void
gen_interp_frequency(struct curve_points *plot)
{
int i, j, curves;
int first_point, num_points;
double y;
curves = num_curves(plot);
first_point = 0;
for (i = 0; i < curves; i++) {
num_points = next_curve(plot, &first_point);
/* If cumulative, replace the current y-value with the
sum of all previous y-values. This assumes that the
data has already been sorted by x-values. */
if( plot->plot_smooth == SMOOTH_CUMULATIVE ) {
y = 0;
for (j = first_point; j < first_point + num_points; j++) {
if (plot->points[j].type == UNDEFINED)
continue;
y += plot->points[j].y;
plot->points[j].y = y;
}
}
do_freq(plot, first_point, num_points);
first_point += num_points + 1;
}
return;
}
void
gen_interp_unwrap(struct curve_points *plot)
{
int i, j, curves;
int first_point, num_points;
double y, lasty, diff;
curves = num_curves(plot);
first_point = 0;
for (i = 0; i < curves; i++) {
num_points = next_curve(plot, &first_point);
lasty = 0; /* make all plots start the same place */
for (j = first_point; j < first_point + num_points; j++) {
if (plot->points[j].type == UNDEFINED)
continue;
y = plot->points[j].y;
do {
diff = y - lasty;
if (diff > M_PI) y -= 2*M_PI;
if (diff < -M_PI) y += 2*M_PI;
} while (fabs(diff) > M_PI);
plot->points[j].y = y;
lasty = y;
}
do_freq(plot, first_point, num_points);
first_point += num_points + 1;
}
return;
}
void
gen_interp(struct curve_points *plot)
{
spline_coeff *sc;
double *bc;
struct coordinate *new_points;
int i, curves;
int first_point, num_points;
curves = num_curves(plot);
new_points = gp_alloc((samples_1 + 1) * curves * sizeof(struct coordinate),
"interpolation table");
first_point = 0;
for (i = 0; i < curves; i++) {
num_points = next_curve(plot, &first_point);
switch (plot->plot_smooth) {
case SMOOTH_CSPLINES:
sc = cp_tridiag(plot, first_point, num_points);
do_cubic(plot, sc, first_point, num_points,
new_points + i * (samples_1 + 1));
free(sc);
break;
case SMOOTH_ACSPLINES:
sc = cp_approx_spline(plot, first_point, num_points);
do_cubic(plot, sc, first_point, num_points,
new_points + i * (samples_1 + 1));
free(sc);
break;
case SMOOTH_BEZIER:
case SMOOTH_SBEZIER:
bc = cp_binomial(num_points);
do_bezier(plot, bc, first_point, num_points,
new_points + i * (samples_1 + 1));
free((char *) bc);
break;
case SMOOTH_KDENSITY:
do_kdensity( plot, first_point, num_points,
new_points + i * (samples_1 + 1));
break;
default: /* keep gcc -Wall quiet */
;
}
new_points[(i + 1) * (samples_1 + 1) - 1].type = UNDEFINED;
first_point += num_points;
}
free(plot->points);
plot->points = new_points;
plot->p_max = curves * (samples_1 + 1);
plot->p_count = plot->p_max - 1;
return;
}
void
gen_interp_frequency(struct curve_points *plot)
{
int i, j, curves;
int first_point, num_points;
double y, y_total;
curves = num_curves(plot);
if (plot->plot_smooth == SMOOTH_CUMULATIVE_NORMALISED) {
y_total = 0.0;
first_point = 0;
for (i = 0; i < curves; i++) {
num_points = next_curve(plot, &first_point);
for (j = first_point; j < first_point + num_points; j++) {
if (plot->points[j].type == UNDEFINED)
continue;
y_total += plot->points[j].y;
}
first_point += num_points + 1;
}
}
first_point = 0;
for (i = 0; i < curves; i++) {
num_points = next_curve(plot, &first_point);
/* If cumulative, replace the current y-value with the
sum of all previous y-values. This assumes that the
data has already been sorted by x-values. */
if( plot->plot_smooth == SMOOTH_CUMULATIVE ) {
y = 0;
for (j = first_point; j < first_point + num_points; j++) {
if (plot->points[j].type == UNDEFINED)
continue;
y += plot->points[j].y;
plot->points[j].y = y;
}
}
/* Alternatively, cumulative normalised means replace the
current y-value with the sum of all previous y-values
divided by the total sum of all values. This assumes the
data is sorted as before. Normalising in this way allows
comparison of the CDF of data sets with differing total
numbers of samples. */
if (plot->plot_smooth == SMOOTH_CUMULATIVE_NORMALISED) {
y = 0;
for (j = first_point; j < first_point + num_points; j++) {
if (plot->points[j].type == UNDEFINED)
continue;
y += plot->points[j].y;
plot->points[j].y = y / y_total;
}
}
do_freq(plot, first_point, num_points);
first_point += num_points + 1;
}
return;
}
