analytics/informix/extend/TimeSeries.6.00.FC8/examples/clip.c

/*
 * Licensed Materials - Property of HCL
 *
 * IBM Informix  DataBlade Module
 * (C) Copyright International Business Machines Corporation 2002.
 * (c) Copyright HCL Technologies Ltd. 2017.  All Rights Reserved.
 *
 * COPYRIGHT LICENSE: 
 * This information contains sample application programs in source language,
 * which illustrate programming techniques on various operating platforms.
 * You may copy, modify, and distribute these sample programs in any form
 * without payment to IBM, for the purposes of developing, using, marketing 
 * or distributing application programs conforming to the application 
 * programming interface for the operating platform for which the sample 
 * programs are written. These examples have not been thoroughly tested under 
 * all conditions. IBM, therefore, cannot guarantee or imply reliability, 
 * serviceability, or function of these programs. You may copy, modify, and 
 * distribute these sample programs in any form without payment to IBM for 
 * the purposes of developing, using, marketing, or distributing application 
 * programs conforming to IBM's application programming interfaces. 
 * Each copy or any portion of these sample programs or any derivative work, 
 * must include a copyright notice as follows: 
 * © (your company name) (year). Portions of this code are derived from 
 * IBM Corp. Sample Programs. © Copyright IBM Corp. (enter the year or 
 * years). All rights reserved. 
 *
 */

#include "tseries.h"

/*
 * Example code for clipping a timeseries
 */
ts_timeseries *
clip(ts_timeseries *ts, mi_datetime *start, mi_datetime *end, MI_FPARAM *fParam)
{
    ts_tsdesc   *tsdesc;
    ts_tsdesc   *new_tsdesc;
    ts_tscan    *tsscan;
    ts_tselem    elem;
    mi_integer	 ret;
    mi_integer	 nelems;
    mi_integer	 off;
    mi_boolean	 isreg;
    ts_timeseries *new_ts;
    MI_TYPEID	*ts_typeid;
    MI_CONNECTION *conn;

    conn = mi_open(NULL, NULL, NULL);

    /* get the type info for the input timeseries */
    ts_typeid = mi_fp_argtype(fParam, 0);

    /* open the input timeseries */
    tsdesc = ts_open(conn, ts, ts_typeid, 0);

    /*
     * not really needed, figure out how many elements
     * could possibly be in result timeseries.  This guess
     * will likely be way too big.  Might be better just
     * to use 0.
     */
    nelems = ts_nelems(tsdesc);

    /*
     * create the new timeseries.  Make it look like 
     * the original timeseries - regularity, calendar, container
     */
    isreg = !TS_IS_IRREGULAR(ts);
    new_ts = ts_create(conn,
		       ts_get_calname(ts),
		       start,
		       ts_get_threshold(ts),
		       isreg ? 0: TS_CREATE_IRR,
		       ts_typeid,
		       nelems,
		       ts_get_containername(ts));
    
    /* open the output timeseries */
    new_tsdesc = ts_open(conn, new_ts, ts_typeid, 0);

    /* start scanning the input timeseries between the given dates */
    off = -1;
    tsscan = ts_begin_scan(tsdesc, 0, start, end);
    while ((ret = ts_next(tsscan, &elem)) != TS_SCAN_EOS) {
	off++;
        if (ret == TS_SCAN_NULL)
	    /* just skip null elements */
	    continue;

	/* add the data */
	if (isreg)
	    ts_put_nth_elem(new_tsdesc, elem, off);
	else
	    ts_put_elem(new_tsdesc, elem, ts_current_timestamp(tsscan));
    }

    /* clean up */
    ts_end_scan(tsscan);
    ts_close(tsdesc);
    ts_close(new_tsdesc);

    /* return the result timeseries */
    return(new_ts);
}