static Averages EvalAvQ(EvalContext *ctx, char *t)
{
Averages *lastweek_vals, newvals;
double last5_vals[CF_OBSERVABLES];
double This[CF_OBSERVABLES];
char name[CF_MAXVARSIZE];
time_t now = time(NULL);
int i;
Banner("Evaluating and storing new weekly averages");
if ((lastweek_vals = GetCurrentAverages(t)) == NULL)
{
Log(LOG_LEVEL_ERR, "Error reading average database");
exit(1);
}
/* Discard any apparently anomalous behaviour before renormalizing database */
for (i = 0; i < CF_OBSERVABLES; i++)
{
double delta2;
char desc[CF_BUFSIZE];
name[0] = '\0';
GetObservable(i, name, desc);
/* Overflow protection */
if (lastweek_vals->Q[i].expect < 0)
{
lastweek_vals->Q[i].expect = 0;
}
if (lastweek_vals->Q[i].q < 0)
{
lastweek_vals->Q[i].q = 0;
}
if (lastweek_vals->Q[i].var < 0)
{
lastweek_vals->Q[i].var = 0;
}
// lastweek_vals is last week's stored data
This[i] =
RejectAnomaly(CF_THIS[i], lastweek_vals->Q[i].expect, lastweek_vals->Q[i].var, LOCALAV.Q[i].expect,
LOCALAV.Q[i].var);
newvals.Q[i].q = This[i];
newvals.last_seen = now; // Record the freshness of this slot
LOCALAV.Q[i].q = This[i];
Log(LOG_LEVEL_DEBUG, "Previous week's '%s.q' %lf", name, lastweek_vals->Q[i].q);
Log(LOG_LEVEL_DEBUG, "Previous week's '%s.var' %lf", name, lastweek_vals->Q[i].var);
Log(LOG_LEVEL_DEBUG, "Previous week's '%s.ex' %lf", name, lastweek_vals->Q[i].expect);
Log(LOG_LEVEL_DEBUG, "Just measured: CF_THIS[%s] = %lf", name, CF_THIS[i]);
Log(LOG_LEVEL_DEBUG, "Just sanitized: This[%s] = %lf", name, This[i]);
newvals.Q[i].expect = WAverage(This[i], lastweek_vals->Q[i].expect, WAGE);
LOCALAV.Q[i].expect = WAverage(newvals.Q[i].expect, LOCALAV.Q[i].expect, ITER);
if (last5_vals[i] > 0)
{
newvals.Q[i].dq = newvals.Q[i].q - last5_vals[i];
LOCALAV.Q[i].dq = newvals.Q[i].q - last5_vals[i];
}
else
{
newvals.Q[i].dq = 0;
LOCALAV.Q[i].dq = 0;
}
// Save the last measured value as the value "from five minutes ago" to get the gradient
last5_vals[i] = newvals.Q[i].q;
delta2 = (This[i] - lastweek_vals->Q[i].expect) * (This[i] - lastweek_vals->Q[i].expect);
if (lastweek_vals->Q[i].var > delta2 * 2.0)
{
/* Clean up past anomalies */
newvals.Q[i].var = delta2;
LOCALAV.Q[i].var = WAverage(newvals.Q[i].var, LOCALAV.Q[i].var, ITER);
}
else
{
newvals.Q[i].var = WAverage(delta2, lastweek_vals->Q[i].var, WAGE);
LOCALAV.Q[i].var = WAverage(newvals.Q[i].var, LOCALAV.Q[i].var, ITER);
}
Log(LOG_LEVEL_VERBOSE, "[%d] %s q=%lf, var=%lf, ex=%lf", i, name,
newvals.Q[i].q, newvals.Q[i].var, newvals.Q[i].expect);
Log(LOG_LEVEL_VERBOSE, "[%d] = %lf -> (%lf#%lf) local [%lf#%lf]", i, This[i], newvals.Q[i].expect,
sqrt(newvals.Q[i].var), LOCALAV.Q[i].expect, sqrt(LOCALAV.Q[i].var));
if (This[i] > 0)
{
Log(LOG_LEVEL_VERBOSE, "Storing %.2lf in %s", This[i], name);
}
}
UpdateAverages(ctx, t, newvals);
UpdateDistributions(ctx, t, lastweek_vals); /* Distribution about mean */
return newvals;
}
static Averages EvalAvQ(char *t)
{
Averages *currentvals, newvals;
double This[CF_OBSERVABLES];
char name[CF_MAXVARSIZE];
int i;
Banner("Evaluating and storing new weekly averages");
if ((currentvals = GetCurrentAverages(t)) == NULL)
{
CfOut(cf_error, "", "Error reading average database");
exit(1);
}
/* Discard any apparently anomalous behaviour before renormalizing database */
for (i = 0; i < CF_OBSERVABLES; i++)
{
double delta2;
char desc[CF_BUFSIZE];
name[0] = '\0';
GetObservable(i, name, desc);
/* Overflow protection */
if (currentvals->Q[i].expect < 0)
{
currentvals->Q[i].expect = 0;
}
if (currentvals->Q[i].q < 0)
{
currentvals->Q[i].q = 0;
}
if (currentvals->Q[i].var < 0)
{
currentvals->Q[i].var = 0;
}
This[i] =
RejectAnomaly(CF_THIS[i], currentvals->Q[i].expect, currentvals->Q[i].var, LOCALAV.Q[i].expect,
LOCALAV.Q[i].var);
newvals.Q[i].q = This[i];
LOCALAV.Q[i].q = This[i];
CfDebug("Current %s.q %lf\n", name, currentvals->Q[i].q);
CfDebug("Current %s.var %lf\n", name, currentvals->Q[i].var);
CfDebug("Current %s.ex %lf\n", name, currentvals->Q[i].expect);
CfDebug("CF_THIS[%s] = %lf\n", name, CF_THIS[i]);
CfDebug("This[%s] = %lf\n", name, This[i]);
newvals.Q[i].expect = WAverage(This[i], currentvals->Q[i].expect, WAGE);
LOCALAV.Q[i].expect = WAverage(newvals.Q[i].expect, LOCALAV.Q[i].expect, ITER);
newvals.Q[i].dq = newvals.Q[i].q - currentvals->Q[i].q;
LOCALAV.Q[i].dq = newvals.Q[i].q - currentvals->Q[i].q;
delta2 = (This[i] - currentvals->Q[i].expect) * (This[i] - currentvals->Q[i].expect);
if (currentvals->Q[i].var > delta2 * 2.0)
{
/* Clean up past anomalies */
newvals.Q[i].var = delta2;
LOCALAV.Q[i].var = WAverage(newvals.Q[i].var, LOCALAV.Q[i].var, ITER);
}
else
{
newvals.Q[i].var = WAverage(delta2, currentvals->Q[i].var, WAGE);
LOCALAV.Q[i].var = WAverage(newvals.Q[i].var, LOCALAV.Q[i].var, ITER);
}
CfOut(cf_verbose, "", "[%d] %s q=%lf, var=%lf, ex=%lf", i, name,
newvals.Q[i].q, newvals.Q[i].var, newvals.Q[i].expect);
CfOut(cf_verbose, "", "[%d] = %lf -> (%lf#%lf) local [%lf#%lf]\n", i, This[i], newvals.Q[i].expect,
sqrt(newvals.Q[i].var), LOCALAV.Q[i].expect, sqrt(LOCALAV.Q[i].var));
if (This[i] > 0)
{
CfOut(cf_verbose, "", "Storing %.2lf in %s\n", This[i], name);
}
}
UpdateAverages(t, newvals);
UpdateDistributions(t, currentvals); /* Distribution about mean */
return newvals;
}
