[Bugfix] Fix mean when empty tensor for readout (#308)

Solving the edge case when mean of an empty tensor returns nan

---------

pyqtorch/noise/readout.py

@@ -148,7 +148,11 @@ def create_confusion_matrices(noise_matrix: Tensor, error_probability: float) ->
     confusion_matrices = []
     for i in range(noise_matrix.size()[1]):
         column_tensor = noise_matrix[:, i]
-        flip_proba = column_tensor[column_tensor < error_probability].mean().item()
+        flip_proba = (
+            flip_proba.mean().item()
+            if len(flip_proba := column_tensor[column_tensor < error_probability]) > 0
+            else 0.0
+        )
         confusion_matrix = torch.tensor(
             [[1.0 - flip_proba, flip_proba], [flip_proba, 1.0 - flip_proba]],
             dtype=torch.float64,

tests/test_readout.py

@@ -11,6 +11,7 @@
 from pyqtorch.noise.readout import (
     WhiteNoise,
     bs_bitflip_corruption,
+    create_confusion_matrices,
     create_noise_matrix,
     sample_to_matrix,
 )
@@ -19,6 +20,17 @@
 from pyqtorch.utils_distributions import js_divergence, js_divergence_counters
 
 
+def test_noise_matrix():
+    noise_mat = torch.tensor([[0.5679, 0.7676]])
+    zero_prob_mat = torch.tensor(
+        [[1.0, 0.0], [0.0, 1.0]],
+        dtype=torch.float64,
+    )
+    assert torch.allclose(
+        create_confusion_matrices(noise_mat, 0.1), torch.stack([zero_prob_mat] * 2)
+    )
+
+
 @pytest.mark.parametrize(
     "error_probability, counters, exp_corrupted_counters, n_qubits",
     [