matplotlib
diff --git a/‎lib/matplotlib/axes/_axes.py
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+1-1Lines changed: 1 addition & 1 deletion b/‎lib/matplotlib/axes/_axes.py
Copy file name to clipboardExpand all lines: lib/matplotlib/axes/_axes.py
+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎lib/matplotlib/tests/test_axes.py
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+21Lines changed: 21 additions & 0 deletions b/‎lib/matplotlib/tests/test_axes.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_axes.py
+21Lines changed: 21 additions & 0 deletions
@@ -2080,7 +2080,7 @@ def xcorr(self, x, y, normed=True, detrend=mlab.detrend_none,
         correls = np.correlate(x, y, mode="full")
 
         if normed:
-            correls /= np.sqrt(np.dot(x, x) * np.dot(y, y))
+            correls = correls / np.sqrt(np.dot(x, x) * np.dot(y, y))
 
         if maxlags is None:
             maxlags = Nx - 1
 
@@ -171,6 +171,27 @@ def test_acorr(fig_test, fig_ref):
     ax_ref.axhline(y=0, xmin=0, xmax=1)
 
 
+@check_figures_equal(extensions=["png"])
+def test_acorr_integers(fig_test, fig_ref):
+    np.random.seed(19680801)
+    Nx = 51
+    x = (np.random.rand(Nx) * 10).cumsum()
+    x = (np.ceil(x)).astype(np.int64)
+    maxlags = Nx-1
+
+    ax_test = fig_test.subplots()
+    ax_test.acorr(x, maxlags=maxlags)
+
+    ax_ref = fig_ref.subplots()
+
+    # Normalized autocorrelation
+    norm_auto_corr = np.correlate(x, x, mode="full")/np.dot(x, x)
+    lags = np.arange(-maxlags, maxlags+1)
+    norm_auto_corr = norm_auto_corr[Nx-1-maxlags:Nx+maxlags]
+    ax_ref.vlines(lags, [0], norm_auto_corr)
+    ax_ref.axhline(y=0, xmin=0, xmax=1)
+
+
 @check_figures_equal(extensions=["png"])
 def test_spy(fig_test, fig_ref):
     np.random.seed(19680801)