def get_minibatch_iterator(seed=8675309,
dataorderseed=0,
nBatch=10,
nObsBatch=None,
nObsTotal=25000,
nLap=1,
startLap=0,
**kwargs):
'''
Args
--------
seed : integer seed for random number generator,
used for actually *generating* the data
dataorderseed : integer seed that determines
(a) how data is divided into minibatches
(b) order these minibatches are traversed
Returns
-------
bnpy MinibatchIterator object, with nObsTotal observations
divided into nBatch batches
'''
X, TrueZ = get_X(seed, nObsTotal)
Data = XData(X=X)
Data.summary = get_data_info()
DataIterator = MinibatchIterator(Data,
nBatch=nBatch,
nObsBatch=nObsBatch,
nLap=nLap,
startLap=startLap,
dataorderseed=dataorderseed)
return DataIterator
def get_data(**kwargs):
'''
Args
-------
filepath
Returns
-------
Data : bnpy XData object, with nObsTotal observations
'''
X = np.loadtxt(filepath, dtype=np.float64)
Data = XData(X=X)
Data.name = get_short_name()
Data.summary = get_data_info()
return Data
def get_data(seed=8675309, nObsTotal=25000, **kwargs):
'''
Args
-------
seed : integer seed for random number generator,
used for actually *generating* the data
nObsTotal : total number of observations for the dataset.
Returns
-------
Data : bnpy XData object, with nObsTotal observations
'''
X, TrueZ = get_X(seed, nObsTotal)
Data = XData(X=X, TrueZ=TrueZ)
Data.summary = get_data_info()
return Data
def get_data(seed=8675309, nObsTotal=25000, **kwargs):
'''
Args
-------
seed : integer seed for random number generator,
used for actually *generating* the data
nObsTotal : total number of observations for the dataset.
Returns
-------
Data : bnpy XData object, with nObsTotal observations
'''
X, TrueZ = get_X(seed, nObsTotal)
Data = XData(X=X, TrueZ=TrueZ)
Data.summary = get_data_info()
return Data
def get_data(seed=8675309, nObsTotal=25000, **kwargs):
''' Create and return toy dataset from 1D standard normal distribution.
Args
-------
seed : integer seed for random number generator,
used for actually *generating* the data
nObsTotal : total number of observations for the dataset.
Returns
-------
Data : bnpy XData object, with nObsTotal observations
'''
X, TrueZ = generate_data(seed, nObsTotal)
Data = XData(X=X, TrueZ=TrueZ)
Data.name = get_short_name()
Data.summary = get_data_info()
return Data
def get_data(seed=8675309, nObsTotal=None, nPerState=20, **kwargs):
'''
Args
-------
seed : integer seed for random number generator,
used for actually *generating* the data
nObsTotal : total number of observations for the dataset.
Returns
-------
Data : bnpy XData object, with nObsTotal observations
'''
if nObsTotal is not None:
nPerState = nObsTotal // K
X, TrueZ = genToyData(seed=seed, nPerState=nPerState)
Data = XData(X=X, TrueZ=TrueZ)
Data.name = get_short_name()
Data.summary = get_data_info()
return Data
def get_minibatch_iterator(seed=8675309, dataorderseed=0, nBatch=10, nObsBatch=None, nObsTotal=25000, nLap=1, startLap=0, **kwargs):
'''
Args
--------
seed : integer seed for random number generator,
used for actually *generating* the data
dataorderseed : integer seed that determines
(a) how data is divided into minibatches
(b) order these minibatches are traversed
Returns
-------
bnpy MinibatchIterator object, with nObsTotal observations
divided into nBatch batches
'''
X, TrueZ = get_X(seed, nObsTotal)
Data = XData(X=X)
Data.summary = get_data_info()
DataIterator = MinibatchIterator(Data, nBatch=nBatch, nObsBatch=nObsBatch, nLap=nLap, startLap=startLap, dataorderseed=dataorderseed)
return DataIterator
def get_data(seed=8675309, nObsTotal=25000, **kwargs):
X, TrueZ = generateData(seed, nObsTotal)
Data = XData(X=X, TrueZ=TrueZ)
Data.name = get_short_name()
Data.summary = get_data_info()
return Data
def get_data(seed=8675309, nObsTotal=25000, **kwargs): X, TrueZ = generateData( seed, nObsTotal) Data = XData(X=X, TrueZ=TrueZ) Data.summary = get_data_info() return Data
