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MD5:2e69f1b3a7e5075510e9fb6f1d3aa0c1 include/boost/fusion/view/filter_view/detail/value_of_impl.hpp @comment MD5:33e65007402be41333794d46df9c6a9e include/boost/fusion/view/filter_view/filter_view.hpp @comment MD5:3321c5e367de340b8ccff519994b4018 include/boost/fusion/view/filter_view/filter_view_iterator.hpp @comment MD5:186010d367434644f4b9cb4b1a5f577f include/boost/fusion/view/iterator_range.hpp @comment MD5:bcfd9d217480dfe457856612af296f90 include/boost/fusion/view/iterator_range/detail/at_impl.hpp @comment MD5:fd0346a4a5f7cb73f07a69d60a69f7e1 include/boost/fusion/view/iterator_range/detail/begin_impl.hpp @comment MD5:0152203346af0b0f673b61ce7c7210ed include/boost/fusion/view/iterator_range/detail/end_impl.hpp @comment MD5:f5bbd48ae6a8e250e86b2bdf05465976 include/boost/fusion/view/iterator_range/detail/value_at_impl.hpp @comment MD5:4453c017e7b9b943f0c87d589979f34a include/boost/fusion/view/iterator_range/iterator_range.hpp @comment MD5:44c67cb9be0208e2aebc809914105dcb 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MD5:8f11401dc27c2cf28ad86ce6b64d0092 include/boost/fusion/view/single_view.hpp @comment MD5:5d448d6a32f4906a3b948320ffc436a0 include/boost/fusion/view/single_view/detail/begin_impl.hpp @comment MD5:9d95a3a83986119e6abf43884d136d7f include/boost/fusion/view/single_view/detail/deref_impl.hpp @comment MD5:178132f8c16b7487f8c6b6308b685019 include/boost/fusion/view/single_view/detail/end_impl.hpp @comment MD5:c5d11191ce40ca63185f7498d93d5c16 include/boost/fusion/view/single_view/detail/next_impl.hpp @comment MD5:7e60186c4d29b96f01964bd28656a78b include/boost/fusion/view/single_view/detail/value_of_impl.hpp @comment MD5:f42f35fe354224482363d32f412c0766 include/boost/fusion/view/single_view/single_view.hpp @comment MD5:f13bf9b8e3a839fa3dfe734f505fbbe4 include/boost/fusion/view/single_view/single_view_iterator.hpp @comment MD5:192ddba2cb2ea2ac3ea9902428292426 include/boost/fusion/view/transform_view.hpp @comment MD5:0cde0c8809af6b576c0cdcc126d42299 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MD5:79190558062569f1f93c5b533526f0d7 include/boost/spirit/home/support/detail/lexer/partition/equivset.hpp @comment MD5:3fe4343b6a4079f2ad9de9c46605204c include/boost/spirit/home/support/detail/lexer/rules.hpp @comment MD5:3acd8c6876f58bb59553446a63360ace include/boost/spirit/home/support/detail/lexer/runtime_error.hpp @comment MD5:6d57cd0a9bcb7d48ce150a8f9d3ef45a include/boost/spirit/home/support/detail/lexer/serialise.hpp @comment MD5:ab51948de8685a356d635c1f224a4dc3 include/boost/spirit/home/support/detail/lexer/size_t.hpp @comment MD5:70f198c5211aeb5ad8b0d0062e1915f2 include/boost/spirit/home/support/detail/lexer/state_machine.hpp @comment MD5:e704a1fc8d52f344001f368f957c5378 include/boost/spirit/home/support/detail/lexer/string_token.hpp @comment MD5:010e6044eec59fa17c6bf23347448e6e include/boost/spirit/home/support/detail/math/detail/fp_traits.hpp @comment MD5:76a4fe4e0658f5d96d179afc283e0c54 include/boost/spirit/home/support/detail/math/fpclassify.hpp @comment 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include/boost/spirit/include/classic_no_actions.hpp @comment MD5:fa2f8af86f73685ae5a0f769e307b998 include/boost/spirit/include/classic_numerics.hpp @comment MD5:0a83e6c1c519cac23ad9e4773c930740 include/boost/spirit/include/classic_numerics_fwd.hpp @comment MD5:6b0c66011ae04632f73b82d50e468263 include/boost/spirit/include/classic_operators.hpp @comment MD5:7ca95536c52fc66449cb2208f1291ce0 include/boost/spirit/include/classic_optional.hpp @comment MD5:21f999e0353e1f65cec09fa1a7f1ae19 include/boost/spirit/include/classic_parametric.hpp @comment MD5:213d5f6cf9ba2aee8a410ec4e7ded658 include/boost/spirit/include/classic_parse_tree.hpp @comment MD5:b23a1b0c21a0a24736d7005834371e32 include/boost/spirit/include/classic_parse_tree_fwd.hpp @comment MD5:bf3fafeb2201b0e0072976391c4023a4 include/boost/spirit/include/classic_parse_tree_utils.hpp @comment MD5:244e00107973db2571bfbf69c2f1c962 include/boost/spirit/include/classic_parser.hpp @comment MD5:50cfb4ff613b36569710f266b05e0c8e include/boost/spirit/include/classic_parser_context.hpp @comment MD5:30bb0fa89c16ba187b0d66cb3bde9e89 include/boost/spirit/include/classic_parser_id.hpp @comment MD5:7dac5094235d7497e36c15853e8e5286 include/boost/spirit/include/classic_parser_names.hpp @comment MD5:d53f361f86b5ff43836f30f5a35bfd78 include/boost/spirit/include/classic_parser_traits.hpp @comment MD5:368a51c33b7e80b490e21118556d7858 include/boost/spirit/include/classic_position_iterator.hpp @comment MD5:13dbcd87abc1d177053f27c1d9b4f4d2 include/boost/spirit/include/classic_position_iterator_fwd.hpp @comment MD5:1be46d6f341f6411422fd0bfa31146dd include/boost/spirit/include/classic_positive.hpp @comment MD5:168d4ea7a14fcc079daf96541e247d6e include/boost/spirit/include/classic_primitives.hpp @comment MD5:58da80cc2ed696f23cb5cb33f333ba16 include/boost/spirit/include/classic_push_back_actor.hpp @comment MD5:b8d953b7f7bbe74a713f0869dd499937 include/boost/spirit/include/classic_push_front_actor.hpp @comment MD5:9dbf102b1c8df06d520934245e17138e include/boost/spirit/include/classic_range_run.hpp @comment MD5:6222de89542acf7a5c578caa12db13c3 include/boost/spirit/include/classic_ref_actor.hpp @comment MD5:2493c72207577e3721ed309d95f5802b include/boost/spirit/include/classic_ref_const_ref_actor.hpp @comment MD5:a65ed420548c0ca045d08f53cd8341e2 include/boost/spirit/include/classic_ref_const_ref_const_ref_a.hpp @comment MD5:40fecc508340b6088ff9c07402727e37 include/boost/spirit/include/classic_ref_const_ref_value_actor.hpp @comment MD5:95b35a8e47e1ff128517b02579169adc include/boost/spirit/include/classic_ref_value_actor.hpp @comment MD5:fb519ce4391c5d5875a75d91728c1328 include/boost/spirit/include/classic_refactoring.hpp @comment MD5:b360dfaae30bed10a585724412be6591 include/boost/spirit/include/classic_regex.hpp @comment MD5:5a333d1b6e7914d16b9037dc28efe8c3 include/boost/spirit/include/classic_rule.hpp @comment MD5:a05655f9c27ab4fb660af97ba353eb82 include/boost/spirit/include/classic_rule_alias.hpp @comment MD5:ebde16f0274a816cdb0b4eed4caa118c include/boost/spirit/include/classic_rule_parser.hpp @comment MD5:a02268efd0ef4c96e915e5617345d3d3 include/boost/spirit/include/classic_safe_bool.hpp @comment MD5:ca966a1ed017fa41283097cf5aa5c130 include/boost/spirit/include/classic_scanner.hpp @comment MD5:bd64225510c76664f5debe2ce3b57f54 include/boost/spirit/include/classic_scanner_fwd.hpp @comment MD5:4ad4a05a7073ed7e5a266deb8e9247cd include/boost/spirit/include/classic_scoped_lock.hpp @comment MD5:ac4ee49d410816bd903448d933a6b6e4 include/boost/spirit/include/classic_select.hpp @comment MD5:f1dfee1ae2f68e2f76d166fd5ec8464d include/boost/spirit/include/classic_sequence.hpp @comment MD5:eff7f070f12db61400a1ab26d5685c89 include/boost/spirit/include/classic_sequential_and.hpp @comment MD5:ebd35449707c2d634c42cd9526dd00e0 include/boost/spirit/include/classic_sequential_or.hpp @comment MD5:8934ff034765dd2891eb1c69913e880e include/boost/spirit/include/classic_skipper.hpp @comment MD5:2fb0196bb1658b6b7c6be3b1595215c6 include/boost/spirit/include/classic_skipper_fwd.hpp @comment MD5:c6e7a3bf6c21d90d0e6cfa66409e593c include/boost/spirit/include/classic_spirit.hpp @comment MD5:da073d2ca7c463dff1dbb483a4f575a3 include/boost/spirit/include/classic_static.hpp @comment MD5:2126cbc7e120147a3e916ae1282e4ff7 include/boost/spirit/include/classic_stored_rule.hpp @comment MD5:03182b6553e099f2ebede62fbf95a2fa include/boost/spirit/include/classic_stored_rule_fwd.hpp @comment MD5:5f93f8e9c57fff82c70e3883f4ac3f52 include/boost/spirit/include/classic_subrule.hpp @comment MD5:f82c1e01c6d7c910d9b8324262a72c8c include/boost/spirit/include/classic_subrule_fwd.hpp @comment MD5:e441732519a4cdc14d42368263076997 include/boost/spirit/include/classic_swap_actor.hpp @comment MD5:e2c2be871683ba99b8acfb25f394a332 include/boost/spirit/include/classic_switch.hpp @comment MD5:8c08d6aee85f2c4cfa7879a9b1278f09 include/boost/spirit/include/classic_symbols.hpp @comment MD5:70c548fb9dcafe948380990a183aa0f0 include/boost/spirit/include/classic_symbols_fwd.hpp @comment MD5:4955e274d44cf92967c2eff3372f660f include/boost/spirit/include/classic_traverse.hpp @comment MD5:d6cf0b92ee2d2ece27f54c22afcc0495 include/boost/spirit/include/classic_tree_to_xml.hpp @comment MD5:50fd1301270d50305b141e4ea0cc0a95 include/boost/spirit/include/classic_typeof.hpp @comment MD5:8e7eaeda48c8b2241c0687c412cf4884 include/boost/spirit/include/classic_utility.hpp @comment MD5:6b741208e5291f5386c1479dc5109458 include/boost/spirit/include/classic_version.hpp @comment MD5:b37788d48f2c91f83069739051d2539b include/boost/spirit/include/classic_while.hpp @comment MD5:4eb45de61a662b593ec58eaa19ca5b82 include/boost/spirit/include/karma.hpp @comment MD5:b5a776eee2e86ff34c52c3a0bfd50a28 include/boost/spirit/include/karma_action.hpp @comment MD5:7f4cab71dcdd64c5f16444977263a4d5 include/boost/spirit/include/karma_auxiliary.hpp @comment MD5:348cdba9a70edb46f3fc995605ea281e include/boost/spirit/include/karma_binary.hpp @comment MD5:a8bbf36189f2e446c4516a5f97d50eae include/boost/spirit/include/karma_char.hpp @comment MD5:688ba0a34d09c9692d7c5de43213b481 include/boost/spirit/include/karma_delimit.hpp @comment MD5:7648ef0ca7e6ca43265c8e53fc3c1211 include/boost/spirit/include/karma_directive.hpp @comment MD5:5260a0e35111bcb1d768087b74361f78 include/boost/spirit/include/karma_domain.hpp @comment MD5:6e07107abf672798ed0c53ece8219cfd include/boost/spirit/include/karma_generate.hpp @comment MD5:0174801e49f2611c61accad601d50f1c include/boost/spirit/include/karma_meta_grammar.hpp @comment MD5:bf24a3e7b02977f170c27219c5234483 include/boost/spirit/include/karma_nonterminal.hpp @comment MD5:c4322490e647b69af29176d64f656fc5 include/boost/spirit/include/karma_numeric.hpp @comment MD5:43d1edcb1d9872b15307013ad62a3601 include/boost/spirit/include/karma_operator.hpp @comment MD5:59efc9ea6a92d11f6b443247486aca94 include/boost/spirit/include/karma_stream.hpp @comment MD5:ed8766876ff5517530140ceb76fa9685 include/boost/spirit/include/karma_string.hpp @comment MD5:db9c1b3c6392838769a83e7e442b0870 include/boost/spirit/include/karma_what.hpp @comment MD5:cf0ac782ba404fc7d3f865b7da69917f include/boost/spirit/include/lex.hpp @comment MD5:43e20eb637ee873a93e3a67fc35532e8 include/boost/spirit/include/lex_domain.hpp @comment MD5:4ab5975e341eb823e2c7f424094fed82 include/boost/spirit/include/lex_lexer.hpp @comment MD5:c1cb56a4e87b6139c15e9237fe09dcee include/boost/spirit/include/lex_lexer_lexertl.hpp @comment MD5:0200a869419e460e312339ff8d4e5bb5 include/boost/spirit/include/lex_lexer_static_lexertl.hpp @comment MD5:56ffd6d93df302098384bd4a516fb0d3 include/boost/spirit/include/lex_meta_grammar.hpp @comment MD5:f0d0c47ed389e802caf05019cd55a240 include/boost/spirit/include/lex_set_state.hpp @comment MD5:6c512d3cfc54d97b1e17bd957acd80f1 include/boost/spirit/include/lex_tokenize_and_parse.hpp @comment MD5:9a30310e039e80479ea1adc155d57803 include/boost/spirit/include/phoenix.hpp @comment MD5:d85b21b615a4c8c3014108bab23c296a include/boost/spirit/include/phoenix1.hpp @comment MD5:bda049417ef2fc1411dddab7e0b6e281 include/boost/spirit/include/phoenix1_actor.hpp @comment MD5:21dd59ed2f7fac73fbf52173e4dade32 include/boost/spirit/include/phoenix1_binders.hpp @comment MD5:27b3b70aa7a11f16986b10294406cca3 include/boost/spirit/include/phoenix1_casts.hpp @comment MD5:beae26e6a1997d4cb3d56df8f48eb47f include/boost/spirit/include/phoenix1_closures.hpp @comment MD5:9a7076f5bea80c6f74567b8484ff40bd include/boost/spirit/include/phoenix1_composite.hpp @comment MD5:6c64b274f75171f6147c666260212083 include/boost/spirit/include/phoenix1_functions.hpp @comment MD5:5233fc3f93aca3f62617a882c04279c1 include/boost/spirit/include/phoenix1_new.hpp @comment MD5:c4536050c184362fb084821453a634bc include/boost/spirit/include/phoenix1_operators.hpp @comment MD5:1ffde685f592d5d54556988ae7a9e7bf include/boost/spirit/include/phoenix1_primitives.hpp @comment MD5:8f16b1388de7a4cf56b4853d20bfed8f include/boost/spirit/include/phoenix1_special_ops.hpp @comment MD5:18f9b035316c93204bb742174d016132 include/boost/spirit/include/phoenix1_statements.hpp @comment MD5:fca3e500c8b65f6d2db5f8806d3b2211 include/boost/spirit/include/phoenix1_tuple_helpers.hpp @comment MD5:8d29c767c8c5814a5f53bedbd69772e1 include/boost/spirit/include/phoenix1_tuples.hpp @comment MD5:08810d8aa766f5df26010a10d6311e0e include/boost/spirit/include/phoenix_algorithm.hpp @comment MD5:b92536035d1e13465dacb00f98b99c89 include/boost/spirit/include/phoenix_bind.hpp @comment MD5:501dff64fab96780074880ee320b5371 include/boost/spirit/include/phoenix_container.hpp @comment MD5:5f5ad734dadd539d81de05587c53faf3 include/boost/spirit/include/phoenix_core.hpp @comment MD5:7a70759a9a4d90441e87abe3649cebd3 include/boost/spirit/include/phoenix_function.hpp @comment MD5:9626cc7c3ab4857cfed3f7f8d25728ba include/boost/spirit/include/phoenix_fusion.hpp @comment MD5:acfc8f01bc024636175b7a554268b814 include/boost/spirit/include/phoenix_object.hpp @comment MD5:06d2819e497dde637ddcc69f150434de include/boost/spirit/include/phoenix_operator.hpp @comment MD5:f3338ca12024bbf4e3f2b8b76f6a78ac include/boost/spirit/include/phoenix_scope.hpp @comment MD5:170888070d79247898cac098373ee8c7 include/boost/spirit/include/phoenix_statement.hpp @comment MD5:f13b33006be0554c17471271f362887b include/boost/spirit/include/phoenix_stl.hpp @comment MD5:70f1e0d8d04e198f8989c685a4fe8149 include/boost/spirit/include/phoenix_version.hpp @comment MD5:dd2342718287e251b3f67e31c0bdcb8a include/boost/spirit/include/qi.hpp @comment MD5:13f070b8a8eb34795ccfe16c1f4cd66f include/boost/spirit/include/qi_action.hpp @comment MD5:7a26113cf3e3b1c21120a225e728f4c5 include/boost/spirit/include/qi_auxiliary.hpp @comment MD5:dd2bd83328a2ae231e5dc74bd8b1dd6b include/boost/spirit/include/qi_binary.hpp @comment MD5:cc6d4c93b2032b40d676951dbf6a70a1 include/boost/spirit/include/qi_char.hpp @comment MD5:e281007a0d56a1c7e89fec919a0a69b5 include/boost/spirit/include/qi_debug.hpp @comment MD5:04713e3af9ffbeaadde351d5e125fd71 include/boost/spirit/include/qi_directive.hpp @comment MD5:7b89e01d49ae4d9a8347d89a47ed1a0f include/boost/spirit/include/qi_domain.hpp @comment MD5:b2bfd2fe06f1234fc34abbe5ae0826c5 include/boost/spirit/include/qi_meta_grammar.hpp @comment MD5:1dcab50a3432d64d3932169ac446c8f6 include/boost/spirit/include/qi_nonterminal.hpp @comment MD5:b81037a6e76822853184f3a32bb51369 include/boost/spirit/include/qi_numeric.hpp @comment MD5:86e0c3940d63084ed94c4f8041f18f73 include/boost/spirit/include/qi_operator.hpp @comment MD5:2563b5ffa2bc2f702da5da236309f89e include/boost/spirit/include/qi_parse.hpp @comment MD5:03ff084be0252fda114dce6e42fe2f61 include/boost/spirit/include/qi_skip.hpp @comment MD5:fb35a7c13129cd8e7b049ea33e1883a9 include/boost/spirit/include/qi_stream.hpp @comment MD5:e754017ca03100d51f1711ad80bf0fea include/boost/spirit/include/qi_string.hpp @comment MD5:b6697e4e5aefa48650bfd54548992b32 include/boost/spirit/include/qi_what.hpp @comment MD5:c5a133759d5bafa6f0fd7c1a14b25cc5 include/boost/spirit/include/support.hpp @comment MD5:518b89cea426d17e13b43b4fe4376bca include/boost/spirit/include/support_any.hpp @comment MD5:90ce7223d37aefd1552654eb245e1284 include/boost/spirit/include/support_any_if.hpp @comment MD5:d8592d57d95eebf0ddd1c12d5eebd5f8 include/boost/spirit/include/support_any_ns.hpp @comment MD5:2c9d7e540453d27a3162a8db638ed01f include/boost/spirit/include/support_argument.hpp @comment MD5:2b9979429f56e0034eb2ce138610e894 include/boost/spirit/include/support_as_variant.hpp @comment MD5:6f619f8e31c929c58b1c3f21e3389069 include/boost/spirit/include/support_ascii.hpp @comment MD5:0df21275546d0a27fdb82ff949f16604 include/boost/spirit/include/support_attribute_of.hpp @comment MD5:e76d5f95262ee2b345c09c673f1fe9e8 include/boost/spirit/include/support_attribute_transform.hpp @comment MD5:7f847beefb7c6baa730e702146266c0e include/boost/spirit/include/support_basic_rules.hpp @comment MD5:8931709ddd01bf4e2301a72856c4f90a include/boost/spirit/include/support_basic_transforms.hpp @comment MD5:8c61bf559fcde134aff04bd106fb3967 include/boost/spirit/include/support_char_class.hpp @comment MD5:ed18bc886dd2835a6bf2237d8bfbb3a1 include/boost/spirit/include/support_component.hpp @comment MD5:1b4aca9d52e65ee2cdf82e7c65e183a2 include/boost/spirit/include/support_functor_holder.hpp @comment MD5:b523003615a09167a543f1ca3bc8545a include/boost/spirit/include/support_grammar.hpp @comment MD5:c6a4e7096d8be803bd9386f4583da263 include/boost/spirit/include/support_iso8859_1.hpp @comment MD5:e828828bee75e05530833b9e1b1812e8 include/boost/spirit/include/support_locals.hpp @comment MD5:773f9b5ab608e6e70827d01f93271ce8 include/boost/spirit/include/support_look_ahead.hpp @comment MD5:1edd65086605d35c2f8d45801fa23451 include/boost/spirit/include/support_meta_function_holder.hpp @comment MD5:173a3de95e33e6a9a7605c0fe52858b1 include/boost/spirit/include/support_meta_grammar.hpp @comment MD5:c57486042585912a7c95798932613005 include/boost/spirit/include/support_modifier.hpp @comment MD5:e346817c023ff11dc0f7501da1dbea50 include/boost/spirit/include/support_multi_pass.hpp @comment MD5:7460d83f5b786f877106ec2b789a584a include/boost/spirit/include/support_multi_pass_fwd.hpp @comment MD5:3d28adb4392641f3862161733235ac7e include/boost/spirit/include/support_nonterminal.hpp @comment MD5:b57bab2362af81c6f5ebb1e6366c4fd4 include/boost/spirit/include/support_placeholders.hpp @comment MD5:c67140dc44a75b3ab9bb252d1ce00ac8 include/boost/spirit/include/support_safe_bool.hpp @comment MD5:8abb5f52bdf4d8c7fd052fc2223228db include/boost/spirit/include/support_standard.hpp @comment MD5:67f94d2758c7f3098baa389674780b59 include/boost/spirit/include/support_standard_wide.hpp @comment MD5:1187b91e865e083eb09fb7aab1d38a2b include/boost/spirit/include/support_unused.hpp @comment MD5:fbcf2f7315c8ecaebba24336f2da86bc include/boost/spirit/iterator.hpp @comment MD5:99f951066f00493afcb0c95f5f429143 include/boost/spirit/iterator/file_iterator.hpp @comment MD5:ff4f90a66dfdcb998b49ff52dc0cd73b include/boost/spirit/iterator/file_iterator_fwd.hpp @comment MD5:f2e776ae7827f1c264e40d4762500c80 include/boost/spirit/iterator/fixed_size_queue.hpp @comment MD5:e39cc38483e531321fec0af9459240ba include/boost/spirit/iterator/multi_pass.hpp @comment MD5:69ab2c824d7ea36aa06c5831fe3522f6 include/boost/spirit/iterator/multi_pass_fwd.hpp @comment MD5:0cb740ddf0f5e2b0193b3cfec6459ce4 include/boost/spirit/iterator/position_iterator.hpp @comment MD5:5c5a36c32a38716f0ee448cb17c586c6 include/boost/spirit/iterator/position_iterator_fwd.hpp @comment MD5:7660bdc4269f39557decd530c5a66025 include/boost/spirit/iterator/typeof.hpp @comment MD5:ab63b99aa38fb917d67cfa879a7feba9 include/boost/spirit/meta.hpp @comment MD5:60f936c0530acd3a0b7cc08667852f3e include/boost/spirit/meta/as_parser.hpp @comment MD5:2b7c453e2463936358f71228601406c1 include/boost/spirit/meta/fundamental.hpp @comment MD5:f1c6f0cdc26f01a9671cf237ada88a48 include/boost/spirit/meta/parser_traits.hpp @comment MD5:2b39864007d0971deb856ae991b30bdc include/boost/spirit/meta/refactoring.hpp @comment MD5:347f0ddd7a24e425277895726f8446e6 include/boost/spirit/meta/traverse.hpp @comment MD5:b7a5bb6feeb82a3811876a881c097444 include/boost/spirit/phoenix.hpp @comment MD5:c1f44e3b0208185d2f7972a960f3f9a6 include/boost/spirit/phoenix/actor.hpp @comment MD5:b733457b8329329cfe780bf6fb4af0d3 include/boost/spirit/phoenix/binders.hpp @comment MD5:976393f51c91839bd31c05f60008d5ca include/boost/spirit/phoenix/casts.hpp @comment MD5:841b1ef50e2dcff0ff1f10a6314f5f10 include/boost/spirit/phoenix/closures.hpp @comment MD5:07ebb8e1751ea175dc63804aa4b94ea2 include/boost/spirit/phoenix/composite.hpp @comment MD5:8914ab314e819c3e21d3e67c90bec3e4 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include/boost/units/physical_dimensions/time.hpp @comment MD5:e14c7843b6fb503b5a89919eb569f9b1 include/boost/units/physical_dimensions/torque.hpp @comment MD5:9b5453ff7ee5018c459a7a12b963bd6f include/boost/units/physical_dimensions/velocity.hpp @comment MD5:6b6898ab14861d1f5e40cc78b4c9f549 include/boost/units/physical_dimensions/volume.hpp @comment MD5:a6023a7c900285a4fb328ed80e0fdf00 include/boost/units/physical_dimensions/wavenumber.hpp @comment MD5:c768764b57df31c702f014ee02ddaa0f include/boost/units/pow.hpp @comment MD5:c5d22dfd4169487103ab0845b3638961 include/boost/units/quantity.hpp @comment MD5:e379409dd644f62c7b58de6ccc297c32 include/boost/units/reduce_unit.hpp @comment MD5:b98bcab2302c314d323eeb064cb5adf1 include/boost/units/scale.hpp @comment MD5:ee83dc0dab4b8221151dcbed5db5f43c include/boost/units/scaled_base_unit.hpp @comment MD5:aab4e482d4545d9527e5edeaff496d74 include/boost/units/static_constant.hpp @comment MD5:8663994b20854fb50914f0780d8b4584 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include/boost/units/systems/si/codata/triton_constants.hpp @comment MD5:05735c73f56be73bc253bf1d48331414 include/boost/units/systems/si/codata/typedefs.hpp @comment MD5:10bd8f76973b65de2e47c5ea2b9f5636 include/boost/units/systems/si/codata/universal_constants.hpp @comment MD5:401c2b6a1cd468ff5417df8c05d152c8 include/boost/units/systems/si/codata_constants.hpp @comment MD5:d4377291ba911354f797c3157951058c include/boost/units/systems/si/conductance.hpp @comment MD5:0030d6c8f6693ba336e9aabebeaa5d83 include/boost/units/systems/si/conductivity.hpp @comment MD5:f8b8b627d7e29edb009cd7ded09f8466 include/boost/units/systems/si/current.hpp @comment MD5:ad43bc5adcd011e6ea1e347661fea738 include/boost/units/systems/si/dimensionless.hpp @comment MD5:a18359b8d058c8eca2d7698aa4e11d8f include/boost/units/systems/si/dose_equivalent.hpp @comment MD5:ee0f1a11f250bfa3a34b7e5761e598ee include/boost/units/systems/si/dynamic_viscosity.hpp @comment MD5:a0c45a9cbd19ca306a16519b3dccd44c include/boost/units/systems/si/electric_charge.hpp @comment MD5:641e19155ee0fd88fe8dd780c07d9155 include/boost/units/systems/si/electric_potential.hpp @comment MD5:2fe65c9622e92b6e9321b0814ccd8e35 include/boost/units/systems/si/energy.hpp @comment MD5:0312700fc4bae8a47b71bf10ae0a337f include/boost/units/systems/si/force.hpp @comment MD5:7502ffefa1d24b9650279b7a43162e7a include/boost/units/systems/si/frequency.hpp @comment MD5:14986eba52fb3699b8d60ed685bf272f include/boost/units/systems/si/illuminance.hpp @comment MD5:1dc858f1ff417ccae7a14e87b7218e9f include/boost/units/systems/si/impedance.hpp @comment MD5:8c76ef9ef6032ea9a6ee4c688b1e4ad4 include/boost/units/systems/si/inductance.hpp @comment MD5:df7f6d2188627811ab7f5cfb0b038aa3 include/boost/units/systems/si/io.hpp @comment MD5:f31b90b561812e4575a813c9343ffbb2 include/boost/units/systems/si/kinematic_viscosity.hpp @comment MD5:3ca3d0f10ae330b20d38762df429f025 include/boost/units/systems/si/length.hpp @comment 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MD5:09ee162a0cbd0415cbde1855960591b3 include/boost/xpressive/proto/expr.hpp @comment MD5:7a878b24a07531b6adbf34b22637cf9a include/boost/xpressive/proto/extends.hpp @comment MD5:dc11f0f8f4348f7f79ef462a3d7dfbb7 include/boost/xpressive/proto/fusion.hpp @comment MD5:ce2a0f6468e43d5ff81500dd9eb4708d include/boost/xpressive/proto/generate.hpp @comment MD5:adb7a9e52e852324829f8077a82fc0b5 include/boost/xpressive/proto/literal.hpp @comment MD5:91b38f1bd94d3ae3bd25db5ab6b29016 include/boost/xpressive/proto/make_expr.hpp @comment MD5:a88cf0f70c031ec07b12c30278f4491b include/boost/xpressive/proto/matches.hpp @comment MD5:f050a4f20297f6a05788704e2bdb46a8 include/boost/xpressive/proto/operators.hpp @comment MD5:b330db624d7a74a5dbb4df36c92542eb include/boost/xpressive/proto/proto.hpp @comment MD5:10e888237bdb4af5eeb5e0ac7dd23582 include/boost/xpressive/proto/proto_fwd.hpp @comment MD5:e92c171975204998ced9477c8464a43f include/boost/xpressive/proto/proto_typeof.hpp @comment MD5:afe0a651b1a6ccdbb1838ea28316f33d include/boost/xpressive/proto/ref.hpp @comment MD5:a74184611aa883cb9915b5c2dcd0d347 include/boost/xpressive/proto/tags.hpp @comment MD5:111aaa9e0955b1dd10d26370ddcc4997 include/boost/xpressive/proto/traits.hpp @comment MD5:976716ee8e3b5b68808c2677268b1ef3 include/boost/xpressive/proto/transform.hpp @comment MD5:0045c594191bc6325e496d396d6fd437 include/boost/xpressive/proto/transform/arg.hpp @comment MD5:94cb73b367000d2513f8744f9c3dd8dd include/boost/xpressive/proto/transform/bind.hpp @comment MD5:34389f8e15e31667c56d961ee23b46a8 include/boost/xpressive/proto/transform/call.hpp @comment MD5:78398a697f37e9061abfa7f91b224795 include/boost/xpressive/proto/transform/fold.hpp @comment MD5:621222b11bd354c2d9f025af2de3e73d include/boost/xpressive/proto/transform/fold_tree.hpp @comment MD5:b2e4e6696001d417b8104a73b6f27179 include/boost/xpressive/proto/transform/make.hpp @comment MD5:ec76d6ccbb7444c27d887f30ff9a1da8 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MD5:cefa663c01764ea6ed71d30d7cc1b7b7 include/boost/xpressive/sub_match.hpp @comment MD5:c58d6512114b1e8e4005fd2ee564446c include/boost/xpressive/traits/c_regex_traits.hpp @comment MD5:3a0178aca33a7822d6421c95e87a867f include/boost/xpressive/traits/cpp_regex_traits.hpp @comment MD5:63d91ed46bebf66e25b7212157fa740c include/boost/xpressive/traits/detail/c_ctype.hpp @comment MD5:d7ee1ea9d280f05317267fe4f72e77b3 include/boost/xpressive/traits/null_regex_traits.hpp @comment MD5:1e5090500aa1bc045a2ed4e663c333b2 include/boost/xpressive/xpressive.hpp @comment MD5:2563f9caa3d75180d6afe35fd0b9dad8 include/boost/xpressive/xpressive_dynamic.hpp @comment MD5:7b98ea028bb65bd548980c41008cf36b include/boost/xpressive/xpressive_fwd.hpp @comment MD5:d09c62052b9929b387b4616d9119f282 include/boost/xpressive/xpressive_static.hpp @comment MD5:f876e69780ccd201c0403ee8fc17af1f include/boost/xpressive/xpressive_typeof.hpp @comment MD5:01aa1de6ab99c876ba53d95a17a2b561 @dirrm include/boost/xpressive/traits/detail 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The emphasis is on portable libraries which work well with the ISO C++ Standard Library. This package provides all the Boost header files required at build-time to compile any package that requires Boost. Binary libraries are provided in the boost-libs and boost-python packages. 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Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_ACCUMULATORS_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_ACCUMULATORS_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #endif include/boost/accumulators/accumulators_fwd.hpp000644 000000 000000 00000017605 11124251427 022372 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // accumulators_fwd.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_ACCUMULATORS_FWD_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_ACCUMULATORS_FWD_HPP_EAN_28_10_2005 #include #include // for mpl::na #include #include #include #include #include #include #include #ifndef BOOST_ACCUMULATORS_MAX_FEATURES /// The maximum number of accumulators that may be put in an accumulator_set. /// Defaults to BOOST_MPL_LIMIT_VECTOR_SIZE (which defaults to 20). # define BOOST_ACCUMULATORS_MAX_FEATURES BOOST_MPL_LIMIT_VECTOR_SIZE #endif #if BOOST_ACCUMULATORS_MAX_FEATURES > BOOST_MPL_LIMIT_VECTOR_SIZE # error BOOST_ACCUMULATORS_MAX_FEATURES cannot be larger than BOOST_MPL_LIMIT_VECTOR_SIZE #endif #ifndef BOOST_ACCUMULATORS_MAX_ARGS /// The maximum number of arguments that may be specified to an accumulator_set's /// accumulation function. Defaults to 15. # define BOOST_ACCUMULATORS_MAX_ARGS 15 #endif #if BOOST_WORKAROUND(__GNUC__, == 3) \ || BOOST_WORKAROUND(__EDG_VERSION__, BOOST_TESTED_AT(306)) # define BOOST_ACCUMULATORS_BROKEN_CONST_OVERLOADS #endif #ifdef BOOST_ACCUMULATORS_BROKEN_CONST_OVERLOADS # include # include # define BOOST_ACCUMULATORS_PROTO_DISABLE_IF_IS_CONST(T)\ , typename boost::disable_if >::type * = 0 #else # define BOOST_ACCUMULATORS_PROTO_DISABLE_IF_IS_CONST(T) #endif namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////////// // Named parameters tags // namespace tag { struct sample; struct weight; struct accumulator; struct weights; } /////////////////////////////////////////////////////////////////////////////// // User-level features // namespace tag { template struct value; template struct value_tag; template struct reference; template struct reference_tag; template struct external; template struct droppable; } template struct droppable_accumulator_base; template struct droppable_accumulator; template struct with_cached_result; template struct accumulator_set; template struct extractor; template struct feature_of; template struct as_feature; template struct as_weighted_feature; template struct depends_on; template struct features; template typename mpl::apply::type const & find_accumulator(AccumulatorSet const &acc); template typename mpl::apply::type::result_type extract_result(AccumulatorSet const &acc); template typename mpl::apply::type::result_type extract_result(AccumulatorSet const &acc, A1 const &a1); // ... other overloads generated by Boost.Preprocessor: /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_EXTRACT_RESULT_FWD(z, n, _) \ template< \ typename Feature \ , typename AccumulatorSet \ BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, typename A) \ > \ typename mpl::apply::type::result_type \ extract_result( \ AccumulatorSet const &acc \ BOOST_PP_ENUM_TRAILING_BINARY_PARAMS_Z(z, n, A, const &a) \ ); /// INTERNAL ONLY /// BOOST_PP_REPEAT_FROM_TO( 2 , BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS) , BOOST_ACCUMULATORS_EXTRACT_RESULT_FWD , _ ) #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED template typename mpl::apply::type::result_type extract_result(AccumulatorSet const &acc, A1 const &a1, A2 const &a2 ...); #endif namespace impl { using namespace numeric::operators; template struct external_impl; } namespace detail { template struct feature_tag; template struct to_accumulator; struct accumulator_set_base; template struct is_accumulator_set; } }} // namespace boost::accumulators // For defining boost::parameter keywords that can be inherited from to // get a nested, class-scoped keyword with the requested alias #define BOOST_PARAMETER_NESTED_KEYWORD(tag_namespace, name, alias) \ namespace tag_namespace \ { \ template \ struct name ## _ \ { \ static char const* keyword_name() \ { \ return #name; \ } \ static ::boost::parameter::keyword > &alias; \ }; \ template \ ::boost::parameter::keyword > &name ## _::alias = \ ::boost::parameter::keyword >::get(); \ typedef name ## _ <> name; \ } \ namespace \ { \ ::boost::parameter::keyword &name = \ ::boost::parameter::keyword::get(); \ } #endif include/boost/accumulators/framework/accumulator_base.hpp000644 000000 000000 00000002666 11124251710 024332 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // accumulator_base.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_BASE_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_BASE_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace detail { typedef void void_; } /////////////////////////////////////////////////////////////////////////////// // dont_care // struct dont_care { template dont_care(Args const &) { } }; /////////////////////////////////////////////////////////////////////////////// // accumulator_base // struct accumulator_base { // hidden if defined in derived classes detail::void_ operator ()(dont_care) { } typedef mpl::false_ is_droppable; detail::void_ add_ref(dont_care) { } detail::void_ drop(dont_care) { } detail::void_ on_drop(dont_care) { } }; }} // namespace boost::accumulators #endif include/boost/accumulators/framework/accumulator_concept.hpp000644 000000 000000 00000001325 11124251710 025042 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // accumulator_concept.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATOR_CONCEPT_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATOR_CONCEPT_HPP_EAN_28_10_2005 #include namespace boost { namespace accumulators { template struct accumulator_concept { void constraints() { // TODO: define the stat concept } Stat stat; }; }} // namespace boost::accumulators #endif include/boost/accumulators/framework/accumulator_set.hpp000644 000000 000000 00000035314 11124251710 024207 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // accumulator_set.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATOR_SET_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATOR_SET_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace detail { /////////////////////////////////////////////////////////////////////////////// // accumulator_visitor // wrap a boost::parameter argument pack in a Fusion extractor object template struct accumulator_visitor { explicit accumulator_visitor(Args const &args) : args(args) { } template void operator ()(Accumulator &accumulator) const { accumulator(this->args); } private: accumulator_visitor &operator =(accumulator_visitor const &); Args const &args; }; template inline accumulator_visitor const make_accumulator_visitor(Args const &args) { return accumulator_visitor(args); } typedef parameter::parameters< parameter::required , parameter::optional // ... and others which are not specified here... > accumulator_params; /////////////////////////////////////////////////////////////////////////////// // accumulator_set_base struct accumulator_set_base { }; /////////////////////////////////////////////////////////////////////////////// // is_accumulator_set template struct is_accumulator_set : is_base_and_derived { }; } // namespace detail #ifdef _MSC_VER #pragma warning(push) #pragma warning(disable: 4355) // warning C4355: 'this' : used in base member initializer list #endif /////////////////////////////////////////////////////////////////////////////// /// \brief A set of accumulators. /// /// accumulator_set resolves the dependencies between features and ensures that /// the accumulators in the set are updated in the proper order. /// /// acccumulator_set provides a general mechanism to visit the accumulators /// in the set in order, with or without a filter. You can also fetch a reference /// to an accumulator that corresponds to a feature. /// template struct accumulator_set : detail::accumulator_set_base { typedef Sample sample_type; ///< The type of the samples that will be accumulated typedef Features features_type; ///< An MPL sequence of the features that should be accumulated. typedef Weight weight_type; ///< The type of the weight parameter. Must be a scalar. Defaults to void. /// INTERNAL ONLY /// typedef typename detail::make_accumulator_tuple< Features , Sample , Weight >::type accumulators_mpl_vector; // generate a fusion::list of accumulators /// INTERNAL ONLY /// typedef typename detail::meta::make_acc_list< accumulators_mpl_vector >::type accumulators_type; /// INTERNAL ONLY /// //BOOST_MPL_ASSERT((mpl::is_sequence)); /////////////////////////////////////////////////////////////////////////////// /// default-construct all contained accumulators accumulator_set() : accumulators( detail::make_acc_list( accumulators_mpl_vector() , detail::accumulator_params()(*this) ) ) { // Add-ref the Features that the user has specified this->template visit_if >( detail::make_add_ref_visitor(detail::accumulator_params()(*this)) ); } /// \overload /// /// \param a1 Optional named parameter to be passed to all the accumulators template explicit accumulator_set(A1 const &a1) : accumulators( detail::make_acc_list( accumulators_mpl_vector() , detail::accumulator_params()(*this, a1) ) ) { // Add-ref the Features that the user has specified this->template visit_if >( detail::make_add_ref_visitor(detail::accumulator_params()(*this)) ); } // ... other overloads generated by Boost.Preprocessor: /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_ACCUMULATOR_SET_CTOR(z, n, _) \ template \ accumulator_set(BOOST_PP_ENUM_BINARY_PARAMS_Z(z, n, A, const &a)) \ : accumulators( \ detail::make_acc_list( \ accumulators_mpl_vector() \ , detail::accumulator_params()( \ *this BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a) \ ) \ ) \ ) \ { \ /* Add-ref the Features that the user has specified */ \ this->template visit_if >( \ detail::make_add_ref_visitor(detail::accumulator_params()(*this)) \ ); \ } /// INTERNAL ONLY /// BOOST_PP_REPEAT_FROM_TO( 2 , BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS) , BOOST_ACCUMULATORS_ACCUMULATOR_SET_CTOR , _ ) #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED /// \overload /// template accumulator_set(A1 const &a1, A2 const &a2, ...); #endif // ... other overloads generated by Boost.Preprocessor below ... /////////////////////////////////////////////////////////////////////////////// /// Visitation /// \param func UnaryFunction which is invoked with each accumulator in turn. template void visit(UnaryFunction const &func) { fusion::for_each(this->accumulators, func); } /////////////////////////////////////////////////////////////////////////////// /// Conditional visitation /// \param func UnaryFunction which is invoked with each accumulator in turn, /// provided the accumulator satisfies the MPL predicate FilterPred. template void visit_if(UnaryFunction const &func) { fusion::filter_view filtered_accs(this->accumulators); fusion::for_each(filtered_accs, func); } /////////////////////////////////////////////////////////////////////////////// /// The return type of the operator() overloads is void. typedef void result_type; /////////////////////////////////////////////////////////////////////////////// /// Accumulation /// \param a1 Optional named parameter to be passed to all the accumulators void operator ()() { this->visit( detail::make_accumulator_visitor( detail::accumulator_params()(*this) ) ); } template void operator ()(A1 const &a1) { this->visit( detail::make_accumulator_visitor( detail::accumulator_params()(*this, a1) ) ); } // ... other overloads generated by Boost.Preprocessor: /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_ACCUMULATOR_SET_FUN_OP(z, n, _) \ template \ void operator ()(BOOST_PP_ENUM_BINARY_PARAMS_Z(z, n, A, const &a)) \ { \ this->visit( \ detail::make_accumulator_visitor( \ detail::accumulator_params()( \ *this BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a) \ ) \ ) \ ); \ } /// INTERNAL ONLY /// BOOST_PP_REPEAT_FROM_TO( 2 , BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS) , BOOST_ACCUMULATORS_ACCUMULATOR_SET_FUN_OP , _ ) #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED /// \overload /// template void operator ()(A1 const &a1, A2 const &a2, ...); #endif /////////////////////////////////////////////////////////////////////////////// /// Extraction template struct apply : fusion::result_of::value_of< typename fusion::result_of::find_if< accumulators_type , detail::matches_feature >::type > { }; /////////////////////////////////////////////////////////////////////////////// /// Extraction template typename apply::type &extract() { return *fusion::find_if >(this->accumulators); } /// \overload template typename apply::type const &extract() const { return *fusion::find_if >(this->accumulators); } /////////////////////////////////////////////////////////////////////////////// /// Drop template void drop() { // You can only drop the features that you have specified explicitly typedef typename apply::type the_accumulator; BOOST_MPL_ASSERT((detail::contains_feature_of)); typedef typename feature_of::type>::type the_feature; (*fusion::find_if >(this->accumulators)) .drop(detail::accumulator_params()(*this)); // Also drop accumulators that this feature depends on typedef typename the_feature::dependencies dependencies; this->template visit_if >( detail::make_drop_visitor(detail::accumulator_params()(*this)) ); } private: accumulators_type accumulators; }; #ifdef _MSC_VER #pragma warning(pop) #endif /////////////////////////////////////////////////////////////////////////////// // find_accumulator // find an accumulator in an accumulator_set corresponding to a feature template typename mpl::apply::type & find_accumulator(AccumulatorSet &acc BOOST_ACCUMULATORS_PROTO_DISABLE_IF_IS_CONST(AccumulatorSet)) { return acc.template extract(); } /// \overload template typename mpl::apply::type const & find_accumulator(AccumulatorSet const &acc) { return acc.template extract(); } /////////////////////////////////////////////////////////////////////////////// // extract_result // extract a result from an accumulator set /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_EXTRACT_RESULT_FUN(z, n, _) \ template< \ typename Feature \ , typename AccumulatorSet \ BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, typename A) \ > \ typename mpl::apply::type::result_type \ extract_result( \ AccumulatorSet const &acc \ BOOST_PP_ENUM_TRAILING_BINARY_PARAMS_Z(z, n, A, const &a) \ ) \ { \ return find_accumulator(acc).result( \ detail::accumulator_params()( \ acc \ BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a) \ ) \ ); \ } BOOST_PP_REPEAT( BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS) , BOOST_ACCUMULATORS_EXTRACT_RESULT_FUN , _ ) }} // namespace boost::accumulators #endif include/boost/accumulators/framework/accumulators/droppable_accumulator.hpp000644 000000 000000 00000023026 11124251217 030065 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // droppable_accumulator.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_DROPPABLE_ACCUMULATOR_HPP_EAN_13_12_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_DROPPABLE_ACCUMULATOR_HPP_EAN_13_12_2005 #include #include #include #include #include // for feature_of #include // for accumulator namespace boost { namespace accumulators { template struct droppable_accumulator; namespace detail { /////////////////////////////////////////////////////////////////////////////// // add_ref_visitor // a fusion function object for add_ref'ing accumulators template struct add_ref_visitor { explicit add_ref_visitor(Args const &args) : args_(args) { } template void operator ()(Accumulator &acc) const { typedef typename Accumulator::feature_tag::dependencies dependencies; acc.add_ref(this->args_); // Also add_ref accumulators that this feature depends on this->args_[accumulator].template visit_if >( *this ); } private: add_ref_visitor &operator =(add_ref_visitor const &); Args const &args_; }; template add_ref_visitor make_add_ref_visitor(Args const &args) { return add_ref_visitor(args); } /////////////////////////////////////////////////////////////////////////////// // drop_visitor // a fusion function object for dropping accumulators template struct drop_visitor { explicit drop_visitor(Args const &args) : args_(args) { } template void operator ()(Accumulator &acc) const { if(typename Accumulator::is_droppable()) { typedef typename Accumulator::feature_tag::dependencies dependencies; acc.drop(this->args_); // Also drop accumulators that this feature depends on this->args_[accumulator].template visit_if >( *this ); } } private: drop_visitor &operator =(drop_visitor const &); Args const &args_; }; template drop_visitor make_drop_visitor(Args const &args) { return drop_visitor(args); } } ////////////////////////////////////////////////////////////////////////// // droppable_accumulator_base template struct droppable_accumulator_base : Accumulator { typedef droppable_accumulator_base base; typedef mpl::true_ is_droppable; typedef typename Accumulator::result_type result_type; template droppable_accumulator_base(Args const &args) : Accumulator(args) , ref_count_(0) { } template void operator ()(Args const &args) { if(!this->is_dropped()) { this->Accumulator::operator ()(args); } } template void add_ref(Args const &) { ++this->ref_count_; } template void drop(Args const &args) { BOOST_ASSERT(0 < this->ref_count_); if(1 == this->ref_count_) { static_cast *>(this)->on_drop(args); } --this->ref_count_; } bool is_dropped() const { return 0 == this->ref_count_; } private: int ref_count_; }; ////////////////////////////////////////////////////////////////////////// // droppable_accumulator // this can be specialized for any type that needs special handling template struct droppable_accumulator : droppable_accumulator_base { template droppable_accumulator(Args const &args) : droppable_accumulator::base(args) { } }; ////////////////////////////////////////////////////////////////////////// // with_cached_result template struct with_cached_result : Accumulator { typedef typename Accumulator::result_type result_type; template with_cached_result(Args const &args) : Accumulator(args) , cache() { } with_cached_result(with_cached_result const &that) : Accumulator(*static_cast(&that)) , cache() { if(that.has_result()) { this->set(that.get()); } } ~with_cached_result() { // Since this is a base class of droppable_accumulator_base, // this destructor is called before any of droppable_accumulator_base's // members get cleaned up, including is_dropped, so the following // call to has_result() is valid. if(this->has_result()) { this->get().~result_type(); } } template void on_drop(Args const &args) { // cache the result at the point this calcuation was dropped BOOST_ASSERT(!this->has_result()); this->set(this->Accumulator::result(args)); } template result_type result(Args const &args) const { return this->has_result() ? this->get() : this->Accumulator::result(args); } private: with_cached_result &operator =(with_cached_result const &); void set(result_type const &result) { ::new(this->cache.address()) result_type(result); } result_type const &get() const { return *static_cast(this->cache.address()); } bool has_result() const { typedef with_cached_result this_type; typedef droppable_accumulator_base derived_type; return static_cast(this)->is_dropped(); } aligned_storage cache; }; namespace tag { template struct as_droppable { typedef droppable type; }; template struct as_droppable > { typedef droppable type; }; ////////////////////////////////////////////////////////////////////////// // droppable template struct droppable : as_feature::type { typedef typename as_feature::type feature_type; typedef typename feature_type::dependencies tmp_dependencies_; typedef typename mpl::transform< typename feature_type::dependencies , as_droppable >::type dependencies; struct impl { template struct apply { typedef droppable_accumulator< typename mpl::apply2::type > type; }; }; }; } // make droppable work template struct as_feature > { typedef tag::droppable::type> type; }; // make droppable work with non-void weights (should become // droppable template struct as_weighted_feature > { typedef tag::droppable::type> type; }; // for the purposes of feature-based dependency resolution, // droppable provides the same feature as Foo template struct feature_of > : feature_of { }; // Note: Usually, the extractor is pulled into the accumulators namespace with // a using directive, not the tag. But the droppable<> feature doesn't have an // extractor, so we can put the droppable tag in the accumulators namespace // without fear of a name conflict. using tag::droppable; }} // namespace boost::accumulators #endif include/boost/accumulators/framework/accumulators/external_accumulator.hpp000644 000000 000000 00000007005 11124251217 027736 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // external_accumulator.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_EXTERNAL_ACCUMULATOR_HPP_EAN_01_12_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_EXTERNAL_ACCUMULATOR_HPP_EAN_01_12_2005 #include #include #include #include // for feature_tag #include #include namespace boost { namespace accumulators { namespace impl { ////////////////////////////////////////////////////////////////////////// // external_impl /// INTERNAL ONLY /// template struct external_impl : accumulator_base { typedef typename Accumulator::result_type result_type; typedef typename detail::feature_tag::type feature_tag; external_impl(dont_care) {} template result_type result(Args const &args) const { return this->extract_(args, args[parameter::keyword::get() | 0]); } private: template static result_type extract_(Args const &args, int) { // No named parameter passed to the extractor. Maybe the external // feature is held by reference<>. extractor extract; return extract(reference_tag(args)); } template static result_type extract_(Args const &, AccumulatorSet const &acc) { // OK, a named parameter for this external feature was passed to the // extractor, so use that. extractor extract; return extract(acc); } }; } // namespace impl namespace tag { ////////////////////////////////////////////////////////////////////////// // external template struct external : depends_on > { typedef accumulators::impl::external_impl< detail::to_accumulator , Tag > impl; }; template struct external : depends_on<> { typedef accumulators::impl::external_impl< detail::to_accumulator , Tag > impl; }; } // for the purposes of feature-based dependency resolution, // external_accumulator provides the same feature as Feature template struct feature_of > : feature_of { }; // Note: Usually, the extractor is pulled into the accumulators namespace with // a using directive, not the tag. But the external<> feature doesn't have an // extractor, so we can put the external tag in the accumulators namespace // without fear of a name conflict. using tag::external; }} // namespace boost::accumulators #endif include/boost/accumulators/framework/accumulators/reference_accumulator.hpp000644 000000 000000 00000004746 11124251217 030063 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // reference_accumulator.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_REFERENCE_ACCUMULATOR_HPP_EAN_03_23_2006 #define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_REFERENCE_ACCUMULATOR_HPP_EAN_03_23_2006 #include #include #include #include // for feature_tag #include #include namespace boost { namespace accumulators { namespace impl { ////////////////////////////////////////////////////////////////////////// // reference_accumulator_impl // template struct reference_accumulator_impl : accumulator_base { typedef Referent &result_type; template reference_accumulator_impl(Args const &args) : ref(args[parameter::keyword::get()]) { } result_type result(dont_care) const { return this->ref; } private: reference_wrapper ref; }; } // namespace impl namespace tag { ////////////////////////////////////////////////////////////////////////// // reference_tag template struct reference_tag { }; ////////////////////////////////////////////////////////////////////////// // reference template struct reference : depends_on<> { /// INTERNAL ONLY /// typedef mpl::always > impl; }; } namespace extract { BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, reference, (typename)(typename)) BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, reference_tag, (typename)) } using extract::reference; using extract::reference_tag; // Map all reference features to reference_tag so // that references can be extracted using reference_tag // without specifying the referent type. template struct feature_of > : feature_of > { }; }} // namespace boost::accumulators #endif include/boost/accumulators/framework/accumulators/value_accumulator.hpp000644 000000 000000 00000004561 11124251217 027234 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // value_accumulator.hpp // // Copyright 2005 Eric Niebler, Daniel Egloff. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_VALUE_ACCUMULATOR_HPP_EAN_03_23_2006 #define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_VALUE_ACCUMULATOR_HPP_EAN_03_23_2006 #include #include #include // for feature_tag #include #include namespace boost { namespace accumulators { namespace impl { ////////////////////////////////////////////////////////////////////////// // value_accumulator_impl template struct value_accumulator_impl : accumulator_base { typedef ValueType result_type; template value_accumulator_impl(Args const &args) : val(args[parameter::keyword::get()]) { } result_type result(dont_care) const { return this->val; } private: ValueType val; }; } // namespace impl namespace tag { ////////////////////////////////////////////////////////////////////////// // value_tag template struct value_tag { }; ////////////////////////////////////////////////////////////////////////// // value template struct value : depends_on<> { /// INTERNAL ONLY /// typedef mpl::always > impl; }; } namespace extract { BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, value, (typename)(typename)) BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, value_tag, (typename)) } using extract::value; using extract::value_tag; // Map all value features to value_tag so // that values can be extracted using value_tag // without specifying the value type. template struct feature_of > : feature_of > { }; }} // namespace boost::accumulators #endif include/boost/accumulators/framework/depends_on.hpp000644 000000 000000 00000032626 11124251710 023136 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // depends_on.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_DEPENDS_ON_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_DEPENDS_ON_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////// // as_feature template struct as_feature { typedef Feature type; }; /////////////////////////////////////////////////////////////////////////// // weighted_feature template struct as_weighted_feature { typedef Feature type; }; /////////////////////////////////////////////////////////////////////////// // feature_of template struct feature_of { typedef Feature type; }; namespace detail { /////////////////////////////////////////////////////////////////////////// // feature_tag template struct feature_tag { typedef typename Accumulator::feature_tag type; }; template struct undroppable { typedef Feature type; }; template struct undroppable > { typedef Feature type; }; // For the purpose of determining whether one feature depends on another, // disregard whether the feature is droppable or not. template struct is_dependent_on : is_base_and_derived< typename undroppable::type , typename undroppable::type > {}; template struct depends_on_base : mpl::inherit_linearly< typename mpl::sort >::type // Don't inherit multiply from a feature , mpl::if_< is_dependent_on , mpl::_1 , mpl::inherit > >::type { }; } /////////////////////////////////////////////////////////////////////////// /// depends_on template struct depends_on : detail::depends_on_base< typename mpl::transform< mpl::vector , as_feature >::type > { typedef mpl::false_ is_weight_accumulator; typedef typename mpl::transform< mpl::vector , as_feature >::type dependencies; }; namespace detail { template struct matches_feature { template struct apply : is_same< typename feature_of::type>::type , typename feature_of::type>::type>::type > {}; }; template struct contains_feature_of { typedef mpl::transform_view > > features_list; typedef typename feature_of::type>::type the_feature; typedef typename mpl::contains::type type; }; // This is to work around a bug in early versions of Fusion which caused // a compile error if contains_feature_of is used as a // predicate to fusion::find_if template struct contains_feature_of_ { template struct apply : contains_feature_of {}; }; template< typename First , typename Last , bool is_empty = fusion::result_of::equal_to::value > struct build_acc_list; template struct build_acc_list { typedef fusion::nil type; template static fusion::nil call(Args const &, First const&, Last const&) { return fusion::nil(); } }; template struct build_acc_list { typedef build_acc_list::type, Last> next_build_acc_list; typedef fusion::cons< typename fusion::result_of::value_of::type , typename next_build_acc_list::type> type; template static type call(Args const &args, First const& f, Last const& l) { return type(args, next_build_acc_list::call(args, fusion::next(f), l)); } }; namespace meta { template struct make_acc_list : build_acc_list< typename fusion::result_of::begin::type , typename fusion::result_of::end::type > {}; } template typename meta::make_acc_list::type make_acc_list(Sequence const &seq, Args const &args) { return meta::make_acc_list::call(args, fusion::begin(seq), fusion::end(seq)); } /////////////////////////////////////////////////////////////////////////// // checked_as_weighted_feature template struct checked_as_weighted_feature { typedef typename as_feature::type feature_type; typedef typename as_weighted_feature::type type; // weighted and non-weighted flavors should provide the same feature. BOOST_MPL_ASSERT(( is_same< typename feature_of::type , typename feature_of::type > )); }; /////////////////////////////////////////////////////////////////////////// // as_feature_list template struct as_feature_list : mpl::transform_view > { }; template struct as_feature_list : mpl::transform_view > { }; /////////////////////////////////////////////////////////////////////////// // accumulator_wrapper template struct accumulator_wrapper : Accumulator { typedef Feature feature_tag; accumulator_wrapper(accumulator_wrapper const &that) : Accumulator(*static_cast(&that)) { } template accumulator_wrapper(Args const &args) : Accumulator(args) { } }; /////////////////////////////////////////////////////////////////////////// // to_accumulator template struct to_accumulator { typedef accumulator_wrapper< typename mpl::apply2::type , Feature > type; }; template struct to_accumulator > { BOOST_MPL_ASSERT((is_same)); BOOST_MPL_ASSERT((is_same)); typedef accumulator_wrapper< typename mpl::apply2::type , Feature > accumulator_type; typedef typename mpl::if_< typename Feature::is_weight_accumulator , accumulator_wrapper, Feature> , accumulator_type >::type type; }; // BUGBUG work around a MPL bug wrt map insertion template struct insert_feature : mpl::eval_if< mpl::has_key::type> , mpl::identity , mpl::insert::type, Feature> > > { }; template struct insert_dependencies : mpl::fold< as_feature_list , FeatureMap , insert_dependencies< insert_feature , mpl::_2 , Weight > > { }; template struct insert_sequence : mpl::fold< // BUGBUG should use insert_range, but doesn't seem to work for maps as_feature_list , FeatureMap , insert_feature > { }; template struct make_accumulator_tuple { typedef typename mpl::fold< as_feature_list , mpl::map0<> , mpl::if_< mpl::is_sequence , insert_sequence , insert_feature > >::type feature_map; // for each element in the map, add its dependencies also typedef typename mpl::fold< feature_map , feature_map , insert_dependencies, Weight> >::type feature_map_with_dependencies; // turn the map into a vector so we can sort it typedef typename mpl::insert_range< mpl::vector<> , mpl::end >::type , mpl::transform_view > >::type feature_vector_with_dependencies; // sort the features according to which is derived from which typedef typename mpl::sort< feature_vector_with_dependencies , is_dependent_on >::type sorted_feature_vector; // From the vector of features, construct a vector of accumulators typedef typename mpl::transform< sorted_feature_vector , to_accumulator >::type type; }; } // namespace detail }} // namespace boost::accumulators #endif include/boost/accumulators/framework/external.hpp000644 000000 000000 00000001416 11124251710 022633 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // external.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_EXTERNAL_HPP_EAN_01_12_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_EXTERNAL_HPP_EAN_01_12_2005 #include #include //namespace boost { namespace accumulators //{ // ///////////////////////////////////////////////////////////////////////////////// //// external //// //template //struct external //{ //}; // //}} // namespace boost::accumulators #endif include/boost/accumulators/framework/extractor.hpp000644 000000 000000 00000024567 11124251710 023040 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // extractor.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_EXTRACTOR_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_EXTRACTOR_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace detail { template struct accumulator_set_result { typedef typename as_feature::type feature_type; typedef typename mpl::apply::type::result_type type; }; template struct argument_pack_result : accumulator_set_result< typename remove_reference< typename parameter::binding::type >::type , Feature > { }; template struct extractor_result : mpl::eval_if< detail::is_accumulator_set , accumulator_set_result , argument_pack_result > { }; template typename extractor_result::type do_extract(AccumulatorSet const &acc, mpl::true_) { typedef typename as_feature::type feature_type; return extract_result(acc); } template typename extractor_result::type do_extract(Args const &args, mpl::false_) { typedef typename as_feature::type feature_type; return find_accumulator(args[accumulator]).result(args); } } // namespace detail /////////////////////////////////////////////////////////////////////////////// /// Extracts the result associated with Feature from the specified accumulator_set. template struct extractor { typedef extractor this_type; /// The result meta-function for determining the return type of the extractor template struct result; template struct result : detail::extractor_result { }; /// Extract the result associated with Feature from the accumulator set /// \param acc The accumulator set object from which to extract the result template typename detail::extractor_result::type operator ()(Arg1 const &arg1) const { // Arg1 could be an accumulator_set or an argument pack containing // an accumulator_set. Dispatch accordingly. return detail::do_extract(arg1, detail::is_accumulator_set()); } /// \overload /// /// \param a1 Optional named parameter to be passed to the accumulator's result() function. template typename detail::extractor_result::type operator ()(AccumulatorSet const &acc, A1 const &a1) const { BOOST_MPL_ASSERT((detail::is_accumulator_set)); typedef typename as_feature::type feature_type; return extract_result(acc, a1); } // ... other overloads generated by Boost.Preprocessor: /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_EXTRACTOR_FUN_OP(z, n, _) \ template \ struct result \ : detail::extractor_result \ {}; \ template< \ typename AccumulatorSet \ BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, typename A) \ > \ typename detail::extractor_result::type \ operator ()( \ AccumulatorSet const &acc \ BOOST_PP_ENUM_TRAILING_BINARY_PARAMS_Z(z, n, A, const &a) \ ) const \ { \ BOOST_MPL_ASSERT((detail::is_accumulator_set)); \ typedef typename as_feature::type feature_type; \ return extract_result(acc BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a));\ } BOOST_PP_REPEAT_FROM_TO( 2 , BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS) , BOOST_ACCUMULATORS_EXTRACTOR_FUN_OP , _ ) #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED /// \overload /// template typename detail::extractor_result::type operator ()(AccumulatorSet const &acc, A1 const &a1, A2 const &a2, ...); #endif }; /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_ARRAY_REM(Array) \ BOOST_PP_TUPLE_REM_CTOR(BOOST_PP_ARRAY_SIZE(Array), BOOST_PP_ARRAY_DATA(Array)) /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_SEQ_REM(Seq) \ BOOST_ACCUMULATORS_ARRAY_REM(BOOST_PP_SEQ_TO_ARRAY(Seq)) /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_ARGS_OP(s, data, elem) \ T ## s /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_PARAMS_OP(s, data, elem) \ elem T ## s /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_MAKE_FEATURE(Tag, Feature, ParamsSeq) \ Tag::Feature< \ BOOST_ACCUMULATORS_SEQ_REM( \ BOOST_PP_SEQ_TRANSFORM(BOOST_ACCUMULATORS_ARGS_OP, ~, ParamsSeq) \ ) \ > /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_DEFINE_EXTRACTOR_FUN_IMPL(z, n, Tag, Feature, ParamsSeq) \ template< \ BOOST_ACCUMULATORS_SEQ_REM( \ BOOST_PP_SEQ_TRANSFORM(BOOST_ACCUMULATORS_PARAMS_OP, ~, ParamsSeq) \ ) \ , typename Arg1 \ BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, typename A) \ > \ typename boost::accumulators::detail::extractor_result< \ Arg1 \ , BOOST_ACCUMULATORS_MAKE_FEATURE(Tag, Feature, ParamsSeq) \ >::type \ Feature(Arg1 const &arg1 BOOST_PP_ENUM_TRAILING_BINARY_PARAMS_Z(z, n, A, const &a) ) \ { \ typedef BOOST_ACCUMULATORS_MAKE_FEATURE(Tag, Feature, ParamsSeq) feature_type; \ return boost::accumulators::extractor()( \ arg1 BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a)); \ } /// INTERNAL ONLY /// #define BOOST_ACCUMULATORS_DEFINE_EXTRACTOR_FUN(z, n, _) \ BOOST_ACCUMULATORS_DEFINE_EXTRACTOR_FUN_IMPL( \ z \ , n \ , BOOST_PP_ARRAY_ELEM(0, _) \ , BOOST_PP_ARRAY_ELEM(1, _) \ , BOOST_PP_ARRAY_ELEM(2, _) \ ) #define BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(Tag, Feature, ParamSeq) \ BOOST_PP_REPEAT( \ BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS) \ , BOOST_ACCUMULATORS_DEFINE_EXTRACTOR_FUN \ , (3, (Tag, Feature, ParamSeq)) \ ) }} // namespace boost::accumulators #endif include/boost/accumulators/framework/features.hpp000644 000000 000000 00000001633 11124251710 022630 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // features.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_STATS_HPP_EAN_08_12_2005 #define BOOST_ACCUMULATORS_STATISTICS_STATS_HPP_EAN_08_12_2005 #include #include #include namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////////// // features // template struct features : mpl::vector { }; }} // namespace boost::accumulators #endif include/boost/accumulators/framework/parameters/accumulator.hpp000644 000000 000000 00000001155 11124251216 025474 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // accumulator.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_ACCUMULATOR_HPP_EAN_31_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_ACCUMULATOR_HPP_EAN_31_10_2005 #include namespace boost { namespace accumulators { BOOST_PARAMETER_KEYWORD(tag, accumulator) }} // namespace boost::accumulators #endif include/boost/accumulators/framework/parameters/sample.hpp000644 000000 000000 00000001131 11124251216 024430 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // sample.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_SAMPLE_HPP_EAN_31_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_SAMPLE_HPP_EAN_31_10_2005 #include namespace boost { namespace accumulators { BOOST_PARAMETER_KEYWORD(tag, sample) }} // namespace boost::accumulators #endif include/boost/accumulators/framework/parameters/weight.hpp000644 000000 000000 00000001172 11124251216 024443 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // weight.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_WEIGHT_HPP_EAN_31_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_WEIGHT_HPP_EAN_31_10_2005 #include namespace boost { namespace accumulators { // The weight of a single sample BOOST_PARAMETER_KEYWORD(tag, weight) }} // namespace boost::accumulators #endif include/boost/accumulators/framework/parameters/weights.hpp000644 000000 000000 00000001167 11124251217 024633 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // weights.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_WEIGHTS_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_WEIGHTS_HPP_EAN_28_10_2005 #include namespace boost { namespace accumulators { // The weight accumulator BOOST_PARAMETER_KEYWORD(tag, weights) }} // namespace boost::accumulators #endif include/boost/accumulators/numeric/detail/function1.hpp000644 000000 000000 00000005171 11124251216 023631 0ustar00rootroot000000 000000 // Copyright David Abrahams 2006. Distributed under the Boost // Software License, Version 1.0. (See accompanying // file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_DETAIL_FUNCTION1_DWA200655_HPP # define BOOST_DETAIL_FUNCTION1_DWA200655_HPP # include # include # include # include namespace boost { namespace detail { // A utility for creating unary function objects that play nicely with // boost::result_of and that handle the forwarding problem. // // mpl::apply::type is expected to be a stateless function // object that accepts an argument of type A0&. It is also expected // to have a nested ::result_type identical to its return type. template struct function1 { template struct result {}; template struct result { // How adding const to arguments handles rvalues. // // if A0 is arg0 is represents actual argument // -------- ------- -------------------------- // T const & T const const T lvalue // T & T non-const T lvalue // T const T const const T rvalue // T T const non-const T rvalue typedef typename remove_reference< typename add_const< A0 >::type >::type arg0; typedef typename mpl::apply1::type impl; typedef typename impl::result_type type; }; // Handles mutable lvalues template typename result::type operator ()(A0 &a0) const { typedef typename result::impl impl; typedef typename result::type type; typedef A0 &arg0; BOOST_CONCEPT_ASSERT((UnaryFunction)); //boost::function_requires >(); return impl()(a0); } // Handles const lvalues and all rvalues template typename result::type operator ()(A0 const &a0) const { typedef typename result::impl impl; typedef typename result::type type; typedef A0 const &arg0; BOOST_CONCEPT_ASSERT((UnaryFunction)); //boost::function_requires >(); return impl()(a0); } }; }} // namespace boost::detail #endif // BOOST_DETAIL_FUNCTION1_DWA200655_HPP include/boost/accumulators/numeric/detail/function2.hpp000644 000000 000000 00000000626 11124251216 023632 0ustar00rootroot000000 000000 // Copyright David Abrahams 2006. Distributed under the Boost // Software License, Version 1.0. (See accompanying // file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_DETAIL_FUNCTION2_DWA200655_HPP # define BOOST_DETAIL_FUNCTION2_DWA200655_HPP # define args (2) # include #endif // BOOST_DETAIL_FUNCTION2_DWA200655_HPP include/boost/accumulators/numeric/detail/function3.hpp000644 000000 000000 00000000631 11124251216 023627 0ustar00rootroot000000 000000 // Copyright David Abrahams 2006. Distributed under the Boost // Software License, Version 1.0. (See accompanying // file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_DETAIL_FUNCTION3_DWA2006514_HPP # define BOOST_DETAIL_FUNCTION3_DWA2006514_HPP # define args (3) # include #endif // BOOST_DETAIL_FUNCTION3_DWA2006514_HPP include/boost/accumulators/numeric/detail/function4.hpp000644 000000 000000 00000000631 11124251216 023630 0ustar00rootroot000000 000000 // Copyright David Abrahams 2006. Distributed under the Boost // Software License, Version 1.0. (See accompanying // file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_DETAIL_FUNCTION4_DWA2006514_HPP # define BOOST_DETAIL_FUNCTION4_DWA2006514_HPP # define args (4) # include #endif // BOOST_DETAIL_FUNCTION4_DWA2006514_HPP include/boost/accumulators/numeric/detail/function_n.hpp000644 000000 000000 00000015105 11124251216 024063 0ustar00rootroot000000 000000 // Copyright David Abrahams 2006. Distributed under the Boost // Software License, Version 1.0. (See accompanying // file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) // // #include guards intentionally disabled. // #ifndef BOOST_DETAIL_FUNCTION_N_DWA2006514_HPP // # define BOOST_DETAIL_FUNCTION_N_DWA2006514_HPP #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace detail { # define BOOST_DETAIL_default_arg(z, n, _) \ typedef mpl::void_ BOOST_PP_CAT(arg, n); # define BOOST_DETAIL_function_arg(z, n, _) \ typedef typename remove_reference< \ typename add_const< BOOST_PP_CAT(A, n) >::type \ >::type BOOST_PP_CAT(arg, n); #define BOOST_DETAIL_cat_arg_counts(s, state, n) \ BOOST_PP_IF( \ n \ , BOOST_PP_CAT(state, BOOST_PP_CAT(_, n)) \ , state \ ) \ /**/ #define function_name \ BOOST_PP_SEQ_FOLD_LEFT( \ BOOST_DETAIL_cat_arg_counts \ , BOOST_PP_CAT(function, BOOST_PP_SEQ_HEAD(args)) \ , BOOST_PP_SEQ_TAIL(args)(0) \ ) \ /**/ template struct function_name { BOOST_PP_REPEAT( BOOST_MPL_LIMIT_METAFUNCTION_ARITY , BOOST_DETAIL_default_arg , ~ ) template struct result {}; #define BOOST_DETAIL_function_result(r, _, n) \ template \ struct result \ { \ BOOST_PP_REPEAT(n, BOOST_DETAIL_function_arg, ~) \ typedef \ typename BOOST_PP_CAT(mpl::apply, BOOST_MPL_LIMIT_METAFUNCTION_ARITY)<\ F \ BOOST_PP_ENUM_TRAILING_PARAMS( \ BOOST_MPL_LIMIT_METAFUNCTION_ARITY \ , arg \ ) \ >::type \ impl; \ typedef typename impl::result_type type; \ }; \ /**/ BOOST_PP_SEQ_FOR_EACH(BOOST_DETAIL_function_result, _, args) # define arg_type(r, _, i, is_const) \ BOOST_PP_COMMA_IF(i) BOOST_PP_CAT(A, i) BOOST_PP_CAT(const_if, is_const) & # define result_(r, n, constness) \ typename result< \ function_name( \ BOOST_PP_SEQ_FOR_EACH_I_R(r, arg_type, ~, constness) \ ) \ > \ /**/ # define param(r, _, i, is_const) BOOST_PP_COMMA_IF(i) \ BOOST_PP_CAT(A, i) BOOST_PP_CAT(const_if, is_const) & BOOST_PP_CAT(x, i) # define param_list(r, n, constness) \ BOOST_PP_SEQ_FOR_EACH_I_R(r, param, ~, constness) # define call_operator(r, constness) \ template \ result_(r, BOOST_PP_SEQ_SIZE(constness), constness)::type \ operator ()( param_list(r, BOOST_PP_SEQ_SIZE(constness), constness) ) const \ { \ typedef result_(r, BOOST_PP_SEQ_SIZE(constness), constness)::impl impl; \ return impl()(BOOST_PP_ENUM_PARAMS(BOOST_PP_SEQ_SIZE(constness), x)); \ } \ /**/ # define const_if0 # define const_if1 const # define bits(z, n, _) ((0)(1)) # define gen_operator(r, _, n) \ BOOST_PP_SEQ_FOR_EACH_PRODUCT_R( \ r \ , call_operator \ , BOOST_PP_REPEAT(n, bits, ~) \ ) \ /**/ BOOST_PP_SEQ_FOR_EACH( gen_operator , ~ , args ) # undef bits # undef const_if1 # undef const_if0 # undef call_operator # undef param_list # undef param # undef result_ # undef default_ # undef arg_type # undef gen_operator # undef function_name # undef args }; }} // namespace boost::detail //#endif // BOOST_DETAIL_FUNCTION_N_DWA2006514_HPP include/boost/accumulators/numeric/detail/pod_singleton.hpp000644 000000 000000 00000001022 11124251216 024556 0ustar00rootroot000000 000000 // Copyright David Abrahams 2006. Distributed under the Boost // Software License, Version 1.0. (See accompanying // file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_DETAIL_POD_SINGLETON_DWA200655_HPP # define BOOST_DETAIL_POD_SINGLETON_DWA200655_HPP namespace boost { namespace detail { template struct pod_singleton { static T instance; }; template T pod_singleton::instance; }} // namespace boost::detail #endif // BOOST_DETAIL_POD_SINGLETON_DWA200655_HPP include/boost/accumulators/numeric/functional.hpp000644 000000 000000 00000051500 11124251710 022617 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// /// \file functional.hpp /// // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_NUMERIC_FUNCTIONAL_HPP_EAN_08_12_2005 #define BOOST_NUMERIC_FUNCTIONAL_HPP_EAN_08_12_2005 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #ifdef BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT # include #endif #ifdef BOOST_NUMERIC_FUNCTIONAL_STD_VALARRAY_SUPPORT # include #endif #ifdef BOOST_NUMERIC_FUNCTIONAL_STD_COMPLEX_SUPPORT # include #endif /// INTERNAL ONLY /// #define BOOST_NUMERIC_FUNCTIONAL_HPP_INCLUDED #ifdef BOOST_NUMERIC_FUNCTIONAL_DOXYGEN_INVOKED // Hack to make Doxygen show the inheritance relationships /// INTERNAL ONLY /// namespace std { /// INTERNAL ONLY /// template struct unary_function {}; /// INTERNAL ONLY /// template struct binary_function {}; } #endif namespace boost { namespace numeric { namespace functional { /// INTERNAL ONLY /// template struct are_integral : mpl::and_, is_integral > {}; template struct left_ref { typedef Left &type; }; namespace detail { template T &lvalue_of(); } } // TODO: handle complex weight, valarray, MTL vectors /// INTERNAL ONLY /// #define BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(Name, Op) \ namespace functional \ { \ template \ struct result_of_ ## Name \ { \ BOOST_TYPEOF_NESTED_TYPEDEF_TPL( \ nested \ , Op boost::numeric::functional::detail::lvalue_of() \ ) \ typedef typename nested::type type; \ }; \ template \ struct Name ## _base \ : std::unary_function< \ typename remove_const::type \ , typename result_of_ ## Name::type \ > \ { \ typename result_of_ ## Name::type operator ()(Arg &arg) const \ { \ return Op arg; \ } \ }; \ template \ struct Name \ : Name ## _base \ {}; \ } \ namespace op \ { \ struct Name \ : boost::detail::function1 > > \ {}; \ } \ namespace \ { \ op::Name const &Name = boost::detail::pod_singleton::instance; \ } \ /**/ /// INTERNAL ONLY /// #define BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(Name, Op, RetType) \ namespace functional \ { \ template \ struct result_of_ ## Name \ { \ RetType(Left, Op, Right) \ }; \ template \ struct Name ## _base \ : std::binary_function< \ typename remove_const::type \ , typename remove_const::type \ , typename result_of_ ## Name::type \ > \ { \ typename result_of_ ## Name::type \ operator ()(Left &left, Right &right) const \ { \ return left Op right; \ } \ }; \ template \ struct Name \ : Name ## _base \ {}; \ } \ namespace op \ { \ struct Name \ : boost::detail::function2< \ functional::Name<_1, _2, functional::tag<_1>, functional::tag<_2> > \ > \ {}; \ } \ namespace \ { \ op::Name const &Name = boost::detail::pod_singleton::instance; \ } \ /**/ /// INTERNAL ONLY /// #define BOOST_NUMERIC_FUNCTIONAL_DEDUCED(Left, Op, Right) \ BOOST_TYPEOF_NESTED_TYPEDEF_TPL( \ nested \ , boost::numeric::functional::detail::lvalue_of() Op \ boost::numeric::functional::detail::lvalue_of() \ ) \ typedef typename nested::type type; \ /**/ /// INTERNAL ONLY /// #define BOOST_NUMERIC_FUNCTIONAL_LEFT(Left, Op, Right) \ typedef Left &type; \ /**/ BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(plus, +, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(minus, -, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(multiplies, *, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(divides, /, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(modulus, %, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(greater, >, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(greater_equal, >=, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(less, <, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(less_equal, <=, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(equal_to, ==, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(not_equal_to, !=, BOOST_NUMERIC_FUNCTIONAL_DEDUCED) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(assign, =, BOOST_NUMERIC_FUNCTIONAL_LEFT) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(plus_assign, +=, BOOST_NUMERIC_FUNCTIONAL_LEFT) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(minus_assign, -=, BOOST_NUMERIC_FUNCTIONAL_LEFT) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(multiplies_assign, *=, BOOST_NUMERIC_FUNCTIONAL_LEFT) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(divides_assign, /=, BOOST_NUMERIC_FUNCTIONAL_LEFT) BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(modulus_assign, %=, BOOST_NUMERIC_FUNCTIONAL_LEFT) BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(unary_plus, +) BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(unary_minus, -) BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(complement, ~) BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(logical_not, !) #undef BOOST_NUMERIC_FUNCTIONAL_LEFT #undef BOOST_NUMERIC_FUNCTIONAL_DEDUCED #undef BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP #undef BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP namespace functional { template struct min_assign_base : std::binary_function { void operator ()(Left &left, Right &right) const { if(numeric::less(right, left)) { left = right; } } }; template struct max_assign_base : std::binary_function { void operator ()(Left &left, Right &right) const { if(numeric::greater(right, left)) { left = right; } } }; template struct average_base : functional::divides {}; // partial specialization that promotes the arguments to double for // integral division. template struct average_base >::type> : functional::divides {}; template struct promote_base : std::unary_function { To operator ()(From &from) const { return from; } }; template struct promote_base : std::unary_function { ToFrom &operator ()(ToFrom &tofrom) { return tofrom; } }; template struct as_min_base : std::unary_function::type> { typename remove_const::type operator ()(Arg &) const { return (std::numeric_limits::type>::min)(); } }; template struct as_min_base >::type> : std::unary_function::type> { typename remove_const::type operator ()(Arg &) const { return -(std::numeric_limits::type>::max)(); } }; template struct as_max_base : std::unary_function::type> { typename remove_const::type operator ()(Arg &) const { return (std::numeric_limits::type>::max)(); } }; template struct as_zero_base : std::unary_function::type> { typename remove_const::type operator ()(Arg &) const { return numeric::zero::type>::value; } }; template struct as_one_base : std::unary_function::type> { typename remove_const::type operator ()(Arg &) const { return numeric::one::type>::value; } }; template struct promote : promote_base {}; template struct min_assign : min_assign_base {}; template struct max_assign : max_assign_base {}; template struct average : average_base {}; template struct as_min : as_min_base {}; template struct as_max : as_max_base {}; template struct as_zero : as_zero_base {}; template struct as_one : as_one_base {}; } namespace op { template struct promote : boost::detail::function1::type, functional::tag<_> > > {}; struct min_assign : boost::detail::function2, functional::tag<_2> > > {}; struct max_assign : boost::detail::function2, functional::tag<_2> > > {}; struct average : boost::detail::function2, functional::tag<_2> > > {}; struct as_min : boost::detail::function1 > > {}; struct as_max : boost::detail::function1 > > {}; struct as_zero : boost::detail::function1 > > {}; struct as_one : boost::detail::function1 > > {}; } namespace { op::min_assign const &min_assign = boost::detail::pod_singleton::instance; op::max_assign const &max_assign = boost::detail::pod_singleton::instance; op::average const &average = boost::detail::pod_singleton::instance; op::as_min const &as_min = boost::detail::pod_singleton::instance; op::as_max const &as_max = boost::detail::pod_singleton::instance; op::as_zero const &as_zero = boost::detail::pod_singleton::instance; op::as_one const &as_one = boost::detail::pod_singleton::instance; } /////////////////////////////////////////////////////////////////////////////// // promote template typename lazy_disable_if, mpl::if_, To &, To> >::type promote(From &from) { return functional::promote()(from); } template typename mpl::if_, To const &, To const>::type promote(From const &from) { return functional::promote()(from); } template struct default_ { typedef default_ type; typedef T value_type; static T const value; operator T const & () const { return default_::value; } }; template T const default_::value = T(); template struct one { typedef one type; typedef T value_type; static T const value; operator T const & () const { return one::value; } }; template T const one::value = T(1); template struct zero { typedef zero type; typedef T value_type; static T const value; operator T const & () const { return zero::value; } }; template T const zero::value = T(); template struct one_or_default : mpl::if_, default_, one >::type {}; template struct zero_or_default : mpl::if_, default_, zero >::type {}; }} // namespace boost::numeric #endif include/boost/accumulators/numeric/functional/complex.hpp000644 000000 000000 00000004414 11124251216 024271 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// /// \file complex.hpp /// // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_NUMERIC_FUNCTIONAL_COMPLEX_HPP_EAN_01_17_2006 #define BOOST_NUMERIC_FUNCTIONAL_COMPLEX_HPP_EAN_01_17_2006 #ifdef BOOST_NUMERIC_FUNCTIONAL_HPP_INCLUDED # error Include this file before boost/accumulators/numeric/functional.hpp #endif #include #include #include #include #include #include namespace boost { namespace numeric { namespace operators { // So that the stats compile when Sample type is std::complex template typename disable_if< mpl::or_, is_same, U> > , std::complex >::type operator *(std::complex ri, U const &u) { // BUGBUG promote result to typeof(T()*u) ? return ri *= static_cast(u); } template typename disable_if< mpl::or_, is_same, U> > , std::complex >::type operator /(std::complex ri, U const &u) { // BUGBUG promote result to typeof(T()*u) ? return ri /= static_cast(u); } }}} // namespace boost::numeric::operators namespace boost { namespace numeric { namespace detail { template struct one_complex { static std::complex const value; }; template std::complex const one_complex::value = std::complex(numeric::one::value, numeric::one::value); } /// INTERNAL ONLY /// template struct one > : detail::one_complex { typedef one type; typedef std::complex value_type; operator value_type const & () const { return detail::one_complex::value; } }; }} // namespace boost::numeric #endif include/boost/accumulators/numeric/functional/valarray.hpp000644 000000 000000 00000040363 11124251216 024446 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// /// \file valarray.hpp /// // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_NUMERIC_FUNCTIONAL_VALARRAY_HPP_EAN_12_12_2005 #define BOOST_NUMERIC_FUNCTIONAL_VALARRAY_HPP_EAN_12_12_2005 #ifdef BOOST_NUMERIC_FUNCTIONAL_HPP_INCLUDED # error Include this file before boost/accumulators/numeric/functional.hpp #endif #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace numeric { namespace operators { /////////////////////////////////////////////////////////////////////////////// // Handle valarray / Right where Right is a scalar and Right != Left. template typename enable_if< mpl::and_, mpl::not_ > > , std::valarray::result_type> >::type operator /(std::valarray const &left, Right const &right) { typedef typename functional::divides::result_type value_type; std::valarray result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::divides(left[i], right); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle valarray * Right where Right is a scalar and Right != Left. template typename enable_if< mpl::and_, mpl::not_ > > , std::valarray::result_type> >::type operator *(std::valarray const &left, Right const &right) { typedef typename functional::multiplies::result_type value_type; std::valarray result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::multiplies(left[i], right); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle valarray + valarray where Right != Left. template typename disable_if< is_same , std::valarray::result_type> >::type operator +(std::valarray const &left, std::valarray const &right) { typedef typename functional::plus::result_type value_type; std::valarray result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::plus(left[i], right[i]); } return result; } } namespace functional { struct std_valarray_tag; template struct tag > { typedef std_valarray_tag type; }; #ifdef __GLIBCXX__ template struct tag > { typedef std_valarray_tag type; }; #endif /// INTERNAL ONLY /// // This is necessary because the GCC stdlib uses expression templates, and // typeof(som-valarray-expression) is not an instance of std::valarray #define BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(Name, Op) \ template \ struct Name \ : std::binary_function< \ Left \ , Right \ , std::valarray< \ typename Name< \ typename Left::value_type \ , typename Right::value_type \ >::result_type \ > \ > \ { \ typedef typename Left::value_type left_value_type; \ typedef typename Right::value_type right_value_type; \ typedef \ std::valarray< \ typename Name::result_type \ > \ result_type; \ result_type \ operator ()(Left &left, Right &right) const \ { \ return numeric::promote >(left) \ Op numeric::promote >(right); \ } \ }; \ template \ struct Name \ : std::binary_function< \ Left \ , Right \ , std::valarray< \ typename Name::result_type \ > \ > \ { \ typedef typename Left::value_type left_value_type; \ typedef \ std::valarray< \ typename Name::result_type \ > \ result_type; \ result_type \ operator ()(Left &left, Right &right) const \ { \ return numeric::promote >(left) Op right;\ } \ }; \ template \ struct Name \ : std::binary_function< \ Left \ , Right \ , std::valarray< \ typename Name::result_type \ > \ > \ { \ typedef typename Right::value_type right_value_type; \ typedef \ std::valarray< \ typename Name::result_type \ > \ result_type; \ result_type \ operator ()(Left &left, Right &right) const \ { \ return left Op numeric::promote >(right);\ } \ }; BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(plus, +) BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(minus, -) BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(multiplies, *) BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(divides, /) BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(modulus, %) #undef BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP /////////////////////////////////////////////////////////////////////////////// // element-wise min of std::valarray template struct min_assign : std::binary_function { void operator ()(Left &left, Right &right) const { BOOST_ASSERT(left.size() == right.size()); for(std::size_t i = 0, size = left.size(); i != size; ++i) { if(numeric::less(right[i], left[i])) { left[i] = right[i]; } } } }; /////////////////////////////////////////////////////////////////////////////// // element-wise max of std::valarray template struct max_assign : std::binary_function { void operator ()(Left &left, Right &right) const { BOOST_ASSERT(left.size() == right.size()); for(std::size_t i = 0, size = left.size(); i != size; ++i) { if(numeric::greater(right[i], left[i])) { left[i] = right[i]; } } } }; // partial specialization of numeric::average<> for std::valarray. template struct average : mpl::if_< are_integral , divides , divides >::type {}; // promote template struct promote : std::unary_function { To operator ()(From &arr) const { typename remove_const::type res(arr.size()); for(std::size_t i = 0, size = arr.size(); i != size; ++i) { res[i] = numeric::promote(arr[i]); } return res; } }; template struct promote : std::unary_function { ToFrom &operator ()(ToFrom &tofrom) const { return tofrom; } }; // for "promoting" a std::valarray to a bool, useful for // comparing 2 valarrays for equality: // if(numeric::promote(a == b)) template struct promote : std::unary_function { bool operator ()(From &arr) const { BOOST_MPL_ASSERT((is_same)); for(std::size_t i = 0, size = arr.size(); i != size; ++i) { if(!arr[i]) { return false; } } return true; } }; template struct promote : promote {}; /////////////////////////////////////////////////////////////////////////////// // functional::as_min template struct as_min : std::unary_function::type> { typename remove_const::type operator ()(T &arr) const { return 0 == arr.size() ? T() : T(numeric::as_min(arr[0]), arr.size()); } }; /////////////////////////////////////////////////////////////////////////////// // functional::as_max template struct as_max : std::unary_function::type> { typename remove_const::type operator ()(T &arr) const { return 0 == arr.size() ? T() : T(numeric::as_max(arr[0]), arr.size()); } }; /////////////////////////////////////////////////////////////////////////////// // functional::as_zero template struct as_zero : std::unary_function::type> { typename remove_const::type operator ()(T &arr) const { return 0 == arr.size() ? T() : T(numeric::as_zero(arr[0]), arr.size()); } }; /////////////////////////////////////////////////////////////////////////////// // functional::as_one template struct as_one : std::unary_function::type> { typename remove_const::type operator ()(T &arr) const { return 0 == arr.size() ? T() : T(numeric::as_one(arr[0]), arr.size()); } }; } // namespace functional }} // namespace boost::numeric #endif include/boost/accumulators/numeric/functional/vector.hpp000644 000000 000000 00000027673 11124251216 024140 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// /// \file vector.hpp /// // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_NUMERIC_FUNCTIONAL_VECTOR_HPP_EAN_12_12_2005 #define BOOST_NUMERIC_FUNCTIONAL_VECTOR_HPP_EAN_12_12_2005 #ifdef BOOST_NUMERIC_FUNCTIONAL_HPP_INCLUDED # error Include this file before boost/accumulators/numeric/functional.hpp #endif #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace numeric { namespace operators { /////////////////////////////////////////////////////////////////////////////// // Handle vector / Right where Right is a scalar. template typename enable_if< is_scalar , std::vector::result_type> >::type operator /(std::vector const &left, Right const &right) { typedef typename functional::divides::result_type value_type; std::vector result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::divides(left[i], right); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle vector / vector. template std::vector::result_type> operator /(std::vector const &left, std::vector const &right) { typedef typename functional::divides::result_type value_type; std::vector result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::divides(left[i], right[i]); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle vector * Right where Right is a scalar. template typename enable_if< is_scalar , std::vector::result_type> >::type operator *(std::vector const &left, Right const &right) { typedef typename functional::multiplies::result_type value_type; std::vector result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::multiplies(left[i], right); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle Left * vector where Left is a scalar. template typename enable_if< is_scalar , std::vector::result_type> >::type operator *(Left const &left, std::vector const &right) { typedef typename functional::multiplies::result_type value_type; std::vector result(right.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::multiplies(left, right[i]); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle vector * vector template std::vector::result_type> operator *(std::vector const &left, std::vector const &right) { typedef typename functional::multiplies::result_type value_type; std::vector result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::multiplies(left[i], right[i]); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle vector + vector template std::vector::result_type> operator +(std::vector const &left, std::vector const &right) { typedef typename functional::plus::result_type value_type; std::vector result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::plus(left[i], right[i]); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle vector - vector template std::vector::result_type> operator -(std::vector const &left, std::vector const &right) { typedef typename functional::minus::result_type value_type; std::vector result(left.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::minus(left[i], right[i]); } return result; } /////////////////////////////////////////////////////////////////////////////// // Handle vector += vector template std::vector & operator +=(std::vector &left, std::vector const &right) { BOOST_ASSERT(left.size() == right.size()); for(std::size_t i = 0, size = left.size(); i != size; ++i) { numeric::plus_assign(left[i], right[i]); } return left; } /////////////////////////////////////////////////////////////////////////////// // Handle -vector template std::vector::result_type> operator -(std::vector const &arg) { typedef typename functional::unary_minus::result_type value_type; std::vector result(arg.size()); for(std::size_t i = 0, size = result.size(); i != size; ++i) { result[i] = numeric::unary_minus(arg[i]); } return result; } } namespace functional { struct std_vector_tag; template struct tag > { typedef std_vector_tag type; }; /////////////////////////////////////////////////////////////////////////////// // element-wise min of std::vector template struct min_assign : std::binary_function { void operator ()(Left &left, Right &right) const { BOOST_ASSERT(left.size() == right.size()); for(std::size_t i = 0, size = left.size(); i != size; ++i) { if(numeric::less(right[i], left[i])) { left[i] = right[i]; } } } }; /////////////////////////////////////////////////////////////////////////////// // element-wise max of std::vector template struct max_assign : std::binary_function { void operator ()(Left &left, Right &right) const { BOOST_ASSERT(left.size() == right.size()); for(std::size_t i = 0, size = left.size(); i != size; ++i) { if(numeric::greater(right[i], left[i])) { left[i] = right[i]; } } } }; // partial specialization for std::vector. template struct average : mpl::if_< are_integral , divides , divides >::type {}; // promote template struct promote : std::unary_function { To operator ()(From &arr) const { typename remove_const::type res(arr.size()); for(std::size_t i = 0, size = arr.size(); i != size; ++i) { res[i] = numeric::promote(arr[i]); } return res; } }; template struct promote : std::unary_function { ToFrom &operator ()(ToFrom &tofrom) const { return tofrom; } }; /////////////////////////////////////////////////////////////////////////////// // functional::as_min template struct as_min : std::unary_function::type> { typename remove_const::type operator ()(T &arr) const { return 0 == arr.size() ? T() : T(arr.size(), numeric::as_min(arr[0])); } }; /////////////////////////////////////////////////////////////////////////////// // functional::as_max template struct as_max : std::unary_function::type> { typename remove_const::type operator ()(T &arr) const { return 0 == arr.size() ? T() : T(arr.size(), numeric::as_max(arr[0])); } }; /////////////////////////////////////////////////////////////////////////////// // functional::as_zero template struct as_zero : std::unary_function::type> { typename remove_const::type operator ()(T &arr) const { return 0 == arr.size() ? T() : T(arr.size(), numeric::as_zero(arr[0])); } }; /////////////////////////////////////////////////////////////////////////////// // functional::as_one template struct as_one : std::unary_function::type> { typename remove_const::type operator ()(T &arr) const { return 0 == arr.size() ? T() : T(arr.size(), numeric::as_one(arr[0])); } }; } // namespace functional }} // namespace boost::numeric #endif include/boost/accumulators/numeric/functional_fwd.hpp000644 000000 000000 00000022401 11124251710 023455 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// /// \file functional_fwd.hpp /// // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_NUMERIC_FUNCTIONAL_FWD_HPP_EAN_08_12_2005 #define BOOST_NUMERIC_FUNCTIONAL_FWD_HPP_EAN_08_12_2005 #include #include #include #include #include namespace boost { namespace numeric { // For using directives -- this namespace may be re-opened elsewhere namespace operators {} namespace op { using mpl::_; using mpl::_1; using mpl::_2; } namespace functional { using namespace operators; template struct tag { typedef void type; }; template struct tag : tag {}; template struct tag : tag {}; template struct tag : tag {}; template struct static_; template struct are_integral; } /// INTERNAL ONLY /// #define BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(Name, Op) \ namespace functional \ { \ template \ struct Name ## _base; \ template::type> \ struct Name; \ } \ namespace op \ { \ struct Name; \ } \ namespace \ { \ extern op::Name const &Name; \ } /// INTERNAL ONLY /// #define BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(Name) \ namespace functional \ { \ template \ struct result_of_ ## Name; \ template \ struct Name ## _base; \ template< \ typename Left \ , typename Right \ , typename LeftTag = typename tag::type \ , typename RightTag = typename tag::type \ > \ struct Name; \ } \ namespace op \ { \ struct Name; \ } \ namespace \ { \ extern op::Name const &Name; \ } BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(plus) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(minus) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(multiplies) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(divides) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(modulus) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(greater) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(greater_equal) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(less) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(less_equal) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(equal_to) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(not_equal_to) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(assign) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(plus_assign) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(minus_assign) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(multiplies_assign) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(divides_assign) BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(modulus_assign) BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(unary_plus, +) BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(unary_minus, -) BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(complement, ~) BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(logical_not, !) #undef BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP #undef BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP namespace functional { template struct promote_base; template struct min_assign_base; template struct max_assign_base; template struct average_base; template struct as_min_base; template struct as_max_base; template struct as_zero_base; template struct as_one_base; template::type, typename FromTag = typename tag::type> struct promote; template::type, typename RightTag = typename tag::type> struct min_assign; template::type, typename RightTag = typename tag::type> struct max_assign; template::type, typename RightTag = typename tag::type> struct average; template::type> struct as_min; template::type> struct as_max; template::type> struct as_zero; template::type> struct as_one; } namespace op { template struct promote; struct min_assign; struct max_assign; struct average; struct as_min; struct as_max; struct as_zero; struct as_one; } namespace { extern op::min_assign const &min_assign; extern op::max_assign const &max_assign; extern op::average const &average; extern op::as_min const &as_min; extern op::as_max const &as_max; extern op::as_zero const &as_zero; extern op::as_one const &as_one; } template typename lazy_disable_if, mpl::if_, To &, To> >::type promote(From &from); template typename mpl::if_, To const &, To const>::type promote(From const &from); template struct default_; template struct one; template struct zero; template struct one_or_default; template struct zero_or_default; }} // namespace boost::numeric #endif include/boost/accumulators/statistics.hpp000644 000000 000000 00000006310 11124251427 021211 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// /// \file statistics.hpp /// Includes all of the Statistical Accumulators Library // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_HPP_EAN_01_17_2006 #define BOOST_ACCUMULATORS_STATISTICS_HPP_EAN_01_17_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #endif include/boost/accumulators/statistics/count.hpp000644 000000 000000 00000003357 11124251707 022352 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // count.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_COUNT_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_COUNT_HPP_EAN_28_10_2005 #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // count_impl struct count_impl : accumulator_base { // for boost::result_of typedef std::size_t result_type; count_impl(dont_care) : cnt(0) { } void operator ()(dont_care) { ++this->cnt; } result_type result(dont_care) const { return this->cnt; } private: std::size_t cnt; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::count // namespace tag { struct count : depends_on<> { /// INTERNAL ONLY /// typedef mpl::always impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::count // namespace extract { extractor const count = {}; } using extract::count; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/covariance.hpp000644 000000 000000 00000015744 11124251706 023336 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // covariance.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_COVARIANCE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_COVARIANCE_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace numeric { namespace functional { struct std_vector_tag; /////////////////////////////////////////////////////////////////////////////// // functional::outer_product template struct outer_product_base : functional::multiplies {}; template::type, typename RightTag = typename tag::type> struct outer_product : outer_product_base {}; template struct outer_product : std::binary_function< Left , Right , ublas::matrix< typename functional::multiplies< typename Left::value_type , typename Right::value_type >::result_type > > { typedef ublas::matrix< typename functional::multiplies< typename Left::value_type , typename Right::value_type >::result_type > result_type; result_type operator ()(Left & left, Right & right) const { std::size_t left_size = left.size(); std::size_t right_size = right.size(); result_type result(left_size, right_size); for (std::size_t i = 0; i < left_size; ++i) for (std::size_t j = 0; j < right_size; ++j) result(i,j) = numeric::multiplies(left[i], right[j]); return result; } }; } namespace op { struct outer_product : boost::detail::function2, functional::tag<_2> > > {}; } namespace { op::outer_product const &outer_product = boost::detail::pod_singleton::instance; } }} namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // covariance_impl // /** @brief Covariance Estimator An iterative Monte Carlo estimator for the covariance \f$\mathrm{Cov}(X,X')\f$, where \f$X\f$ is a sample and \f$X'\f$ is a variate, is given by: \f[ \hat{c}_n = \frac{n-1}{n} \hat{c}_{n-1} + \frac{1}{n-1}(X_n - \hat{\mu}_n)(X_n' - \hat{\mu}_n'),\quad n\ge2,\quad\hat{c}_1 = 0, \f] \f$\hat{\mu}_n\f$ and \f$\hat{\mu}_n'\f$ being the means of the samples and variates. */ template struct covariance_impl : accumulator_base { typedef typename numeric::functional::average::result_type sample_type; typedef typename numeric::functional::average::result_type variate_type; // for boost::result_of typedef typename numeric::functional::outer_product::result_type result_type; template covariance_impl(Args const &args) : cov_( numeric::outer_product( numeric::average(args[sample | Sample()], (std::size_t)1) , numeric::average(args[parameter::keyword::get() | VariateType()], (std::size_t)1) ) ) { } template void operator ()(Args const &args) { std::size_t cnt = count(args); if (cnt > 1) { extractor > const some_mean_of_variates = {}; this->cov_ = this->cov_*(cnt-1.)/cnt + numeric::outer_product( some_mean_of_variates(args) - args[parameter::keyword::get()] , mean(args) - args[sample] ) / (cnt-1.); } } result_type result(dont_care) const { return this->cov_; } private: result_type cov_; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::covariance // namespace tag { template struct covariance : depends_on > { typedef accumulators::impl::covariance_impl impl; }; struct abstract_covariance : depends_on<> { }; } /////////////////////////////////////////////////////////////////////////////// // extract::covariance // namespace extract { extractor const covariance = {}; } using extract::covariance; template struct feature_of > : feature_of { }; // So that covariance can be automatically substituted with // weighted_covariance when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_covariance type; }; template struct feature_of > : feature_of > {}; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/density.hpp000644 000000 000000 00000021766 11124251704 022702 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // density.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_DENSITY_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_DENSITY_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////////// // cache_size and num_bins named parameters // BOOST_PARAMETER_NESTED_KEYWORD(tag, density_cache_size, cache_size) BOOST_PARAMETER_NESTED_KEYWORD(tag, density_num_bins, num_bins) namespace impl { /////////////////////////////////////////////////////////////////////////////// // density_impl // density histogram /** @brief Histogram density estimator The histogram density estimator returns a histogram of the sample distribution. The positions and sizes of the bins are determined using a specifiable number of cached samples (cache_size). The range between the minimum and the maximum of the cached samples is subdivided into a specifiable number of bins (num_bins) of same size. Additionally, an under- and an overflow bin is added to capture future under- and overflow samples. Once the bins are determined, the cached samples and all subsequent samples are added to the correct bins. At the end, a range of std::pair is return, where each pair contains the position of the bin (lower bound) and the samples count (normalized with the total number of samples). @param density_cache_size Number of first samples used to determine min and max. @param density_num_bins Number of bins (two additional bins collect under- and overflow samples). */ template struct density_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef std::vector > histogram_type; typedef std::vector array_type; // for boost::result_of typedef iterator_range result_type; template density_impl(Args const &args) : cache_size(args[density_cache_size]) , cache(cache_size) , num_bins(args[density_num_bins]) , samples_in_bin(num_bins + 2, 0.) , bin_positions(num_bins + 2) , histogram( num_bins + 2 , std::make_pair( numeric::average(args[sample | Sample()],(std::size_t)1) , numeric::average(args[sample | Sample()],(std::size_t)1) ) ) , is_dirty(true) { } template void operator ()(Args const &args) { this->is_dirty = true; std::size_t cnt = count(args); // Fill up cache with cache_size first samples if (cnt <= this->cache_size) { this->cache[cnt - 1] = args[sample]; } // Once cache_size samples have been accumulated, create num_bins bins of same size between // the minimum and maximum of the cached samples as well as an under- and and an overflow bin. // Store their lower bounds (bin_positions) and fill the bins with the cached samples (samples_in_bin). if (cnt == this->cache_size) { float_type minimum = numeric::average((min)(args), (std::size_t)1); float_type maximum = numeric::average((max)(args), (std::size_t)1); float_type bin_size = numeric::average(maximum - minimum, this->num_bins ); // determine bin positions (their lower bounds) for (std::size_t i = 0; i < this->num_bins + 2; ++i) { this->bin_positions[i] = minimum + (i - 1.) * bin_size; } for (typename array_type::const_iterator iter = this->cache.begin(); iter != this->cache.end(); ++iter) { if (*iter < this->bin_positions[1]) { ++(this->samples_in_bin[0]); } else if (*iter >= this->bin_positions[this->num_bins + 1]) { ++(this->samples_in_bin[this->num_bins + 1]); } else { typename array_type::iterator it = std::upper_bound( this->bin_positions.begin() , this->bin_positions.end() , *iter ); std::size_t d = std::distance(this->bin_positions.begin(), it); ++(this->samples_in_bin[d - 1]); } } } // Add each subsequent sample to the correct bin else if (cnt > this->cache_size) { if (args[sample] < this->bin_positions[1]) { ++(this->samples_in_bin[0]); } else if (args[sample] >= this->bin_positions[this->num_bins + 1]) { ++(this->samples_in_bin[this->num_bins + 1]); } else { typename array_type::iterator it = std::upper_bound( this->bin_positions.begin() , this->bin_positions.end() , args[sample] ); std::size_t d = std::distance(this->bin_positions.begin(), it); ++(this->samples_in_bin[d - 1]); } } } template result_type result(Args const &args) const { if (this->is_dirty) { this->is_dirty = false; // creates a vector of std::pair where each pair i holds // the values bin_positions[i] (x-axis of histogram) and // samples_in_bin[i] / cnt (y-axis of histogram). for (std::size_t i = 0; i < this->num_bins + 2; ++i) { this->histogram[i] = std::make_pair(this->bin_positions[i], numeric::average(this->samples_in_bin[i], count(args))); } } // returns a range of pairs return make_iterator_range(this->histogram); } private: std::size_t cache_size; // number of cached samples array_type cache; // cache to store the first cache_size samples std::size_t num_bins; // number of bins array_type samples_in_bin; // number of samples in each bin array_type bin_positions; // lower bounds of bins mutable histogram_type histogram; // histogram mutable bool is_dirty; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::density // namespace tag { struct density : depends_on , density_cache_size , density_num_bins { /// INTERNAL ONLY /// typedef accumulators::impl::density_impl impl; #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED /// tag::density::cache_size named parameter /// tag::density::num_bins named parameter static boost::parameter::keyword const cache_size; static boost::parameter::keyword const num_bins; #endif }; } /////////////////////////////////////////////////////////////////////////////// // extract::density // namespace extract { extractor const density = {}; } using extract::density; // So that density can be automatically substituted // with weighted_density when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::weighted_density type; }; template<> struct feature_of : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/error_of.hpp000644 000000 000000 00000005034 11124251705 023027 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // error_of.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_ERROR_OF_HPP_EAN_29_11_2005 #define BOOST_ACCUMULATORS_STATISTICS_ERROR_OF_HPP_EAN_29_11_2005 #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /// INTERNAL ONLY /// template struct this_feature_has_no_error_calculation : mpl::false_ { }; /////////////////////////////////////////////////////////////////////////////// // error_of_impl /// INTERNAL ONLY /// template struct error_of_impl : accumulator_base { // TODO: specialize this on the specific features that have errors we're // interested in. BOOST_MPL_ASSERT((this_feature_has_no_error_calculation)); // for boost::result_of typedef int result_type; error_of_impl(dont_care) { } result_type result(dont_care) const { return 0; } }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::error_of // namespace tag { template struct error_of : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::error_of_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::error_of // namespace extract { BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, error_of, (typename)) } using extract::error_of; // make tag::error_of work template struct as_feature > { typedef tag::error_of::type> type; }; // make error_of work with non-void weights (should become // error_of template struct as_weighted_feature > { typedef tag::error_of::type> type; }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/error_of_mean.hpp000644 000000 000000 00000004227 11124251704 024031 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // error_of.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_ERROR_OF_MEAN_HPP_EAN_27_03_2006 #define BOOST_ACCUMULATORS_STATISTICS_ERROR_OF_MEAN_HPP_EAN_27_03_2006 #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // error_of_mean_impl template struct error_of_mean_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::average::result_type result_type; error_of_mean_impl(dont_care) {} template result_type result(Args const &args) const { using namespace std; extractor const variance = {}; return sqrt(numeric::average(variance(args), count(args) - 1)); } }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::error_of // namespace tag { template<> struct error_of : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::error_of_mean_impl impl; }; template<> struct error_of : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::error_of_mean_impl impl; }; } }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/extended_p_square.hpp000644 000000 000000 00000025432 11124251707 024717 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // extended_p_square.hpp // // Copyright 2005 Daniel Egloff. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_EXTENDED_SINGLE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_EXTENDED_SINGLE_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////////// // probabilities named parameter // BOOST_PARAMETER_NESTED_KEYWORD(tag, extended_p_square_probabilities, probabilities) namespace impl { /////////////////////////////////////////////////////////////////////////////// // extended_p_square_impl // multiple quantile estimation /** @brief Multiple quantile estimation with the extended \f$P^2\f$ algorithm Extended \f$P^2\f$ algorithm for estimation of several quantiles without storing samples. Assume that \f$m\f$ quantiles \f$\xi_{p_1}, \ldots, \xi_{p_m}\f$ are to be estimated. Instead of storing the whole sample cumulative distribution, the algorithm maintains only \f$m+2\f$ principal markers and \f$m+1\f$ middle markers, whose positions are updated with each sample and whose heights are adjusted (if necessary) using a piecewise-parablic formula. The heights of these central markers are the current estimates of the quantiles and returned as an iterator range. For further details, see K. E. E. Raatikainen, Simultaneous estimation of several quantiles, Simulation, Volume 49, Number 4 (October), 1986, p. 159-164. The extended \f$ P^2 \f$ algorithm generalizess the \f$ P^2 \f$ algorithm of R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and histograms without storing observations, Communications of the ACM, Volume 28 (October), Number 10, 1985, p. 1076-1085. @param extended_p_square_probabilities A vector of quantile probabilities. */ template struct extended_p_square_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef std::vector array_type; // for boost::result_of typedef iterator_range< detail::lvalue_index_iterator< permutation_iterator< typename array_type::const_iterator , detail::times2_iterator > > > result_type; template extended_p_square_impl(Args const &args) : probabilities( boost::begin(args[extended_p_square_probabilities]) , boost::end(args[extended_p_square_probabilities]) ) , heights(2 * probabilities.size() + 3) , actual_positions(heights.size()) , desired_positions(heights.size()) , positions_increments(heights.size()) { std::size_t num_quantiles = this->probabilities.size(); std::size_t num_markers = this->heights.size(); for(std::size_t i = 0; i < num_markers; ++i) { this->actual_positions[i] = i + 1; } this->positions_increments[0] = 0.; this->positions_increments[num_markers - 1] = 1.; for(std::size_t i = 0; i < num_quantiles; ++i) { this->positions_increments[2 * i + 2] = probabilities[i]; } for(std::size_t i = 0; i <= num_quantiles; ++i) { this->positions_increments[2 * i + 1] = 0.5 * (this->positions_increments[2 * i] + this->positions_increments[2 * i + 2]); } for(std::size_t i = 0; i < num_markers; ++i) { this->desired_positions[i] = 1. + 2. * (num_quantiles + 1.) * this->positions_increments[i]; } } template void operator ()(Args const &args) { std::size_t cnt = count(args); // m+2 principal markers and m+1 middle markers std::size_t num_markers = 2 * this->probabilities.size() + 3; // first accumulate num_markers samples if(cnt <= num_markers) { this->heights[cnt - 1] = args[sample]; // complete the initialization of heights by sorting if(cnt == num_markers) { std::sort(this->heights.begin(), this->heights.end()); } } else { std::size_t sample_cell = 1; // find cell k = sample_cell such that heights[k-1] <= sample < heights[k] if(args[sample] < this->heights[0]) { this->heights[0] = args[sample]; sample_cell = 1; } else if(args[sample] >= this->heights[num_markers - 1]) { this->heights[num_markers - 1] = args[sample]; sample_cell = num_markers - 1; } else { typedef typename array_type::iterator iterator; iterator it = std::upper_bound( this->heights.begin() , this->heights.end() , args[sample] ); sample_cell = std::distance(this->heights.begin(), it); } // update actual positions of all markers above sample_cell index for(std::size_t i = sample_cell; i < num_markers; ++i) { ++this->actual_positions[i]; } // update desired positions of all markers for(std::size_t i = 0; i < num_markers; ++i) { this->desired_positions[i] += this->positions_increments[i]; } // adjust heights and actual positions of markers 1 to num_markers-2 if necessary for(std::size_t i = 1; i <= num_markers - 2; ++i) { // offset to desired position float_type d = this->desired_positions[i] - this->actual_positions[i]; // offset to next position float_type dp = this->actual_positions[i+1] - this->actual_positions[i]; // offset to previous position float_type dm = this->actual_positions[i-1] - this->actual_positions[i]; // height ds float_type hp = (this->heights[i+1] - this->heights[i]) / dp; float_type hm = (this->heights[i-1] - this->heights[i]) / dm; if((d >= 1 && dp > 1) || (d <= -1 && dm < -1)) { short sign_d = static_cast(d / std::abs(d)); float_type h = this->heights[i] + sign_d / (dp - dm) * ((sign_d - dm)*hp + (dp - sign_d) * hm); // try adjusting heights[i] using p-squared formula if(this->heights[i - 1] < h && h < this->heights[i + 1]) { this->heights[i] = h; } else { // use linear formula if(d > 0) { this->heights[i] += hp; } if(d < 0) { this->heights[i] -= hm; } } this->actual_positions[i] += sign_d; } } } } result_type result(dont_care) const { // for i in [1,probabilities.size()], return heights[i * 2] detail::times2_iterator idx_begin = detail::make_times2_iterator(1); detail::times2_iterator idx_end = detail::make_times2_iterator(this->probabilities.size() + 1); return result_type( make_permutation_iterator(this->heights.begin(), idx_begin) , make_permutation_iterator(this->heights.begin(), idx_end) ); } private: array_type probabilities; // the quantile probabilities array_type heights; // q_i array_type actual_positions; // n_i array_type desired_positions; // d_i array_type positions_increments; // f_i }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::extended_p_square // namespace tag { struct extended_p_square : depends_on , extended_p_square_probabilities { typedef accumulators::impl::extended_p_square_impl impl; #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED /// tag::extended_p_square::probabilities named paramter static boost::parameter::keyword const probabilities; #endif }; } /////////////////////////////////////////////////////////////////////////////// // extract::extended_p_square // namespace extract { extractor const extended_p_square = {}; } using extract::extended_p_square; // So that extended_p_square can be automatically substituted with // weighted_extended_p_square when the weight parameter is non-void template<> struct as_weighted_feature { typedef tag::weighted_extended_p_square type; }; template<> struct feature_of : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/extended_p_square_quantile.hpp000644 000000 000000 00000027144 11124251706 026622 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // extended_p_square_quantile.hpp // // Copyright 2005 Daniel Egloff. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_EXTENDED_SINGLE_QUANTILE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_EXTENDED_SINGLE_QUANTILE_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #ifdef _MSC_VER # pragma warning(push) # pragma warning(disable: 4127) // conditional expression is constant #endif namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // extended_p_square_quantile_impl // single quantile estimation /** @brief Quantile estimation using the extended \f$P^2\f$ algorithm for weighted and unweighted samples Uses the quantile estimates calculated by the extended \f$P^2\f$ algorithm to compute intermediate quantile estimates by means of quadratic interpolation. @param quantile_probability The probability of the quantile to be estimated. */ template // Impl1: weighted/unweighted // Impl2: linear/quadratic struct extended_p_square_quantile_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef std::vector array_type; typedef iterator_range< detail::lvalue_index_iterator< permutation_iterator< typename array_type::const_iterator , detail::times2_iterator > > > range_type; // for boost::result_of typedef float_type result_type; template extended_p_square_quantile_impl(Args const &args) : probabilities( boost::begin(args[extended_p_square_probabilities]) , boost::end(args[extended_p_square_probabilities]) ) { } template result_type result(Args const &args) const { typedef typename mpl::if_< is_same , tag::weighted_extended_p_square , tag::extended_p_square >::type extended_p_square_tag; extractor const some_extended_p_square = {}; array_type heights(some_extended_p_square(args).size()); std::copy(some_extended_p_square(args).begin(), some_extended_p_square(args).end(), heights.begin()); this->probability = args[quantile_probability]; typename array_type::const_iterator iter_probs = std::lower_bound(this->probabilities.begin(), this->probabilities.end(), this->probability); std::size_t dist = std::distance(this->probabilities.begin(), iter_probs); typename array_type::const_iterator iter_heights = heights.begin() + dist; // If this->probability is not in a valid range return NaN or throw exception if (this->probability < *this->probabilities.begin() || this->probability > *(this->probabilities.end() - 1)) { if (std::numeric_limits::has_quiet_NaN) { return std::numeric_limits::quiet_NaN(); } else { std::ostringstream msg; msg << "probability = " << this->probability << " is not in valid range ("; msg << *this->probabilities.begin() << ", " << *(this->probabilities.end() - 1) << ")"; boost::throw_exception(std::runtime_error(msg.str())); return Sample(0); } } if (*iter_probs == this->probability) { return heights[dist]; } else { result_type result; if (is_same::value) { ///////////////////////////////////////////////////////////////////////////////// // LINEAR INTERPOLATION // float_type p1 = *iter_probs; float_type p0 = *(iter_probs - 1); float_type h1 = *iter_heights; float_type h0 = *(iter_heights - 1); float_type a = numeric::average(h1 - h0, p1 - p0); float_type b = h1 - p1 * a; result = a * this->probability + b; } else { ///////////////////////////////////////////////////////////////////////////////// // QUADRATIC INTERPOLATION // float_type p0, p1, p2; float_type h0, h1, h2; if ( (dist == 1 || *iter_probs - this->probability <= this->probability - *(iter_probs - 1) ) && dist != this->probabilities.size() - 1 ) { p0 = *(iter_probs - 1); p1 = *iter_probs; p2 = *(iter_probs + 1); h0 = *(iter_heights - 1); h1 = *iter_heights; h2 = *(iter_heights + 1); } else { p0 = *(iter_probs - 2); p1 = *(iter_probs - 1); p2 = *iter_probs; h0 = *(iter_heights - 2); h1 = *(iter_heights - 1); h2 = *iter_heights; } float_type hp21 = numeric::average(h2 - h1, p2 - p1); float_type hp10 = numeric::average(h1 - h0, p1 - p0); float_type p21 = numeric::average(p2 * p2 - p1 * p1, p2 - p1); float_type p10 = numeric::average(p1 * p1 - p0 * p0, p1 - p0); float_type a = numeric::average(hp21 - hp10, p21 - p10); float_type b = hp21 - a * p21; float_type c = h2 - a * p2 * p2 - b * p2; result = a * this->probability * this-> probability + b * this->probability + c; } return result; } } private: array_type probabilities; mutable float_type probability; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::extended_p_square_quantile // namespace tag { struct extended_p_square_quantile : depends_on { typedef accumulators::impl::extended_p_square_quantile_impl impl; }; struct extended_p_square_quantile_quadratic : depends_on { typedef accumulators::impl::extended_p_square_quantile_impl impl; }; struct weighted_extended_p_square_quantile : depends_on { typedef accumulators::impl::extended_p_square_quantile_impl impl; }; struct weighted_extended_p_square_quantile_quadratic : depends_on { typedef accumulators::impl::extended_p_square_quantile_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::extended_p_square_quantile // extract::weighted_extended_p_square_quantile // namespace extract { extractor const extended_p_square_quantile = {}; extractor const extended_p_square_quantile_quadratic = {}; extractor const weighted_extended_p_square_quantile = {}; extractor const weighted_extended_p_square_quantile_quadratic = {}; } using extract::extended_p_square_quantile; using extract::extended_p_square_quantile_quadratic; using extract::weighted_extended_p_square_quantile; using extract::weighted_extended_p_square_quantile_quadratic; // extended_p_square_quantile(linear) -> extended_p_square_quantile template<> struct as_feature { typedef tag::extended_p_square_quantile type; }; // extended_p_square_quantile(quadratic) -> extended_p_square_quantile_quadratic template<> struct as_feature { typedef tag::extended_p_square_quantile_quadratic type; }; // weighted_extended_p_square_quantile(linear) -> weighted_extended_p_square_quantile template<> struct as_feature { typedef tag::weighted_extended_p_square_quantile type; }; // weighted_extended_p_square_quantile(quadratic) -> weighted_extended_p_square_quantile_quadratic template<> struct as_feature { typedef tag::weighted_extended_p_square_quantile_quadratic type; }; // for the purposes of feature-based dependency resolution, // extended_p_square_quantile and weighted_extended_p_square_quantile // provide the same feature as quantile template<> struct feature_of : feature_of { }; template<> struct feature_of : feature_of { }; // So that extended_p_square_quantile can be automatically substituted with // weighted_extended_p_square_quantile when the weight parameter is non-void template<> struct as_weighted_feature { typedef tag::weighted_extended_p_square_quantile type; }; template<> struct feature_of : feature_of { }; // So that extended_p_square_quantile_quadratic can be automatically substituted with // weighted_extended_p_square_quantile_quadratic when the weight parameter is non-void template<> struct as_weighted_feature { typedef tag::weighted_extended_p_square_quantile_quadratic type; }; template<> struct feature_of : feature_of { }; }} // namespace boost::accumulators #ifdef _MSC_VER # pragma warning(pop) #endif #endif include/boost/accumulators/statistics/kurtosis.hpp000644 000000 000000 00000006767 11124251705 023113 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // kurtosis.hpp // // Copyright 2006 Olivier Gygi, Daniel Egloff. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_KURTOSIS_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_KURTOSIS_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // kurtosis_impl /** @brief Kurtosis estimation The kurtosis of a sample distribution is defined as the ratio of the 4th central moment and the square of the 2nd central moment (the variance) of the samples, minus 3. The term \f$ -3 \f$ is added in order to ensure that the normal distribution has zero kurtosis. The kurtosis can also be expressed by the simple moments: \f[ \hat{g}_2 = \frac {\widehat{m}_n^{(4)}-4\widehat{m}_n^{(3)}\hat{\mu}_n+6\widehat{m}_n^{(2)}\hat{\mu}_n^2-3\hat{\mu}_n^4} {\left(\widehat{m}_n^{(2)} - \hat{\mu}_n^{2}\right)^2} - 3, \f] where \f$ \widehat{m}_n^{(i)} \f$ are the \f$ i \f$-th moment and \f$ \hat{\mu}_n \f$ the mean (first moment) of the \f$ n \f$ samples. */ template struct kurtosis_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::average::result_type result_type; kurtosis_impl(dont_care) {} template result_type result(Args const &args) const { return numeric::average( moment<4>(args) - 4. * moment<3>(args) * mean(args) + 6. * moment<2>(args) * mean(args) * mean(args) - 3. * mean(args) * mean(args) * mean(args) * mean(args) , ( moment<2>(args) - mean(args) * mean(args) ) * ( moment<2>(args) - mean(args) * mean(args) ) ) - 3.; } }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::kurtosis // namespace tag { struct kurtosis : depends_on, moment<3>, moment<4> > { /// INTERNAL ONLY /// typedef accumulators::impl::kurtosis_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::kurtosis // namespace extract { extractor const kurtosis = {}; } using extract::kurtosis; // So that kurtosis can be automatically substituted with // weighted_kurtosis when the weight parameter is non-void template<> struct as_weighted_feature { typedef tag::weighted_kurtosis type; }; template<> struct feature_of : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/max.hpp000644 000000 000000 00000004011 11124251706 021772 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // max.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_MAX_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_MAX_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // max_impl template struct max_impl : accumulator_base { // for boost::result_of typedef Sample result_type; template max_impl(Args const &args) : max_(numeric::as_min(args[sample | Sample()])) { } template void operator ()(Args const &args) { numeric::max_assign(this->max_, args[sample]); } result_type result(dont_care) const { return this->max_; } private: Sample max_; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::max // namespace tag { struct max : depends_on<> { /// INTERNAL ONLY /// typedef accumulators::impl::max_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::max // namespace extract { extractor const max = {}; } using extract::max; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/mean.hpp000644 000000 000000 00000021347 11124251704 022136 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // mean.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_MEAN_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_MEAN_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // mean_impl // lazy, by default template struct mean_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::average::result_type result_type; mean_impl(dont_care) {} template result_type result(Args const &args) const { extractor sum; return numeric::average(sum(args), count(args)); } }; template struct immediate_mean_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::average::result_type result_type; template immediate_mean_impl(Args const &args) : mean(numeric::average(args[sample | Sample()], numeric::one::value)) { } template void operator ()(Args const &args) { std::size_t cnt = count(args); this->mean = numeric::average( (this->mean * (cnt - 1)) + args[parameter::keyword::get()] , cnt ); } result_type result(dont_care) const { return this->mean; } private: result_type mean; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::mean // tag::immediate_mean // tag::mean_of_weights // tag::immediate_mean_of_weights // tag::mean_of_variates // tag::immediate_mean_of_variates // namespace tag { struct mean : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::mean_impl impl; }; struct immediate_mean : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::immediate_mean_impl impl; }; struct mean_of_weights : depends_on { typedef mpl::true_ is_weight_accumulator; /// INTERNAL ONLY /// typedef accumulators::impl::mean_impl impl; }; struct immediate_mean_of_weights : depends_on { typedef mpl::true_ is_weight_accumulator; /// INTERNAL ONLY /// typedef accumulators::impl::immediate_mean_impl impl; }; template struct mean_of_variates : depends_on > { /// INTERNAL ONLY /// typedef mpl::always > > impl; }; template struct immediate_mean_of_variates : depends_on { /// INTERNAL ONLY /// typedef mpl::always > impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::mean // extract::mean_of_weights // extract::mean_of_variates // namespace extract { extractor const mean = {}; extractor const mean_of_weights = {}; BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, mean_of_variates, (typename)(typename)) } using extract::mean; using extract::mean_of_weights; using extract::mean_of_variates; // mean(lazy) -> mean template<> struct as_feature { typedef tag::mean type; }; // mean(immediate) -> immediate_mean template<> struct as_feature { typedef tag::immediate_mean type; }; // mean_of_weights(lazy) -> mean_of_weights template<> struct as_feature { typedef tag::mean_of_weights type; }; // mean_of_weights(immediate) -> immediate_mean_of_weights template<> struct as_feature { typedef tag::immediate_mean_of_weights type; }; // mean_of_variates(lazy) -> mean_of_variates template struct as_feature(lazy)> { typedef tag::mean_of_variates type; }; // mean_of_variates(immediate) -> immediate_mean_of_variates template struct as_feature(immediate)> { typedef tag::immediate_mean_of_variates type; }; // for the purposes of feature-based dependency resolution, // immediate_mean provides the same feature as mean template<> struct feature_of : feature_of { }; // for the purposes of feature-based dependency resolution, // immediate_mean provides the same feature as mean template<> struct feature_of : feature_of { }; // for the purposes of feature-based dependency resolution, // immediate_mean provides the same feature as mean template struct feature_of > : feature_of > { }; // So that mean can be automatically substituted with // weighted_mean when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::weighted_mean type; }; template<> struct feature_of : feature_of {}; // So that immediate_mean can be automatically substituted with // immediate_weighted_mean when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::immediate_weighted_mean type; }; template<> struct feature_of : feature_of {}; // So that mean_of_weights<> can be automatically substituted with // weighted_mean_of_variates<> when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_mean_of_variates type; }; template struct feature_of > : feature_of > { }; // So that immediate_mean_of_weights<> can be automatically substituted with // immediate_weighted_mean_of_variates<> when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::immediate_weighted_mean_of_variates type; }; template struct feature_of > : feature_of > { }; //////////////////////////////////////////////////////////////////////////// //// droppable_accumulator //// need to specialize droppable lazy mean to cache the result at the //// point the accumulator is dropped. ///// INTERNAL ONLY ///// //template //struct droppable_accumulator > // : droppable_accumulator_base< // with_cached_result > // > //{ // template // droppable_accumulator(Args const &args) // : droppable_accumulator::base(args) // { // } //}; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/median.hpp000644 000000 000000 00000022327 11124251704 022452 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // median.hpp // // Copyright 2006 Eric Niebler, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_MEDIAN_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_MEDIAN_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // median_impl // /** @brief Median estimation based on the \f$P^2\f$ quantile estimator The \f$P^2\f$ algorithm is invoked with a quantile probability of 0.5. */ template struct median_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::average::result_type result_type; median_impl(dont_care) {} template result_type result(Args const &args) const { return p_square_quantile_for_median(args); } }; /////////////////////////////////////////////////////////////////////////////// // with_density_median_impl // /** @brief Median estimation based on the density estimator The algorithm determines the bin in which the \f$0.5*cnt\f$-th sample lies, \f$cnt\f$ being the total number of samples. It returns the approximate horizontal position of this sample, based on a linear interpolation inside the bin. */ template struct with_density_median_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef std::vector > histogram_type; typedef iterator_range range_type; // for boost::result_of typedef float_type result_type; template with_density_median_impl(Args const &args) : sum(numeric::average(args[sample | Sample()], (std::size_t)1)) , is_dirty(true) { } void operator ()(dont_care) { this->is_dirty = true; } template result_type result(Args const &args) const { if (this->is_dirty) { this->is_dirty = false; std::size_t cnt = count(args); range_type histogram = density(args); typename range_type::iterator it = histogram.begin(); while (this->sum < 0.5 * cnt) { this->sum += it->second * cnt; ++it; } --it; float_type over = numeric::average(this->sum - 0.5 * cnt, it->second * cnt); this->median = it->first * over + (it + 1)->first * (1. - over); } return this->median; } private: mutable float_type sum; mutable bool is_dirty; mutable float_type median; }; /////////////////////////////////////////////////////////////////////////////// // with_p_square_cumulative_distribution_median_impl // /** @brief Median estimation based on the \f$P^2\f$ cumulative distribution estimator The algorithm determines the first (leftmost) bin with a height exceeding 0.5. It returns the approximate horizontal position of where the cumulative distribution equals 0.5, based on a linear interpolation inside the bin. */ template struct with_p_square_cumulative_distribution_median_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef std::vector > histogram_type; typedef iterator_range range_type; // for boost::result_of typedef float_type result_type; with_p_square_cumulative_distribution_median_impl(dont_care) : is_dirty(true) { } void operator ()(dont_care) { this->is_dirty = true; } template result_type result(Args const &args) const { if (this->is_dirty) { this->is_dirty = false; range_type histogram = p_square_cumulative_distribution(args); typename range_type::iterator it = histogram.begin(); while (it->second < 0.5) { ++it; } float_type over = numeric::average(it->second - 0.5, it->second - (it - 1)->second); this->median = it->first * over + (it + 1)->first * ( 1. - over ); } return this->median; } private: mutable bool is_dirty; mutable float_type median; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::median // tag::with_densisty_median // tag::with_p_square_cumulative_distribution_median // namespace tag { struct median : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::median_impl impl; }; struct with_density_median : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::with_density_median_impl impl; }; struct with_p_square_cumulative_distribution_median : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::with_p_square_cumulative_distribution_median_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::median // extract::with_density_median // extract::with_p_square_cumulative_distribution_median // namespace extract { extractor const median = {}; extractor const with_density_median = {}; extractor const with_p_square_cumulative_distribution_median = {}; } using extract::median; using extract::with_density_median; using extract::with_p_square_cumulative_distribution_median; // median(with_p_square_quantile) -> median template<> struct as_feature { typedef tag::median type; }; // median(with_density) -> with_density_median template<> struct as_feature { typedef tag::with_density_median type; }; // median(with_p_square_cumulative_distribution) -> with_p_square_cumulative_distribution_median template<> struct as_feature { typedef tag::with_p_square_cumulative_distribution_median type; }; // for the purposes of feature-based dependency resolution, // with_density_median and with_p_square_cumulative_distribution_median // provide the same feature as median template<> struct feature_of : feature_of { }; template<> struct feature_of : feature_of { }; // So that median can be automatically substituted with // weighted_median when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::weighted_median type; }; template<> struct feature_of : feature_of { }; // So that with_density_median can be automatically substituted with // with_density_weighted_median when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::with_density_weighted_median type; }; template<> struct feature_of : feature_of { }; // So that with_p_square_cumulative_distribution_median can be automatically substituted with // with_p_square_cumulative_distribution_weighted_median when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::with_p_square_cumulative_distribution_weighted_median type; }; template<> struct feature_of : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/min.hpp000644 000000 000000 00000004011 11124251707 021771 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // min.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_MIN_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_MIN_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // min_impl template struct min_impl : accumulator_base { // for boost::result_of typedef Sample result_type; template min_impl(Args const &args) : min_(numeric::as_max(args[sample | Sample()])) { } template void operator ()(Args const &args) { numeric::min_assign(this->min_, args[sample]); } result_type result(dont_care) const { return this->min_; } private: Sample min_; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::min // namespace tag { struct min : depends_on<> { /// INTERNAL ONLY /// typedef accumulators::impl::min_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::min // namespace extract { extractor const min = {}; } using extract::min; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/moment.hpp000644 000000 000000 00000006231 11124251706 022512 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // moment.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_MOMENT_HPP_EAN_15_11_2005 #define BOOST_ACCUMULATORS_STATISTICS_MOMENT_HPP_EAN_15_11_2005 #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace numeric { /// INTERNAL ONLY /// template T const &pow(T const &x, mpl::int_<1>) { return x; } /// INTERNAL ONLY /// template T pow(T const &x, mpl::int_) { using namespace operators; T y = numeric::pow(x, mpl::int_()); T z = y * y; return (N % 2) ? (z * x) : z; } }} namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // moment_impl template struct moment_impl : accumulator_base // TODO: also depends_on sum of powers { BOOST_MPL_ASSERT_RELATION(N::value, >, 0); // for boost::result_of typedef typename numeric::functional::average::result_type result_type; template moment_impl(Args const &args) : sum(args[sample | Sample()]) { } template void operator ()(Args const &args) { this->sum += numeric::pow(args[sample], N()); } template result_type result(Args const &args) const { return numeric::average(this->sum, count(args)); } private: Sample sum; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::moment // namespace tag { template struct moment : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::moment_impl, mpl::_1> impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::moment // namespace extract { BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, moment, (int)) } using extract::moment; // So that moment can be automatically substituted with // weighted_moment when the weight parameter is non-void template struct as_weighted_feature > { typedef tag::weighted_moment type; }; template struct feature_of > : feature_of > { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/p_square_cumulative_distribution.hpp000644 000000 000000 00000022656 11124251707 030101 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // p_square_cumulative_distribution.hpp // // Copyright 2005 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_P_SQUARE_CUMULATIVE_DISTRIBUTION_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_P_SQUARE_CUMULATIVE_DISTRIBUTION_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////////// // num_cells named parameter // BOOST_PARAMETER_NESTED_KEYWORD(tag, p_square_cumulative_distribution_num_cells, num_cells) namespace impl { /////////////////////////////////////////////////////////////////////////////// // p_square_cumulative_distribution_impl // cumulative_distribution calculation (as histogram) /** @brief Histogram calculation of the cumulative distribution with the \f$P^2\f$ algorithm A histogram of the sample cumulative distribution is computed dynamically without storing samples based on the \f$ P^2 \f$ algorithm. The returned histogram has a specifiable amount (num_cells) equiprobable (and not equal-sized) cells. For further details, see R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and histograms without storing observations, Communications of the ACM, Volume 28 (October), Number 10, 1985, p. 1076-1085. @param p_square_cumulative_distribution_num_cells. */ template struct p_square_cumulative_distribution_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef std::vector array_type; typedef std::vector > histogram_type; // for boost::result_of typedef iterator_range result_type; template p_square_cumulative_distribution_impl(Args const &args) : num_cells(args[p_square_cumulative_distribution_num_cells]) , heights(num_cells + 1) , actual_positions(num_cells + 1) , desired_positions(num_cells + 1) , positions_increments(num_cells + 1) , histogram(num_cells + 1) , is_dirty(true) { std::size_t b = this->num_cells; for (std::size_t i = 0; i < b + 1; ++i) { this->actual_positions[i] = i + 1.; this->desired_positions[i] = i + 1.; this->positions_increments[i] = numeric::average(i, b); } } template void operator ()(Args const &args) { this->is_dirty = true; std::size_t cnt = count(args); std::size_t sample_cell = 1; // k std::size_t b = this->num_cells; // accumulate num_cells + 1 first samples if (cnt <= b + 1) { this->heights[cnt - 1] = args[sample]; // complete the initialization of heights by sorting if (cnt == b + 1) { std::sort(this->heights.begin(), this->heights.end()); } } else { // find cell k such that heights[k-1] <= args[sample] < heights[k] and adjust extreme values if (args[sample] < this->heights[0]) { this->heights[0] = args[sample]; sample_cell = 1; } else if (this->heights[b] <= args[sample]) { this->heights[b] = args[sample]; sample_cell = b; } else { typename array_type::iterator it; it = std::upper_bound( this->heights.begin() , this->heights.end() , args[sample] ); sample_cell = std::distance(this->heights.begin(), it); } // increment positions of markers above sample_cell for (std::size_t i = sample_cell; i < b + 1; ++i) { ++this->actual_positions[i]; } // update desired position of markers 2 to num_cells + 1 // (desired position of first marker is always 1) for (std::size_t i = 1; i < b + 1; ++i) { this->desired_positions[i] += this->positions_increments[i]; } // adjust heights of markers 2 to num_cells if necessary for (std::size_t i = 1; i < b; ++i) { // offset to desire position float_type d = this->desired_positions[i] - this->actual_positions[i]; // offset to next position float_type dp = this->actual_positions[i + 1] - this->actual_positions[i]; // offset to previous position float_type dm = this->actual_positions[i - 1] - this->actual_positions[i]; // height ds float_type hp = (this->heights[i + 1] - this->heights[i]) / dp; float_type hm = (this->heights[i - 1] - this->heights[i]) / dm; if ( ( d >= 1. && dp > 1. ) || ( d <= -1. && dm < -1. ) ) { short sign_d = static_cast(d / std::abs(d)); // try adjusting heights[i] using p-squared formula float_type h = this->heights[i] + sign_d / (dp - dm) * ( (sign_d - dm) * hp + (dp - sign_d) * hm ); if ( this->heights[i - 1] < h && h < this->heights[i + 1] ) { this->heights[i] = h; } else { // use linear formula if (d>0) { this->heights[i] += hp; } if (d<0) { this->heights[i] -= hm; } } this->actual_positions[i] += sign_d; } } } } template result_type result(Args const &args) const { if (this->is_dirty) { this->is_dirty = false; // creates a vector of std::pair where each pair i holds // the values heights[i] (x-axis of histogram) and // actual_positions[i] / cnt (y-axis of histogram) std::size_t cnt = count(args); for (std::size_t i = 0; i < this->histogram.size(); ++i) { this->histogram[i] = std::make_pair(this->heights[i], numeric::average(this->actual_positions[i], cnt)); } } //return histogram; return make_iterator_range(this->histogram); } private: std::size_t num_cells; // number of cells b array_type heights; // q_i array_type actual_positions; // n_i array_type desired_positions; // n'_i array_type positions_increments; // dn'_i mutable histogram_type histogram; // histogram mutable bool is_dirty; }; } // namespace detail /////////////////////////////////////////////////////////////////////////////// // tag::p_square_cumulative_distribution // namespace tag { struct p_square_cumulative_distribution : depends_on , p_square_cumulative_distribution_num_cells { /// INTERNAL ONLY /// typedef accumulators::impl::p_square_cumulative_distribution_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::p_square_cumulative_distribution // namespace extract { extractor const p_square_cumulative_distribution = {}; } using extract::p_square_cumulative_distribution; // So that p_square_cumulative_distribution can be automatically substituted with // weighted_p_square_cumulative_distribution when the weight parameter is non-void template<> struct as_weighted_feature { typedef tag::weighted_p_square_cumulative_distribution type; }; template<> struct feature_of : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/p_square_quantile.hpp000644 000000 000000 00000022010 11124251705 024724 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // p_square_quantile.hpp // // Copyright 2005 Daniel Egloff. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_P_SQUARE_QUANTILE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_P_SQUARE_QUANTILE_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // p_square_quantile_impl // single quantile estimation /** @brief Single quantile estimation with the \f$P^2\f$ algorithm The \f$P^2\f$ algorithm estimates a quantile dynamically without storing samples. Instead of storing the whole sample cumulative distribution, only five points (markers) are stored. The heights of these markers are the minimum and the maximum of the samples and the current estimates of the \f$(p/2)\f$-, \f$p\f$- and \f$(1+p)/2\f$-quantiles. Their positions are equal to the number of samples that are smaller or equal to the markers. Each time a new samples is recorded, the positions of the markers are updated and if necessary their heights are adjusted using a piecewise- parabolic formula. For further details, see R. Jain and I. Chlamtac, The P^2 algorithmus fordynamic calculation of quantiles and histograms without storing observations, Communications of the ACM, Volume 28 (October), Number 10, 1985, p. 1076-1085. @param quantile_probability */ template struct p_square_quantile_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef array array_type; // for boost::result_of typedef float_type result_type; template p_square_quantile_impl(Args const &args) : p(is_same::value ? 0.5 : args[quantile_probability | 0.5]) , heights() , actual_positions() , desired_positions() , positions_increments() { for(std::size_t i = 0; i < 5; ++i) { this->actual_positions[i] = i + 1; } this->desired_positions[0] = 1.; this->desired_positions[1] = 1. + 2. * this->p; this->desired_positions[2] = 1. + 4. * this->p; this->desired_positions[3] = 3. + 2. * this->p; this->desired_positions[4] = 5.; this->positions_increments[0] = 0.; this->positions_increments[1] = this->p / 2.; this->positions_increments[2] = this->p; this->positions_increments[3] = (1. + this->p) / 2.; this->positions_increments[4] = 1.; } template void operator ()(Args const &args) { std::size_t cnt = count(args); // accumulate 5 first samples if(cnt <= 5) { this->heights[cnt - 1] = args[sample]; // complete the initialization of heights by sorting if(cnt == 5) { std::sort(this->heights.begin(), this->heights.end()); } } else { std::size_t sample_cell = 1; // k // find cell k such that heights[k-1] <= args[sample] < heights[k] and ajust extreme values if (args[sample] < this->heights[0]) { this->heights[0] = args[sample]; sample_cell = 1; } else if (this->heights[4] <= args[sample]) { this->heights[4] = args[sample]; sample_cell = 4; } else { typedef typename array_type::iterator iterator; iterator it = std::upper_bound( this->heights.begin() , this->heights.end() , args[sample] ); sample_cell = std::distance(this->heights.begin(), it); } // update positions of markers above sample_cell for(std::size_t i = sample_cell; i < 5; ++i) { ++this->actual_positions[i]; } // update desired positions of all markers for(std::size_t i = 0; i < 5; ++i) { this->desired_positions[i] += this->positions_increments[i]; } // adjust heights and actual positions of markers 1 to 3 if necessary for(std::size_t i = 1; i <= 3; ++i) { // offset to desired positions float_type d = this->desired_positions[i] - this->actual_positions[i]; // offset to next position float_type dp = this->actual_positions[i + 1] - this->actual_positions[i]; // offset to previous position float_type dm = this->actual_positions[i - 1] - this->actual_positions[i]; // height ds float_type hp = (this->heights[i + 1] - this->heights[i]) / dp; float_type hm = (this->heights[i - 1] - this->heights[i]) / dm; if((d >= 1. && dp > 1.) || (d <= -1. && dm < -1.)) { short sign_d = static_cast(d / std::abs(d)); // try adjusting heights[i] using p-squared formula float_type h = this->heights[i] + sign_d / (dp - dm) * ((sign_d - dm) * hp + (dp - sign_d) * hm); if(this->heights[i - 1] < h && h < this->heights[i + 1]) { this->heights[i] = h; } else { // use linear formula if(d > 0) { this->heights[i] += hp; } if(d < 0) { this->heights[i] -= hm; } } this->actual_positions[i] += sign_d; } } } } result_type result(dont_care) const { return this->heights[2]; } private: float_type p; // the quantile probability p array_type heights; // q_i array_type actual_positions; // n_i array_type desired_positions; // n'_i array_type positions_increments; // dn'_i }; } // namespace detail /////////////////////////////////////////////////////////////////////////////// // tag::p_square_quantile // namespace tag { struct p_square_quantile : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::p_square_quantile_impl impl; }; struct p_square_quantile_for_median : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::p_square_quantile_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::p_square_quantile // extract::p_square_quantile_for_median // namespace extract { extractor const p_square_quantile = {}; extractor const p_square_quantile_for_median = {}; } using extract::p_square_quantile; using extract::p_square_quantile_for_median; // So that p_square_quantile can be automatically substituted with // weighted_p_square_quantile when the weight parameter is non-void template<> struct as_weighted_feature { typedef tag::weighted_p_square_quantile type; }; template<> struct feature_of : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/parameters/quantile_probability.hpp000644 000000 000000 00000001223 11124251215 027567 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // quantile_probability.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_PARAMETERS_QUANTILE_PROBABILITY_HPP_EAN_03_11_2005 #define BOOST_ACCUMULATORS_STATISTICS_PARAMETERS_QUANTILE_PROBABILITY_HPP_EAN_03_11_2005 #include namespace boost { namespace accumulators { BOOST_PARAMETER_KEYWORD(tag, quantile_probability) }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/peaks_over_threshold.hpp000644 000000 000000 00000037644 11124251705 025440 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // peaks_over_threshold.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_PEAKS_OVER_THRESHOLD_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_PEAKS_OVER_THRESHOLD_HPP_DE_01_01_2006 #include #include #include #include #include // pow #include // stringstream #include // runtime_error #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #ifdef _MSC_VER # pragma warning(push) # pragma warning(disable: 4127) // conditional expression is constant #endif namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////////// // threshold_probability and threshold named parameters // BOOST_PARAMETER_NESTED_KEYWORD(tag, pot_threshold_value, threshold_value) BOOST_PARAMETER_NESTED_KEYWORD(tag, pot_threshold_probability, threshold_probability) namespace impl { /////////////////////////////////////////////////////////////////////////////// // peaks_over_threshold_impl // works with an explicit threshold value and does not depend on order statistics /** @brief Peaks over Threshold Method for Quantile and Tail Mean Estimation According to the theorem of Pickands-Balkema-de Haan, the distribution function \f$F_u(x)\f$ of the excesses \f$x\f$ over some sufficiently high threshold \f$u\f$ of a distribution function \f$F(x)\f$ may be approximated by a generalized Pareto distribution \f[ G_{\xi,\beta}(x) = \left\{ \begin{array}{ll} \beta^{-1}\left(1+\frac{\xi x}{\beta}\right)^{-1/\xi-1} & \textrm{if }\xi\neq0\\ \beta^{-1}\exp\left(-\frac{x}{\beta}\right) & \textrm{if }\xi=0, \end{array} \right. \f] with suitable parameters \f$\xi\f$ and \f$\beta\f$ that can be estimated, e.g., with the method of moments, cf. Hosking and Wallis (1987), \f[ \begin{array}{lll} \hat{\xi} & = & \frac{1}{2}\left[1-\frac{(\hat{\mu}-u)^2}{\hat{\sigma}^2}\right]\\ \hat{\beta} & = & \frac{\hat{\mu}-u}{2}\left[\frac{(\hat{\mu}-u)^2}{\hat{\sigma}^2}+1\right], \end{array} \f] \f$\hat{\mu}\f$ and \f$\hat{\sigma}^2\f$ being the empirical mean and variance of the samples over the threshold \f$u\f$. Equivalently, the distribution function \f$F_u(x-u)\f$ of the exceedances \f$x-u\f$ can be approximated by \f$G_{\xi,\beta}(x-u)=G_{\xi,\beta,u}(x)\f$. Since for \f$x\geq u\f$ the distribution function \f$F(x)\f$ can be written as \f[ F(x) = [1 - \P(X \leq u)]F_u(x - u) + \P(X \leq u) \f] and the probability \f$\P(X \leq u)\f$ can be approximated by the empirical distribution function \f$F_n(u)\f$ evaluated at \f$u\f$, an estimator of \f$F(x)\f$ is given by \f[ \widehat{F}(x) = [1 - F_n(u)]G_{\xi,\beta,u}(x) + F_n(u). \f] It can be shown that \f$\widehat{F}(x)\f$ is a generalized Pareto distribution \f$G_{\xi,\bar{\beta},\bar{u}}(x)\f$ with \f$\bar{\beta}=\beta[1-F_n(u)]^{\xi}\f$ and \f$\bar{u}=u-\bar{\beta}\left\{[1-F_n(u)]^{-\xi}-1\right\}/\xi\f$. By inverting \f$\widehat{F}(x)\f$, one obtains an estimator for the \f$\alpha\f$-quantile, \f[ \hat{q}_{\alpha} = \bar{u} + \frac{\bar{\beta}}{\xi}\left[(1-\alpha)^{-\xi}-1\right], \f] and similarly an estimator for the (coherent) tail mean, \f[ \widehat{CTM}_{\alpha} = \hat{q}_{\alpha} - \frac{\bar{\beta}}{\xi-1}(1-\alpha)^{-\xi}, \f] cf. McNeil and Frey (2000). Note that in case extreme values of the left tail are fitted, the distribution is mirrored with respect to the \f$y\f$ axis such that the left tail can be treated as a right tail. The computed fit parameters thus define the Pareto distribution that fits the mirrored left tail. When quantities like a quantile or a tail mean are computed using the fit parameters obtained from the mirrored data, the result is mirrored back, yielding the correct result. For further details, see J. R. M. Hosking and J. R. Wallis, Parameter and quantile estimation for the generalized Pareto distribution, Technometrics, Volume 29, 1987, p. 339-349 A. J. McNeil and R. Frey, Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: an Extreme Value Approach, Journal of Empirical Finance, Volume 7, 2000, p. 271-300 @param quantile_probability @param pot_threshold_value */ template struct peaks_over_threshold_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; // for boost::result_of typedef boost::tuple result_type; // for left tail fitting, mirror the extreme values typedef mpl::int_::value ? -1 : 1> sign; template peaks_over_threshold_impl(Args const &args) : Nu_(0) , mu_(sign::value * numeric::average(args[sample | Sample()], (std::size_t)1)) , sigma2_(numeric::average(args[sample | Sample()], (std::size_t)1)) , threshold_(sign::value * args[pot_threshold_value]) , fit_parameters_(boost::make_tuple(0., 0., 0.)) , is_dirty_(true) { } template void operator ()(Args const &args) { this->is_dirty_ = true; if (sign::value * args[sample] > this->threshold_) { this->mu_ += args[sample]; this->sigma2_ += args[sample] * args[sample]; ++this->Nu_; } } template result_type result(Args const &args) const { if (this->is_dirty_) { this->is_dirty_ = false; std::size_t cnt = count(args); this->mu_ = sign::value * numeric::average(this->mu_, this->Nu_); this->sigma2_ = numeric::average(this->sigma2_, this->Nu_); this->sigma2_ -= this->mu_ * this->mu_; float_type threshold_probability = numeric::average(cnt - this->Nu_, cnt); float_type tmp = numeric::average(( this->mu_ - this->threshold_ )*( this->mu_ - this->threshold_ ), this->sigma2_); float_type xi_hat = 0.5 * ( 1. - tmp ); float_type beta_hat = 0.5 * ( this->mu_ - this->threshold_ ) * ( 1. + tmp ); float_type beta_bar = beta_hat * std::pow(1. - threshold_probability, xi_hat); float_type u_bar = this->threshold_ - beta_bar * ( std::pow(1. - threshold_probability, -xi_hat) - 1.)/xi_hat; this->fit_parameters_ = boost::make_tuple(u_bar, beta_bar, xi_hat); } return this->fit_parameters_; } private: std::size_t Nu_; // number of samples larger than threshold mutable float_type mu_; // mean of Nu_ largest samples mutable float_type sigma2_; // variance of Nu_ largest samples float_type threshold_; mutable result_type fit_parameters_; // boost::tuple that stores fit parameters mutable bool is_dirty_; }; /////////////////////////////////////////////////////////////////////////////// // peaks_over_threshold_prob_impl // determines threshold from a given threshold probability using order statistics /** @brief Peaks over Threshold Method for Quantile and Tail Mean Estimation @sa peaks_over_threshold_impl @param quantile_probability @param pot_threshold_probability */ template struct peaks_over_threshold_prob_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; // for boost::result_of typedef boost::tuple result_type; // for left tail fitting, mirror the extreme values typedef mpl::int_::value ? -1 : 1> sign; template peaks_over_threshold_prob_impl(Args const &args) : mu_(sign::value * numeric::average(args[sample | Sample()], (std::size_t)1)) , sigma2_(numeric::average(args[sample | Sample()], (std::size_t)1)) , threshold_probability_(args[pot_threshold_probability]) , fit_parameters_(boost::make_tuple(0., 0., 0.)) , is_dirty_(true) { } void operator ()(dont_care) { this->is_dirty_ = true; } template result_type result(Args const &args) const { if (this->is_dirty_) { this->is_dirty_ = false; std::size_t cnt = count(args); // the n'th cached sample provides an approximate threshold value u std::size_t n = static_cast( std::ceil( cnt * ( ( is_same::value ) ? this->threshold_probability_ : 1. - this->threshold_probability_ ) ) ); // If n is in a valid range, return result, otherwise return NaN or throw exception if ( n >= static_cast(tail(args).size())) { if (std::numeric_limits::has_quiet_NaN) { return boost::make_tuple( std::numeric_limits::quiet_NaN() , std::numeric_limits::quiet_NaN() , std::numeric_limits::quiet_NaN() ); } else { std::ostringstream msg; msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")"; boost::throw_exception(std::runtime_error(msg.str())); return boost::make_tuple(Sample(0), Sample(0), Sample(0)); } } else { float_type u = *(tail(args).begin() + n - 1) * sign::value; // compute mean and variance of samples above/under threshold value u for (std::size_t i = 0; i < n; ++i) { mu_ += *(tail(args).begin() + i); sigma2_ += *(tail(args).begin() + i) * (*(tail(args).begin() + i)); } this->mu_ = sign::value * numeric::average(this->mu_, n); this->sigma2_ = numeric::average(this->sigma2_, n); this->sigma2_ -= this->mu_ * this->mu_; if (is_same::value) this->threshold_probability_ = 1. - this->threshold_probability_; float_type tmp = numeric::average(( this->mu_ - u )*( this->mu_ - u ), this->sigma2_); float_type xi_hat = 0.5 * ( 1. - tmp ); float_type beta_hat = 0.5 * ( this->mu_ - u ) * ( 1. + tmp ); float_type beta_bar = beta_hat * std::pow(1. - threshold_probability_, xi_hat); float_type u_bar = u - beta_bar * ( std::pow(1. - threshold_probability_, -xi_hat) - 1.)/xi_hat; this->fit_parameters_ = boost::make_tuple(u_bar, beta_bar, xi_hat); } } return this->fit_parameters_; } private: mutable float_type mu_; // mean of samples above threshold u mutable float_type sigma2_; // variance of samples above threshold u mutable float_type threshold_probability_; mutable result_type fit_parameters_; // boost::tuple that stores fit parameters mutable bool is_dirty_; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::peaks_over_threshold // namespace tag { template struct peaks_over_threshold : depends_on , pot_threshold_value { /// INTERNAL ONLY /// typedef accumulators::impl::peaks_over_threshold_impl impl; }; template struct peaks_over_threshold_prob : depends_on > , pot_threshold_probability { /// INTERNAL ONLY /// typedef accumulators::impl::peaks_over_threshold_prob_impl impl; }; struct abstract_peaks_over_threshold : depends_on<> { }; } /////////////////////////////////////////////////////////////////////////////// // extract::peaks_over_threshold // namespace extract { extractor const peaks_over_threshold = {}; } using extract::peaks_over_threshold; // peaks_over_threshold(with_threshold_value) -> peaks_over_threshold template struct as_feature(with_threshold_value)> { typedef tag::peaks_over_threshold type; }; // peaks_over_threshold(with_threshold_probability) -> peaks_over_threshold_prob template struct as_feature(with_threshold_probability)> { typedef tag::peaks_over_threshold_prob type; }; template struct feature_of > : feature_of { }; template struct feature_of > : feature_of { }; // So that peaks_over_threshold can be automatically substituted // with weighted_peaks_over_threshold when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_peaks_over_threshold type; }; template struct feature_of > : feature_of > {}; // So that peaks_over_threshold_prob can be automatically substituted // with weighted_peaks_over_threshold_prob when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_peaks_over_threshold_prob type; }; template struct feature_of > : feature_of > {}; }} // namespace boost::accumulators #ifdef _MSC_VER # pragma warning(pop) #endif #endif include/boost/accumulators/statistics/pot_quantile.hpp000644 000000 000000 00000015744 11124251706 023730 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // pot_quantile.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_POT_QUANTILE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_POT_QUANTILE_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // pot_quantile_impl // /** @brief Quantile Estimation based on Peaks over Threshold Method (for both left and right tails) Computes an estimate \f[ \hat{q}_{\alpha} = \bar{u} + \frac{\bar{\beta}}{\xi}\left[(1-\alpha)^{-\xi}-1\right] \f] for a right or left extreme quantile, \f$\bar[u]\f$, \f$\bar{\beta}\f$ and \f$\xi\f$ being the parameters of the generalized Pareto distribution that approximates the right tail of the distribution (or the mirrored left tail, in case the left tail is used). In the latter case, the result is mirrored back, yielding the correct result. */ template struct pot_quantile_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; // for boost::result_of typedef float_type result_type; pot_quantile_impl(dont_care) : sign_((is_same::value) ? -1 : 1) { } template result_type result(Args const &args) const { typedef typename mpl::if_< is_same , tag::weighted_peaks_over_threshold , tag::peaks_over_threshold >::type peaks_over_threshold_tag; extractor const some_peaks_over_threshold = {}; float_type u_bar = some_peaks_over_threshold(args).template get<0>(); float_type beta_bar = some_peaks_over_threshold(args).template get<1>(); float_type xi_hat = some_peaks_over_threshold(args).template get<2>(); return this->sign_ * (u_bar + beta_bar/xi_hat * ( std::pow( is_same::value ? args[quantile_probability] : 1. - args[quantile_probability] , -xi_hat ) - 1.)); } private: short sign_; // if the fit parameters from the mirrored left tail extreme values are used, mirror back the result }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::pot_quantile<> // tag::pot_quantile_prob<> // tag::weighted_pot_quantile<> // tag::weighted_pot_quantile_prob<> // namespace tag { template struct pot_quantile : depends_on > { /// INTERNAL ONLY /// typedef accumulators::impl::pot_quantile_impl impl; }; template struct pot_quantile_prob : depends_on > { /// INTERNAL ONLY /// typedef accumulators::impl::pot_quantile_impl impl; }; template struct weighted_pot_quantile : depends_on > { /// INTERNAL ONLY /// typedef accumulators::impl::pot_quantile_impl impl; }; template struct weighted_pot_quantile_prob : depends_on > { /// INTERNAL ONLY /// typedef accumulators::impl::pot_quantile_impl impl; }; } // pot_quantile(with_threshold_value) -> pot_quantile template struct as_feature(with_threshold_value)> { typedef tag::pot_quantile type; }; // pot_quantile(with_threshold_probability) -> pot_quantile_prob template struct as_feature(with_threshold_probability)> { typedef tag::pot_quantile_prob type; }; // weighted_pot_quantile(with_threshold_value) -> weighted_pot_quantile template struct as_feature(with_threshold_value)> { typedef tag::weighted_pot_quantile type; }; // weighted_pot_quantile(with_threshold_probability) -> weighted_pot_quantile_prob template struct as_feature(with_threshold_probability)> { typedef tag::weighted_pot_quantile_prob type; }; // for the purposes of feature-based dependency resolution, // pot_quantile and pot_quantile_prob provide // the same feature as quantile template struct feature_of > : feature_of { }; template struct feature_of > : feature_of { }; // So that pot_quantile can be automatically substituted // with weighted_pot_quantile when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_pot_quantile type; }; template struct feature_of > : feature_of > { }; // So that pot_quantile_prob can be automatically substituted // with weighted_pot_quantile_prob when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_pot_quantile_prob type; }; template struct feature_of > : feature_of > { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/pot_tail_mean.hpp000644 000000 000000 00000016665 11124251705 024041 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // pot_tail_mean.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_POT_TAIL_MEAN_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_POT_TAIL_MEAN_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // pot_tail_mean_impl // /** @brief Estimation of the (coherent) tail mean based on the peaks over threshold method (for both left and right tails) Computes an estimate for the (coherent) tail mean \f[ \widehat{CTM}_{\alpha} = \hat{q}_{\alpha} - \frac{\bar{\beta}}{\xi-1}(1-\alpha)^{-\xi}, \f] where \f$\bar[u]\f$, \f$\bar{\beta}\f$ and \f$\xi\f$ are the parameters of the generalized Pareto distribution that approximates the right tail of the distribution (or the mirrored left tail, in case the left tail is used). In the latter case, the result is mirrored back, yielding the correct result. */ template struct pot_tail_mean_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; // for boost::result_of typedef float_type result_type; pot_tail_mean_impl(dont_care) : sign_((is_same::value) ? -1 : 1) { } template result_type result(Args const &args) const { typedef typename mpl::if_< is_same , tag::weighted_peaks_over_threshold , tag::peaks_over_threshold >::type peaks_over_threshold_tag; typedef typename mpl::if_< is_same , tag::weighted_pot_quantile , tag::pot_quantile >::type pot_quantile_tag; extractor const some_peaks_over_threshold = {}; extractor const some_pot_quantile = {}; float_type beta_bar = some_peaks_over_threshold(args).template get<1>(); float_type xi_hat = some_peaks_over_threshold(args).template get<2>(); return some_pot_quantile(args) - this->sign_ * beta_bar/( xi_hat - 1. ) * std::pow( is_same::value ? args[quantile_probability] : 1. - args[quantile_probability] , -xi_hat); } private: short sign_; // if the fit parameters from the mirrored left tail extreme values are used, mirror back the result }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::pot_tail_mean // tag::pot_tail_mean_prob // namespace tag { template struct pot_tail_mean : depends_on, pot_quantile > { /// INTERNAL ONLY /// typedef accumulators::impl::pot_tail_mean_impl impl; }; template struct pot_tail_mean_prob : depends_on, pot_quantile_prob > { /// INTERNAL ONLY /// typedef accumulators::impl::pot_tail_mean_impl impl; }; template struct weighted_pot_tail_mean : depends_on, weighted_pot_quantile > { /// INTERNAL ONLY /// typedef accumulators::impl::pot_tail_mean_impl impl; }; template struct weighted_pot_tail_mean_prob : depends_on, weighted_pot_quantile_prob > { /// INTERNAL ONLY /// typedef accumulators::impl::pot_tail_mean_impl impl; }; } // pot_tail_mean(with_threshold_value) -> pot_tail_mean template struct as_feature(with_threshold_value)> { typedef tag::pot_tail_mean type; }; // pot_tail_mean(with_threshold_probability) -> pot_tail_mean_prob template struct as_feature(with_threshold_probability)> { typedef tag::pot_tail_mean_prob type; }; // weighted_pot_tail_mean(with_threshold_value) -> weighted_pot_tail_mean template struct as_feature(with_threshold_value)> { typedef tag::weighted_pot_tail_mean type; }; // weighted_pot_tail_mean(with_threshold_probability) -> weighted_pot_tail_mean_prob template struct as_feature(with_threshold_probability)> { typedef tag::weighted_pot_tail_mean_prob type; }; // for the purposes of feature-based dependency resolution, // pot_tail_mean and pot_tail_mean_prob provide // the same feature as tail_mean template struct feature_of > : feature_of { }; template struct feature_of > : feature_of { }; // So that pot_tail_mean can be automatically substituted // with weighted_pot_tail_mean when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_pot_tail_mean type; }; template struct feature_of > : feature_of > { }; // So that pot_tail_mean_prob can be automatically substituted // with weighted_pot_tail_mean_prob when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_pot_tail_mean_prob type; }; template struct feature_of > : feature_of > { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/skewness.hpp000644 000000 000000 00000006531 11124251707 023061 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // skewness.hpp // // Copyright 2006 Olivier Gygi, Daniel Egloff. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_SKEWNESS_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_SKEWNESS_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // skewness_impl /** @brief Skewness estimation The skewness of a sample distribution is defined as the ratio of the 3rd central moment and the \f$ 3/2 \f$-th power of the 2nd central moment (the variance) of the sampless 3. The skewness can also be expressed by the simple moments: \f[ \hat{g}_1 = \frac {\widehat{m}_n^{(3)}-3\widehat{m}_n^{(2)}\hat{\mu}_n+2\hat{\mu}_n^3} {\left(\widehat{m}_n^{(2)} - \hat{\mu}_n^{2}\right)^{3/2}} \f] where \f$ \widehat{m}_n^{(i)} \f$ are the \f$ i \f$-th moment and \f$ \hat{\mu}_n \f$ the mean (first moment) of the \f$ n \f$ samples. */ template struct skewness_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::average::result_type result_type; skewness_impl(dont_care) { } template result_type result(Args const &args) const { return numeric::average( moment<3>(args) - 3. * moment<2>(args) * mean(args) + 2. * mean(args) * mean(args) * mean(args) , ( moment<2>(args) - mean(args) * mean(args) ) * std::sqrt( moment<2>(args) - mean(args) * mean(args) ) ); } }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::skewness // namespace tag { struct skewness : depends_on, moment<3> > { /// INTERNAL ONLY /// typedef accumulators::impl::skewness_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::skewness // namespace extract { extractor const skewness = {}; } using extract::skewness; // So that skewness can be automatically substituted with // weighted_skewness when the weight parameter is non-void template<> struct as_weighted_feature { typedef tag::weighted_skewness type; }; template<> struct feature_of : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/stats.hpp000644 000000 000000 00000001714 11124251707 022353 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// /// \file stats.hpp /// Contains the stats<> template. /// // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_STATS_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_STATS_HPP_EAN_28_10_2005 #include #include #include namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////////// /// An MPL sequence of statistics. template struct stats : mpl::vector { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/sum.hpp000644 000000 000000 00000007005 11124251706 022017 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // sum.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_SUM_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_SUM_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // sum_impl template struct sum_impl : accumulator_base { // for boost::result_of typedef Sample result_type; template sum_impl(Args const &args) : sum(args[parameter::keyword::get() | Sample()]) { } template void operator ()(Args const &args) { // what about overflow? this->sum += args[parameter::keyword::get()]; } result_type result(dont_care) const { return this->sum; } private: Sample sum; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::sum // tag::sum_of_weights // tag::sum_of_variates // namespace tag { struct sum : depends_on<> { /// INTERNAL ONLY /// typedef accumulators::impl::sum_impl impl; }; struct sum_of_weights : depends_on<> { typedef mpl::true_ is_weight_accumulator; /// INTERNAL ONLY /// typedef accumulators::impl::sum_impl impl; }; template struct sum_of_variates : depends_on<> { /// INTERNAL ONLY /// typedef mpl::always > impl; }; struct abstract_sum_of_variates : depends_on<> { }; } /////////////////////////////////////////////////////////////////////////////// // extract::sum // extract::sum_of_weights // extract::sum_of_variates // namespace extract { extractor const sum = {}; extractor const sum_of_weights = {}; extractor const sum_of_variates = {}; } using extract::sum; using extract::sum_of_weights; using extract::sum_of_variates; // So that mean can be automatically substituted with // weighted_mean when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::weighted_sum type; }; template<> struct feature_of : feature_of {}; template struct feature_of > : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/tail.hpp000644 000000 000000 00000024352 11124251704 022146 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // tail.hpp // // Copyright 2005 Eric Niebler, Michael Gauckler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_TAIL_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_TAIL_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { /////////////////////////////////////////////////////////////////////////////// // cache_size named parameters BOOST_PARAMETER_NESTED_KEYWORD(tag, right_tail_cache_size, cache_size) BOOST_PARAMETER_NESTED_KEYWORD(tag, left_tail_cache_size, cache_size) namespace detail { /////////////////////////////////////////////////////////////////////////////// // tail_range /// INTERNAL ONLY /// template struct tail_range { typedef boost::iterator_range< boost::reverse_iterator > > type; }; /////////////////////////////////////////////////////////////////////////////// // make_tail_range /// INTERNAL ONLY /// template typename tail_range::type make_tail_range(ElementIterator elem_begin, IndexIterator index_begin, IndexIterator index_end) { return boost::make_iterator_range( boost::make_reverse_iterator( boost::make_permutation_iterator(elem_begin, index_end) ) , boost::make_reverse_iterator( boost::make_permutation_iterator(elem_begin, index_begin) ) ); } /////////////////////////////////////////////////////////////////////////////// // stat_assign_visitor /// INTERNAL ONLY /// template struct stat_assign_visitor { stat_assign_visitor(Args const &args, std::size_t index) : args(args) , index(index) { } template void operator ()(Stat &stat) const { stat.assign(this->args, this->index); } private: stat_assign_visitor &operator =(stat_assign_visitor const &); Args const &args; std::size_t index; }; /////////////////////////////////////////////////////////////////////////////// // stat_assign /// INTERNAL ONLY /// template inline stat_assign_visitor const stat_assign(Args const &args, std::size_t index) { return stat_assign_visitor(args, index); } /////////////////////////////////////////////////////////////////////////////// // is_tail_variate_feature /// INTERNAL ONLY /// template struct is_tail_variate_feature : mpl::false_ { }; /// INTERNAL ONLY /// template struct is_tail_variate_feature, LeftRight> : mpl::true_ { }; /// INTERNAL ONLY /// template struct is_tail_variate_feature, LeftRight> : mpl::true_ { }; } // namespace detail namespace impl { /////////////////////////////////////////////////////////////////////////////// // tail_impl template struct tail_impl : accumulator_base { // LeftRight must be either right or left BOOST_MPL_ASSERT(( mpl::or_, is_same > )); typedef typename mpl::if_< is_same , numeric::functional::greater , numeric::functional::less >::type predicate_type; // for boost::result_of typedef typename detail::tail_range< typename std::vector::const_iterator , std::vector::iterator >::type result_type; template tail_impl(Args const &args) : is_sorted(false) , indices() , samples(args[tag::tail::cache_size], args[sample | Sample()]) { this->indices.reserve(this->samples.size()); } tail_impl(tail_impl const &that) : is_sorted(that.is_sorted) , indices(that.indices) , samples(that.samples) { this->indices.reserve(this->samples.size()); } // This just stores the heap and the samples. // In operator()() below, if we are adding a new sample // to the sample cache, we force all the // tail_variates to update also. (It's not // good enough to wait for the accumulator_set to do it // for us because then information about whether a sample // was stored and where is lost, and would need to be // queried at runtime, which would be slow.) This is // implemented as a filtered visitation over the stats, // which we can access because args[accumulator] gives us // all the stats. template void operator ()(Args const &args) { if(this->indices.size() < this->samples.size()) { this->indices.push_back(this->indices.size()); this->assign(args, this->indices.back()); } else if(predicate_type()(args[sample], this->samples[this->indices[0]])) { std::pop_heap(this->indices.begin(), this->indices.end(), indirect_cmp(this->samples)); this->assign(args, this->indices.back()); } } result_type result(dont_care) const { if(!this->is_sorted) { // Must use the same predicate here as in push_heap/pop_heap above. std::sort_heap(this->indices.begin(), this->indices.end(), indirect_cmp(this->samples)); // sort_heap puts elements in reverse order. Calling std::reverse // turns the sorted sequence back into a valid heap. std::reverse(this->indices.begin(), this->indices.end()); this->is_sorted = true; } return detail::make_tail_range( this->samples.begin() , this->indices.begin() , this->indices.end() ); } private: struct is_tail_variate { template struct apply : detail::is_tail_variate_feature< typename detail::feature_tag::type , LeftRight > {}; }; template void assign(Args const &args, std::size_t index) { BOOST_ASSERT(index < this->samples.size()); this->samples[index] = args[sample]; std::push_heap(this->indices.begin(), this->indices.end(), indirect_cmp(this->samples)); this->is_sorted = false; // Tell the tail variates to store their values also args[accumulator].template visit_if(detail::stat_assign(args, index)); } /////////////////////////////////////////////////////////////////////////////// // struct indirect_cmp : std::binary_function { indirect_cmp(std::vector const &samples) : samples(samples) { } bool operator ()(std::size_t left, std::size_t right) const { return predicate_type()(this->samples[left], this->samples[right]); } private: indirect_cmp &operator =(indirect_cmp const &); std::vector const &samples; }; mutable bool is_sorted; mutable std::vector indices; std::vector samples; }; } // namespace impl // TODO The templatized tag::tail below should inherit from the correct named parameter. // The following lines provide a workaround, but there must be a better way of doing this. template struct tail_cache_size_named_arg { }; template<> struct tail_cache_size_named_arg : tag::left_tail_cache_size { }; template<> struct tail_cache_size_named_arg : tag::right_tail_cache_size { }; /////////////////////////////////////////////////////////////////////////////// // tag::tail<> // namespace tag { template struct tail : depends_on<> , tail_cache_size_named_arg { /// INTERNAL ONLY /// typedef accumulators::impl::tail_impl impl; #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED /// tag::tail::cache_size named parameter static boost::parameter::keyword > const cache_size; #endif }; struct abstract_tail : depends_on<> { }; } /////////////////////////////////////////////////////////////////////////////// // extract::tail // namespace extract { extractor const tail = {}; } using extract::tail; template struct feature_of > : feature_of { }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/tail_mean.hpp000644 000000 000000 00000020774 11124251706 023154 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // tail_mean.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_TAIL_MEAN_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_TAIL_MEAN_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #ifdef _MSC_VER # pragma warning(push) # pragma warning(disable: 4127) // conditional expression is constant #endif namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // coherent_tail_mean_impl // /** @brief Estimation of the coherent tail mean based on order statistics (for both left and right tails) The coherent tail mean \f$\widehat{CTM}_{n,\alpha}(X)\f$ is equal to the non-coherent tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$ plus a correction term that ensures coherence in case of non-continuous distributions. \f[ \widehat{CTM}_{n,\alpha}^{\mathrm{right}}(X) = \widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X) + \frac{1}{\lceil n(1-\alpha)\rceil}\hat{q}_{n,\alpha}(X)\left(1 - \alpha - \frac{1}{n}\lceil n(1-\alpha)\rceil \right) \f] \f[ \widehat{CTM}_{n,\alpha}^{\mathrm{left}}(X) = \widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X) + \frac{1}{\lceil n\alpha\rceil}\hat{q}_{n,\alpha}(X)\left(\alpha - \frac{1}{n}\lceil n\alpha\rceil \right) \f] */ template struct coherent_tail_mean_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; // for boost::result_of typedef float_type result_type; coherent_tail_mean_impl(dont_care) {} template result_type result(Args const &args) const { std::size_t cnt = count(args); std::size_t n = static_cast( std::ceil( cnt * ( ( is_same::value ) ? args[quantile_probability] : 1. - args[quantile_probability] ) ) ); extractor > const some_non_coherent_tail_mean = {}; return some_non_coherent_tail_mean(args) + numeric::average(quantile(args), n) * ( ( is_same::value ) ? args[quantile_probability] : 1. - args[quantile_probability] - numeric::average(n, count(args)) ); } }; /////////////////////////////////////////////////////////////////////////////// // non_coherent_tail_mean_impl // /** @brief Estimation of the (non-coherent) tail mean based on order statistics (for both left and right tails) An estimation of the non-coherent tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$ is given by the mean of the \f$\lceil n\alpha\rceil\f$ smallest samples (left tail) or the mean of the \f$\lceil n(1-\alpha)\rceil\f$ largest samples (right tail), \f$n\f$ being the total number of samples and \f$\alpha\f$ the quantile level: \f[ \widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X) = \frac{1}{\lceil n(1-\alpha)\rceil} \sum_{i=\lceil \alpha n \rceil}^n X_{i:n} \f] \f[ \widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X) = \frac{1}{\lceil n\alpha\rceil} \sum_{i=1}^{\lceil \alpha n \rceil} X_{i:n} \f] It thus requires the caching of at least the \f$\lceil n\alpha\rceil\f$ smallest or the \f$\lceil n(1-\alpha)\rceil\f$ largest samples. @param quantile_probability */ template struct non_coherent_tail_mean_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; // for boost::result_of typedef float_type result_type; non_coherent_tail_mean_impl(dont_care) {} template result_type result(Args const &args) const { std::size_t cnt = count(args); std::size_t n = static_cast( std::ceil( cnt * ( ( is_same::value ) ? args[quantile_probability] : 1. - args[quantile_probability] ) ) ); // If n is in a valid range, return result, otherwise return NaN or throw exception if (n <= static_cast(tail(args).size())) return numeric::average( std::accumulate( tail(args).begin() , tail(args).begin() + n , Sample(0) ) , n ); else { if (std::numeric_limits::has_quiet_NaN) { return std::numeric_limits::quiet_NaN(); } else { std::ostringstream msg; msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")"; boost::throw_exception(std::runtime_error(msg.str())); return Sample(0); } } } }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::coherent_tail_mean<> // tag::non_coherent_tail_mean<> // namespace tag { template struct coherent_tail_mean : depends_on > { typedef accumulators::impl::coherent_tail_mean_impl impl; }; template struct non_coherent_tail_mean : depends_on > { typedef accumulators::impl::non_coherent_tail_mean_impl impl; }; struct abstract_non_coherent_tail_mean : depends_on<> { }; } /////////////////////////////////////////////////////////////////////////////// // extract::non_coherent_tail_mean; // extract::coherent_tail_mean; // namespace extract { extractor const non_coherent_tail_mean = {}; extractor const coherent_tail_mean = {}; } using extract::non_coherent_tail_mean; using extract::coherent_tail_mean; // for the purposes of feature-based dependency resolution, // coherent_tail_mean provides the same feature as tail_mean template struct feature_of > : feature_of { }; template struct feature_of > : feature_of { }; // So that non_coherent_tail_mean can be automatically substituted // with weighted_non_coherent_tail_mean when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::non_coherent_weighted_tail_mean type; }; template struct feature_of > : feature_of > {}; // NOTE that non_coherent_tail_mean cannot be feature-grouped with tail_mean, // which is the base feature for coherent tail means, since (at least for // non-continuous distributions) non_coherent_tail_mean is a different measure! }} // namespace boost::accumulators #ifdef _MSC_VER # pragma warning(pop) #endif #endif include/boost/accumulators/statistics/tail_quantile.hpp000644 000000 000000 00000012242 11124251706 024045 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // tail_quantile.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_TAIL_QUANTILE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_TAIL_QUANTILE_HPP_DE_01_01_2006 #include #include #include #include #include #include // For ceil #include #include #include #include #include #include #include #include #include #include #include #include #include #include #ifdef _MSC_VER # pragma warning(push) # pragma warning(disable: 4127) // conditional expression is constant #endif namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // tail_quantile_impl // Tail quantile estimation based on order statistics /** @brief Tail quantile estimation based on order statistics (for both left and right tails) The estimation of a tail quantile \f$\hat{q}\f$ with level \f$\alpha\f$ based on order statistics requires the chaching of at least the \f$\lceil n\alpha\rceil\f$ smallest or the \f$\lceil n(1-\alpha)\rceil\f$ largest samples, \f$n\f$ being the total number of samples. The largest of the \f$\lceil n\alpha\rceil\f$ smallest samples or the smallest of the \f$\lceil n(1-\alpha)\rceil\f$ largest samples provides an estimate for the quantile: \f[ \hat{q}_{n,\alpha} = X_{\lceil \alpha n \rceil:n} \f] @param quantile_probability */ template struct tail_quantile_impl : accumulator_base { // for boost::result_of typedef Sample result_type; tail_quantile_impl(dont_care) {} template result_type result(Args const &args) const { std::size_t cnt = count(args); std::size_t n = static_cast( std::ceil( cnt * ( ( is_same::value ) ? args[quantile_probability] : 1. - args[quantile_probability] ) ) ); // If n is in a valid range, return result, otherwise return NaN or throw exception if ( n < static_cast(tail(args).size())) { // Note that the cached samples of the left are sorted in ascending order, // whereas the samples of the right tail are sorted in descending order return *(boost::begin(tail(args)) + n - 1); } else { if (std::numeric_limits::has_quiet_NaN) { return std::numeric_limits::quiet_NaN(); } else { std::ostringstream msg; msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")"; boost::throw_exception(std::runtime_error(msg.str())); return Sample(0); } } } }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::tail_quantile<> // namespace tag { template struct tail_quantile : depends_on > { /// INTERNAL ONLY /// typedef accumulators::impl::tail_quantile_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::tail_quantile // namespace extract { extractor const tail_quantile = {}; } using extract::tail_quantile; // for the purposes of feature-based dependency resolution, // tail_quantile provide the same feature as quantile template struct feature_of > : feature_of { }; // So that tail_quantile can be automatically substituted with // weighted_tail_quantile when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::weighted_tail_quantile type; }; template struct feature_of > : feature_of > {}; }} // namespace boost::accumulators #ifdef _MSC_VER # pragma warning(pop) #endif #endif include/boost/accumulators/statistics/tail_variate.hpp000644 000000 000000 00000010064 11124251706 023656 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // tail_variate.hpp // // Copyright 2005 Eric Niebler, Michael Gauckler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_STAT_STATISTICS_TAIL_VARIATE_HPP_EAN_28_10_2005 #define BOOST_STAT_STATISTICS_TAIL_VARIATE_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // tail_variate_impl template struct tail_variate_impl : accumulator_base { // for boost::result_of typedef typename detail::tail_range< typename std::vector::const_iterator , std::vector::iterator >::type result_type; template tail_variate_impl(Args const &args) : variates(args[tag::tail::cache_size], args[parameter::keyword::get() | VariateType()]) { } template void assign(Args const &args, std::size_t index) { this->variates[index] = args[parameter::keyword::get()]; } template result_type result(Args const &args) const { // getting the order result causes the indices vector to be sorted. extractor > const some_tail = {}; return this->do_result(some_tail(args)); } private: template result_type do_result(TailRng const &rng) const { return detail::make_tail_range( this->variates.begin() , rng.end().base().base() // the index iterator , rng.begin().base().base() // (begin and end reversed because these are reverse iterators) ); } std::vector variates; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::tail_variate<> // namespace tag { template struct tail_variate : depends_on > { /// INTERNAL ONLY /// typedef mpl::always > impl; }; struct abstract_tail_variate : depends_on<> { }; template struct tail_weights : depends_on > { /// INTERNAL ONLY /// typedef accumulators::impl::tail_variate_impl impl; }; struct abstract_tail_weights : depends_on<> { }; } /////////////////////////////////////////////////////////////////////////////// // extract::tail_variate // extract::tail_weights // namespace extract { extractor const tail_variate = {}; extractor const tail_weights = {}; } using extract::tail_variate; using extract::tail_weights; template struct feature_of > : feature_of { }; template struct feature_of > { typedef tag::abstract_tail_weights type; }; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/tail_variate_means.hpp000644 000000 000000 00000023357 11124251706 025052 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // tail_variate_means.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_TAIL_VARIATE_MEANS_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_TAIL_VARIATE_MEANS_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #ifdef _MSC_VER # pragma warning(push) # pragma warning(disable: 4127) // conditional expression is constant #endif namespace boost { namespace accumulators { namespace impl { /** @brief Estimation of the absolute and relative tail variate means (for both left and right tails) For all \f$j\f$-th variates associated to the \f$\lceil n(1-\alpha)\rceil\f$ largest samples (or the \f$\lceil n(1-\alpha)\rceil\f$ smallest samples in case of the left tail), the absolute tail means \f$\widehat{ATM}_{n,\alpha}(X, j)\f$ are computed and returned as an iterator range. Alternatively, the relative tail means \f$\widehat{RTM}_{n,\alpha}(X, j)\f$ are returned, which are the absolute tail means normalized with the (non-coherent) sample tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$. \f[ \widehat{ATM}_{n,\alpha}^{\mathrm{right}}(X, j) = \frac{1}{\lceil n(1-\alpha) \rceil} \sum_{i=\lceil \alpha n \rceil}^n \xi_{j,i} \f] \f[ \widehat{ATM}_{n,\alpha}^{\mathrm{left}}(X, j) = \frac{1}{\lceil n\alpha \rceil} \sum_{i=1}^{\lceil n\alpha \rceil} \xi_{j,i} \f] \f[ \widehat{RTM}_{n,\alpha}^{\mathrm{right}}(X, j) = \frac{\sum_{i=\lceil n\alpha \rceil}^n \xi_{j,i}} {\lceil n(1-\alpha)\rceil\widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X)} \f] \f[ \widehat{RTM}_{n,\alpha}^{\mathrm{left}}(X, j) = \frac{\sum_{i=1}^{\lceil n\alpha \rceil} \xi_{j,i}} {\lceil n\alpha\rceil\widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X)} \f] */ /////////////////////////////////////////////////////////////////////////////// // tail_variate_means_impl // by default: absolute tail_variate_means template struct tail_variate_means_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef std::vector array_type; // for boost::result_of typedef iterator_range result_type; tail_variate_means_impl(dont_care) {} template result_type result(Args const &args) const { std::size_t cnt = count(args); std::size_t n = static_cast( std::ceil( cnt * ( ( is_same::value ) ? args[quantile_probability] : 1. - args[quantile_probability] ) ) ); std::size_t num_variates = tail_variate(args).begin()->size(); this->tail_means_.clear(); this->tail_means_.resize(num_variates, Sample(0)); // If n is in a valid range, return result, otherwise return NaN or throw exception if (n < static_cast(tail(args).size())) { this->tail_means_ = std::accumulate( tail_variate(args).begin() , tail_variate(args).begin() + n , this->tail_means_ , numeric::plus ); float_type factor = n * ( (is_same::value) ? non_coherent_tail_mean(args) : 1. ); std::transform( this->tail_means_.begin() , this->tail_means_.end() , this->tail_means_.begin() , std::bind2nd(std::divides(), factor) ); } else { if (std::numeric_limits::has_quiet_NaN) { std::fill( this->tail_means_.begin() , this->tail_means_.end() , std::numeric_limits::quiet_NaN() ); } else { std::ostringstream msg; msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")"; boost::throw_exception(std::runtime_error(msg.str())); } } return make_iterator_range(this->tail_means_); } private: mutable array_type tail_means_; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::absolute_tail_variate_means // tag::relative_tail_variate_means // namespace tag { template struct absolute_tail_variate_means : depends_on, tail_variate > { typedef accumulators::impl::tail_variate_means_impl impl; }; template struct relative_tail_variate_means : depends_on, tail_variate > { typedef accumulators::impl::tail_variate_means_impl impl; }; struct abstract_absolute_tail_variate_means : depends_on<> { }; struct abstract_relative_tail_variate_means : depends_on<> { }; } /////////////////////////////////////////////////////////////////////////////// // extract::tail_variate_means // extract::relative_tail_variate_means // namespace extract { extractor const tail_variate_means = {}; extractor const relative_tail_variate_means = {}; } using extract::tail_variate_means; using extract::relative_tail_variate_means; // tail_variate_means(absolute) -> absolute_tail_variate_means template struct as_feature(absolute)> { typedef tag::absolute_tail_variate_means type; }; // tail_variate_means(relative) ->relative_tail_variate_means template struct as_feature(relative)> { typedef tag::relative_tail_variate_means type; }; // Provides non-templatized extractor template struct feature_of > : feature_of { }; // Provides non-templatized extractor template struct feature_of > : feature_of { }; // So that absolute_tail_means can be automatically substituted // with absolute_weighted_tail_means when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::absolute_weighted_tail_variate_means type; }; template struct feature_of > : feature_of > { }; // So that relative_tail_means can be automatically substituted // with relative_weighted_tail_means when the weight parameter is non-void. template struct as_weighted_feature > { typedef tag::relative_weighted_tail_variate_means type; }; template struct feature_of > : feature_of > { }; }} // namespace boost::accumulators #ifdef _MSC_VER # pragma warning(pop) #endif #endif include/boost/accumulators/statistics/times2_iterator.hpp000644 000000 000000 00000003114 11124251705 024323 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // times2_iterator.hpp // // Copyright 2006 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_TIMES2_ITERATOR_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_TIMES2_ITERATOR_HPP_DE_01_01_2006 #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace detail { typedef transform_iterator< std::binder1st > , counting_iterator > times2_iterator; inline times2_iterator make_times2_iterator(std::size_t i) { return make_transform_iterator( make_counting_iterator(i) , std::bind1st(std::multiplies(), 2) ); } /////////////////////////////////////////////////////////////////////////////// // lvalue_index_iterator template struct lvalue_index_iterator : Base { lvalue_index_iterator(Base base) : Base(base) { } typename Base::reference operator [](typename Base::difference_type n) const { return *(*this + n); } }; } // namespace detail }} #endif include/boost/accumulators/statistics/variance.hpp000644 000000 000000 00000015610 11124251707 023005 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // variance.hpp // // Copyright 2005 Daniel Egloff, Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_VARIANCE_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_VARIANCE_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { //! Lazy calculation of variance. /*! Default sample variance implementation based on the second moment \f$ M_n^{(2)} \f$ moment<2>, mean and count. \f[ \sigma_n^2 = M_n^{(2)} - \mu_n^2. \f] where \f[ \mu_n = \frac{1}{n} \sum_{i = 1}^n x_i. \f] is the estimate of the sample mean and \f$n\f$ is the number of samples. */ template struct lazy_variance_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::average::result_type result_type; lazy_variance_impl(dont_care) {} template result_type result(Args const &args) const { extractor mean; result_type tmp = mean(args); return moment<2>(args) - tmp * tmp; } }; //! Iterative calculation of variance. /*! Iterative calculation of sample variance \f$\sigma_n^2\f$ according to the formula \f[ \sigma_n^2 = \frac{1}{n} \sum_{i = 1}^n (x_i - \mu_n)^2 = \frac{n-1}{n} \sigma_{n-1}^2 + \frac{1}{n-1}(x_n - \mu_n)^2. \f] where \f[ \mu_n = \frac{1}{n} \sum_{i = 1}^n x_i. \f] is the estimate of the sample mean and \f$n\f$ is the number of samples. Note that the sample variance is not defined for \f$n <= 1\f$. A simplification can be obtained by the approximate recursion \f[ \sigma_n^2 \approx \frac{n-1}{n} \sigma_{n-1}^2 + \frac{1}{n}(x_n - \mu_n)^2. \f] because the difference \f[ \left(\frac{1}{n-1} - \frac{1}{n}\right)(x_n - \mu_n)^2 = \frac{1}{n(n-1)}(x_n - \mu_n)^2. \f] converges to zero as \f$n \rightarrow \infty\f$. However, for small \f$ n \f$ the difference can be non-negligible. */ template struct variance_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::average::result_type result_type; template variance_impl(Args const &args) : variance(numeric::average(args[sample | Sample()], numeric::one::value)) { } template void operator ()(Args const &args) { std::size_t cnt = count(args); if(cnt > 1) { extractor mean; result_type tmp = args[parameter::keyword::get()] - mean(args); this->variance = numeric::average(this->variance * (cnt - 1), cnt) + numeric::average(tmp * tmp, cnt - 1); } } result_type result(dont_care) const { return this->variance; } private: result_type variance; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::variance // tag::immediate_variance // namespace tag { struct lazy_variance : depends_on, mean> { /// INTERNAL ONLY /// typedef accumulators::impl::lazy_variance_impl impl; }; struct variance : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::variance_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::lazy_variance // extract::variance // namespace extract { extractor const lazy_variance = {}; extractor const variance = {}; } using extract::lazy_variance; using extract::variance; // variance(lazy) -> lazy_variance template<> struct as_feature { typedef tag::lazy_variance type; }; // variance(immediate) -> variance template<> struct as_feature { typedef tag::variance type; }; // for the purposes of feature-based dependency resolution, // immediate_variance provides the same feature as variance template<> struct feature_of : feature_of { }; // So that variance can be automatically substituted with // weighted_variance when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::weighted_variance type; }; // for the purposes of feature-based dependency resolution, // weighted_variance provides the same feature as variance template<> struct feature_of : feature_of { }; // So that immediate_variance can be automatically substituted with // immediate_weighted_variance when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::lazy_weighted_variance type; }; // for the purposes of feature-based dependency resolution, // immediate_weighted_variance provides the same feature as immediate_variance template<> struct feature_of : feature_of { }; //////////////////////////////////////////////////////////////////////////// //// droppable_accumulator //// need to specialize droppable lazy variance to cache the result at the //// point the accumulator is dropped. ///// INTERNAL ONLY ///// //template //struct droppable_accumulator > // : droppable_accumulator_base< // with_cached_result > // > //{ // template // droppable_accumulator(Args const &args) // : droppable_accumulator::base(args) // { // } //}; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/variates/covariate.hpp000644 000000 000000 00000001212 11124251216 024774 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // weight.hpp // // Copyright 2005 Eric Niebler. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_VARIATES_COVARIATE_HPP_EAN_03_11_2005 #define BOOST_ACCUMULATORS_STATISTICS_VARIATES_COVARIATE_HPP_EAN_03_11_2005 #include namespace boost { namespace accumulators { BOOST_PARAMETER_KEYWORD(tag, covariate1) BOOST_PARAMETER_KEYWORD(tag, covariate2) }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/weighted_covariance.hpp000644 000000 000000 00000011613 11124251705 025204 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // weighted_covariance.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_COVARIANCE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_COVARIANCE_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include // for numeric::outer_product() and type traits #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // weighted_covariance_impl // /** @brief Weighted Covariance Estimator An iterative Monte Carlo estimator for the weighted covariance \f$\mathrm{Cov}(X,X')\f$, where \f$X\f$ is a sample and \f$X'\f$ a variate, is given by: \f[ \hat{c}_n = \frac{\bar{w}_n-w_n}{\bar{w}_n} \hat{c}_{n-1} + \frac{w_n}{\bar{w}_n-w_n}(X_n - \hat{\mu}_n)(X_n' - \hat{\mu}_n'), \quad n\ge2,\quad\hat{c}_1 = 0, \f] \f$\hat{\mu}_n\f$ and \f$\hat{\mu}_n'\f$ being the weighted means of the samples and variates and \f$\bar{w}_n\f$ the sum of the \f$n\f$ first weights \f$w_i\f$. */ template struct weighted_covariance_impl : accumulator_base { typedef typename numeric::functional::multiplies::result_type>::result_type weighted_sample_type; typedef typename numeric::functional::multiplies::result_type>::result_type weighted_variate_type; // for boost::result_of typedef typename numeric::functional::outer_product::result_type result_type; template weighted_covariance_impl(Args const &args) : cov_( numeric::outer_product( numeric::average(args[sample | Sample()], (std::size_t)1) * numeric::one::value , numeric::average(args[parameter::keyword::get() | VariateType()], (std::size_t)1) * numeric::one::value ) ) { } template void operator ()(Args const &args) { std::size_t cnt = count(args); if (cnt > 1) { extractor > const some_weighted_mean_of_variates = {}; this->cov_ = this->cov_ * (sum_of_weights(args) - args[weight]) / sum_of_weights(args) + numeric::outer_product( some_weighted_mean_of_variates(args) - args[parameter::keyword::get()] , weighted_mean(args) - args[sample] ) * args[weight] / (sum_of_weights(args) - args[weight]); } } result_type result(dont_care) const { return this->cov_; } private: result_type cov_; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::weighted_covariance // namespace tag { template struct weighted_covariance : depends_on > { typedef accumulators::impl::weighted_covariance_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::weighted_covariance // namespace extract { extractor const weighted_covariance = {}; } using extract::weighted_covariance; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/weighted_density.hpp000644 000000 000000 00000021367 11124251705 024560 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // weighted_density.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_DENSITY_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_DENSITY_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include // for named parameters density_cache_size and density_num_bins namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // weighted_density_impl // density histogram for weighted samples /** @brief Histogram density estimator for weighted samples The histogram density estimator returns a histogram of the sample distribution. The positions and sizes of the bins are determined using a specifiable number of cached samples (cache_size). The range between the minimum and the maximum of the cached samples is subdivided into a specifiable number of bins (num_bins) of same size. Additionally, an under- and an overflow bin is added to capture future under- and overflow samples. Once the bins are determined, the cached samples and all subsequent samples are added to the correct bins. At the end, a range of std::pair is returned, where each pair contains the position of the bin (lower bound) and the sum of the weights (normalized with the sum of all weights). @param density_cache_size Number of first samples used to determine min and max. @param density_num_bins Number of bins (two additional bins collect under- and overflow samples). */ template struct weighted_density_impl : accumulator_base { typedef typename numeric::functional::average::result_type float_type; typedef std::vector > histogram_type; typedef std::vector array_type; // for boost::result_of typedef iterator_range result_type; template weighted_density_impl(Args const &args) : cache_size(args[density_cache_size]) , cache(cache_size) , num_bins(args[density_num_bins]) , samples_in_bin(num_bins + 2, 0.) , bin_positions(num_bins + 2) , histogram( num_bins + 2 , std::make_pair( numeric::average(args[sample | Sample()],(std::size_t)1) , numeric::average(args[sample | Sample()],(std::size_t)1) ) ) , is_dirty(true) { } template void operator ()(Args const &args) { this->is_dirty = true; std::size_t cnt = count(args); // Fill up cache with cache_size first samples if (cnt <= this->cache_size) { this->cache[cnt - 1] = std::make_pair(args[sample], args[weight]); } // Once cache_size samples have been accumulated, create num_bins bins of same size between // the minimum and maximum of the cached samples as well as an under- and an overflow bin. // Store their lower bounds (bin_positions) and fill the bins with the cached samples (samples_in_bin). if (cnt == this->cache_size) { float_type minimum = numeric::average((min)(args),(std::size_t)1); float_type maximum = numeric::average((max)(args),(std::size_t)1); float_type bin_size = numeric::average(maximum - minimum, this->num_bins); // determine bin positions (their lower bounds) for (std::size_t i = 0; i < this->num_bins + 2; ++i) { this->bin_positions[i] = minimum + (i - 1.) * bin_size; } for (typename histogram_type::const_iterator iter = this->cache.begin(); iter != this->cache.end(); ++iter) { if (iter->first < this->bin_positions[1]) { this->samples_in_bin[0] += iter->second; } else if (iter->first >= this->bin_positions[this->num_bins + 1]) { this->samples_in_bin[this->num_bins + 1] += iter->second; } else { typename array_type::iterator it = std::upper_bound( this->bin_positions.begin() , this->bin_positions.end() , iter->first ); std::size_t d = std::distance(this->bin_positions.begin(), it); this->samples_in_bin[d - 1] += iter->second; } } } // Add each subsequent sample to the correct bin else if (cnt > this->cache_size) { if (args[sample] < this->bin_positions[1]) { this->samples_in_bin[0] += args[weight]; } else if (args[sample] >= this->bin_positions[this->num_bins + 1]) { this->samples_in_bin[this->num_bins + 1] += args[weight]; } else { typename array_type::iterator it = std::upper_bound( this->bin_positions.begin() , this->bin_positions.end() , args[sample] ); std::size_t d = std::distance(this->bin_positions.begin(), it); this->samples_in_bin[d - 1] += args[weight]; } } } template result_type result(Args const &args) const { if (this->is_dirty) { this->is_dirty = false; // creates a vector of std::pair where each pair i holds // the values bin_positions[i] (x-axis of histogram) and // samples_in_bin[i] / cnt (y-axis of histogram). for (std::size_t i = 0; i < this->num_bins + 2; ++i) { this->histogram[i] = std::make_pair(this->bin_positions[i], numeric::average(this->samples_in_bin[i], sum_of_weights(args))); } } // returns a range of pairs return make_iterator_range(this->histogram); } private: std::size_t cache_size; // number of cached samples histogram_type cache; // cache to store the first cache_size samples with their weights as std::pair std::size_t num_bins; // number of bins array_type samples_in_bin; // number of samples in each bin array_type bin_positions; // lower bounds of bins mutable histogram_type histogram; // histogram mutable bool is_dirty; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::weighted_density // namespace tag { struct weighted_density : depends_on , density_cache_size , density_num_bins { /// INTERNAL ONLY /// typedef accumulators::impl::weighted_density_impl impl; #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED static boost::parameter::keyword const cache_size; static boost::parameter::keyword const num_bins; #endif }; } /////////////////////////////////////////////////////////////////////////////// // extract::weighted_density // namespace extract { extractor const weighted_density = {}; } using extract::weighted_density; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/weighted_extended_p_square.hpp000644 000000 000000 00000030067 11124251707 026577 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // weighted_extended_p_square.hpp // // Copyright 2005 Daniel Egloff. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_EXTENDED_P_SQUARE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_EXTENDED_P_SQUARE_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // weighted_extended_p_square_impl // multiple quantile estimation with weighted samples /** @brief Multiple quantile estimation with the extended \f$P^2\f$ algorithm for weighted samples This version of the extended \f$P^2\f$ algorithm extends the extended \f$P^2\f$ algorithm to support weighted samples. The extended \f$P^2\f$ algorithm dynamically estimates several quantiles without storing samples. Assume that \f$m\f$ quantiles \f$\xi_{p_1}, \ldots, \xi_{p_m}\f$ are to be estimated. Instead of storing the whole sample cumulative distribution, the algorithm maintains only \f$m+2\f$ principal markers and \f$m+1\f$ middle markers, whose positions are updated with each sample and whose heights are adjusted (if necessary) using a piecewise-parablic formula. The heights of the principal markers are the current estimates of the quantiles and are returned as an iterator range. For further details, see K. E. E. Raatikainen, Simultaneous estimation of several quantiles, Simulation, Volume 49, Number 4 (October), 1986, p. 159-164. The extended \f$ P^2 \f$ algorithm generalizess the \f$ P^2 \f$ algorithm of R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and histograms without storing observations, Communications of the ACM, Volume 28 (October), Number 10, 1985, p. 1076-1085. @param extended_p_square_probabilities A vector of quantile probabilities. */ template struct weighted_extended_p_square_impl : accumulator_base { typedef typename numeric::functional::multiplies::result_type weighted_sample; typedef typename numeric::functional::average::result_type float_type; typedef std::vector array_type; // for boost::result_of typedef iterator_range< detail::lvalue_index_iterator< permutation_iterator< typename array_type::const_iterator , detail::times2_iterator > > > result_type; template weighted_extended_p_square_impl(Args const &args) : probabilities( boost::begin(args[extended_p_square_probabilities]) , boost::end(args[extended_p_square_probabilities]) ) , heights(2 * probabilities.size() + 3) , actual_positions(heights.size()) , desired_positions(heights.size()) { } template void operator ()(Args const &args) { std::size_t cnt = count(args); std::size_t sample_cell = 1; // k std::size_t num_quantiles = this->probabilities.size(); // m+2 principal markers and m+1 middle markers std::size_t num_markers = 2 * num_quantiles + 3; // first accumulate num_markers samples if(cnt <= num_markers) { this->heights[cnt - 1] = args[sample]; this->actual_positions[cnt - 1] = args[weight]; // complete the initialization of heights (and actual_positions) by sorting if(cnt == num_markers) { // TODO: we need to sort the initial samples (in heights) in ascending order and // sort their weights (in actual_positions) the same way. The following lines do // it, but there must be a better and more efficient way of doing this. typename array_type::iterator it_begin, it_end, it_min; it_begin = this->heights.begin(); it_end = this->heights.end(); std::size_t pos = 0; while (it_begin != it_end) { it_min = std::min_element(it_begin, it_end); std::size_t d = std::distance(it_begin, it_min); std::swap(*it_begin, *it_min); std::swap(this->actual_positions[pos], this->actual_positions[pos + d]); ++it_begin; ++pos; } // calculate correct initial actual positions for (std::size_t i = 1; i < num_markers; ++i) { actual_positions[i] += actual_positions[i - 1]; } } } else { if(args[sample] < this->heights[0]) { this->heights[0] = args[sample]; this->actual_positions[0] = args[weight]; sample_cell = 1; } else if(args[sample] >= this->heights[num_markers - 1]) { this->heights[num_markers - 1] = args[sample]; sample_cell = num_markers - 1; } else { // find cell k = sample_cell such that heights[k-1] <= sample < heights[k] typedef typename array_type::iterator iterator; iterator it = std::upper_bound( this->heights.begin() , this->heights.end() , args[sample] ); sample_cell = std::distance(this->heights.begin(), it); } // update actual position of all markers above sample_cell for(std::size_t i = sample_cell; i < num_markers; ++i) { this->actual_positions[i] += args[weight]; } // compute desired positions { this->desired_positions[0] = this->actual_positions[0]; this->desired_positions[num_markers - 1] = sum_of_weights(args); this->desired_positions[1] = (sum_of_weights(args) - this->actual_positions[0]) * probabilities[0] / 2. + this->actual_positions[0]; this->desired_positions[num_markers - 2] = (sum_of_weights(args) - this->actual_positions[0]) * (probabilities[num_quantiles - 1] + 1.) / 2. + this->actual_positions[0]; for (std::size_t i = 0; i < num_quantiles; ++i) { this->desired_positions[2 * i + 2] = (sum_of_weights(args) - this->actual_positions[0]) * probabilities[i] + this->actual_positions[0]; } for (std::size_t i = 1; i < num_quantiles; ++i) { this->desired_positions[2 * i + 1] = (sum_of_weights(args) - this->actual_positions[0]) * (probabilities[i - 1] + probabilities[i]) / 2. + this->actual_positions[0]; } } // adjust heights and actual_positions of markers 1 to num_markers - 2 if necessary for (std::size_t i = 1; i <= num_markers - 2; ++i) { // offset to desired position float_type d = this->desired_positions[i] - this->actual_positions[i]; // offset to next position float_type dp = this->actual_positions[i + 1] - this->actual_positions[i]; // offset to previous position float_type dm = this->actual_positions[i - 1] - this->actual_positions[i]; // height ds float_type hp = (this->heights[i + 1] - this->heights[i]) / dp; float_type hm = (this->heights[i - 1] - this->heights[i]) / dm; if((d >= 1 && dp > 1) || (d <= -1 && dm < -1)) { short sign_d = static_cast(d / std::abs(d)); float_type h = this->heights[i] + sign_d / (dp - dm) * ((sign_d - dm)*hp + (dp - sign_d) * hm); // try adjusting heights[i] using p-squared formula if(this->heights[i - 1] < h && h < this->heights[i + 1]) { this->heights[i] = h; } else { // use linear formula if(d > 0) { this->heights[i] += hp; } if(d < 0) { this->heights[i] -= hm; } } this->actual_positions[i] += sign_d; } } } } result_type result(dont_care) const { // for i in [1,probabilities.size()], return heights[i * 2] detail::times2_iterator idx_begin = detail::make_times2_iterator(1); detail::times2_iterator idx_end = detail::make_times2_iterator(this->probabilities.size() + 1); return result_type( make_permutation_iterator(this->heights.begin(), idx_begin) , make_permutation_iterator(this->heights.begin(), idx_end) ); } private: array_type probabilities; // the quantile probabilities array_type heights; // q_i array_type actual_positions; // n_i array_type desired_positions; // d_i }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::weighted_extended_p_square // namespace tag { struct weighted_extended_p_square : depends_on , extended_p_square_probabilities { typedef accumulators::impl::weighted_extended_p_square_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::weighted_extended_p_square // namespace extract { extractor const weighted_extended_p_square = {}; } using extract::weighted_extended_p_square; }} // namespace boost::accumulators #endif include/boost/accumulators/statistics/weighted_kurtosis.hpp000644 000000 000000 00000007672 11124251707 024771 0ustar00rootroot000000 000000 /////////////////////////////////////////////////////////////////////////////// // weighted_kurtosis.hpp // // Copyright 2006 Olivier Gygi, Daniel Egloff. Distributed under the Boost // Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_KURTOSIS_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_KURTOSIS_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // weighted_kurtosis_impl /** @brief Kurtosis estimation for weighted samples The kurtosis of a sample distribution is defined as the ratio of the 4th central moment and the square of the 2nd central moment (the variance) of the samples, minus 3. The term \f$ -3 \f$ is added in order to ensure that the normal distribution has zero kurtosis. The kurtosis can also be expressed by the simple moments: \f[ \hat{g}_2 = \frac {\widehat{m}_n^{(4)}-4\widehat{m}_n^{(3)}\hat{\mu}_n+6\widehat{m}_n^{(2)}\hat{\mu}_n^2-3\hat{\mu}_n^4} {\left(\widehat{m}_n^{(2)} - \hat{\mu}_n^{2}\right)^2} - 3, \f] where \f$ \widehat{m}_n^{(i)} \f$ are the \f$ i \f$-th moment and \f$ \hat{\mu}_n \f$ the mean (first moment) of the \f$ n \f$ samples. The kurtosis estimator for weighted samples is formally identical to the estimator for unweighted samples, except that the weighted counterparts of all measures it depends on are to be taken. */ template struct weighted_kurtosis_impl : accumulator_base { typedef typename numeric::functional::multiplies::result_type weighted_sample; // for boost::result_of typedef typename numeric::functional::average::result_type result_type; weighted_kurtosis_impl(dont_care) { } template result_type result(Args const &args) const { return numeric::average( weighted_moment<4>(args) - 4. * weighted_moment<3>(args) * weighted_mean(args) + 6. * weighted_moment<2>(args) * weighted_mean(args) * weighted_mean(args) - 3. * weighted_mean(args) * weighted_mean(args) * weighted_mean(args)