o .wif @sddlZddlmZddlmZddlmZddlmZdededeeeffd d Z ddeded ed defddZ ddeded ed defddZ dS)N)Tensor)Literal)_check_same_shape)reducepredstargetreturncCs|j|jkrtd|jd|jdt||t|jdkr,td|jd|jd|jddks:|jddkrKtd|jdd|jdd||fS)zUpdate and returns variables required to compute Spectral Angle Mapper. Args: preds: Predicted tensor target: Ground truth tensor zEExpected `preds` and `target` to have the same data type. Got preds: z and target: .z@Expected `preds` and `target` to have BxCxHxW shape. Got preds: zSExpected channel dimension of `preds` and `target` to be larger than 1. Got preds: )dtype TypeErrorrlenshape ValueError)rrr^/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/torchmetrics/functional/image/sam.py _sam_updates,  relementwise_mean reduction)rsumnoneNcCsL||jdd}|jdd}|jdd}t|||dd}t||S)aWCompute Spectral Angle Mapper. Args: preds: estimated image target: ground truth image reduction: a method to reduce metric score over labels. - ``'elementwise_mean'``: takes the mean (default) - ``'sum'``: takes the sum - ``'none'`` or ``None``: no reduction will be applied Example: >>> from torch import rand >>> preds = rand([16, 3, 16, 16]) >>> target = rand([16, 3, 16, 16]) >>> preds, target = _sam_update(preds, target) >>> _sam_compute(preds, target) tensor(0.5914) r )dim)rnormtorchclampacosr)rrr dot_product preds_norm target_norm sam_scorerrr _sam_compute1s    r"cCst||\}}t|||S)aUniversal Spectral Angle Mapper. Args: preds: estimated image target: ground truth image reduction: a method to reduce metric score over labels. - ``'elementwise_mean'``: takes the mean (default) - ``'sum'``: takes the sum - ``'none'`` or ``None``: no reduction will be applied Return: Tensor with Spectral Angle Mapper score Raises: TypeError: If ``preds`` and ``target`` don't have the same data type. ValueError: If ``preds`` and ``target`` don't have ``BxCxHxW shape``. Example: >>> from torch import rand >>> from torchmetrics.functional.image import spectral_angle_mapper >>> preds = rand([16, 3, 16, 16],) >>> target = rand([16, 3, 16, 16]) >>> spectral_angle_mapper(preds, target) tensor(0.5914) References: [1] Roberta H. Yuhas, Alexander F. H. Goetz and Joe W. Boardman, "Discrimination among semi-arid landscape endmembers using the Spectral Angle Mapper (SAM) algorithm" in PL, Summaries of the Third Annual JPL Airborne Geoscience Workshop, vol. 1, June 1, 1992. )rr")rrrrrrspectral_angle_mapperQs' r#)r) rrtyping_extensionsrtorchmetrics.utilities.checksr"torchmetrics.utilities.distributedrtuplerr"r#rrrrs4     #