Esempi in Python per load_from_dir

Esempio n. 1

args = parser.parse_args()

############################################################################
# Read config file
############################################################################
paramhelper = parameterhelper.ParameterHelper(args.optconfig)
optconfig = paramhelper._optimization

############################################################################
# Load data
############################################################################
print("Loading data (%s)" % args.data)
# If the data is stored in a directory, load the data from there. Otherwise,
# load from the single file and split it.
if os.path.isdir(args.data):
    Xtr, Ytr, Xval, Yval, _, _ = esnet.load_from_dir(args.data)

else:
    X, Y = esnet.load_from_text(args.data)

    # Construct training/test sets
    Xtr, Ytr, Xval, Yval, _, _ = esnet.generate_datasets(X, Y)

############################################################################
# Initialization of the genetic algorithm
############################################################################
# Fitness and individual. Different formats, depending on dimensionality reduction.
if paramhelper._fixed_values['embedding'] == 'identity':
    creator.create("FitnessMin", base.Fitness,
                   weights=(-1.0, ))  # -1.0 => minimize function
else:

Esempio n. 2

File: esn_experiment.py Progetto: minhdeal/MultivariateESN

# Read config file
############################################################################
config = json.load(open(args.esnconfig + '.json', 'r'))
reconstructconfig = json.load(open(args.reconstructconfig + '.json', 'r'))

############################################################################
# Load data
############################################################################
# If the data is stored in a directory, load the data from there. Otherwise,
# load from the single file and split it.

allPredictions = []
dataType = args.data.split('/')[-1]

if os.path.isdir(args.data):
    Xtr, Ytr, _, _, Xte, Yte, Yscaler = esnet.load_from_dir(args.data)

elif dataType=='SantaFe' or dataType=='Sunspots' or dataType=='Hongik' \
        or dataType=='GEFC' or dataType=='Mackey' or dataType=='SP500' \
        or dataType=='Rainfall' or dataType=='Temperature' \
        or dataType == 'MinTempMel' or dataType == 'SunSpotsZu'\
        or dataType == 'TempAlbuquerque' or dataType == 'TempDenver' or dataType == 'TempLasVegas' \
        or dataType == 'TempLosAngeles' or dataType == 'TempPhoenix' or dataType == 'TempPortland' \
        or dataType == 'TempSanDiego' or dataType == 'TempSanFrancisco' or dataType == 'TempSeattle' \
        or dataType == 'TempVancouver' \
        or dataType == 'eleGB2015_7_12' or dataType == 'eleDE2015_7_12' or dataType == 'eleFR2015_7_12'\
        or dataType == 'Electric':
    #Xtr, Ytr, _, _, Xte, Yte, Yscaler = esnet.generate_datasets_santafe(args.data)
    X, Y = esnet.load_from_text(args.data)

    # Construct training/test sets

Esempio n. 3

File: genoptesn.py Progetto: minhdeal/MultivariateESN

############################################################################
# Read reconstructconfig file
############################################################################
reconstructconfig = json.load(open(args.reconstructconfig + '.json', 'r'))

############################################################################
# Load data
############################################################################
logger.info("Loading data (%s)"%args.data)
# If the data is stored in a directory, load the data from there. Otherwise,
# load from the single file and split it.
dataType = args.data.split('/')[-1]

if os.path.isdir(args.data):
    Xtr, Ytr, Xval, Yval, _, _, Yscaler = esnet.load_from_dir(args.data, reconstructconfig)

elif dataType=='SantaFe' or dataType=='Sunspots' or dataType=='Hongik' \
        or dataType=='GEFC' or dataType=='Mackey' or dataType=='SP500' \
        or dataType == 'Rainfall' or dataType=='Temperature'\
        or dataType=='MinTempMel' or dataType=='SunSpotsZu' \
        or dataType == 'TempAlbuquerque' or dataType == 'TempDenver' or dataType=='TempLasVegas' \
        or dataType == 'TempLosAngeles' or dataType == 'TempPhoenix' or dataType == 'TempPortland' \
        or dataType == 'TempSanDiego' or dataType == 'TempSanFrancisco' or dataType == 'TempSeattle'\
        or dataType == 'TempVancouver' \
        or dataType == 'eleGB2015_7_12' or dataType == 'eleDE2015_7_12' or dataType == 'eleFR2015_7_12' \
        or dataType == 'Electric':
    #Xtr, Ytr, Xval, Yval, _, _, Yscaler = esnet.generate_datasets_santafe(args.data)
    X, Y = esnet.load_from_text(args.data)

    # Construct training/test sets