timecast package¶
Subpackages¶
Module contents¶
timecast: a library for online time series analysis
-
class
timecast.
experiment
(argnames: Union[List[str], str], arglists: List[Any])[source]¶ Bases:
object
Class decorator to run experiments
-
timecast.
tscan
(X: Union[numpy.ndarray, Tuple[numpy.ndarray, ...]], Y: Union[numpy.ndarray, Tuple[numpy.ndarray, ...]], optimizer: flax.optim.base.Optimizer, loss_fn: Callable[[numpy.ndarray, numpy.ndarray], numpy.ndarray] = <function <lambda>>, state: flax.nn.base.Collection = None, objective: Callable[[numpy.ndarray, numpy.ndarray, Callable[[numpy.ndarray, numpy.ndarray], numpy.ndarray], flax.nn.base.Model], Tuple[numpy.ndarray, numpy.ndarray]] = None)[source]¶ Take gradients steps performantly on one data item at a time
- Parameters
X – np.ndarray or tuple of np.ndarray of inputs
Y – np.ndarray or tuple of np.ndarray of outputs
optimizer – initialized optimizer
loss_fn – loss function to compose where first arg is true value and
is pred (second) –
state – state required by flax
objective – function composing loss functions
- Returns
result
- Return type
np.ndarray