PyTorch torch.trapezoid Function
PyTorch torch Reference Manual
torch.trapezoidis a function in PyTorch used to compute trapezoidal integrals. This function uses the trapezoidal rule to perform numerical integration of a given function.
Function Definition
torch.trapezoid(y, x, dx)
Parameter Description
y: the function values to be integratedx: the values of the integration variable (optional)dx: the sampling spacing (used when x is not provided)
Usage Examples
Example
import torch
# Use dx for trapezoidal integration
y = torch.tensor([1.0, 2.0, 3.0, 4.0])
# dx=1.0 indicates uniform sampling spacing
result = torch.trapezoid(y, dx=1.0)
print("Trapezoidal integral result:", result)
# Integrate using x coordinates
x = torch.tensor([0.0, 0.5, 1.0, 1.5])
y2 = torch.tensor([0.0, 0.5, 1.0, 1.5])
result2 = torch.trapezoid(y2, x)
print("Integral result using x coordinates:", result2)
# Use dx for trapezoidal integration
y = torch.tensor([1.0, 2.0, 3.0, 4.0])
# dx=1.0 indicates uniform sampling spacing
result = torch.trapezoid(y, dx=1.0)
print("Trapezoidal integral result:", result)
# Integrate using x coordinates
x = torch.tensor([0.0, 0.5, 1.0, 1.5])
y2 = torch.tensor([0.0, 0.5, 1.0, 1.5])
result2 = torch.trapezoid(y2, x)
print("Integral result using x coordinates:", result2)
The output result is:
梯形积分结果: tensor(7.5000) 使用 x 坐标的积分结果: tensor(1.2500)
Other Extensions