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2016-01-10Bump PKGREVISION for hs-text-1.2.2.0 || hs-hashable-1.2.3.3szptvlfn2-4/+4
2015-11-03Add SHA512 digests for distfiles for math categoryagc1-1/+2
Problems found locating distfiles: Package dfftpack: missing distfile dfftpack-20001209.tar.gz Package eispack: missing distfile eispack-20001130.tar.gz Package fftpack: missing distfile fftpack-20001130.tar.gz Package linpack: missing distfile linpack-20010510.tar.gz Package minpack: missing distfile minpack-20001130.tar.gz Package odepack: missing distfile odepack-20001130.tar.gz Package py-networkx: missing distfile networkx-1.10.tar.gz Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz Package quadpack: missing distfile quadpack-20001130.tar.gz Otherwise, existing SHA1 digests verified and found to be the same on the machine holding the existing distfiles (morden). All existing SHA1 digests retained for now as an audit trail.
2015-08-02Bump PKGREVISION for hs-text-1.2.1.3szptvlfn2-4/+4
2015-06-08Bump PKGREVISION for hs-hashable-1.2.3.2szptvlfn2-4/+4
2015-06-04Bump PKGREVISION for hs-text-1.2.1.1szptvlfn2-3/+4
2015-01-07Update to 0.3.3.5szptvlfn3-8/+8
changelog: 0.3.3.5 * Fixed bug when converting the Scientific: `scientific 0 someBigExponent` to a bounded Integral using toBoundedInteger or to a bounded RealFloat using toBoundedRealFloat. If someBigExponent was big enough to trigger the big-exponent protection the beforementioned functions didn't return 0. This is fixed by explicitly handling a coefficient of 0.
2015-01-06Update to 0.3.3.4szptvlfn3-10/+9
changelog: 0.3.3.4 * Relax upper version bounds of base and deepseq for the test suite and benchmarks. 0.3.3.3 * Add support for `deepseq-1.4`. 0.3.3.2 * Fix parsing of empty digit string (#21).
2014-12-12Bump PKGREVISION for hs-text-1.2.0.3szptvlfn2-4/+4
2014-12-12Bump PKGREVISION for hs-text-1.2.0.2 || hs-hashable-1.2.3.0szptvlfn2-3/+4
2014-09-14Update to 0.3.3.1szptvlfn3-9/+8
changelog: 0.3.3.1 * Allow newer tasty, tasty-hunit and criterion
2014-09-05Bump PKGREVISION for hs-text-1.1.1.3szptvlfn1-1/+2
2014-08-29make it clear what package depend onszptvlfn1-1/+2
discussed with wiz@.
2014-08-16Update to 0.3.3.0szptvlfn5-17/+23
changelog: 0.3.3.0 * Add the isFloating or isInteger predicates. Courtesy of Zejun Wu (@watashi). * Add the toRealFloat' and toBoundedInteger functions. Courtesy of Fujimura Daisuke (@fujimura). 0.3.2.2 * Enable package to link with integer-simple instead of integer-gmp using the -finteger-simple cabal flag. Courtesy of @k0ral. 0.3.2.1 * Parameterize inclusion of the Data.ByteString.Builder.Scientific module using the bytestring-builder flag. Disabling this flag allows building on GHC-7.0.4 which has bytestring-0.9 installed by default. 0.3.2.0 * Add the floatingOrInteger function * Fix build on GHC-7.0.4 * More efficient and better behaving magnitude computation * Lower the number of cached magnitudes to 324 (same as GHC.Float) 0.3.1.0 * Don't normalize on construction but do it when pretty-printing instead. Also provide a manual normalize function. * Improve efficiency of toRealFloat * Added note about caching magnitudes * Dropped dependency on arithmoi * Make benchmark easier to build * Add junit XML output support (for Jenkins) 0.3.0.2 * Lower the minimal QuickCheck version. * Make sure sized exponents are generated in the QuickCheck tests. 0.3.0.1 * Fix build for bytestring-0.10.0.* 0.3.0.0 * Fix a DoS vulnerability that allowed an attacker to crash the process by sending a scientific with a huge exponent like 1e1000000000. * Fix various RealFrac methods. * Cache some powers of 10 to speed up the magnitude computation. * Normalize scientific numbers on construction. * Move the Text Builder to its own module & provide a ByteString builder * Added more documentation
2014-05-31Import scientific-0.2.0.2 as math/hs-scientific,szptvlfn5-0/+61
packaged for wip. A Scientific number is an arbitrary-precision floating-point number represented using scientific notation. A scientific number with coefficient c and base10Exponent e corresponds to the Fractional number: fromInteger c * 10 ^^ e Its primary use-case is to serve as the target of parsing floating point numbers. Since the textual representation of floating point numbers use scientific notation they can be efficiently parsed to a Scientific number.