Histogram¶
Streaming histogram.
Parameters¶
-
max_bins
Default →
256
Maximal number of bins.
Attributes¶
-
n
Total number of seen values.
Examples¶
from river import sketch
import numpy as np
np.random.seed(42)
values = np.hstack((
np.random.normal(-3, 1, 1000),
np.random.normal(3, 1, 1000),
))
hist = sketch.Histogram(max_bins=15)
for x in values:
hist = hist.update(x)
for bin in hist:
print(bin)
[-6.24127, -6.24127]: 1
[-5.69689, -5.19881]: 8
[-5.12390, -4.43014]: 57
[-4.42475, -3.72574]: 158
[-3.71984, -3.01642]: 262
[-3.01350, -2.50668]: 206
[-2.50329, -0.81020]: 294
[-0.80954, 0.29677]: 19
[0.40896, 0.82733]: 7
[0.84661, 1.25147]: 24
[1.26029, 2.30758]: 178
[2.31081, 3.05701]: 284
[3.05963, 3.69695]: 242
[3.69822, 5.64434]: 258
[6.13775, 6.19311]: 2
Methods¶
append
S.append(value) -- append value to the end of the sequence
Parameters
- item
cdf
Cumulative distribution function.
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.
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