cumulative_sum
- Graph.cumulative_sum(x, axis=0, *, name=None)
Calculate the cumulative sum of a tensor along a specified dimension.
- Parameters
x (np.ndarray or Tensor) – The tensor whose elements you want to sum. It must have at least one dimension.
axis (int, optional) – The dimension along which you want to sum the tensor. Defaults to 0.
name (str, optional) – The name of the node.
- Returns
The cumulative sum of x along dimension axis.
- Return type
Examples
>>> x = np.array([1, 2, 3]) >>> y = np.array([[1, 2, 3], [4, 5, 6]])
Calculate the cumulative sum of an array.
>>> graph.cumulative_sum(x, axis=0, name="a") <Tensor: name="a", operation_name="cumulative_sum", shape=(3,)> >>> result = qctrl.functions.calculate_graph(graph=graph, output_node_names=["a"]) >>> result.output["a"]["value"] array([1, 3, 6])
Calculate the cumulative sum of a 2D array along its first dimension.
>>> graph.cumulative_sum(y, axis=0, name="b") <Tensor: name="b", operation_name="cumulative_sum", shape=(2, 3)> >>> result = qctrl.functions.calculate_graph(graph=graph, output_node_names=["b"]) >>> result.output["b"]["value"] array([[1, 2, 3], [5, 7, 9]])
Calculate the cumulative sum of a 2D array along its second dimension.
>>> graph.cumulative_sum(y, axis=1, name="c") <Tensor: name="c", operation_name="cumulative_sum", shape=(2, 3)> >>> result = qctrl.functions.calculate_graph(graph=graph, output_node_names=["c"]) >>> result.output["c"]["value"] array([[ 1, 3, 6], [ 4, 9, 15]])