};
xlab_t xlab[] = {
- {0, TMT_SECOND,30, TMT_MINUTE,5, TMT_MINUTE,5, 0,"%H:%M"},
- {2, TMT_MINUTE,1, TMT_MINUTE,5, TMT_MINUTE,5, 0,"%H:%M"},
- {5, TMT_MINUTE,2, TMT_MINUTE,10, TMT_MINUTE,10, 0,"%H:%M"},
- {10, TMT_MINUTE,5, TMT_MINUTE,20, TMT_MINUTE,20, 0,"%H:%M"},
- {30, TMT_MINUTE,10, TMT_HOUR,1, TMT_HOUR,1, 0,"%H:%M"},
- {60, TMT_MINUTE,30, TMT_HOUR,2, TMT_HOUR,2, 0,"%H:%M"},
- {180, TMT_HOUR,1, TMT_HOUR,6, TMT_HOUR,6, 0,"%H:%M"},
- /*{300, TMT_HOUR,3, TMT_HOUR,12, TMT_HOUR,12, 12*3600,"%a %p"}, this looks silly*/
- {600, TMT_HOUR,6, TMT_DAY,1, TMT_DAY,1, 24*3600,"%a"},
- {1800, TMT_HOUR,12, TMT_DAY,1, TMT_DAY,2, 24*3600,"%a"},
- {3600, TMT_DAY,1, TMT_WEEK,1, TMT_WEEK,1, 7*24*3600,"Week %V"},
- {3*3600, TMT_WEEK,1, TMT_MONTH,1, TMT_WEEK,2, 7*24*3600,"Week %V"},
- {6*3600, TMT_MONTH,1, TMT_MONTH,1, TMT_MONTH,1, 30*24*3600,"%b"},
- {48*3600, TMT_MONTH,1, TMT_MONTH,3, TMT_MONTH,3, 30*24*3600,"%b"},
- {10*24*3600, TMT_YEAR,1, TMT_YEAR,1, TMT_YEAR,1, 365*24*3600,"%y"},
- {-1,TMT_MONTH,0,TMT_MONTH,0,TMT_MONTH,0,0,""}
+ {0, 0, TMT_SECOND,30, TMT_MINUTE,5, TMT_MINUTE,5, 0,"%H:%M"},
+ {2, 0, TMT_MINUTE,1, TMT_MINUTE,5, TMT_MINUTE,5, 0,"%H:%M"},
+ {5, 0, TMT_MINUTE,2, TMT_MINUTE,10, TMT_MINUTE,10, 0,"%H:%M"},
+ {10, 0, TMT_MINUTE,5, TMT_MINUTE,20, TMT_MINUTE,20, 0,"%H:%M"},
+ {30, 0, TMT_MINUTE,10, TMT_HOUR,1, TMT_HOUR,1, 0,"%H:%M"},
+ {60, 0, TMT_MINUTE,30, TMT_HOUR,2, TMT_HOUR,2, 0,"%H:%M"},
+ {180, 0, TMT_HOUR,1, TMT_HOUR,6, TMT_HOUR,6, 0,"%H:%M"},
+ {180, 1*24*3600, TMT_HOUR,1, TMT_HOUR,6, TMT_HOUR,6, 0,"%a %H:%M"},
+ /*{300, 0, TMT_HOUR,3, TMT_HOUR,12, TMT_HOUR,12, 12*3600,"%a %p"}, this looks silly*/
+ {600, 0, TMT_HOUR,6, TMT_DAY,1, TMT_DAY,1, 24*3600,"%a"},
+ {600, 1*24*3600, TMT_HOUR,6, TMT_DAY,1, TMT_DAY,1, 24*3600,"%a %d"},
+ {1800, 0, TMT_HOUR,12, TMT_DAY,1, TMT_DAY,2, 24*3600,"%a"},
+ {1800, 1*24*3600, TMT_HOUR,12, TMT_DAY,1, TMT_DAY,2, 24*3600,"%a %d"},
+ {3600, 0, TMT_DAY,1, TMT_WEEK,1, TMT_WEEK,1, 7*24*3600,"Week %V"},
+ {3*3600, 0, TMT_WEEK,1, TMT_MONTH,1, TMT_WEEK,2, 7*24*3600,"Week %V"},
+ {6*3600, 0, TMT_MONTH,1, TMT_MONTH,1, TMT_MONTH,1, 30*24*3600,"%b"},
+ {48*3600, 0, TMT_MONTH,1, TMT_MONTH,3, TMT_MONTH,3, 30*24*3600,"%b"},
+ {10*24*3600, 0, TMT_YEAR,1, TMT_YEAR,1, TMT_YEAR,1, 365*24*3600,"%y"},
+ {-1,0,TMT_MONTH,0,TMT_MONTH,0,TMT_MONTH,0,0,""}
};
/* sensible logarithmic y label intervals ...
factor=(im->end - im->start)/im->xsize;
xlab_sel=0;
while ( xlab[xlab_sel+1].minsec != -1
- && xlab[xlab_sel+1].minsec <= factor){ xlab_sel++; }
+ && xlab[xlab_sel+1].minsec <= factor) { xlab_sel++; } /* pick the last one */
+ while ( xlab[xlab_sel-1].minsec == xlab[xlab_sel].minsec
+ && xlab[xlab_sel].length > (im->end - im->start)) { xlab_sel--; } /* go back to the smallest size */
im->xlab_user.gridtm = xlab[xlab_sel].gridtm;
im->xlab_user.gridst = xlab[xlab_sel].gridst;
im->xlab_user.mgridtm = xlab[xlab_sel].mgridtm;
return 0;
}
+/* from http://www.cygnus-software.com/papers/comparingfloats/comparingfloats.htm */
+/* yes we are loosing precision by doing tos with floats instead of doubles
+ but it seems more stable this way. */
+
+static int AlmostEqual2sComplement (float A, float B, int maxUlps)
+{
+
+ int aInt = *(int*)&A;
+ int bInt = *(int*)&B;
+ int intDiff;
+ /* Make sure maxUlps is non-negative and small enough that the
+ default NAN won't compare as equal to anything. */
+
+ /* assert(maxUlps > 0 && maxUlps < 4 * 1024 * 1024); */
+
+ /* Make aInt lexicographically ordered as a twos-complement int */
+
+ if (aInt < 0)
+ aInt = 0x80000000l - aInt;
+
+ /* Make bInt lexicographically ordered as a twos-complement int */
+
+ if (bInt < 0)
+ bInt = 0x80000000l - bInt;
+
+ intDiff = abs(aInt - bInt);
+
+ if (intDiff <= maxUlps)
+ return 1;
+
+ return 0;
+}
+
/* draw that picture thing ... */
int
graph_paint(image_desc_t *im, char ***calcpr)
if (im->gdes[i].col != 0x0){
/* GF_LINE and friend */
if(stack_gf == GF_LINE ){
- double last_y=0;
+ double last_y=0.0;
node = NULL;
for(ii=1;ii<im->xsize;ii++){
if (isnan(im->gdes[i].p_data[ii]) || (im->slopemode==1 && isnan(im->gdes[i].p_data[ii-1]))){
}
} else {
double new_y = ytr(im,im->gdes[i].p_data[ii]);
- if ( im->slopemode==0 && new_y != last_y){
+ if ( im->slopemode==0 && ! AlmostEqual2sComplement(new_y,last_y,4)){
gfx_add_point(node,ii-1+im->xorigin,new_y);
- last_y = new_y;
};
+ last_y = new_y;
gfx_add_point(node,ii+im->xorigin,new_y);
};
if ( idxI > 0 && ( drawem != 0 || ii==im->xsize)){
int cntI=1;
int lastI=0;
- while (cntI < idxI && foreY[lastI] == foreY[cntI] && foreY[lastI] == foreY[cntI+1]){cntI++;}
+ while (cntI < idxI && AlmostEqual2sComplement(foreY[lastI],foreY[cntI],4) && AlmostEqual2sComplement(foreY[lastI],foreY[cntI+1],4)){cntI++;}
node = gfx_new_area(im->canvas,
backX[0],backY[0],
foreX[0],foreY[0],
while (cntI < idxI) {
lastI = cntI;
cntI++;
- while ( cntI < idxI && foreY[lastI] == foreY[cntI] && foreY[lastI] == foreY[cntI+1]){cntI++;}
+ while ( cntI < idxI && AlmostEqual2sComplement(foreY[lastI],foreY[cntI],4) && AlmostEqual2sComplement(foreY[lastI],foreY[cntI+1],4)){cntI++;}
gfx_add_point(node,foreX[cntI],foreY[cntI]);
}
gfx_add_point(node,backX[idxI],backY[idxI]);
while (idxI > 1){
lastI = idxI;
idxI--;
- while ( idxI > 1 && backY[lastI] == backY[idxI] && backY[lastI] == backY[idxI-1]){idxI--;}
+ while ( idxI > 1 && AlmostEqual2sComplement(backY[lastI], backY[idxI],4) && AlmostEqual2sComplement(backY[lastI],backY[idxI-1],4)){idxI--;}
gfx_add_point(node,backX[idxI],backY[idxI]);
}
idxI=-1;
else if (!strcmp("TOTAL", func)) gdes->vf.op = VDEF_TOTAL;
else if (!strcmp("FIRST", func)) gdes->vf.op = VDEF_FIRST;
else if (!strcmp("LAST", func)) gdes->vf.op = VDEF_LAST;
+ else if (!strcmp("LSLSLOPE", func)) gdes->vf.op = VDEF_LSLSLOPE;
+ else if (!strcmp("LSLINT", func)) gdes->vf.op = VDEF_LSLINT;
+ else if (!strcmp("LSLCORREL",func)) gdes->vf.op = VDEF_LSLCORREL;
else {
rrd_set_error("Unknown function '%s' in VDEF '%s'\n"
,func
case VDEF_TOTAL:
case VDEF_FIRST:
case VDEF_LAST:
+ case VDEF_LSLSLOPE:
+ case VDEF_LSLINT:
+ case VDEF_LSLCORREL:
if (isnan(param)) {
gdes->vf.param = DNAN;
gdes->vf.val = DNAN;
dst->vf.when = src->start + (step+1)*src->step;
}
break;
+ case VDEF_LSLSLOPE:
+ case VDEF_LSLINT:
+ case VDEF_LSLCORREL:{
+ /* Bestfit line by linear least squares method */
+
+ int cnt=0;
+ double SUMx, SUMy, SUMxy, SUMxx, SUMyy, slope, y_intercept, correl ;
+ SUMx = 0; SUMy = 0; SUMxy = 0; SUMxx = 0; SUMyy = 0;
+
+ for (step=0;step<steps;step++) {
+ if (finite(data[step*src->ds_cnt])) {
+ cnt++;
+ SUMx += step;
+ SUMxx += step * step;
+ SUMxy += step * data[step*src->ds_cnt];
+ SUMy += data[step*src->ds_cnt];
+ SUMyy += data[step*src->ds_cnt]*data[step*src->ds_cnt];
+ };
+ }
+
+ slope = ( SUMx*SUMy - cnt*SUMxy ) / ( SUMx*SUMx - cnt*SUMxx );
+ y_intercept = ( SUMy - slope*SUMx ) / cnt;
+ correl = (SUMxy - (SUMx*SUMy)/cnt) / sqrt((SUMxx - (SUMx*SUMx)/cnt)*(SUMyy - (SUMy*SUMy)/cnt));
+
+ if (cnt) {
+ if (dst->vf.op == VDEF_LSLSLOPE) {
+ dst->vf.val = slope;
+ dst->vf.when = cnt*src->step;
+ } else if (dst->vf.op == VDEF_LSLINT) {
+ dst->vf.val = y_intercept;
+ dst->vf.when = cnt*src->step;
+ } else if (dst->vf.op == VDEF_LSLCORREL) {
+ dst->vf.val = correl;
+ dst->vf.when = cnt*src->step;
+ };
+
+ } else {
+ dst->vf.val = DNAN;
+ dst->vf.when = 0;
+ }
+ }
+ break;
}
return 0;
}
projects / rrdtool.git / blobdiff