From d66c3dc971846c490a9f846e12be299a27856e69 Mon Sep 17 00:00:00 2001
From: Tomáš Jusko
Date: Sat, 30 Sep 2023 16:44:18 +0200
Subject: fix: PR requested changes

---
 pyecsca/sca/stacked_traces/combine.py   |  3 ++-
 pyecsca/sca/stacked_traces/correlate.py |  5 ++++-
 test/sca/test_stacked_correlate.py      | 12 +-----------
 3 files changed, 7 insertions(+), 13 deletions(-)

diff --git a/pyecsca/sca/stacked_traces/combine.py b/pyecsca/sca/stacked_traces/combine.py
index 6e11162..15d5235 100644
--- a/pyecsca/sca/stacked_traces/combine.py
+++ b/pyecsca/sca/stacked_traces/combine.py
@@ -224,7 +224,8 @@ class GPUTraceManager(BaseTraceManager):
         return int(
             chunk_memory_ratio * mem_size / element_size)
 
-    def get_traces_shape(self) -> Tuple[int, ...]:
+    @property
+    def traces_shape(self) -> Tuple[int, ...]:
         return self._traces.samples.shape
 
     def _gpu_combine1D(self,
diff --git a/pyecsca/sca/stacked_traces/correlate.py b/pyecsca/sca/stacked_traces/correlate.py
index 3e0f1d2..c5277d9 100644
--- a/pyecsca/sca/stacked_traces/correlate.py
+++ b/pyecsca/sca/stacked_traces/correlate.py
@@ -22,7 +22,7 @@ def gpu_pearson_corr(intermediate_values: npt.NDArray[np.number],
 
     if (len(intermediate_values.shape) != 1
         or (intermediate_values.shape[0]
-            != trace_manager.get_traces_shape()[0])):
+            != trace_manager.traces_shape[0])):
         raise ValueError("Intermediate values have to be a vector "
                          "as long as trace_count")
 
@@ -51,6 +51,9 @@ def _gpu_pearson_corr(samples: DeviceNDArray,
     :type samples: npt.NDArray[np.number]
     :param intermediate_values: A 1D array of shape (n,) containing the intermediate values.
     :type intermediate_values: npt.NDArray[np.number]
+    :param intermed_sum: A 1D array of shape (1,) containing the precomputed sum of the intermediate values.
+    :type intermed_sum: npt.NDArray[np.number]
+    :param intermed_sq_sum: A 1D array of shape (1,) containing the precomputed sum of the squares of the intermediate values.
     :param result: A 1D array of shape (m,) to store the resulting correlation coefficients.
     :type result: cuda.devicearray.DeviceNDArray
     """
diff --git a/test/sca/test_stacked_correlate.py b/test/sca/test_stacked_correlate.py
index ce5a9ed..954494f 100644
--- a/test/sca/test_stacked_correlate.py
+++ b/test/sca/test_stacked_correlate.py
@@ -35,17 +35,7 @@ def intermediate_values():
 
 
 def pearson_corr(samples, intermediate_values):
-    int_sum = np.sum(intermediate_values)
-    int_sq_sum = np.sum(np.square(intermediate_values))
-    samples_sum = np.sum(samples, axis=0)
-    samples_sq_sum = np.sum(np.square(samples), axis=0)
-    samples_intermed_sum = np.sum(
-        samples * intermediate_values[:, None], axis=0)
-    n = samples.shape[0]
-
-    return (n * samples_intermed_sum - int_sum * samples_sum) / \
-        (np.sqrt(n * int_sq_sum - int_sum ** 2) *
-         np.sqrt(n * samples_sq_sum - np.square(samples_sum)))
+    return np.corrcoef(samples, intermediate_values, rowvar=False)[-1, :-1]
 
 
 def test_pearson_coef_no_chunking(samples, gpu_manager, intermediate_values):
-- 
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