00001 /*****************************************************************************
00002    Major portions of this software are copyrighted by the Medical College
00003    of Wisconsin, 1994-2000, and are released under the Gnu General Public
00004    License, Version 2.  See the file README.Copyright for details.
00005 ******************************************************************************/
00006    
00007 /*
00008   This file contains routines to initialize and implement the 
00009   differential exponential drug response signal model.
00010 
00011   File:     model_diffexp.c
00012   Author:   B. Douglas Ward
00013   Date:     6 June 1997
00014 */
00015 
00016 
00017 /*---------------------------------------------------------------------------*/
00018 
00019 #include <math.h>
00020 #include "NLfit_model.h"
00021 
00022 void signal_model 
00023 (
00024   float * gs,                /* parameters for signal model */
00025   int ts_length,             /* length of time series data */
00026   float ** x_array,          /* independent variable matrix */
00027   float * ts_array           /* estimated signal model time series */  
00028 );
00029 
00030 
00031 /*---------------------------------------------------------------------------*/
00032 /*
00033   Routine to initialize the signal model by defining the number of parameters
00034   in the signal model, the name of the signal model, and the default values
00035   for the minimum and maximum parameter constraints.
00036 */
00037 
00038 DEFINE_MODEL_PROTOTYPE
00039 
00040 MODEL_interface * initialize_model ()
00041 {
00042   MODEL_interface * mi = NULL;
00043 
00044 
00045   /*----- allocate memory space for model interface -----*/
00046   mi = (MODEL_interface *) XtMalloc (sizeof(MODEL_interface));
00047 
00048 
00049   /*----- define interface for the differential - exponential model -----*/   
00050 
00051   /*----- name of this model -----*/
00052   strcpy (mi->label, "DiffExp");
00053 
00054   /*----- this is a signal model -----*/
00055   mi->model_type = MODEL_SIGNAL_TYPE;
00056 
00057   /*----- number of parameters in the model -----*/
00058   mi->params = 4;
00059 
00060   /*----- parameter labels -----*/
00061   strcpy (mi->plabel[0], "t0");
00062   strcpy (mi->plabel[1], "k");
00063   strcpy (mi->plabel[2], "alpha1");
00064   strcpy (mi->plabel[3], "alpha2");
00065 
00066   /*----- minimum and maximum parameter constraints -----*/
00067   mi->min_constr[0] =    45.0;    mi->max_constr[0] =    75.0;
00068   mi->min_constr[1] =  -500.0;    mi->max_constr[1] =   500.0;
00069   mi->min_constr[2] =     0.00;   mi->max_constr[2] =     0.15;
00070   mi->min_constr[3] =     0.15;   mi->max_constr[3] =     0.50;
00071   
00072   /*----- function which implements the model -----*/
00073   mi->call_func = &signal_model;
00074 
00075 
00076   /*----- return pointer to the model interface -----*/
00077   return (mi);
00078 }
00079 
00080 
00081 /*---------------------------------------------------------------------------*/
00082 /*
00083   Routine to calculate the time series which results from using the
00084   differential exponential drug response signal model with the specified
00085   model parameters.
00086 
00087   Definition of model parameters:
00088 
00089      gs[0] = time delay of response (t0)  
00090      gs[1] = multiplicative constant (k)
00091      gs[2] = elimination rate constant (alpha1)
00092      gs[3] = absorption rate constant (alpha2)
00093 */
00094 
00095 void signal_model 
00096 (
00097   float * gs,                /* parameters for signal model */
00098   int ts_length,             /* length of time series data */
00099   float ** x_array,          /* independent variable matrix */
00100   float * ts_array           /* estimated signal model time series */  
00101 )
00102 
00103 {
00104   int it;                           /* time index */     
00105   float t;                          /* time */
00106   float fval;                       /* time series value at time t */  
00107 
00108 
00109   for (it = 0;  it < ts_length;  it++)
00110     {
00111       t = x_array[it][1];
00112       if (t < gs[0])
00113         fval = 0.0;
00114       else
00115         fval = gs[1] * (exp(-gs[2]*(t-gs[0])) - exp(-gs[3]*(t-gs[0])));
00116       ts_array[it] = fval;
00117     }
00118   
00119 }
00120 
00121 
00122 
00123