BUG: Avoid inplace modification of input array in newton

optimize.newton previously changes the users input array when
performing calculations. This PR changes this to perform an explicit
copy of the array before any inplace modifications are performed.

scipy/optimize/tests/test_zeros.py

@@ -5,7 +5,8 @@
 
 from numpy.testing import (assert_warns, assert_,
                            assert_allclose,
-                           assert_equal)
+                           assert_equal,
+                           assert_array_equal)
 import numpy as np
 from numpy import finfo, power, nan, isclose
 
@@ -407,6 +408,14 @@ def test_deriv_zero_warning(self):
         assert_warns(RuntimeWarning, zeros.newton, func, 0.0, dfunc)
 
 
+    def test_newton_does_not_modify_x0(self):
+        # https://github.com/scipy/scipy/issues/9964
+        x0 = np.array([0.1, 3])
+        x0_copy = x0.copy()  # Copy to test for equality.
+        newton(np.sin, x0, np.cos)
+        assert_array_equal(x0, x0_copy)
+
+
 def test_gh_5555():
     root = 0.1
 

scipy/optimize/zeros.py

@@ -359,11 +359,13 @@ def _array_newton(func, x0, fprime, args, tol, maxiter, fprime2, full_output):
     Do not use this method directly. This method is called from `newton`
     when ``np.size(x0) > 1`` is ``True``. For docstring, see `newton`.
     """
+    # Explicitly copy `x0` as `p` will be modified inplace, but, the
+    # user's array should not be altered.
     try:
-        p = np.asarray(x0, dtype=float)
+        p = np.array(x0, copy=True, dtype=float)
     except TypeError:
         # can't convert complex to float
-        p = np.asarray(x0)
+        p = np.array(x0, copy=True)
 
     failures = np.ones_like(p, dtype=bool)
     nz_der = np.ones_like(failures)