PyTorch torch.cumulative_trapezoid Function
PyTorch torch Reference Manual
torch.cumulative_trapezoidIt is a function in PyTorch used to compute the cumulative trapezoidal integral of a function. It uses the trapezoidal rule to calculate the cumulative integral of the function at given points.
Function Definition
torch.cumulative_trapezoid(y, x=None, dx=1.0, dim=-1)
Parameters:
y(Tensor): The function values to be integrated.x(Tensor, optional): The x coordinates corresponding to the function. If None, the dx step size is used.dx(float, optional): The step size between x coordinates. Default is 1.0.dim(int, optional): The dimension along which to integrate. Default is -1.
Return Value:
torch.Tensor: Returns the cumulative integral result.
Usage Example
Example
import torch
# Create function values
y = torch.tensor([1.0, 2.0, 3.0, 4.0, 5.0])
# Cumulative trapezoidal integral
result = torch.cumulative_trapezoid(y)
print("Function values y:", y)
print("Cumulative integral result:", result)
# Create function values
y = torch.tensor([1.0, 2.0, 3.0, 4.0, 5.0])
# Cumulative trapezoidal integral
result = torch.cumulative_trapezoid(y)
print("Function values y:", y)
print("Cumulative integral result:", result)
The output is:
函数值 y: tensor([1., 2., 3., 4., 5.]) 累积积分结果: tensor([0.0000, 1.5000, 3.5000, 6.0000, 9.0000])
Example - Specifying x Coordinates
import torch
y = torch.tensor([1.0, 2.0, 3.0, 4.0, 5.0])
x = torch.tensor([0.0, 0.5, 1.0, 1.5, 2.0])
result = torch.cumulative_trapezoid(y, x)
print("Cumulative integral result:", result)
y = torch.tensor([1.0, 2.0, 3.0, 4.0, 5.0])
x = torch.tensor([0.0, 0.5, 1.0, 1.5, 2.0])
result = torch.cumulative_trapezoid(y, x)
print("Cumulative integral result:", result)
Other Extensions