CovMatrix¶
Sample covariance matrix.
Parameters¶
-
ddof – defaults to
1
Delta Degrees of Freedom.
Examples¶
>>> import numpy as np
>>> import pandas as pd
>>> from river import misc
>>> np.random.seed(42)
>>> X = pd.DataFrame(np.random.random((8, 3)), columns=["red", "green", "blue"])
>>> X
red green blue
0 0.374540 0.950714 0.731994
1 0.598658 0.156019 0.155995
2 0.058084 0.866176 0.601115
3 0.708073 0.020584 0.969910
4 0.832443 0.212339 0.181825
5 0.183405 0.304242 0.524756
6 0.431945 0.291229 0.611853
7 0.139494 0.292145 0.366362
>>> cov = misc.CovMatrix()
>>> for x in X.to_dict(orient="records"):
... cov = cov.update(x)
>>> cov
blue green red
blue 0.076 0.020 -0.010
green 0.020 0.113 -0.053
red -0.010 -0.053 0.079
There is also an update_many
method to process mini-batches. The results are identical.
>>> cov = misc.CovMatrix()
>>> cov = cov.update_many(X)
>>> cov
blue green red
blue 0.076 0.020 -0.010
green 0.020 0.113 -0.053
red -0.010 -0.053 0.079
The covariances are stored in a dictionary, meaning any one of them can be accessed as such:
>>> cov["blue", "green"]
Cov: 0.020292
Diagonal entries are variances:
>>> cov["blue", "blue"]
Var: 0.076119
Methods¶
clear
D.clear() -> None. Remove all items from D.
copy
fromkeys
get
D.get(k[,d]) -> D[k] if k in D, else d. d defaults to None.
Parameters
- key
- default – defaults to
None
items
D.items() -> a set-like object providing a view on D's items
keys
D.keys() -> a set-like object providing a view on D's keys
pop
D.pop(k[,d]) -> v, remove specified key and return the corresponding value. If key is not found, d is returned if given, otherwise KeyError is raised.
Parameters
- key
- default – defaults to
<object object at 0x7f019d2a1150>
popitem
D.popitem() -> (k, v), remove and return some (key, value) pair as a 2-tuple; but raise KeyError if D is empty.
setdefault
D.setdefault(k[,d]) -> D.get(k,d), also set D[k]=d if k not in D
Parameters
- key
- default – defaults to
None
update
Update with a single sample.
Parameters
- x (dict)
update_many
Update with many samples.
Parameters
- X (pandas.core.frame.DataFrame)
values
D.values() -> an object providing a view on D's values