Fix single update in pearson corrcoef (Lightning-AI#2019)

* fix
* changelog

Author: matsumotosan

CHANGELOG.md

@@ -26,6 +26,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+- Fixed bug in `PearsonCorrCoef` is updated on single samples at a time ([#2019](https://github.com/Lightning-AI/torchmetrics/pull/2019)
+
+
 - Fixed support for pixelwise MSE ([#2017](https://github.com/Lightning-AI/torchmetrics/pull/2017)
 
 

src/torchmetrics/functional/regression/pearson.py

@@ -57,11 +57,9 @@ def _pearson_corrcoef_update(
     if weights is not None:
         _check_data_shape_to_weights(preds, weights)
 
-    cond = n_prior.mean() > 0
-
     n_obs = preds.shape[0] if weights is None else weights.sum()
+    cond = n_prior.mean() > 0 or n_obs == 1
 
-    # Calculate means
     if cond:
         if weights is None:
             mx_new = (n_prior * mean_x + preds.sum(0)) / (n_prior + n_obs)

tests/unittests/regression/test_pearson.py

@@ -193,3 +193,20 @@ def test_pearsons_warning_on_small_input(dtype, scale):
     target = scale * torch.randn(100, dtype=dtype)
     with pytest.warns(UserWarning, match="The variance of predictions or target is close to zero.*"):
         pearson_corrcoef(preds, target)
+
+
+def test_single_sample_update():
+    """See issue: https://github.com/Lightning-AI/torchmetrics/issues/2014."""
+    metric = PearsonCorrCoef()
+
+    # Works
+    metric(torch.tensor([3.0, -0.5, 2.0, 7.0]), torch.tensor([2.5, 0.0, 2.0, 8.0]))
+    res1 = metric.compute()
+    metric.reset()
+
+    metric(torch.tensor([3.0]), torch.tensor([2.5]))
+    metric(torch.tensor([-0.5]), torch.tensor([0.0]))
+    metric(torch.tensor([2.0]), torch.tensor([2.0]))
+    metric(torch.tensor([7.0]), torch.tensor([8.0]))
+    res2 = metric.compute()
+    assert torch.allclose(res1, res2)