BUG: lib: Fix histogram problem with signed integer arrays.

An input such as

    np.histogram(np.array([-2, 0, 127], dtype=np.int8), bins="auto")

would raise the exception

    ValueError: Number of samples, -1, must be non-negative.

The problem was that the peak-to-peak value for the input array was
computed with the `ptp` method, which returned negative values for
signed integer arrays when the actual value was more than the
maximum signed value of the array's data type.

The fix is to use a peak-to-peak function that returns an
unsigned value for signed integer arrays.

Closes gh-14379.

1 files changed, 11 insertions, 0 deletions

diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py
index 4895a722c..dbf189f3e 100644
--- a/numpy/lib/tests/test_histograms.py
+++ b/numpy/lib/tests/test_histograms.py
@@ -8,6 +8,7 @@ from numpy.testing import (
     assert_array_almost_equal, assert_raises, assert_allclose,
     assert_array_max_ulp, assert_raises_regex, suppress_warnings,
     )
+import pytest
 
 
 class TestHistogram(object):
@@ -591,6 +592,16 @@ class TestHistogramOptimBinNums(object):
                 msg += " with datasize of {0}".format(testlen)
                 assert_equal(len(a), numbins, err_msg=msg)
 
+    @pytest.mark.parametrize("bins", ['auto', 'fd', 'doane', 'scott',
+                                      'stone', 'rice', 'sturges'])
+    def test_signed_integer_data(self, bins):
+        # Regression test for gh-14379.
+        a = np.array([-2, 0, 127], dtype=np.int8)
+        hist, edges = np.histogram(a, bins=bins)
+        hist32, edges32 = np.histogram(a.astype(np.int32), bins=bins)
+        assert_array_equal(hist, hist32)
+        assert_array_equal(edges, edges32)
+
     def test_simple_weighted(self):
         """
         Check that weighted data raises a TypeError