Package pygeodesy :: Module fstats :: Class Fcook

Class Fcook

  object --+        
           |        
named._Named --+    
               |    
      _StatsBase --+
                   |
                  Fcook

Cook's RunningStats computing the running kurtosis, mean, skewness, (sample) variance, standard deviation and Jarque-Bera normality.

See Also: Fwelford.

Instance Methods

__init__(self, xs=(), name='')
New Fcook accumulator.

__add__(self, other)
Sum of this and a scalar, an Fsum or an other instance.

__iadd__(self, other)
Add a scalar, an Fsum or an other instance to this instance.

__radd__(self, other)
Not implemented.

fadd(self, xs, sample=False)
Accumulate and return the current count.

fcopy(self, deep=False, name='')
Copy this instance, shallow or deep.

copy(self, deep=False, name='')
Copy this instance, shallow or deep.

fjb(self, xs=(), sample=True, excess=True)
Accumulate and compute the current Jarque-Bera normality.

fjb_(self, *xs, **excess_sample)
Accumulate and compute the current Jarque-Bera normality.

fkurtosis(self, xs=(), sample=False, excess=True)
Accumulate and return the current kurtosis.

fkurtosis_(self, *xs, **excess_sample)
Accumulate and return the current kurtosis.

fmean(self, xs=())
Accumulate and return the current mean.

fmedian(self, xs=())
Accumulate and return the current median.

fmedian_(self, *xs)
Accumulate and return the current median.

fskewness(self, xs=(), sample=False)
Accumulate and return the current skewness.

fskewness_(self, *xs, **sample)
Accumulate and return the current skewness.

fstdev(self, xs=(), sample=False)
Accumulate and return the current standard deviation.

fvariance(self, xs=(), sample=False)
Accumulate and return the current variance.

Inherited from _StatsBase: __len__, fadd_, fmean_, fstdev_, fvariance_

Inherited from named._Named: _DOT_, __imatmul__, __matmul__, __repr__, __rmatmul__, __str__, attrs, classof, dup, rename, toRepr, toStr, toStr2

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __subclasshook__

Properties

Inherited from named._Named: classname, classnaming, name, named, named2, named3, named4

Inherited from object: __class__

Method Details

init (self, xs=`()`, name='')
(Constructor)

New Fcook accumulator.

Arguments:

xs - Iterable with initial values (Scalars).
name - Optional name (str).

Overrides: object.__init__

See Also: Method Fcook.fadd.

add (self, other)
(Addition operator)

Sum of this and a scalar, an Fsum or an other instance.

Arguments:

other - Fcook instance or a Scalar.

Returns:

The sum (Fcook).

See Also: Methods Fcook.__iadd__ and Fcook.fadd.

iadd (self, other)

Add a scalar, an Fsum or an other instance to this instance.

Arguments:

other - Fcook instance or a Scalar.

Returns:

This instance, updated (Fcook).

Raises:

TypeError - Invalid other type.

See Also: Method Fcook.fadd.

fadd (self, xs, sample=False)

Accumulate and return the current count.

Arguments:

xs - Iterable with additional values (Scalars).
sample - Return the sample instead of the full population value (bool).

Returns:

Current, running count (float).

Raises:

OverflowError - Partial 2sum overflow.
TypeError - Non-scalar xs value.
ValueError - Invalid or non-finite xs value.

Note: Scalar means an Fsum instance or scalar.

fcopy (self, deep=False, name='')

Copy this instance, shallow or deep.

Arguments:

deep - If True make a deep, otherwise a shallow copy (bool).
name - Optional, non-empty name (str).

Returns:

The copy (Fwelford).

copy (self, deep=False, name='')

Copy this instance, shallow or deep.

Arguments:

deep - If True make a deep, otherwise a shallow copy (bool).
name - Optional, non-empty name (str).

Returns:

The copy (Fwelford).

Overrides: named._Named.copy

fjb (self, xs=`()`, sample=True, excess=True)

Accumulate and compute the current Jarque-Bera normality.

Arguments:

xs - Iterable with additional values (Scalars).
sample - Return the sample value (bool), default.
excess - Return the excess kurtosis (bool), default.

Returns:

Current, running Jarque-Bera normality (float).

See Also: Method Fcook.fadd.

fjb_ (self, *xs, **excess_sample)

Accumulate and compute the current Jarque-Bera normality.

See Also: Method Fcook.fjb.

fkurtosis (self, xs=`()`, sample=False, excess=True)

Accumulate and return the current kurtosis.

Arguments:

xs - Iterable with additional values (Scalars).
sample - Return the sample instead of the full population value (bool).
excess - Return the excess kurtosis (bool), default.

Returns:

Current, running kurtosis or excess kurtosis (float).

See Also:: Kurtosis Formula and Mantalos., Method Fcook.fadd.

fkurtosis_ (self, *xs, **excess_sample)

Accumulate and return the current kurtosis.

See Also: Method Fcook.fkurtosis.

fmean (self, xs=`()`)

Accumulate and return the current mean.

Arguments:

xs - Iterable with additional values (Scalars).

Returns:

Current, running mean (float).

See Also: Method Fcook.fadd.

fmedian (self, xs=`()`)

Accumulate and return the current median.

Arguments:

xs - Iterable with additional values (Scalars).

Returns:

Current, running median (float).

See Also:: Pearson's Skewness Coefficients and Skewness & Kurtosis Simplified https://TowardsDataScience.com/skewness-kurtosis-simplified-1338e094fc85>., Method Fcook.fadd.

fmedian_ (self, *xs)

Accumulate and return the current median.

See Also: Method Fcook.fmedian.

fskewness (self, xs=`()`, sample=False)

Accumulate and return the current skewness.

Arguments:

xs - Iterable with additional values (Scalars).
sample - Return the sample instead of the full population value (bool).

Returns:

Current, running skewness (float).

See Also:: Skewness Formula and Mantalos., Method Fcook.fadd.

fskewness_ (self, *xs, **sample)

Accumulate and return the current skewness.

See Also: Method Fcook.fskewness.

fstdev (self, xs=`()`, sample=False)

Accumulate and return the current standard deviation.

Arguments:

xs - Iterable with additional values (Scalars).
sample - Return the sample instead of the full population value (bool).

Returns:

Current, running standard deviation (float).

See Also: Method Fcook.fadd.

fvariance (self, xs=`()`, sample=False)

Accumulate and return the current variance.

Arguments:

xs - Iterable with additional values (Scalars).
sample - Return the sample instead of the full population value (bool).

Returns:

Current, running variance (float).

See Also: Method Fcook.fadd.

Class Fcook

__init__ (self, xs=(), name='') (Constructor)

__add__ (self, other) (Addition operator)

__iadd__ (self, other)

fadd (self, xs, sample=False)

fcopy (self, deep=False, name='')

copy (self, deep=False, name='')

fjb (self, xs=(), sample=True, excess=True)

fjb_ (self, *xs, **excess_sample)

fkurtosis (self, xs=(), sample=False, excess=True)

fkurtosis_ (self, *xs, **excess_sample)

fmean (self, xs=())

fmedian (self, xs=())

fmedian_ (self, *xs)

fskewness (self, xs=(), sample=False)

fskewness_ (self, *xs, **sample)

fstdev (self, xs=(), sample=False)

fvariance (self, xs=(), sample=False)

init (self, xs=`()`, name='')
(Constructor)

add (self, other)
(Addition operator)

iadd (self, other)

fjb (self, xs=`()`, sample=True, excess=True)

fkurtosis (self, xs=`()`, sample=False, excess=True)

fmean (self, xs=`()`)

fmedian (self, xs=`()`)

fskewness (self, xs=`()`, sample=False)

fstdev (self, xs=`()`, sample=False)

fvariance (self, xs=`()`, sample=False)