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#!/usr/bin/env python3

import argparse
import os
import subprocess
import json
import numpy as np
import scipy.stats as st

samples = 5


def coalg_file(states, monoid, symbols, zero_frequency, i):
    return "bench/wta_%s_%s_%s_%s_%d" % (monoid, symbols, zero_frequency,
                                         states, i)


def generate(args):
    generator = args.generator
    states = args.states
    monoid = args.monoid
    symbols = args.symbols
    zero_frequency = args.zero_frequency

    os.makedirs("bench", exist_ok=True)

    for i in range(0, samples):
        f = coalg_file(states, monoid, symbols, zero_frequency,
                       i) + ".coalgebra"

        if os.path.exists(f):
            continue

        cmd = [
            generator, "--states", states, "--monoid", monoid, "--symbols",
            symbols, "--zero-frequency", zero_frequency
        ]
        subprocess.run(cmd, stdout=open(f, "w+"))


def run_one(args, i):
    copar = args.copar
    states = args.states
    monoid = args.monoid
    symbols = args.symbols
    zero_frequency = args.zero_frequency

    f = coalg_file(states, monoid, symbols, zero_frequency, i) + ".coalgebra"

    copar_args = [copar, 'refine', '--stats-json', f]

    out = subprocess.run(
        copar_args,
        stdout=subprocess.DEVNULL,
        stderr=subprocess.PIPE,
        check=True)

    stats = json.loads(out.stderr.decode('utf-8'))

    stats['monoid'] = monoid
    stats['symbols'] = symbols
    stats['zero-freq'] = zero_frequency
    stats['i'] = i

    return stats


def run_one_simple(args, i):
    copar = args.copar
    states = args.states
    monoid = args.monoid
    symbols = args.symbols
    zero_frequency = args.zero_frequency

    f = coalg_file(states, monoid, symbols, zero_frequency, i) + ".coalgebra"

    copar_args = [copar, 'refine', f]

    subprocess.run(
        copar_args,
        stdout=subprocess.DEVNULL,
        check=True)


def confidence(vals):
    """Compute the 95% confidence intervall (CI) for the mean with the student
distribution.

Returns a tuple of (mean, lower, upper), where lower and upper are the bounds
of the CI"""

    # For a larger sample size (> 30), we could also use the normal
    # distribution.
    #
    # This code is taken from
    # https://stackoverflow.com/questions/15033511/compute-a-confidence-interval-from-sample-data/34474255#34474255

    mean = np.mean(vals)
    ci = st.t.interval(
        0.95, len(vals) - 1, loc=np.mean(vals), scale=st.sem(vals))

    return (mean, ci[0], ci[1])


def stddev(vals):
    """Compute the mean and standard deviation intervall on a sample.

This uses the corrected sample standard deviation."""

    # see also:
    # https://en.wikipedia.org/wiki/Standard_deviation#Corrected_sample_standard_deviation
    mean = np.mean(vals)
    std = np.std(vals, ddof=1)

    return (mean, std)


def print_row(d, header, stddev):
    keys = [
        'i', 'states', 'edges', 'initial-partition-size',
        'final-partition-size', 'explicit-final-partition-size',
        'size1-skipped'
    ]

    for k in [
            'overall-duration', 'parse-duration', 'algorithm-duration',
            'initialize-duration', 'refine-duration'
    ]:
        keys.append(k)
        if stddev:
            keys.append(k + '-stddev')

    values = [d[k] for k in keys]

    if header:
        print('\t'.join(keys))
    else:
        print('\t'.join(str(x) for x in values))


def run(args):
    results = [run_one(args, i) for i in range(0, samples)]

    def confidencekey(vals, k):
        return confidence(list(float(x[k]) for x in vals))

    def stddevkey(vals, k):
        return stddev(list(float(x[k]) for x in vals))

    combined = results[0].copy()
    combined['i'] = samples

    for k in [
            'overall-duration', 'parse-duration', 'initialize-duration',
            'refine-duration', 'algorithm-duration'
    ]:
        ci = stddevkey(results, k)
        combined[k] = str(ci[0])
        combined[k + '-stddev'] = str(ci[1])

    if args.indiv:
        if args.header:
            print_row(combined, True, stddev=False)
        for res in results:
            print_row(res, False, stddev=False)
    else:
        if args.header:
            print_row(combined, True, stddev=args.stddev)
        print_row(combined, False, stddev=args.stddev)


def test(args, states):
    print("Trying %d..." % states)

    args.states = str(states)
    generate(args)

    for i in range(0, samples):
        try:
            run_one_simple(args, i)
        except subprocess.CalledProcessError:
            return False

    return True


def find_bad(args, good):
    states = good*2

    if test(args, states):
        return find_bad(args, states)
    else:
        return (good, states)


def bisect_states(args):
    states = args.start_states

    good = args.good or 0
    bad = args.bad

    if bad is None:
        if good and states < good:
            states = good+1

        if test(args, states):
            (good, bad) = find_bad(args, states)
        else:
            bad = states

    while good+1 < bad:
        states = good + (bad-good)//2
        if test(args, states):
            good = states
        else:
            bad = states

    print("First bad state count: %d" % bad)


def main():
    parser = argparse.ArgumentParser()
    subparsers = parser.add_subparsers(required=True)

    gen_parser = subparsers.add_parser('generate')
    gen_parser.add_argument('generator')
    gen_parser.add_argument('--states', required=True)
    gen_parser.add_argument('--monoid', required=True)
    gen_parser.add_argument('--symbols', required=True)
    gen_parser.add_argument('--zero-frequency', required=True)
    gen_parser.set_defaults(func=generate)

    run_parser = subparsers.add_parser('run')
    run_parser.add_argument('copar')
    run_parser.add_argument('--states', required=True)
    run_parser.add_argument('--monoid', required=True)
    run_parser.add_argument('--symbols', required=True)
    run_parser.add_argument('--zero-frequency', required=True)
    run_parser.add_argument(
        '--stddev', action='store_true', help="report stddev for timings")
    run_parser.add_argument(
        '--indiv', action='store_true', help="report individual samples")
    run_parser.add_argument(
        '--header', action='store_true', help="Print header row for table")
    run_parser.set_defaults(func=run)

    bisect_parser = subparsers.add_parser('bisect')
    bisect_parser.add_argument('generator')
    bisect_parser.add_argument('copar')
    bisect_parser.add_argument('--monoid', required=True)
    bisect_parser.add_argument('--symbols', required=True)
    bisect_parser.add_argument('--zero-frequency', required=True)
    bisect_parser.add_argument('--start-states', type=int, default=50)
    bisect_parser.add_argument('--good', type=int)
    bisect_parser.add_argument('--bad', type=int)

    bisect_parser.set_defaults(func=bisect_states)

    args = parser.parse_args()
    args.func(args)


if __name__ == "__main__":
    main()