Python Model Examples

Example #1

File: run_direct.py Project: kokukuma/nupic_binary_option

def binary_option():
    from nupic.frameworks.opf.model import Model

    # inputFilePath = "./datasets/usdjpy_2001_01_ohlc.csv"
    # inputFilePath = "./datasets/usdjpy_2001_ohlc.csv"
    # inputFilePath = "./datasets/usdjpy_2001_2005_ohlc.csv"
    inputFilePath = "./datasets/usdjpy_2006_2007.csv"

    # predict_mode: disableLearning and dont save the model
    predict_mode = True

    if os.path.exists("./learned_model_direct"):
        print "read learned_model"
        low_model = Model.load("./learned_model_direct/low/")
        if predict_mode:
            low_model.disableLearning()
        else:
            low_model.enableLearning()

    else:
        print "create model ..."
        low_model = createModel("high_low")

    print "run Model ..."
    low_model = runModel(inputFilePath, low_model)

    if not predict_mode:
        print "pickle dump ..."
        low_model.save(os.path.abspath("./learned_model_direct/low/"))

Example #2

File: run.py Project: gotham29/zaychik_proj1

def runModel(file_list, plot=False):
  for file1 in file_list:
    save = False
    file_name = os.path.splitext(file1)[0]
    path = '/home/sheiser1/nupic-master/examples/opf/clients/hotgym/prediction/one_gym/' + file_name
    model = None
    if os.path.exists(path):
      model = Model.load(path)
    else:
      model = createModel(getModelParamsFromName(GYM_NAME))
      save = True
      
    print "Creating model from %s..." % file_name
    inputData = "%s/%s.csv" % (DATA_DIR, file_name.replace(" ", "_"))
    runIoThroughNupic(inputData, model, file_name, plot)
    if save:
      model.save(path)

    for file2 in file_list:
      file2_name = os.path.splitext(file2)[0]
      model.disableLearning()    
      print "Running model" + file_name + 'on' + file2_name 
      inputData = "%s/%s.csv" % (DATA_DIR, file2_name.replace(" ", "_"))
      runIoThroughNupic(inputData, model, file2_name, plot)
      os.rename(file2_name+'_out.csv',file_name + '_'+file2_name + '_out.csv')  

Example #3

File: run.py Project: kokukuma/nupic_binary_option

def binary_option():
    from nupic.frameworks.opf.model import Model
    #inputFilePath = "./datasets/usdjpy_2001_01_ohlc.csv"
    #inputFilePath = "./datasets/usdjpy_2001_ohlc.csv"
    #inputFilePath = "./datasets/usdjpy_2001_2005_ohlc.csv"
    inputFilePath = "./datasets/usdjpy_2006_2007.csv"

    # TODO: 学習したモデルの保存ができてない.
    if os.path.exists('./learned_model'):
        print 'loading model ...'
        #high_model = Model.load('./learned_model/high/')
        low_model  = Model.load('./learned_model/low/')
    else:
        print 'create model ...'
        #high_model = createModel("high")
        low_model  = createModel("low")

    high_model = createModel("high")

    print 'run Model ...'
    runModel(inputFilePath, high_model, low_model, True)

Example #4

File: loadandworkwith.py Project: salexashenko/The-Jinglinator

__author__ = 'sergeyalexashenko'
#This file loads a model and generates a jingle based on a list of notes to begin it with
from music21 import *
from nupic.frameworks.opf.model import Model
ABSOLUTE_PATH_TO_MODEL='/Users/sergeyalexashenko/pycharm/bachify/savedmodel3/'
model=Model.load(ABSOLUTE_PATH_TO_MODEL)
model.resetSequenceStates()
s = stream.Stream()
list_of_notes=['e4','c5','a4','a4']

for everynote in list_of_notes:
    modelInput = {"note": everynote}
    result = model.run(modelInput)
    localnote=note.Note(everynote)
    localnote.duration.type = 'quarter'
    s.append(localnote)
inference = result.inferences['multiStepBestPredictions']
i=1
#If you want more than 50 note predictions - change model_params.py to add more steps
while i<51:
    prediction=inference[i]
    print prediction
    localnote=note.Note(prediction)
    localnote.duration.type = 'quarter'
    s.append(localnote)
    i=i+1
s.show()