public Tuple4f getDynamics() {
Tuple4f dynamics = new Vector4f();
long count = 0;
double total = 0;
float min = Float.POSITIVE_INFINITY;
float max = Float.NEGATIVE_INFINITY;
for (int k = 0; k < size; k++) {
// Do not include NAN or isInfinite in dynamics
if (!((Float.isNaN(f[k])) || (Float.isInfinite(f[k])))) {
// System.out.print(k +"="+f[k]+ ", ");
min = Math.min(min, f[k]);
max = Math.max(max, f[k]);
total += (double) f[k];
count++;
}
}
dynamics.w = min;
dynamics.x = max;
dynamics.y = (float) (total / (double) count);
float range = max - min;
int N = 256;
System.out.println("min: " + min + " Max: " + max + " Range: " + range);
int[] histogram = new int[N];
int level = 0;
float quant = N * 0.999f;
for (int k = 0; k < size; k++) {
if (!((Float.isNaN(f[k])) || (Float.isInfinite(f[k])))) {
level = (int) (quant * ((f[k] - min) / range));
try {
histogram[level]++;
} catch (ArrayIndexOutOfBoundsException e) {
System.out.println("ArrayIndexOutOfBoundsException in ScalarImage.analyze(double) [A].");
}
}
}
for (int j = 0; j < N; j++) {
System.out.println(
"Level: "
+ j
+ " count: "
+ histogram[j]
+ " value: "
+ (float) ((j / quant * (max - min)) + min));
}
int target = (int) (count * 0.9);
int cum = 0;
for (int i = 0; i < N; i++) {
cum += histogram[i];
System.out.println(
"target: "
+ target
+ " cum: "
+ cum
+ " Level: "
+ i
+ " value: "
+ ((i / quant * (max - min)) + min));
if (cum >= target) {
System.out.println(
"target: " + target + " Level: " + i + " value: " + ((i * (max - min)) + min));
dynamics.z = (float) ((i / quant * (max - min)) + min);
break;
}
}
return dynamics;
}
public void normalize(double range) {
double scale = range;
float min = 1000f;
float max = -1000f;
for (int k = 0; k < size; k++) {
// System.out.println(f[k]);
/*
* if (f[k] == Float.NaN) { System.out.println("NaN at k= "+k);
* f[k] = 0f; }
*/
if (Float.isNaN(f[k])) {
System.out.println("NaN at k= " + k);
f[k] = 0f;
continue;
}
if (Float.isInfinite(f[k])) {
if (f[k] < 0) {
System.out.println("-Infinity at k= " + k);
f[k] = 0f; // -1000f;
} else {
System.out.println("+Infinity at k= " + k);
f[k] = 0f; // +1000f;
}
continue;
}
// System.out.print(k +"="+f[k]+ ", ");
min = Math.min(min, f[k]);
max = Math.max(max, f[k]);
}
// System.out.println();
double offset = 0. - min;
if ((max - min) != 0f) {
scale /= (max - min);
offset *= scale;
rescale(scale, offset);
}
System.out.println(
"Normalizing using: min= "
+ min
+ " max= "
+ max
+ ", through scaleAdd("
+ scale
+ ", "
+ offset
+ ").");
min = 1000f;
max = -1000f;
for (int k = 0; k < size; k++) {
/* if (f[k] == Float.NaN) {
System.out.println("NaN at k= " + k);
f[k] = 0f;
}
*/
if (Float.isNaN(f[k])) {
System.out.println("NaN at k= " + k + " after normalization.");
f[k] = 0f;
continue;
}
// System.out.print(k +"="+f[k]+ ", ");
min = Math.min(min, f[k]);
max = Math.max(max, f[k]);
}
System.out.println("After normalization: min= " + min + " max= " + max);
}
public void analyze(boolean doit) {
float min = Float.POSITIVE_INFINITY;
float max = Float.NEGATIVE_INFINITY;
for (int k = 0; k < size; k++) {
// System.out.println(f[k]);
/*
* if (f[k] == Float.NaN) { System.out.println("NaN at k= "+k);
* f[k] = 0f; }
*/
if (Float.isNaN(f[k])) {
System.out.println("NaN at k= " + k);
f[k] = 0f;
continue;
}
if (Float.isInfinite(f[k])) {
if (f[k] < 0) {
System.out.println("-Infinity at k= " + k);
f[k] = 0f; // -1000f;
} else {
System.out.println("+Infinity at k= " + k);
f[k] = 0f; // +1000f;
}
continue;
}
// System.out.print(k +"="+f[k]+ ", ");
min = Math.min(min, f[k]);
max = Math.max(max, f[k]);
}
int N = 256;
float[] histogram = new float[N];
for (int k = 0; k < size; k++) {
int level = (int) (0.999f * (float) N * (f[k] - min) / (max - min));
try {
histogram[level]++;
} catch (ArrayIndexOutOfBoundsException e) {
System.out.println("ArrayIndexOutOfBoundsException in ScalarImage.analyze(double) [A].");
}
}
float[] cumulative = new float[N];
if (histogram[0] > 0) {
if (doit) {
cumulative[0] = histogram[0];
} else {
cumulative[0] = 1; // histogram[0];
}
}
for (int i = 1; i < N; i++) {
if (histogram[i] > 0) {
if (doit) {
cumulative[i] = cumulative[i - 1] + histogram[i];
} else {
cumulative[i] = cumulative[i - 1] + 1; // histogram[i];
}
} else {
cumulative[i] = cumulative[i - 1];
}
}
/* for(int k=0; k<size; k++) {
int level = (int) ( 0.999f*(float)N*(f[k]-min)/(max-min) );
try {
f[k]=(cumulative[level]-cumulative[0])/(cumulative[N-1]-cumulative[0]);
} catch( ArrayIndexOutOfBoundsException e) {
System.out.println("ArrayIndexOutOfBoundsException in ScalarImage.analyze(double) [B].");
}
}
*/
for (int k = 0; k < size; k++) {
float x, x1, x2, f1, f2;
try {
x = Math.abs((f[k] - min) / (max - min));
x1 = (float) Math.floor((float) (N - 1) * x * 0.999f) / (float) (N - 1);
x2 = (float) Math.ceil((float) (N - 1) * x * 0.999f) / (float) (N - 1);
f1 =
(cumulative[(int) Math.floor((float) (N - 1) * x * 0.999f)] - cumulative[0])
/ (cumulative[N - 1] - cumulative[0]);
f2 =
(cumulative[(int) Math.ceil((float) (N - 1) * x * 0.999f)] - cumulative[0])
/ (cumulative[N - 1] - cumulative[0]);
f[k] = (f2 - f1) * (x - x1) / (x2 - x1) + f1;
} catch (ArrayIndexOutOfBoundsException e) {
System.out.println(
"ArrayIndexOutOfBoundsException in ScalarImage.analyze(double) [C]. " + e.getMessage());
}
}
return;
/*
double offset = 0. - min;
if ((max - min) != 0f) {
scale /= (max - min);
offset *= scale;
rescale(scale, offset);
}
System.out.println("Normalizing using: min= " + min + " max= " + max
+ ", through scaleAdd(" + scale + ", " + offset + ").");
min = 1000f;
max = -1000f;
for (int k = 0; k < size; k++) {
if (Float.isNaN(f[k])) {
System.out.println("NaN at k= " + k + " after normalization.");
f[k] = 0f;
continue;
}
min = Math.min(min, f[k]);
max = Math.max(max, f[k]);
}
System.out.println("After normalization: min= " + min + " max= " + max);
*/
}