Exemple #1
0
#!/usr/bin/env python3

import random
from psweep import psweep as ps


def func(pset):
    return {'result': random.random() * pset['a']}


if __name__ == '__main__':
    params = ps.seq2dicts('a', [1, 2, 3, 4])
    df = ps.run(func, params)
    print(df)
#!/usr/bin/env python3

import random
import multiprocessing as mp
from psweep import psweep as ps


def func(pset):
    print(mp.current_process().name)
    return {'result': random.random() * pset['a']}


if __name__ == '__main__':
    params = ps.seq2dicts('a', [1, 2, 3, 4, 5, 6, 7, 8])
    df = ps.run(func, params, poolsize=2)
    print(df)
#!/usr/bin/env python3

import random
from itertools import product
from psweep import psweep as ps

def func(pset):
    return {'result': random.random() * pset['a']}

if __name__ == '__main__':
    params = ps.loops2params(product(ps.seq2dicts('a', [1,2,3,4]),
                                     [{'study': 'a'}]))
    df = ps.run(func, params)
    print(df)
    return {'result': random.random() * pset['a'] * pset['b']}


if __name__ == '__main__':

    print("first run")

    const = {'a': 11111, 'b': 55555}

    params = []
    disp_cols = []

    values = dict(a=[1, 2, 3], b=[66, 77])

    for study, seq in values.items():
        # [{'a': 1}, {'a': 2}, {'a': 3}]
        # [{'b': 66}, {'b': 77}]
        params_1d = ps.seq2dicts(study, seq)
        this_params = ps.loops2params(product(params_1d, [{'study': study}]))
        this_params = [ps.merge_dicts(const, dct) for dct in this_params]
        params += this_params
        disp_cols.append(study)

    disp_cols += ['_run_id']
    df = ps.run(func,
                params,
                backup_script=__file__,
                backup_calc_dir=True,
                verbose=disp_cols)
    print(df[disp_cols + ['result']])
Exemple #5
0
#!/usr/bin/env python3

import random
from itertools import product
from psweep import psweep as ps


def func(pset):
    return {'result': random.random() * pset['a'] * pset['b']}


if __name__ == '__main__':
    params = ps.loops2params(product(
            ps.seq2dicts('a', [1,2,3,4]),
            ps.seq2dicts('b', [8,9]),
            ))
    # First run.
    df = ps.run(func, params)

    # Second run. 
    params = ps.loops2params(product(
            ps.seq2dicts('a', [11,22,33,44]),
            ps.seq2dicts('b', [88,99]),
            ))
    df = ps.run(func, params)
    print(df)
Exemple #6
0
#!/usr/bin/env python3

import random
from itertools import product
from psweep import psweep as ps


def func(pset):
    return {'result': random.random() * pset['a'] * pset['b']}


if __name__ == '__main__':
    sel = ['_calc_dir', 'a', 'b', 'result']

    # 1st real run: produce some data, vary a, b constant
    params = ps.loops2params(
        product(ps.seq2dicts('a', [1, 2, 3, 4]), ps.seq2dicts('b', [100])))
    df = ps.run(func, params)
    print(df[sel])

    # simulate run: check if new parameter grid is OK
    params = ps.loops2params(
        product(ps.seq2dicts('a', [5, 6]), ps.seq2dicts('b', [88, 99])))
    df = ps.run(func, params, simulate=True)
    print(df[sel])

    # looks good, 2nd real run with new params
    df = ps.run(func, params)
    print(df[sel])
 {'a': 4, 'const': 'const', 'b': 2.0}]
"""

import timeit, os
from itertools import product
from subprocess import run
from psweep import psweep as ps
        

def func(pset):
    
    cmd_tmpl = """
        echo "calling func: pset: a={a} b={b} const={const}"; 
        sleep $(echo "0.1 * {a} / {b}" | bc -l)
        """
    cmd = cmd_tmpl.format(**pset)
    timing = min(timeit.repeat(lambda: run(cmd, shell=True),
                               repeat=3,
                               number=1))
    return {'timing': timing}
            
                
if __name__ == '__main__':
    results = 'results.json'
    params = ps.loops2params(product(
            ps.seq2dicts('a', [1,2,3,4]),
            ps.seq2dicts('b', [1.0,2.0]),
            ps.seq2dicts('const', ['const']),
            ))
    df = ps.run(func, params)