path: root/pkgs/applications/science/math/sage/patches/numpy-1.14.3.patch

diff --git a/src/doc/en/faq/faq-usage.rst b/src/doc/en/faq/faq-usage.rst
index 79b4205fd3..9a89bd2136 100644
--- a/src/doc/en/faq/faq-usage.rst
+++ b/src/doc/en/faq/faq-usage.rst
@@ -338,7 +338,7 @@ ints. For example::
     sage: RealNumber = float; Integer = int
     sage: from scipy import stats
     sage: stats.ttest_ind(list([1,2,3,4,5]),list([2,3,4,5,.6]))
-    Ttest_indResult(statistic=0.076752955645333687, pvalue=0.94070490247380478)
+    Ttest_indResult(statistic=0.0767529..., pvalue=0.940704...)
     sage: stats.uniform(0,15).ppf([0.5,0.7])
     array([  7.5,  10.5])
 
diff --git a/src/doc/en/thematic_tutorials/numerical_sage/cvxopt.rst b/src/doc/en/thematic_tutorials/numerical_sage/cvxopt.rst
index 314811c42b..e5f54ec4c2 100644
--- a/src/doc/en/thematic_tutorials/numerical_sage/cvxopt.rst
+++ b/src/doc/en/thematic_tutorials/numerical_sage/cvxopt.rst
@@ -48,11 +48,13 @@ we could do the following.
     sage: B = numpy.array([1.0]*5)
     sage: B.shape=(5,1)
     sage: print(B)
-    [[ 1.]
-     [ 1.]
-     [ 1.]
-     [ 1.]
-     [ 1.]]
+    [[1.]
+     [1.]
+     [1.]
+     [1.]
+     [1.]]
+
+
     sage: print(A)
     [ 2.00e+00  3.00e+00     0         0         0    ]
     [ 3.00e+00     0      4.00e+00     0      6.00e+00]
diff --git a/src/doc/en/thematic_tutorials/numerical_sage/numpy.rst b/src/doc/en/thematic_tutorials/numerical_sage/numpy.rst
index 5b89cd75ee..e50b2ea5d4 100644
--- a/src/doc/en/thematic_tutorials/numerical_sage/numpy.rst
+++ b/src/doc/en/thematic_tutorials/numerical_sage/numpy.rst
@@ -84,7 +84,7 @@ well as take slices
     sage: l[3]
     3.0
     sage: l[3:6]
-    array([ 3.,  4.,  5.])
+    array([3., 4., 5.])
 
 You can do basic arithmetic operations
 
@@ -147,11 +147,11 @@ also do matrix vector multiplication, and matrix addition
     sage: n = numpy.matrix([[1,2],[3,4]],dtype=float)
     sage: v = numpy.array([[1],[2]],dtype=float)
     sage: n*v
-    matrix([[  5.],
-            [ 11.]])
+    matrix([[ 5.],
+            [11.]])
     sage: n+n
-    matrix([[ 2.,  4.],
-            [ 6.,  8.]])
+    matrix([[2., 4.],
+            [6., 8.]])
 
 If ``n`` was created with :meth:`numpy.array`, then to do matrix vector
 multiplication, you would use ``numpy.dot(n,v)``.
@@ -170,11 +170,11 @@ to manipulate
             22.,  23.,  24.])
     sage: n.shape=(5,5)
     sage: n
-    array([[  0.,   1.,   2.,   3.,   4.],
-           [  5.,   6.,   7.,   8.,   9.],
-           [ 10.,  11.,  12.,  13.,  14.],
-           [ 15.,  16.,  17.,  18.,  19.],
-           [ 20.,  21.,  22.,  23.,  24.]])
+    array([[ 0.,  1.,  2.,  3.,  4.],
+           [ 5.,  6.,  7.,  8.,  9.],
+           [10., 11., 12., 13., 14.],
+           [15., 16., 17., 18., 19.],
+           [20., 21., 22., 23., 24.]])
 
 This changes the one-dimensional array into a `5\times 5` array.
 
@@ -187,8 +187,8 @@ NumPy arrays can be sliced as well
     sage: n=numpy.array(range(25),dtype=float)
     sage: n.shape=(5,5)
     sage: n[2:4,1:3]
-    array([[ 11.,  12.],
-           [ 16.,  17.]])
+    array([[11., 12.],
+           [16., 17.]])
 
 It is important to note that the sliced matrices are references to
 the original
@@ -224,8 +224,8 @@ Some particularly useful commands are
 
     sage: x=numpy.arange(0,2,.1,dtype=float)
     sage: x
-    array([ 0. ,  0.1,  0.2,  0.3,  0.4,  0.5,  0.6,  0.7,  0.8,  0.9,  1. ,
-            1.1,  1.2,  1.3,  1.4,  1.5,  1.6,  1.7,  1.8,  1.9])
+    array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. , 1.1, 1.2,
+           1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9])
 
 You can see that :meth:`numpy.arange` creates an array of floats increasing by 0.1
 from 0 to 2. There is a useful command :meth:`numpy.r_` that is best explained by example
@@ -240,10 +240,11 @@ from 0 to 2. There is a useful command :meth:`numpy.r_` that is best explained b
     sage: Integer=int
     sage: n=r_[0.0:5.0]
     sage: n
-    array([ 0.,  1.,  2.,  3.,  4.])
+    array([0., 1., 2., 3., 4.])
     sage: n=r_[0.0:5.0, [0.0]*5]
     sage: n
-    array([ 0.,  1.,  2.,  3.,  4.,  0.,  0.,  0.,  0.,  0.])
+    array([0., 1., 2., 3., 4., 0., 0., 0., 0., 0.])
+
 
 :meth:`numpy.r_` provides a shorthand for constructing NumPy arrays efficiently.
 Note in the above ``0.0:5.0`` was shorthand for ``0.0, 1.0, 2.0, 3.0, 4.0``.
@@ -255,7 +256,7 @@ intervals. We can do this as follows
 ::
 
     sage: r_[0.0:5.0:11*j]
-    array([ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ])
+    array([0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. ])
 
 The notation ``0.0:5.0:11*j`` expands to a list of 11 equally space
 points between 0 and 5 including both endpoints. Note that ``j`` is the
@@ -287,23 +288,23 @@ an equally spaced grid with `\Delta x = \Delta y = .25` for
     sage: y=numpy.r_[0.0:1.0:5*j]
     sage: xx,yy= meshgrid(x,y)
     sage: xx
-    array([[ 0.  ,  0.25,  0.5 ,  0.75,  1.  ],
-           [ 0.  ,  0.25,  0.5 ,  0.75,  1.  ],
-           [ 0.  ,  0.25,  0.5 ,  0.75,  1.  ],
-           [ 0.  ,  0.25,  0.5 ,  0.75,  1.  ],
-           [ 0.  ,  0.25,  0.5 ,  0.75,  1.  ]])
+    array([[0.  , 0.25, 0.5 , 0.75, 1.  ],
+           [0.  , 0.25, 0.5 , 0.75, 1.  ],
+           [0.  , 0.25, 0.5 , 0.75, 1.  ],
+           [0.  , 0.25, 0.5 , 0.75, 1.  ],
+           [0.  , 0.25, 0.5 , 0.75, 1.  ]])
     sage: yy
-    array([[ 0.  ,  0.  ,  0.  ,  0.  ,  0.  ],
-           [ 0.25,  0.25,  0.25,  0.25,  0.25],
-           [ 0.5 ,  0.5 ,  0.5 ,  0.5 ,  0.5 ],
-           [ 0.75,  0.75,  0.75,  0.75,  0.75],
-           [ 1.  ,  1.  ,  1.  ,  1.  ,  1.  ]])
+    array([[0.  , 0.  , 0.  , 0.  , 0.  ],
+           [0.25, 0.25, 0.25, 0.25, 0.25],
+           [0.5 , 0.5 , 0.5 , 0.5 , 0.5 ],
+           [0.75, 0.75, 0.75, 0.75, 0.75],
+           [1.  , 1.  , 1.  , 1.  , 1.  ]])
     sage: f(xx,yy)
-    array([[ 0.    ,  0.0625,  0.25  ,  0.5625,  1.    ],
-           [ 0.0625,  0.125 ,  0.3125,  0.625 ,  1.0625],
-           [ 0.25  ,  0.3125,  0.5   ,  0.8125,  1.25  ],
-           [ 0.5625,  0.625 ,  0.8125,  1.125 ,  1.5625],
-           [ 1.    ,  1.0625,  1.25  ,  1.5625,  2.    ]])
+    array([[0.    , 0.0625, 0.25  , 0.5625, 1.    ],
+           [0.0625, 0.125 , 0.3125, 0.625 , 1.0625],
+           [0.25  , 0.3125, 0.5   , 0.8125, 1.25  ],
+           [0.5625, 0.625 , 0.8125, 1.125 , 1.5625],
+           [1.    , 1.0625, 1.25  , 1.5625, 2.    ]])
 
 You can see that :meth:`numpy.meshgrid` produces a pair of matrices, here denoted
 `xx` and `yy`, such that `(xx[i,j],yy[i,j])` has coordinates
@@ -324,7 +325,7 @@ equation `Ax=b` do
     sage: b=numpy.array(range(1,6))
     sage: x=linalg.solve(A,b)
     sage: numpy.dot(A,x)
-    array([ 1.,  2.,  3.,  4., 5.])
+    array([1., 2., 3., 4., 5.])
 
 This creates a random 5x5 matrix ``A``, and solves `Ax=b` where
 ``b=[0.0,1.0,2.0,3.0,4.0]``. There are many other routines in the :mod:`numpy.linalg`
diff --git a/src/sage/calculus/riemann.pyx b/src/sage/calculus/riemann.pyx
index df85cce43d..34ea164be0 100644
--- a/src/sage/calculus/riemann.pyx
+++ b/src/sage/calculus/riemann.pyx
@@ -1191,30 +1191,30 @@ cpdef complex_to_spiderweb(np.ndarray[COMPLEX_T, ndim = 2] z_values,
         sage: zval = numpy.array([[0, 1, 1000],[.2+.3j,1,-.3j],[0,0,0]],dtype = numpy.complex128)
         sage: deriv = numpy.array([[.1]],dtype = numpy.float64)
         sage: complex_to_spiderweb(zval, deriv,deriv, 4,4,[0,0,0],1,False,0.001)
-        array([[[ 1.,  1.,  1.],
-                [ 1.,  1.,  1.],
-                [ 1.,  1.,  1.]],
+        array([[[1., 1., 1.],
+                [1., 1., 1.],
+                [1., 1., 1.]],
         <BLANKLINE>
-               [[ 1.,  1.,  1.],
-                [ 0.,  0.,  0.],
-                [ 1.,  1.,  1.]],
+               [[1., 1., 1.],
+                [0., 0., 0.],
+                [1., 1., 1.]],
         <BLANKLINE>
-               [[ 1.,  1.,  1.],
-                [ 1.,  1.,  1.],
-                [ 1.,  1.,  1.]]])
+               [[1., 1., 1.],
+                [1., 1., 1.],
+                [1., 1., 1.]]])
 
         sage: complex_to_spiderweb(zval, deriv,deriv, 4,4,[0,0,0],1,True,0.001)
-        array([[[ 1.        ,  1.        ,  1.        ],
-                [ 1.        ,  0.05558355,  0.05558355],
-                [ 0.17301243,  0.        ,  0.        ]],
+        array([[[1.        , 1.        , 1.        ],
+                [1.        , 0.05558355, 0.05558355],
+                [0.17301243, 0.        , 0.        ]],
         <BLANKLINE>
-               [[ 1.        ,  0.96804683,  0.48044583],
-                [ 0.        ,  0.        ,  0.        ],
-                [ 0.77351965,  0.5470393 ,  1.        ]],
+               [[1.        , 0.96804683, 0.48044583],
+                [0.        , 0.        , 0.        ],
+                [0.77351965, 0.5470393 , 1.        ]],
         <BLANKLINE>
-               [[ 1.        ,  1.        ,  1.        ],
-                [ 1.        ,  1.        ,  1.        ],
-                [ 1.        ,  1.        ,  1.        ]]])
+               [[1.        , 1.        , 1.        ],
+                [1.        , 1.        , 1.        ],
+                [1.        , 1.        , 1.        ]]])
      """
     cdef Py_ssize_t i, j, imax, jmax
     cdef FLOAT_T x, y, mag, arg, width, target, precision, dmag, darg
@@ -1279,14 +1279,14 @@ cpdef complex_to_rgb(np.ndarray[COMPLEX_T, ndim = 2] z_values):
         sage: from sage.calculus.riemann import complex_to_rgb
         sage: import numpy
         sage: complex_to_rgb(numpy.array([[0, 1, 1000]], dtype = numpy.complex128))
-        array([[[ 1.        ,  1.        ,  1.        ],
-                [ 1.        ,  0.05558355,  0.05558355],
-                [ 0.17301243,  0.        ,  0.        ]]])
+        array([[[1.        , 1.        , 1.        ],
+                [1.        , 0.05558355, 0.05558355],
+                [0.17301243, 0.        , 0.        ]]])
 
         sage: complex_to_rgb(numpy.array([[0, 1j, 1000j]], dtype = numpy.complex128))
-        array([[[ 1.        ,  1.        ,  1.        ],
-                [ 0.52779177,  1.        ,  0.05558355],
-                [ 0.08650622,  0.17301243,  0.        ]]])
+        array([[[1.        , 1.        , 1.        ],
+                [0.52779177, 1.        , 0.05558355],
+                [0.08650622, 0.17301243, 0.        ]]])
 
 
     TESTS::
diff --git a/src/sage/combinat/fully_packed_loop.py b/src/sage/combinat/fully_packed_loop.py
index 61b1003002..4baee9cbbd 100644
--- a/src/sage/combinat/fully_packed_loop.py
+++ b/src/sage/combinat/fully_packed_loop.py
@@ -72,11 +72,11 @@ def _make_color_list(n, colors=None,  color_map=None, randomize=False):
         sage: _make_color_list(5, ['blue', 'red'])
         ['blue', 'red', 'blue', 'red', 'blue']
         sage: _make_color_list(5, color_map='summer')
-        [(0.0, 0.5, 0.40000000000000002),
-         (0.25098039215686274, 0.62549019607843137, 0.40000000000000002),
-         (0.50196078431372548, 0.75098039215686274, 0.40000000000000002),
-         (0.75294117647058822, 0.87647058823529411, 0.40000000000000002),
-         (1.0, 1.0, 0.40000000000000002)]
+        [(0.0, 0.5, 0.4),
+         (0.25098039215686274, 0.6254901960784314, 0.4),
+         (0.5019607843137255, 0.7509803921568627, 0.4),
+         (0.7529411764705882, 0.8764705882352941, 0.4),
+         (1.0, 1.0, 0.4)]
         sage: _make_color_list(8, ['blue', 'red'], randomize=True)
         ['blue', 'blue', 'red', 'blue', 'red', 'red', 'red', 'blue']
     """
diff --git a/src/sage/finance/time_series.pyx b/src/sage/finance/time_series.pyx
index c37700d14e..49b7298d0b 100644
--- a/src/sage/finance/time_series.pyx
+++ b/src/sage/finance/time_series.pyx
@@ -109,8 +109,8 @@ cdef class TimeSeries:
 
             sage: import numpy
             sage: v = numpy.array([[1,2], [3,4]], dtype=float); v
-            array([[ 1.,  2.],
-                   [ 3.,  4.]])
+            array([[1., 2.],
+                   [3., 4.]])
             sage: finance.TimeSeries(v)
             [1.0000, 2.0000, 3.0000, 4.0000]
             sage: finance.TimeSeries(v[:,0])
@@ -2098,14 +2098,14 @@ cdef class TimeSeries:
 
             sage: w[0] = 20
             sage: w
-            array([ 20. ,  -3. ,   4.5,  -2. ])
+            array([20. , -3. ,  4.5, -2. ])
             sage: v
             [20.0000, -3.0000, 4.5000, -2.0000]
 
         If you want a separate copy do not give the ``copy=False`` option. ::
 
             sage: z = v.numpy(); z
-            array([ 20. ,  -3. ,   4.5,  -2. ])
+            array([20. , -3. ,  4.5, -2. ])
             sage: z[0] = -10
             sage: v
             [20.0000, -3.0000, 4.5000, -2.0000]
diff --git a/src/sage/functions/hyperbolic.py b/src/sage/functions/hyperbolic.py
index 931a4b41e4..bf33fc483d 100644
--- a/src/sage/functions/hyperbolic.py
+++ b/src/sage/functions/hyperbolic.py
@@ -214,7 +214,7 @@ class Function_coth(GinacFunction):
             sage: import numpy
             sage: a = numpy.arange(2, 5)
             sage: coth(a)
-            array([ 1.03731472,  1.00496982,  1.00067115])
+            array([1.03731472, 1.00496982, 1.00067115])
         """
         return 1.0 / tanh(x)
 
@@ -267,7 +267,7 @@ class Function_sech(GinacFunction):
             sage: import numpy
             sage: a = numpy.arange(2, 5)
             sage: sech(a)
-            array([ 0.26580223,  0.09932793,  0.03661899])
+            array([0.26580223, 0.09932793, 0.03661899])
         """
         return 1.0 / cosh(x)
 
@@ -318,7 +318,7 @@ class Function_csch(GinacFunction):
             sage: import numpy
             sage: a = numpy.arange(2, 5)
             sage: csch(a)
-            array([ 0.27572056,  0.09982157,  0.03664357])
+            array([0.27572056, 0.09982157, 0.03664357])
         """
         return 1.0 / sinh(x)
 
@@ -586,7 +586,7 @@ class Function_arccoth(GinacFunction):
             sage: import numpy
             sage: a = numpy.arange(2,5)
             sage: acoth(a)
-            array([ 0.54930614,  0.34657359,  0.25541281])
+            array([0.54930614, 0.34657359, 0.25541281])
         """
         return arctanh(1.0 / x)
 
diff --git a/src/sage/functions/orthogonal_polys.py b/src/sage/functions/orthogonal_polys.py
index 017c85a96f..33fbb499c5 100644
--- a/src/sage/functions/orthogonal_polys.py
+++ b/src/sage/functions/orthogonal_polys.py
@@ -810,12 +810,12 @@ class Func_chebyshev_T(ChebyshevFunction):
             sage: z2 = numpy.array([[1,2],[1,2]])
             sage: z3 = numpy.array([1,2,3.])
             sage: chebyshev_T(1,z)
-            array([ 1.,  2.])
+            array([1., 2.])
             sage: chebyshev_T(1,z2)
-            array([[ 1.,  2.],
-                   [ 1.,  2.]])
+            array([[1., 2.],
+                   [1., 2.]])
             sage: chebyshev_T(1,z3)
-            array([ 1.,  2.,  3.])
+            array([1., 2., 3.])
             sage: chebyshev_T(z,0.1)
             array([ 0.1 , -0.98])
         """
@@ -1095,12 +1095,12 @@ class Func_chebyshev_U(ChebyshevFunction):
             sage: z2 = numpy.array([[1,2],[1,2]])
             sage: z3 = numpy.array([1,2,3.])
             sage: chebyshev_U(1,z)
-            array([ 2.,  4.])
+            array([2., 4.])
             sage: chebyshev_U(1,z2)
-            array([[ 2.,  4.],
-                   [ 2.,  4.]])
+            array([[2., 4.],
+                   [2., 4.]])
             sage: chebyshev_U(1,z3)
-            array([ 2.,  4.,  6.])
+            array([2., 4., 6.])
             sage: chebyshev_U(z,0.1)
             array([ 0.2 , -0.96])
         """
diff --git a/src/sage/functions/other.py b/src/sage/functions/other.py
index 679384c907..d63b295a4c 100644
--- a/src/sage/functions/other.py
+++ b/src/sage/functions/other.py
@@ -390,7 +390,7 @@ class Function_ceil(BuiltinFunction):
             sage: import numpy
             sage: a = numpy.linspace(0,2,6)
             sage: ceil(a)
-            array([ 0.,  1.,  1.,  2.,  2.,  2.])
+            array([0., 1., 1., 2., 2., 2.])
 
         Test pickling::
 
@@ -539,7 +539,7 @@ class Function_floor(BuiltinFunction):
             sage: import numpy
             sage: a = numpy.linspace(0,2,6)
             sage: floor(a)
-            array([ 0.,  0.,  0.,  1.,  1.,  2.])
+            array([0., 0., 0., 1., 1., 2.])
             sage: floor(x)._sympy_()
             floor(x)
 
@@ -840,7 +840,7 @@ def sqrt(x, *args, **kwds):
             sage: import numpy
             sage: a = numpy.arange(2,5)
             sage: sqrt(a)
-            array([ 1.41421356,  1.73205081,  2.        ])
+            array([1.41421356, 1.73205081, 2.        ])
         """
         if isinstance(x, float):
             return math.sqrt(x)
diff --git a/src/sage/functions/trig.py b/src/sage/functions/trig.py
index e7e7a311cd..e7ff78a9de 100644
--- a/src/sage/functions/trig.py
+++ b/src/sage/functions/trig.py
@@ -731,7 +731,7 @@ class Function_arccot(GinacFunction):
             sage: import numpy
             sage: a = numpy.arange(2, 5)
             sage: arccot(a)
-            array([ 0.46364761,  0.32175055,  0.24497866])
+            array([0.46364761, 0.32175055, 0.24497866])
         """
         return math.pi/2 - arctan(x)
 
@@ -787,7 +787,7 @@ class Function_arccsc(GinacFunction):
             sage: import numpy
             sage: a = numpy.arange(2, 5)
             sage: arccsc(a)
-            array([ 0.52359878,  0.33983691,  0.25268026])
+            array([0.52359878, 0.33983691, 0.25268026])
         """
         return arcsin(1.0/x)
 
@@ -845,7 +845,7 @@ class Function_arcsec(GinacFunction):
             sage: import numpy
             sage: a = numpy.arange(2, 5)
             sage: arcsec(a)
-            array([ 1.04719755,  1.23095942,  1.31811607])
+            array([1.04719755, 1.23095942, 1.31811607])
         """
         return arccos(1.0/x)
 
@@ -920,13 +920,13 @@ class Function_arctan2(GinacFunction):
             sage: a = numpy.linspace(1, 3, 3)
             sage: b = numpy.linspace(3, 6, 3)
             sage: atan2(a, b)
-            array([ 0.32175055,  0.41822433,  0.46364761])
+            array([0.32175055, 0.41822433, 0.46364761])
 
             sage: atan2(1,a)
-            array([ 0.78539816,  0.46364761,  0.32175055])
+            array([0.78539816, 0.46364761, 0.32175055])
 
             sage: atan2(a, 1)
-            array([ 0.78539816,  1.10714872,  1.24904577])
+            array([0.78539816, 1.10714872, 1.24904577])
 
         TESTS::
 
diff --git a/src/sage/matrix/constructor.pyx b/src/sage/matrix/constructor.pyx
index 19a1d37df0..5780dfae1c 100644
--- a/src/sage/matrix/constructor.pyx
+++ b/src/sage/matrix/constructor.pyx
@@ -494,8 +494,8 @@ class MatrixFactory(object):
         [7 8 9]
         Full MatrixSpace of 3 by 3 dense matrices over Integer Ring
         sage: n = matrix(QQ, 2, 2, [1, 1/2, 1/3, 1/4]).numpy(); n
-        array([[ 1.        ,  0.5       ],
-               [ 0.33333333,  0.25      ]])
+        array([[1.        , 0.5       ],
+               [0.33333333, 0.25      ]])
         sage: matrix(QQ, n)
         [  1 1/2]
         [1/3 1/4]
diff --git a/src/sage/matrix/matrix_double_dense.pyx b/src/sage/matrix/matrix_double_dense.pyx
index 48e0a8a97f..1be5d35b19 100644
--- a/src/sage/matrix/matrix_double_dense.pyx
+++ b/src/sage/matrix/matrix_double_dense.pyx
@@ -2546,7 +2546,7 @@ cdef class Matrix_double_dense(Matrix_dense):
             sage: P.is_unitary(algorithm='orthonormal')
             Traceback (most recent call last):
             ...
-            ValueError: failed to create intent(cache|hide)|optional array-- must have defined dimensions but got (0,)
+            error: ((lwork==-1)||(lwork >= MAX(1,2*n))) failed for 3rd keyword lwork: zgees:lwork=0
 
         TESTS::
 
@@ -3662,8 +3662,8 @@ cdef class Matrix_double_dense(Matrix_dense):
             [0.0 1.0 2.0]
             [3.0 4.0 5.0]
             sage: m.numpy()
-            array([[ 0.,  1.,  2.],
-                   [ 3.,  4.,  5.]])
+            array([[0., 1., 2.],
+                   [3., 4., 5.]])
 
         Alternatively, numpy automatically calls this function (via
         the magic :meth:`__array__` method) to convert Sage matrices
@@ -3674,16 +3674,16 @@ cdef class Matrix_double_dense(Matrix_dense):
             [0.0 1.0 2.0]
             [3.0 4.0 5.0]
             sage: numpy.array(m)
-            array([[ 0.,  1.,  2.],
-                   [ 3.,  4.,  5.]])
+            array([[0., 1., 2.],
+                   [3., 4., 5.]])
             sage: numpy.array(m).dtype
             dtype('float64')
             sage: m = matrix(CDF, 2, range(6)); m
             [0.0 1.0 2.0]
             [3.0 4.0 5.0]
             sage: numpy.array(m)
-            array([[ 0.+0.j,  1.+0.j,  2.+0.j],
-                   [ 3.+0.j,  4.+0.j,  5.+0.j]])
+            array([[0.+0.j, 1.+0.j, 2.+0.j],
+                   [3.+0.j, 4.+0.j, 5.+0.j]])
             sage: numpy.array(m).dtype
             dtype('complex128')
 
diff --git a/src/sage/matrix/special.py b/src/sage/matrix/special.py
index c698ba5e97..b743bab354 100644
--- a/src/sage/matrix/special.py
+++ b/src/sage/matrix/special.py
@@ -705,7 +705,7 @@ def diagonal_matrix(arg0=None, arg1=None, arg2=None, sparse=True):
 
         sage: import numpy
         sage: entries = numpy.array([1.2, 5.6]); entries
-        array([ 1.2,  5.6])
+        array([1.2, 5.6])
         sage: A = diagonal_matrix(3, entries); A
         [1.2 0.0 0.0]
         [0.0 5.6 0.0]
@@ -715,7 +715,7 @@ def diagonal_matrix(arg0=None, arg1=None, arg2=None, sparse=True):
 
         sage: j = numpy.complex(0,1)
         sage: entries = numpy.array([2.0+j, 8.1, 3.4+2.6*j]); entries
-        array([ 2.0+1.j ,  8.1+0.j ,  3.4+2.6j])
+        array([2. +1.j , 8.1+0.j , 3.4+2.6j])
         sage: A = diagonal_matrix(entries); A
         [2.0 + 1.0*I         0.0         0.0]
         [        0.0         8.1         0.0]
diff --git a/src/sage/modules/free_module_element.pyx b/src/sage/modules/free_module_element.pyx
index 230f142117..2ab1c0ae68 100644
--- a/src/sage/modules/free_module_element.pyx
+++ b/src/sage/modules/free_module_element.pyx
@@ -982,7 +982,7 @@ cdef class FreeModuleElement(Vector):   # abstract base class
             sage: v.numpy()
             array([1, 2, 5/6], dtype=object)
             sage: v.numpy(dtype=float)
-            array([ 1.        ,  2.        ,  0.83333333])
+            array([1.        , 2.        , 0.83333333])
             sage: v.numpy(dtype=int)
             array([1, 2, 0])
             sage: import numpy
@@ -993,7 +993,7 @@ cdef class FreeModuleElement(Vector):   # abstract base class
         be more efficient but may have unintended consequences::
 
             sage: v.numpy(dtype=None)
-            array([ 1.        ,  2.        ,  0.83333333])
+            array([1.        , 2.        , 0.83333333])
 
             sage: w = vector(ZZ, [0, 1, 2^63 -1]); w
             (0, 1, 9223372036854775807)
diff --git a/src/sage/modules/vector_double_dense.pyx b/src/sage/modules/vector_double_dense.pyx
index 39fc2970de..2badf98284 100644
--- a/src/sage/modules/vector_double_dense.pyx
+++ b/src/sage/modules/vector_double_dense.pyx
@@ -807,13 +807,13 @@ cdef class Vector_double_dense(FreeModuleElement):
 
             sage: v = vector(CDF,4,range(4))
             sage: v.numpy()
-            array([ 0.+0.j,  1.+0.j,  2.+0.j,  3.+0.j])
+            array([0.+0.j, 1.+0.j, 2.+0.j, 3.+0.j])
             sage: v = vector(CDF,0)
             sage: v.numpy()
             array([], dtype=complex128)
             sage: v = vector(RDF,4,range(4))
             sage: v.numpy()
-            array([ 0.,  1.,  2.,  3.])
+            array([0., 1., 2., 3.])
             sage: v = vector(RDF,0)
             sage: v.numpy()
             array([], dtype=float64)
@@ -823,11 +823,11 @@ cdef class Vector_double_dense(FreeModuleElement):
             sage: import numpy
             sage: v = vector(CDF, 3, range(3))
             sage: v.numpy()
-            array([ 0.+0.j,  1.+0.j,  2.+0.j])
+            array([0.+0.j, 1.+0.j, 2.+0.j])
             sage: v.numpy(dtype=numpy.float64)
-            array([ 0.,  1.,  2.])
+            array([0., 1., 2.])
             sage: v.numpy(dtype=numpy.float32)
-            array([ 0.,  1.,  2.], dtype=float32)
+            array([0., 1., 2.], dtype=float32)
         """
         if dtype is None or dtype is self._vector_numpy.dtype:
             from copy import copy
diff --git a/src/sage/numerical/optimize.py b/src/sage/numerical/optimize.py
index 17b5ebb84b..92ce35c502 100644
--- a/src/sage/numerical/optimize.py
+++ b/src/sage/numerical/optimize.py
@@ -486,9 +486,9 @@ def minimize_constrained(func,cons,x0,gradient=None,algorithm='default', **args)
                 else:
                     min = optimize.fmin_tnc(f, x0, approx_grad=True, bounds=cons, messages=0, **args)[0]
         elif isinstance(cons[0], function_type) or isinstance(cons[0], Expression):
-            min = optimize.fmin_cobyla(f, x0, cons, iprint=0, **args)
+            min = optimize.fmin_cobyla(f, x0, cons, disp=0, **args)
     elif isinstance(cons, function_type) or isinstance(cons, Expression):
-        min = optimize.fmin_cobyla(f, x0, cons, iprint=0, **args)
+        min = optimize.fmin_cobyla(f, x0, cons, disp=0, **args)
     return vector(RDF, min)
 
 
diff --git a/src/sage/plot/complex_plot.pyx b/src/sage/plot/complex_plot.pyx
index ad9693da62..758fb709b7 100644
--- a/src/sage/plot/complex_plot.pyx
+++ b/src/sage/plot/complex_plot.pyx
@@ -61,9 +61,9 @@ cdef inline double mag_to_lightness(double r):
 
         sage: from sage.plot.complex_plot import complex_to_rgb
         sage: complex_to_rgb([[0, 1, 10]])
-        array([[[ 0.        ,  0.        ,  0.        ],
-                [ 0.77172568,  0.        ,  0.        ],
-                [ 1.        ,  0.22134776,  0.22134776]]])
+        array([[[0.        , 0.        , 0.        ],
+                [0.77172568, 0.        , 0.        ],
+                [1.        , 0.22134776, 0.22134776]]])
     """
     return atan(log(sqrt(r)+1)) * (4/PI) - 1
 
@@ -82,13 +82,13 @@ def complex_to_rgb(z_values):
 
         sage: from sage.plot.complex_plot import complex_to_rgb
         sage: complex_to_rgb([[0, 1, 1000]])
-        array([[[ 0.        ,  0.        ,  0.        ],
-                [ 0.77172568,  0.        ,  0.        ],
-                [ 1.        ,  0.64421177,  0.64421177]]])
+        array([[[0.        , 0.        , 0.        ],
+                [0.77172568, 0.        , 0.        ],
+                [1.        , 0.64421177, 0.64421177]]])
         sage: complex_to_rgb([[0, 1j, 1000j]])
-        array([[[ 0.        ,  0.        ,  0.        ],
-                [ 0.38586284,  0.77172568,  0.        ],
-                [ 0.82210588,  1.        ,  0.64421177]]])
+        array([[[0.        , 0.        , 0.        ],
+                [0.38586284, 0.77172568, 0.        ],
+                [0.82210588, 1.        , 0.64421177]]])
     """
     import numpy
     cdef unsigned int i, j, imax, jmax
diff --git a/src/sage/plot/line.py b/src/sage/plot/line.py
index 23f5e61446..3b1b51d7cf 100644
--- a/src/sage/plot/line.py
+++ b/src/sage/plot/line.py
@@ -502,14 +502,12 @@ def line2d(points, **options):
     from sage.plot.all import Graphics
     from sage.plot.plot import xydata_from_point_list
     from sage.rings.all import CC, CDF
+    points = list(points) # make sure points is a python list
     if points in CC or points in CDF:
         pass
     else:
-        try:
-            if not points:
-                return Graphics()
-        except ValueError: # numpy raises a ValueError if not empty
-            pass
+        if len(points) == 0:
+            return Graphics()
     xdata, ydata = xydata_from_point_list(points)
     g = Graphics()
     g._set_extra_kwds(Graphics._extract_kwds_for_show(options))
diff --git a/src/sage/plot/plot_field.py b/src/sage/plot/plot_field.py
index 0025098a8d..23c80902f3 100644
--- a/src/sage/plot/plot_field.py
+++ b/src/sage/plot/plot_field.py
@@ -49,9 +49,10 @@ class PlotField(GraphicPrimitive):
             sage: r.xpos_array
             [0.0, 0.0, 1.0, 1.0]
             sage: r.yvec_array
-            masked_array(data = [0.0 0.70710678118... 0.70710678118... 0.89442719...],
-                         mask = [False False False False],
-                   fill_value = 1e+20)
+            masked_array(data=[0.0, 0.70710678118..., 0.70710678118...,
+                               0.89442719...],
+                         mask=[False, False, False, False],
+                   fill_value=1e+20)
 
         TESTS:
 
diff --git a/src/sage/plot/streamline_plot.py b/src/sage/plot/streamline_plot.py
index f3da57c370..3806f4b32f 100644
--- a/src/sage/plot/streamline_plot.py
+++ b/src/sage/plot/streamline_plot.py
@@ -38,16 +38,14 @@ class StreamlinePlot(GraphicPrimitive):
             sage: r.options()['plot_points']
             2
             sage: r.xpos_array
-            array([ 0.,  1.])
+            array([0., 1.])
             sage: r.yvec_array
-            masked_array(data =
-             [[1.0 1.0]
-             [0.5403023058681398 0.5403023058681398]],
-                         mask =
-             [[False False]
-             [False False]],
-                   fill_value = 1e+20)
-            <BLANKLINE>
+            masked_array(
+              data=[[1.0, 1.0],
+                    [0.5403023058681398, 0.5403023058681398]],
+              mask=[[False, False],
+                    [False, False]],
+              fill_value=1e+20)
 
         TESTS:
 
diff --git a/src/sage/probability/probability_distribution.pyx b/src/sage/probability/probability_distribution.pyx
index f66cd898b9..35995886d5 100644
--- a/src/sage/probability/probability_distribution.pyx
+++ b/src/sage/probability/probability_distribution.pyx
@@ -130,7 +130,17 @@ cdef class ProbabilityDistribution:
              0.0,
              1.4650000000000003]
             sage: b
-            [0.0, 0.20000000000000001, 0.40000000000000002, 0.60000000000000009, 0.80000000000000004, 1.0, 1.2000000000000002, 1.4000000000000001, 1.6000000000000001, 1.8, 2.0]
+            [0.0,
+             0.2,
+             0.4,
+             0.6000000000000001,
+             0.8,
+             1.0,
+             1.2000000000000002,
+             1.4000000000000001,
+             1.6,
+             1.8,
+             2.0]
         """
         import pylab
         l = [float(self.get_random_element()) for _ in range(num_samples)]
diff --git a/src/sage/rings/rational.pyx b/src/sage/rings/rational.pyx
index a0bfe080f5..7d95e7a1a8 100644
--- a/src/sage/rings/rational.pyx
+++ b/src/sage/rings/rational.pyx
@@ -1056,7 +1056,7 @@ cdef class Rational(sage.structure.element.FieldElement):
             dtype('O')
 
             sage: numpy.array([1, 1/2, 3/4])
-            array([ 1.  ,  0.5 ,  0.75])
+            array([1.  , 0.5 , 0.75])
         """
         if mpz_cmp_ui(mpq_denref(self.value), 1) == 0:
             if mpz_fits_slong_p(mpq_numref(self.value)):
diff --git a/src/sage/rings/real_mpfr.pyx b/src/sage/rings/real_mpfr.pyx
index 4c630867a4..64e2187f5b 100644
--- a/src/sage/rings/real_mpfr.pyx
+++ b/src/sage/rings/real_mpfr.pyx
@@ -1438,7 +1438,7 @@ cdef class RealNumber(sage.structure.element.RingElement):
 
             sage: import numpy
             sage: numpy.arange(10.0)
-            array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9.])
+            array([0., 1., 2., 3., 4., 5., 6., 7., 8., 9.])
             sage: numpy.array([1.0, 1.1, 1.2]).dtype
             dtype('float64')
             sage: numpy.array([1.000000000000000000000000000000000000]).dtype
diff --git a/src/sage/schemes/elliptic_curves/height.py b/src/sage/schemes/elliptic_curves/height.py
index 3d270ebf9d..1144f168e3 100644
--- a/src/sage/schemes/elliptic_curves/height.py
+++ b/src/sage/schemes/elliptic_curves/height.py
@@ -1623,18 +1623,18 @@ class EllipticCurveCanonicalHeight:
         even::
 
             sage: H.wp_on_grid(v,4)
-            array([[ 25.43920182,   5.28760943,   5.28760943,  25.43920182],
-            [  6.05099485,   1.83757786,   1.83757786,   6.05099485],
-            [  6.05099485,   1.83757786,   1.83757786,   6.05099485],
-            [ 25.43920182,   5.28760943,   5.28760943,  25.43920182]])
+            array([[25.43920182,  5.28760943,  5.28760943, 25.43920182],
+                   [ 6.05099485,  1.83757786,  1.83757786,  6.05099485],
+                   [ 6.05099485,  1.83757786,  1.83757786,  6.05099485],
+                   [25.43920182,  5.28760943,  5.28760943, 25.43920182]])
 
         The array of values on the half-grid::
 
             sage: H.wp_on_grid(v,4,True)
-            array([[ 25.43920182,   5.28760943],
-            [  6.05099485,   1.83757786],
-            [  6.05099485,   1.83757786],
-            [ 25.43920182,   5.28760943]])
+            array([[25.43920182,  5.28760943],
+                   [ 6.05099485,  1.83757786],
+                   [ 6.05099485,  1.83757786],
+                   [25.43920182,  5.28760943]])
         """
         tau = self.tau(v)
         fk, err = self.fk_intervals(v, 15, CDF)
diff --git a/src/sage/symbolic/ring.pyx b/src/sage/symbolic/ring.pyx
index 2dcb0492b9..2b1a06385c 100644
--- a/src/sage/symbolic/ring.pyx
+++ b/src/sage/symbolic/ring.pyx
@@ -1135,7 +1135,7 @@ cdef class NumpyToSRMorphism(Morphism):
         sage: cos(numpy.int('2'))
         cos(2)
         sage: numpy.cos(numpy.int('2'))
-        -0.41614683654714241
+        -0.4161468365471424
     """
     cdef _intermediate_ring