PyLDT

This tiny library loads LDT files and calculates the photometric distribution. You can extract this distribution as polar plots, pandas Dataframes, or just a matrix or flat array.

Usage

from pyldt import LDT

ldt = LDT.from_file("example.ldt")
other_ldt = LDT.from_raw_data(RAW_DATA)

ldt.compare_to(other_ldt)
#> 65 

ldt == other
#> False

ldt.dist
#> array([[2534.        , 2534.        , 2534.        , ..., 2534.        ,
#>         2534.        , 2534.        ],
#>         [2512.        , 2511.33333333, 2510.66666667, ..., 2507.6       ,
#>         2507.6       , 2507.6       ],
#>         [2490.        , 2488.66666667, 2487.33333333, ..., 2481.2       ,
#>         2481.2       , 2481.2       ],
#>         ...,
#>         [   0.        ,    0.        ,    0.        , ...,    0.        ,
#>         0.        ,    0.        ],
#>         [   0.        ,    0.        ,    0.        , ...,    0.        ,
#>         0.        ,    0.        ],
#>         [   0.        ,    0.        ,    0.        , ...,    0.        ,
#>         0.        ,    0.        ]])

ldt.max
#> 2536.0
ldt.min
#> 0.0

ldt.has_nan
#> False

ldt.as_array
#> array([2534., 2534., 2534., ...,    0.,    0.,    0.])

ldt.as_dataframe
#>  0            1            2       3    ...     357     358     359     360
#>  0    2534.0  2534.000000  2534.000000  2534.0  ...  2534.0  2534.0  2534.0  2534.0
#>  1    2512.0  2511.333333  2510.666667  2510.0  ...  2507.6  2507.6  2507.6  2507.6
#>  2    2490.0  2488.666667  2487.333333  2486.0  ...  2481.2  2481.2  2481.2  2481.2
#>  3    2468.0  2466.000000  2464.000000  2462.0  ...  2454.8  2454.8  2454.8  2454.8
#>  4    2446.0  2443.333333  2440.666667  2438.0  ...  2428.4  2428.4  2428.4  2428.4
#>  ..      ...          ...          ...     ...  ...     ...     ...     ...     ...
#>  176     0.0     0.000000     0.000000     0.0  ...     0.0     0.0     0.0     0.0
#>  177     0.0     0.000000     0.000000     0.0  ...     0.0     0.0     0.0     0.0
#>  178     0.0     0.000000     0.000000     0.0  ...     0.0     0.0     0.0     0.0
#>  179     0.0     0.000000     0.000000     0.0  ...     0.0     0.0     0.0     0.0
#>  180     0.0     0.000000     0.000000     0.0  ...     0.0     0.0     0.0     0.0
#>  [181 rows x 361 columns]

ldt.save_plot()
# Saves the current distribution as polar plot

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.