2c89b07d23ff637e9272c4/images/array.png
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/notebook_config.py:
--------------------------------------------------------------------------------
1 | c.NotebookApp.iopub_data_rate_limit=1.0e10
2 |
--------------------------------------------------------------------------------
/py_gmm/__init__.py:
--------------------------------------------------------------------------------
1 | # -*- coding: utf-8 -*-
2 | """
3 | A Fortran 90 implementation of the Generalized Multiparticle Mie method.
4 | If you find py_gmm useful for generating results included in publications,
5 | please consider citing the following paper:
6 |
7 | Pellegrini G., Mattei G., Bello V. and Mazzoldi P. (2007)
8 | Interacting metal nanoparticles: Optical properties from
9 | nanoparticle dimers to core-satellite systems
10 | Materials Science and Engineering: C 27:1347–1350.
11 | doi:10.1016/j.msec.2006.07.025"
12 | """
13 |
14 | import py_gmm.gmm_py as gmm_py
15 | import py_gmm.mat as mat
16 |
--------------------------------------------------------------------------------
/py_gmm/datatypes.f90:
--------------------------------------------------------------------------------
1 | MODULE datatypes
2 |
3 | USE Kinds
4 |
5 | IMPLICIT NONE
6 | SAVE
7 |
8 | !******************************************************************************
9 | ! DERIVED DATA TYPES
10 | !******************************************************************************
11 |
12 | TYPE :: RDBL_CHAR
13 | REAL(dbl) :: value
14 | CHARACTER(len=length) :: text
15 | END TYPE
16 |
17 | !******************************************************************************
18 | ! LINKED LIST
19 | !******************************************************************************
20 |
21 |
22 | TYPE :: NODE_SGL_REAL ! Linked list reale single precision
23 | REAL(sgl) :: value
24 | TYPE (NODE_SGL_REAL), POINTER :: next
25 | END TYPE
26 |
27 | TYPE :: NODE_DBL_REAL ! Linked list reale double precision
28 | REAL(dbl) :: value
29 | TYPE (NODE_DBL_REAL), POINTER :: next
30 | END TYPE
31 |
32 | TYPE :: NODE_SGL_CMPLX ! Linked list complesso single precision
33 | COMPLEX(sgl) :: value
34 | TYPE (NODE_SGL_CMPLX), POINTER :: next
35 | END TYPE
36 |
37 | TYPE :: NODE_DBL_CMPLX ! Linked list complesso double precision
38 | COMPLEX(dbl) :: value
39 | TYPE (NODE_DBL_CMPLX), POINTER :: next
40 | END TYPE
41 |
42 |
43 | TYPE :: NODE_SHORT_INT ! Linked list integer short
44 | INTEGER(short) :: value
45 | TYPE (NODE_SHORT_INT), POINTER :: next
46 | END TYPE
47 |
48 | TYPE :: NODE_LONG_INT ! Linked list integer long
49 | INTEGER(lo) :: value
50 | TYPE (NODE_LONG_INT), POINTER :: next
51 | END TYPE
52 |
53 | TYPE :: NODE_CHAR ! Linked list character
54 | CHARACTER(len=length) :: value
55 | TYPE (NODE_CHAR), POINTER :: next
56 | END TYPE
57 |
58 | TYPE :: NODE_RDBL_CHAR ! Linked list character
59 | TYPE (RDBL_CHAR) :: value
60 | TYPE (NODE_RDBL_CHAR), POINTER :: next
61 | END TYPE
62 |
63 | END MODULE datatypes
--------------------------------------------------------------------------------
/py_gmm/f2py.sh:
--------------------------------------------------------------------------------
1 | f2py --overwrite-signature -m gmm_py -h gmm_py.pyf gmm_f2py_module.f90
2 | f2py -c -lopenblas --build-dir ./tmp --f90exec=/usr/bin/gfortran --fcompiler=gnu95 --f90flags='-O3 -fpic -m64 -Wno-argument-mismatch' gmm_py.pyf kinds.f90 datatypes.f90 operators.f90 shared_data.f90 basicsubs.f90 gmmsubs.f90 sing_part.f90 vec_trans.f90 local_field.f90 linear_solver.f90 gmm_f2py_module.f90
3 |
--------------------------------------------------------------------------------
/py_gmm/kinds.f90:
--------------------------------------------------------------------------------
1 | MODULE kinds
2 |
3 | IMPLICIT NONE
4 | SAVE
5 |
6 | INTEGER, PARAMETER :: sgl = SELECTED_REAL_KIND(p=6,r=37)
7 | INTEGER, PARAMETER :: dbl = SELECTED_REAL_KIND(p=15,r=307)
8 | !INTEGER, PARAMETER :: dbl = SELECTED_REAL_KIND(32)
9 | INTEGER, PARAMETER :: vshort = SELECTED_INT_KIND(2)
10 | INTEGER, PARAMETER :: short = SELECTED_INT_KIND(4)
11 | INTEGER, PARAMETER :: long = SELECTED_INT_KIND(9)
12 | INTEGER, PARAMETER :: lo = SELECTED_INT_KIND(9)
13 | INTEGER, PARAMETER :: length=30
14 |
15 | REAL(sgl), PARAMETER :: PI=3.1415926535897932384626433832795028841971
16 | REAL(sgl), PARAMETER :: PIO2=1.57079632679489661923132169163975144209858
17 | REAL(sgl), PARAMETER :: TWOPI=6.283185307179586476925286766559005768394
18 | REAL(sgl), PARAMETER :: SQRT2=1.41421356237309504880168872420969807856967
19 | REAL(sgl), PARAMETER :: EULER=0.5772156649015328606065120900824024310422
20 |
21 | REAL(dbl), PARAMETER :: PI_D=3.141592653589793238462643383279502884197
22 | REAL(dbl), PARAMETER :: PIO2_D=1.57079632679489661923132169163975144209858
23 | REAL(dbl), PARAMETER :: TWOPI_D=6.283185307179586476925286766559005768394
24 | REAL(dbl), PARAMETER :: SQRT2_D=1.41421356237309504880168872420969807856967
25 | REAL(dbl), PARAMETER :: EULER_D=0.5772156649015328606065120900824024310422
26 | REAL(dbl), PARAMETER :: e=1.6021765314e-19 ! Carica dell'elettrone
27 | REAL(dbl), PARAMETER :: me=9.109382616e-31 ! Massa dell'elettrone
28 | REAL(dbl), PARAMETER :: e0=8.854187817e-12 ! Costante dielettrica del vuoto
29 | REAL(dbl), PARAMETER :: c=2.99792458e8 ! Velocita' della luce nel vuoto
30 | REAL(dbl), PARAMETER :: zerodbl=0.0D0 ! Velocita' della luce nel vuoto
31 | END MODULE kinds
32 |
--------------------------------------------------------------------------------
/py_gmm/mat.py:
--------------------------------------------------------------------------------
1 | '''mat.py contains subroutines to create, tabulate and manipulate optical
2 | constants'''
3 |
4 | import numpy as np
5 | import numpy.linalg as np_l
6 | import scipy.constants as sp_c
7 | import glob
8 | import os
9 |
10 |
11 | def import_eps(eps_file):
12 | '''Utility to read in optical constants, i.e.
13 | dielectric functions
14 |
15 | Parameters
16 | ----------
17 | 'eps_file' = optical constant filename with
18 | full path
19 |
20 | Returns
21 | -------
22 | 'e_raw[:,0]' = wavelength
23 | 'e_raw[:,1]' = real part of the dielectric function
24 | 'e_raw[:,2]' = imaginari part of the dielectric function
25 | '''
26 |
27 | e_raw = np.loadtxt(eps_file,skiprows=1)
28 | return e_raw[:,0],e_raw[:,1],e_raw[:,2]
29 |
30 |
31 | def generate_eps_db(path_to_eps,ext="*.edb"):
32 | '''Utility to build a database of optical constants
33 |
34 | Parameters
35 | ----------
36 | 'path_to_eps' = path to the folder containing the
37 | files of the optical constants
38 | 'ext' = extension of the files of the optical
39 | constants. "*.edb" is the default extension for
40 | the optical constant files
41 |
42 |
43 | Returns
44 | -------
45 | 'a dictionary' = {'eps_files':eps_files, = fullpath optical constant file
46 | names
47 | 'eps_names':eps_names, = optical constants formal names
48 | 'eps_db':eps_db} = optical constant database
49 | dictionary
50 | '''
51 |
52 | eps_files = sorted(glob.glob(path_to_eps+ext))
53 | eps_names = [os.path.splitext(os.path.basename(eps))[0] for
54 | eps in eps_files]
55 |
56 | # Dielectric function dictionary database
57 | eps_db = {}
58 | for eps_name,eps_file in zip(eps_names,eps_files):
59 | eps_db[eps_name] = import_eps(eps_file)
60 |
61 | eps_dict = {'eps_files':eps_files,
62 | 'eps_names':eps_names,
63 | 'eps_db':eps_db}
64 |
65 | return eps_dict
66 |
67 |
68 | def db_to_eps(wl,eps_db,eps_list):
69 | '''Utility to do the following: it takes the optical constant database
70 | created with generate_eps_db end a list of optical constant names (taken
71 | from eps_names) and spits out a numpy.array of complex128 values, i.e. a
72 | vector containing the multilayer optical constants at the wavelength wl. It
73 | may come in handy when your multilayer is made of materials whose optical
74 | constants are already tabulated
75 |
76 | Parameters
77 | ----------
78 | 'wl' = interpolation wavelength
79 | 'eps_db' = optical constant database as from generate_eps_db
80 | 'eps_list' = a list of optical constant filenames taken from the output of
81 | generate_eps_db
82 |
83 | Returns
84 | -------
85 | 'e_list' = list of multilayer optical constants'''
86 |
87 | # checking wavelength
88 | for eps in eps_list:
89 | if (wl < eps_db[eps][0].min()):
90 | raise ValueError('interpolation wavelength too small: '
91 | + eps + '(' + str(wl) + '/' +
92 | str(eps_db[eps][0].min()) + ')')
93 | if (wl > eps_db[eps][0].max()):
94 | raise ValueError('interpolation wavelength too large: '
95 | + eps + '(' + str(wl) + '/' +
96 | str(eps_db[eps][0].max()) + ')')
97 |
98 | # dielectric constant array
99 | e_list = np.array([np.interp(wl,eps_db[eps][0],eps_db[eps][1]) +
100 | 1j*np.interp(wl,eps_db[eps][0],eps_db[eps][2])
101 | for eps in eps_list])
102 |
103 | return e_list
104 |
105 |
106 | def eps_drude(wl,eps_inf,w_p,gamma):
107 | '''computation of the drude dielectric function
108 |
109 | Parameters
110 | ----------
111 | 'wl' = computation wavelength (nm)
112 | 'eps_inf' = high frequency constant, for frequency much higher than the
113 | bulk plasma ones
114 | 'w_p' = bulk plasma frequency (eV)
115 | 'gamma' = damping constant (eV)
116 |
117 | Returns
118 | -------
119 | 'eps' = drude optical constant at the wavelength wl'''
120 |
121 | # computation
122 |
123 | # nm to eV
124 | w = 1240.0/wl
125 | eps = eps_inf-(w_p**2)/(w**2+1j*w*gamma)
126 |
127 | return eps
128 |
129 |
130 | def eps_corr_drude(wl,w_p,gamma_inf,vf,r):
131 | '''computation of the drude dielectric function correction
132 | for spherical particles of finite size as in:
133 | Kreibig Vollmer "Optical properties of metal clusters"
134 |
135 | Parameters
136 | ----------
137 | 'wl' = computation wavelength (nm)
138 | 'w_p' = bulk plasma frequency (eV)
139 | 'gamma_inf' = bulk damping constant (eV)
140 | 'vf' = Fermi velocity (m/s)
141 | 'r' = particle radius (nm)
142 |
143 | Returns
144 | -------
145 | 'eps_r' = drude optical constant size correction'''
146 |
147 | # computation
148 | h_bar = 6.58211928e-16 # h_bar eV
149 | gamma_r = gamma_inf+h_bar*vf/(r*1e-9)
150 | w = 1240.0/wl # nm to eV
151 |
152 | eps_r = (w_p**2)/(w**2 + 1j*w*gamma_inf) - (w_p**2)/(w**2 + 1j*w*gamma_r)
153 |
154 | return eps_r
155 |
156 |
157 | def eps_xy_drude(wl,w_p,gamma,B,f_m=0.0):
158 | '''computation of the off diagonal optical constant for a noble metal
159 | according to a free electron model
160 |
161 | Parameters
162 | ----------
163 | 'wl' = computation wavelength (nm)
164 | 'w_p' = bulk plasma frequency (eV)
165 | 'gamma' = damping constant (eV)
166 | 'B' = magnetic field (Tesla)
167 | 'f_m' = Verdet constant
168 |
169 | Returns
170 | -------
171 | 'eps_xy' = off diagonal drude optical constant at the wavelength wl'''
172 |
173 | # computation
174 | h_bar = 6.58211928e-16 # h_bar eV
175 | w = 1240.0/wl # nm to eV
176 | m_e = sp_c.m_e # electron mass
177 | e_el = sp_c.e # elementary charge
178 | w_c = -h_bar*(e_el*B)/m_e # cyclotron frequency (rad/s to eV)
179 | eps_xy = 1j*((w_p**2)*w_c)/(w*(w+1j*gamma)**2)
180 |
181 | return eps_xy
182 |
183 |
184 | def m_eff_MG(m_L,m_D,V,m_e1,m_e2,w_l,f):
185 | '''calculates the MG effective dielectric tensor for the ellipsoid layer
186 |
187 | Parameters
188 | ----------
189 | 'm_L,m_D' = static and dynamic geometrical tensor of the ellipsoid
190 | 'V'=volume of the ellipsoind
191 | 'm_e1,m_e2' = diagonal tensor of the embedding matrix,
192 | Magneto Optical tensor of the ellipsoid
193 | 'w_l' = incident wavelength in nm
194 | 'f' = filling factor
195 |
196 | Returns
197 | -------
198 | 'eff_MG' = effective dielectric tensor of the mixed material
199 | containing the ellipsoids'''
200 |
201 | m_I = np.identity(3)
202 | k = 2.0*np.pi*np.sqrt(m_e1[2,2])/w_l
203 |
204 | m_1 = (1-f)*(m_L - ((k**2)*V*m_D/(4.0*np.pi)) -
205 | 1j*((k**3)*V*m_I/(6.0*np.pi)))
206 | m_2 = m_e2-m_e1
207 | m_3 = m_I+np.dot(np.dot(m_1,m_2),np_l.inv(m_e1))
208 |
209 | eff_MG = m_e1+np.dot(f*m_2,np_l.inv(m_3))
210 |
211 | return eff_MG
212 |
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/py_gmm/operators.f90:
--------------------------------------------------------------------------------
1 | MODULE operators
2 |
3 | USE kinds
4 | USE datatypes
5 |
6 | INTERFACE OPERATOR (==)
7 | MODULE PROCEDURE equals_rdbl_char
8 | END INTERFACE
9 |
10 | CONTAINS
11 |
12 | LOGICAL FUNCTION equals_rdbl_char(left_hand,right_hand)
13 |
14 | IMPLICIT NONE
15 |
16 | ! Dichiarazione dummy arguments
17 | TYPE (RDBL_CHAR), INTENT(IN) :: left_hand, right_hand
18 |
19 | equal_if: IF ( (left_hand%value == right_hand%value) .AND. (right_hand%text == left_hand%text) ) THEN
20 | equals_rdbl_char = .TRUE.
21 | ELSE
22 | equals_rdbl_char = .FALSE.
23 | END IF equal_if
24 | END FUNCTION equals_rdbl_char
25 |
26 |
27 |
28 | END MODULE operators
--------------------------------------------------------------------------------
/py_gmm/shared_data.f90:
--------------------------------------------------------------------------------
1 | MODULE shared_data
2 |
3 | USE KINDS
4 |
5 | IMPLICIT NONE
6 | SAVE
7 | !********************************************************************************************************************
8 | !********************************************************************************************************************
9 | !********************************************************************************************************************
10 | ! Shared Variables
11 | !********************************************************************************************************************
12 | !********************************************************************************************************************
13 | !********************************************************************************************************************
14 | INTEGER(lo) :: nstop,ns,nsc,ncell,nacell,nbcell,ndip,ns_ant,imin,imax,jmin,jmax,namin,namax,nbmin,nbmax
15 | REAL(dbl) :: ax,ay,az,bx,by,bz
16 | COMPLEX(dbl) :: a1mie=-2.0D0*(0.0D0,1.0D0)/3.0D0
17 | INTEGER(lo), ALLOCATABLE, DIMENSION(:) :: v_jBlock,v_iBlock,v_jBlock_rhs,v_iBlock_rhs,v_jBlock_sca,v_iBlock_sca
18 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:,:) :: m_sAij,m_sBij,m_sAij_sca,m_sBij_sca,m_sAij_rhs,m_sBij_rhs
19 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:) :: v_sT1ij,v_sT2ij,v_sU1ij,v_sU2ij,v_sTUij,v_sAij,v_sBij,v_sAijh,v_sBijh
20 | INTEGER(lo), ALLOCATABLE, DIMENSION(:,:) :: m_jABij,m_iABij,m_jABij_rhs,m_iABij_rhs
21 | INTEGER(lo), ALLOCATABLE, DIMENSION(:) :: v_jABij,v_iABij,v_jABij_template,v_iABij_template,v_jTUij,v_iTUij,v_jDij,v_iDij
22 | REAL(dbl), ALLOCATABLE, DIMENSION(:,:) :: m_Dij,m_Dij_rhs,m_Dij_sca
23 | REAL(dbl), ALLOCATABLE, DIMENSION(:) :: v_sDij
24 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:) :: v_mask
25 | INTEGER(lo), ALLOCATABLE, DIMENSION(:,:) :: m_jDij,m_iDij,m_jDij_rhs,m_iDij_rhs,m_jDij_sca,m_iDij_sca
26 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:) :: v_precond_shell ! Vettore preconditioning codice shell
27 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:,:) :: m_exphi, m_exphi_rhs
28 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:) :: v_exphi
29 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:,:) :: m_a,m_b,m_c,m_d !Matrici coefficienti particella singola
30 | INTEGER(lo), ALLOCATABLE ,DIMENSION(:) :: v_patt !Array per il pattern di uguaglianza
31 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:,:) :: m_AB,m_ABJ,m_AB_swap
32 | REAL(dbl), DIMENSION(-200:200) :: v_oner !Real vector for the 1.0D0 exponential
33 | REAL(dbl), DIMENSION(0:120,0:120) :: m_fact !Real vector for the 1.0D0 exponential
34 | COMPLEX(dbl), DIMENSION(0:400) :: v_ic !Complex vector for the (0.0D0,1.0D0) exponential
35 |
36 | !~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | !Core shell codes shared data
38 | !~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
39 | INTEGER(lo), ALLOCATABLE, DIMENSION(:) :: v_iAB,v_jAB,v_iAABB,v_jAABB,v_iM,v_jM,v_iM_dip,v_jM_dip
40 | COMPLEX(dbl), ALLOCATABLE, DIMENSION(:) :: v_sA,v_sB,v_sAABB,v_sM,v_sM_dip
41 | END MODULE shared_data
42 |
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/setup.py:
--------------------------------------------------------------------------------
1 | from setuptools import setup
2 |
3 | setup(name='py_gmm',
4 | version='0.01',
5 | description='Generalized Multiparticle Mie theory code for plasmonics',
6 | url='http://github.com/gevero/py_gmm',
7 | author='Flying Circus',
8 | author_email='johndoe@johndoe.com',
9 | license='GPLv3',
10 | packages=['py_gmm'],
11 | zip_safe=False)
12 |
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