| 1810 | self.a: float | None = None |
| 1811 | |
| 1812 | def randomize(self, data: Any | None = None) -> None: |
| 1813 | super().randomize(None) |
| 1814 | if not self._do_transform: |
| 1815 | return None |
| 1816 | self.x1 = self.R.uniform(low=self.sigma1_x[0], high=self.sigma1_x[1]) |
| 1817 | self.y1 = self.R.uniform(low=self.sigma1_y[0], high=self.sigma1_y[1]) |
| 1818 | self.z1 = self.R.uniform(low=self.sigma1_z[0], high=self.sigma1_z[1]) |
| 1819 | sigma2_x = (self.sigma2_x, self.x1) if not isinstance(self.sigma2_x, Iterable) else self.sigma2_x |
| 1820 | sigma2_y = (self.sigma2_y, self.y1) if not isinstance(self.sigma2_y, Iterable) else self.sigma2_y |
| 1821 | sigma2_z = (self.sigma2_z, self.z1) if not isinstance(self.sigma2_z, Iterable) else self.sigma2_z |
| 1822 | self.x2 = self.R.uniform(low=sigma2_x[0], high=sigma2_x[1]) |
| 1823 | self.y2 = self.R.uniform(low=sigma2_y[0], high=sigma2_y[1]) |
| 1824 | self.z2 = self.R.uniform(low=sigma2_z[0], high=sigma2_z[1]) |
| 1825 | self.a = self.R.uniform(low=self.alpha[0], high=self.alpha[1]) |
| 1826 | |
| 1827 | def __call__(self, img: NdarrayOrTensor, randomize: bool = True) -> NdarrayOrTensor: |
| 1828 | img = convert_to_tensor(img, track_meta=get_track_meta()) |