import pandas as pd
import itertools

filepath = 'ADR4.dat'

vector = []
col_name = ['u', 'u_e', 'g', 'g_e', 'r', 'r_e', 'i', 'i_e', 'z', 'z_e', 'name']

columns_to_use = [35] + list(range(19, 29))  
data = pd.read_csv(filepath, sep="\\s+", usecols=columns_to_use, header=None, names=col_name)

filtered_data = data.loc[data['name'] != '-']
sorted_data = filtered_data.sort_values(by='name')

merged_99_99 = pd.concat([sorted_data[['u', 'g', 'r', 'i', 'z']] == 99.99, sorted_data['name']], axis=1)
merged_9_99 = pd.concat([sorted_data[['u_e', 'g_e', 'r_e', 'i_e', 'z_e']] == 9.99, sorted_data['name']], axis=1)


counts_99_99 = {}
counts_9_99 = {}

for filter_number in range(2, 6):
    for combination in itertools.combinations(['u', 'g', 'r', 'i', 'z'], filter_number):
        count_true = (merged_99_99[list(combination)] == True).any(axis=1).sum()
        counts_99_99[combination] = len(merged_99_99) - count_true
    for combination in itertools.combinations(['u_e', 'g_e', 'r_e', 'i_e', 'z_e'], filter_number):
        count_true = (merged_9_99[list(combination)] == True).any(axis=1).sum()
        counts_9_99[combination] = len(merged_9_99) - count_true

print(counts_99_99, '\n', counts_9_99)