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| = Sage 3.4.1 Release Tour = Sage 3.4.1 was released on FIXME. For the official, comprehensive release note, please refer to [[http://www.sagemath.org/src/announce/sage-3.4.1.txt|sage-3.4.1.txt]]. A nicely formatted version of this release tour can be found at FIXME. The following points are some of the foci of this release: * Merging improvements during the Sage Days 13 coding sprint. * Other bug fixes post Sage 3.4. |
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| == Algebra == * FIXME: summarize ticket #5535. * Speed-up in irreducibility test (Ryan Hinton) -- For polynomials over the finite field {{{GF(2)}}}, the test for irreducibility is now up to 40,000 times faster than previously. On a 64-bit Debian/squeeze machine with Core 2 Duo running at 2.33 GHz, one has the following timing improvements: {{{ # BEFORE sage: P.<x> = GF(2)[] sage: f = P.random_element(1000) sage: %timeit f.is_irreducible() 10 loops, best of 3: 948 ms per loop sage: sage: f = P.random_element(10000) sage: %time f.is_irreducible() # gave up because it took minutes! # AFTER sage: P.<x> = GF(2)[] sage: f = P.random_element(1000) sage: %timeit f.is_irreducible() 10000 loops, best of 3: 22.7 µs per loop sage: sage: f = P.random_element(10000) sage: %timeit f.is_irreducible() 1000 loops, best of 3: 394 µs per loop sage: sage: f = P.random_element(100000) sage: %timeit f.is_irreducible() 100 loops, best of 3: 10.4 ms per loop }}} Furthermore, on Debian 5.0 Lenny with kernel 2.6.24-1-686, an Intel(R) Celeron(R) CPU running at 2.00GHz with 1.0GB of RAM, one has the following timing statistics: {{{ # BEFORE sage: P.<x> = GF(2)[] sage: f = P.random_element(1000) sage: %timeit f.is_irreducible() 10 loops, best of 3: 1.14 s per loop sage: sage: f = P.random_element(10000) sage: %time f.is_irreducible() CPU times: user 4972.13 s, sys: 2.83 s, total: 4974.95 s Wall time: 5043.02 s False # AFTER sage: P.<x> = GF(2)[] sage: f = P.random_element(1000) sage: %timeit f.is_irreducible() 10000 loops, best of 3: 40.7 µs per loop sage: sage: f = P.random_element(10000) sage: %timeit f.is_irreducible() 1000 loops, best of 3: 930 µs per loop sage: sage: sage: f = P.random_element(100000) sage: %timeit f.is_irreducible() 10 loops, best of 3: 27.6 ms per loop }}} == Algebraic Geometry == == Basic Arithmetic == * Speed-up in dividing a polynomial by an integer (Burcin Erocal) -- Dividing a polynomial by an integer is now up to 6x faster than previously. On Debian 5.0 Lenny with kernel 2.6.24-1-686, an Intel(R) Celeron(R) CPU running at 2.00GHz with 1.0GB of RAM, one has the following timing statistics: {{{ # BEFORE sage: R.<x> = ZZ["x"] sage: f = 389 * R.random_element(1000) sage: timeit("f//389") 625 loops, best of 3: 312 µs per loop # AFTER sage: R.<x> = ZZ["x"] sage: f = 389 * R.random_element(1000) sage: timeit("f//389") 625 loops, best of 3: 48.3 µs per loop }}} * New {{{fast_float}}} supports more datatypes with improved performance (Carl Witty) -- A rewrite of {{{fast_float}}} to support multiple types. Here, we get accelerated evaluation over {{{RealField(k)}}} as well as {{{RDF}}}, real double field. As compared with the previous {{{fast_float}}}, improved performance can range from 2% faster to more than 2x as fast. An extended list of benchmark details is available at [[http://trac.sagemath.org/sage_trac/ticket/5093|ticket 5093]]. == Build == == Calculus == * Deprecate the calling of symbolic functions with unnamed arguments (Carl Witty, Michael Abshoff) -- Previous releases of Sage supported symbolic functions with "no arguments". This style of constructing symbolic functions is now deprecated. For example, previously Sage allowed for defining a symbolic function in the following way {{{ f2 = 5 - x^2 # bad; this is deprecated }}} But users are encouraged to explicitly declare the variables used in a symolic function. For instance, the following is encouraged: {{{ sage: x,y = var("x, y") # explicitly declare your variables sage: f(x, y) = x^2 + y^2 # this syntax is encouraged }}} == Coercion == == Combinatorics == * FIXME: summarize #5200 == Commutative Algebra == * New function {{{weil_restriction()}}} on multivariate ideals (Martin Albrecht) -- The new function {{{weil_restriction()}}} computes the [[http://en.wikipedia.org/wiki/Weil_restriction|Weil restriction]] of a multivariate ideal over some extension field. A Weil restriction is also known as a restriction of scalars. Here's an example on computing a Weil restriction: {{{ sage: k.<a> = GF(2^2) sage: P.<x,y> = PolynomialRing(k, 2) sage: I = Ideal([x*y + 1, a*x + 1]) sage: I.variety() [{y: a, x: a + 1}] sage: J = I.weil_restriction() sage: J Ideal (x1*y0 + x0*y1 + x1*y1, x0*y0 + x1*y1 + 1, x0 + x1, x1 + 1) of Multivariate Polynomial Ring in x0, x1, y0, y1 over Finite Field of size 2 }}} * FIXME: summarize #5146 * FIXME: summarize #5353 == Distribution == == Doctest == == Documentation == == Geometry == == Graph Theory == == Graphics == == Group Theory == * Speed-up in comparing elements of a permutation group (Robert Bradshaw, John H. Palmieri, Rob Beezer) -- For elements of a permutation group, comparison between those elements is now up to 13x faster. On Mac OS X 10.4 with Intel Core 2 duo running at 2.33 GHz, one has the following improvement in timing statistics: {{{ # BEFORE sage: a = SymmetricGroup(20).random_element() sage: b = SymmetricGroup(10).random_element() sage: timeit("a == b") 625 loops, best of 3: 3.19 µs per loop # AFTER sage: a = SymmetricGroup(20).random_element() sage: b = SymmetricGroup(10).random_element() sage: time v = [a == b for _ in xrange(2000)] CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s Wall time: 0.00 s sage: timeit("a == b") 625 loops, best of 3: 240 ns per loop }}} == Interfaces == == Linear Algebra == * Deprecate the function {{{invert()}}} (John H. Palmieri) -- The function {{{invert()}}} for calculating the inverse of a dense matrix with rational entries is now deprecated. Instead, users are now advised to use the function {{{inverse()}}}. Here's an example of using the function {{{inverse()}}}: {{{ sage: a = matrix(QQ, 2, [1, 5, 17, 3]) sage: a.inverse() [-3/82 5/82] [17/82 -1/82] }}} * Speed-up in calculating determinants of matrices (John H. Palmieri, William Stein) -- For matrices over {{{Z/nZ}}} with {{{n}}} composite, calculating their determinants is now up to 1500x faster. On Debian 5.0 Lenny with kernel 2.6.24-1-686, an Intel(R) Celeron(R) 2.00GHz CPU with 1.0GB of RAM, one has the following timing statistics: {{{ # BEFORE sage: time random_matrix(Integers(26), 10).determinant() CPU times: user 15.52 s, sys: 0.02 s, total: 15.54 s Wall time: 15.54 s 13 sage: time random_matrix(Integers(256), 10).determinant() CPU times: user 15.38 s, sys: 0.00 s, total: 15.38 s Wall time: 15.38 s 144 # AFTER sage: time random_matrix(Integers(26), 10).determinant() CPU times: user 0.01 s, sys: 0.00 s, total: 0.01 s Wall time: 0.01 s 23 sage: time random_matrix(Integers(256), 10).determinant() CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s Wall time: 0.00 s }}} == Miscellaneous == == Modular Forms == == Notebook == FIXME: A number of tickets related to UTF-8 text got merged and should definitely be mentioned! #4547, #5211; #2896 and #1477 got fixed by those tickets. There's also #5564, which may not get merged for 3.4.1 but should get in soon; it pulls together a whole bunch of UTF-8 fixes and improvements. == Number Theory == * FIXME: summarize #5518 * FIXME: summarize #5508 == Numerical == == Optional Packages == == Packages == * FIXME: summarize #4987 == Quadratic Forms == == Symbolics == == User Interface == == Website / Wiki == |
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