我们可以先获取升序排列的索引列表,然后再将其倒序排列: descending_indices=np.argsort(arr)[::-1] 1. 这样我们就得到了按照值从大到小排列的索引列表descending_indices。 代码示例 下面是完整的代码示例: importnumpyasnp arr=np.array([3,1,4,1,5,9,2,6,5,3])descending_indices=np.argsort(arr)[::...
SortedIndices(Descending):[524031]SortedElements(Descending):[1086532] 通过对NumPy数组取反排序 在这个例子中,我们对NumPy数组取反,使用numy.argsort()按降序对其进行排序。在这里,我们将使用argsort()来获取索引,这些索引将按升序对原始数组进行排序。现在,为了获得按降序排序数组的索引,我们首先使用-arr对数组求反...
>>> s = sorted(student_objects, key=attrgetter('age'))#sort on secondary key>>> sorted(s, key=attrgetter('grade'), reverse=True)#now sort on primary key, descending[('dave','B', 10), ('jane','B', 12), ('john','A', 15)] 6)numpy中数组矩阵的排序方法argsort() argsort(a, ...
`a`thatindexdataalongthegivenaxisinsortedorder. 从中可以看出argsort函数返回的是数组值从小到大的索引值 Examples --- >>>x=np.array([3,1,2]) >>>np.argsort(x) array([1,2,0]) --- argsort函数返回的是数组值从小到大的索引值 [3,1,2]从小到大为[1,2,3],期对应的索引为[1,2,0] stata...
[:, i] for kv in knn_shap_values]), axis=0) sorted_indices_knn = np.argsort(mean_knn_shap_values)[::-1] # Sort indices in descending order sorted_knn_shap_values = mean_knn_shap_values[sorted_indices_knn][:10] # Keep top 10 sorted_knn_features = train_X.columns[sorted_...
argsort:它是沿指定轴的间接排序,本文不讲解。 msort:按值对 input 张量沿其第一维以升序排序。torch.msort(t) 等效于 torch.sort(t, dim=0)。 sort 可以降序或升序,参数说明如下: torch.sort(input, dim=-1, descending=False, stable=False, *, out=None) ...
void selectionSortDescending(int arr[]) { int n = arr.length; // Start by finding the smallest element to put in the very back // One by one move boundary of unsorted subarray for (int i = n-1; i >= 0; i--) { // Find the minimum element in unsorted array int min_idx = ...
descending argsort: [4 6 3 2 5 1 7 0]''' c++ #include <vector>#include<iostream>usingnamespacestd; template<typename T>vector<int> sort_indexes(constvector<T> & v,boolreverse=false) {//initialize original index locationsvector<int>idx(v.size());for(inti =0; i != idx.size(); ...
void selectionSortDescending(int arr[]) { int n = arr.length; // Start by finding the smallest element to put in the very back // One by one move boundary of unsorted subarray for (int i = n-1; i >= 0; i--) { // Find the minimum element in unsorted array int min_idx = ...
idx = scores.argsort(descending=True) # descending rank by score bboxes = bboxes[idx] scores = scores[idx] if len(scores) > pre_num: bboxes = bboxes[:pre_num] scores = scores[:pre_num] # non-maximum suppression, we use cuda version of nms ...