iynorm module

class DMT.extraction.iynorm.IYNorm(y_values)[source]

Bases: object

This abstract class defines an interface for different y_values normalization strategies to be used by XStep objects.

Parameters:

y_valuesnp.array(): This array shall contain the y_values to be normalized.

Methods

normalize()

Return an array that contains normalized y_values according to different Sub-class implementations.

abstract normalize(values)[source]

This abstract method must be overwritten by subclasses.

Parameters:

valuesnp.ndarray(): The y-array that shall be normalized.

Returns:

valuesnp.ndarray(): The normalized data.

class DMT.extraction.iynorm.IYNormDefault(y_values)[source]

Bases: IYNorm

This subclass normalizes the y_values so that they lie between 0 and 1.

normalize(values)[source]

This abstract method must be overwritten by subclasses.

Parameters:

valuesnp.ndarray(): The y-array that shall be normalized.

Returns:

valuesnp.ndarray(): The normalized data.

class DMT.extraction.iynorm.IYNormFactor(y_values)[source]

Bases: IYNorm

This subclass normalizes the y_values using a constant factor that is multiplied to the data. The factor is equal to the minimum of the init values.

normalize(values)[source]

This abstract method must be overwritten by subclasses.

Parameters:

valuesnp.ndarray(): The y-array that shall be normalized.

Returns:

valuesnp.ndarray(): The normalized data.

class DMT.extraction.iynorm.IYNormLog(y_values)[source]

Bases: IYNorm

This subclass normalizes the y_values using np.log10. If somehow a nan value occurs, it is set to 1e9.

normalize(values)[source]

This abstract method must be overwritten by subclasses.

Parameters:

valuesnp.ndarray(): The y-array that shall be normalized.

Returns:

valuesnp.ndarray(): The normalized data.

class DMT.extraction.iynorm.IYNormLogOneRange(y_values)[source]

Bases: IYNorm

This subclass normalizes the y_values using np.log10(values’), where values’ corresponds to the values normalized between 0 and 1. If somehow a nan value occurs, it is set to 1e9.

normalize(values)[source]

This abstract method must be overwritten by subclasses.

Parameters:

valuesnp.ndarray(): The y-array that shall be normalized.

Returns:

valuesnp.ndarray(): The normalized data.

class DMT.extraction.iynorm.IYNormLog_1(y_values)[source]

Bases: IYNorm

This subclass normalizes the y_values using np.log10(1+values). If somehow a nan value occurs, it is set to 1e9.

normalize(values)[source]

This abstract method must be overwritten by subclasses.

Parameters:

valuesnp.ndarray(): The y-array that shall be normalized.

Returns:

valuesnp.ndarray(): The normalized data.

class DMT.extraction.iynorm.IYNormNone(y_values)[source]

Bases: IYNorm

This subclass performs no normalization at all.

normalize(values)[source]

This abstract method must be overwritten by subclasses.

Parameters:

valuesnp.ndarray(): The y-array that shall be normalized.

Returns:

valuesnp.ndarray(): The normalized data.