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See: sagemath/sage#37123 Also apply a few minor fixes.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,3 +1,4 @@ | ||
| # configuration for sage on void linux | ||
| SAGE_SHARE = "/usr/share/sagemath" | ||
| GAP_SHARE_DIR = "/usr/share/gap" | ||
| JMOL_DIR = "/usr/share/jmol" |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,15 @@ | ||
| diff --git a/src/sage/calculus/calculus.py b/src/sage/calculus/calculus.py | ||
| index dfaafb4353f..8d62ade24c8 100644 | ||
| --- a/src/sage/calculus/calculus.py | ||
| +++ b/src/sage/calculus/calculus.py | ||
| @@ -568,8 +568,8 @@ def symbolic_sum(expression, v, a, b, algorithm='maxima', hold=False): | ||
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| An example of this summation with Giac:: | ||
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| - sage: symbolic_sum(1/(1+k^2), k, -oo, oo, algorithm='giac') | ||
| - (pi*e^(2*pi) - pi*e^(-2*pi))/(e^(2*pi) + e^(-2*pi) - 2) | ||
| + sage: symbolic_sum(1/(1+k^2), k, -oo, oo, algorithm='giac').factor() | ||
| + pi*(e^(2*pi) + 1)/((e^pi + 1)*(e^pi - 1)) | ||
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| The same summation is solved by SymPy:: | ||
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|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,26 @@ | ||
| diff --git a/src/sage/matrix/matrix_double_dense.pyx b/src/sage/matrix/matrix_double_dense.pyx | ||
| index 5d19067f2ed..97e50fb2616 100644 | ||
| --- a/src/sage/matrix/matrix_double_dense.pyx | ||
| +++ b/src/sage/matrix/matrix_double_dense.pyx | ||
| @@ -867,7 +867,7 @@ cdef class Matrix_double_dense(Matrix_numpy_dense): | ||
| # set cutoff as RDF element | ||
| if eps == 'auto': | ||
| if scipy is None: import scipy | ||
| - eps = 2*max(self._nrows, self._ncols)*scipy.finfo(float).eps*sv[0] | ||
| + eps = 2*max(self._nrows, self._ncols)*numpy.finfo(float).eps*sv[0] | ||
| eps = RDF(eps) | ||
| # locate non-zero entries | ||
| rank = 0 | ||
| diff --git a/src/sage/numerical/optimize.py b/src/sage/numerical/optimize.py | ||
| index 708d440a205..9f973c6bd69 100644 | ||
| --- a/src/sage/numerical/optimize.py | ||
| +++ b/src/sage/numerical/optimize.py | ||
| @@ -426,7 +426,7 @@ def minimize(func, x0, gradient=None, hessian=None, algorithm="default", | ||
| hess = func.hessian() | ||
| hess_fast = [ [fast_callable(a, vars=var_names, domain=float) for a in row] for row in hess] | ||
| hessian = lambda p: [[a(*p) for a in row] for row in hess_fast] | ||
| - from scipy import dot | ||
| + from numpy import dot | ||
| hessian_p = lambda p,v: dot(numpy.array(hessian(p)),v) | ||
| min = optimize.fmin_ncg(f, [float(_) for _ in x0], fprime=gradient, | ||
| fhess=hessian, fhess_p=hessian_p, disp=verbose, **args) |
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