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Diffstat (limited to 'pkgs/applications/science/math/sage/patches/numpy-1.15.1.patch')
| -rw-r--r-- | pkgs/applications/science/math/sage/patches/numpy-1.15.1.patch | 911 |
1 files changed, 911 insertions, 0 deletions
diff --git a/pkgs/applications/science/math/sage/patches/numpy-1.15.1.patch b/pkgs/applications/science/math/sage/patches/numpy-1.15.1.patch new file mode 100644 index 000000000000..9e855ba4ad94 --- /dev/null +++ b/pkgs/applications/science/math/sage/patches/numpy-1.15.1.patch @@ -0,0 +1,911 @@ +diff --git a/src/doc/en/faq/faq-usage.rst b/src/doc/en/faq/faq-usage.rst +index 2347a1190d..f5b0fe71a4 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 60f37f7557..4ac3dedf1d 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 0a9bd61267..d2193cc2d6 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 28779365df..3ab0282861 100644 +--- a/src/sage/finance/time_series.pyx ++++ b/src/sage/finance/time_series.pyx +@@ -111,8 +111,8 @@ 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]) +@@ -2100,14 +2100,14 @@ 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 aff552f450..7a6df931e7 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 ed6365bef4..99b8b04dad 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 1883daa3e6..9885222817 100644 +--- a/src/sage/functions/other.py ++++ b/src/sage/functions/other.py +@@ -389,7 +389,7 @@ 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:: + +@@ -553,7 +553,7 @@ 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) + +@@ -869,7 +869,7 @@ 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/spike_function.py b/src/sage/functions/spike_function.py +index 1e021de3fe..56635ca98f 100644 +--- a/src/sage/functions/spike_function.py ++++ b/src/sage/functions/spike_function.py +@@ -157,7 +157,7 @@ class SpikeFunction: + sage: S = spike_function([(-3,4),(-1,1),(2,3)]); S + A spike function with spikes at [-3.0, -1.0, 2.0] + sage: P = S.plot_fft_abs(8) +- sage: p = P[0]; p.ydata ++ sage: p = P[0]; p.ydata # abs tol 1e-8 + [5.0, 5.0, 3.367958691924177, 3.367958691924177, 4.123105625617661, 4.123105625617661, 4.759921664218055, 4.759921664218055] + """ + w = self.vector(samples = samples, xmin=xmin, xmax=xmax) +@@ -176,8 +176,8 @@ class SpikeFunction: + sage: S = spike_function([(-3,4),(-1,1),(2,3)]); S + A spike function with spikes at [-3.0, -1.0, 2.0] + sage: P = S.plot_fft_arg(8) +- sage: p = P[0]; p.ydata +- [0.0, 0.0, -0.211524990023434..., -0.211524990023434..., 0.244978663126864..., 0.244978663126864..., -0.149106180027477..., -0.149106180027477...] ++ sage: p = P[0]; p.ydata # abs tol 1e-8 ++ [0.0, 0.0, -0.211524990023434, -0.211524990023434, 0.244978663126864, 0.244978663126864, -0.149106180027477, -0.149106180027477] + """ + w = self.vector(samples = samples, xmin=xmin, xmax=xmax) + xmin, xmax = self._ranges(xmin, xmax) +diff --git a/src/sage/functions/trig.py b/src/sage/functions/trig.py +index 501e7ff6b6..5f760912f0 100644 +--- a/src/sage/functions/trig.py ++++ b/src/sage/functions/trig.py +@@ -724,7 +724,7 @@ 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) + +@@ -780,7 +780,7 @@ 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) + +@@ -838,7 +838,7 @@ 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) + +@@ -913,13 +913,13 @@ 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 12136f1773..491bf22e62 100644 +--- a/src/sage/matrix/constructor.pyx ++++ b/src/sage/matrix/constructor.pyx +@@ -503,8 +503,8 @@ def matrix(*args, **kwds): + [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 66e54a79a4..0498334f4b 100644 +--- a/src/sage/matrix/matrix_double_dense.pyx ++++ b/src/sage/matrix/matrix_double_dense.pyx +@@ -606,6 +606,9 @@ cdef class Matrix_double_dense(Matrix_dense): + [ 3.0 + 9.0*I 4.0 + 16.0*I 5.0 + 25.0*I] + [6.0 + 36.0*I 7.0 + 49.0*I 8.0 + 64.0*I] + sage: B.condition() ++ doctest:warning ++ ... ++ ComplexWarning: Casting complex values to real discards the imaginary part + 203.851798... + sage: B.condition(p='frob') + 203.851798... +@@ -654,9 +657,7 @@ cdef class Matrix_double_dense(Matrix_dense): + True + sage: B = A.change_ring(CDF) + sage: B.condition() +- Traceback (most recent call last): +- ... +- LinAlgError: Singular matrix ++ +Infinity + + Improper values of ``p`` are caught. :: + +@@ -2519,7 +2520,7 @@ 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:: + +@@ -3635,8 +3636,8 @@ 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 +@@ -3647,16 +3648,16 @@ 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 ccbd208810..c3f9a65093 100644 +--- a/src/sage/matrix/special.py ++++ b/src/sage/matrix/special.py +@@ -706,7 +706,7 @@ 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] +@@ -716,7 +716,7 @@ 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 37d92c1282..955d083b34 100644 +--- a/src/sage/modules/free_module_element.pyx ++++ b/src/sage/modules/free_module_element.pyx +@@ -988,7 +988,7 @@ 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 +@@ -999,7 +999,7 @@ 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/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/histogram.py b/src/sage/plot/histogram.py +index 5d28473731..fc4b2046c0 100644 +--- a/src/sage/plot/histogram.py ++++ b/src/sage/plot/histogram.py +@@ -53,10 +53,17 @@ class Histogram(GraphicPrimitive): + """ + import numpy as np + self.datalist=np.asarray(datalist,dtype=float) ++ if 'normed' in options: ++ from sage.misc.superseded import deprecation ++ deprecation(25260, "the 'normed' option is deprecated. Use 'density' instead.") + if 'linestyle' in options: + from sage.plot.misc import get_matplotlib_linestyle + options['linestyle'] = get_matplotlib_linestyle( + options['linestyle'], return_type='long') ++ if options.get('range', None): ++ # numpy.histogram performs type checks on "range" so this must be ++ # actual floats ++ options['range'] = [float(x) for x in options['range']] + GraphicPrimitive.__init__(self, options) + + def get_minmax_data(self): +@@ -80,10 +87,14 @@ class Histogram(GraphicPrimitive): + {'xmax': 4.0, 'xmin': 0, 'ymax': 2, 'ymin': 0} + + TESTS:: +- + sage: h = histogram([10,3,5], normed=True)[0] +- sage: h.get_minmax_data() # rel tol 1e-15 +- {'xmax': 10.0, 'xmin': 3.0, 'ymax': 0.4761904761904765, 'ymin': 0} ++ doctest:warning...: ++ DeprecationWarning: the 'normed' option is deprecated. Use 'density' instead. ++ See https://trac.sagemath.org/25260 for details. ++ sage: h.get_minmax_data() ++ doctest:warning ...: ++ VisibleDeprecationWarning: Passing `normed=True` on non-uniform bins has always been broken, and computes neither the probability density function nor the probability mass function. The result is only correct if the bins are uniform, when density=True will produce the same result anyway. The argument will be removed in a future version of numpy. ++ {'xmax': 10.0, 'xmin': 3.0, 'ymax': 0.476190476190..., 'ymin': 0} + """ + import numpy + +@@ -152,7 +163,7 @@ class Histogram(GraphicPrimitive): + 'rwidth': 'The relative width of the bars as a fraction of the bin width', + 'cumulative': '(True or False) If True, then a histogram is computed in which each bin gives the counts in that bin plus all bins for smaller values. Negative values give a reversed direction of accumulation.', + 'range': 'A list [min, max] which define the range of the histogram. Values outside of this range are treated as outliers and omitted from counts.', +- 'normed': 'Deprecated alias for density', ++ 'normed': 'Deprecated. Use density instead.', + 'density': '(True or False) If True, the counts are normalized to form a probability density. (n/(len(x)*dbin)', + 'weights': 'A sequence of weights the same length as the data list. If supplied, then each value contributes its associated weight to the bin count.', + 'stacked': '(True or False) If True, multiple data are stacked on top of each other.', +@@ -199,7 +210,7 @@ class Histogram(GraphicPrimitive): + subplot.hist(self.datalist.transpose(), **options) + + +-@options(aspect_ratio='automatic',align='mid', weights=None, range=None, bins=10, edgecolor='black') ++@options(aspect_ratio='automatic', align='mid', weights=None, range=None, bins=10, edgecolor='black') + def histogram(datalist, **options): + """ + Computes and draws the histogram for list(s) of numerical data. +@@ -231,8 +242,9 @@ def histogram(datalist, **options): + - ``linewidth`` -- (float) width of the lines defining the bars + - ``linestyle`` -- (default: 'solid') Style of the line. One of 'solid' + or '-', 'dashed' or '--', 'dotted' or ':', 'dashdot' or '-.' +- - ``density`` -- (boolean - default: False) If True, the counts are +- normalized to form a probability density. ++ - ``density`` -- (boolean - default: False) If True, the result is the ++ value of the probability density function at the bin, normalized such ++ that the integral over the range is 1. + - ``range`` -- A list [min, max] which define the range of the + histogram. Values outside of this range are treated as outliers and + omitted from counts +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 1b119e323f..3290b00695 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 12ca1b222b..9bad7dae0c 100644 +--- a/src/sage/rings/rational.pyx ++++ b/src/sage/rings/rational.pyx +@@ -1041,7 +1041,7 @@ 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 9b90c8833e..1ce05b937d 100644 +--- a/src/sage/rings/real_mpfr.pyx ++++ b/src/sage/rings/real_mpfr.pyx +@@ -1439,7 +1439,7 @@ 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 de31fe9883..7a33ea6f5b 100644 +--- a/src/sage/schemes/elliptic_curves/height.py ++++ b/src/sage/schemes/elliptic_curves/height.py +@@ -1627,18 +1627,18 @@ 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 9da38002e8..d61e74bf82 100644 +--- a/src/sage/symbolic/ring.pyx ++++ b/src/sage/symbolic/ring.pyx +@@ -1136,7 +1136,7 @@ cdef class NumpyToSRMorphism(Morphism): + sage: cos(numpy.int('2')) + cos(2) + sage: numpy.cos(numpy.int('2')) +- -0.41614683654714241 ++ -0.4161468365471424 + """ + cdef _intermediate_ring + |