CDF Class Reference

Inheritance diagram for CDF:

Collaboration diagram for CDF:

Public Member Functions
def	__init__ (self, *args)

Public Attributes
	spline
	Spline, fitting the CDF.

Protected Member Functions
def	_fit (self, x, y=None)
def	_transform (self, x)

Detailed Description

Calculates the cumulative distribution (CDF)
Can be used for the flat transformation.

Attributes
----------
spline : InterpolatedUnivariateSpline
    Spline, fitting the CDF

Definition at line 176 of file transform.py.

Constructor & Destructor Documentation

__init__()

def __init__	(		self,
		*	args
	)

 Init function

:param args: None

Reimplemented from Transform.

Definition at line 189 of file transform.py.

    def __init__(self, *args):
        """ Init function
 
        :param args: None
        """
        Transform.__init__(self, "CDF", *args)
 
        
        self.spline = None
 

Member Function Documentation

_fit()

def _fit (   self,   x,   y = None  )

protected

Fit function calculates the cumulative distribution with numpy percentile.

:param x:   Input distribution
:param y:   Will not be used in this transformation

Reimplemented from Transform.

Definition at line 199 of file transform.py.

    def _fit(self, x, y=None):
        """
        Fit function calculates the cumulative distribution with numpy percentile.
 
        :param x:   Input distribution
        :param y:   Will not be used in this transformation
        """
        self.io.debug("Fitting CDF")
        y_ = np.linspace(0, 100, 2 * self.n_bins)
        x_ = pd.Series(np.percentile(x, list(y_)))
 
        # Count same values
        vc = x_.value_counts()
        vc = vc.sort_index()
 
        # replace same values
        for i, xi in enumerate(vc):
            if xi > 1:
                try:
                    nex_val = vc.index[i + 1]
                except IndexError:
                    nex_val = vc.index[i] + 0.01
                fill = np.linspace(vc.index[i], nex_val, xi)
                x_[x_ == vc.index[i]] = fill
        self.spline = InterpolatedUnivariateSpline(x_, y_)
 

_transform()

def _transform (   self,   x  )

protected

Transforms the input data according to the cdf.
:param x:   Input data
:return:    Transformed data

Reimplemented from Transform.

Definition at line 225 of file transform.py.

    def _transform(self, x):
        """
        Transforms the input data according to the cdf.
        :param x:   Input data
        :return:    Transformed data
        """
        x = self.set_limits(x)
        return self.spline(x)
 
 

Member Data Documentation

spline

spline

Spline, fitting the CDF.

Definition at line 197 of file transform.py.

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The documentation for this class was generated from the following file:

• alignment/scripts/alignment/fancystuff/transform.py