RollingMin¶

Running min over a window.

Parameters¶

window_size (int)

Size of the rolling window.

Attributes¶

name
size
window_size

Examples¶

>>> from river import stats

>>> X = [1, -4, 3, -2, 2, 1]
>>> rolling_min = stats.RollingMin(2)
>>> for x in X:
...     print(rolling_min.update(x).get())
1
-4
-4
-2
-2
1

Methods¶

append

S.append(value) -- append value to the end of the sequence

Parameters

x

clear

S.clear() -> None -- remove all items from S

clone

Return a fresh estimator with the same parameters.

The clone has the same parameters but has not been updated with any data. This works by looking at the parameters from the class signature. Each parameter is either - recursively cloned if it's a River classes. - deep-copied via copy.deepcopy if not. If the calling object is stochastic (i.e. it accepts a seed parameter) and has not been seeded, then the clone will not be idempotent. Indeed, this method's purpose if simply to return a new instance with the same input parameters.

copy

count

S.count(value) -> integer -- return number of occurrences of value

Parameters

item

extend

S.extend(iterable) -- extend sequence by appending elements from the iterable

Parameters

other

get

Return the current value of the statistic.

index

S.index(value, [start, [stop]]) -> integer -- return first index of value. Raises ValueError if the value is not present.

Supporting start and stop arguments is optional, but recommended.

Parameters

item
args

insert

S.insert(index, value) -- insert value before index

Parameters

i
item

pop

S.pop([index]) -> item -- remove and return item at index (default last). Raise IndexError if list is empty or index is out of range.

Parameters

i – defaults to -1

remove

S.remove(value) -- remove first occurrence of value. Raise ValueError if the value is not present.

Parameters

item

reverse

S.reverse() -- reverse IN PLACE

revert

Revert and return the called instance.

Parameters

x

sort

update

Update and return the called instance.

Parameters

x