RiiDataFrame¶

Here, a little bit more detail about RiiDataFrame class will be given.

[1]:

import riip
ri = riip.RiiDataFrame()

RiiDataFrame has an attribute named catalog that is a Pandas DataFrame provinding the catalog of experimental data as shown below. The columns formula and tabulated indicate the type of data. If n or k is included in the column tamulated, the experimentally observed refractive index n or extinction coefficient k is given in tabulated form, respectively. If tabulated is f, only coefficients of formula are given. On the other hand, the number written in the column formula indicates the number of dispetsion formula that fits the experimental data. If the number is 0, only the tabulated data are given.

[2]:

ri.catalog.head(3)

[2]:

	shelf	shelf_name	division	book	book_name	section	page	path	formula	tabulated	num_n	num_k	wl_n_min	wl_n_max	wl_k_min	wl_k_max	wl_min	wl_max
id
0	main	MAIN - simple inorganic materials	Ag - Silver	Ag	Ag (Silver)	Experimental data: bulk, thick film	Johnson	/home/mnishida/anaconda3/envs/pymwm/lib/python...	0	nk	49	49	0.1879	1.937	0.1879	1.937	0.1879	1.937
1	main	MAIN - simple inorganic materials	Ag - Silver	Ag	Ag (Silver)	Experimental data: bulk, thick film	Choi	/home/mnishida/anaconda3/envs/pymwm/lib/python...	0	nk	84	84	1.2310	6.988	1.2310	6.988	1.2310	6.988
2	main	MAIN - simple inorganic materials	Ag - Silver	Ag	Ag (Silver)	Experimental data: bulk, thick film	Jiang	/home/mnishida/anaconda3/envs/pymwm/lib/python...	0	nk	1701	1701	0.3000	2.000	0.3000	2.000	0.3000	2.000

The experimental data are given by raw_data:

[3]:

ri.raw_data.loc[3].head(5)  # first 5 rows for the material whose id is 3

[3]:

	c	wl_n	n	wl_k	k
id
3	0.0	0.27	1.364	0.27	1.3180
3	0.0	0.28	1.477	0.28	1.2400
3	0.0	0.29	1.531	0.29	1.1680
3	0.0	0.30	1.609	0.30	0.9126
3	0.0	0.31	1.373	0.31	0.5192

where n is the refractive index and k is the extinction coefficient at the vacuum wavelength wl_n (wl_k) in the unit of μm. The column c gives the coefficients for the dielectric function model.

In the above example, no coefficient is given because only the tabulated data are given (formula number in catalog is 0). On the other hand, if formula number is not 0, some coefficeints are given in the column c as shown below. In this case, formula 21 means Drude-Lorentz model, which is explained in Dispersion formulas.

[4]:

ri.catalog.tail(3)

[4]:

	shelf	shelf_name	division	book	book_name	page	path	formula	tabulated	num_n	num_k	wl_n_min	wl_n_max	wl_k_min	wl_k_max	wl_min	wl_max
id
2909	BB-f22	BB - formula 22: Brendel-Bormann model	Pt - Platinum	Pt	Pt (Platinum)	Rakic-BBF	/home/mnishida/anaconda3/envs/pymwm/lib/python...	22	f	0	0	0.2066	12.4	0.2066	12.4	0.2066	12.4
2910	BB-f22	BB - formula 22: Brendel-Bormann model	Ti - Titanium	Ti	Ti (Titanium)	Rakic-BBF	/home/mnishida/anaconda3/envs/pymwm/lib/python...	22	f	0	0	0.2066	12.4	0.2066	12.4	0.2066	12.4
2911	BB-f22	BB - formula 22: Brendel-Bormann model	W - Tungsten	W	W (Tungsten)	Rakic-BBF	/home/mnishida/anaconda3/envs/pymwm/lib/python...	22	f	0	0	0.2066	12.4	0.2066	12.4	0.2066	12.4

[5]:

ri.raw_data.loc[2911].head(5)  # first 5 rows for the material whose id is 2912

[5]:

	c	wl_n	n	wl_k	k
id
2911	1.000	0.0	0.0	0.0	0.0
2911	0.197	0.0	0.0	0.0	0.0
2911	0.057	0.0	0.0	0.0	0.0
2911	13.220	0.0	0.0	0.0	0.0
2911	0.006	0.0	0.0	0.0	0.0

Using the method load_grid_data(), you can get grid data calculated at 200 wavelength values in the range [wl_min, wl_max], which is the intersection between the domain of n [wl_n_min, wl_n_max] and the domain of k [wl_k_min, wl_k_max]. These values are shown in catalog.

[6]:

grid_data = ri.load_grid_data(3)
grid_data

[6]:

	wl	n	k
id
3	0.270000	1.364000	1.318000
3	0.393869	0.059405	2.019307
3	0.517739	0.052095	3.214604
3	0.641608	0.059819	4.218402
3	0.765477	0.074195	5.168274
...	...	...	...
3	24.424523	48.244988	149.066993
3	24.548392	48.628523	149.645128
3	24.672261	49.013717	150.226267
3	24.796131	49.400800	150.811020
3	24.920000	49.790000	151.400000

200 rows × 3 columns

Helper Methods¶

By using the functionality of Pandas, you may find what you want, easily. But, here some simple helper methods are implemented.

plot¶

plot(id: int, comp: str = "n", fmt1: Optional[str] = "-", fmt2: Optional[str] = "--", **kwargs)

id (int): ID number.
comp (str): ‘n’, ‘k’ or ‘eps’.
fmt1 (Union[str, None]): Plot format for n and Re(eps).
fmt2 (Union[str, None]): Plot format for k and Im(eps).

Plot refractive index (if set comp=”n”), extinction coefficient (comp=”k”) or permittivity (comp=”eps”).

[7]:

import matplotlib.pyplot as plt
ri.plot(3, "n")
plt.show()
ri.plot(3, "k")
plt.show()
ri.plot(3, "eps")
plt.show()

../_images/notebooks_02_RiiDataFrame_13_0.png

../_images/notebooks_02_RiiDataFrame_13_1.png

../_images/notebooks_02_RiiDataFrame_13_2.png

search¶

search(name: str) -> DataFrame

This method searches data whose book or book_name contain given name and return a simplified catalog for them.

[8]:

ri.search("NaCl")

[8]:

	book	page	formula	tabulated	wl_min	wl_max
id
182	NaCl	Li	1	f	0.20	30.0000
183	NaCl	Querry	0	nk	0.22	166.6667

[9]:

ri.search("sodium") # upper or lower case is not significant

[9]:

	book	section	page	formula	tabulated	wl_min	wl_max
id
127	NaBr		Li	1	f	0.210000	34.000000
182	NaCl		Li	1	f	0.200000	30.000000
183	NaCl		Querry	0	nk	0.220000	166.666700
229	NaF		Li	1	f	0.150000	17.000000
295	NaI		Jellison	1	f	0.436000	0.633000
296	NaI		Li	1	f	0.250000	40.000000
376	Na	Solid	Smith	0	nk	0.312539	2.237982
377	Na	Solid	Inagaki	0	nk	0.326000	2.066000
378	Na	Solid	Monin	0	nk	0.253600	0.620000
379	Na	Solid	Yamaguchi	0	nk	0.200000	0.600000
380	Na	Solid	Althoff	0	nk	2.250000	10.150000
381	Na	Solid	Ives	0	nk	0.253600	0.578000
382	Na	Liquid	Inagaki-liquid	0	nk	0.335000	2.000000

select¶

select(condition: str) -> DataFrame

This method make a query with the given condition and return a simplified catalog. It will pick up materials whose experimental data contains some data that fulfill given condition.

[10]:

ri.select("2.5 < n < 3 and 0.4 < wl < 0.8").head(10)

[10]:

	book	section	page	formula	tabulated	wl_min	wl_max
id
23	Al	Experimental data	Mathewson	0	nk	0.495940	1.771200
118	Bi	Experimental data	Hagemann	0	nk	0.000002	6.199000
129	TlBr		Palik	1	f	0.570000	39.400000
135	C	Amorphous thin film	Larruquert	0	nk	0.019656	10.079189
137	C	Graphite	Djurisic-o	0	nk	0.030996	10.332000
146	C	Highly oriented pyrolytic graphite (HOPG)	Song-cHOPG-o	0	nk	0.193000	1.690000
150	C	Graphene	Weber	0	nk	0.210873	0.999007
151	C	Graphene	El-Sayed	0	nk	0.240000	1.000000
152	C	Graphene	Song	0	nk	0.193000	1.690000
157	SiC	6H-SiC (α-SiC) crystal	Singh-o	2	f	0.488000	1.064000

[11]:

ri.plot(157)

../_images/notebooks_02_RiiDataFrame_19_0.png

show¶

show(id: int | Sequence[int]) -> DataFrame

This method shows a simplified catalog for given id.

[12]:

ri.show(1)

[12]:

book                                          Ag
section      Experimental data: bulk, thick film
page                                        Choi
formula                                        0
tabulated                                     nk
wl_min                                     1.231
wl_max                                     6.988
Name: 1, dtype: object

read¶

read(id, as_dict=False)

This method returns the contants of a page associated with the id. If you want the page contents as a python dict, give True for argument as_dict.

[13]:

print(ri.read(0))

# this file is part of refractiveindex.info database
# refractiveindex.info database is in the public domain
# copyright and related rights waived via CC0 1.0

REFERENCES: "P. B. Johnson and R. W. Christy. Optical constants of the noble metals, <a href=\"https://doi.org/10.1103/PhysRevB.6.4370\"><i>Phys. Rev. B</i> <b>6</b>, 4370-4379 (1972)</a>"
COMMENTS: "Room temperature"
DATA:
  - type: tabulated nk
    data: |
        0.1879 1.07 1.212
        0.1916 1.10 1.232
        0.1953 1.12 1.255
        0.1993 1.14 1.277
        0.2033 1.15 1.296
        0.2073 1.18 1.312
        0.2119 1.20 1.325
        0.2164 1.22 1.336
        0.2214 1.25 1.342
        0.2262 1.26 1.344
        0.2313 1.28 1.357
        0.2371 1.28 1.367
        0.2426 1.30 1.378
        0.2490 1.31 1.389
        0.2551 1.33 1.393
        0.2616 1.35 1.387
        0.2689 1.38 1.372
        0.2761 1.41 1.331
        0.2844 1.41 1.264
        0.2924 1.39 1.161
        0.3009 1.34 0.964
        0.3107 1.13 0.616
        0.3204 0.81 0.392
        0.3315 0.17 0.829
        0.3425 0.14 1.142
        0.3542 0.10 1.419
        0.3679 0.07 1.657
        0.3815 0.05 1.864
        0.3974 0.05 2.070
        0.4133 0.05 2.275
        0.4305 0.04 2.462
        0.4509 0.04 2.657
        0.4714 0.05 2.869
        0.4959 0.05 3.093
        0.5209 0.05 3.324
        0.5486 0.06 3.586
        0.5821 0.05 3.858
        0.6168 0.06 4.152
        0.6595 0.05 4.483
        0.7045 0.04 4.838
        0.7560 0.03 5.242
        0.8211 0.04 5.727
        0.8920 0.04 6.312
        0.9840 0.04 6.992
        1.0880 0.04 7.795
        1.2160 0.09 8.828
        1.3930 0.13 10.10
        1.6100 0.15 11.85
        1.9370 0.24 14.08

[14]:

ri.read(0, as_dict=True)

[14]:

{'REFERENCES': 'P. B. Johnson and R. W. Christy. Optical constants of the noble metals, <a href="https://doi.org/10.1103/PhysRevB.6.4370"><i>Phys. Rev. B</i> <b>6</b>, 4370-4379 (1972)</a>',
 'COMMENTS': 'Room temperature',
 'DATA': [{'type': 'tabulated nk',
   'data': '0.1879 1.07 1.212\n0.1916 1.10 1.232\n0.1953 1.12 1.255\n0.1993 1.14 1.277\n0.2033 1.15 1.296\n0.2073 1.18 1.312\n0.2119 1.20 1.325\n0.2164 1.22 1.336\n0.2214 1.25 1.342\n0.2262 1.26 1.344\n0.2313 1.28 1.357\n0.2371 1.28 1.367\n0.2426 1.30 1.378\n0.2490 1.31 1.389\n0.2551 1.33 1.393\n0.2616 1.35 1.387\n0.2689 1.38 1.372\n0.2761 1.41 1.331\n0.2844 1.41 1.264\n0.2924 1.39 1.161\n0.3009 1.34 0.964\n0.3107 1.13 0.616\n0.3204 0.81 0.392\n0.3315 0.17 0.829\n0.3425 0.14 1.142\n0.3542 0.10 1.419\n0.3679 0.07 1.657\n0.3815 0.05 1.864\n0.3974 0.05 2.070\n0.4133 0.05 2.275\n0.4305 0.04 2.462\n0.4509 0.04 2.657\n0.4714 0.05 2.869\n0.4959 0.05 3.093\n0.5209 0.05 3.324\n0.5486 0.06 3.586\n0.5821 0.05 3.858\n0.6168 0.06 4.152\n0.6595 0.05 4.483\n0.7045 0.04 4.838\n0.7560 0.03 5.242\n0.8211 0.04 5.727\n0.8920 0.04 6.312\n0.9840 0.04 6.992\n1.0880 0.04 7.795\n1.2160 0.09 8.828\n1.3930 0.13 10.10\n1.6100 0.15 11.85\n1.9370 0.24 14.08\n'}]}

references¶

references(id: int)

This method returns the REFERENCES of a page associated with the id.

[15]:

ri.references(20)

[15]:

1) J. I. Larruquert, J. A. Méndez, J. A. Aznárez. Optical constants of aluminum films in the extreme ultraviolet interval of 82-77 nm, Appl. Opt. 35, 5692-5697 (1996)
2) J. I. Larruquert, J. A. Méndez, J. A. Aznárez. Far-ultraviolet reflectance measurements and optical constants of unoxidized aluminum films, Appl. Opt. 34, 4892-4899 (1995)

material¶

material(params: dict) -> Material

Create Material-class instance for given parameter dict params.

params can includes the following parameters, * ‘id’: ID number. (int) * ‘book’: book value in catalog of RiiDataFrame. (str) * ‘page’: page value in catalog of RiiDataFrame. (str) * ‘RI’: Constant refractive index. (complex) * ‘e’: Constant permittivity. (complex) * ‘bound_check’: True if bound check should be done. Defaults to True. (bool) * ‘im_factor’: A magnification factor multiplied to the imaginary part of permittivity. Defaults to 1.0. (float)

[16]:

water = ri.material({'id': 428})
water.catalog

[16]:

shelf                                                      main
shelf_name                    MAIN - simple inorganic materials
division                                  O - Oxygen and oxides
book                                                        H2O
book_name     H<sub>2</sub>O, D<sub>2</sub>O (Water, heavy w...
section                                       Liquid water, H2O
page                                                  Kedenburg
path          /home/mnishida/anaconda3/envs/pymwm/lib/python...
formula                                                       2
tabulated                                                     k
num_n                                                         0
num_k                                                      1131
wl_n_min                                                    0.5
wl_n_max                                                    1.6
wl_k_min                                                    0.5
wl_k_max                                                    1.6
wl_min                                                      0.5
wl_max                                                      1.6
Name: 428, dtype: object

[ ]: