DCT¶
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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).
New 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.
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.
Gets the value of inputCol or its default value.
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.
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
Returns all params ordered by name.
Methods Documentation
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clear(param)¶ Clears a param from the param map if it has been explicitly set.
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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
JavaParamsCopy of this instance
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explainParam(param)¶ Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.
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explainParams()¶ Returns the documentation of all params with their optionally default values and user-supplied values.
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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
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getInputCol()¶ Gets the value of inputCol or its default value.
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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.
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getOutputCol()¶ Gets the value of outputCol or its default value.
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getParam(paramName)¶ Gets a param by its name.
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hasDefault(param)¶ Checks whether a param has a default value.
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hasParam(paramName)¶ Tests whether this instance contains a param with a given (string) name.
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isDefined(param)¶ Checks whether a param is explicitly set by user or has a default value.
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isSet(param)¶ Checks whether a param is explicitly set by user.
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classmethod
load(path)¶ Reads an ML instance from the input path, a shortcut of read().load(path).
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classmethod
read()¶ Returns an MLReader instance for this class.
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save(path)¶ Save this ML instance to the given path, a shortcut of ‘write().save(path)’.
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set(param, value)¶ Sets a parameter in the embedded param map.
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setParams(self, \*, inverse=False, inputCol=None, outputCol=None)[source]¶ Sets params for this DCT.
New in version 1.6.0.
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transform(dataset, params=None)¶ Transforms the input dataset with optional parameters.
New in version 1.3.0.
- Parameters
- dataset
pyspark.sql.DataFrame input dataset
- paramsdict, optional
an optional param map that overrides embedded params.
- dataset
- Returns
pyspark.sql.DataFrametransformed dataset
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write()¶ Returns an MLWriter instance for this ML instance.
Attributes Documentation
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inputCol= Param(parent='undefined', name='inputCol', doc='input column name.')¶
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inverse= Param(parent='undefined', name='inverse', doc='Set transformer to perform inverse DCT, default False.')¶
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outputCol= Param(parent='undefined', name='outputCol', doc='output column name.')¶
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params¶ Returns all params ordered by name. The default implementation uses
dir()to get all attributes of typeParam.
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