7.00.02 - DWT Arguments - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Content Type
Programming Reference
User Guide
Publication ID
B700-1022-700K
Language
English (United States)
Last Update
2018-04-17
InputTable
Specifies the name of the table or view that contains the sequences to be transformed.
OutputTable
Specifies the name for the table that the function creates to store the coefficients generated by the wavelet transform. This table must not exist.
MetaTable
Specifies the name for the table that the function creates to store the meta information for the wavelet transform. This table must not exist.
InputColumns
Specifies the names of the columns in the input table or view that contain the data to be transformed. These columns must contain numeric values between -1e308 and 1e308. The function treats NULL as 0.
SortColumn
Specifies the name of the column that defines the order of samples in the sequences to be transformed. In a time series sequence, the column can consist of timestamp values.
If sort_column has duplicate elements in a sequence (that is, in a partition), sequence order can vary, and the function can produce different transform results for the sequence.
PartitionColumns
[Optional] Specifies the names of the partition columns, which identify the sequences. Rows with the same partition column values belong to the same sequence. If you specify multiple partition columns, the function treats the first one as the distribute key of the output and meta tables.

Default behavior: All rows belong to one sequence, and the function generates a distribute key column named dwt_idrandom_name in both the output table and the meta table. In both tables, every cell of dwt_idrandom_name has the value 1.

Wavelet
[Optional] Specifies a wavelet filter name from the following table.
WaveletFilterTable
[Optional] Specifies the name of the table that contains the coefficients of the wave filters.
Level
Specifies the wavelet transform level. The value level must be an integer in the range [1, 1000].
ExtensionMode
[Optional] Specifies the wavelet transform level. The value level must be an integer in the range [1, 1000].
Supported Wavelet Filter Names
Wavelet Family Supported Wavelet Names (wavelet values)
Daubechies 'db1' or 'haar', 'db2', .... ,'db10'
Coiflets 'coif1', ... , 'coif5'
Symlets 'sym1', ... ,' sym10'
Discrete Meyer 'dmey'
Biorthogonal 'bior1.1', 'bior1.3', 'bior1.5', 
'bior2.2', 'bior2.4', 'bior2.6', 'bior2.8',
'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5'
Reverse Biorthogonal 'rbio1.1', 'rbio1.3', 'rbio1.5'
'rbio2.2', 'rbio2.4', 'rbio2.6', 'rbio2.8',
'rbio3.1', 'rbio3.3', 'rbio3.5', 'rbio3.7','rbio3.9',
'rbio4.4', 'rbio5.5'

For the examples in the following table, assume that the sequence before the extension is 1 2 3 4 and the convolution kernel in the wavelet filter has the length 6, which means that the length of the sequence is to be extended by 5 positions before and after the sequence.

Supported Extension Modes
Supported Extension Mode (extension_mode value) Description
sym (Default) Symmetrically replicate boundary values, mirroring the points near the boundaries. For example:

4 4 3 2 1 | 1 2 3 4 | 4 3 2 1 1

zpd Zero-pad boundary values with zero. For example:

0 0 0 0 0 | 1 2 3 4 | 0 0 0 0 0

ppd Periodic extension, fill boundary values as the input sequence is a periodic one. For example:

4 1 2 3 4 | 1 2 3 4 | 1 2 3 4 1