Pyrho Validation - Check re-gridded periodic data

# Validation data for "A representation-independent electronic charge density database for crystalline materials" Each directory is named after the `task_id` field from the following query to the Materials Project database: ```python from pymatgen.ext.matproj import MPRester with MPRester() as m: q_res = m.query( criteria={ "nelements": 1, "e_above_hull": {"$lt": 0.1}, "nsites": {"$lt": 20}, "e_above_hull": {"$lt": 0.00001}, }, properties=["energy", "structure", "e_above_hull", "task_id", "exp"], ) ``` There are 117 directories in all. Each directory contains the `POSCAR` file of the unit cell, the `CHGCAR`'s of the unit cell and two different supercells: ```python sc1 = uc * [ [1, 1, 0], [1, -1, 0], [0, 0, 1], ] sc2 = uc * [ [2, 0, 0], [0, 2, 0], [0, 0, 2], ] ``` and the output of the validation analysis `validate_sc.json` which should look like this: ```json { "sc1": { "1": 0.0002730357775883091, "2": 6.913892646285771e-05, "4": 1.7710165019594026e-05 }, "sc2": { "1": 0.0002667279377434944, "2": 6.911585183768033e-05, "4": 2.6712034073784627e-05 }, "formula": "H2" } ``` The output of the validation analysis is created using the `validate_sc.py` script, which calculates the average of the difference between the re-gridded and explicitly calculated charge densities. The differences are stored in units of electrons/Angstrom^3 for each supercell and up-sampling factors 1/2/4. Once the JSON files are in place, the plot from the paper can be generated using the `plot.py` script.