Histogram¶
Streaming histogram.
Parameters¶
-
max_bins – defaults to
256Maximal number of bins.
Attributes¶
-
n
Total number of seen values.
Examples¶
>>> from river import utils
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> np.random.seed(42)
>>> values = np.hstack((
... np.random.normal(-3, 1, 1000),
... np.random.normal(3, 1, 1000),
... ))
>>> hist = utils.Histogram(max_bins=60)
>>> for x in values:
... hist = hist.update(x)
>>> ax = plt.bar(
... x=[(b.left + b.right) / 2 for b in hist],
... height=[b.count for b in hist],
... width=[(b.right - b.left) / 2 for b in hist]
... )
.. image:: ../../docs/img/histogram_docstring.svg :align: center
Methods¶
append
S.append(value) -- append value to the end of the sequence
Parameters
- item
cdf
Cumulative distribution function.
Example: >>> from river import utils >>> hist = utils.Histogram() >>> for x in range(4): ... hist = hist.update(x) >>> print(hist) [0.00000, 0.00000]: 1 [1.00000, 1.00000]: 1 [2.00000, 2.00000]: 1 [3.00000, 3.00000]: 1 >>> hist.cdf(-1) 0.0 >>> hist.cdf(0) 0.25 >>> hist.cdf(.5) 0.25 >>> hist.cdf(1) 0.5 >>> hist.cdf(2.5) 0.75 >>> hist.cdf(3.5) 1.0
Parameters
- x
clear
S.clear() -> None -- remove all items from S
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
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
iter_cdf
Yields CDF values for a sorted iterable of values.
This is faster than calling cdf with many values. Example: >>> from river import utils >>> hist = utils.Histogram() >>> for x in range(4): ... hist = hist.update(x) >>> print(hist) [0.00000, 0.00000]: 1 [1.00000, 1.00000]: 1 [2.00000, 2.00000]: 1 [3.00000, 3.00000]: 1 >>> X = [-1, 0, .5, 1, 2.5, 3.5] >>> for x, cdf in zip(X, hist.iter_cdf(X)): ... print(x, cdf) -1 0.0 0 0.25 0.5 0.25 1 0.5 2.5 0.75 3.5 1.0
Parameters
- X
- verbose – defaults to
False
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