一个简单的景观生态学“斑块”patch计数算法

#### Patch counting
def expand_array(square_array):
    sh = square_array.shape[0]
    new_array = []
    new_array.extend([0]*(sh+2))
    for i in range(sh):
        new_array.append(0)
        new_array.extend(square_array[i,:])
        new_array.append(0)

    new_array.extend([0]*(sh+2))
    new_array=np.array(new_array).reshape(sh+2,sh+2)
    return new_array

        
def recursive_find_all_points(i,j,data,point_result,flag):
    
    ### if 0, ignore
    if data[i,j]==0:
        return point_result
    ### if already considered, continue
    if (i,j) in [e for w in point_result.values() for e in w]:
        return point_result
    ### if it's a new patch, count it.
    if flag == "origin":
#         print('1 block!')
        point_result[len(point_result)] = []
    point_result[len(point_result)-1].append((i,j)) 
    
    ### recursion in four directions
    for direction in [(-1,0),(1,0),(0,-1),(0,1)]:
        point_result = recursive_find_all_points(i+direction[0], j+direction[1], data, point_result, flag="derived")

    return point_result


def get_patches(array):
    """
        Remember to only input 0,1 matrix. Which means only one class is calculated each time.
    """
    expanded_array = expand_array(array)
    patches = get_points_result(expanded_array)
    return patches

截屏2022-06-26 下午8.35.26.png

写了一个景观生态学“斑块”统计的比较简单的递归算法，每次发现一个斑块（这里指考虑了标准化的正方形区域），向四个方向扩散并判断连接性，直到全部碰壁。然后把这些点放入列表里，避免重复计算。