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#include "Halide.h"
#include <stdio.h>
using namespace Halide;
int main(int argc, char **argv) {
Var x, y;
const double tol = 0.01;
{
// Make a random image and check its statistics.
Func f;
f(x, y) = random_float();
f.vectorize(x, 4);
f.parallel(y);
Buffer<float> rand_image = f.realize({1024, 1024});
// Do some tests for randomness.
Func g;
g(x, y) = cast<double>(rand_image(x, y));
RDom r(rand_image);
Expr val = g(r.x, r.y);
double mean = evaluate<double>(sum(val)) / (1024 * 1024);
double variance = evaluate<double>(sum(pow(val - (float)mean, 2))) / (1024 * 1024 - 1);
// Also check the mean and variance of the gradient in x and y to check for pixel correlations.
Expr dx = g(r.x, r.y) - g((r.x + 1) % 1024, r.y);
Expr dy = g(r.x, r.y) - g(r.x, (r.y + 1) % 1024);
double mean_dx = evaluate<double>(sum(dx)) / (1024 * 1024);
double variance_dx = evaluate<double>(sum(pow(dx - (float)mean_dx, 2))) / (1024 * 1024 - 1);
double mean_dy = evaluate<double>(sum(dy)) / (1024 * 1024);
double variance_dy = evaluate<double>(sum(pow(dy - (float)mean_dy, 2))) / (1024 * 1024 - 1);
if (fabs(mean - 0.5) > tol) {
printf("Bad mean: %f\n", mean);
return 1;
}
if (fabs(variance - 1.0 / 12) > tol) {
printf("Bad variance: %f\n", variance);
return 1;
}
if (fabs(mean_dx) > tol) {
printf("Bad mean_dx: %f\n", mean_dx);
return 1;
}
if (fabs(variance_dx - 1.0 / 6) > tol) {
printf("Bad variance_dx: %f\n", variance_dx);
return 1;
}
if (fabs(mean_dy) > tol) {
printf("Bad mean_dy: %f\n", mean_dy);
return 1;
}
if (fabs(variance_dy - 1.0 / 6) > tol) {
printf("Bad variance_dy: %f\n", variance_dy);
return 1;
}
}
// The same random seed should produce the same image, and
// different random seeds should produce statistically independent
// images.
{
Param<int> seed;
Func f;
f(x, y) = cast<double>(random_float(seed));
seed.set(0);
Buffer<double> im1 = f.realize({1024, 1024});
Buffer<double> im2 = f.realize({1024, 1024});
Func g;
g(x, y) = f(x, y);
seed.set(1);
Buffer<double> im3 = g.realize({1024, 1024});
RDom r(im1);
Expr v1 = im1(r.x, r.y);
Expr v2 = im2(r.x, r.y);
Expr v3 = im3(r.x, r.y);
double e1 = evaluate<double>(sum(abs(v1 - v2))) / (1024 * 1024);
double e2 = evaluate<double>(sum(abs(v1 - v3))) / (1024 * 1024);
if (e1 != 0.0) {
printf("The same random seed should produce the same image. "
"Instead the mean absolute difference was: %f\n",
e1);
return 1;
}
if (fabs(e2 - 1.0 / 3) > 0.01) {
printf("Different random seeds should produce different images. "
"The mean absolute difference should be 1/3 but was %f\n",
e2);
return 1;
}
}
// Test random ints as well.
{
Func f;
f(x, y) = random_int();
Buffer<int> im = f.realize({1024, 1024});
// Count the number of set bits;
RDom r(im);
Expr val = f(r.x, r.y);
int set_bits = evaluate<int>(sum(popcount(val)));
// It should be that about half of them are set
int correct = 512 * 1024 * 32;
if (fabs(double(set_bits) / correct - 1) > tol) {
printf("Set bits was %d instead of %d\n", set_bits, correct);
return 1;
}
// Check to make sure adjacent bits are uncorrelated.
Expr val2 = val ^ (val * 2);
set_bits = evaluate<int>(sum(popcount(val2)));
if (fabs(double(set_bits) / correct - 1) > tol) {
printf("Set bits was %d instead of %d\n", set_bits, correct);
return 1;
}
}
// Check independence and dependence.
{
// Make two random variables
Expr r1 = cast<double>(random_float());
Expr r2 = cast<double>(random_float());
Func f;
f(x, y) = r1 + r1 - 1.0f;
Func g;
g(x, y) = r1 + r2 - 1.0f;
// f is the sum of two dependent (equal) random variables, so should have variance 1/3
// g is the sum of two independent random variables, so should have variance 1/6
const int S = 1024;
RDom r(0, S, 0, S);
Expr f_val = f(r.x, r.y);
Expr g_val = g(r.x, r.y);
double f_var = evaluate<double>(sum(f_val * f_val)) / (S * S - 1);
double g_var = evaluate<double>(sum(g_val * g_val)) / (S * S - 1);
if (fabs(f_var - 1.0 / 3) > tol) {
printf("Variance of f was supposed to be 1/3: %f\n", f_var);
return 1;
}
if (fabs(g_var - 1.0 / 6) > tol) {
printf("Variance of g was supposed to be 1/6 %f\n", g_var);
return 1;
}
}
printf("Success!\n");
return 0;
}
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