codebase / stimlib

Commit 8da0df3ee72d360aef8d26bc1186853477c76cbd

Authored by Jiabing Li
1 parent 0954c632

whatever

Showing 4 changed files with 23 additions and 21 deletions   Show diff stats
Inline Side-by-side
python/network.py
  Show/Hide comments   View file @8da0df3
... ... @@ -318,14 +318,14 @@ class Network:
318 318 R = (200, 200, 200)
319 319  
320 320 #generate a meshgrid of the appropriate size and resolution to surround the network
321   - lower, upper = self.aabb(self.N, self.F) #get the space occupied by the network
  321 + lower, upper = self.aabb() #get the space occupied by the network
322 322 x = np.linspace(lower[0], upper[0], R[0]) #get the grid points for uniform sampling of this space
323 323 y = np.linspace(lower[1], upper[1], R[1])
324 324 z = np.linspace(lower[2], upper[2], R[2])
325 325 X, Y, Z = np.meshgrid(x, y, z)
326 326 #Z = 150 * numpy.ones(X.shape)
327 327  
328   -
  328 +
329 329 Q = np.stack((X, Y, Z), 3)
330 330  
331 331  
... ...
python/network_dpy.py
  Show/Hide comments   View file @8da0df3
... ... @@ -14,7 +14,6 @@ import math
14 14  
15 15  
16 16  
17   -alkjasfdljkhfsadlkjhfsad
18 17 class Point:
19 18 def __init__(self, x, y, z, radius):
20 19 self.x = x
... ...
stim/cuda/templates/gaussian_blur.cuh
  Show/Hide comments   View file @8da0df3
... ... @@ -9,34 +9,34 @@
9 9  
10 10  
11 11 namespace stim{
12   - namespace cuda{
  12 + namespace cuda {
13 13  
14 14 template<typename T>
15   - void gen_gaussian(T* out, T sigma, unsigned int width){
  15 + void gen_gaussian(T* out, T sigma, unsigned int width) {
16 16  
17 17 //fill the kernel with a gaussian
18   - for(unsigned int xi = 0; xi < width; xi++){
  18 + for (unsigned int xi = 0; xi < width; xi++) {
19 19  
20   - float x = (float)xi - (float)(width/2); //calculate the x position of the gaussian
21   - float g = 1.0 / (sigma * sqrt(2 * 3.14159)) * exp( - (x*x) / (2*sigma*sigma) );
  20 + float x = (float)xi - (float)(width / 2); //calculate the x position of the gaussian
  21 + float g = 1.0 / (sigma * sqrt(2 * 3.14159)) * exp(-(x*x) / (2 * sigma*sigma));
22 22 out[xi] = g;
23 23 }
24 24  
25 25 }
26 26  
27 27 template<typename T>
28   - void tex_gaussian_blur2(T* out, T sigma, unsigned int x, unsigned int y, cudaTextureObject_t texObj, cudaArray* cuArray){
  28 + void tex_gaussian_blur2(T* out, T sigma, unsigned int x, unsigned int y, cudaTextureObject_t texObj, cudaArray* cuArray) {
29 29  
30 30 //allocate space for the kernel
31 31 unsigned int kwidth = sigma * 8 + 1;
32   - float* kernel0 = (float*) malloc( kwidth * sizeof(float) );
  32 + float* kernel0 = (float*)malloc(kwidth * sizeof(float));
33 33  
34 34 //fill the kernel with a gaussian
35 35 gen_gaussian(kernel0, sigma, kwidth);
36 36  
37 37 //copy the kernel to the GPU
38 38 T* gpuKernel0;
39   - HANDLE_ERROR(cudaMalloc(&gpuKernel0, kwidth*sizeof(T)));
  39 + HANDLE_ERROR(cudaMalloc(&gpuKernel0, kwidth * sizeof(T)));
40 40 HANDLE_ERROR(cudaMemcpy(gpuKernel0, kernel0, kwidth * sizeof(T), cudaMemcpyHostToDevice));
41 41  
42 42 //perform the gaussian blur as a separable convolution
... ... @@ -48,18 +48,18 @@ namespace stim{
48 48 }
49 49  
50 50 template<typename T>
51   - void gpu_gaussian_blur2(T* image, T sigma, unsigned int x, unsigned int y){
  51 + void gpu_gaussian_blur2(T* image, T sigma, unsigned int x, unsigned int y) {
52 52  
53 53 //allocate space for the kernel
54 54 unsigned int kwidth = sigma * 8 + 1;
55   - float* kernel0 = (float*) malloc( kwidth * sizeof(float) );
  55 + float* kernel0 = (float*)malloc(kwidth * sizeof(float));
56 56  
57 57 //fill the kernel with a gaussian
58 58 gen_gaussian(kernel0, sigma, kwidth);
59 59  
60 60 //copy the kernel to the GPU
61 61 T* gpuKernel0;
62   - HANDLE_ERROR(cudaMalloc(&gpuKernel0, kwidth*sizeof(T)));
  62 + HANDLE_ERROR(cudaMalloc(&gpuKernel0, kwidth * sizeof(T)));
63 63 HANDLE_ERROR(cudaMemcpy(gpuKernel0, kernel0, kwidth * sizeof(T), cudaMemcpyHostToDevice));
64 64  
65 65 //perform the gaussian blur as a separable convolution
... ... @@ -71,21 +71,24 @@ namespace stim{
71 71  
72 72 /// Applies a Gaussian blur to a 2D image stored on the CPU
73 73 template<typename T>
74   - void cpu_gaussian_blur2(T* image, T sigma, unsigned int x, unsigned int y){
  74 + void cpu_gaussian_blur2(T* image, T sigma, unsigned int x, unsigned int y, float &gpu_time) {
75 75  
  76 + gpuTimer_start();
76 77 //allocate space for the kernel
77 78 unsigned int kwidth = sigma * 8 + 1;
78   - float* kernel0 = (float*) malloc( kwidth * sizeof(float) );
  79 + float* kernel0 = (float*)malloc(kwidth * sizeof(float));
79 80  
80 81 //fill the kernel with a gaussian
81 82 gen_gaussian(kernel0, sigma, kwidth);
82 83  
83 84 //perform the gaussian blur as a separable convolution
84 85 stim::cuda::cpu_conv2sep<float>(image, x, y, kernel0, kwidth, kernel0, kwidth);
85   -
  86 + gpu_time = gpuTimer_end();
  87 +
86 88 }
  89 +
87 90  
88   - };
89   -};
  91 + }
  92 +}
90 93  
91 94 #endif
... ...
stim/image/image.h
  Show/Hide comments   View file @8da0df3
... ... @@ -276,8 +276,8 @@ public:
276 276 allocate(cols, rows, channels); //allocate space for the image
277 277 size_t img_bytes = bytes();
278 278 unsigned char* cv_ptr = (unsigned char*)cvImage.data;
279   - if (C() == 1) //if this is a single-color image, just copy the data
280   - type_copy<unsigned char, T>(cv_ptr, img, size());
  279 + //if (C() == 1) //if this is a single-color image, just copy the data
  280 + type_copy<unsigned char, T>(cv_ptr, img, size());
281 281 //memcpy(img, cv_ptr, bytes());
282 282 if(C() == 3) //if this is a 3-color image, OpenCV uses BGR interleaving
283 283 from_opencv(cv_ptr, X(), Y());
... ...