DCT#

class pyspark.ml.feature.DCT(*, inverse=False, inputCol=None, outputCol=None)[source]#

A feature transformer that takes the 1D discrete cosine transform of a real vector. No zero padding is performed on the input vector. It returns a real vector of the same length representing the DCT. The return vector is scaled such that the transform matrix is unitary (aka scaled DCT-II).

Added in version 1.6.0.

Notes

More information on Wikipedia.

Examples

>>> from pyspark.ml.linalg import Vectors
>>> df1 = spark.createDataFrame([(Vectors.dense([5.0, 8.0, 6.0]),)], ["vec"])
>>> dct = DCT( )
>>> dct.setInverse(False)
DCT...
>>> dct.setInputCol("vec")
DCT...
>>> dct.setOutputCol("resultVec")
DCT...
>>> df2 = dct.transform(df1)
>>> df2.head().resultVec
DenseVector([10.969..., -0.707..., -2.041...])
>>> df3 = DCT(inverse=True, inputCol="resultVec", outputCol="origVec").transform(df2)
>>> df3.head().origVec
DenseVector([5.0, 8.0, 6.0])
>>> dctPath = temp_path + "/dct"
>>> dct.save(dctPath)
>>> loadedDtc = DCT.load(dctPath)
>>> loadedDtc.transform(df1).take(1) == dct.transform(df1).take(1)
True
>>> loadedDtc.getInverse()
False

Methods

`clear`(param)	Clears a param from the param map if it has been explicitly set.
`copy`([extra])	Creates a copy of this instance with the same uid and some extra params.
`explainParam`(param)	Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.
`explainParams`()	Returns the documentation of all params with their optionally default values and user-supplied values.
`extractParamMap`([extra])	Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.
`getInputCol`()	Gets the value of inputCol or its default value.
`getInverse`()	Gets the value of inverse or its default value.
`getOrDefault`(param)	Gets the value of a param in the user-supplied param map or its default value.
`getOutputCol`()	Gets the value of outputCol or its default value.
`getParam`(paramName)	Gets a param by its name.
`hasDefault`(param)	Checks whether a param has a default value.
`hasParam`(paramName)	Tests whether this instance contains a param with a given (string) name.
`isDefined`(param)	Checks whether a param is explicitly set by user or has a default value.
`isSet`(param)	Checks whether a param is explicitly set by user.
`load`(path)	Reads an ML instance from the input path, a shortcut of read().load(path).
`read`()	Returns an MLReader instance for this class.
`save`(path)	Save this ML instance to the given path, a shortcut of 'write().save(path)'.
`set`(param, value)	Sets a parameter in the embedded param map.
`setInputCol`(value)	Sets the value of `inputCol`.
`setInverse`(value)	Sets the value of `inverse`.
`setOutputCol`(value)	Sets the value of `outputCol`.
`setParams`(self, \*[, inverse, inputCol, ...])	Sets params for this DCT.
`transform`(dataset[, params])	Transforms the input dataset with optional parameters.
`write`()	Returns an MLWriter instance for this ML instance.

Attributes

`inputCol`
`inverse`
`outputCol`
`params`	Returns all params ordered by name.

Methods Documentation

clear(param)#: Clears a param from the param map if it has been explicitly set.

copy(extra=None)#

Creates a copy of this instance with the same uid and some extra params. This implementation first calls Params.copy and then make a copy of the companion Java pipeline component with extra params. So both the Python wrapper and the Java pipeline component get copied.

Parameters:

extradict, optional: Extra parameters to copy to the new instance

Returns:

JavaParams: Copy of this instance

explainParam(param)#: Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.

explainParams()#: Returns the documentation of all params with their optionally default values and user-supplied values.

extractParamMap(extra=None)#

Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.

Parameters:

extradict, optional: extra param values

Returns:

dict: merged param map

getInputCol()#: Gets the value of inputCol or its default value.

getInverse()[source]#: Gets the value of inverse or its default value.

Added in version 1.6.0.

getOrDefault(param)#: Gets the value of a param in the user-supplied param map or its default value. Raises an error if neither is set.

getOutputCol()#: Gets the value of outputCol or its default value.

getParam(paramName)#: Gets a param by its name.

hasDefault(param)#: Checks whether a param has a default value.

hasParam(paramName)#: Tests whether this instance contains a param with a given (string) name.

isDefined(param)#: Checks whether a param is explicitly set by user or has a default value.

isSet(param)#: Checks whether a param is explicitly set by user.

classmethod load(path)#: Reads an ML instance from the input path, a shortcut of read().load(path).

classmethod read()#: Returns an MLReader instance for this class.

save(path)#: Save this ML instance to the given path, a shortcut of ‘write().save(path)’.

set(param, value)#: Sets a parameter in the embedded param map.

setInputCol(value)[source]#: Sets the value of inputCol.

setInverse(value)[source]#: Sets the value of inverse.

Added in version 1.6.0.

setOutputCol(value)[source]#: Sets the value of outputCol.

setParams(self, \*, inverse=False, inputCol=None, outputCol=None)[source]#: Sets params for this DCT.

Added in version 1.6.0.

transform(dataset, params=None)#

Transforms the input dataset with optional parameters.

Added in version 1.3.0.

Parameters:

datasetpyspark.sql.DataFrame: input dataset
paramsdict, optional: an optional param map that overrides embedded params.

Returns:

pyspark.sql.DataFrame: transformed dataset

write()#: Returns an MLWriter instance for this ML instance.

Attributes Documentation

inputCol = Param(parent='undefined', name='inputCol', doc='input column name.')#

inverse = Param(parent='undefined', name='inverse', doc='Set transformer to perform inverse DCT, default False.')#

outputCol = Param(parent='undefined', name='outputCol', doc='output column name.')#

params#: Returns all params ordered by name. The default implementation uses dir() to get all attributes of type Param.

uid#: A unique id for the object.