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Type 'q()' to quit R. > require("DPQ") Loading required package: DPQ > require("Rmpfr") Loading required package: Rmpfr Loading required package: gmp Attaching package: 'gmp' The following objects are masked from 'package:base': %*%, apply, crossprod, matrix, tcrossprod C code of R package 'Rmpfr': GMP using 64 bits per limb Attaching package: 'Rmpfr' The following object is masked from 'package:gmp': outer The following object is masked from 'package:DPQ': log1mexp The following objects are masked from 'package:stats': dbinom, dgamma, dnbinom, dnorm, dpois, dt, pnorm The following objects are masked from 'package:base': cbind, pmax, pmin, rbind > > source(system.file(package="DPQ", "extraR", "relErr-plots.R", mustWork=TRUE)) Loading required package: sfsmisc Attaching package: 'sfsmisc' The following objects are masked from 'package:gmp': factorize, is.whole > ##-> drawEps.h() , mtextVersion(), ... > (doExtras <- DPQ:::doExtras()) [1] FALSE > (noLdbl <- (.Machine$sizeof.longdouble <= 8)) ## TRUE when --disable-long-double [1] FALSE > options(width = 100, nwarnings = 1e5) > > k1 <- 44300 + (1:800) > p1 <- (63/64) > x <- p1; stopifnot( (1-x)-1 == -x , 1-x == 2^-6 ) > px <- p1 ^ k1 > isNorm <- px >= 2^-1022 # is "normal", i.e., not subnormal > k1 <- k1[isNorm] > px <- px[isNorm] > dput(px,, "digits17") c(1.0154391019094658e-303, 9.9957286594213052e-304, 9.8395453991178462e-304, 9.6858025022566298e-304, 9.5344618381588704e-304, 9.3854858719376382e-304, 9.2388376551886126e-304, 9.0944808168262901e-304, 8.9523795540633802e-304, 8.81249862353114e-304, 8.6748033325384659e-304, 8.5392595304675516e-304, 8.405833600303997e-304, 8.2744924502992464e-304, 8.1452035057633211e-304, 8.0179347009857694e-304, 7.892654471282866e-304, 7.7693317451690711e-304, 7.6479359366508044e-304, 7.528436937640636e-304, 7.4108051104900017e-304, 7.2950112806385953e-304, 7.1810267293786167e-304, 7.0688231867320756e-304, 6.9583728244393874e-304, 6.8496482490575215e-304, 6.7426224951659982e-304, 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9.8154831906675317e-308, 9.6621162658133508e-308, 9.5111456991600184e-308, 9.3625340476106433e-308, 9.216244453116726e-308, 9.0722406335367785e-308, 8.9304868736377661e-308, 8.7909480162371756e-308, 8.6535894534834692e-308, 8.5183771182727905e-308, 8.3852774757997778e-308, 8.254257515240406e-308, 8.1252847415647756e-308, 7.9983271674778251e-308, 7.8733533054859845e-308, 7.7503321600877656e-308, 7.6292332200863951e-308, 7.5100264510225443e-308, 7.3926822877253171e-308, 7.2771716269796092e-308, 7.163465820308053e-308, 7.0515366668657394e-308, 6.9413564064459622e-308, 6.8328977125952446e-308, 6.7261336858359432e-308, 6.6210378469947573e-308, 6.5175841306354638e-308, 6.4157468785942845e-308, 6.315500833616249e-308, 6.2168211330909951e-308, 6.1196833028864483e-308, 6.0240632512788482e-308, 5.9299372629776157e-308, 5.8372819932435903e-308, 5.7460744620991591e-308, 5.6562920486288598e-308, 5.5679124853690338e-308, 5.4809138527851425e-308, 5.3952745738353754e-308, 5.3109734086191969e-308, 5.2279894491095222e-308, 5.1463021139671865e-308, 5.0658911434364491e-308, 4.9867365943202544e-308, 4.9088188350340006e-308, 4.8321185407365938e-308, 4.7566166885375845e-308, 4.6822945527791846e-308, 4.6091337003920103e-308, 4.5371159863233849e-308, 4.4662235490370825e-308, 4.3964388060833778e-308, 4.3277444497383252e-308, 4.2601234427111635e-308, 4.1935590139188015e-308, 4.1280346543263203e-308, 4.0635341128524717e-308, 4.000041392339152e-308, 3.9375407455838524e-308, 3.8760166714341046e-308, 3.8154539109429469e-308, 3.7558374435844633e-308, 3.697152483528456e-308, 3.6393844759733243e-308, 3.5825190935362406e-308, 3.5265422326997369e-308, 3.4714400103138038e-308, 3.4171987601526508e-308, 3.3638050295252652e-308, 3.3112455759389332e-308, 3.2595073638148874e-308, 3.2085775612552798e-308, 3.1584435368606661e-308, 3.1090928565972181e-308, 3.0605132807128865e-308, 3.0126927607017478e-308, 2.9656194363157828e-308, 2.9192816326233486e-308, 2.8736678571136091e-308, 2.8287667968462087e-308, 2.7845673156454869e-308, 2.741058451338526e-308, 2.6982294130363616e-308, 2.6560695784576682e-308, 2.6145684912942676e-308, 2.5737158586177946e-308, 2.5335015483268913e-308, 2.4939155866342835e-308, 2.4549481555931231e-308, 2.4165895906619802e-308, 2.378830378307887e-308, 2.3416611536468261e-308, 2.3050726981210945e-308, 2.2690559372129525e-308, 2.2336019381940003e-308) > dput(px,, "hex") c(0x1.648865267f463p-1007, 0x1.5ef64391e5492p-1007, 0x1.597a6a839db3fp-1007, 0x1.541480d98f3d2p-1007, 0x1.4ec42ed629003p-1007, 0x1.49891e1ad05c3p-1007, 0x1.4462f9a2651acp-1007, 0x1.3f516dbbdb865p-1007, 0x1.3a542804ec184p-1007, 0x1.356ad764d867ep-1007, 0x1.30952c0745064p-1007, 0x1.2bd2d75727f22p-1007, 0x1.27238bf9cb526p-1007, 0x1.2286fdc9e4251p-1007, 0x1.1dfce1d2bc948p-1007, 0x1.1984ee4b71a23p-1007, 0x1.151eda9243dbap-1007, 0x1.10ca5f27facc3p-1007, 0x1.0c8735ab5ae1p-1007, 0x1.085518d4ad758p-1007, 0x1.0433c4715abfbp-1007, 0x1.0022f55f9554bp-1007, 0x1.f844d3142dfebp-1008, 0x1.f063bfc7dd46bp-1008, 0x1.e8a230c8bdd1ap-1008, 0x1.e0ffa8059ada5p-1008, 0x1.d97ba965846efp-1008, 0x1.d215babfee5d3p-1008, 0x1.cacd63d4eea3cp-1008, 0x1.c3a22e459ae93p-1008, 0x1.bc93a58c847d8p-1008, 0x1.b5a156f6526b9p-1008, 0x1.aecad19a7921ep-1008, 0x1.a80fa6540f3d6p-1008, 0x1.a16f67babf006p-1008, 0x1.9ae9aa1bd4046p-1008, 0x1.947e037364b45p-1008, 0x1.8e2c0b6597218p-1008, 0x1.87f35b3800c5p-1008, 0x1.81d38dcb20c1ep-1008, 0x1.7bcc3f93f43eep-1008, 0x1.75dd0e95a46dep-1008, 0x1.70059a5b4ddc3p-1008, 0x1.6a4583f1e0a4cp-1008, 0x1.649c6de219222p-1008, 0x1.5f09fc2a90bdap-1008, 0x1.598dd439e67abp-1008, 0x1.54279ce8fee0cp-1008, 0x1.4ed6fe755ae54p-1008, 0x1.499ba27b8579ap-1008, 0x1.447533f19763cp-1008, 0x1.3f635f21d1063p-1008, 0x1.3a65d1a549c21p-1008, 0x1.357c3a5eb49b1p-1008, 0x1.30a6497539c8ap-1008, 0x1.2be3b04f64e18p-1008, 0x1.2734218e274ep-1008, 0x1.22975107eeb0cp-1008, 0x1.1e0cf3c3cef6p-1008, 0x1.1994bff4bfba2p-1008, 0x1.152e6cf4ecbb4p-1008, 0x1.10d9b34119085p-1008, 0x1.0c964c7414a43p-1008, 0x1.0863f3424451ap-1008, 0x1.044263753b406p-1008, 0x1.003159e766535p-1008, 0x1.f86128ff91741p-1009, 0x1.f07fa45b932e4p-1009, 0x1.e8bda5ca24e19p-1009, 0x1.e11aaf32fc4ep-1009, 0x1.d9964476305cdp-1009, 0x1.d22feb64579b6p-1009, 0x1.cae72bb6c63cfp-1009, 0x1.c3bb8f07eb24p-1009, 0x1.bcaca0cbcb777p-1009, 0x1.b5b9ee489c499p-1009, 0x1.aee3068f79d86p-1009, 0x1.a8277a753bf1p-1009, 0x1.a186dc8b67014p-1009, 0x1.9b00c11939654p-1009, 0x1.9494be14d47fap-1009, 0x1.8e426b1c812dap-1009, 0x1.880961700f28fp-1009, 0x1.81e93bea4eec5p-1009, 0x1.7be196faa5b0ap-1009, 0x1.75f2109ebb19ep-1009, 0x1.701a485c402d7p-1009, 0x1.6a59df3acf2ccp-1009, 0x1.64b077bde3f01p-1009, 0x1.5f1db5deec605p-1009, 0x1.59a13f0770aecp-1009, 0x1.543aba0b52ec1p-1009, 0x1.4ee9cf2325a06p-1009, 0x1.49ae27e69909ep-1009, 0x1.44876f46fea5bp-1009, 0x1.3f755189e2ab2p-1009, 0x1.3a777c43bb207p-1009, 0x1.358d9e52ac33fp-1009, 0x1.30b767d961832p-1009, 0x1.2bf48a39fbfd1p-1009, 0x1.2744b811140d2p-1009, 0x1.22a7a530cfbcfp-1009, 0x1.1e1d069c0c7dfp-1009, 0x1.19a492819c4cp-1009, 0x1.153e003795dadp-1009, 0x1.10e90836b7836p-1009, 0x1.0ca56415dca55p-1009, 0x1.0872ce858532cp-1009, 0x1.0451034b6f1dfp-1009, 0x1.003fbf3e41618p-1009, 0x1.f87d808290b7fp-1010, 0x1.f09b8a8086751p-1010, 0x1.e8d91c56845b4p-1010, 0x1.e135b7e52a49dp-1010, 0x1.d9b0e10595a0ap-1010, 0x1.d24a1d817f4a2p-1010, 0x1.cb00f50b794dp-1010, 0x1.c3d4f1374b67cp-1010, 0x1.bcc59d726e3a3p-1010, 0x1.b5d286fca4814p-1010, 0x1.aefb3ce0b1ef4p-1010, 0x1.a83f4fed2f278p-1010, 0x1.a19e52ad7a6aep-1010, 0x1.9b17d962c4813p-1010, 0x1.94ab79fd396f3p-1010, 0x1.8e58cc1544897p-1010, 0x1.881f68e4ef775p-1010, 0x1.81feeb415bb97p-1010, 0x1.7bf6ef94564a9p-1010, 0x1.760713d604f16p-1010, 0x1.702ef786acddap-1010, 0x1.6a6e3ba8922a2p-1010, 0x1.64c482b9efe18p-1010, 0x1.5f3170af0821fp-1010, 0x1.59b4aaec4c017p-1010, 0x1.544dd8409ad16p-1010, 0x1.4efca0df98662p-1010, 0x1.49c0ae5c1a049p-1010, 0x1.4499aba2a99c7p-1010, 0x1.3f8744f41ef6p-1010, 0x1.3a8927e04e7a3p-1010, 0x1.359f0340cd404p-1010, 0x1.30c88733ca0b4p-1010, 0x1.2c056516fae31p-1010, 0x1.27554f829ef79p-1010, 0x1.22b7fa44947bbp-1010, 0x1.1e2d1a5b8229cp-1010, 0x1.19b465f214211p-1010, 0x1.154d945a4bd09p-1010, 0x1.10f85e08e2a15p-1010, 0x1.0cb47c90bf16dp-1010, 0x1.0881aa9e7c1a7p-1010, 0x1.045fa3f4022ap-1010, 0x1.004e256432216p-1010, 0x1.f899d99d42b1bp-1011, 0x1.f0b77236cda6fp-1011, 0x1.e8f4946df2705p-1011, 0x1.e150c21c3aa69p-1011, 0x1.d9cb7f13c9bbfp-1011, 0x1.d26451177a95p-1011, 0x1.cb1abfd31caabp-1011, 0x1.c3ee54d3d038p-1011, 0x1.bcde9b8080f72p-1011, 0x1.b5eb21127ef34p-1011, 0x1.af13748e34f78p-1011, 0x1.a85726bbfc23ap-1011, 0x1.a1b5ca210c331p-1011, 0x1.9b2ef2f888024p-1011, 0x1.94c2372ca5e24p-1011, 0x1.8e6f2e4ff34abp-1011, 0x1.88357196b37d8p-1011, 0x1.82149bd058af9p-1011, 0x1.7c0c4961174cdp-1011, 0x1.761c183b92efap-1011, 0x1.7043a7daa4a3ep-1011, 0x1.6a82993b3a115p-1011, 0x1.64d88ed64d291p-1011, 0x1.5f452c9af3f46p-1011, 0x1.59c817e888249p-1011, 0x1.5460f788e604p-1011, 0x1.4f0f73aac26bfp-1011, 0x1.49d335dc17624p-1011, 0x1.44abe904a704cp-1011, 0x1.3f9939609468ap-1011, 0x1.3a9ad47b1217p-1011, 0x1.35b0692925ceap-1011, 0x1.30d9a78481377p-1011, 0x1.2c1640e66f329p-1011, 0x1.2765e7e2d575cp-1011, 0x1.22c850434a1ffp-1011, 0x1.1e3d2f023cf77p-1011, 0x1.19c43a4634039p-1011, 0x1.155d295d1b338p-1011, 0x1.1107b4b7a6c6bp-1011, 0x1.0cc395e4c82bap-1011, 0x1.0890878d350afp-1011, 0x1.046e456f0036cp-1011, 0x1.005c8c594435ep-1011, 0x1.f8b6344fbe4a2p-1012, 0x1.f0d35b7e7f50fp-1012, 0x1.e9100e108553bp-1012, 0x1.e16bcdd8433e6p-1012, 0x1.d9e61ea0e2316p-1012, 0x1.d27e86265ea8ap-1012, 0x1.cb348c0dc52ep-1012, 0x1.c407b9dd8e194p-1012, 0x1.bcf79af617e0ep-1012, 0x1.b603bc8a3f816p-1012, 0x1.af2bad9816835p-1012, 0x1.a86efee1b6295p-1012, 0x1.a1cd42e62f50ap-1012, 0x1.9b460dda96936p-1012, 0x1.94d8f5a32c391p-1012, 0x1.8e8591cc9f883p-1012, 0x1.884b7b856d0a1p-1012, 0x1.822a4d975755ep-1012, 0x1.7c21a460f9f89p-1012, 0x1.76311dcf7610bp-1012, 0x1.7058595838387p-1012, 0x1.6a96f7f2d7579p-1012, 0x1.64ec9c130bfa3p-1012, 0x1.5f58e9a2bfca4p-1012, 0x1.59db85fc34cb2p-1012, 0x1.547417e443f7fp-1012, 0x1.4f224784b2e81p-1012, 0x1.49e5be66a01c7p-1012, 0x1.44be276d059cp-1012, 0x1.3fab2ecf51859p-1012, 0x1.3aac8214143f7p-1012, 0x1.35c1d00bc3ee7p-1012, 0x1.30eac8cb94decp-1012, 0x1.2c271da8668b4p-1012, 0x1.27768131c4f11p-1012, 0x1.22d8a72cfddd5p-1012, 0x1.1e4d449049e5ep-1012, 0x1.19d40f7e08be4p-1012, 0x1.156cbf40109b5p-1012, 0x1.11170c431058ep-1012, 0x1.0cd2b01204178p-1012, 0x1.089f6551bc072p-1012, 0x1.047ce7bc7517p-1012, 0x1.006af41d8342ap-1012, 0x1.f8d2909a1a6b3p-1013, 0x1.f0ef4657b2018p-1013, 0x1.e92b893e53398p-1013, 0x1.e186db1959ecap-1013, 0x1.da00bfacf484fp-1013, 0x1.d298bcae40b2dp-1013, 0x1.cb4e59bb87b01p-1013, 0x1.c421205499915p-1013, 0x1.bd109bd3472bp-1013, 0x1.b61c5963fa0e6p-1013, 0x1.af43e7fe6a262p-1013, 0x1.a886d85e707d8p-1013, 0x1.a1e4bcfcf6bb9p-1013, 0x1.9b5d2a0902e0ap-1013, 0x1.94efb560ded52p-1013, 0x1.8e9bf68b5b59dp-1013, 0x1.886186b12dec6p-1013, 0x1.824000966934bp-1013, 0x1.7c3700940f8fep-1013, 0x1.76462491bf51ap-1013, 0x1.706d0bff78546p-1013, 0x1.6aab57cf7a73p-1013, 0x1.6500aa703c894p-1013, 0x1.5f6ca7c67b971p-1013, 0x1.59eef52761a8cp-1013, 0x1.54873952c4221p-1013, 0x1.4f351c6d79119p-1013, 0x1.49f847fbc32d5p-1013, 0x1.44d066dbd4209p-1013, 0x1.3fbd254064d01p-1013, 0x1.3abe30ab633cdp-1013, 0x1.35d337e8b5afep-1013, 0x1.30fbeb0912d92p-1013, 0x1.2c37fb5cee8dcp-1013, 0x1.27871b6f7ad38p-1013, 0x1.22e8ff01bce83p-1013, 0x1.1e5d5b05b5f49p-1013, 0x1.19e3e5999f1ccp-1013, 0x1.157c560338a05p-1013, 0x1.112664ab2bbddp-1013, 0x1.0ce1cb187f0edp-1013, 0x1.08ae43ec1d12ap-1013, 0x1.048b8adc6c9e5p-1013, 0x1.00795cb0faebdp-1013, 0x1.f8eeee7c6e005p-1014, 0x1.f10b32c27c485p-1014, 0x1.e94705f772573p-1014, 0x1.e1a1e9df948ddp-1014, 0x1.da1b6238163bap-1014, 0x1.d2b2f4af35e2bp-1014, 0x1.cb6828dc790b2p-1014, 0x1.c43a88390726fp-1014, 0x1.bd299e18230a6p-1014, 0x1.b634f79fc27e3p-1014, 0x1.af5c23c143743p-1014, 0x1.a89eb3323e666p-1014, 0x1.a1fc3865756cdp-1014, 0x1.9b744783df972p-1014, 0x1.95067665d018cp-1014, 0x1.8eb25c8c38d86p-1014, 0x1.8877931a07f4fp-1014, 0x1.8255b4cd9fd52p-1014, 0x1.7c4c5dfa6955dp-1014, 0x1.765b2c827fb08p-1014, 0x1.7081bfd075b1bp-1014, 0x1.6abfb8d133dafp-1014, 0x1.6514b9edef0b8p-1014, 0x1.5f806706374f5p-1014, 0x1.5a02656a1e722p-1014, 0x1.549a5bd475f85p-1014, 0x1.4f47f26524207p-1014, 0x1.4a0ad29b8f8ffp-1014, 0x1.44e2a7512151bp-1014, 0x1.3fcf1cb3dccc6p-1014, 0x1.3acfe0410d593p-1014, 0x1.35e4a0c00923dp-1014, 0x1.310d0e3d08ff4p-1014, 0x1.2c48da0414db4p-1014, 0x1.2797b69c0487dp-1014, 0x1.22f957c19475bp-1014, 0x1.1e6d72628e23ep-1014, 0x1.19f3bc9903eb5p-1014, 0x1.158beda69fdbap-1014, 0x1.1135bdf0055c3p-1014, 0x1.0cf0e6f84546cp-1014, 0x1.08bd235c6431bp-1014, 0x1.049a2ecef2a0ep-1014, 0x1.0087c613b6d66p-1014, 0x1.f90b4df6cff61p-1015, 0x1.f12720bef4b63p-1015, 0x1.e962843bf8e36p-1015, 0x1.e1bcfa2b08ffdp-1015, 0x1.da3606425cdbdp-1015, 0x1.d2cd2e2953686p-1015, 0x1.cb81f970ae1acp-1015, 0x1.c453f18aeb625p-1015, 0x1.bd42a1c4bfb4dp-1015, 0x1.b64d973dacb5fp-1015, 0x1.af7460e0b6032p-1015, 0x1.a8b68f5d332b1p-1015, 0x1.a213b51fbe5e6p-1015, 0x1.9b8b664b3f64fp-1015, 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0x1.27fb6d418eb4ap-1020, 0x1.235b7f8c8879dp-1020, 0x1.1ece118e5657ep-1020, 0x1.1a52d9481cfe8p-1020, 0x1.15e98de2fc8a8p-1020, 0x1.1191e7ab70986p-1020, 0x1.0d4ba00cc2d6p-1020, 0x1.0916718c8fcaap-1020, 0x1.04f217c65d8b8p-1020, 0x1.00de4f6744155p-1020, 0x1.f9b5ac534e09fp-1021, 0x1.f1ced5a200d1cp-1021, 0x1.ea079a4b78ce8p-1021, 0x1.e25f7be24aeb4p-1021, 0x1.dad5fdf2c1bf9p-1021, 0x1.d36aa5faf6b8ap-1021, 0x1.cc1cfb630addbp-1021, 0x1.c4ec87757eb24p-1021, 0x1.bdd8d557a8b77p-1021, 0x1.b6e172024a14ap-1021, 0x1.b005ec3a40ec4p-1021, 0x1.a945d48957e89p-1021, 0x1.a2a0bd373288fp-1021, 0x1.9c163a4255bedp-1021, 0x1.95a5e1594c67dp-1021, 0x1.8f4f49d3e7363p-1021, 0x1.89120cac97996p-1021, 0x1.82edc479e53afp-1021, 0x1.7ce20d67fda61p-1021, 0x1.76ee85325daf7p-1021, 0x1.7112cb1d9438bp-1021, 0x1.6b4e7ff11de7dp-1021, 0x1.65a145f159703p-1021, 0x1.600ac0d9940a7p-1021, 0x1.5a8a95d62dba5p-1021, 0x1.55206b7ed5036p-1021, 0x1.4fcbe9d0d9af5p-1021, 0x1.4a8cba2996489p-1021, 0x1.45628740efef7p-1021, 0x1.404cfd23ec2fbp-1021, 0x1.3b4bc92f5c7efp-1021, 0x1.365e9a0a9f0dp-1021, 0x1.31851fa27490cp-1021, 0x1.2cbf0b23eabe8p-1021, 0x1.280c0ef75b139p-1021, 0x1.236bdebb7da74p-1021, 0x1.1ede2f408fb0ap-1021, 0x1.1a62b6838d71ep-1021, 0x1.15f92ba97f3c1p-1021, 0x1.11a146fad93f2p-1021, 0x1.0d5ac1deedda2p-1021, 0x1.092556d77222cp-1021, 0x1.0500c17c145a3p-1021, 0x1.00ecbe762408dp-1021, 0x1.f9d216f896f15p-1022, 0x1.f1eace9cb4959p-1022, 0x1.ea23236241c33p-1022, 0x1.e27a96d4b8bc2p-1022, 0x1.daf0ac7965d93p-1022, 0x1.d384e9c78041dp-1022, 0x1.cc36d6206240dp-1022, 0x1.c505fac7e0b7cp-1022, 0x1.bdf1e2dcc134ep-1022, 0x1.b6fa1b514e301p-1022, 0x1.b01e32e408f75p-1022, 0x1.a95dba1878d37p-1022, 0x1.a2b8433016f03p-1022, 0x1.9c2d622356946p-1022, 0x1.95bcac9ac93a1p-1022, 0x1.8f65b9e85e153p-1022, 0x1.89282300bc9cep-1022, 0x1.83038274b9aa6p-1022, 0x1.7cf7746ae6c3cp-1022, 0x1.770396993b28bp-1022, 0x1.7127883ed63c1p-1022, 0x1.6b62ea1ddae32p-1022, 0x1.65b55e7563779p-1022, 0x1.601e88fb8de9bp-1022, 0x1.5a9e0ed79fb21p-1022, 0x1.5533969c41334p-1022, 0x1.4fdec841d02e7p-1022, 0x1.4a9f4d20c8edcp-1022, 0x1.4574cfec45cap-1022, 0x1.405efcac94b2ep-1022, 0x1.3b5d80b9e2601p-1022, 0x1.36700ab6fad69p-1022, 0x1.31964a8c1eeb3p-1022, 0x1.2ccff161ee6f9p-1022, 0x1.281cb19c66b5dp-1022, 0x1.237c3ed5f51afp-1022, 0x1.1eee4dda9d468p-1022, 0x1.1a7294a332d17p-1022, 0x1.1608ca50a6062p-1022, 0x1.11b0a727636e1p-1022, 0x1.0d69e48ac5e05p-1022, 0x1.09343cf89ac8dp-1022, 0x1.050f6c04b85dbp-1022, 0x1.00fb2e54a57c4p-1022) > > > x <- p2 <- 1023/1024 > stopifnot( (1-x)-1 == -x , 1-x == 2^-10 ) > > k2 <- 700000 + (1:1000) > dput(p2^ k2, control = "digits17") ## last 2-3 digits printed *differ* c(9.4086285016650735e-298, 9.3994403878939149e-298, 9.3902612468901133e-298, 9.3810910698911961e-298, 9.3719298481432567e-298, 9.3627775729009291e-298, 9.353634235427393e-298, 9.3444998269943586e-298, 9.3353743388820597e-298, 9.3262577623792452e-298, 9.3171500887831706e-298, 9.3080513093995932e-298, 9.2989614155427581e-298, 9.2898803985353915e-298, 9.2808082497086976e-298, 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5.3646406662970699e-298, 5.3594017593963888e-298, 5.3541679686157282e-298, 5.3489392889588772e-298, 5.3437157154345035e-298, 5.3384972430561497e-298, 5.3332838668422277e-298, 5.328075581816014e-298, 5.322872383005647e-298, 5.3176742654441176e-298, 5.3124812241692704e-298, 5.3072932542237921e-298, 5.3021103506552144e-298, 5.296932508515903e-298, 5.2917597228630549e-298, 5.2865919887586968e-298, 5.2814293012696748e-298, 5.2762716554676536e-298, 5.2711190464291108e-298, 5.2659714692353323e-298, 5.2608289189724073e-298, 5.2556913907312232e-298, 5.2505588796074626e-298, 5.2454313807015958e-298, 5.2403088891188789e-298, 5.2351913999693489e-298, 5.2300789083678169e-298, 5.2249714094338632e-298, 5.2198688982918382e-298, 5.21477137007085e-298, 5.2096788199047651e-298, 5.2045912429322023e-298, 5.1995086342965259e-298, 5.1944309891458463e-298, 5.1893583026330079e-298, 5.1842905699155936e-298, 5.1792277861559103e-298, 5.1741699465209923e-298, 5.1691170461825928e-298, 5.1640690803171803e-298, 5.1590260441059324e-298, 5.1539879327347358e-298, 5.1489547413941744e-298, 5.1439264652795312e-298, 5.1389030995907821e-298, 5.1338846395325876e-298, 5.1288710803142942e-298, 5.1238624171499247e-298, 5.118858645258177e-298, 5.1138597598624172e-298, 5.1088657561906767e-298, 5.1038766294756465e-298, 5.0988923749546744e-298, 5.0939129878697577e-298, 5.0889384634675411e-298, 5.083968796999311e-298, 5.0790039837209911e-298, 5.0740440188931386e-298, 5.0690888977809385e-298, 5.0641386156541988e-298, 5.0591931677873496e-298, 5.0542525494594324e-298, 5.0493167559541001e-298, 5.044385782559614e-298, 5.039459624568833e-298, 5.0345382772792151e-298, 5.02962173599281e-298, 5.0247099960162546e-298, 5.0198030526607699e-298, 5.0149009012421556e-298, 5.0100035370807862e-298, 5.0051109555016061e-298, 5.000223151834124e-298, 4.9953401214124104e-298, 4.9904618595750943e-298, 4.9855883616653524e-298, 4.9807196230309142e-298, 4.975855639024048e-298, 4.9709964050015629e-298, 4.9661419163248043e-298, 4.961292168359643e-298, 4.9564471564764793e-298, 4.9516068760502324e-298, 4.9467713224603396e-298, 4.9419404910907497e-298, 4.9371143773299192e-298, 4.9322929765708079e-298, 4.9274762842108754e-298, 4.9226642956520754e-298, 4.917857006300853e-298, 4.9130544115681368e-298, 4.9082565068693405e-298, 4.903463287624351e-298, 4.8986747492575299e-298, 4.8938908871977079e-298, 4.8891116968781794e-298, 4.8843371737366967e-298, 4.8795673132154692e-298, 4.8748021107611574e-298, 4.870041561824867e-298, 4.8652856618621478e-298, 4.8605344063329857e-298, 4.8557877907018004e-298, 4.8510458104374436e-298, 4.8463084610131879e-298, 4.8415757379067303e-298, 4.8368476366001804e-298, 4.8321241525800633e-298, 4.8274052813373095e-298, 4.8226910183672529e-298, 4.8179813591696285e-298, 4.8132762992485646e-298, 4.8085758341125797e-298, 4.8038799592745794e-298, 4.7991886702518503e-298, 4.7945019625660577e-298, 4.7898198317432392e-298, 4.7851422733138019e-298, 4.7804692828125193e-298, 4.7758008557785224e-298, 4.7711369877553018e-298, 4.7664776742906963e-298, 4.7618229109368968e-298, 4.7571726932504356e-298, 4.7525270167921831e-298, 4.7478858771273465e-298, 4.743249269825465e-298, 4.7386171904604009e-298, 4.7339896346103419e-298, 4.7293665978577927e-298, 4.7247480757895724e-298, 4.7201340639968088e-298, 4.7155245580749371e-298, 4.7109195536236917e-298, 4.7063190462471063e-298, 4.7017230315535052e-298, 4.6971315051555042e-298, 4.6925444626700005e-298, 4.6879618997181743e-298, 4.6833838119254812e-298, 4.6788101949216478e-298, 4.6742410443406689e-298, 4.6696763558208056e-298, 4.6651161250045738e-298, 4.660560347538749e-298, 4.656009019074356e-298, 4.6514621352666663e-298, 4.6469196917751951e-298, 4.6423816842636958e-298, 4.6378481084001573e-298, 4.6333189598567972e-298, 4.6287942343100626e-298, 4.6242739274406183e-298, 4.619758034933353e-298, 4.6152465524773632e-298, 4.6107394757659593e-298, 4.6062368004966564e-298, 4.6017385223711714e-298, 4.5972446370954181e-298, 4.5927551403795046e-298, 4.5882700279377284e-298, 4.5837892954885702e-298, 4.5793129387546949e-298, 4.574840953462942e-298, 4.5703733353443254e-298, 4.5659100801340283e-298, 4.5614511835713979e-298, 4.5569966413999416e-298, 4.5525464493673241e-298, 4.5481006032253642e-298, 4.543659098730027e-298, 4.5392219316414232e-298, 4.5347890977238047e-298, 4.5303605927455588e-298, 4.5259364124792056e-298, 4.5215165527013937e-298, 4.5171010091928961e-298, 4.5126897777386067e-298, 4.5082828541275335e-298, 4.5038802341527995e-298, 4.4994819136116349e-298, 4.4950878883053731e-298, 4.4906981540394499e-298, 4.4863127066233962e-298, 4.4819315418708345e-298, 4.4775546555994755e-298, 4.4731820436311174e-298, 4.4688137017916339e-298, 4.4644496259109774e-298, 4.4600898118231736e-298, 4.4557342553663156e-298, 4.451382952382559e-298, 4.4470358987181232e-298, 4.4426930902232809e-298, 4.4383545227523602e-298, 4.4340201921637346e-298, 4.4296900943198247e-298, 4.4253642250870904e-298, 4.4210425803360286e-298, 4.4167251559411697e-298, 4.4124119477810707e-298, 4.4081029517383155e-298, 4.4037981636995086e-298, 4.399497579555271e-298, 4.3952011952002368e-298, 4.3909090065330491e-298, 4.3866210094563565e-298, 4.3823371998768094e-298, 4.3780575737050547e-298, 4.3737821268557335e-298, 4.3695108552474756e-298, 4.3652437548028982e-298, 4.3609808214485987e-298, 4.3567220511151528e-298, 4.3524674397371102e-298, 4.3482169832529923e-298, 4.3439706776052841e-298, 4.3397285187404348e-298, 4.335490502608853e-298, 4.3312566251648985e-298, 4.3270268823668859e-298, 4.3228012701770747e-298, 4.3185797845616671e-298, 4.3143624214908065e-298, 4.3101491769385695e-298, 4.305940046882965e-298, 4.3017350273059313e-298, 4.2975341141933272e-298, 4.2933373035349353e-298, 4.2891445913244523e-298, 4.2849559735594867e-298, 4.2807714462415578e-298, 4.2765910053760873e-298, 4.2724146469724e-298, 4.2682423670437163e-298, 4.2640741616071496e-298, 4.2599100266837056e-298, 4.2557499582982725e-298, 4.2515939524796218e-298, 4.2474420052604032e-298, 4.2432941126771408e-298, 4.2391502707702298e-298, 4.2350104755839304e-298, 4.2308747231663683e-298, 4.2267430095695263e-298, 4.2226153308492431e-298, 4.2184916830652111e-298, 4.2143720622809676e-298, 4.2102564645638959e-298, 4.2061448859852202e-298, 4.2020373226200003e-298, 4.1979337705471291e-298, 4.1938342258493294e-298, 4.1897386846131488e-298, 4.1856471429289558e-298, 4.1815595968909398e-298, 4.177476042597101e-298, 4.1733964761492517e-298, 4.1693208936530127e-298, 4.1652492912178048e-298, 4.1611816649568498e-298, 4.1571180109871654e-298, 4.1530583254295608e-298, 4.1490026044086333e-298, 4.1449508440527652e-298, 4.14090304049412e-298, 4.1368591898686376e-298, 4.1328192883160316e-298, 4.1287833319797852e-298, 4.1247513170071485e-298, 4.1207232395491343e-298, 4.1166990957605115e-298, 4.112678881799808e-298, 4.1086625938293004e-298, 4.1046502280150142e-298, 4.1006417805267181e-298, 4.0966372475379222e-298, 4.0926366252258743e-298, 4.0886399097715521e-298, 4.084647097359665e-298, 4.0806581841786502e-298, 4.0766731664206635e-298, 4.0726920402815802e-298, 4.0687148019609931e-298, 4.0647414476622028e-298, 4.0607719735922208e-298, 4.0568063759617592e-298, 4.0528446509852337e-298, 4.0488867948807562e-298, 4.0449328038701303e-298, 4.0409826741788508e-298, 4.0370364020360981e-298, 4.0330939836747346e-298, 4.0291554153313024e-298, 4.025220693246018e-298, 4.0212898136627704e-298, 4.017362772829115e-298, 4.0134395669962744e-298, 4.0095201924191291e-298, 4.0056046453562201e-298, 4.0016929220697393e-298, 3.9977850188255309e-298, 3.9938809318930839e-298, 3.989980657545532e-298, 3.9860841920596476e-298, 3.9821915317158396e-298, 3.9783026727981478e-298, 3.9744176115942433e-298, 3.9705363443954215e-298, 3.9666588674965972e-298, 3.9627851771963077e-298, 3.9589152697967021e-298, 3.955049141603541e-298, 3.9511867889261941e-298, 3.9473282080776336e-298, 3.9434733953744328e-298, 3.9396223471367618e-298, 3.9357750596883866e-298, 3.9319315293566597e-298, 3.9280917524725222e-298, 3.9242557253704979e-298, 3.9204234443886911e-298, 3.91659490586878e-298, 3.9127701061560174e-298, 3.9089490415992244e-298, 3.9051317085507878e-298, 3.9013181033666568e-298, 3.8975082224063371e-298, 3.8937020620328936e-298, 3.8898996186129396e-298, 3.8861008885166378e-298, 3.8823058681176957e-298, 3.8785145537933625e-298, 3.8747269419244232e-298, 3.8709430288952007e-298, 3.8671628110935447e-298, 3.8633862849108366e-298, 3.8596134467419779e-298, 3.8558442929853943e-298, 3.8520788200430255e-298, 3.8483170243203276e-298, 3.8445589022262643e-298, 3.8408044501733089e-298, 3.8370536645774366e-298, 3.8333065418581226e-298, 3.8295630784383397e-298, 3.825823270744552e-298, 3.8220871152067155e-298, 3.8183546082582717e-298, 3.8146257463361444e-298, 3.8109005258807378e-298, 3.8071789433359326e-298, 3.8034609951490811e-298, 3.7997466777710058e-298, 3.7960359876559952e-298, 3.7923289212617996e-298, 3.7886254750496299e-298, 3.7849256454841519e-298, 3.781229429033484e-298, 3.7775368221691932e-298, 3.7738478213662936e-298, 3.7701624231032407e-298, 3.7664806238619287e-298, 3.7628024201276885e-298, 3.7591278083892829e-298, 3.7554567851389026e-298, 3.7517893468721654e-298, 3.7481254900881104e-298, 3.7444652112891964e-298, 3.7408085069812966e-298, 3.7371553736736979e-298, 3.7335058078790946e-298, 3.7298598061135876e-298, 3.7262173648966799e-298, 3.7225784807512728e-298, 3.7189431502036641e-298, 3.7153113697835435e-298, 3.7116831360239892e-298, 3.7080584454614661e-298, 3.7044372946358197e-298, 3.700819680090277e-298, 3.6972055983714388e-298, 3.6935950460292795e-298, 3.6899880196171413e-298, 3.686384515691734e-298, 3.6827845308131288e-298, 3.6791880615447568e-298, 3.6755951044534041e-298, 3.6720056561092114e-298, 3.6684197130856676e-298, 3.6648372719596073e-298, 3.6612583293112089e-298, 3.657682881723991e-298, 3.6541109257848077e-298, 3.6505424580838456e-298, 3.6469774752146233e-298, 3.6434159737739842e-298, 3.6398579503620953e-298, 3.6363034015824449e-298, 3.6327523240418369e-298, 3.6292047143503897e-298, 3.6256605691215319e-298, 3.6221198849719992e-298, 3.6185826585218316e-298, 3.6150488863943686e-298, 3.6115185652162493e-298, 3.6079916916174052e-298, 3.6044682622310601e-298, 3.6009482736937249e-298, 3.597431722645196e-298, 3.5939186057285503e-298, 3.5904089195901437e-298, 3.5869026608796062e-298, 3.5833998262498412e-298, 3.579900412357019e-298, 3.5764044158605765e-298, 3.5729118334232128e-298, 3.5694226617108854e-298, 3.5659368973928083e-298, 3.5624545371414482e-298, 3.5589755776325211e-298, 3.555500015544989e-298, 3.5520278475610586e-298, 3.5485590703661745e-298, 3.5450936806490204e-298) > dput(p2^ k2, control = "hex") c(0x1.3b0b694f990ecp-987, 0x1.3abca67545287p-987, 0x1.3a6df74ba7d73p-987, 0x1.3a1f5bcdd4ed3p-987, 0x1.39d0d3f6e178p-987, 0x1.39825fc1e3bfap-987, 0x1.3933ff29f346bp-987, 0x1.38e5b22a28c9ep-987, 0x1.389778bd9e3fbp-987, 0x1.384952df6ed82p-987, 0x1.37fb408ab6fc6p-987, 0x1.37ad41ba944eap-987, 0x1.375f566a25a99p-987, 0x1.37117e948b202p-987, 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0x1.dad326072ee33p-989) > > x <- p3 <- (1- 2^-14) > stopifnot( (1-x)-1 == -x , 1-x == 2^-14 ) > log(1e-300)/ log(p3) # 11317321 [1] 11317321 > > k3 <- 11321012 + (1:1000) > dput(p3^ k3, control = "digits17") ## last 2-3 digits printed *differ* c(7.9823091750159774e-301, 7.9818219735282437e-301, 7.981334801776929e-301, 7.9808476597602195e-301, 7.9803605474762984e-301, 7.9798734649233519e-301, 7.9793864120995648e-301, 7.9788993890031234e-301, 7.9784123956322125e-301, 7.9779254319850184e-301, 7.9774384980597273e-301, 7.9769515938545225e-301, 7.9764647193675935e-301, 7.9759778745971235e-301, 7.975491059541302e-301, 7.9750042741983121e-301, 7.9745175185663418e-301, 7.9740307926435775e-301, 7.9735440964282056e-301, 7.973057429918414e-301, 7.9725707931123891e-301, 7.9720841860083173e-301, 7.9715976086043865e-301, 7.9711110608987832e-301, 7.9706245428896954e-301, 7.9701380545753094e-301, 7.9696515959538148e-301, 7.9691651670233981e-301, 7.9686787677822456e-301, 7.9681923982285486e-301, 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7.5510305651515335e-301, 7.550569686821141e-301, 7.5501088366205299e-301, 7.5496480145479825e-301, 7.5491872206017815e-301, 7.548726454780211e-301, 7.5482657170815552e-301, 7.5478050075040965e-301, 7.5473443260461191e-301, 7.5468836727059073e-301, 7.5464230474817418e-301, 7.5459624503719102e-301, 7.5455018813746949e-301, 7.5450413404883817e-301, 7.5445808277112516e-301, 7.5441203430415921e-301, 7.5436598864776855e-301, 7.5431994580178178e-301, 7.542739057660273e-301, 7.5422786854033355e-301, 7.541818341245291e-301, 7.5413580251844236e-301, 7.5408977372190193e-301, 7.5404374773473621e-301, 7.5399772455677395e-301, 7.5395170418784341e-301, 7.5390568662777334e-301, 7.5385967187639231e-301, 7.5381365993352874e-301, 7.5376765079901139e-301, 7.5372164447266866e-301, 7.5367564095432931e-301, 7.5362964024382176e-301, 7.5358364234097491e-301, 7.5353764724561718e-301, 7.5349165495757717e-301, 7.5344566547668377e-301, 7.5339967880276558e-301, 7.5335369493565117e-301, 7.533077138751693e-301, 7.5326173562114854e-301, 7.5321576017341782e-301, 7.5316978753180554e-301, 7.5312381769614079e-301, 7.5307785066625215e-301, 7.5303188644196837e-301, 7.5298592502311803e-301, 7.5293996640953021e-301, 7.5289401060103366e-301, 7.5284805759745679e-301, 7.5280210739862886e-301, 7.5275616000437844e-301, 7.5271021541453444e-301, 7.5266427362892563e-301, 7.526183346473809e-301, 7.5257239846972918e-301, 7.5252646509579905e-301, 7.5248053452541975e-301, 7.5243460675841986e-301, 7.5238868179462847e-301, 7.5234275963387432e-301, 7.522968402759865e-301, 7.5225092372079391e-301, 7.5220500996812547e-301, 7.5215909901780994e-301, 7.5211319086967655e-301, 7.5206728552355422e-301, 7.5202138297927169e-301, 7.5197548323665822e-301, 7.5192958629554272e-301, 7.518836921557541e-301, 7.5183780081712161e-301, 7.5179191227947416e-301, 7.5174602654264066e-301, 7.5170014360645036e-301, 7.5165426347073218e-301, 7.516083861353152e-301, 7.5156251160002865e-301, 7.5151663986470146e-301, 7.5147077092916288e-301, 7.5142490479324197e-301, 7.5137904145676765e-301, 7.5133318091956934e-301, 7.5128732318147612e-301, 7.5124146824231706e-301, 7.5119561610192142e-301, 7.5114976676011843e-301, 7.5110392021673701e-301, 7.5105807647160657e-301, 7.5101223552455637e-301) > dput(p3^ k3, control = "hex") c(0x1.11b31a015e2efp-997, 0x1.11aed334f6297p-997, 0x1.11aa8c79a9559p-997, 0x1.11a645cf776efp-997, 0x1.11a1ff3660311p-997, 0x1.119db8ae63579p-997, 0x1.11997237809ep-997, 0x1.11952bd1b7cp-997, 0x1.1190e57d08792p-997, 0x1.118c9f397285p-997, 0x1.11885906f59f4p-997, 0x1.118412e591836p-997, 0x1.117fccd545ed2p-997, 0x1.117b86d61298p-997, 0x1.117740e7f73fcp-997, 0x1.1172fb0af39fep-997, 0x1.116eb53f07741p-997, 0x1.116a6f843277fp-997, 0x1.116629da74672p-997, 0x1.1161e441ccfd5p-997, 0x1.115d9eba3bf62p-997, 0x1.11595943c10d3p-997, 0x1.115513de5bfe3p-997, 0x1.1150ce8a0c84cp-997, 0x1.114c8946d25c9p-997, 0x1.11484414ad414p-997, 0x1.1143fef39cee9p-997, 0x1.113fb9e3a1202p-997, 0x1.113b74e4b9919p-997, 0x1.11372ff6e5febp-997, 0x1.1132eb1a26231p-997, 0x1.112ea64e79ba8p-997, 0x1.112a6193e0809p-997, 0x1.11261cea5a311p-997, 0x1.1121d851e687bp-997, 0x1.111d93ca85401p-997, 0x1.11194f543616p-997, 0x1.11150aeef8c52p-997, 0x1.1110c69acd094p-997, 0x1.110c8257b29e1p-997, 0x1.11083e25a93f4p-997, 0x1.1103fa04b0a8ap-997, 0x1.10ffb5f4c895ep-997, 0x1.10fb71f5f0c2cp-997, 0x1.10f72e0828eafp-997, 0x1.10f2ea2b70ca5p-997, 0x1.10eea65fc81c9p-997, 0x1.10ea62a52e9d7p-997, 0x1.10e61efba408bp-997, 0x1.10e1db63281a2p-997, 0x1.10dd97dbba8d8p-997, 0x1.10d954655b1eap-997, 0x1.10d5110009893p-997, 0x1.10d0cdabc589p-997, 0x1.10cc8a688ed9fp-997, 0x1.10c847366537bp-997, 0x1.10c40415485e2p-997, 0x1.10bfc1053809p-997, 0x1.10bb7e0633f42p-997, 0x1.10b73b183bdb5p-997, 0x1.10b2f83b4f7a6p-997, 0x1.10aeb56f6e8d2p-997, 0x1.10aa72b498cf6p-997, 0x1.10a6300acdfdp-997, 0x1.10a1ed720dd1dp-997, 0x1.109daaea58099p-997, 0x1.10996873ac603p-997, 0x1.1095260e0a918p-997, 0x1.1090e3b972596p-997, 0x1.108ca175e3739p-997, 0x1.10885f435d9cp-997, 0x1.10841d21e08e9p-997, 0x1.107fdb116c071p-997, 0x1.107b9911ffc16p-997, 0x1.107757239b796p-997, 0x1.107315463eeafp-997, 0x1.106ed379e9d1fp-997, 0x1.106a91be9bea5p-997, 0x1.1066501454efep-997, 0x1.10620e7b149e8p-997, 0x1.105dccf2dab23p-997, 0x1.10598b7ba6e6dp-997, 0x1.10554a1578f83p-997, 0x1.105108c050a25p-997, 0x1.104cc77c2da1p-997, 0x1.104886490fb05p-997, 0x1.10444526f68c1p-997, 0x1.10400415e1f03p-997, 0x1.103bc315d198bp-997, 0x1.10378226c5417p-997, 0x1.10334148bca65p-997, 0x1.102f007bb7836p-997, 0x1.102abfbfb5948p-997, 0x1.10267f14b695bp-997, 0x1.10223e7aba42dp-997, 0x1.101dfdf1c057fp-997, 0x1.1019bd79c890fp-997, 0x1.10157d12d2a9cp-997, 0x1.10113cbcde5e8p-997, 0x1.100cfc77eb6bp-997, 0x1.1008bc43f98b5p-997, 0x1.10047c21087b7p-997, 0x1.10003c0f17f75p-997, 0x1.0ffbfc0e27bafp-997, 0x1.0ff7bc1e37825p-997, 0x1.0ff37c3f47097p-997, 0x1.0fef3c71560c5p-997, 0x1.0feafcb46447p-997, 0x1.0fe6bd0871757p-997, 0x1.0fe27d6d7d53ap-997, 0x1.0fde3de3879dbp-997, 0x1.0fd9fe6a900f9p-997, 0x1.0fd5bf0296655p-997, 0x1.0fd17fab9a5afp-997, 0x1.0fcd40659bac9p-997, 0x1.0fc901309a162p-997, 0x1.0fc4c20c9553bp-997, 0x1.0fc082f98d216p-997, 0x1.0fbc43f7813b3p-997, 0x1.0fb80506715d2p-997, 0x1.0fb3c6265d436p-997, 0x1.0faf875744a9fp-997, 0x1.0fab4899274cep-997, 0x1.0fa709ec04e84p-997, 0x1.0fa2cb4fdd383p-997, 0x1.0f9e8cc4aff8bp-997, 0x1.0f9a4e4a7ce5fp-997, 0x1.0f960fe143bcp-997, 0x1.0f91d1890436fp-997, 0x1.0f8d9341be12ep-997, 0x1.0f89550b710bfp-997, 0x1.0f8516e61cde2p-997, 0x1.0f80d8d1c145bp-997, 0x1.0f7c9ace5dfebp-997, 0x1.0f785cdbf2c53p-997, 0x1.0f741efa7f557p-997, 0x1.0f6fe12a036b7p-997, 0x1.0f6ba36a7ec36p-997, 0x1.0f6765bbf1196p-997, 0x1.0f63281e5a29ap-997, 0x1.0f5eea91b9b03p-997, 0x1.0f5aad160f695p-997, 0x1.0f566fab5b111p-997, 0x1.0f5232519c63ap-997, 0x1.0f4df508d31d3p-997, 0x1.0f49b7d0fef9ep-997, 0x1.0f457aaa1fb5fp-997, 0x1.0f413d94350d7p-997, 0x1.0f3d008f3ebcap-997, 0x1.0f38c39b3c7fap-997, 0x1.0f3486b82e12bp-997, 0x1.0f3049e61331fp-997, 0x1.0f2c0d24eb99ap-997, 0x1.0f27d074b706p-997, 0x1.0f2393d575332p-997, 0x1.0f1f574725dd4p-997, 0x1.0f1b1ac9c8c0bp-997, 0x1.0f16de5d5d999p-997, 0x1.0f12a201e4241p-997, 0x1.0f0e65b75c1c8p-997, 0x1.0f0a297dc53f1p-997, 0x1.0f05ed551f48p-997, 0x1.0f01b13d69f38p-997, 0x1.0efd7536a4fdep-997, 0x1.0ef93940d0234p-997, 0x1.0ef4fd5beb2p-997, 0x1.0ef0c187f5b06p-997, 0x1.0eec85c4ef908p-997, 0x1.0ee84a12d87ccp-997, 0x1.0ee40e71b0316p-997, 0x1.0edfd2e1766aap-997, 0x1.0edb97622ae4dp-997, 0x1.0ed75bf3cd5c2p-997, 0x1.0ed320965d8cep-997, 0x1.0ecee549db337p-997, 0x1.0ecaaa0e460cp-997, 0x1.0ec66ee39dd2fp-997, 0x1.0ec233c9e2447p-997, 0x1.0ebdf8c1131cfp-997, 0x1.0eb9bdc93018ap-997, 0x1.0eb582e238f3ep-997, 0x1.0eb1480c2d6bp-997, 0x1.0ead0d470d3a4p-997, 0x1.0ea8d292d81e1p-997, 0x1.0ea497ef8dd2bp-997, 0x1.0ea05d5d2e148p-997, 0x1.0e9c22dbb89fcp-997, 0x1.0e97e86b2d30ep-997, 0x1.0e93ae0b8b843p-997, 0x1.0e8f73bcd356p-997, 0x1.0e8b397f0462bp-997, 0x1.0e86ff521e66ap-997, 0x1.0e82c536211e2p-997, 0x1.0e7e8b2b0c45ap-997, 0x1.0e7a5130df997p-997, 0x1.0e7617479ad5fp-997, 0x1.0e71dd6f3db78p-997, 0x1.0e6da3a7c7fa9p-997, 0x1.0e6969f1395b7p-997, 0x1.0e65304b91968p-997, 0x1.0e60f6b6d0684p-997, 0x1.0e5cbd32f58dp-997, 0x1.0e5883c000c13p-997, 0x1.0e544a5df1c12p-997, 0x1.0e50110cc8496p-997, 0x1.0e4bd7cc84164p-997, 0x1.0e479e9d24e43p-997, 0x1.0e43657eaa6fap-997, 0x1.0e3f2c711474fp-997, 0x1.0e3af37462b0ap-997, 0x1.0e36ba8894df1p-997, 0x1.0e3281adaabccp-997, 0x1.0e2e48e3a4061p-997, 0x1.0e2a102a80778p-997, 0x1.0e25d7823fcd8p-997, 0x1.0e219eeae1c48p-997, 0x1.0e1d66646619p-997, 0x1.0e192deecc876p-997, 0x1.0e14f58a14cc3p-997, 0x1.0e10bd363ea3ep-997, 0x1.0e0c84f349caep-997, 0x1.0e084cc135fdcp-997, 0x1.0e0414a002f8ep-997, 0x1.0dffdc8fb078ep-997, 0x1.0dfba4903e3a2p-997, 0x1.0df76ca1abf92p-997, 0x1.0df334c3f9727p-997, 0x1.0deefcf726629p-997, 0x1.0deac53b3285fp-997, 0x1.0de68d901d992p-997, 0x1.0de255f5e758bp-997, 0x1.0dde1e6c8f811p-997, 0x1.0dd9e6f415cedp-997, 0x1.0dd5af8c79fe8p-997, 0x1.0dd17835bbcc9p-997, 0x1.0dcd40efdaf5ap-997, 0x1.0dc909bad7364p-997, 0x1.0dc4d296b04aep-997, 0x1.0dc09b8365f02p-997, 0x1.0dbc6480f7e28p-997, 0x1.0db82d8f65deap-997, 0x1.0db3f6aeafa11p-997, 0x1.0dafbfded4e65p-997, 0x1.0dab891fd56bp-997, 0x1.0da75271b0ebap-997, 0x1.0da31bd46724ep-997, 0x1.0d9ee547f7d34p-997, 0x1.0d9aaecc62b36p-997, 0x1.0d967861a781ep-997, 0x1.0d924207c5fb4p-997, 0x1.0d8e0bbebddc2p-997, 0x1.0d89d5868ee13p-997, 0x1.0d859f5f38c6fp-997, 0x1.0d816948bb4a1p-997, 0x1.0d7d334316272p-997, 0x1.0d78fd4e491adp-997, 0x1.0d74c76a53e1ap-997, 0x1.0d70919736385p-997, 0x1.0d6c5bd4efdb8p-997, 0x1.0d6826238087cp-997, 0x1.0d63f082e7f9cp-997, 0x1.0d5fbaf325ee2p-997, 0x1.0d5b85743a218p-997, 0x1.0d5750062450ap-997, 0x1.0d531aa8e4381p-997, 0x1.0d4ee55c79948p-997, 0x1.0d4ab020e4229p-997, 0x1.0d467af6239fp-997, 0x1.0d4245dc37c67p-997, 0x1.0d3e10d320559p-997, 0x1.0d39dbdadd091p-997, 0x1.0d35a6f36d9dap-997, 0x1.0d31721cd1cffp-997, 0x1.0d2d3d57095cap-997, 0x1.0d2908a214008p-997, 0x1.0d24d3fdf1783p-997, 0x1.0d209f6aa1806p-997, 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0x1.052651ac7038fp-997, 0x1.05223d1329872p-997, 0x1.051e288a353a8p-997, 0x1.051a14119311bp-997, 0x1.0515ffa942cb6p-997, 0x1.0511eb5144265p-997, 0x1.050dd70996e14p-997, 0x1.0509c2d23abafp-997, 0x1.0505aeab2f72p-997, 0x1.05019a9474c54p-997, 0x1.04fd868e0a737p-997, 0x1.04f97297f03b4p-997, 0x1.04f55eb225db8p-997, 0x1.04f14adcab12fp-997, 0x1.04ed37177fa04p-997, 0x1.04e92362a3424p-997, 0x1.04e50fbe15b7bp-997, 0x1.04e0fc29d6bf6p-997, 0x1.04dce8a5e618p-997, 0x1.04d8d53243807p-997, 0x1.04d4c1ceeeb76p-997, 0x1.04d0ae7be77bap-997, 0x1.04cc9b392d8cp-997, 0x1.04c88806c0a75p-997, 0x1.04c474e4a08c5p-997, 0x1.04c061d2ccf9cp-997, 0x1.04bc4ed145ae9p-997, 0x1.04b83be00a698p-997, 0x1.04b428ff1ae95p-997, 0x1.04b0162e76ecep-997, 0x1.04ac036e1e331p-997, 0x1.04a7f0be107a9p-997, 0x1.04a3de1e4d825p-997, 0x1.049fcb8ed5092p-997, 0x1.049bb90fa6cdcp-997, 0x1.0497a6a0c28f3p-997, 0x1.04939442280c2p-997, 0x1.048f81f3d7038p-997, 0x1.048b6fb5cf342p-997, 0x1.04875d88105cep-997, 0x1.04834b6a9a3cap-997, 0x1.047f395d6c924p-997, 0x1.047b2760871c9p-997, 0x1.04771573e99a7p-997, 0x1.0473039793cadp-997, 0x1.046ef1cb856c8p-997, 0x1.046ae00fbe3e6p-997, 0x1.0466ce643dff7p-997, 0x1.0462bcc9046e7p-997, 0x1.045eab3e114a6p-997, 0x1.045a99c364522p-997, 0x1.04568858fd449p-997, 0x1.045276fedbe09p-997, 0x1.044e65b4ffe52p-997, 0x1.044a547b69112p-997, 0x1.0446435217238p-997, 0x1.0442323909db2p-997, 0x1.043e213040f7p-997, 0x1.043a1037bc36p-997, 0x1.0435ff4f7b571p-997, 0x1.0431ee777e192p-997, 0x1.042dddafc43b2p-997, 0x1.0429ccf84d7c1p-997, 0x1.0425bc51199aep-997, 0x1.0421abba28567p-997, 0x1.041d9b33796ddp-997, 0x1.04198abd0c9ffp-997, 0x1.04157a56e1abcp-997, 0x1.04116a00f8503p-997, 0x1.040d59bb504c5p-997, 0x1.04094985e95f1p-997, 0x1.04053960c3477p-997, 0x1.0401294bddc46p-997, 0x1.03fd19473894fp-997, 0x1.03f90952d378p-997, 0x1.03f4f96eae2ccp-997, 0x1.03f0e99ac872p-997, 0x1.03ecd9d72206ep-997, 0x1.03e8ca23baaa5p-997, 0x1.03e4ba80921b7p-997, 0x1.03e0aaeda8192p-997, 0x1.03dc9b6afc628p-997, 0x1.03d88bf88eb69p-997, 0x1.03d47c965ed45p-997, 0x1.03d06d446c7aep-997, 0x1.03cc5e02b7693p-997, 0x1.03c84ed13f5e5p-997, 0x1.03c43fb004195p-997, 0x1.03c0309f05594p-997, 0x1.03bc219e42dd3p-997, 0x1.03b812adbc642p-997, 0x1.03b403cd71ad3p-997, 0x1.03aff4fd62776p-997, 0x1.03abe63d8e81ep-997, 0x1.03a7d78df58bap-997, 0x1.03a3c8ee9753dp-997, 0x1.039fba5f73997p-997, 0x1.039babe08a1bap-997, 0x1.03979d71da997p-997, 0x1.03938f1364d21p-997, 0x1.038f80c528848p-997, 0x1.038b7287256fdp-997, 0x1.038764595b534p-997, 0x1.0383563bc9eddp-997, 0x1.037f482e70febp-997, 0x1.037b3a315044fp-997, 0x1.03772c44677fap-997, 0x1.03731e67b66e1p-997, 0x1.036f109b3ccf3p-997, 0x1.036b02defa624p-997, 0x1.0366f532eee65p-997, 0x1.0362e7971a1a9p-997, 0x1.035eda0b7bbe3p-997, 0x1.035acc9013904p-997, 0x1.0356bf24e14ffp-997, 0x1.0352b1c9e4bc7p-997, 0x1.034ea47f1d94ep-997, 0x1.034a97448b986p-997, 0x1.03468a1a2e863p-997, 0x1.03427d00061d8p-997, 0x1.033e6ff6121d6p-997, 0x1.033a62fc52452p-997, 0x1.03365612c653dp-997, 0x1.033249396e08bp-997, 0x1.032e3c704923p-997, 0x1.032a2fb75761ep-997, 0x1.0326230e98848p-997, 0x1.032216760c4a2p-997, 0x1.031e09edb271fp-997, 0x1.0319fd758abb2p-997, 0x1.0315f10d94e4fp-997, 0x1.0311e4b5d0aeap-997, 0x1.030dd86e3dd76p-997, 0x1.0309cc36dc1e6p-997, 0x1.0305c00fab42fp-997, 0x1.0301b3f8ab045p-997, 0x1.02fda7f1db21ap-997, 0x1.02f99bfb3b5a3p-997, 0x1.02f59014cb6d4p-997, 0x1.02f1843e8b1a1p-997, 0x1.02ed78787a1ffp-997, 0x1.02e96cc2983ep-997, 0x1.02e5611ce533ap-997, 0x1.02e1558760c01p-997, 0x1.02dd4a020aa29p-997, 0x1.02d93e8ce29a6p-997, 0x1.02d53327e866dp-997, 0x1.02d127d31bc73p-997, 0x1.02cd1c8e7c7acp-997, 0x1.02c9115a0a40dp-997, 0x1.02c50635c4d8bp-997, 0x1.02c0fb21ac019p-997, 0x1.02bcf01dbf7aep-997, 0x1.02b8e529ff03ep-997, 0x1.02b4da466a5bfp-997, 0x1.02b0cf7301424p-997, 0x1.02acc4afc3764p-997, 0x1.02a8b9fcb0b73p-997, 0x1.02a4af59c8c47p-997, 0x1.02a0a4c70b5d5p-997, 0x1.029c9a4478412p-997, 0x1.02988fd20f2f4p-997, 0x1.0294856fcfe7p-997, 0x1.02907b1dba27cp-997, 0x1.028c70dbcdb0dp-997, 0x1.028866aa0a41ap-997, 0x1.02845c886f997p-997, 0x1.02805276fd77bp-997, 0x1.027c4875b39bcp-997, 0x1.02783e8491c4fp-997, 0x1.027434a397b2bp-997, 0x1.02702ad2c5245p-997, 0x1.026c211219d94p-997, 0x1.026817619590dp-997, 0x1.02640dc1380a8p-997, 0x1.026004310105ap-997, 0x1.025bfab0f0419p-997, 0x1.0257f141057ddp-997, 0x1.0253e7e14079cp-997, 0x1.024fde91a0f4cp-997, 0x1.024bd55226ae4p-997, 0x1.0247cc22d165ap-997, 0x1.0243c303a0da6p-997, 0x1.023fb9f494cbdp-997, 0x1.023bb0f5acf98p-997, 0x1.0237a806e922dp-997, 0x1.02339f2849073p-997, 0x1.022f9659cc66p-997, 0x1.022b8d9b72fedp-997, 0x1.022784ed3c911p-997, 0x1.02237c4f28dc1p-997, 0x1.021f73c1379f7p-997, 0x1.021b6b43689a9p-997, 0x1.021762d5bb8cfp-997, 0x1.02135a783036p-997, 0x1.020f522ac6554p-997, 0x1.020b49ed7daa3p-997, 0x1.020741c055f43p-997, 0x1.020339a34ef2ep-997, 0x1.01ff31966865ap-997, 0x1.01fb2999a20cp-997, 0x1.01f721acfba57p-997, 0x1.01f319d074f18p-997, 0x1.01ef12040dafbp-997, 0x1.01eb0a47c59f8p-997, 0x1.01e7029b9c806p-997, 0x1.01e2faff9211fp-997, 0x1.01def373a613bp-997, 0x1.01daebf7d8451p-997, 0x1.01d6e48c2865bp-997, 0x1.01d2dd3096351p-997, 0x1.01ced5e52172bp-997, 0x1.01cacea9c9de3p-997, 0x1.01c6c77e8f371p-997, 0x1.01c2c063713cdp-997, 0x1.01beb9586faf1p-997, 0x1.01bab25d8a4d5p-997, 0x1.01b6ab72c0d72p-997, 0x1.01b2a498130c2p-997, 0x1.01ae9dcd80abdp-997, 0x1.01aa97130975dp-997, 0x1.01a69068ad29bp-997, 0x1.01a289ce6b86fp-997, 0x1.019e8344444d4p-997, 0x1.019a7cca373c3p-997, 0x1.0196766044135p-997, 0x1.019270066a924p-997, 0x1.018e69bcaa78ap-997, 0x1.018a63830385fp-997, 0x1.01865d597579ep-997, 0x1.0182574000141p-997) > > require(sfsmisc) # for relErrV(), eaxis() > ## relative error of x ^ k computation - comparing with truth = relEP <- function(x, k, precBits, # see below about precBits needed + mp = mpfr(x, precBits)^k, + FN = function(x,k) x^k) { + stopifnot(is.numeric(x), inherits(mp, "mpfr")) + asNumeric(relErrV(mp, FN(x,k))) + } > > (osV <- abbreviate(gsub("[^[:alnum:]]", '', sub("\\(.*", '', osVersion)), 12)) WindowsServer2022x64 "WndwsS202264" > if(!dev.interactive(TRUE)) pdf(paste0("pow-tst_", osV, ".pdf"), + width = 9, height=5) > > stopifnot(.Machine$double.xmin == 2^-1022) # will use 2^-1022 > > re1. <- relEP(p1, k1, precBits = 2^12) # high precision > re1 <- relEP(p1, k1, precBits = 256) > stopifnot(re1. == re1) # ===> 256 bit suffice here > summary(re1) Min. 1st Qu. Median Mean 3rd Qu. Max. -2.105e-16 -1.404e-16 -1.012e-16 -1.022e-16 -6.464e-17 5.573e-18 > summary(abs(re1)) Min. 1st Qu. Median Mean 3rd Qu. Max. 2.172e-18 6.464e-17 1.012e-16 1.023e-16 1.404e-16 2.105e-16 > > re1pow <- relEP(p1, k1, precBits = 256, FN = pow) > re1pdi <- relEP(p1, k1, precBits = 256, FN = pow_di) > stopifnot(identical(re1pow, re1pdi))# because pow() smartly uses pow_di() here > ## however > all.equal(re1, re1pdi, tolerance = 0) # 2201.618 !! [1] "Mean relative difference: 886.8181" > summary(re1pdi) # negatively biased ! Min. 1st Qu. Median Mean 3rd Qu. Max. -9.179e-14 -9.111e-14 -9.081e-14 -9.079e-14 -9.047e-14 -8.992e-14 > ## Min. 1st Qu. Median Mean 3rd Qu. Max. > ## -9.179e-14 -9.106e-14 -9.070e-14 -7.740e-14 -9.025e-14 0.000e+00 > plot(k1, re1pdi, type="l"); abline(v = min(k1[p1^k1 < 2^-1022]), lty=3) Warning message: In min(k1[p1^k1 < 2^-1022]) : no non-missing arguments to min; returning Inf > > re1pow <- relEP(p1, k1, precBits = 256, FN = .pow) > summary(re1pow) Min. 1st Qu. Median Mean 3rd Qu. Max. -2.105e-16 -1.404e-16 -1.012e-16 -1.022e-16 -6.464e-17 5.573e-18 > ## Min. 1st Qu. Median Mean 3rd Qu. Max. (Linux Fedora 38): > ## -1.070e-16 -3.082e-17 0.000e+00 7.063e-19 3.507e-17 1.075e-16 > > ## Explore more about pow_di()'s "flaw" > k1. <- c(2:64, as.integer(unique(round(lseq(66, 44980, length = 1000))))) > re1.pdi <- relEP(p1, k1., precBits = 256, FN = pow_di) > plot(k1., re1.pdi, type="l", log="x", xaxt="n", + main = "rel.error {wrt MPFR} of (63/64)^k -- using R_pow_di()") > abline(h=0, lty=3); eaxis(1, sub10=3) > > plot(k1., re1.pdi, type="o", cex=1/4, log="x", ylim = c(-50, 2)*2^-53, xaxt="n", + main = "rel.error of (63/64)^k -- R_pow_di() -- zoomed in") > abline(h=(-2:2)*2^-53, lty=c(3,3,1), col=adjustcolor(1, 1/2)); eaxis(1, sub10=3) > > all.equal(p1^k1., pow(p1, k1., FALSE), tolerance=0) # TRUE (everywhere?) [1] TRUE > > ## comparison: R's x^y i.e. R_pow() is *much* better -- starting already at ca k >= 50 (for this x=p1): > plot(k1., abs(re1.pdi), type="l", log="xy", yaxt="n", ylim = c(1e-17, max(abs(re1.pdi))), + xlab = quote(k), main = "|rel.error| {wrt MPFR} of"~ (frac(63,64))^k) Warning message: In xy.coords(x, y, xlabel, ylabel, log) : 7 y values <= 0 omitted from logarithmic plot > lines(k1., abs(relEP(p1, k1., 256)), col = adjustcolor(2, 1/2)) > legend("top", paste("using", c("R_pow_di(x,k)", "x ^ k")), lwd = 1, + col = c(palette()[[1]], adjustcolor(2, 1/2)), bty="n") > eaxis(2); drawEps.h(); abline(h = 8e-18, col=adjustcolor(4, 1/2), lwd=2) > rug(k1.[k1. <= 50], col="gray30") > > plot(k1, re1, type="l", main = "rel.error {wrt MPFR} of (63/64)^k") > mtextVersion() > abline(v = min(k1[p1^k1 < 2^-1022]), lty=3) Warning message: In min(k1[p1^k1 < 2^-1022]) : no non-missing arguments to min; returning Inf > ll <- c(1,1,2,1,1) > abline(h=(-2:2)*2^-53, lty=3-ll, lwd=ll, col=adjustcolor(ll, 1/2)) > ## looks perfect (in Linux; *not* windows > > ## ditto (pow_di exploration) for an even more critical p > p1 <- 0.999 # not exactly representable > print(p1, digits=19) [1] 0.9989999999999999991 > k <- c(2:50, as.integer(lseq(55, 700000, length=1000))) > pk <- p1^k > tail(cbind(k, pk)) k pk [1044,] 667657 7.855476e-291 [1045,] 674004 1.371912e-293 [1046,] 680411 2.256365e-296 [1047,] 686879 3.491300e-299 [1048,] 693408 5.082294e-302 [1049,] 700000 6.946374e-305 > plot(pk ~ k, type = "l", log="xy") > re.pdi <- relEP(p1, k, precBits = 256, FN = pow_di) > > plot(k, abs(re.pdi), type="l", log="xy", xaxt="n", yaxt="n", ylim = c(1e-17, max(abs(re.pdi))), + xlab = quote(k), main = substitute(abs(rel.error) ~~ "of" ~~ P^k, list(P = format(p1)))) > lines(k, abs(relEP(p1, k, 256)), col = adjustcolor(2, 1/2)) > legend("top", paste("using", c("R_pow_di(x,k)", "x ^ k")), lwd = 1, + col = c(palette()[[1]], adjustcolor(2, 1/2)), bty="n") > eaxis(1, sub=3); eaxis(2); drawEps.h(); abline(h = 8e-18, col=adjustcolor(4, 1/2), lwd=2) > rug(k[k <= 50], col="gray30") > axis(1, at=2:6) > mtextVersion() > > ## finaly: pow_di exploration an "easy" p: > p1 <- 0.001 # not exactly representable > k <- 2:105 > pk <- p1^k > tail(cbind(k, pk)) # subnormals .. k pk [99,] 100 1e-300 [100,] 101 1e-303 [101,] 102 1e-306 [102,] 103 1e-309 [103,] 104 1e-312 [104,] 105 1e-315 > plot(pk ~ k, type = "l", log="xy") > re.pdi <- relEP(p1, k, precBits = 256, FN = pow_di) > > plot(k, abs(re.pdi), type="l", log="xy", xaxt="n", yaxt="n", ylim = c(1e-17, max(abs(re.pdi))), + xlab = quote(k), main = substitute(abs(rel.error) ~~ "of" ~~ P^k, list(P = format(p1)))) > lines(k, abs(relEP(p1, k, 256)), col = adjustcolor(2, 1/2)) > legend("top", paste("using", c("R_pow_di(x,k)", "x ^ k")), lwd = 1, + col = c(palette()[[1]], adjustcolor(2, 1/2)), bty="n") > eaxis(1, sub=3); eaxis(2); drawEps.h(); abline(h = 8e-18, col=adjustcolor(4, 1/2), lwd=2) > rug(k, col="gray30") > axis(1, at=2:6) > mtextVersion() > > > re2 <- relEP(p2, k2, 2^ 9) > re2. <- relEP(p2, k2, 2^14) > stopifnot(re2. == re2) > summary(re2) Min. 1st Qu. Median Mean 3rd Qu. Max. 1.268e-15 1.335e-15 1.380e-15 1.378e-15 1.419e-15 1.482e-15 > summary(abs(re2)) Min. 1st Qu. Median Mean 3rd Qu. Max. 1.268e-15 1.335e-15 1.380e-15 1.378e-15 1.419e-15 1.482e-15 > > str(rat2 <- c(MASS:::.rat(p2) $ rat)) num [1:2] 1023 1024 > plot(k2, re2, type="l", xlab = quote(k), main = substitute("rel.Err of " ~ (N/Z)^k, + list(N=rat2[1], Z=rat2[2])), + ylim = range(0, re2)) > if(any((px <- p2^k2) < 2^-1022)) abline(v = min(k2[px < 2^-1022]), lty=3) > abline(h=(-2:2)*2^-53, lty=3-ll, lwd=ll, col=adjustcolor(ll, 1/2)) > > re3 <- relEP(p3, k3, prec = 256) > summary(re3) Min. 1st Qu. Median Mean 3rd Qu. Max. 1.475e-14 1.480e-14 1.485e-14 1.485e-14 1.491e-14 1.496e-14 > str(rat3 <- c(MASS:::.rat(p3, max.denominator=1e5) $ rat)) num [1:2] 16383 16384 > > plot(k3, re3, type="l", xlab = quote(k), ylim = range(0, re3), + main = substitute("rel.Err of " ~ (N/Z)^k, list(N=rat3[1], Z=rat3[2]))) > if(any((px <- p3^k3) < 2^-1022)) abline(v = min(k3[px < 2^-1022]), lty=3) > abline(h=(-2:2)*2^-53, lty=3-ll, lwd=ll, col=adjustcolor(ll, 1/2)) > > ##===> all these are perfect on Linux Fedora 36 & 38; > ## but increasingly (p1 --> p2 --> p3) worse on Windows > > ## even more extreme > e2 <- -(10:21) > ps <- 1 - 2 ^ e2 > (pM <- 1 - mpfr(2, 256) ^ e2) # 12 'mpfr' numbers of precision 256 bits 12 'mpfr' numbers of precision 256 bits [1] 0.9990234375 0.99951171875 0.999755859375 0.9998779296875 [5] 0.99993896484375 0.999969482421875 0.9999847412109375 0.99999237060546875 [9] 0.999996185302734375 0.9999980926513671875 0.99999904632568359375 0.999999523162841796875 > ## 0.9990234375 0.99951171875 ... 0.999999523162841796875 > stopifnot( (1 - ps) -1 == -ps, ps == pM) ## <==> all ps are exactly representable 1 - 2^{-m} > > print(pM, scientific = FALSE, drop0trailing = TRUE) 12 'mpfr' numbers of precision 256 bits [1] 0.9990234375 0.99951171875 0.999755859375 0.9998779296875 [5] 0.99993896484375 0.999969482421875 0.9999847412109375 0.99999237060546875 [9] 0.999996185302734375 0.9999980926513671875 0.99999904632568359375 0.999999523162841796875 > > > ## The range of interesting k -- such that > ## ps^k does *not* underflow (in double prec) but *is* ~= 10^{-300}: > (ks <- as.integer(round( log(1e-300)/ log(ps) ))) [1] 707009 1414363 2829071 5658488 11317321 22634987 45270320 90540985 [9] 181082315 362164975 724330295 1448660934 > ## [1] 707009 1414363 2829071 5658488 11317321 22634987 45270320 > ## [8] 90540985 181082315 362164975 724330295 1448660934 > (k0 <- as.integer(signif(ks, 4))) [1] 707000 1414000 2829000 5658000 11320000 22630000 45270000 90540000 [9] 181100000 362200000 724300000 1449000000 > > cbind(psN <- setNames(seq_along(ps), paste0("1-2^",e2))) [,1] 1-2^-10 1 1-2^-11 2 1-2^-12 3 1-2^-13 4 1-2^-14 5 1-2^-15 6 1-2^-16 7 1-2^-17 8 1-2^-18 9 1-2^-19 10 1-2^-20 11 1-2^-21 12 > reL <- lapply(psN, function(i) relEP(ps[i], k0[i] + 0:999, precBits = 2^8)) > ## can use names(reL) to reconstruct ps exactly: > stopifnot(identical(ps, vapply(lapply(names(reL), str2lang), eval, 0.9))) > if(doExtras) { ## much higher precision -- just to show it's *not* needed + print(system.time( + reLL <- lapply(psN, function(i) relEP(ps[i], k0[i] + 0:999, precBits = 2^ 14)) + )) # 2.407 sec + stopifnot(all.equal(reL, reLL, tolerance = 0)) # exactly the same + } > > absreL <- lapply(reL, abs) > t(sapply(reL, summary)) Min. 1st Qu. Median Mean 3rd Qu. Max. 1-2^-10 1.280447e-15 1.349201e-15 1.394657e-15 1.391766e-15 1.431874e-15 1.500609e-15 1-2^-11 2.670517e-15 2.743236e-15 2.785959e-15 2.783925e-15 2.826796e-15 2.889592e-15 1-2^-12 -3.078755e-15 -3.026682e-15 -2.978716e-15 -2.978479e-15 -2.932214e-15 -2.874825e-15 1-2^-13 -1.226433e-14 -1.221933e-14 -1.217776e-14 -1.217671e-14 -1.213259e-14 -1.209147e-14 1-2^-14 1.475064e-14 1.480261e-14 1.485386e-14 1.485506e-14 1.490780e-14 1.495633e-14 1-2^-15 1.858175e-14 1.861723e-14 1.865487e-14 1.865398e-14 1.868825e-14 1.872753e-14 1-2^-16 9.337607e-15 9.379792e-15 9.421699e-15 9.420715e-15 9.462557e-15 9.504124e-15 1-2^-17 -1.849254e-13 -1.848816e-13 -1.848382e-13 -1.848413e-13 -1.848018e-13 -1.847590e-13 1-2^-18 -1.280356e-13 -1.279937e-13 -1.279501e-13 -1.279491e-13 -1.279062e-13 -1.278583e-13 1-2^-19 -3.789652e-13 -3.789186e-13 -3.788728e-13 -3.788747e-13 -3.788312e-13 -3.787879e-13 1-2^-20 -6.530429e-13 -6.530030e-13 -6.529615e-13 -6.529630e-13 -6.529222e-13 -6.528822e-13 1-2^-21 4.054088e-13 4.054558e-13 4.055043e-13 4.055048e-13 4.055534e-13 4.056033e-13 > t(sapply(absreL, summary)) # very nice on Linux: Min. 1st Qu. Median Mean 3rd Qu. Max. 1-2^-10 1.280447e-15 1.349201e-15 1.394657e-15 1.391766e-15 1.431874e-15 1.500609e-15 1-2^-11 2.670517e-15 2.743236e-15 2.785959e-15 2.783925e-15 2.826796e-15 2.889592e-15 1-2^-12 2.874825e-15 2.932214e-15 2.978716e-15 2.978479e-15 3.026682e-15 3.078755e-15 1-2^-13 1.209147e-14 1.213259e-14 1.217776e-14 1.217671e-14 1.221933e-14 1.226433e-14 1-2^-14 1.475064e-14 1.480261e-14 1.485386e-14 1.485506e-14 1.490780e-14 1.495633e-14 1-2^-15 1.858175e-14 1.861723e-14 1.865487e-14 1.865398e-14 1.868825e-14 1.872753e-14 1-2^-16 9.337607e-15 9.379792e-15 9.421699e-15 9.420715e-15 9.462557e-15 9.504124e-15 1-2^-17 1.847590e-13 1.848018e-13 1.848382e-13 1.848413e-13 1.848816e-13 1.849254e-13 1-2^-18 1.278583e-13 1.279062e-13 1.279501e-13 1.279491e-13 1.279937e-13 1.280356e-13 1-2^-19 3.787879e-13 3.788312e-13 3.788728e-13 3.788747e-13 3.789186e-13 3.789652e-13 1-2^-20 6.528822e-13 6.529222e-13 6.529615e-13 6.529630e-13 6.530030e-13 6.530429e-13 1-2^-21 4.054088e-13 4.054558e-13 4.055043e-13 4.055048e-13 4.055534e-13 4.056033e-13 > ## Min. 1st Qu. Median Mean 3rd Qu. Max. > ## 1-2^-10 4.698362e-20 1.991498e-17 4.117806e-17 4.292841e-17 6.362789e-17 1.085069e-16 > ## 1-2^-11 2.644379e-20 2.143401e-17 4.148793e-17 4.352628e-17 6.504935e-17 1.048650e-16 > ## 1-2^-12 5.185148e-21 2.465148e-17 4.910034e-17 4.719418e-17 6.823981e-17 1.001215e-16 > ## 1-2^-13 1.732619e-19 2.110998e-17 4.188601e-17 4.175295e-17 6.264898e-17 8.759273e-17 > ## 1-2^-14 1.028253e-19 2.692311e-17 5.463435e-17 5.234885e-17 7.736664e-17 1.027465e-16 > ## 1-2^-15 2.173905e-20 1.919186e-17 3.737047e-17 3.683430e-17 5.442273e-17 7.258842e-17 > ## 1-2^-16 7.547357e-20 1.964997e-17 4.034049e-17 4.078038e-17 6.051778e-17 8.354223e-17 > ## 1-2^-17 6.468787e-20 2.113894e-17 4.282366e-17 4.184208e-17 6.196293e-17 8.264685e-17 > ## 1-2^-18 3.053764e-20 2.343907e-17 4.581431e-17 4.515700e-17 6.764085e-17 8.893000e-17 > ## 1-2^-19 3.693339e-20 1.922513e-17 4.318434e-17 4.283787e-17 6.588232e-17 8.900600e-17 > ## 1-2^-20 5.398257e-20 2.190955e-17 4.092451e-17 4.095826e-17 6.083059e-17 8.062014e-17 > ## 1-2^-21 4.708387e-20 2.429069e-17 4.717160e-17 4.758539e-17 7.079720e-17 9.742768e-17 > > d.absre <- as.data.frame(absreL, optional=TRUE) > stopifnot(is.numeric(m.absrel <- as.matrix(d.absre))) > if(doExtras) { # not particularly interesting .. + matplot(0:999, m.absrel, type="l", log="y", ylim = c(1e-17, max(m.absrel))) + drawEps.h(lty=2) + # + ## smoothed rel.errors + s.absre <- d.absre + s.absre[] <- lapply(absreL, function(y) lowess(y, f = 1/20)$y) + matlines(0:999, s.absre, lwd=3, col = adjustcolor(1:12, 1/2)) + } > > ## different "log-scale" k sets for different ps / ks: > k2p <- lapply(setNames(ks, names(psN)), \(k) + as.integer(2^seq(7, floor(log2(k)), by = 1/8))) > stopifnot( sapply(k2p, is.integer) ) # -> so pow_di() / __powi() .. could be used > reL2 <- lapply(psN, function(i) relEP(ps[i], k2p[[i]], precBits = 2^8)) > absre2 <- lapply(reL2, abs) > > K <- length(ks) # 12 here > > plot(k2p[[K]], reL2[[K]], type = "l", log = "x", col=K, + xlab = quote(k), ylab = "relErr{ p ^ k }", + ylim = range((-1:1)*2^-53, unlist(reL2)), xaxt="n"); eaxis(1) > for(i in rev(seq_along(ks))[-1L]) + lines(k2p[[i]], reL2[[i]], col=i) > abline(h = (-2:2)*2^-53, lty=c(3,3,2,3,3), lwd=c(1,1,2,1,1), col=adjustcolor(c(1,1,2,1,1), 1/2)) > > plot(k2p[[K]], absre2[[K]], type = "l", log = "xy", col=K, + xlab = quote(k), ylab = "|relE|", main = expression(abs(rel.Err( p ^ k ))), + ylim = range(2^-53, pmax(8e-18, unlist(absre2))), xaxt="n", yaxt="n"); eaxis(1); eaxis(2) > (pExpr <- as.call(c(quote(list), lapply(names(k2p), str2lang)))) list(1 - 2^-10, 1 - 2^-11, 1 - 2^-12, 1 - 2^-13, 1 - 2^-14, 1 - 2^-15, 1 - 2^-16, 1 - 2^-17, 1 - 2^-18, 1 - 2^-19, 1 - 2^-20, 1 - 2^-21) > mtext(substitute(p == group("{", EE, "}"), list(EE = pExpr)), cex= 2/3) > for(i in rev(seq_along(ks))[-1L]) + lines(k2p[[i]], absre2[[i]], col=i) > drawEps.h(lty=3, lwd=2) > ## looks perfect (in Linux; *not* windows > > t(sapply(absre2, summary)) Min. 1st Qu. Median Mean 3rd Qu. Max. 1-2^-10 9.390336e-19 2.346296e-17 5.335712e-17 1.441629e-16 1.342227e-16 9.784937e-16 1-2^-11 4.641186e-19 3.282452e-17 7.167211e-17 2.609528e-16 2.482842e-16 1.976921e-15 1-2^-12 2.868086e-19 2.748112e-17 5.638903e-17 2.564391e-16 2.393033e-16 2.212747e-15 1-2^-13 1.669060e-19 3.489569e-17 7.429264e-17 9.099490e-16 5.979160e-16 8.969010e-15 1-2^-14 4.684314e-19 2.672919e-17 7.947764e-17 1.044787e-15 6.875389e-16 1.098898e-14 1-2^-15 5.037089e-20 3.045571e-17 6.374634e-17 1.232263e-15 7.890786e-16 1.388033e-14 1-2^-16 3.167997e-19 2.161611e-17 4.928212e-17 5.970448e-16 2.882474e-16 7.062778e-15 1-2^-17 9.995104e-19 3.067666e-17 2.011080e-16 1.079877e-14 5.103947e-15 1.370574e-13 1-2^-18 6.595734e-19 3.191051e-17 1.078896e-16 7.108505e-15 2.940018e-15 9.487097e-14 1-2^-19 4.170203e-19 3.588180e-17 1.818854e-16 2.002418e-14 7.360301e-15 2.807288e-13 1-2^-20 7.930429e-22 3.537090e-17 2.548155e-16 3.295712e-14 1.064094e-14 4.840320e-13 1-2^-21 1.651936e-19 3.257837e-17 8.943541e-17 1.958272e-14 5.556943e-15 3.004945e-13 > summary(are2 <- unlist(absre2)) Min. 1st Qu. Median Mean 3rd Qu. Max. 0.000e+00 3.120e-17 7.450e-17 9.579e-15 1.154e-15 4.840e-13 > > if(.Platform$OS.type == "unix") { # && !noLdbl + stopifnot(m.absrel < 2.23e-16, # see max(.) == 1.085e-16 < 2^-53 = 1.11022e-16 + are2 < 2.23e-16) # see max(.) == 1.032e-16 + } > > ###---- x ^ y -- with *non-integer* y --------------- > > ## keep x = ps { above (1-2^-k) } > > yp <- lapply(setNames(ks, names(psN)), \(k) + 2^seq(7, floor(log2(k)), by = 1/8) - 1/4) # -1/4: sure *not* be int > > reLd <- lapply(psN, function(i) relEP(ps[i], yp[[i]], precBits = 2^8)) > absred <- lapply(reLd, abs) > > K <- length(ks) # 12 here > > plot(yp[[K]], reLd[[K]], type = "l", log = "x", col=K, + xlab = quote(k), ylab = "relErr{ p ^ k }", + ylim = range((-1:1)*2^-53, unlist(reLd)), xaxt="n"); eaxis(1) > for(i in rev(seq_along(ks))[-1L]) + lines(yp[[i]], reLd[[i]], col=i) > abline(h = (-2:2)*2^-53, lty=c(3,3,2,3,3), lwd=c(1,1,2,1,1), col=adjustcolor(c(1,1,2,1,1), 1/2)) > > palROBG <- colorRampPalette(c("red", "darkorange2", "blue", "seagreen"), space = "Lab") > palette(adjustcolor(palROBG(12), 3/4)) > ## pmax(.) for 'y': to "show" the '0' also > plot(yp[[K]], pmax(1e-20, absred[[K]]), type = "l", log = "xy", col=K, + xlab = quote(y), ylab = "|relE|", main = quote(list(abs(rel.Err( x ^ y )), y~"*not* integer")), + ylim = range(2^-53, pmax(8e-18, unlist(absred))), xaxt="n"); eaxis(1, sub10=3) > mtext(substitute(x == group("{", EE, "}"), list(EE = pExpr)), cex= 2/3) > for(i in rev(seq_along(ks))[-1L]) + lines(yp[[i]], absred[[i]], col=i) > abline(h = c(1,2,4)*2^-53, lty=3, lwd=2, col=adjustcolor(2, 1/2)) > axis(4, las=2, line=-1, at=c(1,2,4)*2^-53, labels = expression(2^-53, 2^-52, 2^-51), + col.axis=adjustcolor(2, 1/2), col=NA, col.ticks=NA) > legend("bottomright", legend=do.call(expression, as.list(pExpr[-1])), + col=palette(), lwd=3, cex=2/3) > palette("default")# revert > ## looks perfect (in Linux; *not* Windows) > > t(sapply(absred, summary)) Min. 1st Qu. Median Mean 3rd Qu. Max. 1-2^-10 2.295971e-20 1.832048e-17 3.855744e-17 3.915690e-17 5.467917e-17 8.732578e-17 1-2^-11 6.862345e-19 1.877996e-17 3.510510e-17 3.725985e-17 5.295532e-17 9.126286e-17 1-2^-12 1.074726e-18 1.791156e-17 3.807128e-17 3.924264e-17 5.746482e-17 9.370526e-17 1-2^-13 3.722164e-19 1.405626e-17 3.343672e-17 3.497505e-17 5.113932e-17 9.576086e-17 1-2^-14 1.509081e-19 1.956440e-17 3.444407e-17 3.851610e-17 5.571175e-17 1.010061e-16 1-2^-15 3.707998e-19 1.395077e-17 2.725726e-17 3.390525e-17 5.110957e-17 8.905101e-17 1-2^-16 1.095571e-19 1.549693e-17 3.246712e-17 3.423402e-17 5.057892e-17 9.432710e-17 1-2^-17 3.397116e-19 1.510450e-17 2.837466e-17 3.191959e-17 4.479704e-17 1.040953e-16 1-2^-18 1.299536e-18 1.566903e-17 3.114549e-17 3.376463e-17 4.856218e-17 1.018159e-16 1-2^-19 4.484504e-19 1.506882e-17 3.370768e-17 3.443235e-17 4.969964e-17 1.033987e-16 1-2^-20 4.724846e-20 1.685262e-17 3.291611e-17 3.499646e-17 5.254457e-17 9.747515e-17 1-2^-21 6.103077e-19 1.718093e-17 3.248586e-17 3.437850e-17 4.887190e-17 9.572765e-17 > c(summary(ared <- unlist(absred))) Min. 1st Qu. Median Mean 3rd Qu. Max. 2.295971e-20 1.662607e-17 3.319100e-17 3.525278e-17 5.113847e-17 1.040953e-16 > > if(.Platform$OS.type == "unix") { # && !noLdbl + stopifnot(ared < 2.23e-16) # see max(.) == 1.033987e-16 < 2^-53 + } > > > proc.time() user system elapsed 1.92 0.09 2.00