import numbers
import random
import math
import torch
from torch_geometric.transforms import LinearTransformation
[docs]class RandomRotate(object):
r"""Rotates node positions around a specific axis by a randomly sampled
factor within a given interval.
Args:
degrees (tuple or float): Rotation interval from which the rotation
angle is sampled. If :obj:`degrees` is a number instead of a
tuple, the interval is given by :math:`[-\mathrm{degrees},
\mathrm{degrees}]`.
axis (int, optional): The rotation axis. (default: :obj:`0`)
"""
def __init__(self, degrees, axis=0):
if isinstance(degrees, numbers.Number):
degrees = (-abs(degrees), abs(degrees))
assert isinstance(degrees, (tuple, list)) and len(degrees) == 2
self.degrees = degrees
self.axis = axis
def __call__(self, data):
degree = math.pi * random.uniform(*self.degrees) / 180.0
sin, cos = math.sin(degree), math.cos(degree)
if data.pos.size(-1) == 2:
matrix = [[cos, sin], [-sin, cos]]
else:
if self.axis == 0:
matrix = [[1, 0, 0], [0, cos, sin], [0, -sin, cos]]
elif self.axis == 1:
matrix = [[cos, 0, -sin], [0, 1, 0], [sin, 0, cos]]
else:
matrix = [[cos, sin, 0], [-sin, cos, 0], [0, 0, 1]]
return LinearTransformation(torch.tensor(matrix))(data)
def __repr__(self):
return '{}({}, axis={})'.format(self.__class__.__name__, self.degrees,
self.axis)