- /* Find out the bin values */
- for ( count = 0, d = x_min; d <= x_max ; d += x_interval, ++count )
- {
-
- double y = 0;
-
- for ( frq = hsh_first(fh,&hi); frq != 0; frq = hsh_next(fh,&hi) )
- {
- if ( frq->v.f >= d && frq->v.f < d + x_interval )
- y += frq->c;
- }
-
- ordinate_values[count] = y ;
-
- if ( y > y_max ) y_max = y ;
- if ( y < y_min ) y_min = y;
- }
-
- y_tick = chart_rounded_tick( ( y_max - y_min ) / (double) (YTICKS - 1));
-
-
- y_min = floor( y_min / y_tick ) * y_tick ;
- y_max = ceil( y_max / y_tick ) * y_tick ;
-
- double ordinate_scale =
- fabs(ch->data_top - ch->data_bottom) / fabs(y_max - y_min) ;
-
-
- /* Move to data bottom-left */
- pl_move_r(ch->lp, ch->data_left, ch->data_bottom);
-
- pl_savestate_r(ch->lp);
- pl_fillcolorname_r(ch->lp, ch->fill_colour);
- pl_filltype_r(ch->lp,1);
-
- /* Draw the histogram */
- for ( count = 0, d = x_min; d <= x_max ; d += x_interval, ++count )
- {
- const double x = count * interval_size ;
- pl_savestate_r(ch->lp);
-
- draw_tick (ch, TICK_ABSCISSA, x + (interval_size / 2.0 ), "%.1f",d);
-
- pl_fboxrel_r(ch->lp, x, 0, x + interval_size,
- ordinate_values[count] * ordinate_scale );
-
- pl_restorestate_r(ch->lp);
-
- }
- pl_restorestate_r(ch->lp);
-
- /* Put the y axis on */
- for ( d = y_min; d <= y_max ; d += y_tick )
- {
- draw_tick (ch, TICK_ORDINATE, (d - y_min ) * ordinate_scale, "%g", d);
- }
-
- /* Write the abscissa label */
- pl_move_r(ch->lp,ch->data_left, ch->abscissa_top);
- pl_alabel_r(ch->lp,0,'t',var->label ? var->label : var->name);
-
-
- /* Write the ordinate label */
- pl_savestate_r(ch->lp);
- pl_move_r(ch->lp,ch->data_bottom, ch->ordinate_right);
- pl_textangle_r(ch->lp,90);
- pl_alabel_r(ch->lp,0,0,"Frequency");
-
- pl_restorestate_r(ch->lp);
-
-
- chart_write_title(ch, title);
-
-
- /* Write the legend */
- write_legend(ch,norm);
-
-
- if ( show_normal )
- {
- /* Draw the normal curve */
- double d;
-
- pl_move_r(ch->lp, ch->data_left, ch->data_bottom);
- for( d = ch->data_left;
- d <= ch->data_right ;
- d += (ch->data_right - ch->data_left) / 100.0)
- {
- const double x = (d - ch->data_left - interval_size / 2.0 ) /
- abscissa_scale + x_min ;
-
- pl_fcont_r(ch->lp, d,
- ch->data_bottom +
- norm->N * gaussian(x, norm->mean, norm->stddev)
- * ordinate_scale);
-
- }
- pl_endpath_r(ch->lp);
- }