TD_CONVOLVE Function Example | Teradata Vantage - TD_CONVOLVE Example

TD_CONVOLVE Function Example | Teradata Vantage - TD_CONVOLVE Example - Teradata Vantage

Database Unbounded Array Framework Time Series Functions

Deployment

VantageCloud

VantageCore

Edition

VMware

Enterprise

IntelliFlex

Product

Teradata Vantage

Release Number

17.20

Published

June 2022

ft:locale

en-US

ft:lastEdition

2025-04-04

dita:mapPath

ncd1634149624743.ditamap

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ruu1634160136230.ditaval

dita:id

ncd1634149624743

Example: TD_CONVOLVE Call with XCONVOLVE_COMPLEX_LEFT Input and CONV_SUMMATION Algorithm

Input Table for XCONVOLVE_COMPLEX_LEFT (Time Series) for CONV_SUMMATION
ID	SEQ	A_REAL	A_IMAG
33	0	1.0	0.2
33	1	2.0	0.8
33	2	-1.0	-0.9
33	3	-2.0	1.9
33	4	-3.0	-0.5

Input Table for Input Table HCONVOLVE_COMPLEX_RIGHT (Filter Series) for CONV_SUMMATION
ID	SEQ	A_REAL	A_IMAG
33	0	1.0	0.55
33	1	2.0	0.65
33	2	0.0	0.45
33	3	-3.0	0.11

TD_CONVOLVE Call with XCONVOLVE_COMPLEX_LEFT Input and CONV_SUMMATION Algorithm

EXECUTE FUNCTION INTO VOLATILE ART(ConvCmplxResB)
         TD_CONVOLVE(
         SERIES_SPEC(TABLE_NAME(XCONVOLVE_COMPLEX_LEFT),SERIES_ID(ID),ROW_AXIS(SEQUENCE(SEQ)),
         PAYLOAD( FIELDS(A_REAL,A_IMAG), CONTENT(MULTIVAR_REAL))),
         SERIES_SPEC(TABLE_NAME(HCONVOLVE_COMPLEX_RIGHT),SERIES_ID(ID),ROW_AXIS(SEQUENCE(SEQ)),
         PAYLOAD( FIELDS(A_REAL,A_IMAG), CONTENT(COMPLEX))),
         FUNC_PARAMS(ALGORITHM("CONV_SUMMATION")),
         INPUT_FMT(INPUT_MODE(MATCH)));

TD_CONVOLVE Output for XCONVOLVE_COMPLEX_LEFT Input and CONV_SUMMATION Algorithm

Display the primary RETURNS TABLE with this statement:

SELECT * FROM ConvCmplxResB;

ID  ROW_I  REAL_A_REAL  IMAG_A_REAL   REAL_A_IMAG         IMAG_A_IMAG
-------------------------------------------------------------------------
33  0        2.0         0.0      0.11000000000000001     0.0
33  1        5.0         0.0      0.5700000000000001      0.0 
33  2        1.0         0.0      0.11499999999999994     0.0
33  3        -10.0       0.0      0.8419999999999999      0.0
33  4        -10.0       0.0      0.6429999999999999      0.0
33  5        -3.0        0.0      0.431000                0.0
33  6        6.0         0.0      -0.016000000000000014   0.0
33  7        9.0         0.0      9.05500000000000E       0.0

Example: TD_CONVOLVE with CONV_DFFT Algorithm

Input Table for XCONVOLVE_COMPLEX_LEFT (Time Series) for CONV_DFFT Algorithm
ID	SEQ	A_REAL	A_IMAG	B_REAL	B_IMAG	C_REAL	C_IMAG
33	0	2.0	0.2	2.0	0.2	2.0	0.2
33	1	1.0	0.8	1.0	0.8	1.0	0.8
33	2	-1.0	-0.9	-1.0	-0.9	-1.0	-0.9
33	3	-2.0	1.9	-2.0	1.9	-2.0	1.9
33	4	-3.0	-0.5	-3.0	-0.5	-3.0	-0.5

Input Table for Input Table HCONVOLVE_COMPLEX_RIGHT (Filter Series) for CONV_DFFT Algorithm
ID	SEQ	A_REAL	A_IMAG	B_REAL	B_IMAG	C_REAL	C_IMAG
33	0	1.0	0.55	1.0	0.55	1.0	0.55
33	1	2.0	0.65	2.0	0.65	2.0	0.65
33	2	0.0	0.45	0.0	0.45	0.0	0.45
33	3	-3.0	0.11	-3.0	0.11	-3.0	0.11

TD_CONVOLVE Call with CONV_DFFT Algorithm

EXECUTE FUNCTION INTO VOLATILE ART(ConvCmplxResB)
   TD_CONVOLVE(
   SERIES_SPEC(TABLE_NAME(XCONVOLVE_COMPLEX_LEFTMULTI),SERIES_ID(ID),ROW_AXIS(SEQUENCE(SEQ)),
   PAYLOAD( FIELDS(A_REAL,A_IMAG,B_REAL,B_IMAG,C_REAL,C_IMAG), CONTENT(MULTIVAR_COMPLEX))),
   SERIES_SPEC(TABLE_NAME(HCONVOLVE_COMPLEX_RIGHTMULTI),SERIES_ID(ID),ROW_AXIS(SEQUENCE(SEQ)),
   PAYLOAD( FIELDS(A_REAL,A_IMAG,B_REAL,B_IMAG,C_REAL,C_IMAG), CONTENT(COMPLEX))),
   FUNC_PARAMS(ALGORITHM("CONV_DFFT")),
   INPUT_FMT(INPUT_MODE(MATCH)));

TD_CONVOLVE Output with CONV_DFFT Algorithm

Display the primary RETURNS TABLE with this statement:

SELECT * FROM ConvCmplxResB;

TD_CONVOLVE Output for CONV_DFFT Algorithm

ID	SEQ	REAL_A_REAL	IMAG_A_REAL	REAL_B_REAL	IMAG_B_REAL	REAL_C_REAL	IMAG_C_REAL
33	0	1.8899999999999997	1.3000000000000003	1.8899999999999997	1.3000000000000003	1.8899999999999997	1.3000000000000003
33	1	4.430000000000001	3.05	4.430000000000001	3.05	4.430000000000001	3.05
33	2	0.8849999999999998	1.700000000000001	0.8849999999999998	1.700000000000001	0.8849999999999998	1.700000000000001
33	3	-10.842	-1.5799999999999992	-10.842	-1.5799999999999992	-10.842	-1.5799999999999992
33	4	-10.643000000000004	-2.390000000000004	-10.643000000000004	-2.390000000000004	-10.643000000000004	-2.390000000000004
33	5	-3.4310000000000005	-1.2599999999999991	-3.4310000000000005	-1.2599999999999991	-3.4310000000000005	-1.2599999999999991
33	6	6.016000000000003	-7.269999999999998	6.016000000000003	-7.269999999999998	6.016000000000003	-7.269999999999998
33	7	9.055000000000001	1.169999999999999	9.055000000000001	1.169999999999999	9.055000000000001	1.169999999999999