Exemple #1
0
    return vals


cargs = cli.CommandLine(cli.optsfile('chgpt'))
args = cargs.args

oneday = round(constant.day / constant.minute)
window = nd.Window(args.window_obs, args.window_pred, args.window_trgt)

if args.resume:
    with open(args.resume, mode='rb') as fp:
        observations = pickle.load(fp)
    (measurements, nodes) = data.cleanse(observations)
else:
    db.genop(args.reporting)
    opts = [window, oneday, args.threshold, np.mean]
    with Pool() as pool:
        observations = pool.starmap(f, nd.nodegen(opts))
        observations = list(filter(None, observations))
        assert (observations)

    if args.pickle:
        with open(args.pickle, mode='wb') as fp:
            pickle.dump(observations, fp)

if args.figures:  # and args.verbose:
    aggregate = []
    for i in range(oneday):
        vals = [x[i] for x in observations]
        aggregate.append(np.mean(vals))
Exemple #2
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    vals.append(nid) # this is important
        
    return vals

cargs = cli.CommandLine(cli.optsfile('chgpt'))
args = cargs.args

oneday = round(constant.day / constant.minute)
window = nd.Window(args.window_obs, args.window_pred, args.window_trgt)

if args.resume:
    with open(args.resume, mode='rb') as fp:
        observations = pickle.load(fp)
    (measurements, nodes) = data.cleanse(observations)
else:
    db.genop(args.reporting)
    opts = [ window, oneday, args.threshold, np.mean ]
    with Pool() as pool:
        observations = pool.starmap(f, nd.nodegen(opts))
        observations = list(filter(None, observations))
        assert(observations)

    if args.pickle:
        with open(args.pickle, mode='wb') as fp:
            pickle.dump(observations, fp)
            
if args.figures: # and args.verbose:
    aggregate = []
    for i in range(oneday):
        vals = [ x[i] for x in observations ]
        aggregate.append(np.mean(vals))
Exemple #3
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from lib import db
from lib import cli
from configparser import ConfigParser

cargs = cli.CommandLine(cli.optsfile("prediction"))  # /etc/opts/prediction
args = cargs.args

config = ConfigParser()
config.read(args.config)  # --config

dbinfo = config["database"] if "database" in config else None
db.EstablishCredentials(**dbinfo)

db.genop(int(config["parameters"]["intra-reporting"]))
Exemple #4
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from lib import db
from lib import cli
from configparser import ConfigParser

cargs = cli.CommandLine(cli.optsfile('prediction'))  # /etc/opts/prediction
args = cargs.args

config = ConfigParser()
config.read(args.config)  # --config

dbinfo = config['database'] if 'database' in config else None
db.EstablishCredentials(**dbinfo)

db.genop(int(config['parameters']['intra-reporting']))