#!/usr/bin/env cached-nix-shell
#!nix-shell -i python3 -p "python3.withPackages(ps: with ps; [ ps.pandas ps.numpy ps.tabulate ])"
import pandas as pd
import numpy as np
import sys
from pprint import pprint
from tabulate import tabulate


def process_raw_line(line):
    fields = line.rstrip().split(" ")
    fields = [field.split(":")[-1] for field in fields]
    fields[5] = fields[5][1:-1]
    fields[0] = int(fields[0])
    fields[1:] = list(map(np.float, fields[1:]))
    return fields


with open(sys.argv[1], "r") as f:
    data = list(map(process_raw_line, f.readlines()))

df = pd.DataFrame(data)
df.columns = ["frame", "Y", "U", "V", "All", "dB"]
df["inv"] = [1 - value for value in df["All"]]

print(f'Mean overall SSIM: {df["All"].mean()}')
print(f'Median overall SSIM: {df["All"].median()}')
print(f'Frame with worst SSIM: {df.idxmin()["All"]+1}')
print(f'Frame with best SSIM: {df.idxmax()["All"]+1}')

print(
    tabulate(
        [
            (key, value * 100)
            for key, value in [
                ["best", df["All"].max()],
                [50, 1 - df["inv"].quantile(0.50)],
                [66.6, 1 - df["inv"].quantile(0.666)],
                [75, 1 - df["inv"].quantile(0.75)],
                [80, 1 - df["inv"].quantile(0.80)],
                [90, 1 - df["inv"].quantile(0.90)],
                [95, 1 - df["inv"].quantile(0.95)],
                [98, 1 - df["inv"].quantile(0.98)],
                [99, 1 - df["inv"].quantile(0.99)],
                [99.9, 1 - df["inv"].quantile(0.999)],
                [100, df["All"].min()],
            ]
        ],
        headers=["% Frames", "≥ SSIM"],
    )
)