tensortrade.feed.api.float.window.rolling module

rolling.py contains functions and classes for rolling stream operations.

class tensortrade.feed.api.float.window.rolling.Rolling(*args, **kwargs)

Bases: Stream[List[float]]

A stream that generates a rolling window of values from a stream.

Parameters:

• window (int) – The size of the rolling window.

• min_periods (int, default 1) – The number of periods to wait before producing values from the aggregation function.

agg(func: Callable[[List[float]], float]) → Stream[float]

Computes an aggregation of a rolling window of values.

Parameters:

func (Callable[[List[float]], float]) – A aggregation function.

Returns:

Stream[float] – A stream producing aggregations of a rolling window of values.

count() → Stream[float]

Computes a rolling count from the underlying stream.

Returns:

Stream[float] – A rolling count stream.

forward() → List[float]

Generates the next value from the underlying data streams.

Returns:

T – The next value in the stream.

generic_name: str = 'rolling'

has_next() → bool

Checks if there is another value.

Returns:

bool – If there is another value or not.

max() → Stream[float]

Computes a rolling maximum from the underlying stream.

Returns:

Stream[float] – A rolling maximum stream.

mean() → Stream[float]

Computes a rolling mean from the underlying stream.

Returns:

Stream[float] – A rolling mean stream.

median() → Stream[float]

Computes a rolling median from the underlying stream.

Returns:

Stream[float] – A rolling median stream.

min() → Stream[float]

Computes a rolling minimum from the underlying stream.

Returns:

Stream[float] – A rolling minimum stream.

reset() → None

Resets all inputs to and listeners of the stream and sets stream value to None.

std() → Stream[float]

Computes a rolling standard deviation from the underlying stream.

Returns:

Stream[float] – A rolling standard deviation stream.

sum() → Stream[float]

Computes a rolling sum from the underlying stream.

Returns:

Stream[float] – A rolling sum stream.

var() → Stream[float]

Computes a rolling variance from the underlying stream.

Returns:

Stream[float] – A rolling variance stream.

class tensortrade.feed.api.float.window.rolling.RollingCount(*args, **kwargs)

Bases: RollingNode

A stream operator that counts the number of non-missing values in the rolling window.

forward()

Generates the next value from the underlying data streams.

Returns:

T – The next value in the stream.

class tensortrade.feed.api.float.window.rolling.RollingNode(*args, **kwargs)

Bases: Stream[float]

A stream operator for aggregating a rolling window of a stream.

Parameters:

func (Callable[[List[float]], float]) – A function that aggregates a rolling window.

forward() → float

Generates the next value from the underlying data streams.

Returns:

T – The next value in the stream.

has_next() → bool

Checks if there is another value.

Returns:

bool – If there is another value or not.

reset() → None

Resets all inputs to and listeners of the stream and sets stream value to None.

tensortrade.feed.api.float.window.rolling.rolling(s: Stream[float], window: int, min_periods: int = 1) → Stream[List[float]]

Creates a stream that generates a rolling window of values from a stream.

Parameters:

• s (Stream[float]) – A float stream.

• window (int) – The size of the rolling window.

• min_periods (int, default 1) – The number of periods to wait before producing values from the aggregation function.