def __init__(self,
store=None,
data=None,
train_index=None,
prep_index=None):
"""
**Args**
store: An instance of `store.Store` or a path. If a path
Ramp will default to an `HDFPickleStore` at that path
if PyTables is installed, a `PickleStore` otherwise.
Defaults to MemoryStore.
data: a pandas DataFrame. If all data has been precomputed this
may not be required.
train_index: a pandas Index specifying the data instances to be
used in training. Stored results will be cached against this.
If not provided, the entire index of `data` will be used.
prep_index: a pandas Index specifying the data instances to be
used in prepping ("x" values). Stored results will be cached against this.
If not provided, the entire index of `data` will be used.
"""
if store is None:
self.store = MemoryStore()
else:
self.store = store if isinstance(store,
Store) else default_store(store)
self.data = data
self.train_index = train_index if train_index is not None else self.data.index if self.data is not None else None
self.prep_index = prep_index if prep_index is not None else self.data.index if self.data is not None else None
def __init__(self,
store=None,
data=None,
train_index=None,
prep_index=None,
train_once=False):
"""
Parameters:
-----------
store: string or ramp.store.Store object, default None
An instance of `ramp.store.Store` or a path. If a path, Ramp will
default to an `HDFPickleStore` at that path if PyTables is
installed, a `PickleStore` otherwise. Defaults to MemoryStore.
data: Pandas DataFrame, default None
Dataframe of data. If all data has been precomputed this
may not be required.
train_index: Pandas DataFrame Index, default None
Pandas Index specifying the data instances to be used in training.
Stored results will be cached against this.If not provided, the
entire index of the 'data' parameter will be used.
prep_index: Pandas DataFrame Index, default None
Pandas Index specifying the data instances to be
used in prepping ("x" values). Stored results will be cached
against this. If not provided, the entire index of `data`
keyword arg will be used.
train_once: boolean
If True, train and predict indexes will not be used as part of key
hashes, meaning the values from the first run with this context
will be stored permanently.
"""
if store is None:
self.store = MemoryStore()
else:
self.store = (store if isinstance(store, Store) else
default_store(store))
self.data = data
if train_index is not None:
self.train_index = train_index
elif self.data is not None:
self.train_index = self.data.index
else:
self.train_index = None
if prep_index is not None:
self.prep_index = prep_index
elif self.data is not None:
self.prep_index = self.data.index
else:
self.prep_index = None
self.train_once = train_once
def __init__(self, store=None, data=None, train_index=None,
prep_index=None, train_once=False):
"""
Parameters:
-----------
store: string or ramp.store.Store object, default None
An instance of `ramp.store.Store` or a path. If a path, Ramp will
default to an `HDFPickleStore` at that path if PyTables is
installed, a `PickleStore` otherwise. Defaults to MemoryStore.
data: Pandas DataFrame, default None
Dataframe of data. If all data has been precomputed this
may not be required.
train_index: Pandas DataFrame Index, default None
Pandas Index specifying the data instances to be used in training.
Stored results will be cached against this.If not provided, the
entire index of the 'data' parameter will be used.
prep_index: Pandas DataFrame Index, default None
Pandas Index specifying the data instances to be
used in prepping ("x" values). Stored results will be cached
against this. If not provided, the entire index of `data`
keyword arg will be used.
train_once: boolean
If True, train and predict indexes will not be used as part of key
hashes, meaning the values from the first run with this context
will be stored permanently.
"""
if store is None:
self.store = MemoryStore()
else:
self.store = (store if isinstance(store, Store)
else default_store(store))
self.data = data
if train_index is not None:
self.train_index = train_index
elif self.data is not None:
self.train_index = self.data.index
else:
self.train_index = None
if prep_index is not None:
self.prep_index = prep_index
elif self.data is not None:
self.prep_index = self.data.index
else:
self.prep_index = None
self.train_once = train_once
def __init__(self, store, data=None, train_index=None, prep_index=None):
"""
**Args**
store: An instance of `store.Store` or a path. If a path
Ramp will default to an `HDFPickleStore` at that path
if PyTables is installed, a `PickleStore` otherwise.
data: a pandas DataFrame. If all data has been precomputed this
may not be required.
train_index: a pandas Index specifying the data instances to be
used in training. Stored results will be cached against this.
If not provided, the entire index of `data` will be used.
prep_index: a pandas Index specifying the data instances to be
used in prepping ("x" values). Stored results will be cached against this.
If not provided, the entire index of `data` will be used.
"""
self.store = store if isinstance(store, Store) else default_store(store)
self.data = data
self.train_index = train_index if train_index is not None else self.data.index if self.data is not None else None
self.prep_index = prep_index if prep_index is not None else self.data.index if self.data is not None else None
