make_slots.py

import os
import pandas as pd
import numpy as np


def match_armor_s1(s):
    return s.str.match('Attack|Accuracy|Rng\.Atk\.|Rng\.Acc\.|Mag\.Atk\.Bns\.|Mag\. Acc\.')

def match_armor_s3(s):
    return s.str.match('STR|DEX|VIT|AGI|INT|MND|CHR')

def match_armor_s4(s):
    return s.str.match('Accuracy|Rng\.Acc\.|Mag\. Acc\.')

def match_armor_s5(s):
    return s.str.match('Attack|Rng\.Atk\.|Mag\.Atk\.Bns\.')

def match_armor_s2(s):
    return ~s.str.match('none') & ~match_armor_s1(s) & ~match_armor_s3(s)

def item_is_armor(s):
    return s.str.match('Herculean|Merlinic|Odyssean|Valorous|Chironic')

def match_slots(df, subspace, predicates):
    for augment in range(1, 6):
        s = subspace & ~subspace
        for slot in range(augment, 6):
            r = subspace & predicates[slot - 1](df['augment %d' % augment])
            m, s = r & ~s, r | s
            df.loc[m, ('slot %d' % slot)] = df.loc[m, ('augment %d' % augment)]
            df.loc[m, ('slot %d potency' % slot)] = df.loc[m, ('augment %d potency' % augment)]

def match_armor_slots(df):
    predicates = [
        match_armor_s1,
        match_armor_s2,
        match_armor_s3,
        match_armor_s4,
        match_armor_s5,
    ]
    for stone in ['pellucid', 'fern', 'taupe']:
        subspace = df.stone == stone
        match_slots(df, subspace, predicates)

if __name__ == "__main__":
    df = pd.read_csv('merged.csv')
    for slot in range(1, 6):
        df['slot %d' % slot] = 'none'
        df['slot %d potency' % slot] = 0
    match_armor_slots(df)
    columns = [
        'timestamp',
        'name',
        'stone',
        'path',
    ]
    valid = item_is_armor(df.name) & ~(df.stone == 'dark matter')
    for slot in range(1, 6):
        columns.extend(['slot %d' % slot, 'slot %d potency' % slot])
    df[valid].to_csv("slots.csv", index=False, columns=columns)