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How to use _make_stats method in pytest-benchmark

Best Python code snippet using pytest-benchmark

calc_interene.py

Source:calc_interene.py

...6import argparse7import numpy as np8from sgenlib import pdb9from sgenlib import parsing10def _make_stats(data) :11    mean = data.mean()12    std = data.std()/np.sqrt(data.shape[0])13    nhalf = int(0.5*data.shape[0])14    drift = np.abs(data[:nhalf].mean() - data[nhalf:].mean())15    return "%.3f\t%.3f\t%.3f"%(mean, std, drift),[mean, std, drift]16if __name__ == '__main__' :17  # Command-line input18  parser = argparse.ArgumentParser(description="Calculate ligand-protein interaction energies")19  parser.add_argument('files',nargs="+",help="the Gromacs xvg-files")20  parser.add_argument('-o','--out',help="the output file")21  parser.add_argument('-p','--pdb',help="the protein",default=[])22  parser.add_argument('-r','--repeats', help="repeat replacement", default=["r1_", "r2_", "r3_", "r4_", "r5_", "r6_", "r8_", "r9_", "r10_"])23  args = parser.parse_args()24residues = ["CU", "CL"]25for res in pdb.PDBFile(args.pdb).residues[:235] :26    residues.append("%s%d"%(res.resname.capitalize(),res.serial))27all_data = None28for ri, replacement in enumerate(args.repeats):29    r_data = []30    if ri == 0 :31        outname = args.out32    else:33        outname = args.out.replace(args.repeats[0], replacement)34    with open(outname, "w") as f :35        if ri == 0 :36            files = args.files37        else :38            files = [file.replace(args.repeats[0], replacement) for file in args.files]39        for file in files :40            data = parsing.parse2ndarray(file)41            (nrows, nitems) = data.shape42            for i in range(1, nitems, 2):43                ele_str, ele = _make_stats(data[:, i])44                vdw_str, vdw = _make_stats(data[:, i+1])45                tot_str, tot = _make_stats(data[:, i] + data[:, i+1])46                ele.extend(vdw)47                ele.extend(tot)48                r_data.append(ele)49                f.write("%s\t%s\t%s\t%s\n"%(residues[i-1], ele_str, vdw_str, tot_str))50        if ri == 0 :51            r_data = np.asarray(r_data)52            nrow, ncol = r_data.shape53            all_data = np.zeros([len(args.repeats), nrow, ncol])54            all_data[0, :, : ] = r_data55        else :56            all_data[ri, :, : ] = np.asarray(r_data)57with open(args.out.replace(args.repeats[0], "all_"), "w") as f :58    mean_data = all_data.mean(axis=0)59    for i in range(0, 7, 3):...

test_performance.py

Source:test_performance.py

...14    telegraf_server, telegraf_client = telegraf_server_client15    telegraf_client.sender._batch_size = batch_size16    rounds = 1017    loops = 99918    stats_session = custom_benchmark._make_stats(iterations=1)19    for _ in range(rounds):20        await _runner(telegraf_client, loops=loops, stats_session=stats_session)21        await asyncio.sleep(0.1)  # flush buffers22@pytest.mark.parametrize('batch_size', [0, 50, 200, 500, 1000])23async def test_perf_multiple_workers(custom_benchmark, telegraf_server_client, batch_size):24    telegraf_server, telegraf_client = telegraf_server_client25    telegraf_client.sender._batch_size = batch_size26    rounds = 1027    workers = 1028    stats_session = custom_benchmark._make_stats(iterations=1)29    for round_num in range(rounds):30        tasks = [_runner(telegraf_client, loops=99, stats_session=stats_session) for _ in range(workers)]31        await asyncio.gather(*tasks)32        await asyncio.sleep(0.2)  # flush buffers33async def _runner(telegraf_client, loops, stats_session):34    started_at = timer()35    for i in range(loops):36        telegraf_client.timing('perf.timer', 0.003, tags=['name:marlin', 'flow:custom'])37        await asyncio.sleep(0.0)...

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