Tue Oct 19 17:00:18 2021 pdflib_test(): Python version: 3.6.9 Test pdflib(). initialize(): rnglib() has been initialized. i4_uni_test Python version: 3.6.9 i4_uni returns a random positive integer. 695163044 696626468 1059541850 620042603 758075822 330628445 1215929140 1762482382 698994348 730315574 1922376880 722841757 612082173 1081002351 1661144525 45434058 79485022 624052430 184849954 1605430415 i4_uni_test: Normal end of execution. r8_uni_01_test Python version: 3.6.9 r8_uni_01 produces a sequence of random values. r8_uni_01() 0.359446 0.208128 0.0797663 0.147932 0.708155 0.395446 0.76442 0.645941 0.473061 0.859549 r8_uni_01_test Normal end of execution. r8ge_print_test Python version: 3.6.9 r8ge_print prints an R8GE matrix. Here is an R8MAT: Col: 0 1 2 3 4 Row 0 : 11 12 13 14 15 1 : 21 22 23 24 25 2 : 31 32 33 34 35 3 : 41 42 43 44 45 Col: 5 Row 0 : 16 1 : 26 2 : 36 3 : 46 r8ge_print_test: Normal end of execution. r8ge_print_some_test Python version: 3.6.9 r8ge_print_some prints some of an R8GE matrix. Here is an R8GE matrix: Col: 3 4 5 Row 0 : 14 15 16 1 : 24 25 26 2 : 34 35 36 r8ge_print_some_test: Normal end of execution. r8mat_norm_fro_affine_test Python version: 3.6.9 r8mat_norm_fro_affine computes the Frobenius norm of the difference of two R8MAT's; Expected norm = 1.74153 Computed norm = 1.74153 r8mat_norm_fro_affine_test Normal end of execution. r8po_mv_test Python version: 3.6.9 r8po_mv computes the product of an R8PO matrix and a vector. Matrix order N = 5 Matrix A: Col: 0 1 2 3 4 Row 0 : 2 -1 0 0 0 1 : -1 2 -1 0 0 2 : 0 -1 2 -1 0 3 : 0 0 -1 2 -1 4 : 0 0 0 -1 2 Vector V: 0: 1 1: 2 2: 3 3: 4 4: 5 Product w = A * v: 0: 0 1: 0 2: 0 3: 0 4: 6 r8po_mv_test Normal end of execution. r8ut_sl_test Python version: 3.6.9 r8ut_sl solves a linear system A*x=b with R8UT matrix Matrix order N = 5 The upper triangular matrix: Col: 0 1 2 3 4 Row 0 : 1 2 3 4 5 1 : 2 3 4 5 2 : 3 4 5 3 : 4 5 4 : 5 Right hand side b: 0: 55 1: 54 2: 50 3: 41 4: 25 Solution: 0: 1 1: 2 2: 3 3: 4 4: 5 r8ut_sl_test Normal end of execution. r8vec_indicator1_test Python version: 3.6.9 r8vec_indicator1 returns the 1-based indicator matrix. The 1-based indicator vector: 0: 1 1: 2 2: 3 3: 4 4: 5 5: 6 6: 7 7: 8 8: 9 9: 10 r8vec_indicator1_test Normal end of execution. r8vec_print_test Python version: 3.6.9 Test r8vec_print(), which prints an R8VEC. Use r8vec_print(): 0: 123.456 1: 5e-06 2: -1e+06 3: 3.14159 Use python print(): [ 1.23456000e+02 5.00000000e-06 -1.00000000e+06 3.14159265e+00] r8vec_print_test: Normal end of execution. i4_binomial_pdf_test: Python version: 3.6.9 i4_binomial_pdf evaluates the binomial pdf pdf(n,p,k) = probability, in n trials, of k successes, if a single success has probability p. N P K PDF(N,P,K) PDF(N,P,K) tabulated computed 5 0.829509 5 0.392741 0.392741 12 0.0661187 5 0.000619997 0.000619997 6 0.043829 0 0.764211 0.764211 13 0.449539 0 0.000426035 0.000426035 9 0.797287 7 0.302948 0.302948 1 0.350752 1 0.350752 0.350752 2 0.859097 0 0.0198537 0.0198537 17 0.00751236 2 0.00685439 0.00685439 6 0.113664 6 2.15645e-06 2.15645e-06 8 0.267132 7 0.000569115 0.000569115 i4_binomial_pdf_test: Normal end of execution. i4_binomial_sample_test i4_binomial_sample samples the binomial distribution. N P K PDF(N,P,K) 2 0.986168 2 0.972527 6 0.0967662 1 0.349041 20 0.747479 13 0.115421 12 0.35245 5 0.205649 10 0.739475 9 0.17225 5 0.410096 2 0.345235 18 0.90318 16 0.281197 20 0.863734 20 0.0534077 17 0.0343224 1 0.333688 9 0.625295 7 0.188919 i4_binomial_sample_test: Normal end of execution. initialize(): rnglib() has been initialized. i4_uniform_sample_test Python version: 3.6.9 i4_uniform_sample csamples the uniform distribution on integers. Generate C between A and B. A B C -8 3 -1 0 3 3 6 14 8 3 20 6 0 4 3 -7 6 3 10 15 12 6 9 8 -6 -4 -4 -1 6 2 i4_uniform_sample_test: Normal end of execution. i4vec_multinomial_pdf_test: Python version: 3.6.9 i4vec_multinomial_pdf evaluates the multinomial PDF. Given M possible outcomes on a single trial, with each outcome having probability P, PDF is the probability that after N trials, outcome I occurred X(I) times. N M I P X PDF() PDF() tabulated computed 0 0.7000 2 1 0.3000 1 3 2 0.441 0.441 0 0.7000 2 1 0.3000 2 4 2 0.2646 0.2646 0 0.5000 2 1 0.5000 1 3 2 0.375 0.375 0 0.6000 1 1 0.0000 1 2 0.4000 1 3 3 0 0 0 0.6000 3 1 0.1000 0 2 0.1000 0 3 0.1000 0 4 0.1000 0 3 5 0.216 0.216 0 0.6000 2 1 0.1000 1 2 0.1000 0 3 0.1000 0 4 0.1000 0 3 5 0.108 0.108 0 0.6000 1 1 0.1000 0 2 0.1000 2 3 0.1000 0 4 0.1000 0 3 5 0.018 0.018 0 0.6000 1 1 0.1000 0 2 0.1000 0 3 0.1000 1 4 0.1000 1 3 5 0.036 0.036 0 0.6000 0 1 0.1000 0 2 0.1000 0 3 0.1000 3 4 0.1000 0 3 5 0.001 0.001 0 0.6000 0 1 0.1000 1 2 0.1000 1 3 0.1000 1 4 0.1000 0 3 5 0.006 0.006 i4vec_multinomial_pdf_test: Normal end of execution. i4vec_multinomial_sample_test Python version: 3.6.9 i4vec_multinomial_sample samples the multinomial distribution. N M I P X PDF() 0 0.7596 0 1 0.2376 2 2 0.0028 0 2 3 0.0564558 0 0.0954 0 1 0.3091 0 2 0.0414 0 3 0.2231 0 4 0.3310 4 4 5 0.0120004 0 0.0365 0 1 0.0651 0 2 0.2204 2 3 0.0762 2 4 0.1981 0 5 0.1983 0 6 0.0153 0 7 0.1902 1 5 8 0.00160849 0 0.4232 2 1 0.5768 3 5 2 0.343689 0 0.0537 0 1 0.0780 0 2 0.0186 0 3 0.2036 0 4 0.2310 1 5 0.1408 0 6 0.1249 1 7 0.0130 0 8 0.1364 0 2 9 0.0577094 0 0.0168 0 1 0.1530 0 2 0.2340 1 3 0.1351 0 4 0.0947 0 5 0.0339 2 6 0.0548 0 7 0.0949 0 8 0.1827 0 3 9 0.000804467 0 0.0727 0 1 0.1696 1 2 0.1372 2 3 0.0236 0 4 0.1234 0 5 0.1954 0 6 0.0310 0 7 0.1955 1 8 0.0301 0 9 0.0214 0 4 10 0.00748943 0 0.0772 0 1 0.0653 0 2 0.0363 0 3 0.2008 1 4 0.1031 0 5 0.2151 2 6 0.1196 0 7 0.1824 0 3 8 0.0278807 0 0.0439 0 1 0.0891 0 2 0.0240 0 3 0.1659 1 4 0.1815 1 5 0.1372 1 6 0.0669 1 7 0.1672 1 8 0.1169 0 9 0.0074 0 5 10 0.00554543 0 0.0553 1 1 0.9447 2 3 2 0.148114 i4vec_multinomial_sample_test: Normal end of execution. r8_beta_pdf_test: Python version: 3.6.9 r8_beta_pdf evaluates the BETA PDF. ALPHA BETA X PDF() PDF() tabulated computed 1.09209 4.78159 0.866722 0.00282614 0.00282614 2.80848 2.07654 0.0460776 0.0420895 0.0420895 1.28789 0.549784 0.0221162 0.218406 0.218406 3.16983 0.308636 0.458254 0.133514 0.133514 2.00653 3.77337 0.832083 0.107057 0.107057 0.00919186 4.48752 0.352059 0.00579639 0.00579639 0.472724 0.0680845 0.898529 0.55188 0.55188 4.20424 0.61552 -0.0169242 0 0 1.30151 4.56242 0.0971888 2.87907 2.87907 1.75814 4.11444 0.262167 2.12699 2.12699 r8_beta_pdf_test: Normal end of execution. r8_beta_sample_test Python version: 3.6.9 r8_beta_sample samples the beta distribution. ALPHA BETA X PDF() 2.69262 0.338959 0.791407 0.966273 4.92029 3.61187 0.560177 2.25676 3.45352 0.649648 0.986352 6.80395 4.08923 1.87589 0.396215 0.649585 4.85461 1.45871 0.800053 2.44138 3.43292 4.28409 0.553732 1.79482 0.745189 3.92535 0.0023017 10.2558 2.16184 4.82321 0.590752 0.626282 2.27809 1.74757 0.267423 0.860344 2.129 0.466671 0.73661 1.02034 r8_beta_sample_test: Normal end of execution. r8_chi_pdf_test: Python version: 3.6.9 r8_chi_pdf evaluates the standard chi PDF. DF X PDF() PDF() tabulated computed 1 0.01 3.96953 3.96953 2 0.01 0.497506 0.497506 1 0.02 2.79288 2.79288 2 0.02 0.495025 0.495025 1 0.4 0.516442 0.516442 2 0.4 0.409365 0.409365 3 0.4 0.206577 0.206577 4 0.4 0.0818731 0.0818731 1 1 0.241971 0.241971 2 1 0.303265 0.303265 3 1 0.241971 0.241971 4 1 0.151633 0.151633 5 1 0.0806569 0.0806569 3 2 0.207554 0.207554 3 3 0.15418 0.15418 3 4 0.107982 0.107982 3 5 0.0732249 0.0732249 3 6 0.0486522 0.0486522 10 1 0.000789753 0.000789753 10 2 0.00766416 0.00766416 10 3 0.0235333 0.0235333 r8_chi_pdf_test Normal end of execution. r8_chi_sample_test Python version: 3.6.9 r8_chi_sample samples the CHI distribution: DF R PDF 17.1191 16.3446 0.070083 18.1075 17.1481 0.0684526 6.8898 5.70024 0.11964 15.5469 18.1775 0.0547705 2.75862 0.861867 0.265733 19.2465 8.10034 0.00963328 8.0102 10.8851 0.0582814 8.2658 5.39309 0.106127 4.88794 1.73636 0.133787 10.0327 15.3952 0.0334924 r8_chi_sample_test Normal end of execution r8_exponential_01_pdf_test: Python version: 3.6.9 r8_exponential_01_pdf evaluates the standard exponential pdf. X PDF() PDF() tabulated computed 0.701301 0.49594 0.49594 4.75975 0.00856778 0.00856778 4.0623 0.0172094 0.0172094 2.58932 0.0750707 0.0750707 1.78419 0.167933 0.167933 -0.136347 0 0 0.916678 0.399845 0.399845 0.104762 0.900538 0.900538 -0.258941 0 0 2.98681 0.050448 0.050448 r8_exponential_01_pdf_test: Normal end of execution. r8_exponential_01_sample_test Python version: 3.6.9 r8_exponential_01_sample samples the standard exponential PDF: R PDF(R) 1.47535 0.228699 0.540098 0.582691 0.352507 0.702924 1.62949 0.19603 1.92724 0.145549 0.583439 0.557976 0.123983 0.883395 0.21332 0.807898 0.561141 0.570558 1.03851 0.353983 r8_exponential_01_sample_test Normal end of execution r8_exponential_pdf_test: Python version: 3.6.9 r8_exponential_pdf evaluates the exponential PDF. BETA X PDF() PDF() tabulated computed 1.09209 9.55881 0.0001447 0.0001447 4.14755 5.57312 0.0628985 0.0628985 2.07654 0.567799 0.366361 0.366361 1.28789 1.01056 0.354279 0.354279 0.219145 6.30305 1.47258e-12 1.47258e-12 0.308636 4.44034 1.82964e-06 1.82964e-06 2.00653 7.5222 0.011734 0.011734 3.98643 -0.0814325 0 0 4.48752 3.4426 0.103472 0.103472 0.472724 0.0375306 1.95395 1.95395 r8_exponential_pdf_test: Normal end of execution. r8_exponential_sample_test Python version: 3.6.9 r8_exponential_sample samples the general exponential PDF: BETA R PDF 0.539909 0.705762 0.501159 9.67969 8.9475 0.0409916 1.00021 0.786235 0.455537 5.41911 3.84681 0.0907368 7.7402 4.35183 0.0736328 6.79068 9.51736 0.0362584 4.51826 0.141394 0.214505 6.02019 18.5501 0.00762421 1.94727 0.921284 0.319965 2.9864 10.8714 0.00878792 r8_exponential_sample_test Normal end of execution r8_gamma_01_pdf_test: Python version: 3.6.9 r8_gamma_01_pdf evaluates the standard gamma PDF. ALPHA X PDF(0,1) PDF(0,1) tabulated computed 1.09209 9.54133 9.26081e-05 9.26081e-05 4.14755 5.3978 0.126034 0.126034 2.07654 0.194247 0.136354 0.136354 1.28789 0.654546 0.511445 0.511445 0.219145 6.15664 0.000123014 0.000123014 0.308636 4.22016 0.00187034 0.00187034 2.00653 7.42407 0.004476 0.004476 3.98643 -0.480697 0 0 4.48752 3.1829 0.205667 0.205667 0.472724 -0.357023 0 0 r8_gamma_01_pdf_test Normal end of execution. r8_gamma_01_sample_test Python version: 3.6.9 r8_gamma_01_sample samples the standard gamma distribution. A X PDF() 2.09868 5.54147 0.0245992 4.07832 5.0992 0.138711 1.86087 0.32065 0.287244 4.15521 1.17745 0.0705007 1.9979 1.64843 0.317027 4.40282 3.43622 0.211015 1.92239 3.47494 0.100742 2.8158 5.54418 0.0516014 2.12341 4.97103 0.0396977 4.0698 7.36612 0.0443257 r8_gamma_01_sample_test: Normal end of execution. r8_gamma_pdf_test: Python version: 3.6.9 r8_gamma_pdf evaluates a gamma PDF. BETA ALPHA X PDF PDF tabulated computed 1.09209 4.78159 4.94296 0.167202 0.167202 2.80848 2.07654 0.209936 0.852212 0.852212 1.28789 0.549784 0.0717398 2.12227 2.12227 3.16983 0.308636 2.58714 6.99377e-05 6.99377e-05 2.00653 3.77337 4.74318 0.0167938 0.0167938 0.00919186 4.48752 1.97466 6.68746e-10 6.68746e-10 0.472724 0.0680845 5.1264 0.00129544 0.00129544 4.20424 0.61552 -0.153423 0 0 1.30151 4.56242 0.504717 0.0118989 0.0118989 1.75814 4.11444 1.45622 0.365884 0.365884 r8_gamma_pdf_test Normal end of execution. r8_gamma_sample_test Python version: 3.6.9 r8_gamma_sample samples a gamma distribution. R A X PDF() 3.71211 2.80972 0.530251 1.04487 0.973602 3.17725 1.27999 0.190802 2.26177 3.89028 2.77839 0.163457 0.514526 2.17205 4.1444 0.136513 3.2291 2.76424 0.357672 0.806126 3.36627 4.95425 2.1455 0.272626 3.43966 2.7479 0.560054 0.981663 4.55045 0.465683 0.241115 0.760116 0.6707 4.23199 3.82388 0.133887 2.53102 1.09988 0.0201507 1.87799 r8_gamma_sample_test: Normal end of execution. r8_invchi_pdf_test: Python version: 3.6.9 r8_invchi_pdf returns values of the inverse Chi Square Probability Density Function. DF X PDF PDF 1 0.1 0.08500366602520341 0.08500366602520341 2 0.1 0.3368973499542734 0.3368973499542732 1 0.2 0.3661245640481622 0.3661245640481621 2 0.2 1.026062482798735 1.026062482798735 1 0.4 0.4518059816704532 0.4518059816704532 2 0.4 0.8953274901880941 0.8953274901880941 3 0.4 1.129514954176133 1.129514954176133 4 0.4 1.119159362735118 1.119159362735117 1 1 0.2419707245191433 0.2419707245191434 2 1 0.3032653298563167 0.3032653298563167 3 1 0.2419707245191433 0.2419707245191434 4 1 0.1516326649281584 0.1516326649281584 5 1 0.08065690817304778 0.08065690817304777 3 2 0.0549239111834653 0.05492391118346532 3 3 0.02166329508030457 0.02166329508030457 3 4 0.01100204146138436 0.01100204146138436 3 5 0.006457369034861447 0.006457369034861448 3 6 0.004162370481945731 0.004162370481945732 10 1 0.0007897534631674914 0.0007897534631674914 10 2 1.584474249412852e-05 1.584474249412853e-05 10 3 1.511920090468204e-06 1.511920090468204e-06 r8_invchi_pdf_test: Normal end of execution. r8_invchi_sample_test Python version: 3.6.9 r8_invchi_sample samples an inverse chi square distribution. DF X PDF() 1.71746 5.06218 0.0221994 4.26297 0.250931 2.22219 3.9882 0.571909 0.559362 0.226414 5496.72 7.59069e-06 2.84164 0.60779 0.617899 3.23385 0.320324 1.50353 1.54266 0.251898 0.772532 0.165392 4.84057 0.0133222 0.637052 46.0449 0.00181072 0.764953 141.482 0.000349984 r8_invchi_sample_test: Normal end of execution. r8_invgam_pdf_test: Python version: 3.6.9 r8_invgam_pdf evaluates the inverse gamma Probability Density Function. ALPHA BETA X PDF PDF 1 0.5 1 0.3032653298563167 0.3032653298563167 1 0.5 2 0.09735009788392561 0.09735009788392562 1 0.5 3 0.047026762493923 0.047026762493923 1 0.5 4 0.02757802820576861 0.02757802820576861 1 2 2 0.1839397205857212 0.1839397205857211 1 3 2 0.1673476201113224 0.1673476201113224 1 4 2 0.1353352832366127 0.1353352832366127 1 5 2 0.1026062482798735 0.1026062482798735 2 2 3 0.07606179541223586 0.07606179541223584 3 2 3 0.02535393180407862 0.02535393180407861 4 2 3 0.005634207067573026 0.005634207067573021 5 2 3 0.0009390345112621711 0.0009390345112621706 r8_invgam_pdf_test: Normal end of execution. r8_invgam_sample_test Python version: 3.6.9 r8_invgam_sample samples an inverse gamma distribution. R A X PDF() 3.19457 1.41565 1.51318 0.259992 2.10524 0.842685 3.4911 0.0914122 4.27823 2.699 3.68881 0.0821649 0.849281 0.318446 0.991292 0.145086 2.07386 0.732332 40.2109 0.00215547 2.77862 1.62389 0.863056 0.345005 3.58714 2.20536 0.797477 0.347993 3.51706 0.29719 71.6215 0.00179661 0.258401 1.10346 2.02585 0.0471468 3.67047 3.40422 1.21688 0.576329 r8_invgam_sample_test: Normal end of execution. r8_normal_01_pdf_test: Python version: 3.6.9 r8_normal_01_pdf evaluates the standard normal pdf with mean = 0 and standard deviation = 1. X PDF(0,1) PDF(0,1) tabulated computed -2.252653624140994 0.03155059887555709 0.03155059887555706 3.650540612071437 0.0005094586261557538 0.0005094586261557547 2.636073871461605 0.01235886992552887 0.01235886992552886 0.4935635421351536 0.353192862601275 0.353192862601275 -0.6775433481923101 0.3171212685764107 0.3171212685764107 -3.471050120671749 0.0009653372813755943 0.000965337281375596 -1.939377660943641 0.06083856556197816 0.0608385655619781 -3.120345651740235 0.003066504313116445 0.003066504313116445 -3.649368017767143 0.0005116437388114821 0.0005116437388114826 1.0717256984193 0.2246444116615346 0.2246444116615346 r8_normal_01_pdf_test: Normal end of execution. r8_normal_01_sample_test Python version: 3.6.9 r8_normal_01_sample samples the normal distribution. X PDF(X) -0.923566 0.260429 -1.29345 0.17283 -1.68753 0.0960564 -0.886023 0.269427 0.258378 0.385846 -0.634147 0.326277 -1.04065 0.23214 2.28539 0.0292922 -0.230177 0.388513 0.17545 0.392849 r8_normal_01_sample_test: Normal end of execution. r8_normal_pdf_test: Python version: 3.6.9 r8_normal_pdf evaluates the normal pdf pdf(mu,sigma) is the normal pdf with mu = mean, sigma = standard deviation. MU SIGMA X PDF(MU,SIGMA) PDF(MU,SIGMA) tabulated computed -56.31634060352484 4.785956124893755 -46.85424018542929 0.01180775937213258 0.01180775937213258 12.33908855337884 2.13500469923221 6.781057314200307 0.006307849174478944 0.006307849174478969 -48.48444152359102 0.6387882883091059 -50.23282168570062 0.0147514774470322 0.0147514774470322 26.7931424604825 0.4024634224214489 26.67129012408019 0.9468437743011001 0.9468437743011002 -19.73874370047668 3.79790008346491 -12.9643468135976 0.02140312299941794 0.0214031229994179 -99.63232576831896 4.497769898408682 -103.6600156181528 0.05939959967353488 0.05939959967353472 -81.09104995766396 0.1667227687589636 -80.73183222587458 0.2348929157422787 0.2348929157422788 68.16949013113364 0.7032091872463158 66.09155915000321 0.007207515678571277 0.007207515678571277 -47.93940044652702 4.57117016420902 -58.53544475210675 0.005944396897656727 0.005944396897656727 -29.67426801922078 4.132147851761006 -35.44773135435396 0.03637663165771322 0.03637663165771318 r8_normal_pdf_test: Normal end of execution. r8_normal_sample_test Python version: 3.6.9 r8_normal_sample samples the normal distribution. MU SIGMA X PDF(MU,SIGMA) -25.1283 0.431457 -25.4642 0.682904 -20.4455 0.644942 -20.9967 0.429314 48.7199 0.527707 49.3424 0.376976 -82.2332 0.657972 -81.9971 0.568526 46.9922 0.112607 47.0028 3.5271 -74.233 0.717469 -74.329 0.551086 -84.9373 0.554571 -85.9027 0.158065 -26.0036 0.108328 -25.9542 3.31933 -76.9956 0.511802 -76.8756 0.758337 -26.4697 0.615201 -26.1968 0.587683 r8_normal_sample_test: Normal end of execution. r8_scinvchi_pdf_test: Python version: 3.6.9 r8_scinvchi_pdf evaluates the scaled inverse Chi Square Probability Density Function. DF XI X PDF PDF 1 0.5 0.1 0.7322491280963244 0.7322491280963243 2 0.5 0.1 0.3368973499542734 0.3368973499542732 1 0.5 0.2 0.9036119633409063 0.9036119633409061 2 0.5 0.2 1.026062482798735 1.026062482798735 1 0.5 0.4 0.5968580144169457 0.5968580144169456 2 0.5 0.4 0.8953274901880941 0.8953274901880939 1 1 0.1 0.08500366602520341 0.08500366602520341 2 1 0.1 0.004539992976248485 0.004539992976248483 1 1 0.2 0.3661245640481622 0.3661245640481621 2 1 0.2 0.1684486749771367 0.1684486749771366 1 1 0.4 0.4518059816704532 0.4518059816704532 2 1 0.4 0.5130312413993675 0.5130312413993674 1 2 0.1 0.0008099910956089117 0.0008099910956089113 2 2 0.1 4.122307244877116e-07 4.122307244877103e-07 1 2 0.2 0.04250183301260171 0.0425018330126017 2 2 0.2 0.002269996488124243 0.002269996488124244 1 2 0.4 0.1830622820240811 0.1830622820240811 2 2 0.4 0.08422433748856833 0.08422433748856835 r8_scinvchi_pdf_test: Normal end of execution. r8_scinvchi_sample_test Python version: 3.6.9 r8_scinvchi_sample samples a scaled inverse chi square distribution. DF XI X PDF 3.68107 1.69866 0.514726 0.131257 3.64223 2.7061 2.69407 0.190974 4.42368 0.95813 1.40187 0.353834 3.53014 3.33575 2.8727 0.172463 1.8633 3.04893 7.11681 0.0383612 4.30594 2.50289 3.54864 0.141182 3.06736 3.71403 2.62798 0.160691 1.16351 2.43061 5.04626 0.0466104 1.26256 2.2657 1.41934 0.181804 2.66456 1.70953 1.58249 0.272509 r8_scinvchi_sample_test: Normal end of execution. r8_uniform_01_pdf_test: Python version: 3.6.9 r8_uniform_01_pdf evaluates the standard uniform pdf. X PDF() 1.324478190040008 0 0.1706547182028326 1 1.225853930552976 0 0.1452340380593773 1 0.677213087227087 1 0.1922166029696286 1 0.9499415620610996 1 0.7545721485066639 1 0.5821154129478712 1 1.130607814887224 0 r8_uniform_01_pdf_test: Normal end of execution. r8_uniform_01_sample_test Python version: 3.6.9 r8_uniform_01_sample returns random values in [0,1]: 0.323711 0.324392 0.493388 0.28873 0.353007 0.153961 0.566211 0.82072 0.325495 0.34008 r8_uniform_01_sample_test Normal end of execution r8_uniform_pdf_test: Python version: 3.6.9 r8_uniform_pdf evaluates the uniform pdf over [A,B]. A B X PDF() -3.72201 40.8314 -53.4256 0 -94.3721 85.8125 -94.3036 0.00554986 -2.49406 26.3826 -20.1503 0 32.5363 63.0491 -20.9764 0 57.6765 87.7338 -31.339 0 92.9965 97.5859 -77.1766 0 -92.8677 -37.3923 -93.2478 0 -71.2152 -13.8327 13.3031 0 96.712 99.3126 1.24887 0 -89.0511 -76.6179 76.066 0 r8_uniform_pdf_test: Normal end of execution. r8_uniform_sample_test Python version: 3.6.9 r8_uniform_sample returns random values in [A,B]: A B R -84.4552 52.4048 18.6716 -42.2511 34.0894 -11.2674 -16.7519 90.0188 55.0929 31.7361 55.1577 53.8788 -40.1759 78.2615 63.099 -14.7169 33.7554 -1.38009 -95.39 59.6945 9.555 -29.7319 63.3569 21.6901 -69.4086 -64.2579 -68.324 -74.6068 93.7462 56.3122 r8_uniform_sample_test Normal end of execution initialize(): rnglib() has been initialized. r8vec_multinormal_pdf_test Python version: 3.6.9 r8vec_multinormal_pdf evaluates the PDF for the multinormal distribution. The covariance matrix is C. The definition uses the inverse of C; r8vec_multinormal_pdf uses the Cholesky factor R Verify that the algorithms are equivalent. R1: Col: 0 1 2 3 4 Row 0 : 0.487884 0.471643 0.32876 0.0530927 0.182674 1 : 0.304139 0.419667 0.0308452 0.343446 2 : 0.904836 0.497489 0.798852 3 : 0.142095 0.743209 4 : 0.48614 C: Col: 0 1 2 3 4 Row 0 : 0.238031 0.230107 0.160396 0.0259031 0.0891238 1 : 0.230107 0.314947 0.282694 0.034422 0.190612 2 : 0.160396 0.282694 1.10293 0.480546 0.927019 3 : 0.0259031 0.034422 0.480546 0.271457 0.523319 4 : 0.0891238 0.190612 0.927019 0.523319 1.57818 R2: Col: 0 1 2 3 4 Row 0 : 0.487884 0.471643 0.32876 0.0530927 0.182674 1 : 0.304139 0.419667 0.0308452 0.343446 2 : 0.904836 0.497489 0.798852 3 : 0.142095 0.743209 4 : 0.48614 Determinant of C = 8.60191e-05 inverse(C): Col: 0 1 2 3 4 Row 0 : 40.2185 -53.3275 28.5978 -64.7415 8.83943 1 : -53.3275 81.9777 -47.8194 106.661 -14.1692 2 : 28.5978 -47.8194 32.9976 -71.3352 8.43242 3 : -64.7415 106.661 -71.3352 165.283 -22.1315 4 : 8.83943 -14.1692 8.43242 -22.1315 4.23134 MU: 0: -0.605484 1: -0.456013 2: 0.26816 3: -0.578703 4: 0.48101 X: 0: -0.60108 1: -0.453275 2: 0.27034 3: -0.567975 4: 0.47798 PDF1 = 1.0801 PDF2 = 1.0801 r8vec_multinormal_pdf_test Normal end of execution. initialize(): rnglib() has been initialized. r8vec_multinormal_sample_test Python version: 3.6.9 r8vec_multinormal_sample samples the multinormal distribution. N I MU X PDF() 0 2.4317 3.9368 1 3.2395 3.0689 2 1.8770 1.5980 3 2.4204 2.2231 4 -1.6933 -1.7499 5 0.00205217 0 -1.8715 0.1019 1 2.4180 1.6552 2 -2.7268 -3.1017 3 1.9931 1.1806 4 -0.7705 -0.3340 5 0.000971772 0 -1.3605 -0.8615 1 -2.4729 0.1608 2 1.1287 0.4774 3 -4.1675 -4.5503 4 1.9422 1.3115 5 0.000114811 0 3.8579 2.4109 1 -0.9079 -0.9557 2 1.0371 2.6276 3 -4.2410 -2.8020 4 2.4747 0.2096 5 0.000157498 0 0.3452 -1.3624 1 3.7271 5.7680 2 1.8761 2.8339 3 -1.3947 -3.5128 4 -1.5943 -1.5982 5 0.000255558 0 4.0762 5.3317 1 1.0861 1.0066 2 -2.0869 -1.4895 3 0.8241 -0.1412 4 1.1158 0.6758 5 0.00146783 0 3.4845 4.1542 1 -1.3080 -0.8803 2 2.5781 3.4496 3 1.2151 0.9142 4 -4.7107 -5.1511 5 0.00118862 0 -1.1252 0.6322 1 -2.6119 -2.8234 2 3.9026 4.0545 3 -3.9672 -5.9580 4 -4.7607 -3.5663 5 0.000554288 0 -3.3862 -5.6373 1 2.2310 2.7144 2 3.9657 4.6660 3 2.6798 1.8735 4 2.7335 5.0505 5 0.000209398 0 -1.2444 0.9176 1 1.1464 0.3320 2 -1.4752 -0.6713 3 -4.9759 -6.2347 4 -3.4530 -3.1428 5 0.000778439 r8vec_multinormal_sample_test: Normal end of execution. pdflib_test(): Normal end of execution. Tue Oct 19 17:00:18 2021