whatever

Jiabing Li
1 parent 0954c632
Showing 4 changed files with 23 additions and 21 deletions Show diff stats
python/network.py
python/network_dpy.py
stim/cuda/templates/gaussian_blur.cuh
stim/image/image.h
@@ -318,14 +318,14 @@ class Network:
         R = (200, 200, 200)
         #generate a meshgrid of the appropriate size and resolution to surround the network
-        lower, upper = self.aabb(self.N, self.F)    #get the space occupied by the network
+        lower, upper = self.aabb()    #get the space occupied by the network
         x = np.linspace(lower[0], upper[0], R[0])   #get the grid points for uniform sampling of this space
         y = np.linspace(lower[1], upper[1], R[1])
         z = np.linspace(lower[2], upper[2], R[2])
         X, Y, Z = np.meshgrid(x, y, z)
         #Z = 150 * numpy.ones(X.shape)
-        
+       
         Q = np.stack((X, Y, Z), 3)
@@ -14,7 +14,6 @@ import math
-alkjasfdljkhfsadlkjhfsad
 class Point:
        def __init__(self, x, y, z, radius):
            self.x = x
@@ -9,34 +9,34 @@
 namespace stim{
-	namespace cuda{
+	namespace cuda {
 		template<typename T>
-		void gen_gaussian(T* out, T sigma, unsigned int width){
+		void gen_gaussian(T* out, T sigma, unsigned int width) {
 			//fill the kernel with a gaussian
-			for(unsigned int xi = 0; xi < width; xi++){
+			for (unsigned int xi = 0; xi < width; xi++) {
-				float x = (float)xi - (float)(width/2);	//calculate the x position of the gaussian
-				float g = 1.0 / (sigma * sqrt(2 * 3.14159)) * exp( - (x*x) / (2*sigma*sigma) );
+				float x = (float)xi - (float)(width / 2);	//calculate the x position of the gaussian
+				float g = 1.0 / (sigma * sqrt(2 * 3.14159)) * exp(-(x*x) / (2 * sigma*sigma));
 				out[xi] = g;
 			}
 		}
 		template<typename T>
-		void tex_gaussian_blur2(T* out, T sigma, unsigned int x, unsigned int y, cudaTextureObject_t texObj, cudaArray* cuArray){
+		void tex_gaussian_blur2(T* out, T sigma, unsigned int x, unsigned int y, cudaTextureObject_t texObj, cudaArray* cuArray) {
 			//allocate space for the kernel
 			unsigned int kwidth = sigma * 8 + 1;
-			float* kernel0 = (float*) malloc( kwidth * sizeof(float) );
+			float* kernel0 = (float*)malloc(kwidth * sizeof(float));
 			//fill the kernel with a gaussian
 			gen_gaussian(kernel0, sigma, kwidth);
 			//copy the kernel to the GPU
 			T* gpuKernel0;
-			HANDLE_ERROR(cudaMalloc(&gpuKernel0, kwidth*sizeof(T)));
+			HANDLE_ERROR(cudaMalloc(&gpuKernel0, kwidth * sizeof(T)));
 			HANDLE_ERROR(cudaMemcpy(gpuKernel0, kernel0, kwidth * sizeof(T), cudaMemcpyHostToDevice));
 			//perform the gaussian blur as a separable convolution
@@ -48,18 +48,18 @@ namespace stim{
 		}
 		template<typename T>
-		void gpu_gaussian_blur2(T* image, T sigma, unsigned int x, unsigned int y){
+		void gpu_gaussian_blur2(T* image, T sigma, unsigned int x, unsigned int y) {
 			//allocate space for the kernel
 			unsigned int kwidth = sigma * 8 + 1;
-			float* kernel0 = (float*) malloc( kwidth * sizeof(float) );
+			float* kernel0 = (float*)malloc(kwidth * sizeof(float));
 			//fill the kernel with a gaussian
 			gen_gaussian(kernel0, sigma, kwidth);
 			//copy the kernel to the GPU
 			T* gpuKernel0;
-			HANDLE_ERROR(cudaMalloc(&gpuKernel0, kwidth*sizeof(T)));
+			HANDLE_ERROR(cudaMalloc(&gpuKernel0, kwidth * sizeof(T)));
 			HANDLE_ERROR(cudaMemcpy(gpuKernel0, kernel0, kwidth * sizeof(T), cudaMemcpyHostToDevice));
 			//perform the gaussian blur as a separable convolution
@@ -71,21 +71,24 @@ namespace stim{
 		/// Applies a Gaussian blur to a 2D image stored on the CPU
 		template<typename T>
-		void cpu_gaussian_blur2(T* image, T sigma, unsigned int x, unsigned int y){
+		void cpu_gaussian_blur2(T* image, T sigma, unsigned int x, unsigned int y, float &gpu_time) {
+			gpuTimer_start();
 			//allocate space for the kernel
 			unsigned int kwidth = sigma * 8 + 1;
-			float* kernel0 = (float*) malloc( kwidth * sizeof(float) );
+			float* kernel0 = (float*)malloc(kwidth * sizeof(float));
 			//fill the kernel with a gaussian
 			gen_gaussian(kernel0, sigma, kwidth);
 			//perform the gaussian blur as a separable convolution
 			stim::cuda::cpu_conv2sep<float>(image, x, y, kernel0, kwidth, kernel0, kwidth);
-			
+			gpu_time = gpuTimer_end();
+
 		}
+	
-	};
-};
+	}
+}
 #endif
@@ -276,8 +276,8 @@ public:
 		allocate(cols, rows, channels);			//allocate space for the image
 		size_t img_bytes = bytes();
 		unsigned char* cv_ptr = (unsigned char*)cvImage.data;		
-		if (C() == 1)														//if this is a single-color image, just copy the data
-			type_copy<unsigned char, T>(cv_ptr, img, size());
+		//if (C() == 1)														//if this is a single-color image, just copy the data
+		type_copy<unsigned char, T>(cv_ptr, img, size());
 		//memcpy(img, cv_ptr, bytes());
 		if(C() == 3)														//if this is a 3-color image, OpenCV uses BGR interleaving
 			from_opencv(cv_ptr, X(), Y());