diff --git "a/data/maple/data.json" "b/data/maple/data.json" new file mode 100644--- /dev/null +++ "b/data/maple/data.json" @@ -0,0 +1,100 @@ +{"size":1234,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"#You can also play with deg\ndeg:=2:\nfor n from 4 to 10 do \n for s from 2 to n-1 do \n vars:=[seq(cat(x,i),i=1..n)]:\n f:=expand(add(randpoly(vars,degree=deg)^2,i=1..s)):\n\n #To decompose\n F:=[f, seq(diff(f,v), v in vars[2..n])]:\n\n# rr:=rand(1..512):\n# l:=add(rr()*v, v in vars):\n\n# J:=linalg:-jacobian([f,l], vars):\n# J:=convert(J, Matrix):\n# with(LinearAlgebra):\n# lcols:=combinat:-choose(n, 2):\n\n# #To decompose\n# F1:=[f, seq(Determinant(SubMatrix(J, [1,2], cols)), cols in lcols)]:\n\n str:=cat(\".\/soscritpoints_deg_\", deg, \"_nvars_\", n, \"_s_\",s,\".jl\");\n fd:=fopen(str, WRITE):\n fprintf(fd, \"using SignatureGB\\n\");\n fprintf(fd, \"using Singular\\n\");\n fprintf(fd, \"P, (%a, \", vars[1]);\n for j from 2 to n-1 do\n fprintf(fd, \"%a, \", vars[j]);\n od:\n fprintf(fd, \"%a) = Singular.PolynomialRing(Fp(65521), [\", vars[n]);\n for j from 1 to n-1 do\n fprintf(fd, \"\\\"%a\\\", \", vars[j]);\n od:\n fprintf(fd, \"\\\"%a\\\"]);\\n\", vars[n]);\n fprintf(fd, \"gb = SignatureGB.f5(%a);\", vars[1..n]);\n\n fprintf(fd, \"F = %a;\\n\", F);\n fprintf(fd, \"sort!(F, by = p -> leading_monomial(p))\\n\");\n fprintf(fd, \"println(@elapsed SignatureGB.f5(F, verbose=true));\");\n fprintf(fd, \"exit()\\n\");\n fclose(fd):\n od:\nod:\n","avg_line_length":28.0454545455,"max_line_length":71,"alphanum_fraction":0.556726094} +{"size":9026,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":82.8073394495,"max_line_length":145,"alphanum_fraction":0.7383115444} +{"size":4339,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"######################################\n# Implementation of the lapse choices\n# in standard G-BSSN\n# Gamma drive and 1 + log\n# Also some experimental other lapse\n# choices\n######################################\n\nread \"\/home\/arman\/FD\/FD.mpl\":\n\nCFD();\nMFD();\n\ngrid_functions:= {alpha,K,beta,Lamx,DLamx,BB,ctfmp};\n\n# A generalization of 1 + log\neq1 := diff(alpha(t,x),t) = -gma*alpha(t,x)^gmb*K(t,x);\n\nAVGT := f -> (FD(f,[[1],[0,0,0]]) + FD(f,[[0],[0,0,0]]))\/2 ;\nFD_table[t] := [ [0] , [0,1] ];\n\n\nspec := [ \n { i = [1,1,1] , b=xmin } = Gen_Sten(lhs(eq1)) - AVGT(Gen_Sten(rhs(eq1))) ,\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq1)) - AVGT(Gen_Sten(rhs(eq1))),\n { i=[Nx,Nx,1], b=xmax } = alpha(n+1,i) + myzero*x(i) - 1\n];\n\n\nA_Gen_Solve_Code(spec,{alpha(n+1,i)},proc_name=\"evol_alphaopl\");\nA_Gen_Res_Code(spec,input=\"d\",proc_name=\"resid_alphaopl\");\n\n# Some kinda generalization of 1 + log\neq2:= diff(alpha(t,x),t) + epsal*diff(K(t,x),t) = -epsal*ck*K(t,x);\n\n\n\nspec2 := [ \n { i = [1,1,1] , b=xmin } = Gen_Sten(lhs(eq2)) - AVGT(Gen_Sten(rhs(eq2))) ,\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq2)) - AVGT(Gen_Sten(rhs(eq2))),\n { i=[Nx,Nx,1], b=xmax } = alpha(n+1,i) + myzero*x(i) - 1\n];\n\n\nA_Gen_Solve_Code(spec2,{alpha(n+1,i)},proc_name=\"evol_alphakd\");\nA_Gen_Res_Code(spec2,input=\"d\",proc_name=\"resid_alphakd\");\n\n\n# This is gamma drive\n\neq3 := diff(beta(t,x),t) = mus*Lamx(t,x) - eta*beta(t,x);\neq4 := diff(alpha(t,x),t) = -2*alpha(t,x)*K(t,x);\n\nspec := [ \n { i = [1,1,1] , b=xmin } = Gen_Sten(lhs(eq4)) - AVGT(Gen_Sten(rhs(eq4))) ,\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq4)) - AVGT(Gen_Sten(rhs(eq4))),\n { i=[Nx,Nx,1], b=xmax } = alpha(n+1,i) + myzero*x(i) - 1\n];\n\n\nA_Gen_Solve_Code(spec,{alpha(n+1,i)},proc_name=\"evol_alphadyopl\");\nA_Gen_Res_Code(spec,input=\"d\",proc_name=\"resid_alphadyopl\");\n\n\nspec := [ \n { i = [1,1,1] , b=xmin } = Gen_Sten(lhs(eq3)) - AVGT(Gen_Sten(rhs(eq3))) ,\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq3)) - AVGT(Gen_Sten(rhs(eq3))),\n { i=[Nx,Nx,1], b=xmax } = beta(n+1,i) + myzero*x(i) \n];\n\nA_Gen_Solve_Code(spec,{beta(n+1,i)},proc_name=\"evol_betagd\");\nA_Gen_Res_Code(spec,input=\"d\",proc_name=\"resid_betagd\");\n\n\n# Some strange driver, for testing\neq5 := diff(beta(t,x),t) = mus*diff(K(t,x),x) - eta*beta(t,x);\n\nspec := [ \n { i = [1,1,1] , b=xmin } = beta(n+1,i) + myzero*x(i) ,\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq5)) - AVGT(Gen_Sten(rhs(eq5))),\n { i=[Nx,Nx,1], b=xmax } = beta(n+1,i) + myzero*x(i) \n];\n\nA_Gen_Solve_Code(spec,{beta(n+1,i)},proc_name=\"evol_betakd\");\nA_Gen_Res_Code(spec,input=\"d\",proc_name=\"resid_betakd\");\n\n\n# More playing around with shift condition\neq6:= diff(beta(t,x),t) + epsal*diff(Lamx(t,x),t) = -epsal*ck*Lamx(t,x);\n\n\nspec2 := [ \n { i = [1,1,1] , b=xmin } = Gen_Sten(lhs(eq6)) - AVGT(Gen_Sten(rhs(eq6))) ,\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq6)) - AVGT(Gen_Sten(rhs(eq6))),\n { i=[Nx,Nx,1], b=xmax } = beta(n+1,i) + myzero*x(i)\n];\n\n\nA_Gen_Solve_Code(spec2,{beta(n+1,i)},proc_name=\"evol_betagd2\");\nA_Gen_Res_Code(spec2,input=\"d\",proc_name=\"resid_betagd2\");\n\n\neq7 := diff(beta(t,x),t) = advc*beta(t,x)*diff(beta(t,x),x)\/ctfmp(x) + mus*BB(t,x); \neq8 := diff(BB(t,x),t) = advc*beta(t,x)*diff(BB(t,x),x)\/ctfmp(x) - eta*BB(t,x) + DLamx(t,x);\neq9 := diff(alpha(t,x),t) = advc*beta(t,x)*diff(alpha(t,x),x)\/ctfmp(x) - 2*alpha(t,x)*K(t,x);\n\nspec := [ \n { i = [1,1,1] , b=xmin } = beta(n+1,i)+myzero*x(i) ,\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq7)) - AVGT(Gen_Sten(rhs(eq7))),\n { i=[Nx,Nx,1], b=xmax } = beta(n+1,i) + myzero*x(i)\n];\n\nA_Gen_Solve_Code(spec,{beta(n+1,i)},proc_name=\"evol_beta_hgd_adv\");\nA_Gen_Res_Code(spec,input=\"d\",proc_name=\"resid_beta_hgd_adv\");\n\n\nspec := [ \n { i = [1,1,1] , b=xmin } = BB(n+1,i)+myzero*x(i) ,\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq8)) - AVGT(Gen_Sten(rhs(eq8))),\n { i=[Nx,Nx,1], b=xmax } = BB(n+1,i) + myzero*x(i)\n];\n\nA_Gen_Solve_Code(spec,{BB(n+1,i)},proc_name=\"evol_BB_hgd_adv\");\nA_Gen_Res_Code(spec,input=\"d\",proc_name=\"resid_BB_hgd_adv\");\n\nspec := [ \n { i = [1,1,1] , b=xmin } = Gen_Sten(lhs(eq9)) - AVGT(Gen_Sten(rhs(eq9))),\n { i = [2,Nx-1,1] } = Gen_Sten(lhs(eq9)) - AVGT(Gen_Sten(rhs(eq9))),\n { i=[Nx,Nx,1], b=xmax } = alpha(n+1,i) - 1 + myzero*x(i)\n];\n\nA_Gen_Solve_Code(spec,{alpha(n+1,i)},proc_name=\"evol_alpha_hgd_adv\");\nA_Gen_Res_Code(spec,input=\"d\",proc_name=\"resid_alpha_hgd_adv\");\n\n\n","avg_line_length":31.9044117647,"max_line_length":93,"alphanum_fraction":0.5768610279} +{"size":509409,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"F5020 := [32.45540025*x+108.1628693*x^2+31.92099366*x^3-41.52716889*x^4-51.551\\\n75705*x^5-122.7098640*x^6-89.91448597*x^7-22.37954396*x^8+22.38839872*x^9-19.7\\\n7983325*x^10+85.63799122*x^11-139.9131582*x^12+46.95629587*x^13+115.3861434*x^\n14-130.6933326*x^15-29.67942264*x^16+124.0394750*x^17+214.8554825*x^18+257.207\\\n3656*x^19-73.91559225*x^20-222.9470565*x^21-64.15343183*x^22+138.1997297*x^23-\\\n182.9544081*x^24+183.2404509*x^25+109.6619594*x^26-153.6530852*x^27+127.076891\\\n9*x^28-238.8868087*x^29-81.56753203*x^30-27.95616905+.8635728226*x^31-218.3027\\\n726*x^32+205.3044349*x^33+119.6808922*x^34+21.13609609*x^35+27.98822224*x^36-\\\n29.18956035*x^37-133.8468424*x^38-26.62138844*x^39+116.5567866*x^40-122.565053\\\n0*x^41+256.7719422*x^42-20.50494351*x^43-129.7882493*x^44+203.1999103*x^45-150\\\n.5206085*x^46-18.90618246*x^47+5.642804984*x^48-96.30480319*x^49+83.19495987*x\n^50, -75.22408573*x+46.47854820*x^2+31.11887490*x^3-60.76365678*x^4+4.82170566\\\n4*x^5+7.330203677*x^6+21.16850745*x^7+44.58605483*x^8+53.21534328*x^9+153.2151\\\n883*x^10+151.7926875*x^11-253.8705798*x^12+4.619590651*x^13-19.77621655*x^14-\\\n22.00638743*x^15-18.87232017*x^16-301.5288880*x^17+239.4255990*x^18+284.780006\\\n7*x^19-13.00663144*x^20+118.5348810*x^21+302.3245169*x^22+209.7562283*x^23+12.\\\n25414589*x^24-114.7706638*x^25+68.10586536*x^26-157.4815558*x^27-108.3656983*x\n^28-66.98975532*x^29-.8283475275*x^30+96.42394565*x^31-261.9533426*x^32-244.67\\\n17880*x^33+7.511236601*x^34-11.85508925*x^35-260.7337203*x^36-300.2712910*x^37\n+39.08961665*x^38+56.41688904*x^39-214.4796188*x^40-255.6976193*x^41-103.01600\\\n34*x^42-54.89286979*x^43-41.77641503*x^44-149.1637754*x^45-104.6340208*x^46+1.\\\n376459068*x^47-3.968996200*x^48-58.20616183*x^49-64.97196551*x^50+17.60515737,\n11.40670289*x-1.389769223*x^2-5.921167662*x^3+1.150353541*x^4+134.3847695*x^5+\n108.6087363*x^6+44.12601687*x^7-53.17268861*x^8+153.1713363*x^9+1.236431120*x^\n10-117.8512850*x^11-36.48323357*x^12+156.7764249*x^13+55.18530707*x^14+61.1751\\\n7887*x^15+165.2696082*x^16+324.4376538*x^17+60.03335094*x^18+122.6252760*x^19+\n159.5603617*x^20+102.2324554*x^21-39.44094704*x^22+127.3609980*x^23+56.3245620\\\n0*x^24-129.0308124*x^25+211.5767571*x^26+65.47531346*x^27-92.71846498*x^28+179\\\n.4332569*x^29+20.42610130*x^30-21.81256713+12.35024583*x^31+262.9028847*x^32-\\\n257.8266903*x^33+213.8670599*x^34+57.29455540*x^35-94.43819421*x^36+105.876025\\\n9*x^37+141.3110557*x^38-224.2306849*x^39+76.57695063*x^40-29.77931827*x^41-183\\\n.3051244*x^42-6.664355044*x^43-149.8557929*x^44-46.10230435*x^45+.7851188769*x\n^46-41.17683226*x^47-56.75705225*x^48+63.73723918*x^49-29.33682899*x^50, 65.47\\\n833024*x+94.39767749*x^2-24.76350202*x^3+86.15721953*x^4+14.92269990*x^5-36.08\\\n493651*x^6+61.92137514*x^7-3.945967005*x^8+25.14499351*x^9+132.2871130*x^10-\\\n145.7909563*x^11+18.55767192*x^12+139.7947544*x^13-196.7484583*x^14+70.5120536\\\n3*x^15+159.6785834*x^16+47.56738927*x^17+120.7686123*x^18-202.1540895*x^19-46.\\\n64347695*x^20+204.3030993*x^21-49.52092459*x^22+40.87066182*x^23+311.2284580*x\n^24-33.67004516*x^25+161.4754889*x^26+47.50952823*x^27-182.5838250*x^28+126.02\\\n92119*x^29-7.638119697*x^30-121.8598505*x^31-109.6175044*x^32-84.85762668*x^33\n-95.71485699*x^34+93.59672075*x^35-255.9182182*x^36-1.124414477*x^37+60.006289\\\n86*x^38-173.4376519*x^39-53.91393415*x^40+174.0260110*x^41+78.36949045*x^42+17\\\n.88491170*x^43+67.05466585*x^44+74.74427442*x^45+151.5290538*x^46-8.587788591*\nx^47+15.70948636*x^48+51.34724982*x^49+6.809282689*x^50+11.46728974, 50.729238\\\n70*x-14.50673501*x^2-13.49370051*x^3+103.5439533*x^4-23.04735344*x^5-62.135205\\\n04*x^6+204.4083943*x^7+5.706959644*x^8-190.3290506*x^9+116.7201310*x^10-44.050\\\n30036*x^11-131.7570366*x^12-59.07870551*x^13-60.18645503*x^14+39.55383245*x^15\n-56.21476773*x^16-168.7778853*x^17+256.9584678*x^18-140.7070162*x^19-343.75240\\\n38*x^20-34.39780551*x^21-27.83112121*x^22-167.4924422*x^23-161.7530358*x^24+\n143.0304016*x^25-118.4496699*x^26-118.4968958*x^27-80.67702841*x^28-7.30642182\\\n2*x^29-229.8993198*x^30-187.7028417*x^31-112.5996394*x^32+58.59062974*x^33-102\\\n.8176639*x^34+180.8497435*x^35-131.5995483*x^36+28.60592212*x^37-191.0614315*x\n^38-66.24484141*x^39-73.68131597*x^40-94.21374089*x^41+75.87121746*x^42-34.068\\\n29724*x^43+44.81754571*x^44+5.221451275*x^45-54.41552578*x^46-18.74682223*x^47\n+12.68365229*x^48+89.19040259*x^49+7.947859203*x^50+21.23458961, -44.55241619*\nx-92.07987776*x^2+6.232615379*x^3-37.81015205*x^4-62.46418683*x^5+51.12821625*\nx^6-22.02331378*x^7+140.2844604*x^8+25.45943762*x^9+15.55792754*x^10+34.755232\\\n57*x^11-289.7559643*x^12-14.49166120*x^13+191.3767042*x^14-113.1970251*x^15+6.\\\n661281462*x^16-156.6021559*x^17+231.3482393*x^18+148.2045895*x^19+16.87465174*\nx^20+95.10362082*x^21-207.6941390*x^22+4.137813650*x^23-251.5431715*x^24+64.05\\\n673378*x^25+243.5341107*x^26-209.2034498*x^27-66.34956995*x^28-15.28504517*x^\n29+127.0039529*x^30+258.5951095*x^31-187.4686368*x^32+119.0603542*x^33-89.7980\\\n8983*x^34-26.70073363*x^35+58.93602046*x^36-41.49537454*x^37+220.9082234*x^38+\n39.05183340*x^39+29.23498548*x^40+106.2964370*x^41+68.61672996*x^42+133.043133\\\n0*x^43-7.697124102*x^44+33.93879875*x^45-44.28018692*x^46-80.90126681*x^47-79.\\\n04529496*x^48-59.02921245*x^49-6.397521686*x^50-43.26844977, 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9.59740754+4.64121583*x-4.80860731*x^2+4.441\\\n79208*x^3+5.57131614*x^4+2.23337451*x^5+.86130813*x^6+4.35280299*x^7+3.6821246\\\n8*x^8+.72253481*x^9+4.25430577*x^10-6.65846131*x^11-9.72604276*x^12-5.18966800\n*x^13+1.10229529*x^14-2.94649520*x^15+4.65435387*x^16+1.21375999*x^17+7.414377\\\n88*x^18+2.06160705*x^19-.28608110*x^20];\nFH5020 := [7.19715915*x+9.88898204+9.20464173*x^2+2.37700814*x^3+1.91709612*x^\n4-8.29729551*x^5+.39371870*x^6+1.76061821*x^7-2.59922349*x^8+.94356455*x^9-7.7\\\n8739399*x^10-9.40264742*x^11+.38130108*x^12-2.42005279*x^13-3.52420411*x^14-4.\\\n11909688*x^15+5.23767364*x^16+6.46041038*x^17+.37871200*x^18-2.17941532*x^19-9\\\n.26908069*x^20+.82598741*x^21-3.61175709*x^22+8.30705409*x^23+7.26589613*x^24-\\\n4.91128459*x^25+9.97345157*x^26-1.94504202*x^27-.60631135*x^28+1.77960427*x^29\n-9.01854113*x^30, 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3.96096026*x+6.57286723*x^2-8.6943548\\\n7*x^3+1.97650340*x^4-2.09910918*x^5+4.57735804*x^6+2.27821888*x^7-5.23377565*x\n^8-4.46670076*x^9-4.30549864*x^10+.34606702*x^11+.58210526*x^12+8.17082622*x^\n13+1.68600842*x^14+7.04595967*x^15+2.35917235*x^16-8.82839231*x^17+4.29519045*\nx^18-9.81825088*x^19-3.20647988*x^20-8.11745620*x^21+2.58591837*x^22-5.4221404\\\n3*x^23-7.39603068*x^24-8.69786274*x^25-1.00099360*x^26+8.60399465*x^27-5.92127\\\n222*x^28-5.39288895*x^29-3.28133971*x^30-2.23691055, 5.37706234*x+3.82169515*x\n^2+9.15757346*x^3+2.90159654*x^4+1.95317453*x^5-9.82446548*x^6+6.11400733*x^7-\\\n9.71003548*x^8-2.12836970*x^9+2.41993877*x^10+9.30067711*x^11+1.42533788*x^12+\n4.36252398*x^13+9.72042149*x^14+2.92039158*x^15+7.09423604*x^16+.50523963*x^17\n-3.05767220*x^18-2.49543618*x^19+3.41223269*x^20-.39643842*x^21-4.30293892*x^\n22+4.03156417*x^23-5.76613199*x^24-5.37012102*x^25+5.52210467*x^26+3.29365994*\nx^27-2.35043055*x^28-7.21055244*x^29+1.12528277*x^30+2.76603142, 5.42976082*x+\n2.71164961*x^2+7.51849514*x^3-1.76029978*x^4+2.69138011*x^5-6.08214057*x^6+8.2\\\n9656447*x^7+2.39699766*x^8+6.80675644*x^9+6.85748667*x^10+2.61963617*x^11+7.39\\\n546564*x^12+2.76168018*x^13-5.33892760*x^14-4.54301884*x^15+4.84228941*x^16-6.\\\n62126317*x^17-7.71140017*x^18+4.23155941*x^19+6.79534393*x^20-8.78838390*x^21-\\\n6.76889513*x^22-6.42348650*x^23+3.07581444*x^24-8.80676660*x^25+1.71577199*x^\n26-.36351134*x^27-5.15020774*x^28-.70804784*x^29+1.95998816*x^30-9.15371026, 7\\\n.04995527*x+.74178778*x^2+6.43688247*x^3+6.93394811*x^4-5.63918128*x^5+1.49425\\\n230*x^6+8.50334381*x^7-7.45368658*x^8+1.06462118*x^9-6.17642204*x^10-7.5683406\\\n1*x^11+3.04103717*x^12-9.33120192*x^13-9.87526693*x^14-7.98505680*x^15-8.66839\\\n915*x^16-7.31333658*x^17-7.97433996*x^18+9.07711822*x^19+2.24344374*x^20+8.393\\\n65860*x^21-7.23169682*x^22-1.93655482*x^23-6.84303649*x^24+7.17536488*x^25-8.4\\\n4769376*x^26+4.73153476*x^27-6.29785557*x^28-8.88226705*x^29+.78649798*x^30+3.\\\n06501687, 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5.24941902*x+4.93278449*x^2+3.396080\\\n63*x^3-1.17871298*x^4-4.31240696*x^5+3.68954208*x^6+8.38702047*x^7-2.99902152*\nx^8-8.66427059*x^9-7.36381310*x^10+9.60299497*x^11+6.70148429*x^12-6.10737244*\nx^13+5.17324942*x^14+6.88017940*x^15+4.25018773*x^16+3.94173944*x^17-9.6853296\\\n2*x^18-6.39155276*x^19-6.26463182*x^20-6.74054943*x^21+.31449807*x^22+5.414496\\\n41*x^23+9.77697676*x^24-7.48171197*x^25-3.38941788*x^26-.6935102e-1*x^27-2.795\\\n48417*x^28+4.42258281*x^29-5.49319936*x^30-.10671859, -8.36346781*x-5.10277673\n*x^2-7.85342351*x^3-6.30667798*x^4-8.29723809*x^5+8.14977467*x^6-2.96088329*x^\n7+1.59780904*x^8-6.71040904*x^9-9.29978347*x^10-5.46696079*x^11+8.87246128*x^\n12-4.05296203*x^13-7.36515318*x^14-5.60355476*x^15+1.18890302*x^16+.67713065*x\n^17-8.03818975*x^18-3.10607059*x^19+2.27146407*x^20-6.40256135*x^21-3.68455175\n*x^22-7.94606927*x^23+3.15983213*x^24+7.37091368*x^25+8.59522600*x^26+.5527187\\\n0*x^27+1.20785282*x^28-2.04156325*x^29-7.89666499*x^30+1.18039926, 6.83265003*\nx-4.52431924*x^2+9.19745565*x^3-7.18999320*x^4-8.57412073*x^5-6.90560011*x^6-3\\\n.02393794*x^7-3.31893074*x^8-6.02093259*x^9+8.40260722*x^10-7.69926516*x^11+9.\\\n75948156*x^12-1.49210962*x^13+3.37065520*x^14+7.75541069*x^15+2.32331552*x^16-\\\n3.78244377*x^17-1.34922889*x^18+9.51528018*x^19+1.92572933*x^20+2.71611123*x^\n21+3.20085658*x^22-.46843933*x^23+6.39690304*x^24+5.61588541*x^25+9.74558025*x\n^26+.12945741*x^27+7.08092235*x^28-3.89256569*x^29+2.74410896*x^30-8.40636425]\n;\nGH5020 := 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\n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":78.8416666667,"max_line_length":132,"alphanum_fraction":0.7344889547} +{"size":7346,"ext":"mpl","lang":"Maple","max_stars_count":63.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n 8585453e-6bfb-4d80-98de-b16074f1d86c(jetbrains.mps.lang.test)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 742f6602-5a2f-4313-aa6e-ae1cd4ffdc61(MPS.Platform)<\/dependency>\n 848ef45d-e560-4e35-853c-f35a64cc135c(de.itemis.mps.editor.celllayout.runtime)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 848ef45d-e560-4e35-853c-f35a64cc135c(de.itemis.mps.editor.celllayout.runtime)<\/dependency>\n <\/runtime>\n \n<\/language>\n\n","avg_line_length":82.5393258427,"max_line_length":146,"alphanum_fraction":0.7500680643} +{"size":433,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_gga_x *)\n\na1 := 199.81:\na2 := 4.3476:\nc1 := 0.8524:\nc2 := 1.2264:\n\n# This is Eq. (40) of the paper.\nf0 := s -> c1*(1 - exp(-a1*s^2)) + c2*(1 - exp(-a2*s^4)):\n\nf := x -> f0(X2S*x):","avg_line_length":22.7894736842,"max_line_length":68,"alphanum_fraction":0.6050808314} +{"size":542,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"# \u81ea\u5b9a\u4e49\u751f\u6210\u5305\u7684\u5de5\u5177\u3002\n# \u57fa\u4e8eLibraryTools\u3002\n# \u589e\u52a0\u4e86\u4e0d\u5b58\u5728\u5305\u6587\u4ef6\u5219\u76f4\u63a5\u521b\u5efa\u6587\u4ef6\u7684\u529f\u80fd\u3002\nLibMaker:=module()\n option package;\n export MakeLib;\n\n (*\n \u5c06package\u4fdd\u5b58\u5230\u6587\u4ef6\n \u5982\u679c\u6587\u4ef6\u4e0d\u5b58\u5728\u5219\u521b\u5efa\u6587\u4ef6\n \u5982\u679c\u6587\u4ef6\u4e0d\u542b\u540e\u7f00\u540d\u5219\u8865\u5168\u540e\u7f00\u540d\n \u9ed8\u8ba4\u6587\u4ef6\u540d\u4e3a lib.mla\n *)\n MakeLib:=proc(mName,fName:=\"lib.mla\")\n if not StringTools:-RegMatch(\".*\\\\.mla\",fName) then\n fName:=cat(fName,\".mla\");\n end if;\n if not FileTools:-Exists(fName) then\n LibraryTools:-Create(fName);\n end if;\n LibraryTools:-Save(mName,fNmae);\n end proc:\nend module:","avg_line_length":23.5652173913,"max_line_length":59,"alphanum_fraction":0.5848708487} +{"size":17528,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"#######################################################################\n# This file is part of the crlibm library, and is distributed under\n# the LGPL.\n# To use:\n# restart; read \"exp-td.mpl\";\nDigits := 145:\n\ninterface(quiet=true):\n\nread \"common-procedures.mpl\":\nread \"triple-double.mpl\":\nread \"gal.mpl\":\nmkdir(\"TEMPACOS\"):\n\nwith(orthopoly,T):\n\n\ntruncPoly := proc(p,k) \nlocal i, q:\nq := 0:\nconvert(q,polynom):\nfor i from 0 to min(degree(p,x),k) do\n q := q + coeff(p,x,i) * x^i:\nod:\nreturn (q):\nend:\n\nintervals := 10:\n\nfor i from 1 to intervals do\n\tepsAccurate[i] := 0.5:\n\tepsQuick[i] := 0.5:\n\tpolyAccurate[i] := 1:\n\tpolyQuick[i] := 1:\nod:\nepsAccurateSpecial := 0.5:\nepsQuickExtra := 0.5:\n\nlowestIntervalMax := 0.185:\nhighestIntervalMin := 0.78:\n\npolyAccurateTDCoeffsLowest := 13:\npolyAccurateDDCoeffsLowest := 12:\npolyAccurateDCoeffsLowest := 16:\n\npolyAccurateDegreeLowest := polyAccurateTDCoeffsLowest + polyAccurateDDCoeffsLowest + polyAccurateDCoeffsLowest:\n\npolyQuickDDCoeffsLowest := 12:\npolyQuickDCoeffsLowest := 10:\n\npolyQuickDegreeLowest := polyQuickDDCoeffsLowest + polyQuickDCoeffsLowest:\n\npolyAccurateTDCoeffsMiddle := 7:\npolyAccurateDDCoeffsMiddle := 9:\npolyAccurateDCoeffsMiddle := 19:\n\npolyAccurateDegreeMiddle := polyAccurateTDCoeffsMiddle + polyAccurateDDCoeffsMiddle + polyAccurateDCoeffsMiddle:\n\npolyQuickDDCoeffsMiddle := 7:\npolyQuickDCoeffsMiddle := 7:\n\npolyQuickDegreeMiddle := polyQuickDDCoeffsMiddle + polyQuickDCoeffsMiddle:\n\n\npolyAccurateTDCoeffsHighest := 9:\npolyAccurateDDCoeffsHighest := 9:\npolyAccurateDCoeffsHighest := 11:\n\npolyAccurateDegreeHighest := polyAccurateTDCoeffsHighest + polyAccurateDDCoeffsHighest + polyAccurateDCoeffsHighest:\n\npolyQuickDDCoeffsHighest := 9:\npolyQuickDCoeffsHighest := 9:\n\npolyQuickDegreeHighest := polyQuickDDCoeffsHighest + polyQuickDCoeffsHighest:\n\nextrabound := hexa2ieee([\"3F500000\",\"00000000\"]):\npolyQuickDegreeExtra := 5:\n\nbound[0] := 0:\nb := nearest(lowestIntervalMax):\nhe := ieeehexa(b):\nbound[1] := hexa2ieee([he[1],\"00000000\"]):\nb := nearest(highestIntervalMin):\nhe := ieeehexa(b):\nbound[intervals - 1] := hexa2ieee([he[1],\"00000000\"]):\nbound[intervals] := 1:\nlinearWidth := (highestIntervalMin - lowestIntervalMax) \/ (intervals - 2):\nscaleSum := 0:\nscale[2] := 1.5:\nscale[3] := 1.35:\nscale[4] := 1.18:\nscale[5] := 1.00:\nscale[6] := 0.915:\nscale[7] := 0.74:\nscale[8] := 0.595:\nscale[9] := 0.50:\nfor i from 2 to (intervals-1) do\n\tscaleSum := scaleSum + scale[i]:\nod:\nfor i from 2 to (intervals-1) do\n\tscale[i] := scale[i] \/ scaleSum;\nod:\ncurrent := lowestIntervalMax:\nfor i from 2 to (intervals-2) do\n\tb := nearest(current + (highestIntervalMin - lowestIntervalMax) * scale[i]):\n\tcurrent := b:\n\the := ieeehexa(b):\n\tbound[i] := hexa2ieee([he[1],\"00000000\"]):\nod:\nprintf(\"Using %d intervals with bounds:\\n\",intervals):\nfor i from 0 to intervals do\n\tprintf(\"bound[%d] = %1.30e\\n\",i,bound[i]):\nod:\nprintf(\"Using an extra bound for truncating the quick poly to deg. %d in interval #0 for small args up to %f (2^(%f))\\n\",\n\tpolyQuickDegreeExtra,extrabound,log[2](abs(extrabound)));\n\nprintf(\"Computing Gal's accurate table values for interval midpoints\\n\"):\nfor i from 2 to (intervals-1) do\n\tm := nearest((bound[i] + bound[i-1]) \/ 2):\n\tmhe := ieeehexa(m):\n\tprintf(\"Interval %d: accurate table research start value %f (%s%s)\\n\",i,m,mhe[1],mhe[2]):\n\tmidpointFloat[i] := galDoubleToDoubleDouble(nearest(m),arcsin,2^(-121),2^(15)):\nod:\n\n\nprintf(\"Using the following floating point midpoints for intervals 2-%d:\\n\",intervals-2):\nfor i from 2 to (intervals-1) do\n\tmhe := ieeehexa(midpointFloat[i]):\n\tprintf(\"midpointFloat[%d] = %f (%s%s)\\n\",i,midpointFloat[i],mhe[1],mhe[2]):\nod:\n\nprintf(\"The reduced argument z is therefore bounded by:\\n\"):\nprintf(\"Interval 1: |z| < 2^(%f)\\n\",\n\tlog[2](abs(bound[1]))):\nfor i from 2 to (intervals-1) do\n\tprintf(\"Interval %d: |z| < 2^(%f)\\n\",i,\n\tlog[2](max(abs(midpointFloat[i] - bound[i-1]),abs(midpointFloat[i] - bound[i])))):\nod:\nprintf(\"Interval %d: |z| < 2^(%f)\\n\",intervals,\n\tlog[2](abs(1 - bound[intervals-1]))):\n\n\n\nprintf(\"Using a %d degree polynomial for lowest interval (1) (accurate phase)\\n\",\n\tpolyAccurateDegreeLowest):\nprintf(\"with %d triple-double, %d double-double and %d double coefficients\\n\",\n\tpolyAccurateTDCoeffsLowest, polyAccurateDDCoeffsLowest, polyAccurateDCoeffsLowest):\nprintf(\"Using a %d degree polynomial for lowest interval (1) (quick phase)\\n\",\n\tpolyQuickDegreeLowest):\nprintf(\"with %d double-double and %d double coefficients\\n\",\n\tpolyQuickDDCoeffsLowest, polyQuickDCoeffsLowest):\nprintf(\"Using a %d degree polynomial for middle intervals (2-%d) (accurate phase)\\n\",\n\tpolyAccurateDegreeMiddle,intervals-2):\nprintf(\"with %d triple-double, %d double-double and %d double coefficients\\n\",\n\tpolyAccurateTDCoeffsMiddle, polyAccurateDDCoeffsMiddle, polyAccurateDCoeffsMiddle):\nprintf(\"Using a %d degree polynomial for middle intervals (2-%d) (quick phase)\\n\",\n\tpolyQuickDegreeMiddle,intervals-2):\nprintf(\"with %d double-double and %d double coefficients\\n\",\n\tpolyQuickDDCoeffsMiddle, polyQuickDCoeffsMiddle):\nprintf(\"Using a %d degree polynomial for highest interval (%d) (accurate phase)\\n\",\n\tpolyAccurateDegreeHighest,intervals):\nprintf(\"with %d triple-double, %d double-double and %d double coefficients\\n\",\n\tpolyAccurateTDCoeffsHighest, polyAccurateDDCoeffsHighest, polyAccurateDCoeffsHighest):\nprintf(\"Using a %d degree polynomial for highest interval (%d) (quick phase)\\n\",\n\tpolyQuickDegreeHighest,intervals):\nprintf(\"with %d double-double and %d double coefficients\\n\",\n\tpolyQuickDDCoeffsHighest, polyQuickDCoeffsHighest):\n\nif true then \n\nprintf(\"Computing polynomials for interval 1 ([%f;%f])\\n\",bound[0],bound[1]):\n\nf := unapply(convert(series((arcsin(sqrt(x))\/sqrt(x) - 1)\/x,x=0,300),polynom),x):\n\np := unapply(eval(numapprox[chebyshev](f(x),x=(bound[0])^2..(bound[1])^2,2^(-127))),x):\n\npolyAccuExact[1] := truncPoly(subs(X=x^2,p(X))*x^3+x,polyAccurateDegreeLowest):\n\npolyAccurate[1] := poly_exact32(polyAccuExact[1],polyAccurateTDCoeffsLowest,polyAccurateDDCoeffsLowest):\n\nepsAccurate[1] := numapprox[infnorm]((polyAccurate[1]\/arcsin(x))-1, x=bound[0]..bound[1]):\nepsAccurateSpecial := numapprox[infnorm]((polyAccurate[1]\/arcsin(x))-1, x=bound[0]..evalf(sin(2^(-18)))):\n\nepsAccurateUnknown := numapprox[infnorm]((polyAccurate[1]\/arcsin(x))-1, x=bound[0]..evalf(cos(12867\/8192))):\n\npolyQuickExact[1] := truncPoly(polyAccuExact[1],polyQuickDegreeLowest):\npolyQuick[1] := poly_exact2(polyQuickExact[1],polyQuickDDCoeffsLowest):\n\nepsQuick[1] := numapprox[infnorm]((polyQuick[1]\/arcsin(x))-1, x=bound[0]..bound[1]):\n\npolyQuickExtraExact := truncPoly(polyAccuExact[1],polyQuickDegreeExtra):\npolyQuickExtra := poly_exact2(polyQuickExtraExact,polyQuickDegreeExtra):\nepsQuickExtra := numapprox[infnorm]((polyQuickExtra\/arcsin(x))-1, x=bound[0]..extrabound):\n\nend if:\n\nfor i from 2 to (intervals-1) do\n\nprintf(\"Computing polynomials for interval %d ([%f;%f])\\n\",i,bound[i-1],bound[i]):\nprintf(\"Reduced argument z will be in interval [%1.8e;%1.8e] ([-2^%f,2^%f]),\\n\",\n\tbound[i-1]-midpointFloat[i],bound[i]-midpointFloat[i],\n\tlog[2](abs(bound[i-1]-midpointFloat[i])),log[2](abs(bound[i]-midpointFloat[i]))):\n\nf := unapply(arcsin(x+midpointFloat[i]),x):\n\nfhelp := unapply(convert(series((f(x)-arcsin(midpointFloat[i]))\/x,x=0,polyAccurateDegreeMiddle*3),polynom),x):\n\npolyAccuExact[i] := numapprox[minimax](fhelp(x),\n\t\t\t\tx=bound[i-1]-midpointFloat[i]..bound[i]-midpointFloat[i],\n\t\t\t\t[polyAccurateDegreeMiddle,0],1,'err')*x + nearestDD(evalf(arcsin(midpointFloat[i]))):\n\npolyAccurate[i] := poly_exact32(polyAccuExact[i],polyAccurateTDCoeffsMiddle,polyAccurateDDCoeffsMiddle):\n\nepsAccurate[i] := numapprox[infnorm]((polyAccurate[i]\/f(x))-1, \n\t\t\t\t\tx=bound[i-1]-midpointFloat[i]..bound[i]-midpointFloat[i]):\n\npolyQuickExact[i] := truncPoly(polyAccuExact[i],polyQuickDegreeMiddle):\npolyQuick[i] := poly_exact2(polyQuickExact[i],polyQuickDDCoeffsMiddle):\n\nepsQuick[i] := numapprox[infnorm]((polyQuick[i]\/f(x))-1, \n\t\t\t \t x=bound[i-1]-midpointFloat[i]..bound[i]-midpointFloat[i]):\n\n\nod:\n\n\nif true then \n\nprintf(\"Computing polynomials for interval %d ([%f;%f])\\n\",intervals,bound[intervals-1],bound[intervals]):\n\n\ng := unapply(((arcsin(1 - x) - Pi\/2)\/sqrt(2*x)),x):\nf := unapply(convert(series(((g(x)+1)\/x),x=0,polyAccurateDegreeHighest*4),polynom),x):\n\n\npolyAccuExact[intervals] := numapprox[minimax](f(x),x=(1-bound[intervals]+2^(-53))..(1-bound[intervals-1]),\n\t\t\t\t\t\t[polyAccurateDegreeHighest-1,0],1,'err')*x-1:\n\npolyAccurate[intervals] := poly_exact32(polyAccuExact[intervals],polyAccurateTDCoeffsHighest,polyAccurateDDCoeffsHighest):\n\n\nepsAccurate[intervals] := numapprox[infnorm](((unapply(polyAccurate[intervals],x)(x)\/g(x))-1), \n\t\t\t\t\tx=(1-bound[intervals]+2^(-53))..(1-bound[intervals-1])):\n\n\npolyQuickExact[intervals] := truncPoly(polyAccuExact[intervals],polyQuickDegreeHighest):\npolyQuick[intervals] := poly_exact2(polyQuickExact[intervals],polyQuickDDCoeffsHighest):\n\nepsQuick[intervals] := numapprox[infnorm](((unapply(polyQuick[intervals],x)(x)\/g(x))-1), \n\t\t\t\t\tx=(1-bound[intervals]+2^(-53))..(1-bound[intervals-1])):\n\nprintf(\"Checking if the polynomial for interval %d is exactly -1 in z = %f...\\n\",intervals,1-bound[intervals]);\n\nif (unapply(polyAccurate[intervals],x)(1-bound[intervals]) = -1) then\n\tprintf(\" Check passed!\\n\"):\nelse\n\tprintf(\" Check failed!\\n\"):\nend if:\n\nend if:\n\n\n\nfor i from 1 to intervals do \n\tprintf(\"Relative error for accurate phase polynomial in interval %d ([%f;%f]) is 2^(%f)\\n\",\n \t\ti,bound[i-1],bound[i],log[2](abs(epsAccurate[i]))):\n\tprintf(\"Relative error for quick phase polynomial in interval %d ([%f;%f]) is 2^(%f)\\n\",\n \t\ti,bound[i-1],bound[i],log[2](abs(epsQuick[i]))):\nod:\nprintf(\"Relative error for accurate phase polynomial #1 in special interval [0;sin(2^(-18))]) is 2^(%f)\\n\",\n log[2](abs(epsAccurateSpecial))):\nprintf(\"Relative error for accurate phase polynomial #1 in \\\"unknown\\\" interval [0;cos(12867\/8192)]) is 2^(%f)\\n\",\n log[2](abs(epsAccurateUnknown))):\n\n\nprintf(\"Relative error for quick phase extra case truncated polynomial #1 in special interval [0;%f]) is 2^(%f)\\n\",\n extrabound,log[2](abs(epsQuickExtra))):\n\n\n(PiHalfH, PiHalfM, PiHalfL) := hi_mi_lo(evalf(Pi\/2)):\n(PiH, PiM, PiL) := hi_mi_lo(evalf(Pi)):\n\nepsPiDD := evalf(((PiHalfH + PiHalfM) - Pi\/2)\/(Pi\/2)):\nepsPiTD := evalf(((PiHalfH + PiHalfM + PiHalfL) - Pi\/2) \/ (Pi\/2)):\n\nprintf(\"Relative error for storing Pi\/2 as a double-double is 2^(%f)\\n\",evalf(log[2](abs(epsPiDD)))):\nprintf(\"Relative error for storing Pi\/2 as a triple-double is 2^(%f)\\n\",evalf(log[2](abs(epsPiTD)))):\n\n# Ce qui suit est pifometrique et doit etre prouve en Gappa ensuite\n\narithmeticalErrorQuick[1] := 2^(-61):\narithmeticalErrorQuick[2] := 2^(-61):\narithmeticalErrorQuick[3] := 2^(-61):\narithmeticalErrorQuick[4] := 2^(-61):\narithmeticalErrorQuick[5] := 2^(-61):\narithmeticalErrorQuick[6] := 2^(-61):\narithmeticalErrorQuick[7] := 2^(-61):\narithmeticalErrorQuick[8] := 2^(-61):\narithmeticalErrorQuick[9] := 2^(-61):\narithmeticalErrorQuick[10] := 2^(-68):\n\narithmeticalErrorQuickExtra := 2^(-80):\n\nfor i from 1 to intervals do\n\testimatedOverallEpsQuick[i] := abs(epsQuick[i]) + \n\t\t\t\t abs(arithmeticalErrorQuick[i]) + \n abs(epsQuick[i]) * abs(arithmeticalErrorQuick[i]):\n\tprintf(\"Relative quick phase overall error bound to show in Gappa for interval %d ([%f;%f]) is 2^(%f)\\n\",\n\t\ti,bound[i-1],bound[i],log[2](abs(estimatedOverallEpsQuick[i]))):\nod:\n\nestimatedOverallEpsQuickExtra := abs(epsQuickExtra) + \n\t\t\t\t abs(arithmeticalErrorQuickExtra) + \n abs(epsQuickExtra) * abs(arithmeticalErrorQuickExtra):\nprintf(\"Relative quick phase overall error bound to show for extra truncted poly in interval [0;%f]) is 2^(%f)\\n\",\n\textrabound,log[2](abs(estimatedOverallEpsQuickExtra))):\n\n\nprintf(\"Write tables...\\n\"):\n\nfilename:=\"TEMPACOS\/acos-td.h\":\nfd:=fopen(filename, WRITE, TEXT):\n\nfprintf(fd, \"#include \\\"crlibm.h\\\"\\n#include \\\"crlibm_private.h\\\"\\n\"):\n\nfprintf(fd, \"\\n\/* File generated by maple\/acos-td.mpl *\/\\n\\n\"):\n\nprintf(\"Write table with bounds\\n\"):\n\nfprintf(fd, \"\/* High order words of interval bounds (low order word is 0) *\/\\n\"):\nfor i from 1 to (intervals-1) do \n\theb := ieeehexa(bound[i]):\n\tfprintf(fd, \"\\#define BOUND%d 0x%s\\n\",i,heb[1]):\nod:\n\nheb := ieeehexa(extrabound):\nfprintf(fd, \"\\#define EXTRABOUND 0x%s\\n\",heb[1]):\n\nprintf(\"Write additional constants\\n\"):\n\nfprintf(fd, \"\\n\\n\/* Pi\/2 as a triple-double*\/\\n\"):\nfprintf(fd, \"\\#define PIHALFH %1.50e\\n\",PiHalfH):\nfprintf(fd, \"\\#define PIHALFM %1.50e\\n\",PiHalfM):\nfprintf(fd, \"\\#define PIHALFL %1.50e\\n\",PiHalfL):\nfprintf(fd, \"\\n\\n\/* Pi as a triple-double*\/\\n\"):\nfprintf(fd, \"\\#define PIH %1.50e\\n\",PiH):\nfprintf(fd, \"\\#define PIM %1.50e\\n\",PiM):\nfprintf(fd, \"\\#define PIL %1.50e\\n\",PiL):\nfprintf(fd, \"\\#define PIHALFDOUBLERN %1.50e\\n\",nearest(evalf(Pi\/2))):\nfprintf(fd, \"\\#define PIHALFDOUBLERU %1.50e\\n\",roundUp(evalf(Pi\/2))):\nfprintf(fd, \"\\#define PIHALFDOUBLERD %1.50e\\n\",roundDown(evalf(Pi\/2))):\n\nprintf(\"Write table with midpoints and polynomial coefficients\\n\"):\nk := 0:\nfor i from 0 to polyAccurateDegreeLowest do\n\t(hi,mi,lo) := hi_mi_lo(coeff(polyAccurate[1],x,i)):\n\tif ((abs(hi) = 1.0) and (mi = 0) and (lo = 0)) then \n\t\tprintf(\n\t\t\"Coefficient %d of interval 1 polynomial is exactly %f and will not be stored in the table\\n\",i,hi): \n\telse \n\tg := 0;\n\tif (hi <> 0) then\n\t\tif (i <= polyQuickDegreeLowest) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dh, quickPolyLowC%dh *\/\",hi,k,i,i):\n\t\telse\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dh *\/\",hi,k,i):\n\t\tend if:\n\t\tk := k + 1:\n\tend if:\n\tif (mi <> 0) then\n\t\tif (i <= polyQuickDDCoeffsLowest) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dm, quickPolyLowC%dl *\/\",mi,k,i,i):\n\t\telse\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dm *\/\",mi,k,i):\n\t\tend if:\n\t\tk := k + 1:\n\tend if:\n\tif (lo <> 0) then\n\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dl *\/\",lo,k,i):\n\t\tk := k + 1:\n\tend if:\n\tend if:\nod:\ntbl[k] := sprintf(\"%1.50e, \\t\/* %d, RN rounding constant quick poly low*\/\",\n\t\tcompute_rn_constant(estimatedOverallEpsQuick[1]),k):\nk := k + 1:\ntbl[k] := sprintf(\"%1.50e, \\t\/* %d, RD rounding constant quick poly low*\/\",\n\t\testimatedOverallEpsQuick[1],k):\nk := k + 1:\nprintf(\"Table for interval 1 written\\n\"):\nfor l from 2 to (intervals-1) do\n\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, midpoint in interval %d*\/\",midpointFloat[l],k,l):\n\ttblidx[l] := k;\n\tk := k + 1;\n\tfor i from 0 to polyAccurateDegreeMiddle do\n\t\t(hi,mi,lo) := hi_mi_lo(coeff(polyAccurate[l],x,i)):\n\t\tif ((abs(hi) = 1.0) and (mi = 0) and (lo = 0)) then \n\t\t\tprintf(\n\t\t\"Coefficient %d of interval %d polynomial is exactly %f and will not be stored in the table\\n\",i,l,hi): \n\t\telse \n\t\tg := 0;\n\t\tif (hi <> 0) then\n\t\t\tif (i <= polyQuickDegreeMiddle) then\n\t\t\t\ttbl[k] := sprintf(\n\t\t\t\t\t\"%1.50e, \\t\/* %d, accPolyMid%dC%dh, quickPolyMid%dC%dh *\/\",hi,k,l,i,l,i):\n\t\t\telse\n\t\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyMid%dC%dh *\/\",hi,k,l,i):\n\t\t\tend if:\n\t\t\tk := k + 1:\n\t\tend if:\n\t\tif (mi <> 0) then\n\t\t\tif (i <= polyQuickDDCoeffsMiddle) then\n\t\t\t\ttbl[k] := sprintf(\n\t\t\t\t\t\"%1.50e, \\t\/* %d, accPolyMid%dC%dm, quickPolyMid%dC%dl *\/\",mi,k,l,i,l,i):\n\t\t\telse\n\t\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyMid%dC%dm *\/\",mi,k,l,i):\n\t\t\tend if:\n\t\t\tk := k + 1:\n\t\tend if:\n\t\tif (lo <> 0) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyMid%dC%dl *\/\",lo,k,l,i):\n\t\t\tk := k + 1:\n\t\tend if:\n\t\tend if:\n\tod:\n\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, RN rounding constant quick poly middle %d*\/\",\n\t\t\tcompute_rn_constant(estimatedOverallEpsQuick[l]),k,l):\n\tk := k + 1:\n\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, RD rounding constant quick poly middle %d*\/\",\n\t\t\testimatedOverallEpsQuick[l],k,l):\n\tk := k + 1:\n\tprintf(\"Table for interval %d written\\n\",l):\nod:\ntblidx[intervals] := k:\nfor i from 0 to polyAccurateDegreeHighest do\n\t(hi,mi,lo) := hi_mi_lo(coeff(polyAccurate[intervals],x,i)):\n\tif ((abs(hi) = 1.0) and (mi = 0) and (lo = 0)) then \n\t\tprintf(\n\t\"Coefficient %d of interval %d polynomial is exactly %f and will not be stored in the table\\n\",i,intervals,hi): \n\telse \n\tg := 0;\t\n\tif (hi <> 0) then\n\t\tif (i <= polyQuickDegreeHighest) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dh, quickPolyHighC%dh *\/\",hi,k,i,i):\n\t\telse\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dh *\/\",hi,k,i):\n\t\tend if:\n\t\tk := k + 1:\n\tend if:\n\tif (mi <> 0) then\n\t\tif (i <= polyQuickDDCoeffsHighest) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dm, quickPolyHighC%dl *\/\",mi,k,i,i):\n\t\telse\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dm *\/\",mi,k,i):\n\t\tend if:\n\t\tk := k + 1:\n\tend if:\n\tif (lo <> 0) then\n\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dl *\/\",lo,k,i):\n\t\tk := k + 1:\n\tend if:\n\tend if:\nod:\ntbl[k] := sprintf(\"%1.50e, \\t\/* %d, RN rounding constant quick poly high*\/\",\n\t\tcompute_rn_constant(estimatedOverallEpsQuick[intervals]),k):\nk := k + 1:\ntbl[k] := sprintf(\"%1.50e, \\t\/* %d, RD rounding constant quick poly high*\/\",\n \t\testimatedOverallEpsQuick[intervals],k):\nk := k + 1:\nprintf(\"Table for interval %d written\\n\",intervals):\ntbllen := k:\nprintf(\"The whole table has %d entries, so uses %d bytes of memory\\n\",tbllen,tbllen*8):\nfprintf(fd,\"\\n\\n\/* Indices to the following table *\/\\n\"):\nfor i from 2 to intervals do\n\tfprintf(fd,\"\\#define TBLIDX%d %d\\n\",i,tblidx[i]):\nod:\nfprintf(fd, \"\\n\\n\/* Table with midpoints and polynomial coefficients *\/\\n\"):\nfprintf(fd, \"static const double tbl[%d] = {\\n\",tbllen):\nfor i from 0 to (tbllen - 1) do\n\tfprintf(fd, \"%s\\n\",tbl[i]):\nod:\nfprintf(fd, \"};\\n\\n\"):\n\nfclose(fd):\n\nprintf(\"----DONE---\\n\"):\n\n\n","avg_line_length":35.8445807771,"max_line_length":122,"alphanum_fraction":0.6760041077} +{"size":15991,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 0bf7bc3b-b11d-42e4-b160-93d72af96397(de.q60.mps.shadowmodels.runtimelang)<\/dependency>\n a7322769-ef64-4daa-a2f4-fd4228fb713e(de.q60.mps.shadowmodels.target.text)<\/dependency>\n 6ed54515-acc8-4d1e-a16c-9fd6cfe951ea(MPS.Core)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n e52a4835-844d-46a1-99f8-c06129db796f(de.q60.mps.shadowmodels.runtime)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 18bc6592-03a6-4e29-a83a-7ff23bde13ba(jetbrains.mps.lang.editor)<\/dependency>\n 0f2359af-040e-43bb-b438-cf024da41518(org.modelix.ui.sm.json)<\/dependency>\n 6f6906a4-f244-4806-a98b-0bc781cef2a8(org.modelix.ui.sm.dom)<\/dependency>\n 87f4b21e-a3a5-459e-a54b-408fd9eb7350(org.modelix.lib)<\/dependency>\n da981293-1ec2-4df0-95e4-df162984154c(org.modelix.ui.common)<\/dependency>\n 5622e615-959d-4843-9df6-ef04ee578c18(org.modelix.model)<\/dependency>\n 18463265-6d45-4514-82f1-cf7eb1222492(de.q60.mps.polymorphicfunctions.runtime)<\/dependency>\n fc3c2aa8-0d4b-463f-a774-40d450aa04a0(org.modelix.jetty)<\/dependency>\n 95085166-3236-4dd7-bd8e-e753c8d20885(de.q60.mps.incremental.runtime)<\/dependency>\n 3f233e7f-b8a6-46d2-a57f-795d56775243(Annotations)<\/dependency>\n ecfb9949-7433-4db5-85de-0f84d172e4ce(de.q60.mps.libs)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n 34e84b8f-afa8-4364-abcd-a279fddddbe7(jetbrains.mps.editor.runtime)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":87.3825136612,"max_line_length":129,"alphanum_fraction":0.7413545119} +{"size":6590,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n ceab5195-25ea-4f22-9b92-103b95ca8c0c(jetbrains.mps.lang.core)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":76.6279069767,"max_line_length":133,"alphanum_fraction":0.7373292868} +{"size":385,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_gga_x *)\n\nmkappa := 0.4604:\nmmu := 0.354546875:\n\nf0 := s -> 1 + mkappa*(1 - mkappa\/(mkappa + mmu*s^2)):\nf := x -> f0(X2S_2D*x):\n","avg_line_length":24.0625,"max_line_length":68,"alphanum_fraction":0.638961039} +{"size":8081,"ext":"mpl","lang":"Maple","max_stars_count":3.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":76.2358490566,"max_line_length":130,"alphanum_fraction":0.7276327187} +{"size":492,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"use DocumentTools in \nif parse(GetProperty(\"RunSIAN\", value)) then\n\n\tSetProperty(\"printSolutions\", enabled, true):\n\tSetProperty(\"bypass\", enabled, true):\n\tSetProperty(\"p\", enabled, true):\n\tSetProperty(\"params\", enabled, true):\n\tSetProperty(\"replicas\", enabled, true):\nelse\n\tSetProperty(\"bypass\", enabled, false):\n\tSetProperty(\"printSolutions\", enabled, false):\n\tSetProperty(\"p\", enabled, false):\n\tSetProperty(\"params\", enabled, false):\n\tSetProperty(\"replicas\", enabled, false):\nfi:\nend use; \n","avg_line_length":28.9411764706,"max_line_length":47,"alphanum_fraction":0.7296747967} +{"size":12921,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n <\/external-templates>\n \n 2ee24ef5-1b25-4fce-9708-9af3e9c3b8d7(Importers.runtime)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 3ac18869-0828-4401-abad-822a47bf83f1(jetbrains.mps.lang.descriptor#9020561928507175817)<\/dependency>\n 86ef8290-12bb-4ca7-947f-093788f263a9(jetbrains.mps.lang.project)<\/dependency>\n e45a8b22-94f2-427f-b849-77f254c4eef5(jetbrains.mps.lang.aspect#3274906159125927726)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 446c26eb-2b7b-4bf0-9b35-f83fa582753e(jetbrains.mps.lang.modelapi)<\/dependency>\n 6ed54515-acc8-4d1e-a16c-9fd6cfe951ea(MPS.Core)<\/dependency>\n 982eb8df-2c96-4bd7-9963-11712ea622e5(jetbrains.mps.lang.resources)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n c72da2b9-7cce-4447-8389-f407dc1158b7(jetbrains.mps.lang.structure)<\/dependency>\n 446c26eb-2b7b-4bf0-9b35-f83fa582753e(jetbrains.mps.lang.modelapi)<\/dependency>\n 982eb8df-2c96-4bd7-9963-11712ea622e5(jetbrains.mps.lang.resources)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 2ee24ef5-1b25-4fce-9708-9af3e9c3b8d7(Importers.runtime)<\/dependency>\n <\/runtime>\n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":82.2993630573,"max_line_length":137,"alphanum_fraction":0.7377911926} +{"size":1161,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"return_comp:=proc(A,coord::list,dim::integer,{diag:=false,tp:=dn})\n\n local i, j;\n local s;\n local cn,cm;\n\n if dim = 0 then\n s:= grcomponent(A)\n return s;\n end if;\n \n\n if dim = 1 then\n for i from 1 to nops(coord)-1 do\n cn:=coord[i];\n s:= cat(s,convert(A||cn,string));\n s:= cat(s,\"_expr\");\n s:= cat(s,sprintf(\":=\"));\n s:=cat(s,convert(grcomponent(A(tp),[coord[i]]),string));\n s:= cat(s,sprintf(\";\\n\"));\n end do;\n return s;\n end if;\n\n if dim = 2 then\n s:=\"\";\n if not(diag) then \n for i from 1 to nops(coord)-1 do\n for j from 1 to nops(coord)-1 do\n cn:=coord[i];\n cm := coord[j];\n s:=cat(s,convert(A||cn||cm,string));\n s:= cat(s,\"_expr\");\n s:=cat(s,sprintf(\":=\"));\n s:=cat(s,convert(grcomponent(A(tp,tp),[coord[i],coord[j]]),string));\n s:=cat(s,sprintf(\";\\n\"));\n end do;\n end do;\n\n else\n for i from 1 to nops(coord)-1 do\n cn:=coord[i];\n s:=cat(s,convert(A||cn||cn,string));\n s:= cat(s,\"_expr\");\n s:=cat(s,sprintf(\":=\"));\n s:=cat(s,convert(grcomponent(A(tp,tp),[coord[i],coord[i]]),string));\n s:=cat(s,sprintf(\";\\n\"));\n end do;\n end if;\n\n return s;\n end if;\n\nend proc;\n\n\n","avg_line_length":20.3684210526,"max_line_length":72,"alphanum_fraction":0.5383290267} +{"size":897,"ext":"mpl","lang":"Maple","max_stars_count":2.0,"content":"#ifndef SERVER_STUB_H__\n#define SERVER_STUB_H__\n\n#include \n#include \n#include \n#include \"server\/proto.h\"\n\n#define SVR_IMPL(NAME, req, zone) \\\n\tvoid svr_##NAME(ccf::session_request req, \\\n\t\t\tccf::auto_zone& zone)\n\nnamespace server {\n\n%self.each do |msg|\n%next unless msg.id\nSVR_IMPL([%msg.name%], req, zone);\n%end\n\nstatic inline void dispatch(ccf::method_t method, ccf::msgobj param,\n\t\tccf::session_responder response,\n\t\t\/*const ccf::address& from, *\/ccf::auto_zone& z)\n{\n\tswitch(method) {\n\t%self.each do |msg|\n\t%next unless msg.id\n\tcase [%msg.name%]::method:\n\t\tsvr_[%msg.name%](ccf::session_request<[%msg.name%]\/*, ccf::address*\/>(\n\t\t\t\tparam, response\/*, from*\/), z);\n\t\tbreak;\n\t%end\n\tdefault:\n\t\tthrow std::runtime_error(\"unknown method\"); \/\/ FIXME\n\t}\n}\n\n\n} \/\/ namespace server\n\n#endif \/* server\/stub.h *\/\n%# vim: syntax=mplex\n","avg_line_length":21.3571428571,"max_line_length":72,"alphanum_fraction":0.6778149387} +{"size":7025,"ext":"mpl","lang":"Maple","max_stars_count":63.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 1144260c-e9a5-49a2-9add-39a1a1a7077e(de.itemis.mps.editor.diagram.runtime)<\/dependency>\n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":83.630952381,"max_line_length":148,"alphanum_fraction":0.7487544484} +{"size":1606,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"!This file is subject to the terms and conditions defined in\n!file 'LICENSE.txt', which is part of this source code package.\n\nTITLE\n \n\tCAP_extensive_form_cap114_250;\n\nSTOCHASTIC\n\nDATA\n\t\n\tI := DATAFILE(\"cap114_250_SETS.dat\");\n\tJ := DATAFILE(\"cap114_250_SETS.dat\");\n\tK := DATAFILE(\"cap114_250_SETS.dat\");\t\t\t\t! - num scenarios\n\tQ := I;\t\t\t\t\t\t\t! - num 1st stage columns\n\tT := I*J;\t\t\t\t\t\t! - num 2nd stage columns\n\tR := J+I;\t\t\t\t\t\t! - num rows in T and W\n\t\n\nSCENARIO\n \n\tk := 1..K;\n\nINDEX\n\tFirstStCol := 1..Q;\n\tSecondStCol := 1..T;\n\tRow := 1..R;\t\n\nPROBABILITIES\n \n\tp[k] := ALLEQUAL;\n\nRANDOM DATA\n\n\tVector_h[k, Row] := DATAFILE(\"cap114_250_RANDOM.dat\");\t! - rows are related to scenarios\n\nDATA\n \n\tVector_c[FirstStCol] := DATAFILE(\"cap114_250_DATA.dat\");\n\tVector_d[SecondStCol] := DATAFILE(\"cap114_250_DATA.dat\");\n\tVector_b := DATAFILE(\"cap114_250_DATA.dat\");\t\t\t! - max sum of h over all scenarios\n\tMatrix_A[FirstStCol] := DATAFILE(\"cap114_250_DATA.dat\");\n\tMatrix_T[Row, FirstStCol] := DATAFILE(\"cap114_250_DATA.dat\");\n\tMatrix_W[Row, SecondStCol] := DATAFILE(\"cap114_250_DATA.dat\");\n\tx_ub[FirstStCol] := DATAFILE(\"cap114_250_DATA.dat\");\n\nSTAGE1 BINARY VARIABLES\n\n\tx[FirstStCol];\n\nSTAGE2 VARIABLES\n\n\ty[SecondStCol];\n\nMACROS\n\n\tStageFirst = sum(FirstStCol: Vector_c * x);\n\tStageSecond = sum(SecondStCol: Vector_d * y);\n\nMIN\n\n\tObjective = StageFirst + StageSecond;\n\nSUBJECT TO\n\t\n\tFirstStCnstr: sum(FirstStCol: Matrix_A * x) >= Vector_b;\n \tSecondStCnstr[Row]: sum(FirstStCol: Matrix_T * x) + sum(SecondStCol: Matrix_W * y) >= Vector_h;\n\nBOUNDS\n\n\tBinBounds[FirstStCol]: x <= x_ub;\t! - why do we need it\n\nEND","avg_line_length":22.0,"max_line_length":100,"alphanum_fraction":0.6855541719} +{"size":390,"ext":"mpl","lang":"Maple","max_stars_count":5.0,"content":"\nfunc $fact (\n var %n i32, var %p1 a64, var %p2 a64) i32 {\n var %r1 i32\n var %r2 i32\n var %r3 i32\n if (ne i32 i32 (dread i32 %n, constval i32 1)) {\n # Not correct, but for parse and dump test.\n intrinsiccallassigned JSOP_ADD (\n dread a64 %p1, dread a64 %p2, dread i32 %n) {\n dassign %r1 1\n dassign %r2 2\n dassign %r3 3\n }\n return (constval i32 0)\n }\n}\n","avg_line_length":21.6666666667,"max_line_length":51,"alphanum_fraction":0.5820512821} +{"size":1582,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"!This file is subject to the terms and conditions defined in\n!file 'LICENSE.txt', which is part of this source code package.\n\nTITLE\n \n\tCAP_extensive_form_cap111_5;\n\nSTOCHASTIC\n\nDATA\n\t\n\tI := DATAFILE(\"cap111_5_SETS.dat\");\n\tJ := DATAFILE(\"cap111_5_SETS.dat\");\n\tK := DATAFILE(\"cap111_5_SETS.dat\");\t\t\t\t! - num scenarios\n\tQ := I;\t\t\t\t\t\t\t! - num 1st stage columns\n\tT := I*J;\t\t\t\t\t\t! - num 2nd stage columns\n\tR := J+I;\t\t\t\t\t\t! - num rows in T and W\n\t\n\nSCENARIO\n \n\tk := 1..K;\n\nINDEX\n\tFirstStCol := 1..Q;\n\tSecondStCol := 1..T;\n\tRow := 1..R;\t\n\nPROBABILITIES\n \n\tp[k] := ALLEQUAL;\n\nRANDOM DATA\n\n\tVector_h[k, Row] := DATAFILE(\"cap111_5_RANDOM.dat\");\t! - rows are related to scenarios\n\nDATA\n \n\tVector_c[FirstStCol] := DATAFILE(\"cap111_5_DATA.dat\");\n\tVector_d[SecondStCol] := DATAFILE(\"cap111_5_DATA.dat\");\n\tVector_b := DATAFILE(\"cap111_5_DATA.dat\");\t\t\t! - max sum of h over all scenarios\n\tMatrix_A[FirstStCol] := DATAFILE(\"cap111_5_DATA.dat\");\n\tMatrix_T[Row, FirstStCol] := DATAFILE(\"cap111_5_DATA.dat\");\n\tMatrix_W[Row, SecondStCol] := DATAFILE(\"cap111_5_DATA.dat\");\n\tx_ub[FirstStCol] := DATAFILE(\"cap111_5_DATA.dat\");\n\nSTAGE1 BINARY VARIABLES\n\n\tx[FirstStCol];\n\nSTAGE2 VARIABLES\n\n\ty[SecondStCol];\n\nMACROS\n\n\tStageFirst = sum(FirstStCol: Vector_c * x);\n\tStageSecond = sum(SecondStCol: Vector_d * y);\n\nMIN\n\n\tObjective = StageFirst + StageSecond;\n\nSUBJECT TO\n\t\n\tFirstStCnstr: sum(FirstStCol: Matrix_A * x) >= Vector_b;\n \tSecondStCnstr[Row]: sum(FirstStCol: Matrix_T * x) + sum(SecondStCol: Matrix_W * y) >= Vector_h;\n\nBOUNDS\n\n\tBinBounds[FirstStCol]: x <= x_ub;\t! - why do we need it\n\nEND","avg_line_length":21.6712328767,"max_line_length":100,"alphanum_fraction":0.680783818} +{"size":5443,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: gga_exc *)\n\n$include \"scaling.mpl\"\n\n(* parameters *)\nwpbeh_A := 1.0161144:\nwpbeh_B := -0.37170836:\nwpbeh_C := -0.077215461:\nwpbeh_D := 0.57786348:\nwpbeh_E := -0.051955731:\n\n(*\n Note that kF has a 6 and not a 3 as it should in principle\n be. This is because the HSE formula, if one would take the papers\n seriously, does not fulfill the spin sum-rule. This is probably\n an oversight from them. So, we have to choose, either a 6 or a 3.\n\n Nwchem seems to have the factor of 6, but VASP and espresso have\n a 3. This would amount to rescaling omega by a factor of\n cbrt(2). We follow the quantum chemistry community and put the 6.\n*)\n\n(* Cutoff criterion below which to use polynomial expansion *)\nEGscut := 0.08:\nwcutoff := 14:\nexpfcutoff := 700:\n\n(* first let us calculate H(s) *)\nwpbeh_Ha1 := 0.00979681:\nwpbeh_Ha2 := 0.0410834:\nwpbeh_Ha3 := 0.187440:\nwpbeh_Ha4 := 0.00120824:\nwpbeh_Ha5 := 0.0347188:\nwpbeh_H := s ->\n + (wpbeh_Ha1*s^2 + wpbeh_Ha2*s^4)\n \/ (1 + wpbeh_Ha3*s^4 + wpbeh_Ha4*s^5 + wpbeh_Ha5*s^6):\n\n(*\n Now we calculate F(s). We use the parameters that were in the original code,\n but these constants are:\n\n wpbeh_Fc1 := 4*wpbeh_A^2\/(9*wpbeh_C) + (wpbeh_B - wpbeh_A*wpbeh_D)\/wpbeh_C:\n wpbeh_Fc2 := -4\/(3*36*wpbeh_C):\n*)\nwpbeh_Fc1 := 6.4753871:\nwpbeh_Fc2 := 0.47965830:\nwpbeh_F := s ->\n wpbeh_Fc1*wpbeh_H(s) + wpbeh_Fc2:\n\n(* several auxiliary variables *)\neb1 := w -> my_piecewise3(w < wcutoff, 1.455915450052607, 2):\naux1 := s -> wpbeh_D + s^2*wpbeh_H(s):\naux2 := s -> 9*wpbeh_H(s)*s^2\/(4*wpbeh_A):\naux3 := (w, s) -> aux1(s) + w^2:\naux4 := (w, s) -> s^2*wpbeh_H(s) + eb1(w)*w^2:\naux5 := (w, s) -> 9*aux4(w, s)\/(4*wpbeh_A):\naux6 := (w, s) -> wpbeh_D + aux4(w, s):\n\n(* and now G(s) *)\nGa := s ->\n + sqrt(Pi)*(\n + 15*wpbeh_E\n + 6*wpbeh_C*(1 + wpbeh_F(s)*s^2)*aux1(s)\n + 4*wpbeh_B*aux1(s)^2\n + 8*wpbeh_A*aux1(s)^3)\n \/ (16*aux1(s)^(7\/2))\n - (3*Pi\/4)*sqrt(wpbeh_A)*exp(aux2(s))*(1 - erf(sqrt(aux2(s)))):\nGb := s ->\n 15*sqrt(Pi)*s^2\/(16*aux1(s)^(7\/2)):\n\nwpbeh_EGa1 := -0.02628417880:\nwpbeh_EGa2 := -0.07117647788:\nwpbeh_EGa3 := 0.08534541323:\nwpbeh_EG := s -> my_piecewise3(s > EGscut,\n -(3*Pi\/4 + Ga(s))\/Gb(s),\n wpbeh_EGa1 + wpbeh_EGa2*s^2 + wpbeh_EGa3*s^4\n):\n\nterm2 := s-> (\n + aux1(s)^2*wpbeh_B\n + aux1(s)*wpbeh_C\n + 2*wpbeh_E\n + aux1(s)*s^2*wpbeh_C*wpbeh_F(s)\n + 2*s^2*wpbeh_EG(s)\n)\/(2*aux1(s)^3):\n\nterm3 := (w, s) -> -w*(\n + 4*aux3(w, s)^2*wpbeh_B\n + 6*aux3(w, s)*wpbeh_C\n + 15*wpbeh_E\n + 6*aux3(w, s)*s^2*wpbeh_C*wpbeh_F(s)\n + 15*s^2*wpbeh_EG(s)\n)\/(8*aux1(s)*aux3(w, s)^(5\/2)):\n\nterm4 := (w, s) -> -w^3*(\n + aux3(w, s)*wpbeh_C\n + 5*wpbeh_E\n + aux3(w, s)*s^2*wpbeh_C*wpbeh_F(s)\n + 5*s^2*wpbeh_EG(s)\n)\/(2*aux1(s)^2*aux3(w, s)^(5\/2)):\n\nterm5 := (w, s) -> -w^5*(\n + wpbeh_E\n + s^2*wpbeh_EG(s)\n)\/(aux1(s)^3*aux3(w, s)^(5\/2)):\n\nt10 := (w, s) ->\n 1\/2*wpbeh_A*log(aux4(w, s)\/aux6(w, s)):\n\n(* Use simple gaussian approximation for large w *)\nterm1_largew := (w, s) ->\n -1\/2*wpbeh_A*(-xc_E1_scaled(aux5(w, s)) + log(aux6(w, s)) - log(aux4(w, s))):\n\n(* For everything else use the full blown expression *)\nea1 := -1.128223946706117:\nea2 := 1.452736265762971:\nea3 := -1.243162299390327:\nea4 := 0.971824836115601:\nea5 := -0.568861079687373:\nea6 := 0.246880514820192:\nea7 := -0.065032363850763:\nea8 := 0.008401793031216:\n\nnp1 := w ->\n - 1.5*ea1*sqrt(wpbeh_A)*w\n + 27*ea3*w^3\/(8*sqrt(wpbeh_A))\n - 243*ea5*w^5\/(32*(wpbeh_A)^(3\/2))\n + 2187*ea7*w^7\/(128*(wpbeh_A)^(5\/2)):\n\nnp2 := w ->\n - wpbeh_A\n + 9*ea2*w^2\/4.0\n - 81*ea4*w^4\/(16*wpbeh_A)\n + 729*ea6*w^6\/(64*wpbeh_A^2)\n - 6561*ea8*w^8\/(256*wpbeh_A^3):\n\nt1 := (w, s) ->\n 1\/2*(np1(w)*Pi*xc_erfcx(sqrt(aux5(w, s))) - np2(w)*xc_E1_scaled(aux5(w, s))):\n\nf2 := (w, s) ->\n 1\/2*ea1*sqrt(Pi)*wpbeh_A\/sqrt(aux6(w, s)):\nf3 := (w, s) ->\n 1\/2*ea2*wpbeh_A\/aux6(w, s):\nf4 := (w, s) ->\n ea3*sqrt(Pi)*(-9\/(8*sqrt(aux4(w, s))) + 0.25*wpbeh_A\/aux6(w, s)^(3\/2)):\nf5 := (w, s) ->\n (ea4\/128)*(-144\/aux4(w, s) + 64*wpbeh_A\/aux6(w, s)^2):\nf6 := (w, s) ->\n ea5*(3*sqrt(Pi)*(3*aux6(w, s)^(5\/2)*(9*aux4(w, s) - 2*wpbeh_A)\n + 4*aux4(w, s)^(3\/2)*wpbeh_A^2))\/(32*aux6(w, s)^(5\/2)*aux4(w, s)^(3\/2)*wpbeh_A):\nf7 := (w, s) ->\n ea6*((32*wpbeh_A\/aux6(w, s)^3 + (-36 + 81*s^2*wpbeh_H(s)\/wpbeh_A)\/aux4(w, s)^2))\/32:\nf8 := (w, s) ->\n ea7*(-3*sqrt(Pi)*(-40*aux4(w, s)^(5\/2)*wpbeh_A^3\n + 9*aux6(w, s)^(7\/2)*(27*aux4(w, s)^2 - 6*aux4(w, s)*wpbeh_A + 4*wpbeh_A^2)))\n \/(128*aux6(w, s)^(7\/2)*aux4(w, s)^(5\/2)*wpbeh_A^2):\nf9 := (w, s) -> (\n + 324*ea6*eb1(w)*aux6(w, s)^4*aux4(w, s)*wpbeh_A\n + ea8*(384*aux4(w, s)^3*wpbeh_A^3\n + aux6(w, s)^4*(-729*aux4(w, s)^2 + 324*aux4(w, s)*wpbeh_A - 288*wpbeh_A^2))\n )\/(128*aux6(w, s)^4*aux4(w, s)^3*wpbeh_A^2):\n\nt2t9 := (w, s) ->\n + f2(w, s)*w + f3(w, s)*w^2 + f4(w, s)*w^3 + f5(w, s)*w^4\n + f6(w, s)*w^5 + f7(w, s)*w^6 + f8(w, s)*w^7 + f9(w, s)*w^8:\n\nterm1 := (w, s) -> my_piecewise3(\n w > wcutoff, term1_largew(w, s),\n t1(m_min(w, wcutoff), s) + t2t9(m_min(w, wcutoff), s) + t10(m_min(w, wcutoff), s)\n):\n\nf_wpbeh0 := (w, s) -> - 8\/9 *(\n term1(w, s) + term2(s) + term3(w, s) + term4(w, s) + term5(w, s)\n):\n\nf_wpbeh := (rs, z, x) ->\n f_wpbeh0(nu(rs, z), m_max(1e-15, s_scaling_2(X2S*x))):\n\nf := (rs, z, xt, xs0, xs1) ->\n gga_exchange_nsp(f_wpbeh, rs, z, xs0, xs1):\n","avg_line_length":28.7989417989,"max_line_length":86,"alphanum_fraction":0.5822156899} +{"size":10796,"ext":"mpl","lang":"Maple","max_stars_count":4.0,"content":"# Step 2 of 3: computer algebra\n\nimprove := proc(lo :: LO(name, anything), {_ctx :: t_kb := empty}, opts := [], $)\nlocal r, `&context`;\n userinfo(5, improve, \"input: \", print(lo &context _ctx));\n _Env_HakaruSolve := true;\n r:= LO(op(1,lo), reduce(op(2,lo), op(1,lo), _ctx, opts));\n userinfo(5, improve, \"output: \", print(r));\n r\nend proc;\n\n# Walk through integrals and simplify, recursing through grammar\n# h - name of the linear operator above us\n# kb - domain information\nreduce := proc(ee, h :: name, kb :: t_kb, opts := [], $)\n local e, elim, subintegral, w, ww, x, c, kb1, with_kb1, dom_specw, dom_specb\n , body, dom_spec, ed, mkDom, vars, rr\n , do_domain := evalb( not ( \"no_domain\" in {op(opts)} ) ) ;\n e := ee;\n\n if do_domain then\n rr := reduce_Integrals(e, h, kb, opts);\n if rr <> FAIL then return rr end if;\n end if;\n if e :: 'applyintegrand(anything, anything)' then\n map(simplify_assuming, e, kb)\n elif e :: `+` then\n map(reduce, e, h, kb, opts)\n elif e :: `*` then\n (subintegral, w) := selectremove(depends, e, h);\n if subintegral :: `*` then error \"Nonlinear integral %1\", e end if;\n subintegral := convert(reduce(subintegral, h, kb, opts), 'list', `*`);\n (subintegral, ww) := selectremove(depends, subintegral, h);\n simplify_factor_assuming(`*`(w, op(ww)), kb)\n * `*`(op(subintegral));\n elif e :: Or(Partition,t_pw) then\n if e :: t_pw then e := PWToPartition(e); end if;\n e := Partition:-Simpl(e);\n e := kb_Partition(e, kb, simplify_assuming,\n ((rhs, kb) -> %reduce(rhs, h, kb, opts)));\n e := eval(e, %reduce=reduce);\n # big hammer: simplify knows about bound variables, amongst many\n # other things\n Testzero := x -> evalb(simplify(x) = 0);\n e := Partition:-Simpl(e);\n if ee::t_pw and e :: Partition then\n e := Partition:-PartitionToPW(e);\n end if;\n e;\n elif e :: t_case then\n subsop(2=map(proc(b :: Branch(anything, anything))\n eval(subsop(2='reduce'(op(2,b),x,c,opts),b),\n {x=h, c=kb})\n end proc,\n op(2,e)),\n e);\n elif e :: 'Context(anything, anything)' then\n kb1 := assert(op(1,e), kb);\n # A contradictory `Context' implies anything, so produce 'anything'\n # In particular, 42 :: t_Hakaru = false, so a term under a false\n # assumption should never be inspected in any way.\n if kb1 :: t_not_a_kb then\n return 42\n end if;\n applyop(reduce, 2, e, h, kb1, opts);\n elif e :: 'toLO:-integrate(anything, Integrand(name, anything), list)' then\n x := gensym(op([2,1],e));\n # If we had HType information for op(1,e),\n # then we could use it to tell kb about x.\n subsop(2=Integrand(x, reduce(subs(op([2,1],e)=x, op([2,2],e)), h, kb, opts)), e)\n else\n simplify_assuming(e, kb)\n end if;\nend proc;\n\n# \"Integrals\" refers to any types of \"integrals\" understood by domain (Int,\n# Sum currently)\nreduce_Integrals := module()\n export ModuleApply;\n local\n # The callbacks passed by reduce_Integrals to Domain:-Reduce\n reduce_Integrals_body, reduce_Integrals_into\n # tries to evaluate a RootOf\n , try_eval_Root\n # tries to evaluate Int\/Sum\/Ints\/Sums\n , elim_intsum;\n\n reduce_Integrals_body := proc(h,opts,x,kb1) reduce(x,h,kb1,opts) end proc;\n reduce_Integrals_into := proc(h,opts,kind,e,vn,vt,kb,$)\n local rr;\n rr := elim_intsum(Domain:-Apply:-do_mk(args[3..-1]), h, kb,opts);\n rr := subsindets(rr, specfunc(RootOf), x->try_eval_Root(x,a->a));\n return rr;\n end proc;\n\n ModuleApply := proc(expr, h, kb, opts, $)\n local rr;\n rr := Domain:-Reduce(expr, kb\n ,curry(reduce_Integrals_into,h,opts)\n ,curry(reduce_Integrals_body,h,opts)\n ,(_->:-DOM_FAIL));\n rr := kb_assuming_mb(Partition:-Simpl)(rr, kb, x->x);\n if has(rr, :-DOM_FAIL) then\n return FAIL;\n elif has(rr, FAIL) then\n error \"Something strange happened in reduce_Integral(%a, %a, %a, %a)\\n%a\"\n , expr, kb, kb, opts, rr;\n end if;\n rr;\n end proc;\n\n try_eval_Root := proc(e0::specfunc(`RootOf`),on_fail := (_->FAIL), $)\n local ix,e := e0;\n try\n if nops(e)=2 or nops(e)=3\n and op(-1,e) :: `=`(identical(index),{specindex(real),nonnegint}) then\n ix := op([2,-1],e);\n if ix :: specindex(real) then ix := op(ix); end if;\n e := op(0,e)(op(1,e));\n else\n ix := NULL;\n end if;\n e := convert(e, 'radical', ix);\n if e :: specfunc(RootOf) then return on_fail(e) end if;\n return e;\n catch: return on_fail(e0); end try;\n end proc;\n\n # Try to find an eliminate (by evaluation, or simplification) integrals which\n # are free of `applyintegrand`s.\n elim_intsum := module ()\n export ModuleApply := proc(inert0, h :: name, kb :: t_kb, opts, $)\n local ex, e, inert := inert0;\n ex := extract_elim(inert, h, kb);\n e[0] := apply_elim(h, kb, ex);\n e[1] := check_elim(inert, e[0]);\n if e[1] = FAIL then inert\n else\n e[2] := reduce(e[1],h,kb,opts);\n if has(e[2], {csgn}) then\n WARNING(\"Throwing away an eliminated result result containing csgn (this \"\n \"could be a bug!):\\n%1\\n(while running %2)\", e[2], ex);\n inert;\n else e[2] end if;\n end if\n end proc;\n\n local known_tys := table([Int=int_assuming,Sum=sum_assuming,Ints=ints,Sums=sums]);\n local extract_elim := proc(e, h::name, kb::t_kb,$)\n local t, intapps, var, f, e_k, e_args, vs, blo, bhi;\n vs := {op(KB:-kb_to_variables(kb))};\n t := 'applyintegrand'('identical'(h), 'anything');\n intapps := indets(op(1,e), t);\n if intapps = {} then\n return FAIL;\n end if;\n e_k := op(0,e); e_args := op([2..-1],e);\n if Domain:-Has:-Bound(e) and assigned(known_tys[e_k]) then\n var := Domain:-ExtBound[e_k]:-ExtractVar(e_args);\n ASSERT(var::DomBoundVar);\n blo, bhi := Domain:-ExtBound[e_k]:-SplitRange\n (Domain:-ExtBound[e_k]:-ExtractRange(e_args));\n if ormap(b->op(1,b) in map((q-> (q,-q)), vs) and op(2,b)::SymbolicInfinity\n ,[[blo,bhi],[bhi,blo]]) then\n return FAIL end if;\n if var :: list then var := op(1,var) end if;\n if not depends(intapps, var) then\n f := known_tys[e_k];\n else\n return FAIL;\n end if;\n end if;\n [ op(1,e), f, var, [e_args] ];\n end proc;\n\n local apply_elim := proc(h::name,kb::t_kb,todo::{list,identical(FAIL)})\n local body, f, var, rrest;\n if todo = FAIL then return FAIL; end if;\n body, f, var, rrest := op(todo);\n banish(body, h, kb, infinity, var,\n proc (kb1,g,$) do_elim_intsum(kb1, f, g, op(rrest)) end proc);\n end proc;\n\n local check_elim := proc(e, elim,$)\n if has(elim, {MeijerG, undefined, FAIL}) or e = elim or elim :: SymbolicInfinity then\n return FAIL;\n end if;\n return elim;\n end proc;\n\n local do_elim_intsum := proc(kb, f, ee, v::{name,name=anything})\n local w, e, x, g, t, r;\n w, e := op(Domain:-Extract:-Shape(ee));\n w := Domain:-Shape:-toConstraints(w);\n e := piecewise_And(w, e, 0);\n e := f(e,v,_rest,kb);\n x := `if`(v::name, v, lhs(v));\n g := '{sum, sum_assuming, sums}';\n if f in g then\n t := {'identical'(x),\n 'identical'(x) = 'Not(range(Not({SymbolicInfinity, undefined})))'};\n else\n g := '{int, int_assuming, ints}';\n t := {'identical'(x),\n 'identical'(x) = 'anything'};\n if not f in g then g := {f} end if;\n end if;\n for r in indets(e, 'specfunc'(g)) do\n if 1 module()\n option record;\n export MakeKB := (`if`(kind=Sum,KB:-genSummation,KB:-genLebesgue));\n export ExtractVar := (e->op(1,e));\n export ExtractRange := (e->op(2,e));\n export MakeRange := `..`;\n export SplitRange := (e->op(e));\n export Constrain := `if`(kind=Sum,`<=`,`<`);\n export DoMk := ((e,v,t)->kind(e,v=t));\n export Min := `min`; export Max := `max`;\n export VarType := 'name';\n export RangeType := 'range';\n export MapleType := 'And'('specfunc'(kind), 'anyfunc(anything,name=range)');\n export BoundType := `if`(kind=Sum,'integer','real');\n export RecogBound := `if`(kind=Sum,\n (proc(k,b)\n if k = `<=` then (x->subsop(2=b,x))\n elif k = `>=` then (x->subsop(1=b,x))\n elif k = `<` then (x->subsop(2=(b-1),x))\n elif k = `>` then (x->subsop(1=b+1,x))\n end if;\n end proc),\n (proc(k,b)\n if k in {`<=`,`<`} then (x->subsop(2=b,x))\n elif k in {`>=`,`>`} then (x->subsop(1=b,x))\n end if;\n end proc));\nend module;\n\n# Ints( .., var::name, var_ty::range, dims::list(name=range) ) ==\n# [ var , map(lhs,dims) ] :: list(name) &X\n# [ var_ty, map(rhs,dims) ] :: list(range)\nisBound_IntsSums := kind -> module()\n option record;\n export MakeKB := proc(vars, lo, hi, kb, $)\n local var, dims, ty, rngs, x, kb1;\n var := op(1, vars);\n rngs := zip(`..`,lo,hi);\n ty := op(1, rngs);\n dims := subsop(1=NULL,zip(`=`,vars,rngs));\n x, kb1 := genType(var,\n mk_HArray(`if`(kind=Ints,\n HReal(open_bounds(ty)),\n HInt(closed_bounds(ty))),\n dims),kb);\n if nops(dims) > 0 then\n kb1 := assert(size(x)=op([-1,2,2],dims)-op([-1,2,1],dims)+1, kb1);\n end if;\n x, kb1;\n end proc;\n export ExtractVar := ((v,t,d)->[v,map(lhs,d)[]]);\n export ExtractRange := ((v,t,d)->[t,map(rhs,d)[]]);\n export MakeRange := ((a,b)->zip(`..`,a,b));\n export SplitRange := (rs->(map(x->op(1,x),rs), map(x->op(2,x),rs)));\n export Constrain := ((a,b)->zip(`if`(kind=Ints, `<`, `<=`),a,b)[]);\n export DoMk := ((e,v,t)->kind( e,op(1,v),op(1,t), subsop(1=NULL,zip(`=`,v,t)) ));\n export Min := ((a,b)->zip(`min`,a,b));\n export Max := ((a,b)->zip(`max`,a,b));\n export VarType := 'And(list(name),satisfies(x->x<>[]))';\n export RangeType := 'And(list(range),satisfies(x->x<>[]))';\n export MapleType := 'And'('specfunc'(kind),'anyfunc'('anything', 'name', 'range', 'list(name=range)'));\n export BoundType := TopProp;\n export RecogBound := (_->NULL);\nend module;\n","avg_line_length":37.3564013841,"max_line_length":108,"alphanum_fraction":0.5529825861} 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@numoffields u16 final,\n @numofmethods u16 final,\n @flag u16 final,\n @numofsuperclasses u16 final,\n @padding u32 final,\n @mod i32 final,\n @annotation i32 final,\n @clinitAddr i32 final}>\ntype $__method_info__ \ntype $__method_info_compact__ \ntype $__field_info__ final}>\ntype $__field_info_compact__ \ntype $__superclass_meta__ final}>\ntype $MUIDFuncDefTabEntry \ntype $MUIDFuncInfTabEntry \ntype $MUIDFuncDefMuidTabEntry \ntype $MUIDDataDefTabEntry \ntype $MUIDDataDefMuidTabEntry \ntype $MUIDUnifiedUndefTabEntry \ntype $MUIDUnifiedUndefMuidTabEntry \ntype $MUIDRangeTabEntry ,\n @tabEnd <* void>}>\njavaclass $LArith_3B <$LArith_3B> public\nvar $Ljava_2Flang_2FSystem_3B_7Cout extern <* <$Ljava_2Fio_2FPrintStream_3B>> final public static\nvar $__cinf_Ljava_2Flang_2FString_3B <$__class_meta__>\nfunc &MCC_GetOrInsertLiteral () <* <$Ljava_2Flang_2FString_3B>>\nvar $__vtb_LArith_3B fstatic <[11] <* void>> = [16, 24, 32, 36, 8, 4, 52, 12, 20, 48, 28]\nvar $__cinf_LArith_3B <$__class_meta__> public\nvar $__methods_info__LArith_3B fstatic <[4] <$__method_info__>> public = [[1= 0xfff6, 2= addrof ptr $__cinf_LArith_3B, 3= addroffunc ptr &LArith_3B_7Craise__sigfpe_7C_28_29V, 4= 266, 5= 4, 6= 56, 7= 72, 8= 0x2f41, 9= 0, 10= 0], [1= 0xfff6, 2= addrof ptr $__cinf_LArith_3B, 3= addroffunc ptr &LArith_3B_7Cmain_7C_28ALjava_2Flang_2FString_3B_29V, 4= 9, 5= 88, 6= 108, 7= 72, 8= 0xa201, 9= 1, 10= 0], [1= 0xfff6, 2= addrof ptr $__cinf_LArith_3B, 3= addroffunc ptr &LArith_3B_7C_3Cinit_3E_7C_28_29V, 4= 0x10001, 5= 200, 6= 56, 7= 72, 8= 0xad81, 9= 1, 10= 0], [1= 0xfff6, 2= addrof ptr $__cinf_LArith_3B, 3= addroffunc ptr &LArith_3B_7CTestMain_7C_28I_29I, 4= 9, 5= 228, 6= 264, 7= 72, 8= 0xc081, 9= 1, 10= 0]]\nvar $__cinf_Ljava_2Flang_2FObject_3B extern <$__class_meta__> public\nvar $__superclasses__LArith_3B fstatic <[1] <$__superclass_meta__>> public = [[1= 0x4000000000000000]]\nvar $__classinforo__LArith_3B fstatic <$__class_meta_ro__> public = [1= 7, 2= 0, 3= addrof ptr $__methods_info__LArith_3B, 4= addrof ptr $__superclasses__LArith_3B, 5= 0, 6= 4, 7= 0, 8= 1, 9= 0, 10= 33, 11= 72, 12= 0]\nvar $MCC_GCTIB__LArith_3B fstatic <* void> public\nvar $classStateInitialized u64\nvar $__cinf_LArith_3B <$__class_meta__> public = [1= 0x17eca191257f4b, 2= 0, 3= 0xffff, 4= 0, 5= 0, 6= addrof ptr $__vtb_LArith_3B, 7= addrof ptr $MCC_GCTIB__LArith_3B, 8= addrof ptr $__classinforo__LArith_3B, 9= addrof ptr $classStateInitialized]\nvar $__muid_classmetadata_bucket$$Arith_jar <[1] <* void>> public = [addrof ptr $__cinf_LArith_3B]\nfunc &MCC_Reflect_ThrowCastException nosideeffect () void\nfunc &MCC_Reflect_Check_Casting_NoArray nosideeffect () void\nfunc &MCC_Reflect_Check_Casting_Array nosideeffect () void\nfunc &MCC_CheckThrowPendingException nosideeffect () void\nfunc &MCC_PreNativeCall (var %caller ref) <* void>\nfunc &MCC_PostNativeCall (var %env <* void>) void\nfunc &MCC_DecodeReference nosideeffect (var %obj ref) ref\nfunc &MCC_CallFastNative (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative0 (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative1 (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative2 (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative3 (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative4 (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative5 (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative6 (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative7 (var %func <* void>) <* void>\nfunc &MCC_CallSlowNative8 (var %func <* void>) <* void>\nfunc &MCC_CallFastNativeExt (var %func <* void>) <* void>\nfunc &MCC_CallSlowNativeExt (var %func <* void>) <* void>\nfunc &MCC_SetReliableUnwindContext nosideeffect () void\nvar $__reg_jni_func_tab$$Arith_jar <[1] <* void>> = [-72057594037927936]\nfunc &Java_Arith_raise_1sigfpe__ weak () void\nfunc &MCC_CannotFindNativeMethod nosideeffect () <* void>\nfunc &MCC_FindNativeMethodPtrWithoutException nosideeffect () <* void>\nfunc &MCC_DummyNativeMethodPtr nosideeffect () <* void>\nvar $__reg_jni_tab$$Arith_jar <[1] <* void>> = [7, 39]\nvar $__cinf_Ljava_2Flang_2FSystem_3B extern <$__class_meta__>\nfunc &MCC_getFuncPtrFromItabSecondHash64 nosideeffect () ptr\nvar $__cinf_Ljava_2Flang_2FArithmeticException_3B extern ptr\nvar $__muid_func_def_tab$$Arith_jar fstatic <[4] <$MUIDFuncDefTabEntry>> = [[1= addroffunc ptr &LArith_3B_7C_3Cinit_3E_7C_28_29V], [1= addroffunc ptr &LArith_3B_7Craise__sigfpe_7C_28_29V], [1= addroffunc ptr &LArith_3B_7CTestMain_7C_28I_29I], [1= addroffunc ptr &LArith_3B_7Cmain_7C_28ALjava_2Flang_2FString_3B_29V]]\nvar $__muid_func_inf_tab$$Arith_jar fstatic <[4] <$MUIDFuncInfTabEntry>> = [[1= addroffunc ptr &LArith_3B_7C_3Cinit_3E_7C_28_29V, 2= addroffunc ptr &LArith_3B_7C_3Cinit_3E_7C_28_29V], [1= addroffunc ptr &LArith_3B_7Craise__sigfpe_7C_28_29V, 2= addroffunc ptr &LArith_3B_7Craise__sigfpe_7C_28_29V], [1= addroffunc ptr &LArith_3B_7CTestMain_7C_28I_29I, 2= addroffunc ptr &LArith_3B_7CTestMain_7C_28I_29I], [1= addroffunc ptr &LArith_3B_7Cmain_7C_28ALjava_2Flang_2FString_3B_29V, 2= addroffunc ptr &LArith_3B_7Cmain_7C_28ALjava_2Flang_2FString_3B_29V]]\nvar $__muid_func_def_muid_tab$$Arith_jar fstatic <[4] <$MUIDFuncDefMuidTabEntry>> = [[1= -4001351761653078127, 2= -1310918331262075617], [1= -8478930883496526569, 2= -2136361627923192435], [1= 0x1ea56a56b0696218, 2= -2592354488807809467], [1= -4467004309115070999, 2= -2701549801737661972]]\nvar $__muid_func_muid_idx_tab$$Arith_jar fstatic <[4] u32> = [3, 2, 1, 0]\nvar $__muid_data_def_tab$$Arith_jar fstatic <[1] <$MUIDDataDefTabEntry>> = [[1= addrof ptr $__cinf_LArith_3B]]\nvar $__muid_data_def_muid_tab$$Arith_jar fstatic <[1] <$MUIDDataDefMuidTabEntry>> = [[1= -7613525522286655244, 2= -2842220972116417222]]\nvar $__muid_func_undef_tab$$Arith_jar fstatic <[13] <$MUIDUnifiedUndefTabEntry>> = [[1= 0], [1= 0], [1= 0], [1= 0], [1= 0], [1= 0], [1= 0], [1= 0], [1= 0], [1= 0], [1= 0], [1= 0], [1= 0]]\nvar $__muid_func_undef_muid_tab$$Arith_jar fstatic <[13] <$MUIDUnifiedUndefMuidTabEntry>> = [[1= 0x3e32352aee789835, 2= -3887705395317205813], [1= -4187412136968710015, 2= -3800091941095621250], [1= 0x6742c234127e0a27, 2= -3762262047879347071], [1= 0x7230554331c55d92, 2= -3676689525926909155], [1= -715372855679083712, 2= -2647497990906227723], [1= -7464356948810446352, 2= -2259485500590180091], [1= 0x783627f2afd1cbde, 2= -2046851302095768916], [1= -2701934576591406938, 2= -1693831364093527548], [1= 0x126777a7fe39e1fb, 2= -1314856249532362766], [1= 0xbf40578f3343f7a, 2= -1198421541845410999], [1= 0xf83f176d111918a, 2= -976603133906039419], [1= 0x7ca2bdf69a6c7c94, 2= -801329978528900548], [1= 0x477aafa4d7dd102b, 2= -442561182569419835]]\nvar $__muid_data_undef_tab$$Arith_jar fstatic <[4] <$MUIDUnifiedUndefTabEntry>> = [[1= addrof ptr $__cinf_Ljava_2Flang_2FObject_3B], [1= addrof ptr $Ljava_2Flang_2FSystem_3B_7Cout], [1= addrof ptr $__cinf_Ljava_2Flang_2FArithmeticException_3B], [1= addrof ptr $__cinf_Ljava_2Flang_2FSystem_3B]]\nvar $__muid_data_undef_muid_tab$$Arith_jar fstatic <[4] <$MUIDUnifiedUndefMuidTabEntry>> = [[1= -567417612161374449, 2= -3298852447504547670], [1= 0x191283ac418c4bb9, 2= -1676204161023949463], [1= -8918818566091393965, 2= -1601760931404013578], [1= -5921653145571052587, 2= -171150348656858163]]\nvar $__muid_range_tab$$Arith_jar fstatic <[29] <$MUIDRangeTabEntry>> = [[1= 0x33693ce2ebe87faa, 2= -3126084233764470422], [1= 0x46d1a81c5146f046, 2= -4313720312531179750], [1= 2, 2= 2], [1= 3, 2= 3], [1= 4, 2= 4], [1= 5, 2= 5], [1= 6, 2= 6], [1= 7, 2= 7], [1= 8, 2= 8], [1= 9, 2= 9], [1= 0, 2= 0], [1= 11, 2= 11], [1= 12, 2= 12], [1= 13, 2= 13], [1= 14, 2= 14], [1= 15, 2= 15], [1= addrof ptr $__muid_func_def_tab$$Arith_jar, 2= addrof ptr $__muid_func_def_tab$$Arith_jar], [1= 0, 2= 0], [1= addrof ptr $__muid_func_inf_tab$$Arith_jar, 2= addrof ptr $__muid_func_inf_tab$$Arith_jar], [1= addrof ptr $__muid_func_undef_tab$$Arith_jar, 2= addrof ptr $__muid_func_undef_tab$$Arith_jar], [1= addrof ptr $__muid_data_def_tab$$Arith_jar, 2= addrof ptr $__muid_data_def_tab$$Arith_jar], [1= 0, 2= 0], [1= addrof ptr $__muid_data_undef_tab$$Arith_jar, 2= addrof ptr $__muid_data_undef_tab$$Arith_jar], [1= addrof ptr $__muid_func_def_muid_tab$$Arith_jar, 2= addrof ptr $__muid_func_def_muid_tab$$Arith_jar], [1= addrof ptr $__muid_func_undef_muid_tab$$Arith_jar, 2= addrof ptr $__muid_func_undef_muid_tab$$Arith_jar], [1= addrof ptr $__muid_data_def_muid_tab$$Arith_jar, 2= addrof ptr $__muid_data_def_muid_tab$$Arith_jar], [1= addrof ptr $__muid_data_undef_muid_tab$$Arith_jar, 2= addrof ptr $__muid_data_undef_muid_tab$$Arith_jar], [1= addrof ptr $__muid_func_muid_idx_tab$$Arith_jar, 2= addrof ptr $__muid_func_muid_idx_tab$$Arith_jar], [1= 0, 2= 0]]\nvar $__reflection_run_hot_strtab$$Arith_jar fstatic <[26] u8> = [0, 76, 65, 114, 105, 116, 104, 59, 0, 114, 97, 105, 115, 101, 95, 115, 105, 103, 102, 112, 101, 124, 40, 41, 86, 0]\nvar $__reflection_strtab$$Arith_jar fstatic <[71] u8> = [0, 114, 97, 105, 115, 101, 95, 115, 105, 103, 102, 112, 101, 0, 40, 41, 86, 0, 48, 33, 48, 0, 109, 97, 105, 110, 0, 40, 91, 76, 106, 97, 118, 97, 47, 108, 97, 110, 103, 47, 83, 116, 114, 105, 110, 103, 59, 41, 86, 0, 60, 105, 110, 105, 116, 62, 0, 84, 101, 115, 116, 77, 97, 105, 110, 0, 40, 73, 41, 73, 0]\nvar $__compilerVersionNum$$Arith_jar <[0] <* void>> = [1, 0]\nfunc &LArith_3B_7C_3Cinit_3E_7C_28_29V public constructor (var %_this <* <$LArith_3B>>) void {\n funcid 48153\n var %Reg1_R43694 <* <$LArith_3B>> localrefvar\n var %Reg1_R57 <* <$Ljava_2Flang_2FObject_3B>> localrefvar\n var %__muid_symptr <* void>\n\n intrinsiccall MCCIncRef (dread ref %_this)\n intrinsiccall MCCDecRef (dread ref %Reg1_R43694)\n dassign %Reg1_R43694 0 (dread ref %_this)\n #INSTIDX : 0||0000: aload_0\n #INSTIDX : 1||0001: invokespecial\n regassign ptr %1 (dread ref %Reg1_R57)\n dassign %Reg1_R57 0 (retype ref <* <$Ljava_2Flang_2FObject_3B>> (dread ref %Reg1_R43694))\n intrinsiccall MCCIncRef (dread ref %Reg1_R57)\n intrinsiccall MCCDecRef (regread ptr %1)\n #Call function:Ljava_2Flang_2FObject_3B_7C_3Cinit_3E_7C_28_29V\n dassign %__muid_symptr 0 (iread ptr <* <$MUIDUnifiedUndefTabEntry>> 1 (array 0 ptr <* <[13] <$MUIDUnifiedUndefTabEntry>>> (addrof ptr $__muid_func_undef_tab$$Arith_jar, constval i64 9)))\n icallassigned (dread ptr %__muid_symptr, dread ref %Reg1_R57) {}\n #INSTIDX : 4||0004: return\n intrinsiccall MPL_CLEANUP_LOCALREFVARS (dread ref %Reg1_R43694, dread ref %Reg1_R57)\n return ()\n}\nfunc &LArith_3B_7Craise__sigfpe_7C_28_29V private static native local () void {\n funcid 48154\n var %env_ptr <* void>\n\n callassigned &MCC_PreNativeCall (addrof ptr $__cinf_LArith_3B) { dassign %env_ptr 0 }\n regassign ptr %1 (iread ptr <* <* void>> 0 (array 0 ptr <* <[1] <* void>>> (addrof ptr $__reg_jni_func_tab$$Arith_jar, constval i32 0)))\n regassign ptr %2 (lshr ptr (regread ptr %1, constval u64 56))\n if (eq u1 ptr (regread ptr %2, constval ptr 255)) {\n callassigned &MCC_FindNativeMethodPtrWithoutException (array 0 ptr <* <[1] <* void>>> (addrof ptr $__reg_jni_func_tab$$Arith_jar, constval i32 0)) { regassign ptr %1}\n callassigned &MCC_DummyNativeMethodPtr () { regassign ptr %3}\n if (eq u1 ptr (regread ptr %1, regread ptr %3)) {\n regassign ptr %1 (addroffunc ptr &Java_Arith_raise_1sigfpe__)\n iassign <* <* void>> 0 (\n array 0 ptr <* <[1] <* void>>> (addrof ptr $__reg_jni_func_tab$$Arith_jar, constval i32 0), \n regread ptr %1)\n }\n }\n call &MCC_CallSlowNative2 (regread ptr %1, dread ptr %env_ptr, addrof ptr $__cinf_LArith_3B)\n callassigned &MCC_PostNativeCall (dread ptr %env_ptr) {}\n callassigned &MCC_CheckThrowPendingException () {}\n callassigned &MCC_SetReliableUnwindContext () {}\n}\nfunc &LArith_3B_7CTestMain_7C_28I_29I public static (var %Reg4_I i32) i32 {\n funcid 48155\n var %Reg0_I i32\n var %Reg2_I i32\n var %Reg0_R19929 <* <$Ljava_2Flang_2FArithmeticException_3B>> localrefvar\n var %Reg0_R510 <* <$Ljava_2Flang_2FThrowable_3B>> localrefvar\n var %Reg3_R19929 <* <$Ljava_2Flang_2FArithmeticException_3B>> localrefvar\n var %__muid_symptr <* void>\n\n #INSTIDX : 0||0000: iconst_0\n dassign %Reg0_I 0 (constval i32 0)\n #INSTIDX : 1||0001: istore_1\n dassign %Reg2_I 0 (dread i32 %Reg0_I)\n try { @label2 }\n #INSTIDX : 2||0002: iinc\n dassign %Reg2_I 0 (add i32 (dread i32 %Reg2_I, constval i32 1))\n #INSTIDX : 5||0005: iload_0\n #INSTIDX : 6||0006: ifle\n brtrue @label0 (le i32 i32 (dread i32 %Reg4_I, constval i32 0))\n #INSTIDX : 9||0009: invokestatic\n #Call function:LArith_3B_7Craise__sigfpe_7C_28_29V\n dassign %__muid_symptr 0 (iread ptr <* <$MUIDFuncDefTabEntry>> 1 (array 0 ptr <* <[4] <$MUIDFuncDefTabEntry>>> (addrof ptr $__muid_func_def_tab$$Arith_jar, constval i64 1)))\n icallassigned (dread ptr %__muid_symptr) {}\n #INSTIDX : 12||000c: goto\n goto @label1\n@label0 #INSTIDX : 15||000f: iload_0\n #INSTIDX : 16||0010: ifne\n brtrue @label1 (ne i32 i32 (dread i32 %Reg4_I, constval i32 0))\n #INSTIDX : 19||0013: iinc\n dassign %Reg2_I 0 (add i32 (dread i32 %Reg2_I, constval i32 103))\n #INSTIDX : 22||0016: new\n regassign ptr %1 (dread ref %Reg0_R19929)\n dassign %Reg0_R19929 0 (gcmalloc ref <$Ljava_2Flang_2FArithmeticException_3B>)\n intrinsiccall MCCDecRef (regread ptr %1)\n #INSTIDX : 25||0019: dup\n #INSTIDX : 26||001a: invokespecial\n #Call function:Ljava_2Flang_2FArithmeticException_3B_7C_3Cinit_3E_7C_28_29V\n dassign %__muid_symptr 0 (iread ptr <* <$MUIDUnifiedUndefTabEntry>> 1 (array 0 ptr <* <[13] <$MUIDUnifiedUndefTabEntry>>> (addrof ptr $__muid_func_undef_tab$$Arith_jar, constval i64 10)))\n icallassigned (dread ptr %__muid_symptr, dread ref %Reg0_R19929) {}\n #INSTIDX : 29||001d: athrow\n regassign ptr %2 (dread ref %Reg0_R510)\n dassign %Reg0_R510 0 (retype ref <* <$Ljava_2Flang_2FThrowable_3B>> (dread ref %Reg0_R19929))\n intrinsiccall MCCIncRef (dread ref %Reg0_R510)\n intrinsiccall MCCDecRef (regread ptr %2)\n throw (dread ref %Reg0_R510)\n@label1 #INSTIDX : 30||001e: iinc\n dassign %Reg2_I 0 (add i32 (dread i32 %Reg2_I, constval i32 3))\n endtry\n dassign %Reg2_I 0 (cvt i32 i32 (dread i32 %Reg2_I))\n #INSTIDX : 33||0021: goto\n goto @label3\n@label2 catch { <* <$Ljava_2Flang_2FArithmeticException_3B>> }\n intrinsiccall MCCDecRef (dread ref %Reg0_R19929)\n dassign %Reg0_R19929 0 (regread ptr %%thrownval)\n #INSTIDX : 36||0024: astore_2\n intrinsiccall MCCIncRef (dread ref %Reg0_R19929)\n intrinsiccall MCCDecRef (dread ref %Reg3_R19929)\n dassign %Reg3_R19929 0 (dread ref %Reg0_R19929)\n #INSTIDX : 37||0025: iinc\n dassign %Reg2_I 0 (add i32 (dread i32 %Reg2_I, constval i32 100))\n dassign %Reg2_I 0 (cvt i32 i32 (dread i32 %Reg2_I))\n@label3 #INSTIDX : 40||0028: iload_1\n #INSTIDX : 41||0029: ireturn\n intrinsiccall MPL_CLEANUP_LOCALREFVARS (dread ref %Reg0_R19929, dread ref %Reg0_R510, dread ref %Reg3_R19929)\n return (dread i32 %Reg2_I)\n}\nfunc &LArith_3B_7Cmain_7C_28ALjava_2Flang_2FString_3B_29V public static (var %Reg2_R743 <* <[] <* <$Ljava_2Flang_2FString_3B>>>>) void {\n funcid 48156\n var %Reg0_R562 <* <$Ljava_2Fio_2FPrintStream_3B>> localrefvar\n var %Reg1_I i32\n var %__muid_symptr <* void>\n\n #INSTIDX : 0||0000: getstatic\n intrinsiccall MPL_CLINIT_CHECK (addrof ptr $__cinf_Ljava_2Flang_2FSystem_3B)\n regassign ptr %1 (dread ref %Reg0_R562)\n #Read from: Ljava_2Flang_2FSystem_3B_7Cout\n dassign %Reg0_R562 0 (iread ref <* <* <$Ljava_2Fio_2FPrintStream_3B>>> 0 (iread ptr <* <$MUIDUnifiedUndefTabEntry>> 1 (array 0 ptr <* <[4] <$MUIDUnifiedUndefTabEntry>>> (addrof ptr $__muid_data_undef_tab$$Arith_jar, constval i64 1))))\n intrinsiccall MCCIncRef (dread ref %Reg0_R562)\n intrinsiccall MCCDecRef (regread ptr %1)\n #INSTIDX : 3||0003: bipush\n dassign %Reg1_I 0 (constval i32 -5)\n #INSTIDX : 5||0005: invokestatic\n #Call function:LArith_3B_7CTestMain_7C_28I_29I\n dassign %__muid_symptr 0 (iread ptr <* <$MUIDFuncDefTabEntry>> 1 (array 0 ptr <* <[4] <$MUIDFuncDefTabEntry>>> (addrof ptr $__muid_func_def_tab$$Arith_jar, constval i64 2)))\n icallassigned (dread ptr %__muid_symptr, dread i32 %Reg1_I) { dassign %Reg1_I 0 }\n #INSTIDX : 8||0008: invokevirtual\n icallassigned (\n iread u64 <* u64> 0 (add ptr (\n iread ptr <* <$__class_meta__>> 6 (iread ref <* <$Ljava_2Flang_2FObject_3B>> 1 (dread ref %Reg0_R562)),\n constval u32 272)),\n dread ref %Reg0_R562,\n dread i32 %Reg1_I) {}\n #INSTIDX : 11||000b: getstatic\n intrinsiccall MPL_CLINIT_CHECK (addrof ptr $__cinf_Ljava_2Flang_2FSystem_3B)\n regassign ptr %2 (dread ref %Reg0_R562)\n #Read from: Ljava_2Flang_2FSystem_3B_7Cout\n dassign %Reg0_R562 0 (iread ref <* <* <$Ljava_2Fio_2FPrintStream_3B>>> 0 (iread ptr <* <$MUIDUnifiedUndefTabEntry>> 1 (array 0 ptr <* <[4] <$MUIDUnifiedUndefTabEntry>>> (addrof ptr $__muid_data_undef_tab$$Arith_jar, constval i64 1))))\n intrinsiccall MCCIncRef (dread ref %Reg0_R562)\n intrinsiccall MCCDecRef (regread ptr %2)\n #INSTIDX : 14||000e: iconst_0\n dassign %Reg1_I 0 (constval i32 0)\n #INSTIDX : 15||000f: invokestatic\n #Call function:LArith_3B_7CTestMain_7C_28I_29I\n dassign %__muid_symptr 0 (iread ptr <* <$MUIDFuncDefTabEntry>> 1 (array 0 ptr <* <[4] <$MUIDFuncDefTabEntry>>> (addrof ptr $__muid_func_def_tab$$Arith_jar, constval i64 2)))\n icallassigned (dread ptr %__muid_symptr, dread i32 %Reg1_I) { dassign %Reg1_I 0 }\n #INSTIDX : 18||0012: invokevirtual\n icallassigned (\n iread u64 <* u64> 0 (add ptr (\n iread ptr <* <$__class_meta__>> 6 (iread ref <* <$Ljava_2Flang_2FObject_3B>> 1 (dread ref %Reg0_R562)),\n constval u32 272)),\n dread ref %Reg0_R562,\n dread i32 %Reg1_I) {}\n #INSTIDX : 21||0015: return\n intrinsiccall MPL_CLEANUP_LOCALREFVARS (dread ref %Reg0_R562)\n return ()\n}\nfunc &Java_Arith_raise_1sigfpe__ weak () void {\n funcid 0\n\n callassigned &MCC_CannotFindNativeMethod (conststr ptr \"LArith_3B_7Craise__sigfpe_7C_28_29V\") {}\n}\n","avg_line_length":63.1791530945,"max_line_length":1445,"alphanum_fraction":0.7327799546} +{"size":11370,"ext":"mpl","lang":"Maple","max_stars_count":32.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n 7b68d745-a7b8-48b9-bd9c-05c0f8725a35(org.iets3.core.base)<\/dependency>\n daafa647-f1f7-4b0b-b096-69cd7c8408c0(jetbrains.mps.baseLanguage.regexp)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 6ed54515-acc8-4d1e-a16c-9fd6cfe951ea(MPS.Core)<\/dependency>\n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/dependency>\n 47f075a6-558e-4640-a606-7ce0236c8023(com.mbeddr.mpsutil.interpreter)<\/dependency>\n 92d2ea16-5a42-4fdf-a676-c7604efe3504(de.slisson.mps.richtext)<\/dependency>\n b0f8641f-bd77-4421-8425-30d9088a82f7(org.apache.commons)<\/dependency>\n dbe08fb5-334d-4b64-86a0-622406fa0e87(org.iets3.core.expr.base.runtime)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/extendedLanguage>\n ceab5195-25ea-4f22-9b92-103b95ca8c0c(jetbrains.mps.lang.core)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":90.2380952381,"max_line_length":136,"alphanum_fraction":0.7541776605} +{"size":5498,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":80.8529411765,"max_line_length":148,"alphanum_fraction":0.7464532557} +{"size":1896,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"#################################\n# Using direct einstein's tensor\n# equation to built IREs\n################################\nread(\"eq_ire.mpl\"):\n\nres2:=grcomponent(HSR):\ntg2:=grcomponent(TG2(up),[x]):\n\nwith(DEtools):\naddcoords(compact,[t,x],[t,ctfm(x)]);\n\nire_fields := [res2, tg2, restt, restx, resxx, resthth, ire_rpsi_direct]:\nc_ire_fields := [0, 0, 0 , 0 , 0 , 0 , 0]:\n\n# Compactifying Einstein's equation:\nfor ii from 1 to nops(ire_fields) do\n c_ire_fields[ii] := PDEchangecoords(ire_fields[ii],[t,x],compact,[t,x]);\n c_ire_fields[ii] := subs({diff(ctfm(x),x)=ctfmp(x),diff(ctfm(x),x,x)=ctfmpp(x)},c_ire_fields[ii]); \n\n for kk from 1 to nops(grid_functions) do\n fn := grid_functions[kk];\n c_ire_fields[ii] := subs(fn(t,ctfm(x))=fn(t,x),c_ire_fields[ii]);\n end do:\n\nend do:\n\nprintf(\"checking compactification... all residuals should be zero:\\n\");\nfor ii from 1 to nops(ire_fields) do\n res := simplify(ire_fields[ii] - eval(c_ire_fields[ii],{ctfm(x) = x, ctfmp(x) = 1, ctfmpp(x) = 0})):\n printf(\"res = %a\\n\",res);\nend do:\n\n\nfor ii from 1 to nops(ire_fields) do\n c_ire_fields[ii] := collect(collect(eval(expand(c_ire_fields[ii]),{ctfmpp(x)=octfmp(x)*ctfmp(x)^2}),1\/ctfmp(x)),1\/ctfm(x));\nend do:\n\nres2 := c_ire_fields[1]:\ntg2 := c_ire_fields[2]:\nrestt := c_ire_fields[3]:\nrestx := c_ire_fields[4]:\nresxx := c_ire_fields[5]:\nresthth := c_ire_fields[6]:\nire_rpsi_direct := c_ire_fields[7]:\n\n\nGen_Eval_Code(restx,input=\"c\",proc_name=\"ire_restx\");\nGen_Eval_Code(resxx,input=\"c\",proc_name=\"ire_resxx\");\nGen_Eval_Code(restt,input=\"c\",proc_name=\"ire_restt\");\nGen_Eval_Code(resthth,input=\"c\",proc_name=\"ire_resthth\");\nGen_Eval_Code(tg2-Lamx(t,x),input=\"c\",proc_name=\"ire_val_lamx\");\nGen_Eval_Code(ire_rpsi_direct,input=\"c\",proc_name=\"ire_rpsi_direct\");\n\npl:=table([ t=[-1,-1],x=[-1,0],y=[-1,-1],z=[-1,-1] ]):\nUpdate_FD_Table(2,pl):\n\nGen_Eval_Code(res2,input=\"c\",proc_name=\"ire_hs\");\n","avg_line_length":32.1355932203,"max_line_length":126,"alphanum_fraction":0.6624472574} +{"size":8931,"ext":"mpl","lang":"Maple","max_stars_count":327.0,"content":"kernelopts(assertlevel=2): # be strict on all assertions while testing\nkernelopts(opaquemodules=false): # allow testing of internal routines\nif not (NewSLO :: `module`) then\n WARNING(\"loading NewSLO failed\");\n `quit`(3);\nend if;\n\nwith(Hakaru):\nwith(NewSLO):\n\n#####################################################################\n#\n# plate\/array tests\n#\n#####################################################################\n\ntriv := Plate(k, i, Ret(i)):\nTestHakaru(triv, Ret(ary(k, i, i)), label=\"Dirac Plate\");\n\nary0 := Bind(Plate(k, i, Gaussian(0,1)), xs, Ret([xs])):\nTestHakaru(ary0, ary0, label=\"plate roundtripping\", ctx = [k::nonnegint]);\n\nary1 := Bind(Gaussian(0,1), x,\n Bind(Plate(n, i, Weight(density[Gaussian](x,1)(idx(t,i)), Ret(Unit))), ys,\n Ret(x))):\nary1w := 2^(-(1\/2)*n+1\/2)*exp(sum(idx(t,i),i=0..n-1)^2\/(n+1)\/2)*exp(-sum(idx(t,i)^2,i=0..n-1)\/2)*Pi^(-(1\/2)*n)\/sqrt(2+2*n):\nTestHakaru(ary1, \n Weight(ary1w, Gaussian((sum(idx(t, i), i = 0 .. n-1))\/(n+1), 1\/sqrt(n+1))),\n label=\"Wednesday goal\", ctx = [n::nonnegint]);\nTestHakaru(Bind(ary1, x, Ret(Unit)), Weight(ary1w, Ret(Unit)), \n label=\"Wednesday goal total\", ctx = [n::nonnegint]);\nary2 := Bind(Gaussian(0,1), x,\n Bind(Plate(n, i, Bind(Gaussian(idx(t,i),1),z, Weight(density[Gaussian](x,1)(idx(t,i)), Ret(z+1)))), ys,\n Ret(ys))):\nTestHakaru(ary2, \n Weight(ary1w, Bind(Plate(n, i, Gaussian(idx(t,i),1)), zs, Ret(ary(n, i, idx(zs,i)+1)))), \n label=\"Reason for fission\", ctx = [n::nonnegint]);\nary3 := Bind(Gaussian(0,1), x,\n Bind(Plate(n, i, Bind(Gaussian(idx(t,i),1),z, Weight(density[Gaussian](x,1)(idx(t,i)), Ret(z)))), zs,\n Ret(zs))):\nTestHakaru(ary3, Weight(ary1w, Plate(n, i, Gaussian(idx(t,i),1))),\n label=\"Array eta\", ctx = [n::nonnegint]);\nTestHakaru(Ret(ary(n,i,idx(f(i),i))), label=\"Don't overdo array eta\");\n\nbry1 := Bind(BetaD(alpha,beta), x,\n Bind(Plate(n, i, Weight(x ^piecewise(idx(y,i)=true ,1) *\n (1-x)^piecewise(idx(y,i)=false,1),\n Ret(Unit))), ys,\n Ret(x))):\nbry1s := Weight(Beta(alpha+sum(piecewise(idx(y,i)=true ,1), i=0..n-1),\n beta +sum(piecewise(idx(y,i)=false,1), i=0..n-1))\/Beta(alpha,beta),\n BetaD(alpha+sum(piecewise(idx(y,i)=true ,1), i=0..n-1),\n beta +sum(piecewise(idx(y,i)=false,1), i=0..n-1))):\nTestHakaru(bry1, bry1s, \n label=\"first way to express flipping a biased coin many times\",\n ctx = [n::nonnegint]);\n\nbry2 := Bind(BetaD(alpha,beta), x,\n Bind(Plate(n, i, Weight(x ^( idx(y,i)) *\n (1-x)^(1-idx(y,i)),\n Ret(Unit))), ys,\n Ret(x))):\nbry2s := Weight(Beta(alpha+ sum(idx(y,i),i=0..n-1),\n beta +n-sum(idx(y,i),i=0..n-1))\/Beta(alpha,beta),\n BetaD(alpha+ sum(idx(y,i),i=0..n-1),\n beta +n-sum(idx(y,i),i=0..n-1))):\nTestHakaru(bry2, bry2s, \n label=\"second way to express flipping a biased coin many times\", \n ctx = [n::nonnegint]);\n\nfission := Bind(Plate(k, i, Gaussian(f(i),1)), xs, Plate(k, i, Gaussian(idx(xs,i),1))):\nfusion := Plate(k, i, Bind(Gaussian(f(i),1), x, Gaussian(x,1))):\nconjugacies := Plate(k, i, Gaussian(f(i), sqrt(2))):\nconjugacies5:= Bind(Gaussian(f(0), sqrt(2)), x0,\n Bind(Gaussian(f(1), sqrt(2)), x1,\n Bind(Gaussian(f(2), sqrt(2)), x2,\n Bind(Gaussian(f(3), sqrt(2)), x3,\n Bind(Gaussian(f(4), sqrt(2)), x4,\n Ret([x0,x1,x2,x3,x4])))))):\nTestHakaru( fission , conjugacies , verify=normal, label=\"Conjugacy across plates (function)\", ctx=[k::nonnegint]);\nTestHakaru( fusion , conjugacies , verify=normal, label=\"Conjugacy in plate (function)\", ctx=[k::nonnegint]);\nTestHakaru(eval(fission,{k=5 }), conjugacies5 , verify=normal, label=\"Conjugacy across plates unrolled (function)\");\nTestHakaru(eval(fusion ,{k=5 }), conjugacies5 , verify=normal, label=\"Conjugacy in plate unrolled (function)\");\nTestHakaru(eval(fission,{ f=1 }), eval(conjugacies ,{ f=1 }), verify=normal, label=\"Conjugacy across iid plates\", ctx=[k::nonnegint]);\nTestHakaru(eval(fusion ,{ f=1 }), eval(conjugacies ,{ f=1 }), verify=normal, label=\"Conjugacy in iid plate\", ctx=[k::nonnegint]);\nTestHakaru(eval(fission,{k=5,f=1 }), eval(conjugacies5,{ f=1 }), verify=normal, label=\"Conjugacy across iid plates unrolled\");\nTestHakaru(eval(fusion ,{k=5,f=1 }), eval(conjugacies5,{ f=1 }), verify=normal, label=\"Conjugacy in iid plate unrolled\");\nTestHakaru(eval(fission,{ f=(i->z^i)}), eval(conjugacies ,{ f=(i->z^i)}), verify=normal, label=\"Conjugacy across plates\", ctx=[k::nonnegint,z>0]);\nTestHakaru(eval(fusion ,{ f=(i->z^i)}), eval(conjugacies ,{ f=(i->z^i)}), verify=normal, label=\"Conjugacy in plate\", ctx=[k::nonnegint,z>0]);\nTestHakaru(eval(fission,{k=5,f=(i->z^i)}), eval(conjugacies5,{k=5,f=(i->z^i)}), verify=normal, label=\"Conjugacy across plates unrolled\", ctx=[z>0]);\nTestHakaru(eval(fusion ,{k=5,f=(i->z^i)}), eval(conjugacies5,{k=5,f=(i->z^i)}), verify=normal, label=\"Conjugacy in plate unrolled\", ctx=[z>0]);\n\n# Don't be confused by extra iterations in plate\nextra_1 := Bind(Plate(n+1,i,Gaussian(0,1)),xs, Plate(n,i,Gaussian(idx(xs,i+1),1))):\nextra_2 := Bind(Plate(n+1,i,Gaussian(0,1)),xs, Plate(n,i,Gaussian(idx(xs,i ),1))):\nextra_s := Plate(n,i,Gaussian(0,sqrt(2))):\nTestHakaru(extra_1, extra_s, label=\"Don't be confused by extra iterations at beginning of plate\", ctx=[n::nonnegint]);\nTestHakaru(extra_2, extra_s, label=\"Don't be confused by extra iterations at end of plate\" , ctx=[n::nonnegint]);\n\n# Simplify by size of array\nTestHakaru(Bind(Plate(k,c,Uniform(37,42)),xs,Weight(f(size(xs)),Ret(Unit))),\n Weight(f(k),Ret(Unit)),\n label=\"plate size\", ctx = [k::nonnegint]):\n\n# Simplifying gmm below is a baby step towards index manipulations we need\ngmm := Bind(Plate(k, c, Gaussian(0,1)), xs,\n Bind(Plate(n, i, Weight(density[Gaussian](idx(xs,idx(cs,i)),1)(idx(t,i)), Ret(Unit))), ys,\n Ret(xs))):\ngmm_s := Weight(2^(-(1\/2)*n)*Pi^(-(1\/2)*n)*exp(-(1\/2)*(sum(idx(t,i)^2, i=0..n-1)))*\n exp((1\/2)*(sum((sum(piecewise(c=idx(cs,i), idx(t,i), 0), i=0..n-1))^2\/(1+sum(piecewise(c=idx(cs,i), 1, 0), i=0..n-1)), c=0..k-1))) *\n sqrt(1\/product(1+sum(piecewise(c=idx(cs,i), 1, 0), i=0..n-1), c=0..k-1)),\n Plate(k, c,\n Gaussian((sum(piecewise(c=idx(cs,i), idx(t,i), 0), i=0..n-1))\/\n (sum(piecewise(c=idx(cs,i), 1, 0), i=0..n-1)+1),\n (1\/(sum(piecewise(c=idx(cs,i), 1, 0), i=0..n-1)+1))^(1\/2)))):\nTestHakaru(gmm, gmm_s,\n label=\"gmm (currently failing -- due to alpha-equivalence)\",\n ctx = [k::nonnegint, n::nonnegint]);\nTestHakaru(Bind(gmm, xs, Ret(cs)),\n subsop(2=Ret(cs), gmm_s),\n label=\"gmm total (currently failing -- due to alpha-equivalence)\",\n ctx = [k::nonnegint, n::nonnegint]);\n\n# Detecting Dirichlet-multinomial conjugacy when unrolled\ndirichlet := proc(as)\n Bind(Plate(size(as)-1, i, BetaD(sum(idx(as,j), j=0..i), idx(as,i+1))), xs,\n Ret(ary(size(as), i,\n product(idx(xs,j), j=i..size(as)-2)\n * piecewise(0=i, 1, 1-idx(xs,i-1)))))\nend proc:\ncategorical := proc(ps)\n Bind(Counting(0, size(ps)), i, Weight(idx(ps,i), Ret(i)))\nend proc:\n# The next line eta-expands CodeTools[Test] so that its arguments get evaluated\n(proc() CodeTools[Test](_passed) end proc)\n (op(2, [unweight(\n fromLO(improve(toLO(\n Plate(n,k,\n Bind(dirichlet(ary(5,i,1)),ps,\n Weight(product(idx(ps,i)^idx(idx(t,k),i),i=0..size(ps)-1),\n Ret(ps))))))))]),\n fromLO(toLO(\n Plate(n,k,\n dirichlet(ary(5,i,1+idx(idx(t,k),i)))))),\n measure(simplify),\n label=\"Conjugacy between unrolled symmetric Dirichlet and multinomial\");\n# We'd like the test above to pass even if the count 5 becomes symbolic.\n# Below is some progress towards this goal:\nTestHakaru(dirichlet(as), label=\"Dirichlet symbolic prior roundtrip\");\nTestHakaru(Context(size(as)>0,\n Bind(dirichlet(as),ps,\n Weight(product(idx(ps,i)^idx(t,i),i=0..size(ps)-1),\n Ret(ps)))),\n Context(size(as)>0,\n Weight(product(Beta(idx(as,i+1)+idx(t,i+1),idx(t,0)+sum(idx(as,k),k=0..i)+sum(idx(t,k),k=1..i)),i=0..size(as)-2)\n \/product(Beta(idx(as,i+1),sum(idx(as,k),k=0..i)),i=0..size(as)-2),\n Bind(Plate(size(as)-1,i,BetaD(idx(t,0)+sum(idx(as,k),k=0..i)+sum(idx(t,k),k=1..i),idx(as,i+1)+idx(t,i+1))),xs,\n Ret(ary(size(as),i,piecewise(i=0,product(idx(xs,j),j=0..size(as)-2),product(idx(xs,j),j=i..size(as)-2)*(1-idx(xs,i-1)))))))),\n label=\"Conjugacy between rolled Dirichlet and multinomial\");\n","avg_line_length":55.81875,"max_line_length":159,"alphanum_fraction":0.5709327063} +{"size":7465,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":73.1862745098,"max_line_length":143,"alphanum_fraction":0.7311453449} +{"size":10228,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n 2d3c70e9-aab2-4870-8d8d-6036800e4103(jetbrains.mps.kernel)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":79.90625,"max_line_length":141,"alphanum_fraction":0.7368987094} +{"size":9323,"ext":"mpl","lang":"Maple","max_stars_count":32.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n d4280a54-f6df-4383-aa41-d1b2bffa7eb1(com.mbeddr.core.base)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 7d21cc4b-4c24-41db-9868-8af4a7f3eba9(org.iets3.core.trace)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":87.1308411215,"max_line_length":130,"alphanum_fraction":0.7494368765} +{"size":409,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_gga_x *)\n\nmu := 0.0617:\nkappa := 1.245:\nalpha := 0.0483:\n\nf0 := s -> 1 + mu*s^2*exp(-alpha*s^2) + kappa*(1 - exp(-1\/2*alpha*s^2)):\nf := x -> f0(X2S*x):\n","avg_line_length":24.0588235294,"max_line_length":72,"alphanum_fraction":0.6185819071} +{"size":6850,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n adfd00cb-58d7-4094-bca8-f941a491e04f(org.campagnelab.gobyweb)<\/dependency>\n 0202ed86-955d-4227-9c20-377dd6b1f9ff(org.campagnelab.nyosh.lib)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n ceab5195-25ea-4f22-9b92-103b95ca8c0c(jetbrains.mps.lang.core)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":76.1111111111,"max_line_length":136,"alphanum_fraction":0.739270073} +{"size":1431,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_lda *)\n(* prefix:\n lda_c_pw_params *params;\n\n assert(p->params != NULL);\n params = (lda_c_pw_params * )(p->params);\n*)\n\n$ifdef lda_c_pw_params\nparams_a_pp := [1, 1, 1]:\nparams_a_a := [0.031091, 0.015545, 0.016887]:\nparams_a_alpha1 := [0.21370, 0.20548, 0.11125]:\nparams_a_beta1 := [7.5957, 14.1189, 10.357]:\nparams_a_beta2 := [3.5876, 6.1977, 3.6231]:\nparams_a_beta3 := [1.6382, 3.3662, 0.88026]:\nparams_a_beta4 := [0.49294, 0.62517, 0.49671]:\nparams_a_fz20 := 1.709921:\n$endif\n\n$ifdef lda_c_pw_modified_params\nparams_a_a := [0.0310907, 0.01554535, 0.0168869]:\nparams_a_fz20 := 1.709920934161365617563962776245:\n$endif\n\n(* Equation (10) *)\ng_aux := (k, rs) -> params_a_beta1[k]*sqrt(rs) + params_a_beta2[k]*rs\n + params_a_beta3[k]*rs^1.5 + params_a_beta4[k]*rs^(params_a_pp[k] + 1):\ng := (k, rs) -> -2*params_a_a[k]*(1 + params_a_alpha1[k]*rs)\n * log(1 + 1\/(2*params_a_a[k]*g_aux(k, rs))):\n\n(* Equation (8) *)\n(* Attention, the function g parametrizes -alpha *)\nf_pw := (rs, zeta) ->\n g(1, rs) + zeta^4*f_zeta(zeta)*(g(2, rs) - g(1, rs) + g(3, rs)\/params_a_fz20)\n - f_zeta(zeta)*g(3, rs)\/params_a_fz20:\n\nf := (rs, zeta) -> f_pw(rs, zeta):\n","avg_line_length":31.1086956522,"max_line_length":79,"alphanum_fraction":0.642907058} +{"size":2914,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"`phi\/F1bar\/ord` := (A::set) -> proc(x)\n return sort([op(A)],(a,b) -> ((a=b) or (op(x[{a,b}][a]) < op(x[{a,b}][b]))));\nend:\n\n######################################################################\n# Apply the isomorphism R^1 = R\n\n`trim\/F1bar` := (A::set) -> proc(x)\n local u,x0,P,T,a;\n\n x0 := table();\n P := `list_elements\/big_subsets`(A);\n for T in P do\n u := `bottom_normalise\/SW`(1)(T)(x[T]); \n x0[T] := table();\n for a in T do \n x0[T][a] := op(u[a]);\n od;\n od;\n\n return eval(x0):\nend:\n\n######################################################################\n\n`subcritical_tree\/F1bar` := (A::set) -> proc(x)\n local x0,R,n,SS,i,j,J,J1,g1,g2,is_subcritical,a,k;\n\n x0 := `trim\/F1bar`(A)(x);\n\n R := `phi\/F1bar\/ord`(A)(x);\n n := nops(A);\n SS := seq({a},a in A);\n\n for i from 1 to n-1 do \n for j from i+1 to n do\n J := {seq(R[k],k=i..j)};\n is_subcritical := true;\n if i > 1 then\n J1 := {R[i-1],op(J)};\n g1 := `gap\/real_functions`(J )(x0[J1]);\n g2 := `gap\/real_functions`(J1)(x0[J1]);\n if g2 = g1 then\n is_subcritical := false;\n fi;\n fi;\n if j < n then\n J1 := {op(J),R[j+1]};\n g1 := `gap\/real_functions`(J )(x0[J1]);\n g2 := `gap\/real_functions`(J1)(x0[J1]);\n if g2 = g1 then\n is_subcritical := false;\n fi;\n fi;\n\n if is_subcritical then\n SS := SS,J;\n fi;\n od;\n od;\n SS := {SS};\n return SS;\nend:\n\n######################################################################\n\n`theta\/F1bar\/K` := (A::set) -> proc(x)\n local x0,R,n,SS,i,j,k,J,J1,t,parent;\n\n x0 := `trim\/F1bar`(A)(x);\n R := `phi\/F1bar\/ord`(A)(x);\n SS := `subcritical_tree\/F1bar`(A)(x);\n parent := parent_map(A)(SS);\n n := nops(A);\n t := table();\n\n for i from 1 to n do \n for j from i to n do \n J := {seq(R[k],k=i..j)};\n if nops(J) = 1 or nops(J) = n then\n t[J] := 1; \n elif not(member(J,SS)) then\n t[J] := 0;\n else\n J1 := parent[J];\n t[J] := 1 - `gap\/real_functions`(J)(x0[J1])\/\n `gap\/real_functions`(J1)(x0[J1]);\n fi;\n od;\n od;\n\n return [R,eval(t)];\nend:\n\n######################################################################\n\n`phi\/K\/F1bar` := (A::set) -> proc(Rt)\n local R,t,n,r,i,j,k,l,x,P,Q,Q1,J,M,M1,m,T,U;\n\n R,t := op(Rt);\n \n n := nops(A);\n r := table();\n for i from 1 to n do r[R[i]] := i; od;\n\n x := table();\n m := table();\n\n P := `list_elements\/big_subsets`(A);\n Q := {seq(seq([seq(R[k],k=i..j)],j=i..n),i=1..n)};\n Q1 := select(J -> nops(J)>1,Q);\n\n for J in Q do\n m[J] := table();\n M := select(U -> ({op(J)} minus {op(U)} <> {}),Q);\n for i from 1 to nops(J) - 1 do\n M1 := select(U -> member(J[i],U) and member(J[i+1],U),M);\n m[J][J[i]] := mul(1-t[{op(U)}],U in M1);\n od;\n od;\n\n for T in P do \n x[T] := table();\n i := min(op(map(a -> r[a],T)));\n j := max(op(map(a -> r[a],T)));\n J := [seq(R[k],k=i..j)];\n for k from i to j do\n if member(R[k],T) then\n x[T][R[k]] := [add(m[J][R[l]],l=i..k-1)];\n fi\n od;\n od;\n\n return eval(x);\nend:\n","avg_line_length":21.4264705882,"max_line_length":78,"alphanum_fraction":0.4440631434} +{"size":613,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_gga_c *)\n(* prefix:\n gga_c_zpbeint_params *params;\n \n assert(p->params != NULL);\n params = (gga_c_zpbeint_params * )(p->params);\n*)\n\nparams_a_gamma := (1 - log(2))\/Pi^2:\nparams_a_BB := 1:\n$include \"gga_c_pbe.mpl\"\n\nff := (z, t) -> mphi(z)^(params_a_alpha*t^3):\n\nf := (rs, z, xt, xs0, xs1) ->\n f_pw(rs, z) + ff(z, tp(rs, z, xt))*fH(rs, z, tp(rs, z, xt)):","avg_line_length":25.5416666667,"max_line_length":68,"alphanum_fraction":0.6264274062} +{"size":13957,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n f3eafff0-30d2-46d6-9150-f0f3b880ce27(org.iets3.core.expr.path)<\/dependency>\n d4280a54-f6df-4383-aa41-d1b2bffa7eb1(com.mbeddr.core.base)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 9464fa06-5ab9-409b-9274-64ab29588457(org.iets3.core.expr.lambda)<\/dependency>\n 47f075a6-558e-4640-a606-7ce0236c8023(com.mbeddr.mpsutil.interpreter)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n 7b68d745-a7b8-48b9-bd9c-05c0f8725a35(org.iets3.core.base)<\/dependency>\n db8bd035-3f51-41d8-8fed-954c202d18be(org.iets3.analysis.base)<\/dependency>\n 8d29d73f-ed99-4652-ae0a-083cdfe53c34(jetbrains.mps.ide.platform)<\/dependency>\n 6ed54515-acc8-4d1e-a16c-9fd6cfe951ea(MPS.Core)<\/dependency>\n 498d89d2-c2e9-11e2-ad49-6cf049e62fe5(MPS.IDEA)<\/dependency>\n 726886d1-ef90-4249-a08f-1e3ec23a7113(com.mbeddr.mpsutil.traceExplorer)<\/dependency>\n 28583149-5b6e-4663-9c02-b9a8fa3cb099(com.mbeddr.mpsutil.contextactions.runtime)<\/dependency>\n dbe08fb5-334d-4b64-86a0-622406fa0e87(org.iets3.core.expr.base.runtime)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 2f7e2e35-6e74-4c43-9fa5-2465d68f5996(org.iets3.core.expr.collections)<\/extendedLanguage>\n ceab5195-25ea-4f22-9b92-103b95ca8c0c(jetbrains.mps.lang.core)<\/extendedLanguage>\n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/extendedLanguage>\n 7b68d745-a7b8-48b9-bd9c-05c0f8725a35(org.iets3.core.base)<\/extendedLanguage>\n 9464fa06-5ab9-409b-9274-64ab29588457(org.iets3.core.expr.lambda)<\/extendedLanguage>\n f3eafff0-30d2-46d6-9150-f0f3b880ce27(org.iets3.core.expr.path)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":93.0466666667,"max_line_length":133,"alphanum_fraction":0.7573260729} +{"size":16549,"ext":"mpl","lang":"Maple","max_stars_count":796.0,"content":"# 1 + 8 -> 9\nfunc $testSum (var %i i32) i32 {\n return (\n add i32(constval i32 1, constval i32 8))\n}\n\n# sqrt(4.0) -> 2.0\nfunc $testSqrt (var %i i32) f32 {\n return (\n sqrt f32(constval f32 4.0f))\n}\n\n# 5 + (5 + a) -> a + 10\nfunc &testConstVarFold00 (var %a i32) i32 {\n return (add i32 (\n constval i32 5,\n add i32 (constval i32 5, dread i32 %a)))\n}\n\n# 5 + (5 - a) -> 10 - a\nfunc &testConstVarFold01 (var %a i32) i32 {\n return (add i32 (\n constval i32 5,\n sub i32 (constval i32 5, dread i32 %a)))\n}\n\n# 5 + (a + 5) -> a + 10\nfunc &testConstVarFold02 (var %a i32) i32 {\n return (add i32 (\n constval i32 5,\n add i32 (dread i32 %a, constval i32 5)))\n}\n\n# 6 + (a - 5) -> a + 1\nfunc &testConstVarFold03 (var %a i32) i32 {\n return (add i32 (\n constval i32 6,\n sub i32 (dread i32 %a, constval i32 5)))\n}\n\n# 5 * (5 * a) -> 5 * (5 * a)\nfunc &testConstVarFold04 (var %a i32) i32 {\n return (mul i32 (\n constval i32 5,\n mul i32 (constval i32 5, dread i32 %a)))\n}\n\n# 5 * (a * 5) -> 5 * (a * 5)\nfunc &testConstVarFold05 (var %a i32) i32 {\n return (mul i32 (\n constval i32 5,\n mul i32 (dread i32 %a, constval i32 5)))\n}\n\n# 3 - (2 - a) -> a + 1\nfunc &testConstVarFold06 (var %a i32) i32 {\n return (sub i32 (\n constval i32 3,\n sub i32 (constval i32 2, dread i32 %a)))\n}\n\n# 3 - (2 + a) -> 1 - a\nfunc &testConstVarFold07 (var %a i32) i32 {\n return (sub i32 (\n constval i32 3,\n add i32 (constval i32 2, dread i32 %a)))\n}\n\n# 3 - (a + 2) -> 1 - a\nfunc &testConstVarFold08 (var %a i32) i32 {\n return (sub i32 (\n constval i32 3,\n add i32 (dread i32 %a, constval i32 2)))\n}\n\n# 3 - (a - 2) -> 5 - a\nfunc &testConstVarFold09 (var %a i32) i32 {\n return (sub i32 (\n constval i32 3,\n sub i32 (dread i32 %a, constval i32 2)))\n}\n\n# (2 + a) - 3 -> a - 1\nfunc &testConstVarFold10 (var %a i32) i32 {\n return (sub i32 (\n add i32 (constval i32 2, dread i32 %a),\n constval i32 3))\n}\n\n# (2 - a) - 3 -> -a - 1\nfunc &testConstVarFold11 (var %a i32) i32 {\n return (sub i32 (\n sub i32 (constval i32 2, dread i32 %a),\n constval i32 3))\n}\n\n# (a + 2) - 3 -> a - 1\nfunc &testConstVarFold12 (var %a i32) i32 {\n return (sub i32 (\n add i32 (dread i32 %a, constval i32 2),\n constval i32 3))\n}\n\n# (a - 2) - 3 -> a - 5\nfunc &testConstVarFold13 (var %a i32) i32 {\n return (sub i32 (\n sub i32 (dread i32 %a, constval i32 2),\n constval i32 3))\n}\n\n# 1 + (5 + ((5 - a) - 3)) -> 8 - a\nfunc &testConstVarFold15 (var %a i32) i32 {\n return (add i32 (\n constval i32 1,\n add i32 (\n constval i32 5,\n sub i32 (\n sub i32 (constval i32 5, dread i32 %a),\n constval i32 3))))\n}\n\n# 1 + (5 + ((5 - a) * 3)) -> ((5 - a) * 3) + 6\nfunc &testConstVarFold16 (var %a i32) i32 {\n return (add i32 (\n constval i32 1,\n add i32 (\n constval i32 5,\n mul i32 (\n sub i32 (constval i32 5, dread i32 %a),\n constval i32 3))))\n}\n\n# (-a) + b --> (-a) + b\nfunc &testConstantFoldAdd00 (var %a i32, var %b i32) i32 {\n return (add i32 (\n neg i32 (dread i32 %a),\n dread i32 %b))\n}\n\n# a + (-b) --> a + (-b)\nfunc &testConstantFoldAdd01 (var %a i32, var %b i32) i32 {\n return (add i32 (\n dread i32 %a,\n neg i32 (dread i32 %b)))\n}\n\n\n# 5.0f + (5 - a) -> same, no folding with floating point numbers\nfunc &testConstVarFold20 (var %a i32) i32 {\n return (add f32 (\n constval f32 5.0f,\n sub i32 (constval i32 5, dread i32 %a)))\n}\n\n\nfunc &testConstFold0 (var %a i32, var %b i32, var %c i32) i32 {\n # ((a + 5) + ((2 + c) + (4 + 2))) -> ((a + c) + 13)\n return (add i32 (\n add i32 (dread i32 %a, constval i32 0x5),\n add i32 (\n add i32 (constval i32 0x2, dread i32 %c),\n add i32 (constval i32 0x4, constval i32 0x2))))\n}\n\nfunc &testConstFold1 (var %a i32, var %b i32, var %c i32) i32 {\n # ((a + 5) + (2 + c)) -> ((a + c) + 7)\n return (add i32 (\n add i32 (dread i32 %a, constval i32 0x5),\n add i32 (constval i32 0x2, dread i32 %c)))\n}\n\nfunc &testConstFold2 (var %a i32, var %b i32, var %c i32) i32 {\n # ((a - 5) - ((b - c) - (4 - 2))) -> ((a - (b - c)) - 3)\n return (sub i32 (\n sub i32 (dread i32 %a, constval i32 0x5),\n sub i32 (\n sub i32 (dread i32 %b, dread i32 %c),\n sub i32 (constval i32 0x4, constval i32 0x2))))\n}\n\nfunc &testConstFold3 (var %a i32, var %b i32, var %c i32) i32 {\n # ((a - 5) + ((b - c) - (4 - 2))) -> ((a + (b - c)) - 7)\n return (add i32 (\n sub i32 (dread i32 %a, constval i32 0x5),\n sub i32 (\n sub i32 (dread i32 %b, dread i32 %c),\n sub i32 (constval i32 0x4, constval i32 0x2))))\n}\n\nfunc &testConstFold4 (var %a i32, var %b i32, var %c i32) i32 {\n # ((a - 5) - ((4 - 2) - (4 - b))) -> ((a - b) - 3)\n return (sub i32 (\n sub i32 (dread i32 %a, constval i32 0x5),\n sub i32 (\n sub i32 (constval i32 0x4, constval i32 0x2),\n sub i32 (constval i32 0x4, dread i32 %b))))\n}\n\nfunc &testConstFold5 (var %a i32, var %b i32, var %c i32) i32 {\n # ((5 - a) - ((b - 4) - (4 - b))) -> (((-a) - (b - (-b))) + 13)\n return (sub i32 (\n sub i32 (constval i32 0x5, dread i32 %a),\n sub i32 (\n sub i32 (dread i32 %b, constval i32 0x4),\n sub i32 (constval i32 0x4, dread i32 %b))))\n}\n\nfunc &testConstFold6 (var %a i32, var %b i32, var %c i32) i32 {\n # ((5 - a) - ((4 - b) - (b - 4))) -> (((-a) - ((-b) - b)) - 3)\n return (sub i32 (\n sub i32 (constval i32 0x5, dread i32 %a),\n sub i32 (\n sub i32 (constval i32 0x4, dread i32 %b),\n sub i32 (dread i32 %b, constval i32 0x4))))\n}\n\nfunc &testConstFold7 (var %a i32, var %b i32, var %c i32) i32 {\n # ((a - 5) - ((4 + 2) - (4 - (b - c)))) -> ((a - (b - c)) - 7)\n return (sub i32 (\n sub i32 (dread i32 %a, constval i32 0x5),\n sub i32 (\n add i32 (constval i32 0x4, constval i32 0x2),\n sub i32 (\n constval i32 0x4,\n sub i32 (dread i32 %b, dread i32 %c)))))\n}\n\nfunc &testConstFold8 (var %a i32, var %b i32, var %c i32) i32 {\n # ((a - 5) - ((4 + 2) - (4 * (b - c)))) -> ((a - (-(4 * (b - c)))) - 11)\n return (sub i32 (\n sub i32 (dread i32 %a, constval i32 0x5),\n sub i32 (\n add i32 (constval i32 0x4, constval i32 0x2),\n mul i32 (\n constval i32 0x4,\n sub i32 (dread i32 %b, dread i32 %c)))))\n}\n\nfunc &testConstFold9 (var %a i32, var %b i32, var %c i32) i32 {\n # ((a - 5) - ((4 + 2) - (-(4 - (b - c))))) -> ((a - (-(b - c))) - 15)\n return (sub i32 (\n sub i32 (dread i32 %a, constval i32 0x5),\n sub i32 (\n add i32 (constval i32 0x4, constval i32 0x2),\n neg i32 (sub i32 (\n constval i32 0x4,\n sub i32 (dread i32 %b, dread i32 %c))))))\n}\n\nfunc &testConstFold10 (var %a i32, var %b i32, var %c i32) i32 {\n # ((4 + 2) * (-(4 - (3 - c)))) -> (6 * ((-c) - 1))\n return (mul i32 (\n add i32 (constval i32 0x4, constval i32 0x2),\n neg i32 (sub i32 (\n constval i32 0x4,\n sub i32 (constval i32 0x3, dread i32 %c)))))\n}\n\nfunc &testConstFold11 (var %a i32, var %b i32, var %c i32) i32 {\n # ((4 + 2) * (4 - (3 - c))) -> (6 * (c + 1))\n return (mul i32 (\n add i32 (constval i32 0x4, constval i32 0x2),\n sub i32 (\n constval i32 0x4,\n sub i32 (constval i32 0x3, dread i32 %c))))\n}\n\nfunc &testConstFold12 (var %a i32, var %b i32, var %c i32) i32 {\n # ((4 + 2) * (~(4 - (3 - c)))) -> (6 * (~(c + 1)))\n return (mul i32 (\n add i32 (constval i32 0x4, constval i32 0x2),\n bnot i32 (sub i32 (\n constval i32 0x4,\n sub i32 (constval i32 0x3, dread i32 %c)))))\n}\n\nfunc &testConstFold13 (var %a i32, var %b i32, var %c i32) i32 {\n # (5 * (((4 - 2) + (2 & 4)) - (4 - (c | 3)))) -> (5 * ((c | 3) - 2))\n return (mul i32 (\n constval i32 0x5,\n sub i32 (\n add i32 (\n sub i32 (constval i32 0x4, constval i32 0x2),\n band i32 (constval i32 0x2, constval i32 0x4)),\n sub i32 (\n constval i32 0x4,\n bior i32 (dread i32 %c, constval i32 0x3)))))\n}\n\nfunc &testConstFold14 (var %a i32, var %b i32, var %c i32) i32 {\n # (5 * (((4 - 2) + (2 & 4)) * (4 - (c | 3)))) -> (5 * (2 * (4 - (c | 3))))\n return (mul i32 (\n constval i32 0x5,\n mul i32 (\n add i32 (\n sub i32 (constval i32 0x4, constval i32 0x2),\n band i32 (constval i32 0x2, constval i32 0x4)),\n sub i32 (\n constval i32 0x4,\n bior i32 (dread i32 %c, constval i32 0x3)))))\n}\n\nfunc &testConstFold15 (var %a i32, var %b i32, var %c i32) i32 {\n # ((1 + 0) * (~(4 - (0 * c)))) -> (~4)\n return (mul i32 (\n add i32 (constval i32 0x1, constval i32 0x0),\n bnot i32 (sub i32 (\n constval i32 0x4,\n mul i32 (constval i32 0x0, dread i32 %c)))))\n}\n\nfunc &testConstFold16 (var %a i32, var %b i32, var %c i32) i32 {\n # ((~(4 - (c * 0))) * (1 + 0)) -> (~4)\n return (mul i32 (\n bnot i32 (sub i32 (\n constval i32 0x4,\n mul i32 (dread i32 %c, constval i32 0x0))),\n add i32 (constval i32 0x1, constval i32 0x0)))\n}\n\n\nfunc &testConstFoldDiv0 (var %a i32, var %b i32, var %c i32) i32 {\n # (5 \/ 0) * (1 + 1) -> 2\n return (mul i32 (\n div i32 (constval i32 0x5, constval i32 0x0),\n add i32 (constval i32 0x1, constval i32 0x1)))\n}\n\nfunc &testConstFoldFloor00 (var %a i32, var %b i32, var %c i32) i32 {\n # (floor(4.25) + c) * (1 + 1) -> (c + 4) * 2\n return (mul i32 (\n add i32 (floor i32 f32 (constval f32 4.25f), dread i32 %c),\n add i32 (constval i32 0x1, constval i32 0x1)))\n}\n\nfunc &testConstFoldFloor01 (var %a i32, var %b i32, var %c i32) i32 {\n # (floor(4.25) + 2) * (1 + 1) -> 12\n return (mul i32 (\n add i32 (floor i32 f32 (constval f32 4.25f), constval i32 0x2),\n add i32 (constval i32 0x1, constval i32 0x1)))\n}\n\nfunc &testConstFoldFloor02 (var %a i32, var %b i32, var %c i32) i32 {\n # floor((floor(4.25) + 1) + (1 + a)) -> floor(a + 6)\n return (floor i32 i32 (add i32 (\n add i32 (floor i32 f32 (constval f32 4.25f), constval i32 0x1),\n add i32 (constval i32 0x1, dread i32 %a))))\n}\n\nfunc &testConstFoldExtractbitsNode00 () i32 {\n # 487 = 00111100111\n # extractbits i32 6 5 (487) = 7 = 0111\n return (extractbits i32 6 5 (constval i32 487))\n}\n\nfunc &testConstFoldExtractbitsNode01 () i32 {\n # 487 = 00111100111\n # extractbits i32 4 5 (487) = -2 = 0xfffffffffffffffe\n return (extractbits i32 4 5 (constval i32 487))\n}\n\nfunc &testConstFoldExtractbitsNode02 (var %a i32, var %b i32, var %c i32) i32 {\n # 487 = 00111100111\n # extractbits i32 4 5 (487) = -2 = 0xfffffffffffffffe\n # extractbits((extractbits(487) + 1) + (1 + a)) -> extractbits(a)\n return (extractbits i32 4 5 (add i32 (\n add i32 (extractbits i32 4 5 (constval i32 487), constval i32 0x1),\n add i32 (constval i32 0x1, dread i32 %a))))\n}\n\nfunc &testConstFoldExtractbitsNode03 (var %a i32, var %b i32, var %c i32) i32 {\n # 487 = 00111100111\n # extractbits i32 6 5 (487) = 7 = 0111\n # extractbits((extractbits(487) + 1) + (1 + a)) -> extractbits(a + 9)\n return (extractbits i32 6 5 (add i32 (\n add i32 (extractbits i32 6 5 (constval i32 487), constval i32 0x1),\n add i32 (constval i32 0x1, dread i32 %a))))\n}\n\nfunc &testConstFoldCompareNode00 (var %a i32, var %b i32, var %c i32) i32 {\n # (ge(6, 2) + 1) + (1 + 2) -> 5\n return (add i32 (\n add i32 (\n ge i32 i32 (constval i32 6, constval i32 2),\n constval i32 1),\n add i32 (constval i32 1, constval i32 2)))\n}\n\nfunc &testConstFoldCompareNode01 (var %a i32, var %b i32, var %c i32) i32 {\n # ge((ge(6, 2) + 1), (1 + a)) -> ge(2, a + 1)\n return (ge i32 i32 (\n add i32 (\n ge i32 i32 (constval i32 6, constval i32 2),\n constval i32 1),\n add i32 (constval i32 1, dread i32 %a)))\n}\n\nfunc &testConstFoldTernaryNode00 (var %a i32, var %b i32, var %c i32) i32 {\n # (6 > 2 ? 5 : 0) + (1 + 2) -> 8\n return ( add i32 (\n select i32 (\n ge i32 i32 (constval i32 6, constval i32 2),\n constval i32 5,\n constval i32 0),\n add i32 (constval i32 1, constval i32 2)))\n}\n\nfunc &testConstFoldTernaryNode01 (var %a i32, var %b i32, var %c i32) i32 {\n # (6 > 10 ? 5 : 0) + (1 + a) -> (a + 1)\n return ( add i32 (\n select i32 (\n ge i32 i32 (constval i32 6, constval i32 10),\n constval i32 5,\n constval i32 0),\n add i32 (constval i32 1, dread i32 %a)))\n}\n\nfunc &testConstFoldTernaryNode02 (var %a i32, var %b i32, var %c i32) i32 {\n # 6 > a ? (1 + 6) + (1 + a) : 0 -> 6 > a ? a + 8 : 0\n return ( select i32 (\n ge i32 i32 (constval i32 6, dread i32 %a),\n add i32 (\n add i32 (constval i32 1, constval i32 6),\n add i32 (constval i32 1, dread i32 %a)),\n constval i32 0))\n}\n\ntype $Hello \n\ntype $Person ,\n @sex u1}>\n\n\nfunc &testConstFoldIassignNode00 (var %a i32) void {\n # this is equivalent to dassign %a 0 (constval i32 0x6)\n iassign <* i32> 0 (addrof ptr %a 0, add i32 (constval i32 1, constval i32 5))\n}\n\nfunc &testConstFoldIassignNode01 (var %a i32) void {\n var %bob $Person\n\n # this is equivalent to dassign %bob 5 (constval i32 0x6)\n iassign <* $Hello> 3 (addrof ptr %bob 2, add i32 (constval i32 1, constval i32 5))\n}\n\n\nfunc &testConstFoldIassignNode02 (var %a i32) void {\n # this is equivalent to dassign %a 0 (constval i32 0x6)\n iassign <* i32> 0 (\n iaddrof ptr <* i32> 0 (addrof ptr %a 0),\n add i32 (constval i32 1, constval i32 5))\n}\n\nfunc &testConstFoldIassignNode03 (var %a i32) void {\n\n var %bob $Person\n # this is equivalent to dassign %bob 5 (constval i32 0x6)\n iassign <* <$Hello>> 3 (\n iaddrof ptr <* <$Person>> 2 (addrof ptr %bob 0),\n add i32 (constval i32 1, constval i32 5))\n}\n\nfunc &testConstFoldIassignNode04 (var %a i32) void {\n\n var %bob $Person\n # this is equivalent to dassign %bob 5 (constval i32 0x6)\n iassign <* <$Hello>> 3 (\n iaddrof ptr <* <$Hello>> 0 (addrof ptr %bob 2),\n add i32 (constval i32 1, constval i32 5))\n}\n\n\nfunc &testConstFoldIassignNode05 (var %a i32) void {\n var %b <* i32>\n\n dassign %b (addrof ptr %a 0)\n\n # this is equivalent to iassign <* i32> 0 (dread ptr %a, constval i32 0x6)\n iassign <* i32> 0 (\n iaddrof ptr <* i32> 0 (dread ptr %a),\n add i32 (constval i32 1, constval i32 5))\n}\n\nfunc &testConstFoldIassignNode06 (var %a i32) void {\n var %bob $Person\n # this is equivalent to dassign %a 0 (dread i32 %bob 1)\n dassign %a 0 (iread agg <* <$Person>> 1 (addrof ptr %bob 0))\n}\n\nfunc &testConstFoldSwitchNode00 () void {\n # switch (1+4) ... -> goto @lab1\n switch ( add i32 (constval i32 1, constval i32 4)) @labdft {\n -2: goto @lab0\n 5: goto @lab1\n 8: goto @lab9 }\n\n @lab0\n return (constval i32 1)\n @labdft\n return (constval i32 2)\n @lab9\n return (constval i32 3)\n @lab1\n return (constval i32 4)\n}\n\nfunc &testConstFoldSwitchNode01 () void {\n # switch (1 + 10) ... -> goto @labdft\n switch ( add i32 (constval i32 1, constval i32 10)) @labdft {\n -2: goto @lab0\n 5: goto @lab1\n 8: goto @lab9 }\n\n @lab0\n return (constval i32 1)\n @labdft\n return (constval i32 2)\n @lab9\n return (constval i32 3)\n @lab1\n return (constval i32 4)\n}\n\nfunc &testConstFoldSwitchNode02 (var %a i32) void {\n # switch (5 + (5 - a)) ... -> switch (10 - a) ...\n switch (add i32 (\n constval i32 5,\n sub i32 (constval i32 5, dread i32 %a))) @labdft {\n -2: goto @lab0\n 5: goto @lab1\n 8: goto @lab9 }\n\n @lab0\n return (constval i32 1)\n @labdft\n return (constval i32 2)\n @lab9\n return (constval i32 3)\n @lab1\n return (constval i32 4)\n}\n\n\nfunc &testConstFoldArrayNode00 (var %x i32) void {\n var %a <* [15][15] i32>\n # fold indexes -> array ptr <* <[15][15] i32>> (constval i32 0x6, constval i32 0x4)\n dassign %x (\n iread i32 <* i32> (\n array 1 ptr <* [15][15] i32> (addrof ptr %a,\n add i32 (constval i32 1, constval i32 5),\n sub i32 (constval i32 5, constval i32 1))))\n}\n\nfunc &testDepositbitsNodeNode00 (var %a i32, var %c i32) i32 {\n return ( depositbits i32 1 23 (\n add i32 (\n add i32 (dread i32 %a, constval i32 0x5),\n add i32 (\n add i32 (constval i32 0x2, dread i32 %c),\n add i32 (constval i32 0x4, constval i32 0x2))),\n add i32 (constval i32 0x4, constval i32 0x8)))\n}\n\nfunc &testDepositbitsNodeNode01 () i32 {\n return ( depositbits i32 1 23 (\n add i32 (\n add i32 (constval i32 0x5, constval i32 0x5),\n add i32 (\n add i32 (constval i32 0x2, constval i32 0x2),\n add i32 (constval i32 0x4, constval i32 0x2))),\n add i32 (constval i32 0x4, constval i32 0x8)))\n}\n # EXEC: %irbuild Main.mpl\n # EXEC: %irbuild Main.irb.mpl\n # EXEC: %cmp Main.irb.mpl Main.irb.irb.mpl\n","avg_line_length":28.3859348199,"max_line_length":85,"alphanum_fraction":0.5652305275} +{"size":11298,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n <\/accessoryModels>\n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n ceab5195-25ea-4f22-9b92-103b95ca8c0c(jetbrains.mps.lang.core)<\/dependency>\n 16bafbb4-c6cd-4cc5-8332-7c6de8729b3f(jetbrains.mps.samples.Shapes)<\/dependency>\n c72da2b9-7cce-4447-8389-f407dc1158b7(jetbrains.mps.lang.structure)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n c72da2b9-7cce-4447-8389-f407dc1158b7(jetbrains.mps.lang.structure)<\/dependency>\n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 4caf0310-491e-41f5-8a9b-2006b3a94898(jetbrains.mps.execution.util)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":80.7,"max_line_length":133,"alphanum_fraction":0.7361479908} +{"size":3950,"ext":"mpl","lang":"Maple","max_stars_count":1.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n daafa647-f1f7-4b0b-b096-69cd7c8408c0(jetbrains.mps.baseLanguage.regexp)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":70.5357142857,"max_line_length":121,"alphanum_fraction":0.742278481} +{"size":1161,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: mgga_exc *)\n(* prefix:\n mgga_c_bc95_params *params;\n\n assert(p->params != NULL);\n params = (mgga_c_bc95_params * )(p->params);\n*)\n\n$define lda_c_pw_params\n$define lda_c_pw_modified_params\n$include \"lda_c_pw.mpl\"\n\n(* The B97 function g *)\nbc95_gpar := (xs, ts) -> ts*Fermi_D(xs, ts)\/(K_FACTOR_C*(1 + params_a_css*xs^2)^2):\nbc95_gperp := (xs0, xs1) -> 1\/(1 + params_a_copp*(xs0^2 + xs1^2)):\n\n(* The parallel and perpendicular components of the energy *)\nbc95_fpar := (rs, z, xs0, xs1, ts0, ts1) ->\n + lda_stoll_par(f_pw, rs, z, 1) * bc95_gpar(xs0, ts0)\n + lda_stoll_par(f_pw, rs, -z, -1) * bc95_gpar(xs1, ts1):\n\nbc95_fperp := (rs, z, xs0, xs1) ->\n lda_stoll_perp(f_pw, rs, z) * bc95_gperp(xs0, xs1):\n\nf_bc95 := (rs, z, xs0, xs1, ts0, ts1) ->\n + bc95_fpar (rs, z, xs0, xs1, ts0, ts1)\n + bc95_fperp(rs, z, xs0, xs1):\n\nf := (rs, z, xt, xs0, xs1, us0, us1, ts0, ts1) ->\n f_bc95(rs, z, xs0, xs1, ts0, ts1):\n\n","avg_line_length":29.025,"max_line_length":84,"alphanum_fraction":0.6408268734} +{"size":6726,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":77.3103448276,"max_line_length":129,"alphanum_fraction":0.7308950342} +{"size":3040,"ext":"mpl","lang":"Maple","max_stars_count":147.0,"content":"with(LinearAlgebra):\nwith(VectorCalculus):\nwith(plottools);\n\nNALU := proc(w1,w2,ghat1,ghat2,x,t,epsilon)\n\tlocal g1, g2, z1, z2, L, i;\n\tg1 := 1\/~(1 +~ exp~(-ghat1));\n\tz1 := g1 *~ (w1.x) +~ (1 -~ g1) *~ exp~(w1.log~(abs(x) +~ epsilon));\n\n\tg2 := 1\/~(1 +~ exp~(-ghat2));\n\tz2 := g2 *~ (w2.z1) +~ (1 -~ g2) *~ exp~(w2.log~(abs(z1) +~ epsilon));\n\n\tL := (z2 -~ t)^~2;\n\treturn add(L[i],i=1..numelems(L));\nend proc:\n\nNALUsafe := proc(w1,w2,ghat1,ghat2,x,t)\n\tlocal g1, g2, z1, z2, L, i;\n\tg1 := 1\/~(1 +~ exp~(-ghat1));\n\tz1 := g1 *~ (w1.x) +~ (1 -~ g1) *~ exp~(w1.log~(abs(x -~ 1) +~ 1));\n\n\tg2 := 1\/~(1 +~ exp~(-ghat2));\n\tz2 := g2 *~ (w2.z1) +~ (1 -~ g2) *~ exp~(w2.log~(abs(z1 -~ 1) +~ 1));\n\n\tL := (z2 -~ t)^~2;\n\treturn add(L[i],i=1..numelems(L));\nend proc:\n\n\nNALU(<, >, <>, , , , t, epsilon);\n\nP := plot3d(\n\tNALU(<, >, <>, , , <2, 2>, 8, 10^(-8)),\n\tw = -1.5..1.5, g = -3..3,\n\tview = [-1.5..1.5, -3..3, 0..300],\n\taxes=boxed):\nP;\n\nP := plot3d(\n\tNALU(<, >, <>, , , <2, 2>, 16, 10^(-8)),\n\tw = -1.5..1.5, g = -3..3,\n\tview = [-1.5..1.5, -3..3, 0..300],\n\taxes=boxed):\nP;\n\nNALUsafe(<, >, <>, , , , t, epsilon);\n\nP := plot3d(\n\tNALUsafe(<, >, <>, , , <2, 2>, 8),\n\tw = -1.5..1.5, g = -3..3,\n\tview = [-1.5..1.5, -3..3, 0..300],\n\taxes=boxed):\nP;\n\nP := plot3d(\n\tNALUsafe(<, >, <>, , , <2, 2>, 16),\n\tw = -1.5..1.5, g = -3..3,\n\tview = [-1.5..1.5, -3..3, 0..300],\n\taxes=boxed):\nP;\n\nsolveNALUsafe := proc(x, t)\n\tlocal i, v, w, g, eq, sol1, sol2, sols;\n\n\teq := NALUsafe(<, >, <>, , , x, t);\n\tsols := [];\n for v from -3 to 3 by 0.1 do\n sol1 := fsolve(eval(eq, g=v) = 0, w);\n sol2 := fsolve(eval(eq, g=v) = 0, w, avoid={{w = sol1}});\n sols := [op(sols), [sol1, v], [sol2, v]];\n end do;\n\n\treturn sols;\nend proc:\n\nsolveNALU := proc(x, t, epsilon)\n\tlocal i, v, w, g, eq, sols, sol1, sol2, sol3, sol4;\n\n\teq := NALU(<, >, <>, , , x, t, epsilon);\n\tsols := [];\n for v from -3 to 3 by 0.1 do\n sol1 := fsolve(eval(eq, g=v) = 0, w);\n sol2 := fsolve(eval(eq, g=v) = 0, w, avoid={{w = sol1}});\n if v < 0.9 and v >= 0 then\n sol3 := fsolve(eval(eq, g=v) = 0, w, avoid={{w = sol1}, {w = sol2}});\n sols := [op(sols), [sol1, v], [sol2, v], [sol3, v]];\n elif v < 0 then\n sol3 := fsolve(eval(eq, g=v) = 0, w, avoid={{w = sol1}, {w = sol2}});\n sol4 := fsolve(eval(eq, g=v) = 0, w, avoid={{w = sol1}, {w = sol2}, {w = sol3}});\n sols := [op(sols), [sol1, v], [sol2, v], [sol3, v], [sol4, v]];\n else\n sols := [op(sols), [sol1, v], [sol2, v]];\n end if;\n end do;\n\n\treturn sols;\nend proc:\n\nNALUsols := solveNALU(<2, 2>, 8, 10^(-8));\nP := plot(NALUsols, style = 'point', view = [-1.5..1.5, -3..3]):\nP;\n\nNALUsafesols := solveNALUsafe(<2, 2>, 8);\nP := plot(NALUsafesols, style = 'point', view = [-1.5..1.5, -3..3]):\nP;\n","avg_line_length":28.679245283,"max_line_length":90,"alphanum_fraction":0.4414473684} +{"size":6112,"ext":"mpl","lang":"Maple","max_stars_count":6.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n c901f7a1-ed4f-4b52-8d35-10d1a33974f0(org.campagnelab.metar.code)<\/dependency>\n fd3fc8d7-bebb-4053-88a0-6dcc12448e6e(org.campagnelab.instantrefresh.plugin)<\/dependency>\n 498d89d2-c2e9-11e2-ad49-6cf049e62fe5(MPS.IDEA)<\/dependency>\n 742f6602-5a2f-4313-aa6e-ae1cd4ffdc61(MPS.Platform)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 2d3c70e9-aab2-4870-8d8d-6036800e4103(jetbrains.mps.kernel)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":83.7260273973,"max_line_length":132,"alphanum_fraction":0.7529450262} +{"size":753,"ext":"mpl","lang":"Maple","max_stars_count":1.0,"content":"\/\/impulse: \/give @p spawn_egg 1 0 {display:{Name:\"Propulsion Gel Spawner\"},EntityTag:{id:\"minecraft:chicken\",CustomName:\"MMH_PropulsionGelSpawner\",Silent:1,NoGravity:1}}\n\/\/MMH_loadChunks()\n\/\/\/clone ~1 ~1 ~1 ~3 ~5 ~3 20 1 24\n\n#MMH\nrepeat process MMH_propulsionGelSpawner {\nif: \/testfor @e[type=Chicken,name=MMH_PropulsionGelSpawner]\nthen {\n MMH_loadChunks()\n \/execute @e[type=Chicken,name=MMH_PropulsionGelSpawner] ~ ~ ~ clone 20 1 24 22 5 26 ~-1 ~ ~-1 masked\n \/execute @e[type=Chicken,name=MMH_PropulsionGelSpawner] ~ ~ ~ fill ~ ~ ~ ~ ~ ~ air 0 replace pumpkin\n \/tp @e[type=Chicken,name=MMH_PropulsionGelSpawner] ~ -100 ~\n}\n}\n\n\/\/\/summon item ~-1 ~-1 ~-1 {CustomName:\"ACV_PropulsionGel\",PickupDelay:32767,Item:{Count:1,Damage:1,id:\"minecraft:wool\"}}\n","avg_line_length":44.2941176471,"max_line_length":169,"alphanum_fraction":0.7184594954} +{"size":1605,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"mobius_complex := proc()\n local T,V,E,F,R,r,v,a,mob,mob_arc,i,e;\n \n V := [seq(seq([i,a],a=0..2),i=0..1)];\n F := [\n seq([[0,a],[0,modp(a+1,3)],[1,a]],a=0..2),\n seq([[0,a],[0,modp(a+1,3)],[1,modp(a+1,3)]],a=0..2),\n seq([[0,a],[1,modp(a+1,3)],[1,modp(a+2,3)]],a=0..2) \n ];\n\n E := map(f -> ([f[1],f[2]],[f[1],f[3]],[f[2],f[3]]),F);\n\n T := table([]);\n\n T[\"vertices\"] := V;\n T[\"edges\"] := E;\n T[\"faces\"] := F;\n T[\"max_simplices\"] := T[\"faces\"];\n \n T[\"all_simplices\"] := [map(v -> [v],V),op(E),op(F)];\n\n v := table():\n for a from 0 to 2 do \n v[0,a] := [a\/6,0];\n v[1,a] := [a\/3,1];\n od:\n\n R := 1;\n r := 1\/3:\n mob := mobius_embedding(R,r);\n \n mob_arc := mobius_arc(R,r);\n\n T[\"plot\"] :=\n display(\n spacecurve(mob(t,1),t=0..1,colour=blue),\n plot3d(mob(t,u),t=0..1,u=0..1,style=wireframe,colour=\"LightGray\"),\n seq(mob_arc(op(v[op(e[1])]),op(v[op(e[2])]),colour=red),e in E),\n axes=none,scaling=constrained\n );\n\n return eval(T);\nend():\n\nflat_mobius_complex := proc(n::posint)\n local f,g,T,V,E,F,r,v,a,i;\n\n f := (i) -> modp(i+1,4*n+2);\n g := (i) -> modp(i+2*n+3\/2+(-1)^i\/2,4*n+2);\n \n V := [seq(i,i=0..4*n+1)];\n E := [seq([i,f(i)],i=0..4*n+1),seq([i,g(i)],i=0..4*n+1)];\n F := [seq([i,f(i),g(i)],i=0..4*n+1)];\n\n T := table([]);\n\n T[\"vertices\"] := V;\n T[\"edges\"] := E;\n T[\"faces\"] := F;\n T[\"max_simplices\"] := T[\"faces\"];\n T[\"all_simplices\"] := [map(v -> [v],V),op(E),op(F)];\n\n T[\"embedding_dim\"] := 3;\n T[\"embedding\"] := table([seq(i = evalf(mobius_embedding(0.2)(i\/(4*n+2),1)),i=0..4*n+1)]);\n\n T[\"plot\"] := `plot\/raw_simplicial_complex`(T[\"vertices\"])(T[\"faces\"],3,T[\"embedding\"]);\n\n return eval(T);\n\nend:","avg_line_length":22.9285714286,"max_line_length":90,"alphanum_fraction":0.4953271028} +{"size":17471,"ext":"mpl","lang":"Maple","max_stars_count":32.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 71934284-d7d1-45ee-a054-8c072591085f(org.iets3.core.expr.toplevel)<\/dependency>\n dbe08fb5-334d-4b64-86a0-622406fa0e87(org.iets3.core.expr.base.runtime)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/extendedLanguage>\n 5186c6ce-428c-4f09-a9df-73d9e86c27d3(org.iets3.core.expr.typetags)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":89.137755102,"max_line_length":137,"alphanum_fraction":0.7334439929} +{"size":195,"ext":"mpl","lang":"Maple","max_stars_count":14.0,"content":"[plugin]\npluginname = RebootMadDevice\ndescription = Reboot MAD Devices if they are not responding\nauthor = GhostTalker\nurl = https:\/\/github.com\/GhostTalker\/RebootMadDevice\/tree\/V2\nversion = 2.4.0","avg_line_length":32.5,"max_line_length":60,"alphanum_fraction":0.8} +{"size":3980,"ext":"mpl","lang":"Maple","max_stars_count":12.0,"content":"\/\/ Deletes all portals whose color is specified by an entity named ACV_deletePortals_PARAM and then kill the params\n\/\/ Params: entities with name ACV_deletePortals_PARAM and a score of ACV_COLOR\nprocess ACV_deletePortals {\n triggerAntiBridges()\n closeConnections()\n killPortals()\n lightUpHorizontalPortals()\n\n \/\/ Kill the Params\n \/kill @e[name=ACV_deletePortals_PARAM]\n}\n\n\/\/ Triggers the AntiBridges at every specified Portal\n\/\/ Params: entities with tag ACV_deletePortals_PARAM and a score of ACV_COLOR\nprocess triggerAntiBridges {\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=0,score_ACV_COLOR=1] ~ ~ ~ execute @e[type=area_effect_cloud,name=ACV_PortalOut,score_ACV_COLOR_min=0,score_ACV_COLOR=1] ~ ~ ~ entitydata @e[type=area_effect_cloud,name=ACV_AntiBridge_Idle,dy=0] {CustomName:\"ACV_AntiBridge\"}\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=2,score_ACV_COLOR=3] ~ ~ ~ execute @e[type=area_effect_cloud,name=ACV_PortalOut,score_ACV_COLOR_min=2,score_ACV_COLOR=3] ~ ~ ~ entitydata @e[type=area_effect_cloud,name=ACV_AntiBridge_Idle,dy=0] {CustomName:\"ACV_AntiBridge\"}\n start ACV_antiBridges\n}\n\n\/\/ Close the connection between the two portals\n\/\/ Params: entities with tag ACV_deletePortals_PARAM and a score of ACV_COLOR\nprocess closeConnections {\n ACV_loadChunks()\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=0,score_ACV_COLOR=1] ~ ~ ~ execute @e[type=area_effect_cloud,name=ACV_PortalIn,score_ACV_COLOR_min=0,score_ACV_COLOR=0] ~ ~ ~ clone 0 1 0 0 2 0 ~ ~ ~\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=0,score_ACV_COLOR=1] ~ ~ ~ execute @e[type=area_effect_cloud,name=ACV_PortalIn,score_ACV_COLOR_min=1,score_ACV_COLOR=1] ~ ~ ~ clone 1 1 0 1 2 0 ~ ~ ~\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=2,score_ACV_COLOR=3] ~ ~ ~ execute @e[type=area_effect_cloud,name=ACV_PortalIn,score_ACV_COLOR_min=2,score_ACV_COLOR=2] ~ ~ ~ clone 2 1 0 2 2 0 ~ ~ ~\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=2,score_ACV_COLOR=3] ~ ~ ~ execute @e[type=area_effect_cloud,name=ACV_PortalIn,score_ACV_COLOR_min=3,score_ACV_COLOR=3] ~ ~ ~ clone 3 1 0 3 2 0 ~ ~ ~\n}\n\n\/\/ Delete the specified portals\n\/\/ Params: entities with tag ACV_deletePortals_PARAM and a score of ACV_COLOR\nprocess killPortals {\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=0,score_ACV_COLOR=0] ~ ~ ~ kill @e[tag=ACV_Portal,score_ACV_COLOR_min=0,score_ACV_COLOR=0]\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=1,score_ACV_COLOR=1] ~ ~ ~ kill @e[tag=ACV_Portal,score_ACV_COLOR_min=1,score_ACV_COLOR=1]\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=2,score_ACV_COLOR=2] ~ ~ ~ kill @e[tag=ACV_Portal,score_ACV_COLOR_min=2,score_ACV_COLOR=2]\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=3,score_ACV_COLOR=3] ~ ~ ~ kill @e[tag=ACV_Portal,score_ACV_COLOR_min=3,score_ACV_COLOR=3]\n}\n\n\/\/ Place barrier blocks at floor and ceiling portals, because otherwise the display turns dark\n\/\/ Params: entities with tag ACV_deletePortals_PARAM and a score of ACV_COLOR\nprocess lightUpHorizontalPortals { \n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=0,score_ACV_COLOR=0] ~ ~ ~ execute @e[type=armor_stand,name=ACV_PortalDisplay,score_ACV_COLOR_min=1,score_ACV_COLOR=1] ~ ~ ~ setblock ~ ~2 ~ barrier\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=1,score_ACV_COLOR=1] ~ ~ ~ execute @e[type=armor_stand,name=ACV_PortalDisplay,score_ACV_COLOR_min=0,score_ACV_COLOR=0] ~ ~ ~ setblock ~ ~2 ~ barrier\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=2,score_ACV_COLOR=2] ~ ~ ~ execute @e[type=armor_stand,name=ACV_PortalDisplay,score_ACV_COLOR_min=3,score_ACV_COLOR=3] ~ ~ ~ setblock ~ ~2 ~ barrier\n \/execute @e[name=ACV_deletePortals_PARAM,score_ACV_COLOR_min=3,score_ACV_COLOR=3] ~ ~ ~ execute @e[type=armor_stand,name=ACV_PortalDisplay,score_ACV_COLOR_min=2,score_ACV_COLOR=2] ~ ~ ~ setblock ~ ~2 ~ barrier\n}\n","avg_line_length":82.9166666667,"max_line_length":287,"alphanum_fraction":0.7939698492} +{"size":2231,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: mgga_exc *)\n(* prefix:\n mgga_x_scan_params *params;\n\n assert(p->params != NULL);\n params = (mgga_x_scan_params * )(p->params);\n*)\n\nscan_p := x -> X2S^2*x^2:\nscan_alpha := (x, t) -> (t - x^2\/8)\/K_FACTOR_C:\n\n(* The interpolating functions are nasty for a -> 1, so we need to\n truncate them. The natural choice is to cut off the functions to\n zero when the exponential term reaches machine epsilon.\n\n The left cutoff is |log epsilon|\/(|log epsilon| + c1) < 1\n and the right one is (|log epsilon| + c2)\/|log epsilon| > 1,\n so we don't even really need the step function.\n*)\nscan_f_alpha_left0 := a -> exp(-params_a_c1*a\/(1 - a)):\nscan_f_alpha_left_cutoff := -log(DBL_EPSILON)\/(-log(DBL_EPSILON) + params_a_c1):\nscan_f_alpha_left := a -> my_piecewise3(a > scan_f_alpha_left_cutoff, 0, scan_f_alpha_left0(m_min(scan_f_alpha_left_cutoff, a))):\n\nscan_f_alpha_right0 := a -> -params_a_d*exp(params_a_c2\/(1 - a)):\nscan_f_alpha_right_cutoff := (-log(DBL_EPSILON\/abs(params_a_d)) + params_a_c2)\/(-log(DBL_EPSILON\/abs(params_a_d))):\nscan_f_alpha_right := a -> my_piecewise3(a < scan_f_alpha_right_cutoff, 0, scan_f_alpha_right0(m_max(scan_f_alpha_right_cutoff, a))):\nscan_f_alpha := a -> my_piecewise3(\n a <= 1, scan_f_alpha_left(a), scan_f_alpha_right(a)\n ):\n\nscan_h1x := x -> 1 + params_a_k1*(1 - params_a_k1\/(params_a_k1 + x)):\n\nscan_b2 := sqrt(5913\/405000):\nscan_b1 := (511\/13500)\/(2*scan_b2):\nscan_b3 := 1\/2:\nscan_b4 := MU_GE^2\/params_a_k1 - 1606\/18225 - scan_b1^2:\nscan_y := (x, a) -> MU_GE*scan_p(x) + scan_b4*scan_p(x)^2*exp(-scan_b4*scan_p(x)\/MU_GE)\n + (scan_b1*scan_p(x) + scan_b2*(1 - a)*exp(-scan_b3*(1 - a)^2))^2:\n\nscan_a1 := 4.9479:\nscan_gx := x -> 1 - exp(-scan_a1\/sqrt(X2S*x)):\n\nscan_h0x := 1.174:\nscan_f := (x, u, t) -> (scan_h1x(scan_y(x, scan_alpha(x, t)))*(1 - scan_f_alpha(scan_alpha(x, t)))\n + scan_h0x*scan_f_alpha(scan_alpha(x, t)))*scan_gx(x):\n\nf := (rs, z, xt, xs0, xs1, u0, u1, t0, t1) -> mgga_exchange(scan_f, rs, z, xs0, xs1, u0, u1, t0, t1):\n","avg_line_length":39.8392857143,"max_line_length":133,"alphanum_fraction":0.6786194532} +{"size":16836,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"#######################################################################\n# This file is part of the crlibm library, and is distributed under\n# the LGPL.\n# To use:\n# restart; read \"exp-td.mpl\";\nDigits := 145:\n\ninterface(quiet=true):\n\nread \"common-procedures.mpl\":\nread \"triple-double.mpl\":\nread \"gal.mpl\":\nmkdir(\"TEMPASIN\"):\n\nwith(orthopoly,T):\n\n\ntruncPoly := proc(p,k) \nlocal i, q:\nq := 0:\nconvert(q,polynom):\nfor i from 0 to min(degree(p,x),k) do\n q := q + coeff(p,x,i) * x^i:\nod:\nreturn (q):\nend:\n\nintervals := 10:\n\nfor i from 1 to intervals do\n\tepsAccurate[i] := 0.5:\n\tepsQuick[i] := 0.5:\n\tpolyAccurate[i] := 1:\n\tpolyQuick[i] := 1:\nod:\nepsAccurateSpecial := 0.5:\nepsQuickExtra := 0.5:\n\nlowestIntervalMax := 0.185:\nhighestIntervalMin := 0.78:\n\npolyAccurateTDCoeffsLowest := 13:\npolyAccurateDDCoeffsLowest := 12:\npolyAccurateDCoeffsLowest := 16:\n\npolyAccurateDegreeLowest := polyAccurateTDCoeffsLowest + polyAccurateDDCoeffsLowest + polyAccurateDCoeffsLowest:\n\npolyQuickDDCoeffsLowest := 12:\npolyQuickDCoeffsLowest := 10:\n\npolyQuickDegreeLowest := polyQuickDDCoeffsLowest + polyQuickDCoeffsLowest:\n\npolyAccurateTDCoeffsMiddle := 7:\npolyAccurateDDCoeffsMiddle := 9:\npolyAccurateDCoeffsMiddle := 19:\n\npolyAccurateDegreeMiddle := polyAccurateTDCoeffsMiddle + polyAccurateDDCoeffsMiddle + polyAccurateDCoeffsMiddle:\n\npolyQuickDDCoeffsMiddle := 7:\npolyQuickDCoeffsMiddle := 7:\n\npolyQuickDegreeMiddle := polyQuickDDCoeffsMiddle + polyQuickDCoeffsMiddle:\n\n\npolyAccurateTDCoeffsHighest := 9:\npolyAccurateDDCoeffsHighest := 9:\npolyAccurateDCoeffsHighest := 11:\n\npolyAccurateDegreeHighest := polyAccurateTDCoeffsHighest + polyAccurateDDCoeffsHighest + polyAccurateDCoeffsHighest:\n\npolyQuickDDCoeffsHighest := 9:\npolyQuickDCoeffsHighest := 9:\n\npolyQuickDegreeHighest := polyQuickDDCoeffsHighest + polyQuickDCoeffsHighest:\n\nextrabound := hexa2ieee([\"3F500000\",\"00000000\"]):\npolyQuickDegreeExtra := 5:\n\nbound[0] := 0:\nb := nearest(lowestIntervalMax):\nhe := ieeehexa(b):\nbound[1] := hexa2ieee([he[1],\"00000000\"]):\nb := nearest(highestIntervalMin):\nhe := ieeehexa(b):\nbound[intervals - 1] := hexa2ieee([he[1],\"00000000\"]):\nbound[intervals] := 1:\nlinearWidth := (highestIntervalMin - lowestIntervalMax) \/ (intervals - 2):\nscaleSum := 0:\nscale[2] := 1.5:\nscale[3] := 1.35:\nscale[4] := 1.18:\nscale[5] := 1.00:\nscale[6] := 0.915:\nscale[7] := 0.74:\nscale[8] := 0.595:\nscale[9] := 0.50:\nfor i from 2 to (intervals-1) do\n\tscaleSum := scaleSum + scale[i]:\nod:\nfor i from 2 to (intervals-1) do\n\tscale[i] := scale[i] \/ scaleSum;\nod:\ncurrent := lowestIntervalMax:\nfor i from 2 to (intervals-2) do\n\tb := nearest(current + (highestIntervalMin - lowestIntervalMax) * scale[i]):\n\tcurrent := b:\n\the := ieeehexa(b):\n\tbound[i] := hexa2ieee([he[1],\"00000000\"]):\nod:\nprintf(\"Using %d intervals with bounds:\\n\",intervals):\nfor i from 0 to intervals do\n\tprintf(\"bound[%d] = %1.30e\\n\",i,bound[i]):\nod:\nprintf(\"Using an extra bound for truncating the quick poly to deg. %d in interval #0 for small args up to %f (2^(%f))\\n\",\n\tpolyQuickDegreeExtra,extrabound,log[2](abs(extrabound)));\n\nprintf(\"Computing Gal's accurate table values for interval midpoints\\n\"):\nfor i from 2 to (intervals-1) do\n\tm := nearest((bound[i] + bound[i-1]) \/ 2):\n\tmhe := ieeehexa(m):\n\tprintf(\"Interval %d: accurate table research start value %f (%s%s)\\n\",i,m,mhe[1],mhe[2]):\n\tmidpointFloat[i] := galDoubleToDoubleDouble(nearest(m),arcsin,2^(-121),2^(15)):\nod:\n\n\nprintf(\"Using the following floating point midpoints for intervals 2-%d:\\n\",intervals-2):\nfor i from 2 to (intervals-1) do\n\tmhe := ieeehexa(midpointFloat[i]):\n\tprintf(\"midpointFloat[%d] = %f (%s%s)\\n\",i,midpointFloat[i],mhe[1],mhe[2]):\nod:\n\nprintf(\"The reduced argument z is therefore bounded by:\\n\"):\nprintf(\"Interval 1: |z| < 2^(%f)\\n\",\n\tlog[2](abs(bound[1]))):\nfor i from 2 to (intervals-1) do\n\tprintf(\"Interval %d: |z| < 2^(%f)\\n\",i,\n\tlog[2](max(abs(midpointFloat[i] - bound[i-1]),abs(midpointFloat[i] - bound[i])))):\nod:\nprintf(\"Interval %d: |z| < 2^(%f)\\n\",intervals,\n\tlog[2](abs(1 - bound[intervals-1]))):\n\n\n\nprintf(\"Using a %d degree polynomial for lowest interval (1) (accurate phase)\\n\",\n\tpolyAccurateDegreeLowest):\nprintf(\"with %d triple-double, %d double-double and %d double coefficients\\n\",\n\tpolyAccurateTDCoeffsLowest, polyAccurateDDCoeffsLowest, polyAccurateDCoeffsLowest):\nprintf(\"Using a %d degree polynomial for lowest interval (1) (quick phase)\\n\",\n\tpolyQuickDegreeLowest):\nprintf(\"with %d double-double and %d double coefficients\\n\",\n\tpolyQuickDDCoeffsLowest, polyQuickDCoeffsLowest):\nprintf(\"Using a %d degree polynomial for middle intervals (2-%d) (accurate phase)\\n\",\n\tpolyAccurateDegreeMiddle,intervals-2):\nprintf(\"with %d triple-double, %d double-double and %d double coefficients\\n\",\n\tpolyAccurateTDCoeffsMiddle, polyAccurateDDCoeffsMiddle, polyAccurateDCoeffsMiddle):\nprintf(\"Using a %d degree polynomial for middle intervals (2-%d) (quick phase)\\n\",\n\tpolyQuickDegreeMiddle,intervals-2):\nprintf(\"with %d double-double and %d double coefficients\\n\",\n\tpolyQuickDDCoeffsMiddle, polyQuickDCoeffsMiddle):\nprintf(\"Using a %d degree polynomial for highest interval (%d) (accurate phase)\\n\",\n\tpolyAccurateDegreeHighest,intervals):\nprintf(\"with %d triple-double, %d double-double and %d double coefficients\\n\",\n\tpolyAccurateTDCoeffsHighest, polyAccurateDDCoeffsHighest, polyAccurateDCoeffsHighest):\nprintf(\"Using a %d degree polynomial for highest interval (%d) (quick phase)\\n\",\n\tpolyQuickDegreeHighest,intervals):\nprintf(\"with %d double-double and %d double coefficients\\n\",\n\tpolyQuickDDCoeffsHighest, polyQuickDCoeffsHighest):\n\nif true then \n\nprintf(\"Computing polynomials for interval 1 ([%f;%f])\\n\",bound[0],bound[1]):\n\nf := unapply(convert(series((arcsin(sqrt(x))\/sqrt(x) - 1)\/x,x=0,300),polynom),x):\n\np := unapply(eval(numapprox[chebyshev](f(x),x=(bound[0])^2..(bound[1])^2,2^(-127))),x):\n\npolyAccuExact[1] := truncPoly(subs(X=x^2,p(X))*x^3+x,polyAccurateDegreeLowest):\n\npolyAccurate[1] := poly_exact32(polyAccuExact[1],polyAccurateTDCoeffsLowest,polyAccurateDDCoeffsLowest):\n\n\nepsAccurate[1] := numapprox[infnorm]((polyAccurate[1]\/arcsin(x))-1, x=bound[0]..bound[1]):\nepsAccurateSpecial := numapprox[infnorm]((polyAccurate[1]\/arcsin(x))-1, x=bound[0]..evalf(sin(2^(-18)))):\n\n\npolyQuickExact[1] := truncPoly(polyAccuExact[1],polyQuickDegreeLowest):\npolyQuick[1] := poly_exact2(polyQuickExact[1],polyQuickDDCoeffsLowest):\n\nepsQuick[1] := numapprox[infnorm]((polyQuick[1]\/arcsin(x))-1, x=bound[0]..bound[1]):\n\npolyQuickExtraExact := truncPoly(polyAccuExact[1],polyQuickDegreeExtra):\npolyQuickExtra := poly_exact2(polyQuickExtraExact,polyQuickDegreeExtra):\nepsQuickExtra := numapprox[infnorm]((polyQuickExtra\/arcsin(x))-1, x=bound[0]..extrabound):\n\nend if:\n\nfor i from 2 to (intervals-1) do\n\nprintf(\"Computing polynomials for interval %d ([%f;%f])\\n\",i,bound[i-1],bound[i]):\nprintf(\"Reduced argument z will be in interval [%1.8e;%1.8e] ([-2^%f,2^%f]),\\n\",\n\tbound[i-1]-midpointFloat[i],bound[i]-midpointFloat[i],\n\tlog[2](abs(bound[i-1]-midpointFloat[i])),log[2](abs(bound[i]-midpointFloat[i]))):\n\nf := unapply(arcsin(x+midpointFloat[i]),x):\n\nfhelp := unapply(convert(series((f(x)-arcsin(midpointFloat[i]))\/x,x=0,polyAccurateDegreeMiddle*3),polynom),x):\n\npolyAccuExact[i] := numapprox[minimax](fhelp(x),\n\t\t\t\tx=bound[i-1]-midpointFloat[i]..bound[i]-midpointFloat[i],\n\t\t\t\t[polyAccurateDegreeMiddle,0],1,'err')*x + nearestDD(evalf(arcsin(midpointFloat[i]))):\n\npolyAccurate[i] := poly_exact32(polyAccuExact[i],polyAccurateTDCoeffsMiddle,polyAccurateDDCoeffsMiddle):\n\nepsAccurate[i] := numapprox[infnorm]((polyAccurate[i]\/f(x))-1, \n\t\t\t\t\tx=bound[i-1]-midpointFloat[i]..bound[i]-midpointFloat[i]):\n\npolyQuickExact[i] := truncPoly(polyAccuExact[i],polyQuickDegreeMiddle):\npolyQuick[i] := poly_exact2(polyQuickExact[i],polyQuickDDCoeffsMiddle):\n\nepsQuick[i] := numapprox[infnorm]((polyQuick[i]\/f(x))-1, \n\t\t\t \t x=bound[i-1]-midpointFloat[i]..bound[i]-midpointFloat[i]):\n\n\nod:\n\n\nif true then \n\nprintf(\"Computing polynomials for interval %d ([%f;%f])\\n\",intervals,bound[intervals-1],bound[intervals]):\n\n\ng := unapply(((arcsin(1 - x) - Pi\/2)\/sqrt(2*x)),x):\nf := unapply(convert(series(((g(x)+1)\/x),x=0,polyAccurateDegreeHighest*4),polynom),x):\n\n\npolyAccuExact[intervals] := numapprox[minimax](f(x),x=(1-bound[intervals]+2^(-53))..(1-bound[intervals-1]),\n\t\t\t\t\t\t[polyAccurateDegreeHighest-1,0],1,'err')*x-1:\n\npolyAccurate[intervals] := poly_exact32(polyAccuExact[intervals],polyAccurateTDCoeffsHighest,polyAccurateDDCoeffsHighest):\n\n\nepsAccurate[intervals] := numapprox[infnorm](((unapply(polyAccurate[intervals],x)(x)\/g(x))-1), \n\t\t\t\t\tx=(1-bound[intervals]+2^(-53))..(1-bound[intervals-1])):\n\n\npolyQuickExact[intervals] := truncPoly(polyAccuExact[intervals],polyQuickDegreeHighest):\npolyQuick[intervals] := poly_exact2(polyQuickExact[intervals],polyQuickDDCoeffsHighest):\n\nepsQuick[intervals] := numapprox[infnorm](((unapply(polyQuick[intervals],x)(x)\/g(x))-1), \n\t\t\t\t\tx=(1-bound[intervals]+2^(-53))..(1-bound[intervals-1])):\n\nprintf(\"Checking if the polynomial for interval %d is exactly -1 in z = %f...\\n\",intervals,1-bound[intervals]);\n\nif (unapply(polyAccurate[intervals],x)(1-bound[intervals]) = -1) then\n\tprintf(\" Check passed!\\n\"):\nelse\n\tprintf(\" Check failed!\\n\"):\nend if:\n\nend if:\n\n\n\nfor i from 1 to intervals do \n\tprintf(\"Relative error for accurate phase polynomial in interval %d ([%f;%f]) is 2^(%f)\\n\",\n \t\ti,bound[i-1],bound[i],log[2](abs(epsAccurate[i]))):\n\tprintf(\"Relative error for quick phase polynomial in interval %d ([%f;%f]) is 2^(%f)\\n\",\n \t\ti,bound[i-1],bound[i],log[2](abs(epsQuick[i]))):\nod:\nprintf(\"Relative error for accurate phase polynomial #1 in special interval [0;sin(2^(-18))]) is 2^(%f)\\n\",\n log[2](abs(epsAccurateSpecial))):\n\nprintf(\"Relative error for quick phase extra case truncated polynomial #1 in special interval [0;%f]) is 2^(%f)\\n\",\n extrabound,log[2](abs(epsQuickExtra))):\n\n\n(PiHalfH, PiHalfM, PiHalfL) := hi_mi_lo(evalf(Pi\/2)):\n\nepsPiDD := evalf(((PiHalfH + PiHalfM) - Pi\/2)\/(Pi\/2)):\nepsPiTD := evalf(((PiHalfH + PiHalfM + PiHalfL) - Pi\/2) \/ (Pi\/2)):\n\nprintf(\"Relative error for storing Pi\/2 as a double-double is 2^(%f)\\n\",evalf(log[2](abs(epsPiDD)))):\nprintf(\"Relative error for storing Pi\/2 as a triple-double is 2^(%f)\\n\",evalf(log[2](abs(epsPiTD)))):\n\n# Ce qui suit est pifometrique et doit etre prouve en Gappa ensuite\n\narithmeticalErrorQuick[1] := 2^(-61):\narithmeticalErrorQuick[2] := 2^(-61):\narithmeticalErrorQuick[3] := 2^(-61):\narithmeticalErrorQuick[4] := 2^(-61):\narithmeticalErrorQuick[5] := 2^(-61):\narithmeticalErrorQuick[6] := 2^(-61):\narithmeticalErrorQuick[7] := 2^(-61):\narithmeticalErrorQuick[8] := 2^(-61):\narithmeticalErrorQuick[9] := 2^(-61):\narithmeticalErrorQuick[10] := 2^(-68):\n\narithmeticalErrorQuickExtra := 2^(-80):\n\nfor i from 1 to intervals do\n\testimatedOverallEpsQuick[i] := abs(epsQuick[i]) + \n\t\t\t\t abs(arithmeticalErrorQuick[i]) + \n abs(epsQuick[i]) * abs(arithmeticalErrorQuick[i]):\n\tprintf(\"Relative quick phase overall error bound to show in Gappa for interval %d ([%f;%f]) is 2^(%f)\\n\",\n\t\ti,bound[i-1],bound[i],log[2](abs(estimatedOverallEpsQuick[i]))):\nod:\n\nestimatedOverallEpsQuickExtra := abs(epsQuickExtra) + \n\t\t\t\t abs(arithmeticalErrorQuickExtra) + \n abs(epsQuickExtra) * abs(arithmeticalErrorQuickExtra):\nprintf(\"Relative quick phase overall error bound to show for extra truncted poly in interval [0;%f]) is 2^(%f)\\n\",\n\textrabound,log[2](abs(estimatedOverallEpsQuickExtra))):\n\n\nprintf(\"Write tables...\\n\"):\n\nfilename:=\"TEMPASIN\/asin-td.h\":\nfd:=fopen(filename, WRITE, TEXT):\n\nfprintf(fd, \"#include \\\"crlibm.h\\\"\\n#include \\\"crlibm_private.h\\\"\\n\"):\n\nfprintf(fd, \"\\n\/* File generated by maple\/asin-td.mpl *\/\\n\\n\"):\n\nprintf(\"Write table with bounds\\n\"):\n\nfprintf(fd, \"\/* High order words of interval bounds (low order word is 0) *\/\\n\"):\nfor i from 1 to (intervals-1) do \n\theb := ieeehexa(bound[i]):\n\tfprintf(fd, \"\\#define BOUND%d 0x%s\\n\",i,heb[1]):\nod:\n\nheb := ieeehexa(extrabound):\nfprintf(fd, \"\\#define EXTRABOUND 0x%s\\n\",heb[1]):\n\nprintf(\"Write additional constants\\n\"):\n\nfprintf(fd, \"\\n\\n\/* Pi\/2 as a triple-double*\/\\n\"):\nfprintf(fd, \"\\#define PIHALFH %1.50e\\n\",PiHalfH):\nfprintf(fd, \"\\#define PIHALFM %1.50e\\n\",PiHalfM):\nfprintf(fd, \"\\#define PIHALFL %1.50e\\n\",PiHalfL):\n\nprintf(\"Write table with midpoints and polynomial coefficients\\n\"):\nk := 0:\nfor i from 0 to polyAccurateDegreeLowest do\n\t(hi,mi,lo) := hi_mi_lo(coeff(polyAccurate[1],x,i)):\n\tif ((abs(hi) = 1.0) and (mi = 0) and (lo = 0)) then \n\t\tprintf(\n\t\t\"Coefficient %d of interval 1 polynomial is exactly %f and will not be stored in the table\\n\",i,hi): \n\telse \n\tg := 0;\n\tif (hi <> 0) then\n\t\tif (i <= polyQuickDegreeLowest) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dh, quickPolyLowC%dh *\/\",hi,k,i,i):\n\t\telse\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dh *\/\",hi,k,i):\n\t\tend if:\n\t\tk := k + 1:\n\tend if:\n\tif (mi <> 0) then\n\t\tif (i <= polyQuickDDCoeffsLowest) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dm, quickPolyLowC%dl *\/\",mi,k,i,i):\n\t\telse\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dm *\/\",mi,k,i):\n\t\tend if:\n\t\tk := k + 1:\n\tend if:\n\tif (lo <> 0) then\n\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyLowC%dl *\/\",lo,k,i):\n\t\tk := k + 1:\n\tend if:\n\tend if:\nod:\ntbl[k] := sprintf(\"%1.50e, \\t\/* %d, RN rounding constant quick poly low*\/\",\n\t\tcompute_rn_constant(estimatedOverallEpsQuick[1]),k):\nk := k + 1:\ntbl[k] := sprintf(\"%1.50e, \\t\/* %d, RD rounding constant quick poly low*\/\",\n\t\testimatedOverallEpsQuick[1],k):\nk := k + 1:\nprintf(\"Table for interval 1 written\\n\"):\nfor l from 2 to (intervals-1) do\n\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, midpoint in interval %d*\/\",midpointFloat[l],k,l):\n\ttblidx[l] := k;\n\tk := k + 1;\n\tfor i from 0 to polyAccurateDegreeMiddle do\n\t\t(hi,mi,lo) := hi_mi_lo(coeff(polyAccurate[l],x,i)):\n\t\tif ((abs(hi) = 1.0) and (mi = 0) and (lo = 0)) then \n\t\t\tprintf(\n\t\t\"Coefficient %d of interval %d polynomial is exactly %f and will not be stored in the table\\n\",i,l,hi): \n\t\telse \n\t\tg := 0;\n\t\tif (hi <> 0) then\n\t\t\tif (i <= polyQuickDegreeMiddle) then\n\t\t\t\ttbl[k] := sprintf(\n\t\t\t\t\t\"%1.50e, \\t\/* %d, accPolyMid%dC%dh, quickPolyMid%dC%dh *\/\",hi,k,l,i,l,i):\n\t\t\telse\n\t\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyMid%dC%dh *\/\",hi,k,l,i):\n\t\t\tend if:\n\t\t\tk := k + 1:\n\t\tend if:\n\t\tif (mi <> 0) then\n\t\t\tif (i <= polyQuickDDCoeffsMiddle) then\n\t\t\t\ttbl[k] := sprintf(\n\t\t\t\t\t\"%1.50e, \\t\/* %d, accPolyMid%dC%dm, quickPolyMid%dC%dl *\/\",mi,k,l,i,l,i):\n\t\t\telse\n\t\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyMid%dC%dm *\/\",mi,k,l,i):\n\t\t\tend if:\n\t\t\tk := k + 1:\n\t\tend if:\n\t\tif (lo <> 0) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyMid%dC%dl *\/\",lo,k,l,i):\n\t\t\tk := k + 1:\n\t\tend if:\n\t\tend if:\n\tod:\n\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, RN rounding constant quick poly middle %d*\/\",\n\t\t\tcompute_rn_constant(estimatedOverallEpsQuick[l]),k,l):\n\tk := k + 1:\n\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, RD rounding constant quick poly middle %d*\/\",\n\t\t\testimatedOverallEpsQuick[l],k,l):\n\tk := k + 1:\n\tprintf(\"Table for interval %d written\\n\",l):\nod:\ntblidx[intervals] := k:\nfor i from 0 to polyAccurateDegreeHighest do\n\t(hi,mi,lo) := hi_mi_lo(coeff(polyAccurate[intervals],x,i)):\n\tif ((abs(hi) = 1.0) and (mi = 0) and (lo = 0)) then \n\t\tprintf(\n\t\"Coefficient %d of interval %d polynomial is exactly %f and will not be stored in the table\\n\",i,intervals,hi): \n\telse \n\tg := 0;\t\n\tif (hi <> 0) then\n\t\tif (i <= polyQuickDegreeHighest) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dh, quickPolyHighC%dh *\/\",hi,k,i,i):\n\t\telse\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dh *\/\",hi,k,i):\n\t\tend if:\n\t\tk := k + 1:\n\tend if:\n\tif (mi <> 0) then\n\t\tif (i <= polyQuickDDCoeffsHighest) then\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dm, quickPolyHighC%dl *\/\",mi,k,i,i):\n\t\telse\n\t\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dm *\/\",mi,k,i):\n\t\tend if:\n\t\tk := k + 1:\n\tend if:\n\tif (lo <> 0) then\n\t\ttbl[k] := sprintf(\"%1.50e, \\t\/* %d, accPolyHighC%dl *\/\",lo,k,i):\n\t\tk := k + 1:\n\tend if:\n\tend if:\nod:\ntbl[k] := sprintf(\"%1.50e, \\t\/* %d, RN rounding constant quick poly high*\/\",\n\t\tcompute_rn_constant(estimatedOverallEpsQuick[intervals]),k):\nk := k + 1:\ntbl[k] := sprintf(\"%1.50e, \\t\/* %d, RD rounding constant quick poly high*\/\",\n \t\testimatedOverallEpsQuick[intervals],k):\nk := k + 1:\nprintf(\"Table for interval %d written\\n\",intervals):\ntbllen := k:\nprintf(\"The whole table has %d entries, so uses %d bytes of memory\\n\",tbllen,tbllen*8):\nfprintf(fd,\"\\n\\n\/* Indices to the following table *\/\\n\"):\nfor i from 2 to intervals do\n\tfprintf(fd,\"\\#define TBLIDX%d %d\\n\",i,tblidx[i]):\nod:\nfprintf(fd, \"\\n\\n\/* Table with midpoints and polynomial coefficients *\/\\n\"):\nfprintf(fd, \"static const double tbl[%d] = {\\n\",tbllen):\nfor i from 0 to (tbllen - 1) do\n\tfprintf(fd, \"%s\\n\",tbl[i]):\nod:\nfprintf(fd, \"};\\n\\n\"):\n\nfclose(fd):\n\nprintf(\"----DONE---\\n\"):\n\n\n","avg_line_length":35.2217573222,"max_line_length":122,"alphanum_fraction":0.6761701117} +{"size":11434,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n c72da2b9-7cce-4447-8389-f407dc1158b7(jetbrains.mps.lang.structure)<\/dependency>\n 7866978e-a0f0-4cc7-81bc-4d213d9375e1(jetbrains.mps.lang.smodel)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n c72bb5ed-7d2b-4e68-8d06-5f02045d0bcc(com.specificlanguages.model2json)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 7866978e-a0f0-4cc7-81bc-4d213d9375e1(jetbrains.mps.lang.smodel)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":82.2589928058,"max_line_length":147,"alphanum_fraction":0.7357880007} +{"size":1920,"ext":"mpl","lang":"Maple","max_stars_count":12.0,"content":"# convert from Gonnet's FPAccuracy data sets to mpfr format\n# http:\/\/www.inf.ethz.ch\/personal\/gonnet\/FPAccuracy\/all.tar.Z\n\n# 1 - cut the lines from (say) C\/acos.c, remove the 3rd (eps) field,\n# replace the commata ',' by spaces, and remove the final '};'\n# (hint: cut -d\" \" -f1,2,4,5 \/tmp\/acos.c > \/tmp\/acos2.c)\n# 2 - edit the infile and outfile lines below, and run\n# maple -q < gonnet.mpl \n\ninfile := \"\/tmp\/acos2.c\":\noutfile := \"acos\":\n\n###################### don't edit below this line #############################\n\nfoo := proc(arg_m, val_m, arg_e, val_e, fp)\n fprintf (fp, \"53 53 n \", 53);\n to_hex(arg_m, arg_e, fp);\n fprintf (fp, \" \");\n # warning: Gonnet stores -val_e\n to_hex(val_m, -val_e, fp);\n fprintf (fp, \"\\n\");\nend:\n\nto_hex := proc(m, e, fp)\n if m<0 then fprintf (fp, \"-\") fi;\n fprintf (fp, \"0x%sp%d\", convert(abs(m),hex), e);\nend:\n\ncopyright := proc(fp)\n fprintf (fp, \"# This file was generated from the FPAccuracy package\\n# http:\/\/www.inf.ethz.ch\/personal\/gonnet\/FPAccuracy\/all.tar.Z:\\n# Copyright (C) Gaston H. Gonnet\\n# This program is free software; you can redistribute it and\/or\\n# modify it under the terms of the GNU General Public License\\n# as published by the Free Software Foundation; either version 2\\n# of the License, or (at your option) any later version.\\n# This program is distributed in the hope that it will be useful,\\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\\n# GNU General Public License for more details.\\n# You should have received a copy of the GNU General Public License\\n# along with this program; if not, write to the Free Software\\n# Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.\\n\")\nend:\n\nfp := fopen (outfile, WRITE):\n\nl := readdata(infile, integer, 4):\ncopyright(fp):\nfor e in l do foo(op(e), fp) od:\n\nfclose (fp);\n\nquit;\n\n","avg_line_length":44.6511627907,"max_line_length":881,"alphanum_fraction":0.6682291667} +{"size":11304,"ext":"mpl","lang":"Maple","max_stars_count":32.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n 7b68d745-a7b8-48b9-bd9c-05c0f8725a35(org.iets3.core.base)<\/dependency>\n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n ecfb9949-7433-4db5-85de-0f84d172e4ce(de.q60.mps.collections.libs)<\/dependency>\n 498d89d2-c2e9-11e2-ad49-6cf049e62fe5(MPS.IDEA)<\/dependency>\n 742f6602-5a2f-4313-aa6e-ae1cd4ffdc61(MPS.Platform)<\/dependency>\n b0f8641f-bd77-4421-8425-30d9088a82f7(org.apache.commons)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 7b68d745-a7b8-48b9-bd9c-05c0f8725a35(org.iets3.core.base)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":89.7142857143,"max_line_length":128,"alphanum_fraction":0.752388535} +{"size":846,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"# Maple Code Generator\n\n##\n## Copyright (C) 2015-2017 Maplesoft\n## Authors: Behzad Samadi \n## Created: September 2017\n## Version: 0.2\n## Keywords: Maple, Code Generation, Model Predictive Control (MPC)\n##\n## Procedures:\n## CGMRES\n##\n\nMapleCodeGenerator := module()\ndescription \"Maple code generation for numerical optimization\";\noption package;\n\nexport DotProduct,\n GMRES,\n GradientDescent,\n LMGMRES,\n Minimize1D,\n NewName,\n NewtonsMethod,\n NewtonsMethodGMRES,\n nfGMRES,\n Norm2;\n\n$include \"DotProduct.mm\"\n$include \"GMRES.mm\"\n$include \"GradientDescent.mm\"\n$include \"LMGMRES.mm\"\n$include \"Minimize1D.mm\"\n$include \"NewName.mm\"\n$include \"NewtonsMethod.mm\"\n$include \"NewtonsMethodGMRES.mm\"\n$include \"nfGMRES.mm\"\n$include \"Norm2.mm\"\n\nend module; # MCG\n","avg_line_length":20.6341463415,"max_line_length":69,"alphanum_fraction":0.6773049645} +{"size":12944,"ext":"mpl","lang":"Maple","max_stars_count":6.0,"content":"\n\n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n <\/facets>\n \n \n <\/external-templates>\n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 6ed54515-acc8-4d1e-a16c-9fd6cfe951ea(MPS.Core)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n 0647eca7-da98-422a-8a8b-6ebc0bd014ea(jetbrains.mps.lang.editor#1129914002149)<\/dependency>\n 2e24a298-44d1-4697-baec-5c424fed3a3b(jetbrains.mps.editorlang.runtime)<\/dependency>\n 18bc6592-03a6-4e29-a83a-7ff23bde13ba(jetbrains.mps.lang.editor)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n \n \n \n \n \n <\/external-mapping>\n <\/greater-priority-mapping>\n \n \n \n \n <\/external-mapping>\n <\/lesser-priority-mapping>\n <\/mapping-priority-rule>\n <\/mapping-priorities>\n <\/generator>\n <\/generators>\n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 6ed54515-acc8-4d1e-a16c-9fd6cfe951ea(MPS.Core)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 18bc6592-03a6-4e29-a83a-7ff23bde13ba(jetbrains.mps.lang.editor)<\/dependency>\n 498d89d2-c2e9-11e2-ad49-6cf049e62fe5(MPS.IDEA)<\/dependency>\n 742f6602-5a2f-4313-aa6e-ae1cd4ffdc61(MPS.Platform)<\/dependency>\n d99339ed-76f8-45c0-bf5f-697b98ae6a17(org.campagnelab.editor.listeners.plugin)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 18bc6592-03a6-4e29-a83a-7ff23bde13ba(jetbrains.mps.lang.editor)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":81.4088050314,"max_line_length":177,"alphanum_fraction":0.7336217553} +{"size":1618,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"!This file is subject to the terms and conditions defined in\n!file 'LICENSE.txt', which is part of this source code package.\n\nTITLE\n \n\tCAP_extensive_form_cap123_3000;\n\nSTOCHASTIC\n\nDATA\n\t\n\tI := DATAFILE(\"cap123_3000_SETS.dat\");\n\tJ := DATAFILE(\"cap123_3000_SETS.dat\");\n\tK := DATAFILE(\"cap123_3000_SETS.dat\");\t\t\t\t! - num scenarios\n\tQ := I;\t\t\t\t\t\t\t! - num 1st stage columns\n\tT := I*J;\t\t\t\t\t\t! - num 2nd stage columns\n\tR := J+I;\t\t\t\t\t\t! - num rows in T and W\n\t\n\nSCENARIO\n \n\tk := 1..K;\n\nINDEX\n\tFirstStCol := 1..Q;\n\tSecondStCol := 1..T;\n\tRow := 1..R;\t\n\nPROBABILITIES\n \n\tp[k] := ALLEQUAL;\n\nRANDOM DATA\n\n\tVector_h[k, Row] := DATAFILE(\"cap123_3000_RANDOM.dat\");\t! - rows are related to scenarios\n\nDATA\n \n\tVector_c[FirstStCol] := DATAFILE(\"cap123_3000_DATA.dat\");\n\tVector_d[SecondStCol] := DATAFILE(\"cap123_3000_DATA.dat\");\n\tVector_b := DATAFILE(\"cap123_3000_DATA.dat\");\t\t\t! - max sum of h over all scenarios\n\tMatrix_A[FirstStCol] := DATAFILE(\"cap123_3000_DATA.dat\");\n\tMatrix_T[Row, FirstStCol] := DATAFILE(\"cap123_3000_DATA.dat\");\n\tMatrix_W[Row, SecondStCol] := DATAFILE(\"cap123_3000_DATA.dat\");\n\tx_ub[FirstStCol] := DATAFILE(\"cap123_3000_DATA.dat\");\n\nSTAGE1 BINARY VARIABLES\n\n\tx[FirstStCol];\n\nSTAGE2 VARIABLES\n\n\ty[SecondStCol];\n\nMACROS\n\n\tStageFirst = sum(FirstStCol: Vector_c * x);\n\tStageSecond = sum(SecondStCol: Vector_d * y);\n\nMIN\n\n\tObjective = StageFirst + StageSecond;\n\nSUBJECT TO\n\t\n\tFirstStCnstr: sum(FirstStCol: Matrix_A * x) >= Vector_b;\n \tSecondStCnstr[Row]: sum(FirstStCol: Matrix_T * x) + sum(SecondStCol: Matrix_W * y) >= Vector_h;\n\nBOUNDS\n\n\tBinBounds[FirstStCol]: x <= x_ub;\t! - why do we need it\n\nEND","avg_line_length":22.1643835616,"max_line_length":100,"alphanum_fraction":0.6878862794} +{"size":645,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_mgga_c *)\n\n$include \"gga_c_gapc.mpl\"\n\n(* override definition of gap_C *)\ngap_G := (rs, z, xt, par) -> RS_FACTOR^2\/8 * xt^2\/rs^2:\n\nf_kcis := (rs, z, xt, xs0, xs1, ts0, ts1) ->\n + f_gap(rs, z, xt)\n - xs0^2\/(8*ts0) * (1 + z)\/2 * f_gap(rs, 1, xs0)\n - xs1^2\/(8*ts1) * (1 - z)\/2 * f_gap(rs, -1, xs1):\n\nf := (rs, z, xt, xs0, xs1, ts0, ts1, us0, us1) ->\n f_kcis(rs, z, xt, xs0, xs1, ts0, ts1):\n","avg_line_length":28.0434782609,"max_line_length":68,"alphanum_fraction":0.5937984496} +{"size":7762,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n d7b89f88-e35a-4352-b1df-0d102968826c(com.dslfoundry.examples.graph)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n 83888646-71ce-4f1c-9c53-c54016f6ad4f(jetbrains.mps.baseLanguage.collections)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":79.2040816327,"max_line_length":145,"alphanum_fraction":0.7364081422} +{"size":12846,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 2374bc90-7e37-41f1-a9c4-c2e35194c36a(com.mbeddr.doc)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n d4280a54-f6df-4383-aa41-d1b2bffa7eb1(com.mbeddr.core.base)<\/dependency>\n c72da2b9-7cce-4447-8389-f407dc1158b7(jetbrains.mps.lang.structure)<\/dependency>\n ceab5195-25ea-4f22-9b92-103b95ca8c0c(jetbrains.mps.lang.core)<\/dependency>\n f95247f1-a285-4e98-864f-7f4b1723a807(org.iets3.core.users)<\/dependency>\n 8e4e17de-bc10-4a34-a376-a243fbde540e(org.iets3.glossary)<\/dependency>\n 92d2ea16-5a42-4fdf-a676-c7604efe3504(de.slisson.mps.richtext)<\/dependency>\n b0f8641f-bd77-4421-8425-30d9088a82f7(org.apache.commons)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 7b68d745-a7b8-48b9-bd9c-05c0f8725a35(org.iets3.core.base)<\/extendedLanguage>\n d4280a54-f6df-4383-aa41-d1b2bffa7eb1(com.mbeddr.core.base)<\/extendedLanguage>\n 2374bc90-7e37-41f1-a9c4-c2e35194c36a(com.mbeddr.doc)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":86.7972972973,"max_line_length":123,"alphanum_fraction":0.7410088744} +{"size":16062,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 71934284-d7d1-45ee-a054-8c072591085f(org.iets3.core.expr.toplevel)<\/dependency>\n 6b277d9a-d52d-416f-a209-1919bd737f50(org.iets3.core.expr.simpleTypes)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n d441fba0-f46b-43cd-b723-dad7b65da615(org.iets3.core.expr.tests)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":91.7828571429,"max_line_length":142,"alphanum_fraction":0.7387622961} +{"size":11745,"ext":"mpl","lang":"Maple","max_stars_count":25.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 0fda14cc-a416-4c81-869a-2175d8b3325d(jetbrains.mps.baseLanguageExt)<\/extendedLanguage>\n df345b11-b8c7-4213-ac66-48d2a9b75d88(jetbrains.mps.baseLanguageInternal)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":83.8928571429,"max_line_length":142,"alphanum_fraction":0.7389527458} +{"size":763,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n Copyright (C) 2018 Susi Lehtola\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: mgga_exc *)\n(* prefix:\n mgga_x_rtpss_params *params;\n\n assert(p->params != NULL);\n params = (mgga_x_rtpss_params * ) (p->params);\n*)\n\n(* These are used within the tpss_x routine *)\ntpss_ff := z -> 2:\ntpss_kappa := (x, t) -> params_a_kappa:\n\n$include \"tpss_x.mpl\"\n\n(* Equation (6) *)\n\nrtpss_f := (x, u, t) -> 1 + tpss_kappa(x, t)*(1 - exp(-tpss_fx(x, t)\/tpss_kappa(x,t))):\n\nf := (rs, z, xt, xs0, xs1, u0, u1, t0, t1) -> mgga_exchange(rtpss_f, rs, z, xs0, xs1, u0, u1, t0, t1):","avg_line_length":27.25,"max_line_length":102,"alphanum_fraction":0.6356487549} +{"size":2754,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n 2019 Susi Lehtola\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* Equation 28 squared with Equation 25 built in *)\ntpss_xi2 := (z, xt, xs0, xs1) ->\n (1 - z^2)*(t_total(z, xs0^2, xs1^2) - xt^2)\/(2*(3*Pi^2)^(1\/3))^2:\n\n(* Equation 33 *)\ntpss_C00 := (cc, z) ->\n + add(cc[i]*z^(2*(i-1)), i=1..4):\n\n(* Equation 34 *)\n(* The series expansion of C0 for z -> +- 1 goes as C + D*(1+-z)^(2\/3) + O(1+-z)\n whose first derivative seems to diverge for ferromagnetic densities, leading\n to severe numerical instabilities. I can not correct for the bad design of\n the functional, and this is the possible solution that I found *)\ntpss_C0_den := (z, xt, xs0, xs1) ->\n 1 + tpss_xi2(z, xt, xs0, xs1)*((1 + z)^(-4\/3) + (1 - z)^(-4\/3))\/2:\ntpss_C0 := (cc, z, xt, xs0, xs1) -> my_piecewise3(1 - m_abs(z) <= 1e-12,\n add(cc[i], i=1..4),\n tpss_C00(cc, z) \/ tpss_C0_den(z_thr(z), xt, xs0, xs1)^4):\n\n(* Equation 11, with tau_W from Equation 12 *)\ntpss_aux := (z, xt, ts0, ts1) ->\n m_min(xt^2\/(8*t_total(z, ts0, ts1)), 1):\n\n(* n_sigma\/n \\epsilon^sigma in Equation 25 *)\ntpss_par_s0 := (f_gga, rs, z, xt, xs0, xs1) ->\n m_max(f_gga(rs*(2\/(1 + z))^(1\/3), 1, xs0, xs0, 0), f_gga(rs, z, xt, xs0, xs1))*(1 + z)\/2:\ntpss_par_s1 := (f_gga, rs, z, xt, xs0, xs1) ->\n m_max(f_gga(rs*(2\/(1 - z))^(1\/3), -1, xs1, 0, xs1), f_gga(rs, z, xt, xs0, xs1))*(1 - z)\/2:\n\n(* Second line of Equation 25 *)\n(* The screening of the density is important in order to stabilize this functional\n for ferromagnetic densities *)\ntpss_par := (f_gga, rs, z, xt, xs0, xs1, ts0, ts1) ->\n - (1 + tpss_C0(params_a_C0_c, z, xt, xs0, xs1))*tpss_aux(z, xt, ts0, ts1)^2*(\n + my_piecewise3(screen_dens_zeta(rs, z),\n f_gga(rs, z_thr(z), xt, xs0, xs1)*(1 + z)\/2,\n tpss_par_s0(f_gga, rs, z_thr(z), xt, xs0, xs1)\n )\n + my_piecewise3(screen_dens_zeta(rs, -z),\n f_gga(rs, z_thr(z), xt, xs0, xs1)*(1 - z)\/2,\n tpss_par_s1(f_gga, rs, z_thr(z), xt, xs0, xs1)\n )\n ):\n\n(* First line of Equation 25 *)\ntpss_perp := (f_gga, rs, z, xt, xs0, xs1, ts0, ts1) ->\n (1 + tpss_C0(params_a_C0_c, z, xt, xs0, xs1)*tpss_aux(z, xt, ts0, ts1)^2)\n * f_gga(rs, z, xt, xs0, xs1):\n\n(* Equation in full 25 *)\ntpss_f0 := (f_gga, rs, z, xt, xs0, xs1, ts0, ts1) ->\n + tpss_par (f_gga, rs, z, xt, xs0, xs1, ts0, ts1)\n + tpss_perp(f_gga, rs, z, xt, xs0, xs1, ts0, ts1):\n\n(* Equation 24 *)\ntpss_f := (f_gga, rs, z, xt, xs0, xs1, ts0, ts1) ->\n + tpss_f0(f_gga, rs, z, xt, xs0, xs1, ts0, ts1)\n * (1 + params_a_d*tpss_f0(f_gga, rs, z, xt, xs0, xs1, ts0, ts1)*tpss_aux(z, xt, ts0, ts1)^3):\n","avg_line_length":40.5,"max_line_length":95,"alphanum_fraction":0.5922294844} +{"size":1594,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"!This file is subject to the terms and conditions defined in\n!file 'LICENSE.txt', which is part of this source code package.\n\nTITLE\n \n\tCAP_extensive_form_cap123_50;\n\nSTOCHASTIC\n\nDATA\n\t\n\tI := DATAFILE(\"cap123_50_SETS.dat\");\n\tJ := DATAFILE(\"cap123_50_SETS.dat\");\n\tK := DATAFILE(\"cap123_50_SETS.dat\");\t\t\t\t! - num scenarios\n\tQ := I;\t\t\t\t\t\t\t! - num 1st stage columns\n\tT := I*J;\t\t\t\t\t\t! - num 2nd stage columns\n\tR := J+I;\t\t\t\t\t\t! - num rows in T and W\n\t\n\nSCENARIO\n \n\tk := 1..K;\n\nINDEX\n\tFirstStCol := 1..Q;\n\tSecondStCol := 1..T;\n\tRow := 1..R;\t\n\nPROBABILITIES\n \n\tp[k] := ALLEQUAL;\n\nRANDOM DATA\n\n\tVector_h[k, Row] := DATAFILE(\"cap123_50_RANDOM.dat\");\t! - rows are related to scenarios\n\nDATA\n \n\tVector_c[FirstStCol] := DATAFILE(\"cap123_50_DATA.dat\");\n\tVector_d[SecondStCol] := DATAFILE(\"cap123_50_DATA.dat\");\n\tVector_b := DATAFILE(\"cap123_50_DATA.dat\");\t\t\t! - max sum of h over all scenarios\n\tMatrix_A[FirstStCol] := DATAFILE(\"cap123_50_DATA.dat\");\n\tMatrix_T[Row, FirstStCol] := DATAFILE(\"cap123_50_DATA.dat\");\n\tMatrix_W[Row, SecondStCol] := DATAFILE(\"cap123_50_DATA.dat\");\n\tx_ub[FirstStCol] := DATAFILE(\"cap123_50_DATA.dat\");\n\nSTAGE1 BINARY VARIABLES\n\n\tx[FirstStCol];\n\nSTAGE2 VARIABLES\n\n\ty[SecondStCol];\n\nMACROS\n\n\tStageFirst = sum(FirstStCol: Vector_c * x);\n\tStageSecond = sum(SecondStCol: Vector_d * y);\n\nMIN\n\n\tObjective = StageFirst + StageSecond;\n\nSUBJECT TO\n\t\n\tFirstStCnstr: sum(FirstStCol: Matrix_A * x) >= Vector_b;\n \tSecondStCnstr[Row]: sum(FirstStCol: Matrix_T * x) + sum(SecondStCol: Matrix_W * y) >= Vector_h;\n\nBOUNDS\n\n\tBinBounds[FirstStCol]: x <= x_ub;\t! - why do we need it\n\nEND","avg_line_length":21.8356164384,"max_line_length":100,"alphanum_fraction":0.6831869511} +{"size":582,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_lda *)\n(* prefix:\n lda_x_params *params;\n\n assert(p->params != NULL);\n params = (lda_x_params * )(p->params);\n*)\n\n$ifdef lda_x_params\nparams_a_alpha := 1:\n$endif\n\nlda_x_ax := -params_a_alpha*RS_FACTOR*X_FACTOR_C\/2^(4\/3):\n\nf_lda_x := (rs, z) -> lda_x_ax*((1 + z)^(4\/3) + (1 - z)^(4\/3))\/rs:\nf := (rs, z) -> f_lda_x(rs, z):","avg_line_length":24.25,"max_line_length":68,"alphanum_fraction":0.6357388316} +{"size":17764,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 7b68d745-a7b8-48b9-bd9c-05c0f8725a35(org.iets3.core.base)<\/dependency>\n daafa647-f1f7-4b0b-b096-69cd7c8408c0(jetbrains.mps.baseLanguage.regexp)<\/dependency>\n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 6ed54515-acc8-4d1e-a16c-9fd6cfe951ea(MPS.Core)<\/dependency>\n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/dependency>\n 47f075a6-558e-4640-a606-7ce0236c8023(com.mbeddr.mpsutil.interpreter)<\/dependency>\n 92d2ea16-5a42-4fdf-a676-c7604efe3504(de.slisson.mps.richtext)<\/dependency>\n b0f8641f-bd77-4421-8425-30d9088a82f7(org.apache.commons)<\/dependency>\n dbe08fb5-334d-4b64-86a0-622406fa0e87(org.iets3.core.expr.base.runtime)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n cfaa4966-b7d5-4b69-b66a-309a6e1a7290(org.iets3.core.expr.base)<\/extendedLanguage>\n ceab5195-25ea-4f22-9b92-103b95ca8c0c(jetbrains.mps.lang.core)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":89.2663316583,"max_line_length":136,"alphanum_fraction":0.7399797343} +{"size":12201,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n 2d3c70e9-aab2-4870-8d8d-6036800e4103(jetbrains.mps.kernel)<\/dependency>\n 3b3d39a8-ff6e-47f3-9c9e-1888a27699ed(org.campagnelab.util)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n c6c823fb-a9da-46e7-9850-129b0f7a7aa5(org.campagnelab.workflow)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":87.15,"max_line_length":139,"alphanum_fraction":0.7381362183} +{"size":856,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: mgga_exc *)\n(* prefix:\n mgga_x_tau_hcth_params *params;\n\n assert(p->params != NULL);\n params = (mgga_x_tau_hcth_params * ) (p->params);\n*)\n\nhcth_coeff_a := [0, 1, 0, -2, 0, 1]:\n\n(* Equation (29) *)\nhcth_gamX := 0.004:\nhcth_ux := x -> hcth_gamX*x^2\/(1 + hcth_gamX*x^2):\n\nhcth_gxl := x -> add(params_a_cx_local [i]*hcth_ux(x)^(i-1), i=1..4):\nhcth_gxnl := x -> add(params_a_cx_nlocal[i]*hcth_ux(x)^(i-1), i=1..4):\n\nhcth_f := (x, u, t) -> hcth_gxl(x) + hcth_gxnl(x)*mgga_series_w(hcth_coeff_a, 6, t):\n\nf := (rs, z, xt, xs0, xs1, u0, u1, t0, t1) -> mgga_exchange(hcth_f, rs, z, xs0, xs1, u0, u1, t0, t1):","avg_line_length":30.5714285714,"max_line_length":101,"alphanum_fraction":0.6285046729} +{"size":522,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: lda_exc *)\n\n$include \"vwn.mpl\"\n\nf_vwn := (rs, z) ->\n + f_aux(A_vwn[1], b_vwn[1], c_vwn[1], x0_vwn[1], rs)\n + DMC(rs, z)\/DRPA(rs, z)*f_aux(A_rpa[3], b_rpa[3], c_rpa[3], x0_rpa[3], rs)*f_zeta(z)*(1 - z^4)\/fpp_vwn\n + DMC(rs, z)*f_zeta(z)*z^4:\n\nf := (rs, z) -> f_vwn(rs, z):\n","avg_line_length":27.4736842105,"max_line_length":105,"alphanum_fraction":0.6168582375} +{"size":5498,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":80.8529411765,"max_line_length":148,"alphanum_fraction":0.7464532557} +{"size":8106,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n 6f14e29b-9796-426f-ae46-86ea46d4d320(de.slisson.mps.structurecheck.runtime)<\/dependency>\n fd392034-7849-419d-9071-12563d152375(jetbrains.mps.baseLanguage.closures)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 6f14e29b-9796-426f-ae46-86ea46d4d320(de.slisson.mps.structurecheck.runtime)<\/dependency>\n <\/runtime>\n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":78.6990291262,"max_line_length":134,"alphanum_fraction":0.7346410067} +{"size":543,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_mgga_x *)\n\na2 := 146\/2025:\na3 := -73\/405:\na4 := 0.131957187845257783631757384393: (* DD + 100\/(81*81*kappa) *)\n\nkappa := 0.804:\n\nxx := (p, qt) -> MU_GE*p + a2*qt*qt + a3*qt*p + a4*p*p:\n\nf := (rs, x, t, u) -> 1 + kappa - \\\n kappa^2\/(kappa + xx(X2S^2*x^2, 6*X2S^2*t - 9\/20 - X2S^2*x^2\/12)):\n","avg_line_length":25.8571428571,"max_line_length":68,"alphanum_fraction":0.6077348066} 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+{"size":10169,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"# Number of subspaces of dimension d in F^n, if |F|=q\n\ngrassmann_count := (q::posint) -> proc(n,d)\n local i;\n return mul(q^(n-i)-1,i=0..d-1)\/mul(q^(d-i)-1,i=0..d-1);\nend:\n\n# Number of splittings of F^(n+m) as a sum of subspaces of\n# dimensions n and m, if |F| = q.\n\nsplitting_count := (q::posint) -> (n,m) ->\n grassman_count(q)(n+m,n) * q^(n*m);\n\n# tanabe_N(p,n,r)(k) is the number of irreducible F-linear representations\n# of Z_p^n that have dimension p^k over F.\n\ntanabe_N := (p,n,r) -> (k) -> `if`(k = 0,p^(n*r),(p^n-1) * p^((n-1)*k + n*(r-1)));\n\n# The socle of K^0(BGL_{p^k}(F)) is generated by\n# euler(V)^{N-1}, where N = tanabe_N_bar(n,v,k)\n\ntanabe_N_bar := (p,n,r) -> proc(k)\n local j;\n p^(n*r) + (p^n-1)*p^(n*(r-1))*sum(p^((n-1)*j),j=1..k);\nend:\n\ntanabe_N_star := (p,n,r) -> proc(k)\n local j;\n p^(n*r-1) * (p-1) * sum(p^((n-1)*j),j=0..k-1);\nend:\n\ntanabe_N_lim := (p,n,r) -> (k) -> p^(n*r+n*k-k) * (1-p^(-n))\/(1-p^(1-n));\n\n# The natural numbers can be partitioned as the disjoint union of\n# the sets tanabe_NN(p,n,r)(k), of size tanabe_N(p,n,r)(k).\n\ntanabe_NN := (p,n,r) -> proc(k::nonnegint)\n local i;\n if k = 0 then\n return [seq(i,i=0..tanabe_N_bar(p,n,r)(0)-1)];\n else\n return [seq(i,i=tanabe_N_bar(p,n,r)(k-1)..tanabe_N_bar(p,n,r)(k)-1)];\n fi;\nend:\n\n# tanabe_s(p,n,r)(m) is the unique k such that m lies in tanabe_NN(p,n,r)(k).\ntanabe_s := (p,n,r) -> proc(m)\n local k;\n k := 0;\n while m >= tanabe_N_bar(p,n,r)(k) do\n k := k+1;\n od;\n return k;\nend:\n\n# tanabe_X(p,n,r)(k) is the set of generators for E^0(BGL_*(F)) in\n# degree p^k.\n\ntanabe_X := (p,n,r) -> proc(k)\n local j;\n return [seq(c[p^k] ^ j, j = 0..tanabe_N(p,n,r)(k)-1)]; \nend:\n\n# tanabe_prim_gen(p,n,r)(k) is a generator for the primitives\n# in K^0(BGL_*(F)) in degree p^k\ntanabe_prim_gen := (p,n,r) -> (k) -> c[p^k] ^ tanabe_N_bar(p,n,r)(k-1);\n\n# tanabe_soc_gen(p,n,r)(k) is a generator for the socle of\n# K^0(BGL_{p^k}(F))\ntanabe_soc_gen := (p,n,r) -> (k) -> c[p^k] ^ (tanabe_N_bar(p,n,r)(k) - 1);\n\n# tanabe_m(p)(k) has p-adic valuation k and divides\n# tanabe_m(p)(k+1). Moreover, any positive integer n divides\n# tanabe_m(p)(k) when k is sufficiently large.\n\ntanabe_m := (p) -> proc(k) \n local m,i;\n m := 1;\n i := 1;\n while ithprime(i) <= p + k do\n m := m * ithprime(i) ^ k;\n i := i + 1;\n od:\n return m;\nend:\n\ncheck_tanabe_m := proc(p,k)\n _ASSERT(padic_val(tanabe_m(p)(k),p) = k,\n \"v_p(m[k])\");\n\n _ASSERT(type(tanabe_m(p)(k+1)\/tanabe_m(p)(k),posint),\n \"m[k] divides m[k+1]\");\nend:\n\n# Given a polynomial f over the integers and a prime q, return\n# the first irreducible factor of f mod q, in the standard\n# Maple order.\n\nfirst_factor := proc(f,q)\n local F;\n F := :-Factor(f) mod q;\n if type(F,`*`) then F := [op(F)] else F := [F]; fi:\n F := sort(map(g -> `if`(type(g,`^`),op(1,g),g),F));\n return F[1];\nend:\n\n# Return an irreducible polynomial f[k](x) of degree v0 * p^k over\n# Z\/q0. This gives a field F(k) of degree p^k over F = F(0),\n# where F(0) has order q = q0 ^ v0. The polynomials are arranged\n# so that the canonical primitive element x[k] in F(k) generates\n# the group of units, and there is an inclusion F(k) -> F(k+1)\n# sending x[k] to x[k+1] ^ m, where m = |F(k+1)^x|\/|F(k)^x|.\ntanabe_FF_poly := (q0,v0,p) -> proc(k::nonnegint)\n option remember;\n local q,m,f;\n\n q := q0 ^ v0;\n if k = 0 then \n f := NumberTheory[CyclotomicPolynomial](q0 ^ v0 - 1,x);\n else\n m := (q ^ (p ^ k) - 1)\/(q ^ (p ^ (k - 1)) - 1);\n f := subs(x = x ^ m, tanabe_FF_poly(q0,v0,p)(k - 1));\n end:\n\n return first_factor(f,q0);\nend:\n\n# tanabe_F(q0,v0)(m) is the field denoted by F[m] in the paper,\n# where q = q0 ^ v0 with q0 prime and v0 > 0.\n# tanabe_FF(q0,v0)(p,k) is F(k) = F[p^k].\n\ntanabe_F := (q0,v0) -> (m) -> GF(q0,v0 * m);\ntanabe_FF := (q0,v0) -> (p,k) -> GF(q0,v0 * p ^ k,tanabe_FF_poly);\n\n# Orders of various groups: G is the general linear group,\n# N is the subgroup of monomial matrices, H is the block\n# diagonal subgroup of p' index as in prop-non-p-power.\n\ntanabe_G_order := (q) -> proc(d)\n local k;\n return mul(q ^ d - q ^ k,k = 0..d-1);\nend:\n\ntanabe_N_order := (q) -> (d) -> d! * (q - 1)^d;\n\ntanabe_H_order := (q,p) -> proc(d)\n local dd,m,i;\n dd := digit_list(d,p);\n m := nops(dd);\n mul(tanabe_G_order(q)(p ^ i) ^ dd[i+1], i = 0..m-1);\nend:\n\n\n# The E^2 page of the AHSS converging to K_*(BV) has a trigrading\n# with E^2_{ijk} = H_i(BV_k;K_j). It has even generators\n# b[i] and u, and odd generators e[i] with\n# |b[i]| = tanabe_b_trideg(p,n,r)(i) = [2i,0,1]\n# |e[i]| = tanabe_e_trideg(p,n,r)(i) = [2i+1,0,1]\n# |u| = tanabe_u_trideg(p,n,r) = [0,2,0].\n\ntanabe_b_trideg := (p,n,r) -> (i) -> [2*i,0,1];\ntanabe_e_trideg := (p,n,r) -> (i) -> [2*i+1,0,1];\ntanabe_u_trideg := (p,n,r) -> [0,2,0];\n\n# The only nontrivial differentials have the form d_r, where\n# r = tanabe_AHSS_page(p,n,r)(k) for some k >= 0\n# [From now on we refer to this as the k'th differential,\n# and the page on which it occurs as the k'th page.]\n\ntanabe_AHSS_page := (p,n,r) -> (k) -> 2*p^(n*(r+k)) - 1;\n\n# Tridegree of the k'th differential\ntanabe_AHSS_d_trideg := (p,n,r) -> (k) ->\n [1-2*p^(n*(r+k)),2*p^(n*(r+k))-2,0];\n\n# The k'th page can be described in terms of generators\n# bb[m,i] and ee[m,i]\n\ntanabe_bb_defined := (p,n,r) -> (k) -> (m,i) ->\n m >= min(k,tanabe_s(p,n,r)(i));\n\ntanabe_bb_indec := (p,n,r) -> (k) -> (m,i) ->\n m = min(k,tanabe_s(p,n,r)(i));\n\ntanabe_ee_defined := (p,n,r) -> (k) -> (m,i) ->\n m = k and i >= tanabe_N_star(p,n,r)(k);\n\ntanabe_bb_trideg := (p,n,r) -> (m,i) -> [2*p^m*i,0,p^m];\ntanabe_ee_trideg := (p,n,r) -> (m,i) -> [2*p^m*i + 1,0,p^m];\n\ntanabe_dbb0 := (p,n,r) -> (k) -> (m,i) ->\n ee[k,i - tanabe_N_bar(p,n,r)(k) + tanabe_N_star(p,n,r)(k)] *\n u ^ (p^(n * (k + r)) - 1);\n\ntanabe_dbb := (p,n,r) -> (k) -> (m,i) ->\n `if`(m < k, 0, `if`(i < tanabe_N_bar(p,n,r)(k), 0, tanabe_dbb0(p,n,r)(k)(m,i)));\n\n# This is the part of the inverse Poincare series contributed by\n# irreducible representations of dimension at most p^k.\n\ntanabe_inverse_poincare_series := (p,n,r) -> proc(k)\n local j;\n (1-t)^(p^(n*r)) * mul((1 - t^(p^j))^(p^(n*(r+j))*(1-1\/p^n)),j=1..k);\nend:\n\ntanabe_poincare_series := (p,n,r) -> (k) ->\n convert(series(1\/tanabe_inverse_poincare_series(p,n,r)(k),t=0,p^k+1),\n polynom,t);\n\ntanabe_trideg := (p,n,r) -> proc(x)\n local d,d0,y;\n \n if type(x,indexed) then\n if op(0,x) = b then\n return tanabe_b_trideg(p,n,r)(op(x));\n elif op(0,x) = e then\n return tanabe_e_trideg(p,n,r)(op(x));\n elif op(0,x) = bb then\n return tanabe_bb_trideg(p,n,r)(op(x));\n elif op(0,x) = ee then\n return tanabe_ee_trideg(p,n,r)(op(x));\n else\n return [0,0,0];\n fi;\n elif x = u then\n return tanabe_u_trideg(p,n,r);\n elif type(x,`+`) then\n d := map(tanabe_trideg(p,n,r),{op(x)});\n if nops(d) = 1 then\n return op(d);\n else\n return FAIL;\n fi;\n elif type(x,`*`) then\n d := [0,0,0];\n for y in [op(x)] do\n d0 := tanabe_trideg(p,n,r)(y);\n if d0 = FAIL then return FAIL; fi;\n d := d +~ d0;\n od;\n return d;\n elif type(x,`^`) then\n return tanabe_trideg(p,n,r)(op(1,x)) *~ op(2,x);\n else\n return [0,0,0];\n fi;\nend:\n\n######################################################################\n\n# Check v_p(q ^ j - 1) = r + v_p(j) \ncheck_lem_vp := (p) -> proc(q::posint,j::posint)\n local r;\n r := padic_val(q - 1,p);\n _ASSERT(r > 0, \"r > 0\");\n\n _ASSERT(padic_val(q ^ j - 1,p) = r + padic_val(j,p),\n sprintf(\"v_{%d}(%d ^ %d - 1)\",p,q,j));\nend;\n\ncheck_tanabe_numbers := proc()\n local n,r,k,p,L,N,N_bar,N_star,N_lim,P,err;\n\n assume(n::posint);\n assume(r::posint);\n assume(k::posint);\n assume(p::posint);\n\n N := tanabe_N(p,n,r);\n N_bar := tanabe_N_bar(p,n,r);\n N_star := tanabe_N_star(p,n,r);\n N_lim := tanabe_N_lim(p,n,r);\n \n _ASSERT(\n simplify(N_bar(k) - N_bar(k-1) - N(k)) = 0,\n \"N_bar(k) - N_bar(k-1) = N(k)\"\n );\n\n _ASSERT(\n simplify(N_star(k) - (N_bar(k) - p^(n*k + n*r - k))) = 0,\n \"N_star(k) = N_bar(k) - p^(n*k + n*r - k)\"\n );\n\n _ASSERT(\n simplify(p^k * (N_bar(k) - N_star(k)) - p^(n * (k + r))) = 0,\n \"p^k * (N_bar(k) - N_star(k)) = p^(n * (k + r))\"\n );\n \n _ASSERT(\n simplify(p^(k + 1) * (N_bar(k) - N_star(k + 1)) - p^(n * (k + r))) = 0,\n \"p^(k + 1) * (N_bar(k) - N_star(k + 1)) = p^(n * (k + r))\"\n );\n \n _ASSERT(\n simplify(N(0) + sum(p^j * N(j),j=1..k) - p^(n*(r+k))) = 0,\n \"sum(p^j * N(j),j=0..k) = p^(n*(r+k))\"\n );\n\n _ASSERT(\n simplify((1 - p^(-k)) * N(0) +\n sum(expand((1 - p^(j - k)) * N(j)),j=1..k) - N_star(k)) = 0,\n \"sum((1 - p^(j-k)) * N(j),j=0..k) = N_star(k)\"\n );\n\n _ASSERT(\n simplify(p^(k + 1) * N_star(k + 1) - p^k * N_star(k) - (p - 1) * p^k * N_bar(k)) = 0,\n \"p^(k + 1) * N_star(k + 1) = p^k * N_star(k) + (p - 1) * p^k * N_bar(k)\"\n );\n\n _ASSERT(\n simplify(factor(N_bar(k) - (N_star(k)*(p^n-1)\/(p-1) + p^(n*r)))) = 0,\n \"N_bar(k) = N_star(k)*(p^n-1)\/(p-1) + p^(n*r)\"\n );\n\n _ASSERT(\n simplify(sum(p^j*(p-1)*N_bar(j),j=0..k-1) - p^k*N_bar(k) + p^(n*(r+k))) = 0,\n \"sum(p^j*(p-1)*N_bar(j),j=0..k-1)\"\n );\n \n _ASSERT(\n limit(simplify(N_bar(k)\/N_lim(k)-1),k=infinity) = 0,\n \"N_bar(k) is asymptotic to N_lim(k)\"\n );\nend:\n\n\ncheck_factorial_congruences := proc() \n local p,i;\n p := ithprime(20);\n\n _ASSERT(\n {seq(modp((-1)^i * (i - 1)! * (p - i)!,p),i=1..p-1)} = {1},\n \"(-1)^i * (i - 1)! * (p - i)! = 1 mod p\"\n );\n\n _ASSERT(\n {seq(mods((-1)^i * binomial(p-1,i-1),p),i=1..p-1)} = {-1},\n \"(-1)^i * binomial(p-1,i-1) = -1 mod p\"\n );\nend:\n\n\ncheck_valuations := proc()\n local q0,v0,q,p,r,d,m;\n q0 := 19;\n v0 := 1;\n q := q0 ^ v0;\n p := 3;\n r := padic_val(q - 1, p);\n d := 20;\n \n _ASSERT(\n padic_val(tanabe_G_order(q)(d),p) - (d * r + (d - digit_sum(d,p))\/(p - 1)) = 0,\n \"valuation of |G(d)|\"\n );\n\n m := tanabe_G_order(q)(d) \/ tanabe_N_order(q)(d):\n _ASSERT(type(m,posint) and padic_val(m,p) = 0,\n \"N(d) has p' index in G(d)\"\n );\n\n m := tanabe_G_order(q)(d) \/ tanabe_H_order(q,p)(d):\n _ASSERT(type(m,posint) and padic_val(m,p) = 0,\n \"H(d) has p' index in G(d)\"\n );\n\nend:\n\ncheck_diff_trideg := proc()\n local p,n,r,k,m,i,err,d0,d1,d2;\n\n d0 := tanabe_bb_trideg(p,n,r)(k,i);\n d1 := tanabe_AHSS_d_trideg(p,n,r)(k);\n d2 := tanabe_trideg(p,n,r)(tanabe_dbb0(p,n,r)(k)(m,i));\n\n err := simplify(d0 + d1 - d2, symbolic);\n\n _ASSERT(err = [0,0,0], \"differential respects tridegrees\");\nend:\n","avg_line_length":26.7605263158,"max_line_length":87,"alphanum_fraction":0.5513816501} +{"size":13795,"ext":"mpl","lang":"Maple","max_stars_count":63.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n <\/external-templates>\n \n c0080a47-7e37-4558-bee9-9ae18e690549(jetbrains.mps.lang.extension)<\/dependency>\n ceab5195-25ea-4f22-9b92-103b95ca8c0c(jetbrains.mps.lang.core)<\/dependency>\n efc9f360-4711-4223-b9a5-469bba1c960d(de.itemis.mps.modelmerger.runtime)<\/dependency>\n 7866978e-a0f0-4cc7-81bc-4d213d9375e1(jetbrains.mps.lang.smodel)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n \n \n \n \n \n <\/external-mapping>\n <\/greater-priority-mapping>\n \n \n \n \n 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<\/mapping-priority-rule>\n \n \n \n \n \n <\/external-mapping>\n <\/greater-priority-mapping>\n \n \n \n \n <\/external-mapping>\n <\/lesser-priority-mapping>\n <\/mapping-priority-rule>\n \n \n \n \n \n <\/external-mapping>\n <\/greater-priority-mapping>\n \n \n \n \n <\/external-mapping>\n <\/lesser-priority-mapping>\n <\/mapping-priority-rule>\n <\/mapping-priorities>\n <\/generator>\n <\/generators>\n \n \n 3f233e7f-b8a6-46d2-a57f-795d56775243(Annotations)<\/dependency>\n da8e6b62-7ca3-4489-86bc-b70a501ca28f(de.q60.mps.incremental)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n fd392034-7849-419d-9071-12563d152375(jetbrains.mps.baseLanguage.closures)<\/dependency>\n 95085166-3236-4dd7-bd8e-e753c8d20885(de.q60.mps.incremental.runtime)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 95085166-3236-4dd7-bd8e-e753c8d20885(de.q60.mps.incremental.runtime)<\/dependency>\n <\/runtime>\n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":75.4790419162,"max_line_length":141,"alphanum_fraction":0.7187623959} +{"size":8371,"ext":"mpl","lang":"Maple","max_stars_count":1.0,"content":"\n\n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 1144260c-e9a5-49a2-9add-39a1a1a7077e(de.itemis.mps.editor.diagram.runtime)<\/dependency>\n f7ad14aa-a3e2-4301-8822-d919845c8bcf(de.itemis.mps.editor.diagram.shapes)<\/dependency>\n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":80.4903846154,"max_line_length":142,"alphanum_fraction":0.7395771115} +{"size":3397,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n# MG10HL\n\n# Autor\n# Abderahman Bejaoui\n# Studienarbeit bei: Moritz Schappler, moritz.schappler@imes.uni-hannover.de, 2018-08\n# (C) Institut fuer mechatronische Systeme, Leibniz Universitaet Hannover\n# Quellen\n# TODO\n# \n# Initialisierung\n# Import \nrestart:\nkin_constraints_exist := true: # F\u00fcr Speicherung\n;\nwith(StringTools): # F\u00fcr Zeitausgabe\nwith(LinearAlgebra):\nwith(codegen):\nwith(CodeGeneration):\n#with(ListTools):\ncodegen_act := true:\ncodegen_opt := 1: # Geringerer Optimierungsgrad. Sonst zu lange.\ncodegen_debug := 0: # Zur Code-Generierung auch f\u00fcr Nicht-Inert-Ausdr\u00fccke\n;\nread \"..\/helper\/proc_MatlabExport\":\nread \"..\/transformation\/proc_rotx\":\nread \"..\/transformation\/proc_roty\":\nread \"..\/transformation\/proc_rotz\":\nread \"..\/helper\/proc_convert_s_t\":\nread \"..\/helper\/proc_convert_t_s\":\nread \"..\/robot_codegen_constraints\/proc_subs_kintmp_exp\":\nwith(RealDomain): # Schr\u00e4nkt alle Funktionen auf den reellen Bereich ein. Muss nach Definition von MatlabExport kommen. Sonst geht dieses nicht.\n;\nread \"..\/robot_codegen_definitions\/robot_env\":\nread sprintf(\"..\/codeexport\/%s\/tmp\/tree_floatb_definitions\",robot_name):\n# Variable mit Winkeln der Nebenstruktur nur in Abh\u00e4ngigkeit der verallgemeinerten Koordinaten\n\n# Ergebnisse von Trigonometrischer Elimination lesen\nread sprintf(\"..\/codeexport\/mg10hlTE\/tmp\/kinematic_constraints_maple_inert.m\"):\nkin_constraints_exist := kin_constraints_exist:\nkintmp_qs := kintmp_qs:\nkintmp_qt := kintmp_qt:\nkintmp_subsexp := kintmp_subsexp:\n# Variable entfernen\nkintmp_subsexp:= Matrix(2*RowDimension(kintmp_s),2):\n# Export\nkintmp_qt := convert_s_t(kintmp_qs):\nsave kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_kintmp_subsexp_maple\", robot_name):\nsave kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_kintmp_subsexp_maple.m\", robot_name):\n#printf(\"Ausdr\u00fccke f\u00fcr kintmp_subsexp gespeichert (Maple). %s. CPU-Zeit bis hier: %1.2fs.\\n\", FormatTime(\"%Y-%m-%d %H:%M:%S\"), time()-st):\nfor i from 1 to RowDimension(kintmp_s) do\n tmp := kintmp_qs(i):\n save tmp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert_kintmpq_%d\",robot_name, i):\n save tmp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert_kintmpq_%d.m\", robot_name, i):\nend do:\nsave kin_constraints_exist, kintmp_qs, kintmp_qt,kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert\" ,robot_name):\nsave kin_constraints_exist, kintmp_qs, kintmp_qt, kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert.m\", robot_name):\nsave kintmp_qs, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_kintmp_qs_maple_inert\", robot_name):\n#printf(\"Ausdr\u00fccke mit Inert-Arctan exportiert (Matlab). %s. CPU-Zeit bis hier: %1.2fs.\\n\", FormatTime(\"%Y-%m-%d %H:%M:%S\"), time()-st):\n# Liste mit abh\u00e4ngigen konstanten Kinematikparametern erstellen (wichtig f\u00fcr Matlab-Funktionsgenerierung)\nread \"..\/helper\/proc_list_constant_expressions\";\nkc_symbols := Matrix(list_constant_expressions( kintmp_qs ));\n#kc_symbols :=Transpose(kc_symbols);\nsave kc_symbols, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_symbols_list_maple\", robot_name):\nMatlabExport(kc_symbols, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_symbols_list_matlab.m\",robot_name),2);\n#printf(\"Fertig. %s. CPU-Zeit bis hier: %1.2fs.\\n\", FormatTime(\"%Y-%m-%d %H:%M:%S\"), time()-st):\nkintmp_qs(1,1);\nkc_symbols(1,1);\nkintmp_qs(2,1);\n\n","avg_line_length":47.8450704225,"max_line_length":146,"alphanum_fraction":0.7801000883} +{"size":830,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: mgga_exc *)\n\nparams_a_mu := MU_GE:\nparams_a_b := 0.4:\nparams_a_c := 2.14951:\nparams_a_e := 1.987:\n\nvt84_gamma := 0.000023:\ntpss_ff := z -> 3:\ntpss_kappa := (x, t) ->\n 1\/(vt84_gamma\/params_a_mu^2 + vt84_gamma\/params_a_mu + 1):\n\n$include \"tpss_x.mpl\"\n\n(* Equation (8) *)\n\nvt84_f := (x, u, t) -> 1\n + tpss_fx(x, t)*exp(-vt84_gamma*tpss_fx(x, t)\/params_a_mu)\/(1 + tpss_fx(x, t))\n + (1 - exp(-vt84_gamma*tpss_fx(x, t)^2\/params_a_mu^2))*(params_a_mu\/tpss_fx(x, t) - 1):\n\nf := (rs, z, xt, xs0, xs1, u0, u1, t0, t1) -> mgga_exchange(vt84_f, rs, z, xs0, xs1, u0, u1, t0, t1):\n","avg_line_length":27.6666666667,"max_line_length":101,"alphanum_fraction":0.6289156627} +{"size":817,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_mgga_x *)\n\nn_mbeef := 5:\ncoefs_mbeef := [\n [ 1.17114923e+00, 1.15594371e-01, -5.32167416e-02, -2.01131648e-02, 1.41417107e-03],\n [-6.76157938e-02, 4.53837246e-02, -2.22650139e-02, 1.92374554e-02, 9.19317034e-07],\n [ 1.48659502e-02, 3.18024096e-02, -5.21818079e-03, 1.33707403e-07, -5.00749348e-07],\n [ 1.40794142e-03, -6.08338264e-03, -6.57949254e-07, -5.49909413e-08, 5.74317889e-08],\n [ 1.41530486e-04, -1.00478906e-07, 2.01895739e-07, 3.97324768e-09, -3.40722258e-09]\n]:\n\n$include \"mbeef.mpl\"\n\nf := (rs, x, t, u) ->\n mgga_mbeef(x, t):\n","avg_line_length":34.0416666667,"max_line_length":90,"alphanum_fraction":0.6560587515} +{"size":456,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: gga_exc *)\n\n# Note that the files have to be included in this specific order\n$define gga_x_pbe_params\n$include \"gga_x_pbe.mpl\"\n\n$include \"op.mpl\"\n\nop_qab := 2.3789:\nop_enhancement := xs -> pbe_f(xs):\n","avg_line_length":24.0,"max_line_length":68,"alphanum_fraction":0.6973684211} +{"size":4236,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/stubModelEntries>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":74.3157894737,"max_line_length":126,"alphanum_fraction":0.7438621341} +{"size":1109,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: gga_exc *)\n(* prefix:\n gga_c_sogga11_params *params;\n\n assert(p->params != NULL);\n params = (gga_c_sogga11_params * )(p->params);\n*)\n\n$define lda_c_pw_params\n$define lda_c_pw_modified_params\n$include \"lda_c_pw.mpl\"\n\nmbeta := 15.75592*0.004235: (* the usual value of 0.066726 *)\nmalpha := mbeta\/(16*2^(2\/3)):\n\nsogga11_yy := (rs, z, xt) -> -malpha*mphi(z)*xt^2\/(rs*f_pw(rs, z)):\n\nsogga11_f0 := (rs, z, xt) -> 1 - 1\/(1 + sogga11_yy(rs, z, xt)):\nsogga11_f1 := (rs, z, xt) -> 1 - exp(-sogga11_yy(rs, z, xt)):\n\nsogga11_t0 := (rs, z, xt) -> add(params_a_sogga11_a[i]*sogga11_f0(rs, z, xt)^(i-1), i=1..6):\nsogga11_t1 := (rs, z, xt) -> add(params_a_sogga11_b[i]*sogga11_f1(rs, z, xt)^(i-1), i=1..6):\n\nsogga11_f := (rs, z, xt, xs0, xs1) ->\n f_pw(rs, z)*(sogga11_t0(rs, z, xt) + sogga11_t1(rs, z, xt)):\n\nf := (rs, z, xt, xs0, xs1) -> sogga11_f(rs, z, xt, xs0, xs1):\n","avg_line_length":30.8055555556,"max_line_length":92,"alphanum_fraction":0.6275924256} +{"size":657,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\nop_a1 := 1.5214:\nop_a2 := 0.5764:\nop_b1 := 1.1284:\nop_b2 := 0.3183:\n\nop_beta := (rs, z, xs0, xs1) ->\n op_qab\/b88_zab(1, op_f, rs, z, xs0, xs1):\n\nf_op := (rs, z, xt, xs0, xs1) ->\n - (1 - z^2)*n_total(rs)\/4.0\n * (op_a1*op_beta(rs, z, xs0, xs1) + op_a2)\n \/ (op_beta(rs, z, xs0, xs1)^4 + op_b1*op_beta(rs, z, xs0, xs1)^3 + op_b2*op_beta(rs, z, xs0, xs1)^2):\n\nf := (rs, z, xt, xs0, xs1) ->\n f_op(rs, z, xt, xs0, xs1):\n","avg_line_length":27.375,"max_line_length":103,"alphanum_fraction":0.601217656} +{"size":9891,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 4b7c56eb-9347-4ed1-a5d9-938a850b9e1d(jetbrains.mps.baseLanguage.date)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 194d1782-2e1a-47e7-9530-40a1f8d132aa(jetbrains.mps.baseLanguage.box.runtime)<\/dependency>\n <\/runtime>\n \n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":77.2734375,"max_line_length":135,"alphanum_fraction":0.7321807704} +{"size":8102,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n<\/language>\n\n","avg_line_length":76.4339622642,"max_line_length":134,"alphanum_fraction":0.7280918292} +{"size":967,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: gga_exc *)\n(* prefix:\n gga_x_n12_params *params;\n\n assert(p->params != NULL);\n params = (gga_x_n12_params * )(p->params);\n*)\n\nn12_omega_x := 2.5:\nn12_gamma_x := 0.004:\n\nn12_rss := (rs, z) -> rs * 2^(1\/3) * opz_pow_n(z,-1\/3):\n\nn12_vx := rs -> 1\/(1 + (1\/(RS_FACTOR*n12_omega_x))*rs):\nn12_ux := x -> n12_gamma_x*x^2\/(1 + n12_gamma_x*x^2):\n\nn12_FN12 := (rs, z, x) ->\n + add(params_a_CC_0_[i+1]*n12_ux(x)^i, i=0..3)\n + add(params_a_CC_1_[i+1]*n12_ux(x)^i, i=0..3) * n12_vx(n12_rss(rs, z))\n + add(params_a_CC_2_[i+1]*n12_ux(x)^i, i=0..3) * n12_vx(n12_rss(rs, z))^2\n + add(params_a_CC_3_[i+1]*n12_ux(x)^i, i=0..3) * n12_vx(n12_rss(rs, z))^3:\n\nf := (rs, z, xt, xs0, xs1) -> gga_exchange_nsp(n12_FN12, rs, z, xs0, xs1):\n","avg_line_length":30.21875,"max_line_length":76,"alphanum_fraction":0.6235780765} +{"size":10876,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n# Berechne kinematische Zwangsbedingungen f\u00fcr den picker2Dm1 aus 2 Viergelenkketten und einer F\u00fcnfgelenkkette\n# Einleitung\n# \n# Herleitung der Kinematischen Zwangsbedingungen f\u00fcr einen 2-FG hybriden Palettier-\/Verpackungsroboter mit zwei Parallelogrammen und einer F\u00fcnfgelenkkette\n# Roboter: Triowin (Hersteller), \"TDR Series 2-Axis Parallel Robot\"\n# Link: http:\/\/en.triowin.com\/tdr-series2-axisparallelrobot-15268685491267769.html\n# \n# Die kinematischen Zwangsbedingungen werden als Ersetzungsausdruck f\u00fcr die abh\u00e4ngigen Winkel aufgestellt.\n# picker2Dm1TE -> modellierung der Zwangsbedingungen mit Ausdr\u00fccken f\u00fcr trigonometrische Elimination\n\n# Voraussetzung\n# Vier- und F\u00fcnf gelenkkette muss mit der Toolbox berechnet worden sein (Arbeitsbl\u00e4tter \"fourbar1TE_kinematic_constraints.mw\" und fivebar1TE_kinematic_constraints.mw)\n# \n# Autor\n# Abderahman Bejaoui\n# Hiwi bei: Moritz Schappler, moritz.schappler@imes.uni-hannover.de, 2019-01\n# (C) Institut fuer mechatronische Systeme, Leibniz Universitaet Hannover\n# Initialisierung\n# Import \ninterface(warnlevel=0): # Unterdr\u00fccke die folgende Warnung.\nrestart: # Gibt eine Warnung, wenn \u00fcber Terminal-Maple mit read gestartet wird.\ninterface(warnlevel=3):\nkin_constraints_exist := true: # F\u00fcr Speicherung\n;\nwith(StringTools): # F\u00fcr Zeitausgabe\nwith(LinearAlgebra):\nwith(codegen):\nwith(CodeGeneration):\ncodegen_act := true:\ncodegen_opt := 1: # Geringerer Optimierungsgrad. Sonst zu lange.\ncodegen_debug := 0: # Zur Code-Generierung auch f\u00fcr Nicht-Inert-Ausdr\u00fccke\n;\nread \"..\/helper\/proc_MatlabExport\":\nread \"..\/transformation\/proc_rotx\":\nread \"..\/transformation\/proc_roty\":\nread \"..\/transformation\/proc_rotz\":\nread \"..\/helper\/proc_convert_s_t\":\nread \"..\/helper\/proc_convert_t_s\":\nread \"..\/robot_codegen_constraints\/proc_subs_kintmp_exp\":\nwith(RealDomain): # Schr\u00e4nkt alle Funktionen auf den reellen Bereich ein. Muss nach Definition von MatlabExport kommen. Sonst geht dieses nicht.\n;\nread \"..\/robot_codegen_definitions\/robot_env\":\nread sprintf(\"..\/codeexport\/%s\/tmp\/tree_floatb_definitions\",robot_name):\n# Variable mit Winkeln der Nebenstruktur nur in Abh\u00e4ngigkeit der verallgemeinerten Koordinaten\nkintmp_qs := Matrix(RowDimension(kintmp_s),1):\n# Konstante Winkel bereits hineinschreiben \nfor i from 1 to RowDimension(kintmp_s) do\n if diff(kintmp_s(i,1), t) = 0 then\n kintmp_qs(i,1) := kintmp_s(i,1):\n end if:\nend do:\n# Variablen definieren f\u00fcr die Hilfswinkel\n# \n# Ersetzungsausdr\u00fccke definieren.\n# Speichere Sinus und Cosinus der Winkel direkt ab, da diese in den Rotationsmatrizen direkt auftreten.\n# Spalte 1: Zu suchender Ausdruck (sin oder cos eines Winkels)\n# Spalte 2: Einzusetzender Ausdruck.\n# Dadurch werden arctan-Ausdr\u00fccke in der direkten Kinematik reduziert.\nkintmp_subsexp := Matrix(2*RowDimension(kintmp_s),2):\nfor i from 1 to RowDimension(kintmp_s) do\n kintmp_subsexp(2*i-1, 1) := sin(kintmp_s(i,1)):\n kintmp_subsexp(2*i, 1) := cos(kintmp_s(i,1)):\n # Initialisierung der rechten Spalte mit gleichen Werten. Sp\u00e4ter nur Ersetzung, wenn Vorteilhaft.\n kintmp_subsexp(2*i-1, 2) := kintmp_subsexp(2*i-1, 1):\n kintmp_subsexp(2*i, 2) := kintmp_subsexp(2*i, 1):\nend do:\n\n# Sicherung der aktuellen Daten\nbackup_kintmp_qs := kintmp_qs:\nbackup_kintmp_qt := kintmp_qt:\nbackup_kintmp_subsexp := kintmp_subsexp:\n# Aufruf der Viergelenkkette\nread sprintf(\"..\/codeexport\/fourbar1TE\/tmp\/kinematic_constraints_maple_inert.m\"):\nkintmp_subsexp_fourbar:= kintmp_subsexp:\nkintmp_qs_fourbar := kintmp_qs:\nkintmp_qt_fourbar := kintmp_qt:\n# Aufrud der F\u00fcnfgelenkkette\nread sprintf(\"..\/codeexport\/fivebar1TE\/tmp\/kinematic_constraints_maple_inert.m\"):\nkintmp_subsexp_fivebar := kintmp_subsexp:\nkintmp_qs_fivebar := kintmp_qs:\nkintmp_qt_fivebar := kintmp_qt:\n# Vorherige Werte f\u00fcr dieses System wieder herstellen\nkintmp_qs := backup_kintmp_qs:\nkintmp_qt := backup_kintmp_qt:\nkintmp_subsexp := backup_kintmp_subsexp:\n# F\u00fcnfgelenkkettte A-B-C-E-D\nwinkel1:=<;;;;;>:\n\nfor i from 1 to 6 do\n\t# Daten der allgemeinen F\u00fcnfgelenkkette laden\n\twinkel1(i,2):=kintmp_subsexp_fivebar(i,2): \n\t# Kinematikparameter der FGK an die des Roboters anpassen\n winkel1(i,2) := subs({BC=L1}, winkel1(i,2)):\n winkel1(i,2) := subs({AB=e}, winkel1(i,2)):\n winkel1(i,2) := subs({CD=L3}, winkel1(i,2)):\n winkel1(i,2) := subs({ED=L4}, winkel1(i,2)):\n winkel1(i,2) := subs({AE=L3}, winkel1(i,2)):\n\t# variable qJ bezogen auf FGK durch allgemeine Variable ersetzen\n\twinkel1(i,2) := subs({sin(qJ1s)= sin_phi_s},winkel1(i,2)): \n\twinkel1(i,2) := subs({cos(qJ1s)= cos_phi_s},winkel1(i,2)):\n\twinkel1(i,2) := subs({sin(qJ2s)= sin_psi_s},winkel1(i,2)): \n\twinkel1(i,2) := subs({cos(qJ2s)= cos_psi_s},winkel1(i,2)):\t\n\t# Allgemeine Variable durch qJ bezogen auf Roboter ersetzen\n\twinkel1(i,2) := subs({sin_phi_s = cos(qJ2s)},winkel1(i,2)): \n\twinkel1(i,2) := subs({cos_phi_s = -sin(qJ2s)},winkel1(i,2)):\n\twinkel1(i,2) := subs({sin_psi_s = sin(qJ1s)},winkel1(i,2)): \n\twinkel1(i,2) := subs({cos_psi_s = cos(qJ1s)},winkel1(i,2)):\t\nend do:\n# Umrechnung aus Zwangsbedingugen f\u00fcr Winkel aus MDH-Tabelle\nsin_eta3_s:=winkel1(1,2):\ncos_eta3_s:=winkel1(2,2): \nsin_eta12_s:=winkel1(3,2): \ncos_eta12_s:=winkel1(4,2): \nsin_eta24_s:=winkel1(5,2): \ncos_eta24_s:=winkel1(6,2): \nsin_eta410_s:=sin_eta3_s:\ncos_eta410_s:=-cos_eta3_s:\n\n# Viergelenkkette B-H-L-C\nwinkel2:=<;;;;;>:\nfor i from 1 to 6 do\n\t# Daten der allgemeinen Viergelenkkette laden\n\twinkel2(i,2) := kintmp_subsexp_fourbar(i,2): \n\t# Kinematikparameter der FGK an die des Roboters anpassen\n winkel2(i,2) := subs({l1=L5}, winkel2(i,2)):\n winkel2(i,2) := subs({l2=L1}, winkel2(i,2)):\n winkel2(i,2) := subs({l3=L5}, winkel2(i,2)):\n winkel2(i,2) := subs({l4=L1}, winkel2(i,2)):\n # variable qJ bezogen auf FGK durch allgemeine Variable ersetzen\n winkel2(i,2) := subs({sin(qJ1s)= sin_phi_s},winkel2(i,2)): \n\twinkel2(i,2) := subs({cos(qJ1s)= cos_phi_s},winkel2(i,2)):\n\t# Allgemeine Variable durch qJ bezogen auf Roboter ersetzen\n\twinkel2(i,2) := subs({cos_phi_s = -cos(phi05)*cos(qJ1s)-sin(phi05)*sin(qJ1s)},winkel2(i,2)): \n\twinkel2(i,2) := subs({sin_phi_s = -cos(phi05)*sin(qJ1s)+sin(phi05)*cos(qJ1s)},winkel2(i,2)):\t\n end do:\nsin_rho18_s:=winkel2(1,2):\ncos_rho18_s:=winkel2(2,2):\nsin_rho05_s:=winkel2(3,2):\ncos_rho05_s:=winkel2(4,2):\nsin_rho811_s:=winkel2(5,2): \ncos_rho811_s:=winkel2(6,2): \n# Viergelenkkette C-G-F-P\nwinkel3:=<;;;;;>:\ncos_xi26_s:= - ( -cos(phi1)*(cos_rho18_s*cos_eta12_s+sin_rho18_s*sin_eta12_s)-sin(phi1)*(sin_eta12_s*cos_rho18_s-cos_eta12_s*sin_rho18_s)): \nsin_xi26_s:= -cos(phi1)*(sin_eta12_s*cos_rho18_s-cos_eta12_s*sin_rho18_s)+sin(phi1)*(cos_eta12_s*cos_rho18_s+sin_eta12_s*sin_rho18_s):\nfor i from 1 to 6 do\n\t# Daten der allgemeinen Viergelenkkette laden\n\twinkel3(i,2) := kintmp_subsexp_fourbar(i,2): \n\t# Kinematikparameter der FGK an die des Roboters anpassen\n winkel3(i,2) := subs({l1=L6}, winkel3(i,2)):\n winkel3(i,2) := subs({l2=L2}, winkel3(i,2)):\n winkel3(i,2) := subs({l3=L6}, winkel3(i,2)):\n winkel3(i,2) := subs({l4=L2}, winkel3(i,2)):\n # variable qJ bezogen auf FGK durch allgemeine Variable ersetzen\n winkel3(i,2) := subs({sin(qJ1s) = sin_phi_s},winkel3(i,2)): \n\twinkel3(i,2) := subs({cos(qJ1s) = cos_phi_s},winkel3(i,2)):\n\t# Allgemeine Variable durch qJ bezogen auf Roboter ersetzen\n\twinkel3(i,2) := subs({cos_phi_s = -cos(phi1)*(cos_rho18_s*cos_eta12_s+sin_rho18_s*sin_eta12_s)-sin(phi1)*(sin_eta12_s*cos_rho18_s-cos_eta12_s*sin_rho18_s)},winkel3(i,2)): \n\twinkel3(i,2) := subs({sin_phi_s = -cos(phi1)*(sin_eta12_s*cos_rho18_s-cos_eta12_s*sin_rho18_s)+sin(phi1)*(cos_eta12_s*cos_rho18_s+sin_eta12_s*sin_rho18_s)},winkel3(i,2)):\n end do:\nwinkel3(1..6,1):\nsin_xi23_s:=winkel3(1,2):\ncos_xi23_s:=winkel3(2,2):\nsin_xi612_s:=winkel3(3,2): # schon in MDH\n;\ncos_xi612_s:=winkel3(4,2): # schon in MDH\n;\nsin_xi39_s:=winkel3(5,2):\ncos_xi39_s:=winkel3(6,2):\n# Kintmp_subsexp\nkintmp_subsexp(1,2) := sin_eta12_s:\nkintmp_subsexp(2,2) := cos_eta12_s:\nkintmp_subsexp(3,2) := sin_xi23_s:\nkintmp_subsexp(4,2) := cos_xi23_s:\nkintmp_subsexp(5,2) := sin_eta24_s:\nkintmp_subsexp(6,2) := cos_eta24_s:\nkintmp_subsexp(7,2) := sin_rho05_s:\nkintmp_subsexp(8,2) := cos_rho05_s:\nkintmp_subsexp(9,2) := sin_xi26_s:\nkintmp_subsexp(10,2) := cos_xi26_s:\nkintmp_subsexp(11,2) := sin_rho18_s:\nkintmp_subsexp(12,2) := cos_rho18_s:\nkintmp_subsexp(13,2) := sin_xi39_s:\nkintmp_subsexp(14,2) := cos_xi39_s:\nkintmp_subsexp(15,2) := sin_eta410_s:\nkintmp_subsexp(16,2) := cos_eta410_s:\nkintmp_subsexp(17,2) := sin_rho811_s:\nkintmp_subsexp(18,2) := cos_rho811_s:\nkintmp_subsexp(19,2) := sin_xi612_s:\nkintmp_subsexp(20,2) := cos_xi612_s:\n# Kintmp_qs\nkintmp_qs(1,1):=%arctan(sin_eta12_s,cos_eta12_s):\nkintmp_qs(2,1):=%arctan(sin_xi23_s,cos_xi23_s):\nkintmp_qs(3,1):=%arctan(sin_eta24_s,cos_eta24_s):\nkintmp_qs(4,1):=%arctan(sin_rho05_s,cos_rho05_s):\nkintmp_qs(5,1):=%arctan(sin_xi26_s,cos_xi26_s):\nkintmp_qs(6,1):=%arctan(sin_rho18_s,cos_rho18_s):\nkintmp_qs(7,1):=%arctan(sin_xi39_s,cos_xi39_s):\nkintmp_qs(8,1):=%arctan(sin_eta410_s,cos_eta410_s):\nkintmp_qs(9,1):=%arctan(sin_rho811_s,cos_rho811_s):\nkintmp_qs(10,1):=%arctan(sin_xi612_s,cos_xi612_s):\n# Export\nkintmp_qt := convert_s_t(kintmp_qs):\nsave kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_kintmp_subsexp_maple\", robot_name):\nsave kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_kintmp_subsexp_maple.m\", robot_name):\nfor i from 1 to RowDimension(kintmp_s) do\n tmp := kintmp_qs(i):\n save tmp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert_kintmpq_%d\",robot_name, i):\n save tmp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert_kintmpq_%d.m\", robot_name, i):\nend do:\nsave kin_constraints_exist, kintmp_qs, kintmp_qt,kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert\" ,robot_name):\nsave kin_constraints_exist, kintmp_qs, kintmp_qt, kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert.m\", robot_name):\nsave kintmp_qs, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_kintmp_qs_maple_inert\", robot_name):\n# Liste mit abh\u00e4ngigen konstanten Kinematikparametern erstellen (wichtig f\u00fcr Matlab-Funktionsgenerierung)\nread \"..\/helper\/proc_list_constant_expressions\";\nkc_symbols := Matrix(list_constant_expressions( kintmp_subsexp ));\nsave kc_symbols, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_symbols_list_maple\", robot_name):\nMatlabExport(kc_symbols, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_symbols_list_matlab.m\",robot_name),2);\n\n","avg_line_length":49.2126696833,"max_line_length":172,"alphanum_fraction":0.7532180949} +{"size":8315,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n \n \n \n <\/stubModelEntries>\n \n \n 6354ebe7-c22a-4a0f-ac54-50b52ab9b065(JDK)<\/dependency>\n 1ed103c3-3aa6-49b7-9c21-6765ee11f224(MPS.Editor)<\/dependency>\n f32fddd3-9ea0-405b-9874-fdda57f5e83d(org.iets3.structuralCoder)<\/dependency>\n f3061a53-9226-4cc5-a443-f952ceaf5816(jetbrains.mps.baseLanguage)<\/dependency>\n 33eb1b5b-ad96-4262-9112-684c487e01e0(org.iets3.graphicalLustre)<\/dependency>\n 8865b7a8-5271-43d3-884c-6fd1d9cfdd34(MPS.OpenAPI)<\/dependency>\n 7731a166-da1f-472e-a40a-2283f5e47dc5(org.iets3.ears.gxw)<\/dependency>\n 2d3c70e9-aab2-4870-8d8d-6036800e4103(jetbrains.mps.kernel)<\/dependency>\n b0f8641f-bd77-4421-8425-30d9088a82f7(org.apache.commons)<\/dependency>\n <\/dependencies>\n \n 2677cb18-f558-4e33-bc38-a5139cee06dc(jetbrains.mps.devkit.language-design)<\/usedDevKit>\n fbc25dd2-5da4-483a-8b19-70928e1b62d7(jetbrains.mps.devkit.general-purpose)<\/usedDevKit>\n <\/usedDevKits>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n d4280a54-f6df-4383-aa41-d1b2bffa7eb1(com.mbeddr.core.base)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":84.8469387755,"max_line_length":155,"alphanum_fraction":0.7564642213} +{"size":1618,"ext":"mpl","lang":"Maple","max_stars_count":null,"content":"!This file is subject to the terms and conditions defined in\n!file 'LICENSE.txt', which is part of this source code package.\n\nTITLE\n \n\tCAP_extensive_form_cap124_1000;\n\nSTOCHASTIC\n\nDATA\n\t\n\tI := DATAFILE(\"cap124_1000_SETS.dat\");\n\tJ := DATAFILE(\"cap124_1000_SETS.dat\");\n\tK := DATAFILE(\"cap124_1000_SETS.dat\");\t\t\t\t! - num scenarios\n\tQ := I;\t\t\t\t\t\t\t! - num 1st stage columns\n\tT := I*J;\t\t\t\t\t\t! - num 2nd stage columns\n\tR := J+I;\t\t\t\t\t\t! - num rows in T and W\n\t\n\nSCENARIO\n \n\tk := 1..K;\n\nINDEX\n\tFirstStCol := 1..Q;\n\tSecondStCol := 1..T;\n\tRow := 1..R;\t\n\nPROBABILITIES\n \n\tp[k] := ALLEQUAL;\n\nRANDOM DATA\n\n\tVector_h[k, Row] := DATAFILE(\"cap124_1000_RANDOM.dat\");\t! - rows are related to scenarios\n\nDATA\n \n\tVector_c[FirstStCol] := DATAFILE(\"cap124_1000_DATA.dat\");\n\tVector_d[SecondStCol] := DATAFILE(\"cap124_1000_DATA.dat\");\n\tVector_b := DATAFILE(\"cap124_1000_DATA.dat\");\t\t\t! - max sum of h over all scenarios\n\tMatrix_A[FirstStCol] := DATAFILE(\"cap124_1000_DATA.dat\");\n\tMatrix_T[Row, FirstStCol] := DATAFILE(\"cap124_1000_DATA.dat\");\n\tMatrix_W[Row, SecondStCol] := DATAFILE(\"cap124_1000_DATA.dat\");\n\tx_ub[FirstStCol] := DATAFILE(\"cap124_1000_DATA.dat\");\n\nSTAGE1 BINARY VARIABLES\n\n\tx[FirstStCol];\n\nSTAGE2 VARIABLES\n\n\ty[SecondStCol];\n\nMACROS\n\n\tStageFirst = sum(FirstStCol: Vector_c * x);\n\tStageSecond = sum(SecondStCol: Vector_d * y);\n\nMIN\n\n\tObjective = StageFirst + StageSecond;\n\nSUBJECT TO\n\t\n\tFirstStCnstr: sum(FirstStCol: Matrix_A * x) >= Vector_b;\n \tSecondStCnstr[Row]: sum(FirstStCol: Matrix_T * x) + sum(SecondStCol: Matrix_W * y) >= Vector_h;\n\nBOUNDS\n\n\tBinBounds[FirstStCol]: x <= x_ub;\t! - why do we need it\n\nEND","avg_line_length":22.1643835616,"max_line_length":100,"alphanum_fraction":0.6878862794} +{"size":482,"ext":"mpl","lang":"Maple","max_stars_count":16.0,"content":"(*\n Copyright (C) 2017 M.A.L. Marques\n\n This Source Code Form is subject to the terms of the Mozilla Public\n License, v. 2.0. If a copy of the MPL was not distributed with this\n file, You can obtain one at http:\/\/mozilla.org\/MPL\/2.0\/.\n*)\n\n(* type: work_lda *)\n(* prefix:\n lda_k_tf_params *params;\n\n assert(p->params != NULL);\n params = (lda_k_tf_params * )(p->params);\n*)\n\nf_zeta_k := z -> 1\/2*((1 + z)^(5\/3) + (1 - z)^(5\/3)):\n\nf := (rs, zeta) -> params_a_ax*f_zeta_k(zeta)\/rs^2:","avg_line_length":25.3684210526,"max_line_length":68,"alphanum_fraction":0.632780083} +{"size":4022,"ext":"mpl","lang":"Maple","max_stars_count":1.0,"content":"\n# Kinematik-Berechnung 3. Arm KAS5\n# Beschreibung\n# \n# Modell m5: \n# * Kurbel N7 ist starr mit K\u00f6rper K2 gekoppelt (\u00fcber die Achse) (wie m3), \n# * Zahnradkopplung zwischen K\u00f6rpern Z2 und Z3 (Unterschied zu m3)\n# \n# Setze die Zwangsbedingung (Zahnradkopplung) in die bereits berechneten Zwangsbedingungen f\u00fcr das KAS5m3 ein\n# \n# Berechnung der Kopplung der Zahnr\u00e4der am Ellenbogen\n# Autor\n# Moritz Schappler, schappler@irt.uni-hannover.de, 2016-02\n# Institut fuer Regelungstechnik, Leibniz Universitaet Hannover\n# Initialisierung\nrestart:\nkin_constraints_exist := true: # F\u00fcr Speicherung\n;\nwith(LinearAlgebra):\nwith(StringTools):\nread \"..\/helper\/proc_convert_s_t\":\nread \"..\/helper\/proc_convert_t_s\": \nread \"..\/helper\/proc_MatlabExport\":\nread \"..\/robot_codegen_constraints\/proc_subs_kintmp_exp\":\nread \"..\/robot_codegen_definitions\/robot_env\":\nread sprintf(\"..\/codeexport\/%s\/tmp\/tree_floatb_definitions\", robot_name):\n# Lese Ergebnisse der Kinematik von KAS5m3 aus.\n# Siehe KAS5m3_sym_codegen_kinematic_constraints.mw\n# kintmp_qs, kintmp_qt, lpar_qs, lpar_qt, kintmp_subsexp\nread sprintf(\"..\/codeexport\/KAS5m3\/tmp\/kinematic_constraints_maple_inert.m\", robot_name):\nkintmp_qs_KAS5m3 := kintmp_qs:\nkintmp_qt_KAS5m3 := kintmp_qt:\nlpar_qs_KAS5m3 := lpar_qs:\nlpar_qt_KAS5m3 := lpar_qt:\nkintmp_subsexp_KAS5m3 := kintmp_subsexp:\n# Wende Zwangsbedingungen aus Zahnradkontakt an\n# Wandle die verallgemeinerten Koordinaten um. Benutze die Reihenfolge f\u00fcr KAS5m5.\n# Funktion zur Ersetzung der Gelenkwinkel (allgemein -> m3)\nsubs_q_J_m3 := proc(A)\n local A_s, j; \n A_s := A; \n for j from 1 to RowDimension(qJ_s) do\n A_s := subs({qJ_s(j,1) = qJs_KAS5m3(j,1)}, A_s):\n end do:\n return A_s:\nend proc:\nqJs_KAS5m3:=Matrix(7, 1, [qJs1_m3, qJs2_m3, qJs3_m3, qJs4_m3, qJs5_m3, qJs6_m3, qJs7_m3]):\nkintmp_subsexp_KAS5m3 := subs_q_J_m3(kintmp_subsexp_KAS5m3):\nkintmp_qs_KAS5m3 := subs_q_J_m3(kintmp_qs_KAS5m3):\nlpar_qs_KAS5m3 := subs_q_J_m3(lpar_qs_KAS5m3):\n# Funktion zur Ersetzung der verallgemeinerten Koordinaten (m3 -> m5)\nsubs_q_m3_m5 := proc(A)\n local A_s, j; \n A_s := A; \n for j from 1 to RowDimension(qJ_s) do\n A_s := subs({qJs_KAS5m3(j,1) = qJs_KAS5m3m5subs(j,1)}, A_s):\n end do:\n return A_s:\nend proc:\nqJs_KAS5m3m5subs:=Matrix(7, 1, [qJs1_m5, qJs2_m5, qJs3_m5, qJs4_m5, qJs4_m5-qJs3_m5+delta18s, qJs5_m5, 0]):\nkintmp_subsexp_KAS5m5 := subs_q_m3_m5(kintmp_subsexp_KAS5m3):\nkintmp_qs_KAS5m5 := subs_q_m3_m5(kintmp_qs_KAS5m3):\nlpar_qs_KAS5m5 := subs_q_m3_m5(lpar_qs_KAS5m3):\n# Konvertiere Ergebnisse\n# R\u00fcckersetzung der markierten Koordinaten gegen die normale Form (qJ_KAS5m5 -> qJ)\nsubs_q_m5_J := proc(A)\n local A_s, j; \n A_s := A; \n for j from 1 to RowDimension(qJs_KAS5m5) do\n A_s := subs({qJs_KAS5m5(j,1) = qJ_s(j,1)}, A_s):\n end do:\n return A_s:\nend proc:\nqJs_KAS5m5:=Matrix(5, 1, [qJs1_m5, qJs2_m5, qJs3_m5, qJs4_m5, qJs5_m5]):\nkintmp_subsexp := subs_q_m5_J(kintmp_subsexp_KAS5m5):\nkintmp_qs := subs_q_m5_J(kintmp_qs_KAS5m5):\nlpar_qs := subs_q_m5_J(lpar_qs_KAS5m5):\nkintmp_qt := convert_s_t(kintmp_qs):\nlpar_qt := convert_s_t(lpar_qs):\n# Speichern der Ergebnisse\nsave kin_constraints_exist, kintmp_qs, kintmp_qt, lpar_qs, lpar_qt, kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert\", robot_name):\nsave kin_constraints_exist, kintmp_qs, kintmp_qt, lpar_qs, lpar_qt, kintmp_subsexp, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_maple_inert.m\", robot_name):\n# Liste der Parameter speichern\n# Liste mit abh\u00e4ngigen konstanten Kinematikparametern erstellen (wichtig f\u00fcr Matlab-Funktionsgenerierung)\nread \"..\/helper\/proc_list_constant_expressions\";\nkc_symbols := Matrix(list_constant_expressions( kintmp_subsexp(..,2) )):\nsave kc_symbols, sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_symbols_list_maple\", robot_name):\nMatlabExport(Transpose(kc_symbols), sprintf(\"..\/codeexport\/%s\/tmp\/kinematic_constraints_symbols_list_matlab.m\", robot_name), 2):\nprintf(\"Zwangsbedingungen der Parallelstruktur von KAS5m3 nach KAS5m5 angepasst. %s\\n\", FormatTime(\"%Y-%m-%d %H:%M:%S\")):\n\n\n","avg_line_length":43.7173913043,"max_line_length":164,"alphanum_fraction":0.7737444058} +{"size":13459,"ext":"mpl","lang":"Maple","max_stars_count":25.0,"content":"\n\n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n <\/modelRoot>\n <\/models>\n \n \n \n <\/facet>\n <\/facets>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n <\/generator>\n <\/generators>\n \n \n 0eddeefa-c2d6-4437-bc2c-de50fd4ce470(jetbrains.mps.lang.script)<\/dependency>\n c72da2b9-7cce-4447-8389-f407dc1158b7(jetbrains.mps.lang.structure)<\/dependency>\n 65e59b42-e7f3-45ec-8692-6c7829780afe(jetbrains.mps.lang.smodelExt)<\/dependency>\n <\/dependencies>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/languageVersions>\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n <\/dependencyVersions>\n \n 0fda14cc-a416-4c81-869a-2175d8b3325d(jetbrains.mps.baseLanguageExt)<\/extendedLanguage>\n 0eddeefa-c2d6-4437-bc2c-de50fd4ce470(jetbrains.mps.lang.script)<\/extendedLanguage>\n <\/extendedLanguages>\n<\/language>\n\n","avg_line_length":85.1835443038,"max_line_length":133,"alphanum_fraction":0.7391336652}