要获取NumPy数组中唯一值的索引(数组中唯一值的第一个索引位置数组),只需传递np.unique()中的return_index参数以及数组。 >>> unique_values, indices_list = np.unique(a, return_index=True) >>> print(indices_list) [ 0 2 3 4 5 6 7 12 13 14] You can pass
:return: """a_part = np.argpartition(matrix, K, axis=axis)ifaxis ==0: row_index = np.arange(matrix.shape[1- axis]) a_sec_argsort_K = np.argsort(matrix[a_part[0:K, :], row_index], axis=axis)returna_part[0:K, :][a_sec_argsort_K, row_index]else: column_index = np.ar...
返回一个索引数组，这个数组可以将原始数组的元素按照从小到大（或指定顺序）排列。输入：待排序的数组。...
Index of sorted array on last axis(-1): [[2 0 1] [0 1 2] [0 2 1]] Index of a flattened sorted array: [3 2 6 0 4 8 5 7 1] Index of sorted array on axis 0: [[1 1 0] [2 2 2] [0 0 1]] When sorting on axis0, rows are compared. The elements in the first c...
:return: """a_part = np.argpartition(matrix, K, axis=axis)ifaxis ==0: row_index = np.arange(matrix.shape[1- axis]) a_sec_argsort_K = np.argsort(matrix[a_part[0:K, :], row_index], axis=axis)returna_part[0:K, :][a_sec_argsort_K, row_index]else: ...
vertices))) # 返回图的边集合 @property def edges(self): return self._E # 返回从具有索引 `v_i` 的顶点可达的顶点的内部索引列表 def get_neighbors(self, v_i): """ Return the internal indices of the vertices reachable from the vertex with index `v_i`. """ return [self._V2I[e.to...
In this section, you’ll work through some examples of real, useful data science operations: filtering, sorting, and aggregating data. Indexing Indexing uses many of the same idioms that normal Python code uses. You can use positive or negative indices to index from the front or back of the...
Return a sorted copy of an array. Args: a : array_like Array to be sorted. axis : int or None, optional Axis along which to sort. If None, the array is flattened before sorting. The default is -1, which sorts along the last axis. last axis is fastest for kind : {'quicksort'...
return a_part[0:K, :][a_sec_argsort_K, row_index]else:column_index = np.arange(matrix.shape[1 - axis])[:, None]a_sec_argsort_K = np.argsort(matrix[column_index, a_part[:, 0:K]], axis=axis)return a_part[:, 0:K][column_index, a_sec_argsort_K]# Example >>> dists =...
(self, y, y_pred):returnnp.mean((y - y_pred) **2)# 返回基本估计器defbase_estimator(self):returnMeanBaseEstimator()# 计算梯度defgrad(self, y, y_pred):return-2/len(y) * (y - y_pred)# 线搜索函数defline_search(self, y, y_pred, h_pred):#TODO:revise thisLp = np.sum((y ...