SASA Database

I don't think this is usable by anyone lese but it's a dependency to sasa_stacker and I wanted to package it separately. An explanation to the whole project can be found here.

Usage

exl_to_sql.py -h:

exl_to_sql.py [-h] [-n SHEET_NUMBER] [-v] [-s] exl db

positional arguments:
  exl                   path to excel-file
  db                    path to sqlite3-db


optional arguments:
  -h, --help            show this help message and exit
  -n SHEET_NUMBER, --sheet-number SHEET_NUMBER
                        which excel-sheet to convert
  -v, --verbose         verbose output
  -s, --skip-existing   skipping rows already contained in the db

Writes the excel file exl into the sqlite database db. Every row in the Excel sheet represents one simulation run of metasurfaces. The problem is with our current setup they are saved as one big .mat file but the sasa_stacker needs to access them and their parameters individually. This script assigns each single metasurface an address and saves its parameters in the db separately. Examples for the formating of the excel sheet can be found in data/NN_smats.xlsx.

Crawler

The Crawler class allows access to the db and loads the simulation data. The main functions are:

find_smat

Crawler.find_smat(name, adress=None)

Loads the simulation data to name. If an adress is provided it only loads this single S-matrix.

Arguments

• name: string, name of the simulation in the database
• adress: list, for example [1,4,5,3] the adress can also be found in the database

find_smat_by_id

Crawler.find_smat_by_id(id)

Same as above but takes the simulation id

Arguments

• id: int, simulation id found in the database

extract_params

Crawler.extract_params(id)

Queries meta_materials.db for all the parameters to the given ID.

Arguments

• id: int, simulation id found in the database

Returns

• param_dict: dict, contains the combined data from the simulations and geometry tables with coresponding names