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Removing direct dispy import from hyperparam modules

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Petrônio Cândido 2020-01-27 14:54:38 -03:00
parent 783a77ec0f
commit 6a1ee719b7
3 changed files with 12 additions and 5 deletions
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6
pyFTS/hyperparam/Evolutionary.py
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@ -8,7 +8,6 @@ import math
import time import time
from functools import reduce from functools import reduce
from operator import itemgetter from operator import itemgetter
import dispy
import random import random
from pyFTS.common import Util from pyFTS.common import Util
@ -17,7 +16,7 @@ from pyFTS.partitioners import Grid, Entropy # , Huarng
from pyFTS.common import Membership from pyFTS.common import Membership
from pyFTS.models import hofts, ifts, pwfts from pyFTS.models import hofts, ifts, pwfts
from pyFTS.hyperparam import Util as hUtil from pyFTS.hyperparam import Util as hUtil
from pyFTS.distributed import dispy as dUtil
__measures = ['f1', 'f2', 'rmse', 'size'] __measures = ['f1', 'f2', 'rmse', 'size']
@ -415,6 +414,8 @@ def GeneticAlgorithm(dataset, **kwargs):
for key in __measures: for key in __measures:
individual[key] = ret[key] individual[key] = ret[key]
elif distributed=='dispy': elif distributed=='dispy':
from pyFTS.distributed import dispy as dUtil
import dispy
jobs = [] jobs = []
for ct, individual in enumerate(population): for ct, individual in enumerate(population):
job = cluster.submit(dataset, individual, **kwargs) job = cluster.submit(dataset, individual, **kwargs)
@ -602,6 +603,7 @@ def execute(datasetname, dataset, **kwargs):
shortname = str(fts_method.__module__).split('.')[-1] shortname = str(fts_method.__module__).split('.')[-1]
if distributed == 'dispy': if distributed == 'dispy':
from pyFTS.distributed import dispy as dUtil
nodes = kwargs.get('nodes', ['127.0.0.1']) nodes = kwargs.get('nodes', ['127.0.0.1'])
cluster, http_server = dUtil.start_dispy_cluster(evaluate, nodes=nodes) cluster, http_server = dUtil.start_dispy_cluster(evaluate, nodes=nodes)
kwargs['cluster'] = cluster kwargs['cluster'] = cluster

7
pyFTS/hyperparam/GridSearch.py
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@ -4,8 +4,7 @@ from pyFTS.models import hofts
from pyFTS.partitioners import Grid, Entropy from pyFTS.partitioners import Grid, Entropy
from pyFTS.benchmarks import Measures from pyFTS.benchmarks import Measures
from pyFTS.hyperparam import Util as hUtil from pyFTS.hyperparam import Util as hUtil
from pyFTS.distributed import dispy as dUtil
import dispy
import numpy as np import numpy as np
from itertools import product from itertools import product
@ -73,6 +72,8 @@ def cluster_method(individual, dataset, **kwargs):
def process_jobs(jobs, datasetname, conn): def process_jobs(jobs, datasetname, conn):
from pyFTS.distributed import dispy as dUtil
import dispy
for ct, job in enumerate(jobs): for ct, job in enumerate(jobs):
print("Processing job {}".format(ct)) print("Processing job {}".format(ct))
result = job() result = job()
@ -98,6 +99,8 @@ def process_jobs(jobs, datasetname, conn):
def execute(hyperparams, datasetname, dataset, **kwargs): def execute(hyperparams, datasetname, dataset, **kwargs):
from pyFTS.distributed import dispy as dUtil
import dispy
nodes = kwargs.get('nodes',['127.0.0.1']) nodes = kwargs.get('nodes',['127.0.0.1'])

4
pyFTS/hyperparam/mvfts.py
View File

@ -28,7 +28,7 @@ from pyFTS.partitioners import Grid, Entropy # , Huarng
from pyFTS.common import Membership from pyFTS.common import Membership
from pyFTS.models import hofts, ifts, pwfts from pyFTS.models import hofts, ifts, pwfts
from pyFTS.hyperparam import Util as hUtil from pyFTS.hyperparam import Util as hUtil
from pyFTS.distributed import dispy as dUtil
from pyFTS.hyperparam import Evolutionary, random_search as RS from pyFTS.hyperparam import Evolutionary, random_search as RS
from pyFTS.models.multivariate import mvfts, wmvfts, variable from pyFTS.models.multivariate import mvfts, wmvfts, variable
from pyFTS.models.seasonal import partitioner as seasonal from pyFTS.models.seasonal import partitioner as seasonal
@ -458,6 +458,8 @@ def execute(datasetname, dataset, **kwargs):
kwargs['random_individual'] = random_genotype kwargs['random_individual'] = random_genotype
if distributed == 'dispy': if distributed == 'dispy':
from pyFTS.distributed import dispy as dUtil
import dispy
nodes = kwargs.get('nodes', ['127.0.0.1']) nodes = kwargs.get('nodes', ['127.0.0.1'])
cluster, http_server = dUtil.start_dispy_cluster(evaluate, nodes=nodes) cluster, http_server = dUtil.start_dispy_cluster(evaluate, nodes=nodes)
kwargs['cluster'] = cluster kwargs['cluster'] = cluster