在numpy数组中找到独特点(Finding unique points in numpy array)

在numpy数组中找到独特点(Finding unique points in numpy array)

在numpy数组中找到唯一的x，y点（删除重复项）的更快方法是：

points = numpy.random.randint(0, 5, (10,2))

我想将点转换为复数，然后检查独特的，但这似乎相当复杂：

b = numpy.unique(points[:,0] + 1j * points[:,1]) points = numpy.column_stack((b.real, b.imag))

What is a faster way of finding unique x,y points (removing duplicates) in a numpy array like:

points = numpy.random.randint(0, 5, (10,2))

I thought of converting points to a complex numbers and then checking for unique, but that seems rather convoluted:

b = numpy.unique(points[:,0] + 1j * points[:,1]) points = numpy.column_stack((b.real, b.imag))

最满意答案

我会这样做：

numpy.array(list(set(tuple(p) for p in points)))

对于最常见情况下的快速解决方案，也许这个配方会让你感兴趣： http : //code.activestate.com/recipes/52560-remove-duplicates-from-a-sequence/

I would do it like this:

numpy.array(list(set(tuple(p) for p in points)))

For the fast solution in the most general case, maybe this recipe would interest you: http://code.activestate.com/recipes/52560-remove-duplicates-from-a-sequence/