void fake_data()
{
/* use this function to create fake data to test your analysis, before you try real data */
/* how many data in all? */
int numdata = 999;
/* create internal table to hold data */
table_create("fakedata");
/* define table structure */
// table_addcolumn("fakedata", <column_name>);
// ...
/* create fake data */
for(int ii = 0; ii < numdata; ii++)
{
/* compute values of a fake data row */
/* write these values to the data (as if reading real data) */
// table_writevalue("fakedata", <column_name>, ii, <computed_value>);
// ...
}
/* output data to use later on */
table_output("fakedata","./workspace/mymodel_fakedata.txt");
return;
}
/**
* val_analyse:
* @widgets: The widget layout
* @tracks_and_layers: A list of #vik_trw_track_list_t
* @include_invisible: Whether to include invisible layers and tracks
*
* Analyse each item in the @tracks_and_layers list
*
*/
void val_analyse ( GtkWidget *widgets[], GList *tracks_and_layers, gboolean include_invisible, gboolean extended )
{
val_reset ( TS_TRACKS );
GList *gl = g_list_first ( tracks_and_layers );
if ( gl ) {
g_list_foreach ( gl, (GFunc) val_analyse_item_maybe, GINT_TO_POINTER(include_invisible) );
}
table_output ( tracks_stats[TS_TRACKS], widgets, extended );
g_list_free_full ( tracks_stats[TS_TRACKS].e_list, g_free );
}
void final_output()
{
char fname[100];
/* create file name for output -- fname gets the 'path' and analysis name */
get_filzbach_path(fname, 100);
/* now your bit to add to the path */
strcat(fname,"_my_output.txt");
/* print internal table out to file with name taken from above */
table_output("mydata",fname);
return;
}
void fake_data()
{
/* use this to create fake data to test your analysis, before you try real data */
/* do we get these parameters back out again? */
double true_m0 = 2.0, true_beta=0.010, true_gph=0.40, true_gdepth=0.00, true_gmoss=0.20; // nb -- no effect of depth
double phref=7.0, depthref=10.0, mossref=0.0;
double ph, depth, moss, lambda, count;
int ii;
/* create internal table to hold data, and model predictions (written in later) */
table_create("fakedata");
table_addcolumn("fakedata","ph");
table_addcolumn("fakedata","depth");
table_addcolumn("fakedata","moss");
table_addcolumn("fakedata","count");
/* how many data in all? */
numdata = 999;
for(ii=0 ; ii<numdata ; ii++)
{
/* draw fakedata values for factors: ph, depth, moss */
depth = random(0.0,20.0);
ph = 5.0 + 2.0*(depth/20.0) + random(0.0,2.0);
if(random(0.0,1.0)<0.50)
moss = 1.0;
else
moss = 0.0;
/* calculte lambda (=average seedling count) for these conditions */
lambda = true_beta + true_m0*exp( true_gph*(ph-phref) + true_gdepth*(depth-depthref) + true_gmoss*(moss-mossref));
/* draw fakedata no. of seedlings from poisson with this lambda */
count = poisson_draw(lambda);
/* write these values to the data (as if reading real data) */
table_writevalue("fakedata","moss",ii,moss);
table_writevalue("fakedata","ph",ii,ph);
table_writevalue("fakedata","depth",ii,depth);
table_writevalue("fakedata","count",ii,count);
}
table_output("fakedata","./workspace/EgDataz2_seedrain.txt");
return;
}
void fake_data()
{
/* use this to create fake data to test your analysis, before you try real data */
/* do we get these parameters back out again? */
double true_sigma1 = 9.0;
double true_mean1 = 37.0;
double true_sigma2 = 25.0;
double true_mean2 = 100.0;
double true_q = 0.80;
/* how many data in all? */
int numdata = 99;
/* create internal table to hold data */
table_create("fakedata");
table_addcolumn("fakedata","y");
for(int ii=0 ; ii<numdata ; ii++)
{
/* first, randomly choose normal1, or normal 2 */
int choice;
if(random(0.0,1.0)<true_q)
choice = 1;
else
choice = 2;
/* now draw random value for y from the appropriate normal distribution */
double y;
if(choice==1)
y = normal_draw(true_mean1,true_sigma1);
if(choice==2)
y = normal_draw(true_mean2,true_sigma2);
/* write the y value to the data (as if reading real data) */
table_writevalue("fakedata","y",ii,y);
}
/* output data to use later on */
table_output("fakedata","./workspace/eg03_mixednormal_fakedata.txt");
return;
}
void final_output()
{
/* create link to file */
char fname[100];
/* create file name for output */
get_filzbach_path(fname, 100);
/* now your bit */
strcat(fname,"_my_output.txt");
/* we're ouputting predictions */
/* in this case, one set of preds with params set at posterior means */
/* but could output an ensemble of predictions, with each set with param vector drawn at random */
/* see the commented out line below... */
params_set_to_posterior_mean();
// params_draw_random_vector();
/* in this case it's the likelihood function that writes the preds into the table */
likelihood();
/* output */
table_output("mydata",fname);
return;
}
