diff --git a/pkgs/applications/science/math/sage/default.nix b/pkgs/applications/science/math/sage/default.nix index 46e60a2b81e4..dfdf210eec04 100644 --- a/pkgs/applications/science/math/sage/default.nix +++ b/pkgs/applications/science/math/sage/default.nix @@ -70,7 +70,7 @@ let sage-env = callPackage ./sage-env.nix { sagelib = python.pkgs.sagelib; inherit env-locations; - inherit python rWrapper ecl singular palp flint pynac pythonEnv; + inherit python ecl singular palp flint pynac pythonEnv; pkg-config = pkgs.pkgconfig; # not to confuse with pythonPackages.pkgconfig }; @@ -124,19 +124,6 @@ let ignoreCollisions = true; } // { extraLibs = pythonRuntimeDeps; }; # make the libs accessible - # needs to be rWrapper, standard "R" doesn't include default packages - rWrapper = pkgs.rWrapper.override { - # https://trac.sagemath.org/ticket/25674 - R = pkgs.R.overrideAttrs (attrs: rec { - name = "R-3.4.4"; - doCheck = false; - src = fetchurl { - url = "http://cran.r-project.org/src/base/R-3/${name}.tar.gz"; - sha256 = "0dq3jsnwsb5j3fhl0wi3p5ycv8avf8s5j1y4ap3d2mkjmcppvsdk"; - }; - }); - }; - arb = pkgs.arb.override { inherit flint; }; singular = pkgs.singular.override { inherit flint; }; diff --git a/pkgs/applications/science/math/sage/patches/dont-test-guess-gaproot.patch b/pkgs/applications/science/math/sage/patches/dont-test-guess-gaproot.patch new file mode 100644 index 000000000000..32b877428d51 --- /dev/null +++ b/pkgs/applications/science/math/sage/patches/dont-test-guess-gaproot.patch @@ -0,0 +1,13 @@ +diff --git a/src/sage/libs/gap/util.pyx b/src/sage/libs/gap/util.pyx +index 5ff67107c1..1318df86fd 100644 +--- a/src/sage/libs/gap/util.pyx ++++ b/src/sage/libs/gap/util.pyx +@@ -165,7 +165,7 @@ def _guess_gap_root(): + EXAMPLES:: + + sage: from sage.libs.gap.util import _guess_gap_root +- sage: _guess_gap_root() ++ sage: _guess_gap_root() # not tested (not necessary on nixos) + The gap-4.5.5.spkg (or later) seems to be not installed! + ... + """ 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 deleted file mode 100644 index 9e855ba4ad94..000000000000 --- a/pkgs/applications/science/math/sage/patches/numpy-1.15.1.patch +++ /dev/null @@ -1,911 +0,0 @@ -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.]], - -- [[ 1., 1., 1.], -- [ 0., 0., 0.], -- [ 1., 1., 1.]], -+ [[1., 1., 1.], -+ [0., 0., 0.], -+ [1., 1., 1.]], - -- [[ 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. ]], - -- [[ 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. ]], - -- [[ 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) -- -+ 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 - diff --git a/pkgs/applications/science/math/sage/sage-env.nix b/pkgs/applications/science/math/sage/sage-env.nix index c071f8945506..d5e057d53357 100644 --- a/pkgs/applications/science/math/sage/sage-env.nix +++ b/pkgs/applications/science/math/sage/sage-env.nix @@ -77,6 +77,7 @@ let singular giac palp + # needs to be rWrapper since the default `R` doesn't include R's default libraries rWrapper gfan cddlib diff --git a/pkgs/applications/science/math/sage/sage-src.nix b/pkgs/applications/science/math/sage/sage-src.nix index 5dc73e26a596..be41c7219cc1 100644 --- a/pkgs/applications/science/math/sage/sage-src.nix +++ b/pkgs/applications/science/math/sage/sage-src.nix @@ -9,14 +9,14 @@ # all get the same sources with the same patches applied. stdenv.mkDerivation rec { - version = "8.4"; + version = "8.5"; name = "sage-src-${version}"; src = fetchFromGitHub { owner = "sagemath"; repo = "sage"; rev = version; - sha256 = "0gips1hagiz9m7s21bg5as8hrrm2x5k47h1bsq0pc46iplfwmv2d"; + sha256 = "08mb9626phsls2phdzqxsnp2df5pn5qr72m0mm4nncby26pwn19c"; }; # Patches needed because of particularities of nix or the way this is packaged. @@ -46,6 +46,8 @@ stdenv.mkDerivation rec { # tests) are also run. That is necessary to test dochtml individually. See # https://trac.sagemath.org/ticket/26110 for an upstream discussion. ./patches/Only-test-py2-py3-optional-tests-when-all-of-sage-is.patch + + ./patches/dont-test-guess-gaproot.patch ]; # Patches needed because of package updates. We could just pin the versions of @@ -68,6 +70,7 @@ stdenv.mkDerivation rec { ); in [ # New glpk version has new warnings, filter those out until upstream sage has found a solution + # Should be fixed with glpk > 4.65. # https://trac.sagemath.org/ticket/24824 ./patches/pari-stackwarn.patch # not actually necessary since the pari upgrade, but necessary for the glpk patch to apply (fetchpatch { @@ -76,32 +79,9 @@ stdenv.mkDerivation rec { stripLen = 1; }) - # https://trac.sagemath.org/ticket/25260 - ./patches/numpy-1.15.1.patch - # https://trac.sagemath.org/ticket/26315 ./patches/giac-1.5.0.patch - # needed for ntl update - # https://trac.sagemath.org/ticket/25532 - (fetchpatch { - name = "lcalc-c++11.patch"; - url = "https://git.archlinux.org/svntogit/community.git/plain/trunk/sagemath-lcalc-c++11.patch?h=packages/sagemath&id=0e31ae526ab7c6b5c0bfacb3f8b1c4fd490035aa"; - sha256 = "0p5wnvbx65i7cp0bjyaqgp4rly8xgnk12pqwaq3dqby0j2bk6ijb"; - }) - - (fetchpatch { - name = "cython-0.29.patch"; - url = "https://git.sagemath.org/sage.git/patch/?h=f77de1d0e7f90ee12761140500cb8cbbb789ab20"; - sha256 = "14wrpy8jgbnpza1j8a2nx8y2r946y82pll1fv3cn6gpfmm6640l3"; - }) - # https://trac.sagemath.org/ticket/26360 - (fetchpatch { - name = "arb-2.15.1.patch"; - url = "https://git.sagemath.org/sage.git/patch/?id=30cc778d46579bd0c7537ed33e8d7a4f40fd5c31"; - sha256 = "13vc2q799dh745sm59xjjabllfj0sfjzcacf8k59kwj04x755d30"; - }) - # https://trac.sagemath.org/ticket/26326 # needs to be split because there is a merge commit in between (fetchSageDiff { diff --git a/pkgs/applications/science/math/sage/sage-tests.nix b/pkgs/applications/science/math/sage/sage-tests.nix index 1f400db18fcb..12433e12fe90 100644 --- a/pkgs/applications/science/math/sage/sage-tests.nix +++ b/pkgs/applications/science/math/sage/sage-tests.nix @@ -3,7 +3,12 @@ , sage-with-env , makeWrapper , files ? null # "null" means run all tests -, longTests ? true # run tests marked as "long time" +, longTests ? true # run tests marked as "long time" (roughly doubles runtime) +# Run as many tests as possible in approximately n seconds. This will give each +# file to test a "time budget" and stop tests if it is exceeded. 300 is the +# upstream default value. +# https://trac.sagemath.org/ticket/25270 for details. +, timeLimit ? null }: # for a quick test of some source files: @@ -14,6 +19,7 @@ let runAllTests = files == null; testArgs = if runAllTests then "--all" else testFileList; patienceSpecifier = if longTests then "--long" else ""; + timeSpecifier = if timeLimit == null then "" else "--short ${toString timeLimit}"; relpathToArg = relpath: lib.escapeShellArg "${src}/${relpath}"; # paths need to be absolute testFileList = lib.concatStringsSep " " (map relpathToArg files); in @@ -45,7 +51,7 @@ stdenv.mkDerivation rec { export HOME="$TMPDIR/sage-home" mkdir -p "$HOME" - # "--long" tests are in the order of 1h, without "--long" its 1/2h - "sage" -t --timeout=0 --nthreads "$NIX_BUILD_CORES" --optional=sage ${patienceSpecifier} ${testArgs} + echo "Running sage tests with arguments ${timeSpecifier} ${patienceSpecifier} ${testArgs}" + "sage" -t --nthreads "$NIX_BUILD_CORES" --optional=sage ${timeSpecifier} ${patienceSpecifier} ${testArgs} ''; } diff --git a/pkgs/applications/science/math/sage/sage.nix b/pkgs/applications/science/math/sage/sage.nix index ac255643a348..541b9cb36dc2 100644 --- a/pkgs/applications/science/math/sage/sage.nix +++ b/pkgs/applications/science/math/sage/sage.nix @@ -54,6 +54,7 @@ stdenv.mkDerivation rec { passthru = { tests = sage-tests; + quicktest = sage-tests.override { longTests = false; timeLimit = 600; }; # as many tests as possible in ~10m doc = sagedoc; lib = sage-with-env.env.lib; kernelspec = jupyter-kernel-definition;