0s autopkgtest [18:54:13]: starting date and time: 2025-05-03 18:54:13+0000 0s autopkgtest [18:54:13]: git checkout: 9986aa8c Merge branch 'skia/fix_network_interface' into 'ubuntu/production' 0s autopkgtest [18:54:13]: host juju-7f2275-prod-proposed-migration-environment-23; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.hhs_bub5/out --timeout-copy=6000 --setup-commands /home/ubuntu/autopkgtest-cloud/worker-config-production/setup-canonical.sh --apt-pocket=proposed=src:nlme --apt-upgrade r-cran-spatstat.model --timeout-short=300 --timeout-copy=20000 --timeout-build=20000 --env=ADT_TEST_TRIGGERS=nlme/3.1.168-1 -- ssh -s /home/ubuntu/autopkgtest/ssh-setup/nova -- --flavor builder-cpu2-ram4-disk20 --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-23@bos03-4.secgroup --name adt-questing-amd64-r-cran-spatstat.model-20250503-185413-juju-7f2275-prod-proposed-migration-environment-23-8c037848-b444-46e2-9465-2a592f07f3ae --image adt/ubuntu-questing-amd64-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-23 --net-id=net_prod-proposed-migration-amd64 -e TERM=linux --mirror=http://ftpmaster.internal/ubuntu/ 47s autopkgtest [18:55:00]: testbed dpkg architecture: amd64 47s autopkgtest [18:55:00]: testbed apt version: 3.0.0 47s autopkgtest [18:55:00]: @@@@@@@@@@@@@@@@@@@@ test bed setup 47s autopkgtest [18:55:00]: testbed release detected to be: None 48s autopkgtest [18:55:01]: updating testbed package index (apt update) 48s Get:1 http://ftpmaster.internal/ubuntu questing-proposed InRelease [110 kB] 49s Hit:2 http://ftpmaster.internal/ubuntu questing InRelease 49s Hit:3 http://ftpmaster.internal/ubuntu questing-updates InRelease 49s Hit:4 http://ftpmaster.internal/ubuntu questing-security InRelease 49s Get:5 http://ftpmaster.internal/ubuntu questing-proposed/multiverse Sources [33.7 kB] 49s Get:6 http://ftpmaster.internal/ubuntu questing-proposed/main Sources [149 kB] 49s Get:7 http://ftpmaster.internal/ubuntu questing-proposed/universe Sources [1442 kB] 49s Get:8 http://ftpmaster.internal/ubuntu questing-proposed/main amd64 Packages [203 kB] 49s Get:9 http://ftpmaster.internal/ubuntu questing-proposed/main i386 Packages [146 kB] 49s Get:10 http://ftpmaster.internal/ubuntu questing-proposed/universe amd64 Packages [1424 kB] 49s Get:11 http://ftpmaster.internal/ubuntu questing-proposed/universe i386 Packages [576 kB] 49s Get:12 http://ftpmaster.internal/ubuntu questing-proposed/multiverse amd64 Packages [48.6 kB] 49s Get:13 http://ftpmaster.internal/ubuntu questing-proposed/multiverse i386 Packages [23.1 kB] 49s Fetched 4155 kB in 1s (3816 kB/s) 50s Reading package lists... 51s autopkgtest [18:55:04]: upgrading testbed (apt dist-upgrade and autopurge) 51s Reading package lists... 51s Building dependency tree... 51s Reading state information... 52s Calculating upgrade...Starting pkgProblemResolver with broken count: 0 52s Starting 2 pkgProblemResolver with broken count: 0 52s Done 52s Entering ResolveByKeep 52s 52s Calculating upgrade... 52s The following packages will be upgraded: 52s cloud-init cloud-init-base debianutils libmbim-glib4 libmbim-proxy 52s libnftnl11 libqmi-glib5 libqmi-proxy libsepol2 python3-lazr.restfulclient 52s sos 53s 11 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 53s Need to get 2693 kB of archives. 53s After this operation, 104 kB disk space will be freed. 53s Get:1 http://ftpmaster.internal/ubuntu questing/main amd64 debianutils amd64 5.22 [93.0 kB] 53s Get:2 http://ftpmaster.internal/ubuntu questing/main amd64 libsepol2 amd64 3.8.1-1 [327 kB] 53s Get:3 http://ftpmaster.internal/ubuntu questing/main amd64 libnftnl11 amd64 1.2.9-1 [69.1 kB] 53s Get:4 http://ftpmaster.internal/ubuntu questing/main amd64 cloud-init-base all 25.2~1g7a0265d3-0ubuntu1 [619 kB] 53s Get:5 http://ftpmaster.internal/ubuntu questing/main amd64 libmbim-proxy amd64 1.32.0-1 [6276 B] 53s Get:6 http://ftpmaster.internal/ubuntu questing/main amd64 libmbim-glib4 amd64 1.32.0-1 [233 kB] 53s Get:7 http://ftpmaster.internal/ubuntu questing/main amd64 libqmi-proxy amd64 1.36.0-1 [6220 B] 53s Get:8 http://ftpmaster.internal/ubuntu questing/main amd64 libqmi-glib5 amd64 1.36.0-1 [920 kB] 53s Get:9 http://ftpmaster.internal/ubuntu questing/main amd64 python3-lazr.restfulclient all 0.14.6-3 [51.0 kB] 53s Get:10 http://ftpmaster.internal/ubuntu questing/main amd64 sos all 4.9.1-1 [367 kB] 53s Get:11 http://ftpmaster.internal/ubuntu questing/main amd64 cloud-init all 25.2~1g7a0265d3-0ubuntu1 [2106 B] 53s Preconfiguring packages ... 53s Fetched 2693 kB in 1s (4388 kB/s) 54s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 80514 files and directories currently installed.) 54s Preparing to unpack .../debianutils_5.22_amd64.deb ... 54s Unpacking debianutils (5.22) over (5.21) ... 54s Setting up debianutils (5.22) ... 54s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 80514 files and directories currently installed.) 54s Preparing to unpack .../libsepol2_3.8.1-1_amd64.deb ... 54s Unpacking libsepol2:amd64 (3.8.1-1) over (3.7-1) ... 54s Setting up libsepol2:amd64 (3.8.1-1) ... 54s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 80514 files and directories currently installed.) 54s Preparing to unpack .../0-libnftnl11_1.2.9-1_amd64.deb ... 54s Unpacking libnftnl11:amd64 (1.2.9-1) over (1.2.8-1) ... 54s Preparing to unpack .../1-cloud-init-base_25.2~1g7a0265d3-0ubuntu1_all.deb ... 54s Unpacking cloud-init-base (25.2~1g7a0265d3-0ubuntu1) over (25.1.1-0ubuntu2) ... 54s Preparing to unpack .../2-libmbim-proxy_1.32.0-1_amd64.deb ... 54s Unpacking libmbim-proxy (1.32.0-1) over (1.31.2-0ubuntu4) ... 54s Preparing to unpack .../3-libmbim-glib4_1.32.0-1_amd64.deb ... 54s Unpacking libmbim-glib4:amd64 (1.32.0-1) over (1.31.2-0ubuntu4) ... 54s Preparing to unpack .../4-libqmi-proxy_1.36.0-1_amd64.deb ... 54s Unpacking libqmi-proxy (1.36.0-1) over (1.35.6-1) ... 54s Preparing to unpack .../5-libqmi-glib5_1.36.0-1_amd64.deb ... 54s Unpacking libqmi-glib5:amd64 (1.36.0-1) over (1.35.6-1) ... 54s Preparing to unpack .../6-python3-lazr.restfulclient_0.14.6-3_all.deb ... 55s Unpacking python3-lazr.restfulclient (0.14.6-3) over (0.14.6-2) ... 55s Preparing to unpack .../7-sos_4.9.1-1_all.deb ... 55s Unpacking sos (4.9.1-1) over (4.9.0-6) ... 55s Preparing to unpack .../8-cloud-init_25.2~1g7a0265d3-0ubuntu1_all.deb ... 55s Unpacking cloud-init (25.2~1g7a0265d3-0ubuntu1) over (25.1.1-0ubuntu2) ... 55s Setting up sos (4.9.1-1) ... 55s Setting up libnftnl11:amd64 (1.2.9-1) ... 55s Setting up cloud-init-base (25.2~1g7a0265d3-0ubuntu1) ... 57s Setting up python3-lazr.restfulclient (0.14.6-3) ... 57s Setting up libmbim-glib4:amd64 (1.32.0-1) ... 57s Setting up cloud-init (25.2~1g7a0265d3-0ubuntu1) ... 57s Setting up libmbim-proxy (1.32.0-1) ... 57s Setting up libqmi-glib5:amd64 (1.36.0-1) ... 57s Setting up libqmi-proxy (1.36.0-1) ... 57s Processing triggers for libc-bin (2.41-6ubuntu1) ... 57s Processing triggers for rsyslog (8.2412.0-2ubuntu2) ... 57s Processing triggers for man-db (2.13.0-1) ... 59s Reading package lists... 59s Building dependency tree... 59s Reading state information... 60s Starting pkgProblemResolver with broken count: 0 60s Starting 2 pkgProblemResolver with broken count: 0 60s Done 60s Solving dependencies... 60s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 60s autopkgtest [18:55:13]: rebooting testbed after setup commands that affected boot 83s autopkgtest [18:55:36]: testbed running kernel: Linux 6.14.0-15-generic #15-Ubuntu SMP PREEMPT_DYNAMIC Sun Apr 6 15:05:05 UTC 2025 85s autopkgtest [18:55:38]: @@@@@@@@@@@@@@@@@@@@ apt-source r-cran-spatstat.model 87s Get:1 http://ftpmaster.internal/ubuntu questing/universe r-cran-spatstat.model 3.3-4-1 (dsc) [2601 B] 87s Get:2 http://ftpmaster.internal/ubuntu questing/universe r-cran-spatstat.model 3.3-4-1 (tar) [808 kB] 87s Get:3 http://ftpmaster.internal/ubuntu questing/universe r-cran-spatstat.model 3.3-4-1 (diff) [3508 B] 88s gpgv: Signature made Fri Jan 31 08:13:11 2025 UTC 88s gpgv: using RSA key 73471499CC60ED9EEE805946C5BD6C8F2295D502 88s gpgv: issuer "plessy@debian.org" 88s gpgv: Can't check signature: No public key 88s dpkg-source: warning: cannot verify inline signature for ./r-cran-spatstat.model_3.3-4-1.dsc: no acceptable signature found 88s autopkgtest [18:55:41]: testing package r-cran-spatstat.model version 3.3-4-1 88s autopkgtest [18:55:41]: build not needed 90s autopkgtest [18:55:43]: test run-unit-test: preparing testbed 91s Reading package lists... 91s Building dependency tree... 91s Reading state information... 91s Starting pkgProblemResolver with broken count: 0 91s Starting 2 pkgProblemResolver with broken count: 0 91s Done 92s The following NEW packages will be installed: 92s fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono 92s fonts-mathjax libblas3 libcairo2 libdatrie1 libdeflate0 libfontconfig1 92s libgfortran5 libgomp1 libgraphite2-3 libgsl28 libgslcblas0 libharfbuzz0b 92s libice6 libjbig0 libjpeg-turbo8 libjpeg8 libjs-mathjax liblapack3 liblerc4 92s libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 libpaper-utils 92s libpaper2 libpixman-1-0 libsharpyuv0 libsm6 libtcl8.6 libthai-data libthai0 92s libtiff6 libtk8.6 libwebp7 libxcb-render0 libxcb-shm0 libxft2 libxrender1 92s libxss1 libxt6t64 littler r-base-core r-cran-abind r-cran-codetools 92s r-cran-deldir r-cran-foreach r-cran-glmnet r-cran-goftest r-cran-gsl 92s r-cran-iterators r-cran-lattice r-cran-littler r-cran-locfit r-cran-matrix 92s r-cran-mgcv r-cran-nleqslv r-cran-nlme r-cran-pkgkitten r-cran-polyclip 92s r-cran-rcpp r-cran-rcppeigen r-cran-rpart r-cran-shape r-cran-sm 92s r-cran-spatial r-cran-spatstat r-cran-spatstat.data r-cran-spatstat.explore 92s r-cran-spatstat.geom r-cran-spatstat.linnet r-cran-spatstat.model 92s r-cran-spatstat.random r-cran-spatstat.sparse r-cran-spatstat.univar 92s r-cran-spatstat.utils r-cran-survival r-cran-tensor unzip x11-common 92s xdg-utils zip 92s 0 upgraded, 84 newly installed, 0 to remove and 0 not upgraded. 92s Need to get 103 MB of archives. 92s After this operation, 218 MB of additional disk space will be used. 92s Get:1 http://ftpmaster.internal/ubuntu questing/main amd64 fonts-dejavu-mono all 2.37-8 [502 kB] 92s Get:2 http://ftpmaster.internal/ubuntu questing/main amd64 fonts-dejavu-core all 2.37-8 [835 kB] 92s Get:3 http://ftpmaster.internal/ubuntu questing/main amd64 fontconfig-config amd64 2.15.0-2.2ubuntu1 [37.8 kB] 92s Get:4 http://ftpmaster.internal/ubuntu questing/main amd64 libfontconfig1 amd64 2.15.0-2.2ubuntu1 [164 kB] 92s Get:5 http://ftpmaster.internal/ubuntu questing/main amd64 fontconfig amd64 2.15.0-2.2ubuntu1 [180 kB] 92s Get:6 http://ftpmaster.internal/ubuntu questing/main amd64 fonts-mathjax all 2.7.9+dfsg-1 [2208 kB] 93s Get:7 http://ftpmaster.internal/ubuntu questing/main amd64 libblas3 amd64 3.12.1-2 [359 kB] 93s Get:8 http://ftpmaster.internal/ubuntu questing/main amd64 libpixman-1-0 amd64 0.44.0-3 [427 kB] 93s Get:9 http://ftpmaster.internal/ubuntu questing/main amd64 libxcb-render0 amd64 1.17.0-2 [16.2 kB] 93s Get:10 http://ftpmaster.internal/ubuntu questing/main amd64 libxcb-shm0 amd64 1.17.0-2 [5758 B] 93s Get:11 http://ftpmaster.internal/ubuntu questing/main amd64 libxrender1 amd64 1:0.9.10-1.1build1 [19.0 kB] 93s Get:12 http://ftpmaster.internal/ubuntu questing/main amd64 libcairo2 amd64 1.18.4-1 [662 kB] 93s Get:13 http://ftpmaster.internal/ubuntu questing/main amd64 libdatrie1 amd64 0.2.13-3build1 [19.0 kB] 93s Get:14 http://ftpmaster.internal/ubuntu questing/main amd64 libdeflate0 amd64 1.23-2 [49.9 kB] 93s Get:15 http://ftpmaster.internal/ubuntu questing/main amd64 libgfortran5 amd64 15-20250404-0ubuntu1 [926 kB] 93s Get:16 http://ftpmaster.internal/ubuntu questing/main amd64 libgomp1 amd64 15-20250404-0ubuntu1 [151 kB] 93s Get:17 http://ftpmaster.internal/ubuntu questing/main amd64 libgraphite2-3 amd64 1.3.14-2ubuntu1 [73.1 kB] 93s Get:18 http://ftpmaster.internal/ubuntu questing/universe amd64 libgslcblas0 amd64 2.8+dfsg-5ubuntu1 [113 kB] 93s Get:19 http://ftpmaster.internal/ubuntu questing/universe amd64 libgsl28 amd64 2.8+dfsg-5ubuntu1 [1043 kB] 93s Get:20 http://ftpmaster.internal/ubuntu questing/main amd64 libharfbuzz0b amd64 10.2.0-1 [543 kB] 93s Get:21 http://ftpmaster.internal/ubuntu questing/main amd64 x11-common all 1:7.7+23ubuntu4 [21.8 kB] 93s Get:22 http://ftpmaster.internal/ubuntu questing/main amd64 libice6 amd64 2:1.1.1-1 [44.1 kB] 93s Get:23 http://ftpmaster.internal/ubuntu questing/main amd64 libjpeg-turbo8 amd64 2.1.5-3ubuntu2 [179 kB] 93s Get:24 http://ftpmaster.internal/ubuntu questing/main amd64 libjpeg8 amd64 8c-2ubuntu11 [2148 B] 93s Get:25 http://ftpmaster.internal/ubuntu questing/main amd64 liblapack3 amd64 3.12.1-2 [3179 kB] 93s Get:26 http://ftpmaster.internal/ubuntu questing/main amd64 liblerc4 amd64 4.0.0+ds-5ubuntu1 [271 kB] 93s Get:27 http://ftpmaster.internal/ubuntu questing/main amd64 libthai-data all 0.1.29-2build1 [158 kB] 93s Get:28 http://ftpmaster.internal/ubuntu questing/main amd64 libthai0 amd64 0.1.29-2build1 [18.9 kB] 93s Get:29 http://ftpmaster.internal/ubuntu questing/main amd64 libpango-1.0-0 amd64 1.56.3-1 [256 kB] 93s Get:30 http://ftpmaster.internal/ubuntu questing/main amd64 libpangoft2-1.0-0 amd64 1.56.3-1 [52.9 kB] 93s Get:31 http://ftpmaster.internal/ubuntu questing/main amd64 libpangocairo-1.0-0 amd64 1.56.3-1 [29.1 kB] 93s Get:32 http://ftpmaster.internal/ubuntu questing/main amd64 libpaper2 amd64 2.2.5-0.3 [17.4 kB] 93s Get:33 http://ftpmaster.internal/ubuntu questing/main amd64 libpaper-utils amd64 2.2.5-0.3 [15.5 kB] 93s Get:34 http://ftpmaster.internal/ubuntu questing/main amd64 libsharpyuv0 amd64 1.5.0-0.1 [25.9 kB] 93s Get:35 http://ftpmaster.internal/ubuntu questing/main amd64 libsm6 amd64 2:1.2.4-1 [17.4 kB] 93s Get:36 http://ftpmaster.internal/ubuntu questing/main amd64 libtcl8.6 amd64 8.6.16+dfsg-1 [1086 kB] 93s Get:37 http://ftpmaster.internal/ubuntu questing/main amd64 libjbig0 amd64 2.1-6.1ubuntu2 [29.7 kB] 93s Get:38 http://ftpmaster.internal/ubuntu questing/main amd64 libwebp7 amd64 1.5.0-0.1 [378 kB] 93s Get:39 http://ftpmaster.internal/ubuntu questing/main amd64 libtiff6 amd64 4.7.0-3ubuntu1 [204 kB] 93s Get:40 http://ftpmaster.internal/ubuntu questing/main amd64 libxft2 amd64 2.3.6-1build1 [45.3 kB] 93s Get:41 http://ftpmaster.internal/ubuntu questing/main amd64 libxss1 amd64 1:1.2.3-1build3 [7204 B] 93s Get:42 http://ftpmaster.internal/ubuntu questing/main amd64 libtk8.6 amd64 8.6.16-1 [868 kB] 94s Get:43 http://ftpmaster.internal/ubuntu questing/main amd64 libxt6t64 amd64 1:1.2.1-1.2build1 [171 kB] 94s Get:44 http://ftpmaster.internal/ubuntu questing/main amd64 zip amd64 3.0-14ubuntu2 [185 kB] 94s Get:45 http://ftpmaster.internal/ubuntu questing/main amd64 unzip amd64 6.0-28ubuntu6 [181 kB] 94s Get:46 http://ftpmaster.internal/ubuntu questing/main amd64 xdg-utils all 1.2.1-2ubuntu1 [66.0 kB] 94s Get:47 http://ftpmaster.internal/ubuntu questing/universe amd64 r-base-core amd64 4.4.3-1 [28.9 MB] 95s Get:48 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-littler amd64 0.3.20-2 [96.6 kB] 95s Get:49 http://ftpmaster.internal/ubuntu questing/universe amd64 littler all 0.3.20-2 [2554 B] 95s Get:50 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-abind all 1.4-8-1 [66.9 kB] 95s Get:51 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-codetools all 0.2-20-1 [90.5 kB] 95s Get:52 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-deldir amd64 2.0-4-1build1 [270 kB] 95s Get:53 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-iterators all 1.0.14-1 [336 kB] 95s Get:54 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-foreach all 1.5.2-1 [124 kB] 95s Get:55 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-lattice amd64 0.22-6-1 [1340 kB] 95s Get:56 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-matrix amd64 1.7-3-1 [4349 kB] 95s Get:57 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-shape all 1.4.6.1-1 [749 kB] 95s Get:58 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-survival amd64 3.8-3-1 [8239 kB] 95s Get:59 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-pkgkitten all 0.2.4-1 [27.2 kB] 95s Get:60 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-rcpp amd64 1.0.14-1 [1998 kB] 95s Get:61 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-rcppeigen amd64 0.3.4.0.2-1 [1428 kB] 95s Get:62 http://ftpmaster.internal/ubuntu questing/main amd64 libjs-mathjax all 2.7.9+dfsg-1 [5665 kB] 95s Get:63 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-glmnet amd64 4.1-8-1 [1926 kB] 95s Get:64 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-goftest amd64 1.2-3-1 [59.5 kB] 95s Get:65 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-gsl amd64 2.1-8-1build1 [486 kB] 95s Get:66 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-locfit amd64 1.5-9.12-1 [552 kB] 95s Get:67 http://ftpmaster.internal/ubuntu questing-proposed/universe amd64 r-cran-nlme amd64 3.1.168-1 [2320 kB] 95s Get:68 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-mgcv amd64 1.9-1-1 [3252 kB] 95s Get:69 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-nleqslv amd64 3.3.5-1 [102 kB] 95s Get:70 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-polyclip amd64 1.10-7-1 [116 kB] 95s Get:71 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-rpart amd64 4.1.24-1 [670 kB] 95s Get:72 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-sm amd64 2.2-6.0-1 [788 kB] 96s Get:73 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatial amd64 7.3-18-1 [137 kB] 96s Get:74 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.utils amd64 3.1-3-1 [387 kB] 96s Get:75 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.data all 3.1-6-1 [4153 kB] 96s Get:76 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.univar amd64 3.1-2-1 [315 kB] 96s Get:77 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.geom amd64 3.3-6-1 [3968 kB] 96s Get:78 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.random amd64 3.3-3-1 [1177 kB] 96s Get:79 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-tensor all 1.5-4 [15.7 kB] 96s Get:80 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.sparse amd64 3.1-0-1 [221 kB] 96s Get:81 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.explore amd64 3.3-4-1 [3347 kB] 96s Get:82 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.model amd64 3.3-4-1 [3397 kB] 96s Get:83 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.linnet amd64 3.2-5-1 [1509 kB] 96s Get:84 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat amd64 3.3-1-1 [4121 kB] 96s Preconfiguring packages ... 97s Fetched 103 MB in 4s (23.0 MB/s) 97s Selecting previously unselected package fonts-dejavu-mono. 97s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 80518 files and directories currently installed.) 97s Preparing to unpack .../00-fonts-dejavu-mono_2.37-8_all.deb ... 97s Unpacking fonts-dejavu-mono (2.37-8) ... 97s Selecting previously unselected package fonts-dejavu-core. 97s Preparing to unpack .../01-fonts-dejavu-core_2.37-8_all.deb ... 97s Unpacking fonts-dejavu-core (2.37-8) ... 97s Selecting previously unselected package fontconfig-config. 97s Preparing to unpack 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libpixman-1-0:amd64 (0.44.0-3) ... 97s Selecting previously unselected package libxcb-render0:amd64. 97s Preparing to unpack .../08-libxcb-render0_1.17.0-2_amd64.deb ... 97s Unpacking libxcb-render0:amd64 (1.17.0-2) ... 97s Selecting previously unselected package libxcb-shm0:amd64. 97s Preparing to unpack .../09-libxcb-shm0_1.17.0-2_amd64.deb ... 97s Unpacking libxcb-shm0:amd64 (1.17.0-2) ... 97s Selecting previously unselected package libxrender1:amd64. 97s Preparing to unpack .../10-libxrender1_1%3a0.9.10-1.1build1_amd64.deb ... 97s Unpacking libxrender1:amd64 (1:0.9.10-1.1build1) ... 97s Selecting previously unselected package libcairo2:amd64. 97s Preparing to unpack .../11-libcairo2_1.18.4-1_amd64.deb ... 97s Unpacking libcairo2:amd64 (1.18.4-1) ... 97s Selecting previously unselected package libdatrie1:amd64. 97s Preparing to unpack .../12-libdatrie1_0.2.13-3build1_amd64.deb ... 97s Unpacking libdatrie1:amd64 (0.2.13-3build1) ... 97s Selecting previously unselected package libdeflate0:amd64. 98s Preparing to unpack .../13-libdeflate0_1.23-2_amd64.deb ... 98s Unpacking libdeflate0:amd64 (1.23-2) ... 98s Selecting previously unselected package libgfortran5:amd64. 98s Preparing to unpack .../14-libgfortran5_15-20250404-0ubuntu1_amd64.deb ... 98s Unpacking libgfortran5:amd64 (15-20250404-0ubuntu1) ... 98s Selecting previously unselected package libgomp1:amd64. 98s Preparing to unpack .../15-libgomp1_15-20250404-0ubuntu1_amd64.deb ... 98s Unpacking libgomp1:amd64 (15-20250404-0ubuntu1) ... 98s Selecting previously unselected package libgraphite2-3:amd64. 98s Preparing to unpack .../16-libgraphite2-3_1.3.14-2ubuntu1_amd64.deb ... 98s Unpacking libgraphite2-3:amd64 (1.3.14-2ubuntu1) ... 98s Selecting previously unselected package libgslcblas0:amd64. 98s Preparing to unpack .../17-libgslcblas0_2.8+dfsg-5ubuntu1_amd64.deb ... 98s Unpacking libgslcblas0:amd64 (2.8+dfsg-5ubuntu1) ... 98s Selecting previously unselected package libgsl28:amd64. 98s Preparing to unpack .../18-libgsl28_2.8+dfsg-5ubuntu1_amd64.deb ... 98s Unpacking libgsl28:amd64 (2.8+dfsg-5ubuntu1) ... 98s Selecting previously unselected package libharfbuzz0b:amd64. 98s Preparing to unpack .../19-libharfbuzz0b_10.2.0-1_amd64.deb ... 98s Unpacking libharfbuzz0b:amd64 (10.2.0-1) ... 98s Selecting previously unselected package x11-common. 98s Preparing to unpack .../20-x11-common_1%3a7.7+23ubuntu4_all.deb ... 98s Unpacking x11-common (1:7.7+23ubuntu4) ... 98s Selecting previously unselected package libice6:amd64. 98s Preparing to unpack .../21-libice6_2%3a1.1.1-1_amd64.deb ... 98s Unpacking libice6:amd64 (2:1.1.1-1) ... 98s Selecting previously unselected package libjpeg-turbo8:amd64. 98s Preparing to unpack .../22-libjpeg-turbo8_2.1.5-3ubuntu2_amd64.deb ... 98s Unpacking libjpeg-turbo8:amd64 (2.1.5-3ubuntu2) ... 98s Selecting previously unselected package libjpeg8:amd64. 98s Preparing to unpack .../23-libjpeg8_8c-2ubuntu11_amd64.deb ... 98s Unpacking libjpeg8:amd64 (8c-2ubuntu11) 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to unpack .../46-r-base-core_4.4.3-1_amd64.deb ... 99s Unpacking r-base-core (4.4.3-1) ... 99s Selecting previously unselected package r-cran-littler. 99s Preparing to unpack .../47-r-cran-littler_0.3.20-2_amd64.deb ... 99s Unpacking r-cran-littler (0.3.20-2) ... 99s Selecting previously unselected package littler. 99s Preparing to unpack .../48-littler_0.3.20-2_all.deb ... 99s Unpacking littler (0.3.20-2) ... 99s Selecting previously unselected package r-cran-abind. 99s Preparing to unpack .../49-r-cran-abind_1.4-8-1_all.deb ... 99s Unpacking r-cran-abind (1.4-8-1) ... 99s Selecting previously unselected package r-cran-codetools. 99s Preparing to unpack .../50-r-cran-codetools_0.2-20-1_all.deb ... 99s Unpacking r-cran-codetools (0.2-20-1) ... 99s Selecting previously unselected package r-cran-deldir. 99s Preparing to unpack .../51-r-cran-deldir_2.0-4-1build1_amd64.deb ... 99s Unpacking r-cran-deldir (2.0-4-1build1) ... 99s Selecting previously unselected package r-cran-iterators. 99s 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package r-cran-pkgkitten. 99s Preparing to unpack .../58-r-cran-pkgkitten_0.2.4-1_all.deb ... 99s Unpacking r-cran-pkgkitten (0.2.4-1) ... 99s Selecting previously unselected package r-cran-rcpp. 99s Preparing to unpack .../59-r-cran-rcpp_1.0.14-1_amd64.deb ... 99s Unpacking r-cran-rcpp (1.0.14-1) ... 99s Selecting previously unselected package r-cran-rcppeigen. 99s Preparing to unpack .../60-r-cran-rcppeigen_0.3.4.0.2-1_amd64.deb ... 99s Unpacking r-cran-rcppeigen (0.3.4.0.2-1) ... 99s Selecting previously unselected package libjs-mathjax. 100s Preparing to unpack .../61-libjs-mathjax_2.7.9+dfsg-1_all.deb ... 100s Unpacking libjs-mathjax (2.7.9+dfsg-1) ... 100s Selecting previously unselected package r-cran-glmnet. 100s Preparing to unpack .../62-r-cran-glmnet_4.1-8-1_amd64.deb ... 100s Unpacking r-cran-glmnet (4.1-8-1) ... 100s Selecting previously unselected package r-cran-goftest. 100s Preparing to unpack .../63-r-cran-goftest_1.2-3-1_amd64.deb ... 100s Unpacking r-cran-goftest 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previously unselected package r-cran-spatstat.univar. 101s Preparing to unpack .../75-r-cran-spatstat.univar_3.1-2-1_amd64.deb ... 101s Unpacking r-cran-spatstat.univar (3.1-2-1) ... 101s Selecting previously unselected package r-cran-spatstat.geom. 101s Preparing to unpack .../76-r-cran-spatstat.geom_3.3-6-1_amd64.deb ... 101s Unpacking r-cran-spatstat.geom (3.3-6-1) ... 101s Selecting previously unselected package r-cran-spatstat.random. 101s Preparing to unpack .../77-r-cran-spatstat.random_3.3-3-1_amd64.deb ... 101s Unpacking r-cran-spatstat.random (3.3-3-1) ... 101s Selecting previously unselected package r-cran-tensor. 101s Preparing to unpack .../78-r-cran-tensor_1.5-4_all.deb ... 101s Unpacking r-cran-tensor (1.5-4) ... 101s Selecting previously unselected package r-cran-spatstat.sparse. 101s Preparing to unpack .../79-r-cran-spatstat.sparse_3.1-0-1_amd64.deb ... 101s Unpacking r-cran-spatstat.sparse (3.1-0-1) ... 101s Selecting previously unselected package r-cran-spatstat.explore. 101s Preparing to unpack .../80-r-cran-spatstat.explore_3.3-4-1_amd64.deb ... 101s Unpacking r-cran-spatstat.explore (3.3-4-1) ... 101s Selecting previously unselected package r-cran-spatstat.model. 101s Preparing to unpack .../81-r-cran-spatstat.model_3.3-4-1_amd64.deb ... 101s Unpacking r-cran-spatstat.model (3.3-4-1) ... 101s Selecting previously unselected package r-cran-spatstat.linnet. 101s Preparing to unpack .../82-r-cran-spatstat.linnet_3.2-5-1_amd64.deb ... 101s Unpacking r-cran-spatstat.linnet (3.2-5-1) ... 101s Selecting previously unselected package r-cran-spatstat. 101s Preparing to unpack .../83-r-cran-spatstat_3.3-1-1_amd64.deb ... 101s Unpacking r-cran-spatstat (3.3-1-1) ... 101s Setting up libgraphite2-3:amd64 (1.3.14-2ubuntu1) ... 101s Setting up libpixman-1-0:amd64 (0.44.0-3) ... 101s Setting up libsharpyuv0:amd64 (1.5.0-0.1) ... 101s Setting up fonts-mathjax (2.7.9+dfsg-1) ... 101s Setting up liblerc4:amd64 (4.0.0+ds-5ubuntu1) ... 101s 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104s Setting up r-cran-spatstat.data (3.1-6-1) ... 104s Setting up r-cran-spatstat.geom (3.3-6-1) ... 104s Setting up r-cran-glmnet (4.1-8-1) ... 104s Setting up r-cran-rpart (4.1.24-1) ... 104s Setting up r-cran-spatstat.random (3.3-3-1) ... 104s Setting up r-cran-spatstat.explore (3.3-4-1) ... 104s Setting up r-cran-spatstat.model (3.3-4-1) ... 104s Setting up r-cran-spatstat.linnet (3.2-5-1) ... 104s Setting up r-cran-spatstat (3.3-1-1) ... 104s Processing triggers for install-info (7.1.1-1) ... 104s Processing triggers for libc-bin (2.41-6ubuntu1) ... 104s Processing triggers for man-db (2.13.0-1) ... 107s autopkgtest [18:56:00]: test run-unit-test: [----------------------- 107s BEGIN TEST testsAtoC.R 107s 107s R version 4.4.3 (2025-02-28) -- "Trophy Case" 107s Copyright (C) 2025 The R Foundation for Statistical Computing 107s Platform: x86_64-pc-linux-gnu 107s 107s R is free software and comes with ABSOLUTELY NO WARRANTY. 107s You are welcome to redistribute it under certain conditions. 107s Type 'license()' or 'licence()' for distribution details. 107s 107s R is a collaborative project with many contributors. 107s Type 'contributors()' for more information and 107s 'citation()' on how to cite R or R packages in publications. 107s 107s Type 'demo()' for some demos, 'help()' for on-line help, or 107s 'help.start()' for an HTML browser interface to help. 107s Type 'q()' to quit R. 107s 107s > #' 107s > Loading required package: spatstat.model 107s #' Header for all (concatenated) test files 107s > #' 107s > #' Require spatstat.model 107s > #' Obtain environment variable controlling tests. 107s > #' 107s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 107s > 107s > require(spatstat.model) 107s Loading required package: spatstat.data 108s Loading required package: spatstat.univar 108s spatstat.univar 3.1-2 108s Loading required package: spatstat.geom 108s spatstat.geom 3.3-6 108s Loading required package: spatstat.random 108s spatstat.random 3.3-3 108s Loading required package: spatstat.explore 108s Loading required package: nlme 108s spatstat.explore 3.3-4 108s Loading required package: rpart 108s spatstat.model 3.3-4 108s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 108s > ALWAYS <- TRUE 108s > cat(paste("--------- Executing", 108s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 108s + "test code -----------\n")) 108s --------- Executing **RESTRICTED** subset of test code ----------- 108s > #' tests/aucroc.R 108s > #' 108s > #' AUC and ROC code 108s > #' 108s > #' $Revision: 1.6 $ $Date: 2020/11/02 06:26:45 $ 108s > 108s > local({ 108s + if(FULLTEST) { 108s + fit <- kppm(redwood ~ I(y-x)) 108s + a <- roc(fit) 108s + b <- auc(fit) 108s + fet <- ppm(amacrine~x+y+marks) 108s + d <- roc(fet) 108s + e <- auc(fet) 108s + } 108s + }) 108s > ## tests/cdf.test.R 108s > 108s > 108s > local({ 108s + NSIM <- 9 108s + op <- spatstat.options(ndummy.min=16, npixel=32) 108s + if(FULLTEST) { 108s + ## Monte Carlo test for Gibbs model 108s + fit <- ppm(cells ~ 1, Strauss(0.07)) 108s + cdf.test(fit, "x", nsim=NSIM) 108s + 108s + ## cdf.test.slrm 108s + fut <- slrm(japanesepines ~ x + y) 108s + Z <- distmap(japanesepines) 108s + cdf.test(fut, Z) 108s + } 108s + reset.spatstat.options() 108s + }) 108s > 108s > 108s > #' 108s > #' tests/contrib.R 108s > #' 108s > #' Tests for user-contributed code in spatstat 108s > #' 108s > #' $Revision: 1.4 $ $Date: 2021/04/17 02:32:24 $ 108s > 108s > local({ 108s + #' Jinhom 108s + #' Marie-Colette van Lieshout and Ottmar Cronie 108s + X <- redwood3 108s + if(FULLTEST) { 108s + fit <- ppm(X ~ polynom(x,y,2)) 108s + } else { 108s + X <- X[c(TRUE,FALSE)] 108s + spatstat.options(npixel=32, ndummy.min=16) 108s + fit <- ppm(X ~ x) 108s + } 108s + lam <- predict(fit) 108s + lamX <- fitted(fit, dataonly=TRUE) 108s + lmin <- 0.9 * min(lam) 108s + g1 <- Ginhom(X, lambda=fit, update=TRUE) 108s + if(FULLTEST) { 108s + g2 <- Ginhom(X, lambda=fit, update=FALSE, lmin = lmin) 108s + g3 <- Ginhom(X, lambda=lam, lmin=lmin) 108s + g4 <- Ginhom(X, lambda=lamX, lmin=lmin) 108s + } 108s + if(ALWAYS) { 108s + f2 <- Finhom(X, lambda=fit, update=FALSE) 108s + } 108s + if(FULLTEST) { 108s + f1 <- Finhom(X, lambda=fit, update=TRUE) 108s + f3 <- Finhom(X, lambda=lam, lmin=lmin) 108s + } 108s + if(!FULLTEST) reset.spatstat.options() 108s + }) 108s > 108s BEGIN TEST testsD.R 108s 108s R version 4.4.3 (2025-02-28) -- "Trophy Case" 108s Copyright (C) 2025 The R Foundation for Statistical Computing 108s Platform: x86_64-pc-linux-gnu 108s 108s R is free software and comes with ABSOLUTELY NO WARRANTY. 108s You are welcome to redistribute it under certain conditions. 108s Type 'license()' or 'licence()' for distribution details. 108s 108s R is a collaborative project with many contributors. 108s Type 'contributors()' for more information and 108s 'citation()' on how to cite R or R packages in publications. 108s 108s Type 'demo()' for some demos, 'help()' for on-line help, or 108s 'help.start()' for an HTML browser interface to help. 108s Type 'q()' to quit R. 108s 109s > #' 109s > #' Header for all (concatenated) test files 109s > #' 109s > #' Require spatstat.model 109s > #' Obtain environment variable controlling tests. 109s > #' 109s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 109s > 109s > require(spatstat.model) 109s Loading required package: spatstat.model 109s Loading required package: spatstat.data 109s Loading required package: spatstat.univar 109s spatstat.univar 3.1-2 109s Loading required package: spatstat.geom 109s spatstat.geom 3.3-6 109s Loading required package: spatstat.random 109s spatstat.random 3.3-3 109s Loading required package: spatstat.explore 109s Loading required package: nlme 110s spatstat.explore 3.3-4 110s Loading required package: rpart 110s spatstat.model 3.3-4 110s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 110s > ALWAYS <- TRUE 110s > cat(paste("--------- Executing", 110s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 110s + "test code -----------\n")) 110s --------- Executing **RESTRICTED** subset of test code ----------- 110s > #' 110s > #' tests/deltasuffstat.R 110s > #' 110s > #' Explicit tests of 'deltasuffstat' 110s > #' 110s > #' $Revision: 1.4 $ $Date: 2021/01/22 08:08:48 $ 110s > 110s > if(!FULLTEST) 110s + spatstat.options(npixel=32, ndummy.min=16) 110s > 110s > if(ALWAYS) { # depends on C code 110s + local({ 110s + 110s + disagree <- function(x, y, tol=1e-7) { !is.null(x) && !is.null(y) && max(abs(x-y)) > tol } 110s + 110s + flydelta <- function(model, modelname="") { 110s + ## Check execution of different algorithms for 'deltasuffstat' 110s + dSS <- deltasuffstat(model, sparseOK=TRUE) 110s + dBS <- deltasuffstat(model, sparseOK=TRUE, use.special=FALSE, force=TRUE) 110s + dBF <- deltasuffstat(model, sparseOK=FALSE, use.special=FALSE, force=TRUE) 110s + ## Compare results 110s + if(disagree(dBS, dSS)) 110s + stop(paste(modelname, "model: Brute force algorithm disagrees with special algorithm")) 110s + if(disagree(dBF, dBS)) 110s + stop(paste(modelname, "model: Sparse and full versions of brute force algorithm disagree")) 110s + return(invisible(NULL)) 110s + } 110s + 110s + modelS <- ppm(cells ~ x, Strauss(0.13), nd=10) 110s + flydelta(modelS, "Strauss") 110s + 110s + antsub <- ants[c(FALSE,TRUE,FALSE)] 110s + rmat <- matrix(c(130, 90, 90, 60), 2, 2) 110s + 110s + modelM <- ppm(antsub ~ 1, MultiStrauss(rmat), nd=16) 110s + flydelta(modelM, "MultiStrauss") 110s + 110s + modelA <- ppm(antsub ~ 1, HierStrauss(rmat, archy=c(2,1)), nd=16) 110s + flydelta(modelA, "HierStrauss") 110s + }) 110s + 110s + } 113s > 113s > reset.spatstat.options() 113s > #' 113s > #' tests/density.R 113s > #' 113s > #' Test behaviour of density() methods, 113s > #' relrisk(), Smooth() 113s > #' and inhomogeneous summary functions 113s > #' and idw, adaptive.density, intensity 113s > #' and SpatialMedian, SpatialQuantile 113s > #' 113s > #' $Revision: 1.67 $ $Date: 2024/01/29 07:07:16 $ 113s > #' 113s > 113s > if(!FULLTEST) 113s + spatstat.options(npixel=32, ndummy.min=16) 113s > 113s > 113s > local({ 113s + ## likewise 'relrisk.ppm' 113s + fit <- ppm(ants ~ x) 113s + rants <- function(..., model=fit) { 113s + a <- relrisk(model, sigma=100, se=TRUE, ...) 113s + return(TRUE) 113s + } 113s + if(ALWAYS) { 113s + rants() 113s + rants(diggle=TRUE) 113s + rants(edge=FALSE) 113s + rants(at="points") 113s + rants(casecontrol=FALSE) 113s + rants(relative=TRUE) 113s + } 113s + if(FULLTEST) { 113s + rants(diggle=TRUE, at="points") 113s + rants(edge=FALSE, at="points") 113s + rants(casecontrol=FALSE, relative=TRUE) 113s + rants(casecontrol=FALSE,at="points") 113s + rants(relative=TRUE,at="points") 113s + rants(casecontrol=FALSE, relative=TRUE,at="points") 113s + rants(relative=TRUE, control="Cataglyphis", case="Messor") 113s + rants(relative=TRUE, control="Cataglyphis", case="Messor", at="points") 113s + } 113s + ## more than 2 types 113s + fut <- ppm(sporophores ~ x) 113s + if(ALWAYS) { 113s + rants(model=fut) 113s + } 113s + if(FULLTEST) { 113s + rants(model=fut, at="points") 113s + rants(model=fut, relative=TRUE, at="points") 113s + } 113s + if(FULLTEST) { 113s + ## cases of 'intensity' etc 113s + a <- intensity(ppm(amacrine ~ 1)) 113s + } 113s + }) 113s > 113s > reset.spatstat.options() 113s > 113s > #' 113s > #' tests/diagnostique.R 113s > #' 113s > #' Diagnostic tools such as diagnose.ppm, qqplot.ppm 113s > #' 113s > #' $Revision: 1.6 $ $Date: 2020/04/28 12:58:26 $ 113s > #' 113s > 113s > if(FULLTEST) { 113s + local({ 113s + fit <- ppm(cells ~ x) 113s + diagE <- diagnose.ppm(fit, type="eem") 113s + diagI <- diagnose.ppm(fit, type="inverse") 113s + diagP <- diagnose.ppm(fit, type="Pearson") 113s + plot(diagE, which="all") 113s + plot(diagI, which="smooth") 113s + plot(diagP, which="x") 113s + plot(diagP, which="marks", plot.neg="discrete") 113s + plot(diagP, which="marks", plot.neg="contour") 113s + plot(diagP, which="smooth", srange=c(-5,5)) 113s + plot(diagP, which="smooth", plot.smooth="contour") 113s + plot(diagP, which="smooth", plot.smooth="image") 113s + 113s + fitS <- ppm(cells ~ x, Strauss(0.08)) 113s + diagES <- diagnose.ppm(fitS, type="eem", clip=FALSE) 113s + diagIS <- diagnose.ppm(fitS, type="inverse", clip=FALSE) 113s + diagPS <- diagnose.ppm(fitS, type="Pearson", clip=FALSE) 113s + plot(diagES, which="marks", plot.neg="imagecontour") 113s + plot(diagPS, which="marks", plot.neg="discrete") 113s + plot(diagPS, which="marks", plot.neg="contour") 113s + plot(diagPS, which="smooth", plot.smooth="image") 113s + plot(diagPS, which="smooth", plot.smooth="contour") 113s + plot(diagPS, which="smooth", plot.smooth="persp") 113s + 113s + #' infinite reach, not border-corrected 113s + fut <- ppm(cells ~ x, Softcore(0.5), correction="isotropic") 113s + diagnose.ppm(fut) 113s + 113s + #' 113s + diagPX <- diagnose.ppm(fit, type="Pearson", cumulative=FALSE) 113s + plot(diagPX, which="y") 113s + 113s + #' simulation based 113s + e <- envelope(cells, nsim=4, savepatterns=TRUE, savefuns=TRUE) 113s + Plist <- rpoispp(40, nsim=5) 113s + 113s + qf <- qqplot.ppm(fit, nsim=4, expr=e, plot.it=FALSE) 113s + print(qf) 113s + qp <- qqplot.ppm(fit, nsim=5, expr=Plist, fast=FALSE) 113s + print(qp) 113s + qp <- qqplot.ppm(fit, nsim=5, expr=expression(rpoispp(40)), plot.it=FALSE) 113s + print(qp) 113s + qg <- qqplot.ppm(fit, nsim=5, style="classical", plot.it=FALSE) 113s + print(qg) 113s + 113s + #' lurking.ppm 113s + #' covariate is numeric vector 113s + fitx <- ppm(cells ~ x) 113s + yvals <- coords(as.ppp(quad.ppm(fitx)))[,"y"] 113s + lurking(fitx, yvals) 113s + #' covariate is stored but is not used in model 113s + Z <- as.im(function(x,y){ x+y }, Window(cells)) 113s + fitxx <- ppm(cells ~ x, data=solist(Zed=Z), allcovar=TRUE) 113s + lurking(fitxx, expression(Zed)) 113s + #' envelope is a ppplist; length < nsim; glmdata=NULL 113s + fit <- ppm(cells ~ 1) 113s + stuff <- lurking(fit, expression(x), envelope=Plist, plot.sd=FALSE) 113s + #' plot.lurk 113s + plot(stuff, shade=NULL) 113s + }) 113s + } 113s > 113s > #' 113s > #' tests/deepeepee.R 113s > #' 113s > #' Tests for determinantal point process models 113s > #' 113s > #' $Revision: 1.9 $ $Date: 2022/04/24 09:14:46 $ 113s > 113s > local({ 113s + if(ALWAYS) { 113s + #' simulate.dppm 113s + jpines <- residualspaper$Fig1 113s + fit <- dppm(jpines ~ 1, dppGauss) 113s + set.seed(10981) 113s + simulate(fit, W=square(5)) 113s + } 113s + if(FULLTEST) { 113s + #' simulate.detpointprocfamily - code blocks 113s + model <- dppGauss(lambda=100, alpha=.05, d=2) 113s + simulate(model, seed=1999, correction="border") 113s + u <- is.stationary(model) 113s + #' other methods for dppm 113s + kay <- Kmodel(fit) 113s + gee <- pcfmodel(fit) 113s + lam <- intensity(fit) 113s + arr <- reach(fit) 113s + pah <- parameters(fit) 113s + #' a user bug report - matrix dimension error 113s + set.seed(256) 113s + dat <- simulate( dppGauss(lambda = 8.5, alpha = 0.1, d = 2), nsim = 1) 113s + } 113s + if(FULLTEST) { 113s + ## cover print.summary.dppm 113s + jpines <- japanesepines[c(TRUE,FALSE,FALSE,FALSE)] 113s + print(summary(dppm(jpines ~ 1, dppGauss))) 113s + print(summary(dppm(jpines ~ 1, dppGauss, method="c"))) 113s + print(summary(dppm(jpines ~ 1, dppGauss, method="p"))) 113s + print(summary(dppm(jpines ~ 1, dppGauss, method="a"))) 113s + } 113s + #' dppeigen code blocks 113s + if(ALWAYS) { 113s + mod <- dppMatern(lambda=2, alpha=0.01, nu=1, d=2) 113s + uT <- dppeigen(mod, trunc=1.1, Wscale=c(1,1), stationary=TRUE) 113s + } 113s + if(FULLTEST) { 113s + uF <- dppeigen(mod, trunc=1.1, Wscale=c(1,1), stationary=FALSE) 113s + vT <- dppeigen(mod, trunc=0.98, Wscale=c(1,1), stationary=TRUE) 113s + vF <- dppeigen(mod, trunc=0.98, Wscale=c(1,1), stationary=FALSE) 113s + } 113s + }) 114s > 114s BEGIN TEST testsEtoF.R 114s 114s R version 4.4.3 (2025-02-28) -- "Trophy Case" 114s Copyright (C) 2025 The R Foundation for Statistical Computing 114s Platform: x86_64-pc-linux-gnu 114s 114s R is free software and comes with ABSOLUTELY NO WARRANTY. 114s You are welcome to redistribute it under certain conditions. 114s Type 'license()' or 'licence()' for distribution details. 114s 114s R is a collaborative project with many contributors. 114s Type 'contributors()' for more information and 114s 'citation()' on how to cite R or R packages in publications. 114s 114s Type 'demo()' for some demos, 'help()' for on-line help, or 114s 'help.start()' for an HTML browser interface to help. 114s Type 'q()' to quit R. 114s 114s > #' 114s > #' Header for all (concatenated) test files 114s > #' 114s > #' Require spatstat.model 114s > #' Obtain environment variable controlling tests. 114s > #' 114s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 114s > 114s > require(spatstat.model) 114s Loading required package: spatstat.model 114s Loading required package: spatstat.data 115s Loading required package: spatstat.univar 115s spatstat.univar 3.1-2 115s Loading required package: spatstat.geom 115s spatstat.geom 3.3-6 115s Loading required package: spatstat.random 115s spatstat.random 3.3-3 115s Loading required package: spatstat.explore 115s Loading required package: nlme 115s spatstat.explore 3.3-4 115s Loading required package: rpart 115s spatstat.model 3.3-4 115s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 115s > ALWAYS <- TRUE 115s > cat(paste("--------- Executing", 115s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 115s + "test code -----------\n")) 115s --------- Executing **RESTRICTED** subset of test code ----------- 115s > # 115s > # tests/envelopes.R 115s > # 115s > # Test validity of envelope data 115s > # 115s > # $Revision: 1.29 $ $Date: 2024/01/10 13:45:29 $ 115s > # 115s > 115s > local({ 115s + 115s + 115s + checktheo <- function(fit) { 115s + fitname <- deparse(substitute(fit)) 115s + en <- envelope(fit, nsim=4, verbose=FALSE, nrep=1e3) 115s + nama <- names(en) 115s + expecttheo <- is.poisson(fit) && is.stationary(fit) 115s + context <- paste("Envelope of", fitname) 115s + if(expecttheo) { 115s + if(!("theo" %in% nama)) 115s + stop(paste(context, "did not contain", sQuote("theo"))) 115s + if("mmean" %in% nama) 115s + stop(paste(context, "unexpectedly contained", sQuote("mmean"))) 115s + } else { 115s + if("theo" %in% nama) 115s + stop(paste(context, "unexpectedly contained", sQuote("theo"))) 115s + if(!("mmean" %in% nama)) 115s + stop(paste(context, "did not contain", sQuote("mmean"))) 115s + } 115s + cat(paste(context, "has correct format\n")) 115s + } 115s + 115s + if(ALWAYS) { 115s + checktheo(ppm(cells ~x)) 115s + } 115s + if(FULLTEST) { 115s + checktheo(ppm(cells)) 115s + checktheo(ppm(cells ~1, Strauss(0.1))) 115s + } 115s + 115s + 115s + #' check savefuns/savepatterns with global 115s + fit <- ppm(cells~x) 115s + if(ALWAYS) Ef <- envelope(fit, Kest, nsim=4, savefuns=TRUE, global=TRUE) 115s + if(FULLTEST) Ep <- envelope(fit, Kest, nsim=4, savepatterns=TRUE, global=TRUE) 115s + #' check handling of 'dangerous' cases 115s + if(FULLTEST) { 115s + fut <- ppm(redwood ~ x) 115s + Ek <- envelope(fut, Kinhom, update=FALSE, nsim=4) 115s + kfut <- kppm(redwood3 ~ x) 115s + Ekk <- envelope(kfut, Kinhom, lambda=density(redwood3), nsim=7) 115s + } 115s + 115s + 115s + if(ALWAYS) { # invokes C code 115s + fit <- ppm(japanesepines ~ 1, Strauss(0.04)) 115s + e6 <- envelope(fit, Kest, nsim=4, fix.n=TRUE) 115s + fit2 <- ppm(amacrine ~ 1, Strauss(0.03)) 115s + e7 <- envelope(fit2, Gcross, nsim=4, fix.marks=TRUE) 115s + } 115s + 115s + 115s + if(FULLTEST) { 115s + fit <- ppm(cells ~ 1, Strauss(0.07)) 115s + U <- envelope(fit, nsim=3, simulate=expression(runifpoint(20))) 115s + kfit <- kppm(redwood3 ~ x) 115s + UU <- envelope(kfit, nsim=7, simulate=expression(simulate(kfit, drop=TRUE))) 115s + VV <- envelope(kfit, nsim=7, weights=1:7) 115s + MM <- envelope(kfit, nsim=7, Kinhom, lambda=density(redwood3)) 115s + } 115s + 115s + if(FULLTEST) { 115s + ## from Marcelino de la Cruz - scoping in update.ppm 115s + X <- cells 115s + Z <- density(X) 115s + pfit <- ppm(X ~ Z) 115s + cat("Fitted ppm(X~Z)", fill=TRUE) 115s + penv <- envelope(pfit, Kinhom, lambda=pfit, nsim=3) 115s + RX <- rotate(X, pi/3, centre="centroid") 115s + RZ <- density(RX) 115s + Rpfit <- ppm(RX ~ RZ) 115s + cat("Fitted ppm(RX~RZ)", fill=TRUE) 115s + Rpenv <- envelope(Rpfit, Kinhom, lambda=Rpfit, nsim=3) 115s + } 115s + 115s + if(FULLTEST) { 115s + #' envelope computations in other functions 115s + P <- lurking(cells, expression(x), envelope=TRUE, nsim=9) 115s + print(P) 115s + #' re-using envelope objects in other functions 115s + A <- envelope(cells, nsim=9, savepatterns=TRUE, savefuns=TRUE) 115s + S <- lurking(cells, expression(x), envelope=A, nsim=9) 115s + #' envelope.envelope 115s + B <- envelope(cells, nsim=5, savepatterns=TRUE, savefuns=FALSE) 115s + envelope(B) 115s + } 115s + 115s + 115s + 115s + ## close 'local' 115s + }) 115s Envelope of ppm(cells ~ x) has correct format 116s Generating 8 simulated realisations of fitted Poisson model (4 to estimate the 116s mean and 4 to calculate envelopes) ... 116s 1, 2, 3, 4, 5, 6, 7, 116s 8. 116s 116s Done. 116s Generating 4 simulated realisations of fitted Gibbs model with fixed number of 116s points ... 116s 1, 2, 3, 116s 4. 116s 116s Done. 116s Generating 4 simulated realisations of fitted Gibbs model with fixed number of 116s points of each type ... 116s 1, 2, 3, The formula does not involve “g” and is therefore unchanged 116s Don't know how to reduce the term “sin(x - z)” 116s 116s 4. 116s 116s Done. 116s > #' tests/enveltest.R 116s > #' Envelope tests (dclf.test, mad.test) 116s > #' and two-stage tests (bits.test, dg.test, bits.envelope, dg.envelope) 116s > #' 116s > #' $Revision: 1.3 $ $Date: 2020/04/28 12:58:26 $ 116s > #' 116s > if(FULLTEST) { 116s + local({ 116s + #' handling of NA function values (due to empty point patterns) 116s + set.seed(1234) 116s + X <- rThomas(5, 0.05, 10) 116s + fit <- kppm(X ~ 1, "Thomas") 116s + set.seed(100000) 116s + dclf.test(fit) 116s + set.seed(909) 116s + dg.test(fit, nsim=9) 116s + #' other code blocks 116s + dclf.test(fit, rinterval=c(0, 3), nsim=9) 116s + envelopeTest(X, exponent=3, clamp=TRUE, nsim=9) 116s + }) 116s + } 116s > # 116s > # tests/fastgeyer.R 116s > # 116s > # checks validity of fast C implementation of Geyer interaction 116s > # 116s > # $Revision: 1.4 $ $Date: 2020/04/28 12:58:26 $ 116s > # 116s > if(FULLTEST) { # depends on hardware 116s + local({ 116s + X <- redwood 116s + Q <- quadscheme(X) 116s + U <- union.quad(Q) 116s + EP <- equalpairs.quad(Q) 116s + G <- Geyer(0.11, 2) 116s + # The value r=0.11 is chosen to avoid hardware numerical effects (gcc bug 323). 116s + # It avoids being close any value of pairdist(redwood). 116s + # The nearest such values are 0.1077.. and 0.1131.. 116s + # By contrast if r = 0.1 there are values differing from 0.1 by 3e-17 116s + a <- pairsat.family$eval(X,U,EP,G$pot,G$par,"border") 116s + b <- G$fasteval(X,U,EP,G$pot,G$par,"border") 116s + if(!all(a==b)) 116s + stop("Results of Geyer()$fasteval and pairsat.family$eval do not match") 116s + # ... 116s + # and again for a non-integer value of 'sat' 116s + # (spotted by Thordis Linda Thorarinsdottir) 116s + G <- Geyer(0.11, 2.5) 116s + a <- pairsat.family$eval(X,U,EP,G$pot,G$par,"border") 116s + b <- G$fasteval(X,U,EP,G$pot,G$par,"border") 116s + if(!all(a==b)) 116s + stop("Results of Geyer()$fasteval and pairsat.family$eval do not match when sat is not an integer") 116s + # and again for sat < 1 116s + # (spotted by Rolf) 116s + G <- Geyer(0.11, 0.5) 116s + a <- pairsat.family$eval(X,U,EP,G$pot,G$par,"border") 116s + b <- G$fasteval(X,U,EP,G$pot,G$par,"border") 116s + if(!all(a==b)) 116s + stop("Results of Geyer()$fasteval and pairsat.family$eval do not match when sat < 1") 116s + }) 116s + } 116s > 116s > #' tests/formuli.R 116s > #' 116s > #' Test machinery for manipulating formulae 116s > #' 116s > #' $Revision: 1.7 $ $Date: 2020/04/28 12:58:26 $ 116s > 116s > local({ 116s + 116s + ff <- function(A, deletevar, B) { 116s + D <- reduceformula(A, deletevar) 116s + if(!spatstat.utils::identical.formulae(D, B)) { 116s + AD <- as.expression(substitute(reduceformula(A,d), 116s + list(A=A, d=deletevar))) 116s + stop(paste(AD, "\n\tyields ", spatstat.utils::pasteFormula(D), 116s + " instead of ", spatstat.utils::pasteFormula(B)), 116s + call.=FALSE) 116s + } 116s + invisible(NULL) 116s + } 116s + 116s + ff(~ x + z, "x", ~z) 116s + 116s + ff(y ~ x + z, "x", y~z) 116s + 116s + ff(~ I(x^2) + z, "x", ~z) 116s + 116s + ff(y ~ poly(x,2) + poly(z,3), "x", y ~poly(z,3)) 116s + 116s + ff(y ~ x + z, "g", y ~ x + z) 116s + 116s + reduceformula(y ~ x+z, "g", verbose=TRUE) 116s + reduceformula(y ~ sin(x-z), "z", verbose=TRUE) 116s + 116s + illegal.iformula(~str*g, itags="str", dfvarnames=c("marks", "g", "x", "y")) 116s + }) 116s NULL 116s > 116s > 116s > 116s > ## 116s > ## tests/funnymarks.R 116s > ## 116s > ## tests involving strange mark values 116s > ## $Revision: 1.7 $ $Date: 2020/04/28 12:58:26 $ 116s > 116s > if(ALWAYS) { # depends on locale 116s + local({ 116s + ## ppm() where mark levels contain illegal characters 116s + hyphenated <- c("a", "not-a") 116s + spaced <- c("U", "non U") 116s + suffixed <- c("a+", "a*") 116s + charred <- c("+", "*") 116s + 116s + irad <- matrix(0.1, 2,2) 116s + hrad <- matrix(0.005, 2, 2) 116s + 116s + tryit <- function(types, X, irad, hrad) { 116s + levels(marks(X)) <- types 116s + fit <- ppm(X ~marks + polynom(x,y,2), 116s + MultiStraussHard(types=types,iradii=irad,hradii=hrad)) 116s + print(fit) 116s + print(coef(fit)) 116s + val <- fitted(fit) 116s + pred <- predict(fit) 116s + return(invisible(NULL)) 116s + } 116s + 116s + tryit(hyphenated, amacrine, irad, hrad) 116s + tryit(spaced, amacrine, irad, hrad) 116s + tryit(suffixed, amacrine, irad, hrad) 116s + tryit(charred, amacrine, irad, hrad) 116s + 116s + ## marks which are dates 116s + X <- cells 116s + n <- npoints(X) 116s + endoftime <- rep(ISOdate(2001,1,1), n) 116s + eotDate <- rep(as.Date("2001-01-01"), n) 116s + markformat(endoftime) 116s + markformat(eotDate) 116s + marks(X) <- endoftime 116s + print(X) 116s + Y <- X %mark% data.frame(id=1:42, date=endoftime, dd=eotDate) 116s + print(Y) 116s + md <- markformat(endoftime) 116s + 116s + ## mark formats 116s + Z <- Y 116s + marks(Z) <- marks(Z)[1,,drop=FALSE] 116s + ms <- markformat(solist(cells, redwood)) 116s + marks(Z) <- factor(1:npoints(Z)) 116s + marks(Z)[12] <- NA 116s + mz <- is.multitype(Z) 116s + cZ <- coerce.marks.numeric(Z) 116s + marks(Z) <- data.frame(n=1:npoints(Z), 116s + a=factor(sample(letters, npoints(Z), replace=TRUE))) 116s + cZ <- coerce.marks.numeric(Z) 116s + stopifnot(is.multitype(cells %mark% data.frame(a=factor(1:npoints(cells))))) 116s + 116s + a <- numeric.columns(finpines) 116s + b1 <- numeric.columns(amacrine) 116s + b2 <- coerce.marks.numeric(amacrine) 116s + d <- numeric.columns(cells) 116s + f <- numeric.columns(longleaf) 116s + ff <- data.frame(a=factor(letters[1:10]), y=factor(sample(letters, 10))) 116s + numeric.columns(ff) 116s + 116s + ## mark operations 116s + df <- data.frame(x=1:2, y=sample(letters, 2)) 116s + h <- hyperframe(z=1:2, p=solist(cells, cells)) 116s + a <- NULL %mrep% 3 116s + a <- 1:4 %mrep% 3 116s + a <- df %mrep% 3 116s + a <- h %mrep% 3 116s + b <- markcbind(df, h) 116s + b <- markcbind(h, df) 116s + }) 116s + } 117s Nonstationary Multitype Strauss Hardcore process 117s Fitted to point pattern dataset ‘X’ 117s 117s Possible marks: ‘a’ and ‘not-a’ 117s 117s Log trend: ~marks + (x + y + I(x^2) + I(x * y) + I(y^2)) 117s 117s Fitted trend coefficients: 117s (Intercept) marksnot-a x y I(x^2) I(x * y) 117s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 0.3384324 117s I(y^2) 117s -0.5425654 117s 117s 2 types of points 117s Possible types: 117s [1] a not-a 117s Interaction radii: 117s a not-a 117s a 0.1 0.1 117s not-a 0.1 0.1 117s Hardcore radii: 117s a not-a 117s a 0.005 0.005 117s not-a 0.005 0.005 117s Fitted interaction parameters gamma_ij 117s a not-a 117s a 0.2699920 0.8920719 117s not-a 0.8920719 0.2694374 117s 117s Relevant coefficients: 117s markaxa markaxnot.a marknot.axnot.a 117s -1.3093629 -0.1142086 -1.3114192 117s 117s For standard errors, type coef(summary(x)) 117s (Intercept) marksnot-a x y I(x^2) 117s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 117s I(x * y) I(y^2) markaxa markaxnot.a marknot.axnot.a 117s 0.3384324 -0.5425654 -1.3093629 -0.1142086 -1.3114192 117s Nonstationary Multitype Strauss Hardcore process 117s Fitted to point pattern dataset ‘X’ 117s 117s Possible marks: ‘U’ and ‘non U’ 117s 117s Log trend: ~marks + (x + y + I(x^2) + I(x * y) + I(y^2)) 117s 117s Fitted trend coefficients: 117s (Intercept) marksnon U x y I(x^2) I(x * y) 117s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 0.3384324 117s I(y^2) 117s -0.5425654 117s 117s 2 types of points 117s Possible types: 117s [1] U non U 117s Interaction radii: 117s U non U 117s U 0.1 0.1 117s non U 0.1 0.1 117s Hardcore radii: 117s U non U 117s U 0.005 0.005 117s non U 0.005 0.005 117s Fitted interaction parameters gamma_ij 117s U non U 117s U 0.2699920 0.8920719 117s non U 0.8920719 0.2694374 117s 117s Relevant coefficients: 117s markUxU markUxnon.U marknon.Uxnon.U 117s -1.3093629 -0.1142086 -1.3114192 117s 117s For standard errors, type coef(summary(x)) 117s (Intercept) marksnon U x y I(x^2) 117s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 117s I(x * y) I(y^2) markUxU markUxnon.U marknon.Uxnon.U 117s 0.3384324 -0.5425654 -1.3093629 -0.1142086 -1.3114192 117s Nonstationary Multitype Strauss Hardcore process 117s Fitted to point pattern dataset ‘X’ 117s 117s Possible marks: ‘a+’ and ‘a*’ 117s 117s Log trend: ~marks + (x + y + I(x^2) + I(x * y) + I(y^2)) 117s 117s Fitted trend coefficients: 117s (Intercept) marksa* x y I(x^2) I(x * y) 117s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 0.3384324 117s I(y^2) 117s -0.5425654 117s 117s 2 types of points 117s Possible types: 117s [1] a+ a* 117s Interaction radii: 117s a+ a* 117s a+ 0.1 0.1 117s a* 0.1 0.1 117s Hardcore radii: 117s a+ a* 117s a+ 0.005 0.005 117s a* 0.005 0.005 117s Fitted interaction parameters gamma_ij 117s a+ a* 117s a+ 0.2699920 0.8920719 117s a* 0.8920719 0.2694374 117s 117s Relevant coefficients: 117s marka.xa. marka.xa..1 marka..1xa..1 117s -1.3093629 -0.1142086 -1.3114192 117s 117s For standard errors, type coef(summary(x)) 117s (Intercept) marksa* x y I(x^2) 117s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 117s I(x * y) I(y^2) marka.xa. marka.xa..1 marka..1xa..1 117s 0.3384324 -0.5425654 -1.3093629 -0.1142086 -1.3114192 117s Nonstationary Multitype Strauss Hardcore process 117s Fitted to point pattern dataset ‘X’ 117s 117s Possible marks: ‘+’ and ‘*’ 117s 117s Log trend: ~marks + (x + y + I(x^2) + I(x * y) + I(y^2)) 117s 117s Fitted trend coefficients: 117s (Intercept) marks* x y I(x^2) I(x * y) 117s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 0.3384324 117s I(y^2) 117s -0.5425654 117s 117s 2 types of points 117s Possible types: 117s [1] + * 117s Interaction radii: 117s + * 117s + 0.1 0.1 117s * 0.1 0.1 117s Hardcore radii: 117s + * 117s + 0.005 0.005 117s * 0.005 0.005 117s Fitted interaction parameters gamma_ij 117s + * 117s + 0.2699920 0.8920719 117s * 0.8920719 0.2694374 117s 117s Relevant coefficients: 117s markX.xX. markX.xX..1 markX..1xX..1 117s -1.3093629 -0.1142086 -1.3114192 117s 117s For standard errors, type coef(summary(x)) 117s (Intercept) marks* x y I(x^2) 117s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 117s I(x * y) I(y^2) markX.xX. markX.xX..1 markX..1xX..1 117s 0.3384324 -0.5425654 -1.3093629 -0.1142086 -1.3114192 117s Marked planar point pattern: 42 points 117s marks are dates, of class ‘POSIXt’ 117s window: rectangle = [0, 1] x [0, 1] units 117s Marked planar point pattern: 42 points 117s Mark variables: id, date, dd 117s window: rectangle = [0, 1] x [0, 1] units 117s Warning messages: 117s 1: In is.multitype.ppp(Z) : some mark values are NA in the point pattern Z 117s 2: Factor-valued marks were converted to integer codes 117s 3: Factor-valued mark variable ‘a’ was converted to integer codes 117s 4: Factor-valued marks were converted to integer codes 117s > 117s BEGIN TEST testsGtoJ.R 117s 117s R version 4.4.3 (2025-02-28) -- "Trophy Case" 117s Copyright (C) 2025 The R Foundation for Statistical Computing 117s Platform: x86_64-pc-linux-gnu 117s 117s R is free software and comes with ABSOLUTELY NO WARRANTY. 117s You are welcome to redistribute it under certain conditions. 117s Type 'license()' or 'licence()' for distribution details. 117s 117s R is a collaborative project with many contributors. 117s Type 'contributors()' for more information and 117s 'citation()' on how to cite R or R packages in publications. 117s 117s Type 'demo()' for some demos, 'help()' for on-line help, or 117s 'help.start()' for an HTML browser interface to help. 117s Type 'q()' to quit R. 117s 118s > #' 118s > #' Header for all (concatenated) test files 118s > #' 118s > #' Require spatstat.model 118s > #' Obtain environment variable controlling tests. 118s > #' 118s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 118s > 118s > require(spatstat.model) 118s Loading required package: spatstat.model 118s Loading required package: spatstat.data 118s Loading required package: spatstat.univar 118s spatstat.univar 3.1-2 118s Loading required package: spatstat.geom 118s spatstat.geom 3.3-6 118s Loading required package: spatstat.random 118s spatstat.random 3.3-3 118s Loading required package: spatstat.explore 118s Loading required package: nlme 119s spatstat.explore 3.3-4 119s Loading required package: rpart 119s spatstat.model 3.3-4 119s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 119s > ALWAYS <- TRUE 119s > cat(paste("--------- Executing", 119s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 119s + "test code -----------\n")) 119s --------- Executing **RESTRICTED** subset of test code ----------- 119s > #' 119s > #' tests/hobjects.R 119s > #' 119s > #' Validity of methods for ppm(... method="ho") 119s > #' 119s > #' $Revision: 1.4 $ $Date: 2022/06/18 10:14:44 $ 119s > 119s > 119s > if(FULLTEST) { 119s + local({ 119s + set.seed(42) 119s + fit <- ppm(cells ~1, Strauss(0.1), improve.type="ho", nsim=10) 119s + fitx <- ppm(cells ~offset(x), Strauss(0.1), improve.type="ho", nsim=10) 119s + 119s + a <- AIC(fit) 119s + ax <- AIC(fitx) 119s + 119s + f <- fitted(fit) 119s + fx <- fitted(fitx) 119s + 119s + p <- predict(fit) 119s + px <- predict(fitx) 119s + }) 119s + } 119s > 119s > 119s > #' tests/hypotests.R 119s > #' Hypothesis tests 119s > #' 119s > #' $Revision: 1.10 $ $Date: 2023/07/17 07:30:48 $ 119s > 119s > if(FULLTEST) { 119s + local({ 119s + 119s + #' scan test with baseline 119s + fit <- ppm(cells ~ x) 119s + lam <- predict(fit) 119s + rr <- c(0.05, 1) 119s + scan.test(cells, rr, nsim=5, 119s + method="poisson", baseline=fit, alternative="less") 119s + scan.test(cells, rr, nsim=5, 119s + method="poisson", baseline=lam, alternative="less") 119s + }) 119s + } 119s > #' 119s > #' tests/interact.R 119s > #' 119s > #' Support for interaction objects 119s > #' 119s > #' $Revision: 1.2 $ $Date: 2020/04/28 12:58:26 $ 119s > 119s > if(FULLTEST) { 119s + local({ 119s + #' print.intermaker 119s + Strauss 119s + Geyer 119s + Ord 119s + #' intermaker 119s + BS <- get("BlankStrauss", envir=environment(Strauss)) 119s + BD <- function(r) { instantiate.interact(BS, list(r=r)) } 119s + BlueDanube <- intermaker(BD, BS) 119s + }) 119s + } 119s > 119s > #' tests/ippm.R 119s > #' Tests of 'ippm' class 119s > #' $Revision: 1.6 $ $Date: 2020/04/28 12:58:26 $ 119s > 119s > if(FULLTEST) { 119s + local({ 119s + # .......... set up example from help file ................. 119s + nd <- 10 119s + gamma0 <- 3 119s + delta0 <- 5 119s + POW <- 3 119s + # Terms in intensity 119s + Z <- function(x,y) { -2*y } 119s + f <- function(x,y,gamma,delta) { 1 + exp(gamma - delta * x^POW) } 119s + # True intensity 119s + lamb <- function(x,y,gamma,delta) { 200 * exp(Z(x,y)) * f(x,y,gamma,delta) } 119s + # Simulate realisation 119s + lmax <- max(lamb(0,0,gamma0,delta0), lamb(1,1,gamma0,delta0)) 119s + set.seed(42) 119s + X <- rpoispp(lamb, lmax=lmax, win=owin(), gamma=gamma0, delta=delta0) 119s + # Partial derivatives of log f 119s + DlogfDgamma <- function(x,y, gamma, delta) { 119s + topbit <- exp(gamma - delta * x^POW) 119s + topbit/(1 + topbit) 119s + } 119s + DlogfDdelta <- function(x,y, gamma, delta) { 119s + topbit <- exp(gamma - delta * x^POW) 119s + - (x^POW) * topbit/(1 + topbit) 119s + } 119s + # irregular score 119s + Dlogf <- list(gamma=DlogfDgamma, delta=DlogfDdelta) 119s + # fit model 119s + fit <- ippm(X ~Z + offset(log(f)), 119s + covariates=list(Z=Z, f=f), 119s + iScore=Dlogf, 119s + start=list(gamma=1, delta=1), 119s + nd=nd) 119s + # fit model with logistic likelihood but without iScore 119s + fitlo <- ippm(X ~Z + offset(log(f)), 119s + method="logi", 119s + covariates=list(Z=Z, f=f), 119s + start=list(gamma=1, delta=1), 119s + nd=nd) 119s + 119s + ## ............. test ippm class support ...................... 119s + Ar <- model.matrix(fit) 119s + Ai <- model.matrix(fit, irregular=TRUE) 119s + An <- model.matrix(fit, irregular=TRUE, keepNA=FALSE) 119s + AS <- model.matrix(fit, irregular=TRUE, subset=(abs(Z) < 0.5)) 119s + 119s + Zr <- model.images(fit) 119s + Zi <- model.images(fit, irregular=TRUE) 119s + ## update.ippm 119s + fit2 <- update(fit, . ~ . + I(Z^2)) 119s + fit0 <- update(fit, 119s + . ~ . - Z, 119s + start=list(gamma=2, delta=4)) 119s + oldfit <- ippm(X, 119s + ~Z + offset(log(f)), 119s + covariates=list(Z=Z, f=f), 119s + iScore=Dlogf, 119s + start=list(gamma=1, delta=1), 119s + nd=nd) 119s + oldfit2 <- update(oldfit, . ~ . + I(Z^2)) 119s + oldfit0 <- update(oldfit, 119s + . ~ . - Z, 119s + start=list(gamma=2, delta=4)) 119s + ## again with logistic 119s + fitlo2 <- update(fitlo, . ~ . + I(Z^2)) 119s + fitlo0 <- update(fitlo, 119s + . ~ . - Z, 119s + start=list(gamma=2, delta=4)) 119s + oldfitlo <- ippm(X, 119s + ~Z + offset(log(f)), 119s + method="logi", 119s + covariates=list(Z=Z, f=f), 119s + start=list(gamma=1, delta=1), 119s + nd=nd) 119s + oldfitlo2 <- update(oldfitlo, . ~ . + I(Z^2)) 119s + oldfitlo0 <- update(oldfitlo, 119s + . ~ . - Z, 119s + start=list(gamma=2, delta=4)) 119s + ## anova.ppm including ippm objects 119s + fit0 <- update(fit, . ~ Z) 119s + fit0lo <- update(fitlo, . ~ Z) 119s + A <- anova(fit0, fit) 119s + Alo <- anova(fit0lo, fitlo) 119s + }) 119s + } 119s > 119s BEGIN TEST testsK.R 119s 119s R version 4.4.3 (2025-02-28) -- "Trophy Case" 119s Copyright (C) 2025 The R Foundation for Statistical Computing 119s Platform: x86_64-pc-linux-gnu 119s 119s R is free software and comes with ABSOLUTELY NO WARRANTY. 119s You are welcome to redistribute it under certain conditions. 119s Type 'license()' or 'licence()' for distribution details. 119s 119s R is a collaborative project with many contributors. 119s Type 'contributors()' for more information and 119s 'citation()' on how to cite R or R packages in publications. 119s 119s Type 'demo()' for some demos, 'help()' for on-line help, or 119s 'help.start()' for an HTML browser interface to help. 119s Type 'q()' to quit R. 119s 119s > #' 119s > #' Header for all (concatenated) test files 119s > #' 119s > #' Require spatstat.model 119s > #' Obtain environment variable controlling tests. 119s > #' 119s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 119s > 119s > require(spatstat.model) 119s Loading required package: spatstat.model 119s Loading required package: spatstat.data 120s Loading required package: spatstat.univar 120s spatstat.univar 3.1-2 120s Loading required package: spatstat.geom 120s spatstat.geom 3.3-6 120s Loading required package: spatstat.random 120s spatstat.random 3.3-3 120s Loading required package: spatstat.explore 120s Loading required package: nlme 120s spatstat.explore 3.3-4 120s Loading required package: rpart 120s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 120s > ALWAYS <- TRUE 120s > cat(paste("--------- Executing", 120s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 120s + "test code -----------\n")) 120s spatstat.model 3.3-4 120s --------- Executing **RESTRICTED** subset of test code ----------- 120s > # 120s > # tests/kppm.R 120s > # 120s > # $Revision: 1.40 $ $Date: 2024/02/26 05:44:02 $ 120s > # 120s > # Test functionality of kppm that once depended on RandomFields 120s > # Test update.kppm for old style kppm objects 120s > 120s > if(!FULLTEST) 120s + spatstat.options(npixel=32, ndummy.min=16) 120s > 120s > local({ 120s + 120s + fit <- kppm(redwood ~1, "Thomas") # sic 120s + fitx <- kppm(redwood ~x, "Thomas", verbose=TRUE) 120s + if(FULLTEST) { 120s + fitx <- update(fit, ~ . + x) 120s + fitM <- update(fit, clusters="MatClust") 120s + fitC <- update(fit, cells) 120s + fitCx <- update(fit, cells ~ x) 120s + #' 120s + Wsub <- owin(c(0, 0.5), c(-0.5, 0)) 120s + Zsub <- (bdist.pixels(Window(redwood)) > 0.1) 120s + fitWsub <- kppm(redwood ~1, "Thomas", subset=Wsub) 120s + fitZsub <- kppm(redwood ~1, "Thomas", subset=Zsub) 120s + fitWsub 120s + 120s + #' various methods 120s + ff <- as.fv(fitx) 120s + uu <- unitname(fitx) 120s + unitname(fitCx) <- "furlong" 120s + mo <- model.images(fitCx) 120s + p <- psib(fit) 120s + px <- psib(fitx) 120s + } 120s + if(ALWAYS) { 120s + Y <- simulate(fitx, seed=42, saveLambda=TRUE)[[1]] 120s + } 120s + 120s + if(FULLTEST) { 120s + #' vcov.kppm different algorithms 120s + vc <- vcov(fitx) 120s + vc2 <- vcov(fitx, fast=TRUE) 120s + vc3 <- vcov(fitx, fast=TRUE, splitup=TRUE) 120s + vc4 <- vcov(fitx, splitup=TRUE) 120s + 120s + ## other code blocks 120s + a <- varcount(fitx, function(x,y){x+1}) # always positive 120s + a <- varcount(fitx, function(x,y){y-1}) # always negative 120s + a <- varcount(fitx, function(x,y){x+y}) # positive or negative 120s + 120s + #' improve.kppm 120s + fitI <- update(fit, improve.type="quasi") 120s + fitxI <- update(fitx, improve.type="quasi") 120s + fitxIs <- update(fitx, improve.type="quasi", fast=FALSE) 120s + #' vcov.kppm 120s + vcI <- vcov(fitxI) 120s + } 120s + 120s + ## plot.kppm including predict.kppm 120s + if(ALWAYS) { 120s + fitMC <- kppm(redwood ~ x, "Thomas") 120s + plot(fitMC) 120s + } 120s + if(FULLTEST) { 120s + fitCL <- kppm(redwood ~ x, "Thomas", method="c") 120s + fitPA <- kppm(redwood ~ x, "Thomas", method="p") 120s + plot(fitCL) 120s + plot(fitPA) 120s + 120s + ## fit with composite likelihood method [thanks to Abdollah Jalilian] 120s + fut <- kppm(redwood ~ x, "VarGamma", method="clik2", nu.ker=-3/8) 120s + kfut <- as.fv(fut) 120s + } 120s + 120s + if(ALWAYS) { 120s + fit0 <- kppm(redwood ~1, "LGCP") 120s + is.poisson(fit0) 120s + Y0 <- simulate(fit0, saveLambda=TRUE)[[1]] 120s + stopifnot(is.ppp(Y0)) 120s + p0 <- psib(fit0) # issues a warning 120s + 120s + if(FULLTEST) { 120s + ## fit LGCP using K function: slow 120s + fit1 <- kppm(redwood ~x, "LGCP", 120s + covmodel=list(model="matern", nu=0.3), 120s + control=list(maxit=3)) 120s + Y1 <- simulate(fit1, saveLambda=TRUE)[[1]] 120s + stopifnot(is.ppp(Y1)) 120s + } 120s + 120s + ## fit LGCP using pcf 120s + fit1p <- kppm(redwood ~x, "LGCP", 120s + covmodel=list(model="matern", nu=0.3), 120s + statistic="pcf") 120s + Y1p <- simulate(fit1p, saveLambda=TRUE)[[1]] 120s + stopifnot(is.ppp(Y1p)) 120s + 120s + ## .. and using different fitting methods 120s + if(FULLTEST) { 120s + fit1pClik <- update(fit1p, method="clik") 120s + fit1pPalm <- update(fit1p, method="palm") 120s + } 120s + 120s + ## shortcut evaluation of pcf 120s + ## (the code being tested is in spatstat.random::clusterinfo.R) 120s + if(FULLTEST) { 120s + putSpatstatVariable("RFshortcut", TRUE) 120s + fitGshort <- kppm(redwood ~ 1, "LGCP", covmodel=list(model="gauss")) 120s + fitSshort <- kppm(redwood ~ 1, "LGCP", covmodel=list(model="stable", alpha=1)) 120s + putSpatstatVariable("RFshortcut", FALSE) 120s + fitGlong <- kppm(redwood ~ 1, "LGCP", covmodel=list(model="gauss")) 120s + fitSlong <- kppm(redwood ~ 1, "LGCP", covmodel=list(model="stable", alpha=1)) 120s + discrepG <- unlist(parameters(fitGshort)) - unlist(parameters(fitGlong)) 120s + discrepS <- unlist(parameters(fitSshort)) - unlist(parameters(fitSlong)) 120s + print(discrepG) 120s + print(discrepS) 120s + if(max(abs(discrepG) > 0.01)) 120s + stop("Discrepancy in short-cut fitting of Gaussian LGCP") 120s + if(max(abs(discrepS) > 0.01)) 120s + stop("Discrepancy in short-cut fitting of stable LGCP") 120s + } 120s + 120s + ## image covariate (a different code block) 120s + xx <- as.im(function(x,y) x, Window(redwood)) 120s + fit1xx <- update(fit1p, . ~ xx, data=solist(xx=xx)) 120s + Y1xx <- simulate(fit1xx, saveLambda=TRUE)[[1]] 120s + stopifnot(is.ppp(Y1xx)) 120s + if(FULLTEST) { 120s + fit1xxVG <- update(fit1xx, clusters="VarGamma", nu=-1/4) 120s + Y1xxVG <- simulate(fit1xxVG, saveLambda=TRUE)[[1]] 120s + stopifnot(is.ppp(Y1xxVG)) 120s + } 120s + fit1xxLG <- update(fit1xx, clusters="LGCP", 120s + covmodel=list(model="matern", nu=0.3), 120s + statistic="pcf") 120s + Y1xxLG <- simulate(fit1xxLG, saveLambda=TRUE, drop=TRUE) 120s + stopifnot(is.ppp(Y1xxLG)) 120s + 120s + # ... and Abdollah's code 120s + if(FULLTEST) { 120s + fit2 <- kppm(redwood ~x, cluster="Cauchy", statistic="K") 120s + Y2 <- simulate(fit2, saveLambda=TRUE)[[1]] 120s + stopifnot(is.ppp(Y2)) 120s + } 120s + } 120s + 120s + }) 120s Fitting cluster model 120s Retrieved cluster model information 120s Algorithm parameters: 120s $rmax 120s NULL 120s 120s $q 120s [1] 0.25 120s 120s $p 120s [1] 2 120s 120s $rmin 120s NULL 120s 120s Using point pattern data 120s Starting parameters: 120s kappa sigma2 120s 62.000000000 0.006173033 120s Calculating summary function...Done. 120s Starting minimum contrast fit 120s Returned from minimum contrast fit 120s Returning from clusterfit 121s Warning messages: 121s > 121s > if(FULLTEST) { 121s + local({ 121s + #' various code blocks 121s + fut <- kppm(redwood, ~x) 121s + fet <- update(fut, redwood3) 121s + fot <- update(fut, trend=~y) 121s 1: Internal error: fvlabels truncated the function name 121s 2: Internal error: fvlabels truncated the function name 121s 3: Internal error: fvlabels truncated the function name 121s 4: In psib.kppm(fit0) : The model is not a cluster process 121s 5: The value of the empirical function ‘pcf’ for r= 0 was Inf. Range of r values was reset to [0.00048828125, 0.25] 121s 6: The value of the empirical function ‘pcf’ for r= 0 was Inf. Range of r values was reset to [0.00048828125, 0.25] 121s 7: The value of the empirical function ‘pcf’ for r= 0 was Inf. Range of r values was reset to [0.00048828125, 0.25] 121s + fit <- kppm(redwoodfull ~ x) 121s + Y <- simulate(fit, window=redwoodfull.extra$regionII, saveLambda=TRUE) 121s + gut <- improve.kppm(fit, type="wclik1") 121s + gut <- improve.kppm(fit, vcov=TRUE, fast.vcov=TRUE, save.internals=TRUE) 121s + hut <- kppm(redwood ~ x, method="clik", weightfun=NULL) 121s + hut <- kppm(redwood ~ x, method="palm", weightfun=NULL) 121s + mut <- kppm(redwood) 121s + nut <- update(mut, Y) 121s + }) 121s + } 121s > 121s > if(FULLTEST) { 121s + local({ 121s + #' minimum contrast code 121s + K <- Kest(redwood) 121s + a <- matclust.estK(K) 121s + a <- thomas.estK(K) 121s + a <- cauchy.estK(K) 121s + a <- vargamma.estK(K) 121s + a <- lgcp.estK(K) 121s + 121s + print(a) 121s + u <- unitname(a) 121s + 121s + g <- pcf(redwood) 121s + a <- matclust.estpcf(g) 121s + a <- thomas.estpcf(g) 121s + a <- cauchy.estpcf(g) 121s + a <- vargamma.estpcf(g) 121s + a <- lgcp.estpcf(g) 121s + 121s + #' auxiliary functions 121s + b <- resolve.vargamma.shape(nu.pcf=1.5) 121s + Z <- clusterfield("Thomas", kappa=1, scale=0.2) 121s + 121s + aa <- NULL 121s + aa <- accumulateStatus(simpleMessage("Woof"), aa) 121s + aa <- accumulateStatus(simpleMessage("Sit"), aa) 121s + aa <- accumulateStatus(simpleMessage("Woof"), aa) 121s + printStatusList(aa) 121s + 121s + RMIN <- 0.01 121s + fit <- kppm(redwood ~ 1, ctrl=list(rmin=RMIN,q=1/2)) 121s + if(fit$Fit$mcfit$ctrl$rmin != RMIN) 121s + stop("kppm did not handle parameter 'rmin' in argument 'ctrl' ") 121s + fit <- kppm(redwood ~ 1, ctrl=list(rmin=0,q=1/2), rmin=RMIN) 121s + if(fit$Fit$mcfit$ctrl$rmin != RMIN) 121s + stop("kppm did not handle parameter 'rmin' in argument 'ctrl'") 121s + 121s + RMIN <- 2 121s + fit <- dppm(swedishpines~1, dppGauss(), ctrl=list(rmin=RMIN,q=1)) 121s + if(fit$Fit$mcfit$ctrl$rmin != RMIN) 121s + stop("dppm did not handle parameter 'rmin' in argument 'ctrl'") 121s + fit <- dppm(swedishpines~1, dppGauss(), ctrl=list(rmin=0,q=1), rmin=RMIN) 121s + if(fit$Fit$mcfit$ctrl$rmin != RMIN) 121s + stop("dppm did not handle argument 'rmin'") 121s + }) 121s + } 121s > 121s > 121s > 121s > if(FULLTEST) { 121s + local({ 121s + #' cover a few code blocks 121s + fut <- kppm(redwood ~ x, method="clik") 121s + print(summary(fut)) 121s + a <- residuals(fut) 121s + fut2 <- kppm(redwood ~ x, "LGCP", method="palm") 121s + print(summary(fut2)) 121s + b <- residuals(fut2) 121s + #' 121s + po <- ppm(redwood ~ 1) 121s + A <- kppmComLik(redwood, Xname="redwood", po=po, clusters="Thomas", 121s + statistic="pcf", statargs=list(), control=list(), 121s + weightfun=NULL, rmax=0.1) 121s + A <- kppmPalmLik(redwood, Xname="redwood", po=po, clusters="Thomas", 121s + statistic="pcf", statargs=list(), control=list(), 121s + weightfun=NULL, rmax=0.1) 121s + }) 121s + } 121s > 121s > reset.spatstat.options() 121s > 121s > #' 121s > #' tests/Kfuns.R 121s > #' 121s > #' Various K and L functions and pcf 121s > #' 121s > #' $Revision: 1.43 $ $Date: 2022/06/17 01:47:08 $ 121s > #' 121s > #' Assumes 'EveryStart.R' was run 121s > 121s > if(FULLTEST) { 121s + Cells <- cells 121s + Amacrine <- amacrine 121s + Redwood <- redwood 121s + } else { 121s + ## reduce numbers of data + dummy points 121s + spatstat.options(npixel=32, ndummy.min=16) 121s + Cells <- cells[c(FALSE, TRUE)] 121s + Amacrine <- amacrine[c(FALSE, TRUE)] 121s + Redwood <- redwood[c(FALSE, TRUE)] 121s + } 121s > 121s > 121s > if(FULLTEST) { 121s + local({ 121s + #' code blocks using fitted model to determine intensity 121s + #' Kinhom 121s + X <- rpoispp(function(x,y) { 100 * x }, 100, square(1)) 121s + fut <- ppm(X ~ x) 121s + Kio <- Kinhom(X, fut, update=FALSE) 121s + Kiu <- Kinhom(X, fut, update=TRUE, diagonal=FALSE) 121s + fit <- ppm(Amacrine ~ marks) 121s + #' lohboot Linhom 121s + Zred <- predict(ppm(Redwood ~ x+y)) 121s + Lred <- lohboot(Redwood, Linhom, lambda=Zred) 121s + #' Kmulti.inhom 121s + K1 <- Kcross.inhom(Amacrine, lambdaX=fit) 121s + On <- split(Amacrine)$on 121s + Off <- split(Amacrine)$off 121s + K4 <- Kcross.inhom(Amacrine, lambdaI=ppm(On), lambdaJ=ppm(Off)) 121s + #' local K functions 121s + fut <- ppm(swedishpines ~ polynom(x,y,2)) 121s + Z <- predict(fut) 121s + Lam <- fitted(fut, dataonly=TRUE) 121s + a <- localLinhom(swedishpines, lambda=fut) 121s + a <- localLinhom(swedishpines, lambda=Z) 121s + a <- localLinhom(swedishpines, lambda=Lam) 121s + a <- localLinhom(swedishpines, lambda=Z, correction="none") 121s + a <- localLinhom(swedishpines, lambda=Z, correction="translate") 121s + #' local cross K functions 121s + fat <- ppm(Amacrine ~ x * marks) 121s + Zed <- predict(fat) 121s + Lum <- fitted(fat, dataonly=TRUE) 121s + moff <- (marks(Amacrine) == "off") 121s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=Zed) 121s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=Lum) 121s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=fat) 121s + a <- localLcross.inhom(Amacrine, from="off", to="on", 121s + lambdaFrom=Lum[moff], lambdaTo=Lum[!moff]) 121s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=Zed, 121s + correction="none") 121s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=Zed, 121s + correction="translate") 121s + #' cases of resolve.lambdacross 121s + h <- resolve.lambdacross(Amacrine, moff, !moff, lambdaX=fat) 121s + h <- resolve.lambdacross(Amacrine, moff, !moff, lambdaX=fat, update=FALSE) 121s + h <- resolve.lambdacross(Amacrine, moff, !moff, 121s + lambdaI=fat, lambdaJ=fat) 121s + h <- resolve.lambdacross(Amacrine, moff, !moff, 121s + lambdaI=fat, lambdaJ=fat, 121s + update=FALSE) 121s + #' lohboot 121s + b <- lohboot(Amacrine, Lcross.inhom, from="off", to="on", lambdaX=Zed) 121s + b <- lohboot(Amacrine, Lcross.inhom, from="off", to="on", lambdaX=Lum) 121s + b <- lohboot(Amacrine, Lcross.inhom, from="off", to="on", lambdaX=fat) 121s + b <- lohboot(Amacrine, Lcross.inhom, from="off", to="on", 121s + lambdaFrom=Lum[moff], lambdaTo=Lum[!moff]) 121s + #' 121s + #' residual K functions etc 121s + #' 121s + rco <- compareFit(Cells, Kcom, 121s + interaction=anylist(P=Poisson(), S=Strauss(0.08)), 121s + same="trans", different="tcom") 121s + fit <- ppm(Cells ~ x, Strauss(0.07)) 121s + K <- Kcom(Cells, model=fit, restrict=TRUE) 121s + }) 121s + } 121s > 121s > reset.spatstat.options() 121s > 121s BEGIN TEST testsL.R 121s 121s R version 4.4.3 (2025-02-28) -- "Trophy Case" 121s Copyright (C) 2025 The R Foundation for Statistical Computing 121s Platform: x86_64-pc-linux-gnu 121s 121s R is free software and comes with ABSOLUTELY NO WARRANTY. 121s You are welcome to redistribute it under certain conditions. 121s Type 'license()' or 'licence()' for distribution details. 121s 121s R is a collaborative project with many contributors. 121s Type 'contributors()' for more information and 121s 'citation()' on how to cite R or R packages in publications. 121s 121s Type 'demo()' for some demos, 'help()' for on-line help, or 121s 'help.start()' for an HTML browser interface to help. 121s Type 'q()' to quit R. 121s 121s > Loading required package: spatstat.model 121s #' 121s > #' Header for all (concatenated) test files 121s > #' 121s > #' Require spatstat.model 121s > #' Obtain environment variable controlling tests. 121s > #' 121s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 121s > 121s > require(spatstat.model) 121s Loading required package: spatstat.data 122s Loading required package: spatstat.univar 122s spatstat.univar 3.1-2 122s Loading required package: spatstat.geom 122s spatstat.geom 3.3-6 122s Loading required package: spatstat.random 122s spatstat.random 3.3-3 122s Loading required package: spatstat.explore 122s Loading required package: nlme 122s spatstat.explore 3.3-4 122s Loading required package: rpart 123s spatstat.model 3.3-4 123s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 123s > ALWAYS <- TRUE 123s > cat(paste("--------- Executing", 123s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 123s + "test code -----------\n")) 123s --------- Executing **RESTRICTED** subset of test code ----------- 123s > ## 123s > ## tests/legacy.R 123s > ## 123s > ## Test that current version of spatstat is compatible with outmoded usage 123s > ## $Revision: 1.3 $ $Date: 2020/04/29 08:55:17 $ 123s > 123s > if(FULLTEST) { 123s + local({ 123s + 123s + ## (1) Old syntax of ppm 123s + ppm(cells, ~x) 123s + 123s + ## (2) Old syntax of MultiStrauss etc. 123s + r <- matrix(3, 2, 2) 123s + a <- MultiStrauss( , r) 123s + a <- MultiStrauss(NULL, r) 123s + a <- MultiHard(, r) 123s + 123s + h <- r/2 123s + a <- MultiStraussHard( , r, h) 123s + 123s + NULL 123s + }) 123s + } 123s > #' 123s > #' tests/leverinf.R 123s > #' 123s > #' leverage and influence for Gibbs models 123s > #' 123s > #' $Revision: 1.35 $ $Date: 2022/06/18 10:15:17 $ 123s > #' 123s > 123s > if(FULLTEST) { 123s + Cells <- cells 123s + Amacrine <- amacrine 123s + Redwood <- redwood 123s + } else { 123s + ## reduce number of data + dummy points 123s + spatstat.options(npixel=32, ndummy.min=16) 123s + Cells <- cells[c(FALSE,TRUE)] 123s + Redwood <- redwood[c(FALSE, TRUE)] 123s + Amacrine <- amacrine[c(FALSE, TRUE)] 123s + } 123s > 123s > local({ 123s + cat("Running non-sparse algorithm...", fill=TRUE) 123s + # original non-sparse algorithm 123s + Leverage <- function(...) leverage(..., sparseOK=FALSE) 123s + Influence <- function(...) influence(..., sparseOK=FALSE) 123s + Dfbetas <- function(...) dfbetas(..., sparseOK=FALSE) 123s + if(ALWAYS) { 123s + ## Strauss()$delta2 123s + fitS <- ppm(Cells ~ x, Strauss(0.12), rbord=0) 123s + levS <- Leverage(fitS) 123s + infS <- Influence(fitS) 123s + dfbS <- Dfbetas(fitS) 123s + ## Geyer()$delta2 123s + fitG <- ppm(Redwood ~ 1, Geyer(0.1, 2), rbord=0) 123s + levG <- Leverage(fitG) 123s + infG <- Influence(fitG) 123s + ## AreaInter()$delta2 123s + fitA <- ppm(Cells ~ 1, AreaInter(0.06), rbord=0, nd=11) 123s + levA <- Leverage(fitA) 123s + infA <- Influence(fitA) 123s + ## pairwise.family$delta2 123s + fitD <- ppm(Cells ~ 1, DiggleGatesStibbard(0.12), rbord=0) 123s + levD <- Leverage(fitD) 123s + infD <- Influence(fitD) 123s + ## DiggleGratton() special code 123s + fitDG <- ppm(Cells ~ 1, DiggleGratton(0.05, 0.12), rbord=0) 123s + levDG <- Leverage(fitDG) 123s + infDG <- Influence(fitDG) 123s + ## ppmInfluence; offset is present; coefficient vector has length 0 123s + fitH <- ppm(Cells ~ 1, Hardcore(0.07)) 123s + levH <- Leverage(fitH) 123s + infH <- Influence(fitH) 123s + ## ppmInfluence; hard core 123s + fitSH <- ppm(Cells ~ 1, StraussHard(0.07, 0.01)) 123s + levSH <- Leverage(fitSH) 123s + infSH <- Influence(fitSH) 123s + ## ppmInfluence; offset is present; coefficient vector has length 1 123s + fitHx <- ppm(Cells ~ x, Hardcore(0.07), rbord=0) 123s + levHx <- Leverage(fitHx) 123s + infHx <- Influence(fitHx) 123s + ## multitype 123s + futAm <- ppm(Amacrine ~ x + marks, Strauss(0.07)) 123s + levAm <- leverage(futAm) 123s + } 123s + 123s + if(FULLTEST) { 123s + ## ......... class support ............................. 123s + ## other methods for classes leverage.ppm and influence.ppm 123s + ## not elsewhere tested 123s + cat("Testing class support...", fill=TRUE) 123s + w <- domain(levS) 123s + w <- Window(infS) 123s + vv <- shift(levS, c(1.2, 1.3)) 123s + vv <- shift(infS, c(1.2, 1.3)) 123s + A <- quadrats(Window(Cells), 2) 123s + a <- integral(levS,domain=A) 123s + b <- integral(infS,domain=A) 123s + u <- Smooth(levS, sigma=0.07) 123s + v <- Smooth(infS, sigma=0.1) 123s + ## plot options 123s + plot(levS, what="exact") 123s + plot(levS, what="nearest") 123s + contour(levS, what="nearest") 123s + persp(levS, what="nearest") 123s + ## plotting for multitype models 123s + plot(levAm) 123s + contour(levAm) 123s + persp(levAm) 123s + plot(levAm, multiplot=FALSE) 123s + contour(levAm, multiplot=FALSE) 123s + } 123s + 123s + if(ALWAYS) { 123s + ## .......... compare algorithms ......................... 123s + ## divide and recombine algorithm 123s + cat("Reduce maximum block side to 50,000 ...", fill=TRUE) 123s + op <- spatstat.options(maxmatrix=50000) 123s + ## non-sparse 123s + levSB <- Leverage(fitS) 123s + infSB <- Influence(fitS) 123s + dfbSB <- Dfbetas(fitS) 123s + } 123s + 123s + chk <- function(x, y, what, 123s + from="single-block and multi-block", 123s + thresh=1e-12) { 123s + if(max(abs(x-y)) > thresh) 123s + stop(paste("Different results for", what, "obtained from", 123s + from, "algorithms"), 123s + call.=FALSE) 123s + invisible(NULL) 123s + } 123s + 123s + if(ALWAYS) { 123s + cat("Compare single-block to multi-block...", fill=TRUE) 123s + chk(marks(as.ppp(infS)), marks(as.ppp(infSB)), "influence") 123s + chk(as.im(levS), as.im(levSB), "leverage") 123s + chk(dfbS$val, dfbSB$val, "dfbetas$value") 123s + chk(dfbS$density, dfbSB$density, "dfbetas$density") 123s + } 123s + 123s + if(FULLTEST) { 123s + ## also check case of zero cif 123s + cat("Check zero cif cases...", fill=TRUE) 123s + levHB <- Leverage(fitH) 123s + infHB <- Influence(fitH) 123s + dfbHB <- Dfbetas(fitH) 123s + levHxB <- Leverage(fitHx) 123s + infHxB <- Influence(fitHx) 123s + dfbHxB <- Dfbetas(fitHx) 123s + } 123s + 123s + ## run all code segments 123s + Everything <- function(model, ...) { ppmInfluence(model, ..., what="all") } 123s + 123s + if(FULLTEST) { 123s + cat("Run full code on AreaInteraction model...", fill=TRUE) 123s + pmiA <- Everything(fitA) 123s + 123s + ## sparse algorithm, with blocks 123s + cat("Run sparse algorithm with blocks...", fill=TRUE) 123s + pmiSSB <- Everything(fitS, sparseOK=TRUE) 123s + ## also check case of zero cif 123s + pmiHSB <- Everything(fitH, sparseOK=TRUE) 123s + pmiSHSB <- Everything(fitSH, sparseOK=TRUE) 123s + pmiHxSB <- Everything(fitHx, sparseOK=TRUE) 123s + 123s + cat("Reinstate maxmatrix...", fill=TRUE) 123s + spatstat.options(op) 123s + } 123s + 123s + if(ALWAYS) { 123s + ## sparse algorithm, no blocks 123s + cat("Compare sparse and non-sparse results...", fill=TRUE) 123s + pmi <- Everything(fitS, sparseOK=TRUE) 123s + levSp <- pmi$leverage 123s + infSp <- pmi$influence 123s + dfbSp <- pmi$dfbetas 123s + chks <- function(...) chk(..., from="sparse and non-sparse") 123s + 123s + chks(marks(as.ppp(infS)), marks(as.ppp(infSp)), "influence") 123s + chks(as.im(levS), as.im(levSp), "leverage") 123s + chks(dfbS$val, dfbSp$val, "dfbetas$value") 123s + chks(dfbS$density, dfbSp$density, "dfbetas$density") 123s + } 123s + 123s + if(ALWAYS) { 123s + #' case of zero cif 123s + cat("zero cif...", fill=TRUE) 123s + pmiH <- Everything(fitH, sparseOK=TRUE) 123s + pmiSH <- Everything(fitSH, sparseOK=TRUE) 123s + pmiHx <- Everything(fitHx, sparseOK=TRUE) 123s + } 123s + if(FULLTEST) { 123s + #' other code blocks - check execution only 123s + cat("other code blocks...", fill=TRUE) 123s + a <- Everything(fitS) 123s + a <- Everything(fitS, method="interpreted") 123s + a <- Everything(fitS, method="interpreted", entrywise=FALSE) 123s + a <- Everything(fitS, entrywise=FALSE) 123s + #' zero cif 123s + b <- Everything(fitSH) 123s + b <- Everything(fitSH, method="interpreted") 123s + b <- Everything(fitSH, method="interpreted", entrywise=FALSE) 123s + b <- Everything(fitSH, entrywise=FALSE) 123s + } 123s + #' NOTE: code for irregular parameters is tested below, and in 'make bookcheck' 123s + 123s + ## ........... logistic fits ....................... 123s + cat("Logistic fits...", fill=TRUE) 123s + #' special algorithm for delta2 123s + fitSlogi <- ppm(Cells ~ x, Strauss(0.12), rbord=0, method="logi") 123s + 123s + if(FULLTEST) { 123s + pmiSlogi <- Everything(fitSlogi) 123s + #' special algorithm for delta2 123s + fitGlogi <- ppm(Redwood ~ 1, Geyer(0.1, 2), rbord=0, method="logi") 123s + pmiGlogi <- Everything(fitGlogi) 123s + #' generic algorithm for delta2 123s + fitDlogi <- ppm(Cells ~ 1, DiggleGatesStibbard(0.12), 123s + rbord=0, method="logi") 123s + pmiDlogi <- Everything(fitDlogi) 123s + #' generic algorithm for delta2 : offset; zero-dimensional 123s + fitHlogi <- ppm(Cells ~ 1, Hardcore(0.07), method="logi") 123s + pmiHlogi <- Everything(fitHlogi) 123s + #' generic algorithm for delta2 : offset; 1-dimensional 123s + fitHxlogi <- ppm(Cells ~ x, Hardcore(0.07), rbord=0, method="logi") 123s + pmiHxlogi <- Everything(fitHxlogi) 123s + #' plotting 123s + plot(leverage(fitSlogi)) 123s + plot(influence(fitSlogi)) 123s + plot(dfbetas(fitSlogi)) 123s + } 123s + 123s + if(ALWAYS) { 123s + #' other code blocks - check execution only 123s + cat("Other code blocks...", fill=TRUE) 123s + b <- Everything(fitSlogi) # i.e. full set of results 123s + b <- Everything(fitSlogi, method="interpreted") 123s + b <- Everything(fitSlogi, method="interpreted", entrywise=FALSE) 123s + b <- Everything(fitSlogi, entrywise=FALSE) 123s + } 123s + 123s + #' irregular parameters 123s + cat("Irregular parameters...", fill=TRUE) 123s + ytoa <- function(x,y, alpha=1) { y^alpha } 123s + lam <- function(x,y,alpha=1) { exp(4 + y^alpha) } 123s + set.seed(90210) 123s + X <- rpoispp(lam, alpha=2) 123s + iScor <- list(alpha=function(x,y,alpha) { alpha * y^(alpha-1) } ) 123s + iHess <- list(alpha=function(x,y,alpha) { alpha * (alpha-1) * y^(alpha-2) } ) 123s + gogo <- function(tag, ..., iS=iScor, iH=iHess) { 123s + cat(tag, fill=TRUE) 123s + #' compute all leverage+influence terms 123s + ppmInfluence(..., what="all", iScore=iS, iHessian=iH) 123s + } 123s + gogogo <- function(hdr, fit) { 123s + cat(hdr, fill=TRUE) 123s + force(fit) 123s + #' try all code options 123s + d <- gogo("a", fit) 123s + d <- gogo("b", fit, method="interpreted") 123s + d <- gogo("c", fit, method="interpreted", entrywise=FALSE) 123s + d <- gogo("d", fit, entrywise=FALSE) 123s + invisible(NULL) 123s + } 123s + gogogo("Offset model...", 123s + ippm(X ~ offset(ytoa), start=list(alpha=1), iterlim=40)) 123s + gogogo("Offset model (logistic) ...", 123s + ippm(X ~ offset(ytoa), start=list(alpha=1), 123s + method="logi", iterlim=40)) 123s + gogogo("Offset+x model...", 123s + ippm(X ~ x + offset(ytoa), start=list(alpha=1), iterlim=40)) 123s + gogogo("Offset+x model (logistic) ...", 123s + ippm(X ~ x + offset(ytoa), start=list(alpha=1), 123s + method="logi", iterlim=40)) 123s + gogogo("Offset model Strauss ...", 123s + ippm(X ~ offset(ytoa), Strauss(0.07), start=list(alpha=1), iterlim=40)) 123s + gogogo("Offset model Strauss (logistic) ...", 123s + ippm(X ~ offset(ytoa), Strauss(0.07), start=list(alpha=1), 123s + method="logi", iterlim=40)) 123s + if(FULLTEST) { 123s + gogogo("Offset+x model Strauss ...", 123s + ippm(X ~ x + offset(ytoa), Strauss(0.07), start=list(alpha=1), 123s + iterlim=40)) 123s + gogogo("Offset+x model Strauss (logistic)...", 123s + ippm(X ~ x + offset(ytoa), Strauss(0.07), start=list(alpha=1), 123s + method="logi", iterlim=40)) 123s + } 123s + #' 123s + if(FULLTEST) { 123s + set.seed(452) 123s + foo <- ppm(Cells ~ 1, Strauss(0.15), improve.type="ho", nsim=5) 123s + aa <- Everything(foo) 123s + 123s + #' Gradient and Hessian obtained by symbolic differentiation 123s + f <- deriv(expression((1+x)^a), 123s + "a", function.arg=c("x", "y", "a"), 123s + hessian=TRUE) 123s + #' check they can be extracted 123s + fit <- ippm(Cells ~offset(f), start=list(a=0.7)) 123s + Everything(fit) 123s + } 123s + }) 123s Running non-sparse algorithm... 129s Reduce maximum block side to 50,000 ... 130s Compare single-block to multi-block... 130s Compare sparse and non-sparse results... 131s zero cif... 133s Logistic fits... 133s Other code blocks... 136s Irregular parameters... 136s Offset model... 136s a 136s b 137s c 137s d 138s Offset model (logistic) ... 138s a 139s b 139s c 140s d 140s Offset+x model... 140s a 141s b 141s c 142s d 142s Offset+x model (logistic) ... 143s a 143s b 144s c 144s d 145s Offset model Strauss ... 145s a 145s Large quadrature scheme split into blocks to avoid memory size limits; 404 dummy points split into 2 blocks, each containing 202 dummy points. Consider increasing the matrix size limit spatstat.options('maxmatrix') if you have sufficient RAM 146s b 146s Large quadrature scheme split into blocks to avoid memory size limits; 404 dummy points split into 2 blocks, each containing 202 dummy points. Consider increasing the matrix size limit spatstat.options('maxmatrix') if you have sufficient RAM 146s c 146s Large quadrature scheme split into blocks to avoid memory size limits; 404 dummy points split into 2 blocks, each containing 202 dummy points. Consider increasing the matrix size limit spatstat.options('maxmatrix') if you have sufficient RAM 147s d 147s Large quadrature scheme split into blocks to avoid memory size limits; 404 dummy points split into 2 blocks, each containing 202 dummy points. Consider increasing the matrix size limit spatstat.options('maxmatrix') if you have sufficient RAM 148s Offset model Strauss (logistic) ... 148s a 148s Large quadrature scheme split into blocks to avoid memory size limits; 400 dummy points split into 2 blocks, each containing 200 dummy points. Consider increasing the matrix size limit spatstat.options('maxmatrix') if you have sufficient RAM 149s b 149s Large quadrature scheme split into blocks to avoid memory size limits; 400 dummy points split into 2 blocks, each containing 200 dummy points. Consider increasing the matrix size limit spatstat.options('maxmatrix') if you have sufficient RAM 150s c 150s Large quadrature scheme split into blocks to avoid memory size limits; 400 dummy points split into 2 blocks, each containing 200 dummy points. Consider increasing the matrix size limit spatstat.options('maxmatrix') if you have sufficient RAM 150s d 150s Large quadrature scheme split into blocks to avoid memory size limits; 400 dummy points split into 2 blocks, each containing 200 dummy points. Consider increasing the matrix size limit spatstat.options('maxmatrix') if you have sufficient RAM 151s > 151s > There were 11 warnings (use warnings() to see them) 151s reset.spatstat.options() 151s > 151s BEGIN TEST testsM.R 151s 151s R version 4.4.3 (2025-02-28) -- "Trophy Case" 151s Copyright (C) 2025 The R Foundation for Statistical Computing 151s Platform: x86_64-pc-linux-gnu 151s 151s R is free software and comes with ABSOLUTELY NO WARRANTY. 151s You are welcome to redistribute it under certain conditions. 151s Type 'license()' or 'licence()' for distribution details. 151s 151s R is a collaborative project with many contributors. 151s Type 'contributors()' for more information and 151s 'citation()' on how to cite R or R packages in publications. 151s 151s Type 'demo()' for some demos, 'help()' for on-line help, or 151s 'help.start()' for an HTML browser interface to help. 151s Type 'q()' to quit R. 151s 151s > #' 151s > #' Header for all (concatenated) test files 151s > #' 151s > #' Require spatstat.model 151s > #' Obtain environment variable controlling tests. 151s > #' 151s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 151s > 151s > require(spatstat.model) 151s Loading required package: spatstat.model 151s Loading required package: spatstat.data 152s Loading required package: spatstat.univar 152s spatstat.univar 3.1-2 152s Loading required package: spatstat.geom 152s spatstat.geom 3.3-6 152s Loading required package: spatstat.random 152s spatstat.random 3.3-3 152s Loading required package: spatstat.explore 152s Loading required package: nlme 152s spatstat.explore 3.3-4 152s Loading required package: rpart 152s spatstat.model 3.3-4 152s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 152s > ALWAYS <- TRUE 152s > cat(paste("--------- Executing", 152s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 152s + "test code -----------\n")) 152s --------- Executing **RESTRICTED** subset of test code ----------- 152s > ## 152s > ## tests/marcelino.R 152s > ## 152s > ## $Revision: 1.4 $ $Date: 2020/04/30 02:18:23 $ 152s > ## 152s > 152s > local({ 152s + if(FULLTEST) { 152s + Y <- split(urkiola) 152s + B <- Y$birch 152s + O <- Y$oak 152s + B.lam <- predict (ppm(B ~polynom(x,y,2)), type="trend") 152s + O.lam <- predict (ppm(O ~polynom(x,y,2)), type="trend") 152s + 152s + Kinhom(B, lambda=B.lam, correction="iso") 152s + Kinhom(B, lambda=B.lam, correction="border") 152s + 152s + Kcross.inhom(urkiola, i="birch", j="oak", B.lam, O.lam) 152s + Kcross.inhom(urkiola, i="birch", j="oak", B.lam, O.lam, correction = "iso") 152s + Kcross.inhom(urkiola, i="birch", j="oak", B.lam, O.lam, correction = "border") 152s + } 152s + }) 152s > 152s > 152s > #' tests/mctests.R 152s > #' Monte Carlo tests 152s > #' (mad.test, dclf.test, envelopeTest, hasenvelope) 152s > #' $Revision: 1.5 $ $Date: 2022/05/23 04:09:49 $ 152s > 152s > 152s > local({ 152s + if(FULLTEST) { 152s + fitx <- ppm(redwood~x) 152s + ax <- envelopeTest(fitx, exponent=2, nsim=9, savefuns=TRUE) 152s + print(ax) 152s + } 152s + }) 152s > 152s > 152s > # 152s > # tests/mppm.R 152s > # 152s > # Basic tests of mppm 152s > # 152s > # $Revision: 1.23 $ $Date: 2022/07/08 04:55:13 $ 152s > # 152s > 152s > if(!FULLTEST) 152s + spatstat.options(npixel=32, ndummy.min=16) 152s > 152s > local({ 152s + ## test interaction formulae and subfits 152s + fit1 <- mppm(Points ~ group, simba, 152s + hyperframe(po=Poisson(), str=Strauss(0.1)), 152s + iformula=~ifelse(group=="control", po, str)) 152s + fit2 <- mppm(Points ~ group, simba, 152s + hyperframe(po=Poisson(), str=Strauss(0.1)), 152s + iformula=~str/id) 152s + fit2w <- mppm(Points ~ group, simba, 152s + hyperframe(po=Poisson(), str=Strauss(0.1)), 152s + iformula=~str/id, weights=runif(nrow(simba))) 152s + # currently invalid 152s + # fit3 <- mppm(Points ~ group, simba, 152s + # hyperframe(po=Poisson(), pie=PairPiece(c(0.05,0.1))), 152s + # iformula=~I((group=="control") * po) + I((group=="treatment") * pie)) 152s + 152s + fit1 152s + fit2 152s + fit2w 152s + # fit3 152s + 152s + if(FULLTEST) { 152s + ## run summary.mppm which currently sits in spatstat-internal.Rd 152s + summary(fit1) 152s + summary(fit2) 152s + summary(fit2w) 152s + # summary(fit3) 152s + } 152s + 152s + ## test vcov algorithm 152s + vcov(fit1) 152s + vcov(fit2) 152s + # vcov(fit3) 152s + 152s + if(FULLTEST) { 152s + fit4 <- mppm(Points ~ group, simba, hyperframe(str=Strauss(0.1)), iformula=~str/group) 152s + fit4 152s + summary(fit4) 152s + vcov(fit4) 152s + fit0 <- mppm(Points ~ group, simba) 152s + anova(fit0, fit4, test="Chi") 152s + ## [bug from Fernando Milesi] 152s + fit5 <- mppm(Wat ~ id, 152s + data=hyperframe(Wat=waterstriders), 152s + interaction=StraussHard(4.5, 1.5), 152s + iformula=~Interaction:id) 152s + fit5 152s + summary(fit5) 152s + vcov(fit5) 152s + } 152s + 152s + ## test subfits algorithm 152s + if(FULLTEST) { 152s + s1 <- subfits(fit1) 152s + s2 <- subfits(fit2) 152s + # s3 <- subfits(fit3) 152s + s4 <- subfits(fit4) 152s + s5 <- subfits(fit5) 152s + 152s + ## validity of results of subfits() 152s + p1 <- solapply(s1, predict) 152s + p2 <- solapply(s2, predict) 152s + # p3 <- solapply(s3, predict) 152s + p4 <- solapply(s4, predict) 152s + p5 <- solapply(s5, predict) 152s + } 152s + }) 154s > 154s > local({ 154s + if(FULLTEST) { 154s + ## cases of predict.mppm 154s + W <- solapply(waterstriders, Window) 154s + Fakes <- solapply(W, runifpoint, n=30) 154s + FakeDist <- solapply(Fakes, distfun) 154s + H <- hyperframe(Bugs=waterstriders, 154s + D=FakeDist) 154s + fit <- mppm(Bugs ~ D, data=H) 154s + p1 <- predict(fit) 154s + p2 <- predict(fit, locations=Fakes) 154s + p3 <- predict(fit, locations=solapply(W, erosion, r=4)) 154s + locn <- as.data.frame(do.call(cbind, lapply(Fakes, coords))) 154s + df <- data.frame(id=sample(1:3, nrow(locn), replace=TRUE), 154s + D=runif(nrow(locn))) 154s + p4 <- predict(fit, locations=locn, newdata=df) 154s + 154s + fitG <- mppm(Bugs ~ D, data=H, use.gam=TRUE) 154s + p1G <- predict(fitG) 154s + p2G <- predict(fitG, locations=Fakes) 154s + p3G <- predict(fitG, locations=solapply(W, erosion, r=4)) 154s + p4G <- predict(fitG, locations=locn, newdata=df) 154s + } 154s + }) 154s > 154s > local({ 154s + ## [thanks to Sven Wagner] 154s + ## factor covariate, with some levels unused in some rows 154s + if(FULLTEST) { 154s + set.seed(14921788) 154s + H <- hyperframe(X=replicate(3, runifpoint(20), simplify=FALSE), 154s + Z=solist(as.im(function(x,y){x}, owin()), 154s + as.im(function(x,y){y}, owin()), 154s + as.im(function(x,y){x+y}, owin()))) 154s + H$Z <- solapply(H$Z, cut, breaks=(0:4)/2) 154s + 154s + fit6 <- mppm(X ~ Z, H) 154s + v6 <- vcov(fit6) 154s + s6 <- subfits(fit6) 154s + p6 <- solapply(s6, predict) 154s + 154s + ## random effects 154s + fit7 <- mppm(X ~ Z, H, random=~1|id) 154s + v7 <- vcov(fit7) 154s + s7 <- subfits(fit7) 154s + p7 <- solapply(s7, predict) 154s + 154s + fit7a <- mppm(X ~ Z, H, random=~x|id) 154s + v7a <- vcov(fit7a) 154s + s7a <- subfits(fit7a) 154s + p7a <- solapply(s7a, predict) 154s + 154s + ## multitype: collisions in vcov.ppm, predict.ppm 154s + H$X <- lapply(H$X, rlabel, labels=factor(c("a","b")), permute=FALSE) 154s + M <- MultiStrauss(matrix(0.1, 2, 2), c("a","b")) 154s + fit8 <- mppm(X ~ Z, H, M) 154s + v8 <- vcov(fit8, fine=TRUE) 154s + s8 <- subfits(fit8) 154s + p8 <- lapply(s8, predict) 154s + c8 <- lapply(s8, predict, type="cif") 154s + 154s + fit9 <- mppm(X ~ Z, H, M, iformula=~Interaction * id) 154s + v9 <- vcov(fit9, fine=TRUE) 154s + s9 <- subfits(fit9) 154s + p9 <- lapply(s9, predict) 154s + c9 <- lapply(s9, predict, type="cif") 154s + 154s + ## and a simple error in recognising 'marks' 154s + fit10 <- mppm(X ~ marks, H) 154s + } 154s + }) 154s > 154s > local({ 154s + if(FULLTEST) { 154s + ## test handling of offsets and zero cif values in mppm 154s + H <- hyperframe(Y = waterstriders) 154s + (fit1 <- mppm(Y ~ 1, data=H, Hardcore(1.5))) 154s + (fit2 <- mppm(Y ~ 1, data=H, StraussHard(7, 1.5))) 154s + (fit3 <- mppm(Y ~ 1, data=H, Hybrid(S=Strauss(7), H=Hardcore(1.5)))) 154s + s1 <- subfits(fit1) 154s + s2 <- subfits(fit2) 154s + s3 <- subfits(fit3) 154s + 154s + ## prediction, in training/testing context 154s + ## (example from Markus Herrmann and Ege Rubak) 154s + X <- waterstriders 154s + dist <- solapply(waterstriders, 154s + function(z) distfun(runifpoint(1, Window(z)))) 154s + i <- 3 154s + train <- hyperframe(pattern = X[-i], dist = dist[-i]) 154s + test <- hyperframe(pattern = X[i], dist = dist[i]) 154s + fit <- mppm(pattern ~ dist, data = train) 154s + pred <- predict(fit, type="cif", newdata=test, verbose=TRUE) 154s + 154s + ## examples from Robert Aue 154s + GH <- Hybrid(G=Geyer(r=0.1, sat=3), H=Hardcore(0.01)) 154s + res <- mppm(Points ~ 1, interaction = GH, data=demohyper) 154s + print(summary(res)) 154s + sub <- subfits(res, verbose=TRUE) 154s + print(sub) 154s + } 154s + }) 154s > 154s > local({ 154s + if(FULLTEST) { 154s + ## test handling of interaction coefficients in multitype case 154s + set.seed(42) 154s + XX <- as.solist(replicate(3, rthin(amacrine, 0.8), simplify=FALSE)) 154s + H <- hyperframe(X=XX) 154s + M <- MultiStrauss(matrix(0.1, 2, 2), levels(marks(amacrine))) 154s + fit <- mppm(X ~ 1, H, M) 154s + co <- coef(fit) 154s + subco <- sapply(subfits(fit), coef) 154s + if(max(abs(subco - co)) > 0.001) 154s + stop("Wrong coefficient values in subfits, for multitype interaction") 154s + } 154s + }) 154s > 154s > local({ 154s + if(FULLTEST) { 154s + ## test lurking.mppm 154s + ## example from 'mppm' 154s + n <- 7 154s + H <- hyperframe(V=1:n, 154s + U=runif(n, min=-1, max=1)) 154s + H$Z <- setcov(square(1)) 154s + H$U <- with(H, as.im(U, as.rectangle(Z))) 154s + H$Y <- with(H, rpoispp(eval.im(exp(2+3*Z)))) 154s + fit <- mppm(Y ~ Z + U + V, data=H) 154s + 154s + lurking(fit, expression(Z), type="P") 154s + lurking(fit, expression(V), type="raw") # design covariate 154s + lurking(fit, expression(U), type="raw") # image, constant in each row 154s + lurking(fit, H$Z, type="P") # list of images 154s + } 154s + }) 154s > 154s > local({ 154s + if(FULLTEST) { 154s + ## test anova.mppm code blocks and scoping problem 154s + H <- hyperframe(X=waterstriders) 154s + mod0 <- mppm(X~1, data=H, Poisson()) 154s + modxy <- mppm(X~x+y, data=H, Poisson()) 154s + mod0S <- mppm(X~1, data=H, Strauss(2)) 154s + modxyS <- mppm(X~x+y, data=H, Strauss(2)) 154s + anova(mod0, modxy, test="Chi") 154s + anova(mod0S, modxyS, test="Chi") 154s + anova(modxy, test="Chi") 154s + anova(modxyS, test="Chi") 154s + #' models with random effects (example from Marcelino de la Cruz) 154s + mod0r <- mppm(X~1, data=H, Poisson(), random = ~1|id) 154s + modxr <- mppm(X~x, data=H, Poisson(), random = ~1|id) 154s + anova(mod0r, modxr, test="Chi") 154s + } 154s + }) 154s > 154s > local({ 154s + if(FULLTEST) { 154s + ## test multitype stuff 154s + foo <- flu[1:3,] 154s + msh <- MultiStraussHard(iradii=matrix(100, 2, 2), 154s + hradii=matrix(10,2,2), 154s + types=levels(marks(foo$pattern[[1]]))) 154s + msh0 <- MultiStraussHard(iradii=matrix(100, 2, 2), 154s + hradii=matrix(10,2,2)) 154s + fit <- mppm(pattern ~ 1, data=foo, interaction=msh0) 154s + print(fit) 154s + print(summary(fit)) 154s + v <- vcov(fit) 154s + } 154s + }) 154s > 154s > reset.spatstat.options() 154s > #' 154s > #' tests/msr.R 154s > #' 154s > #' $Revision: 1.5 $ $Date: 2020/11/30 07:27:44 $ 154s > #' 154s > #' Tests of code for measures 154s > #' 154s > 154s > if(FULLTEST) { 154s + local({ 154s + 154s + ## cases of 'msr' 154s + Q <- quadscheme(cells) 154s + nQ <- n.quad(Q) 154s + nX <- npoints(cells) 154s + A <- matrix(nX * 3, nX, 3) 154s + B <- matrix(nQ * 3, nQ, 3) 154s + 154s + m <- msr(Q, A, B) 154s + 154s + M <- msr(Q, A, 1) 154s + M <- msr(Q, 1, B) 154s + M <- msr(Q, A, B[,1]) 154s + M <- msr(Q, A[,1], B) 154s + M <- msr(Q, A, B[,1,drop=FALSE]) 154s + M <- msr(Q, A[,1,drop=FALSE], B) 154s + 154s + ## methods 154s + a <- summary(m) 154s + b <- is.marked(m) 154s + w <- as.owin(m) 154s + z <- domain(m) 154s + ss <- scalardilate(m, 2) 154s + tt <- rescale(m, 2) 154s + ee <- rotate(m, pi/4) 154s + aa <- affine(m, mat=diag(c(1,2)), vec=c(0,1)) 154s + ff <- flipxy(m) 154s + 154s + am <- augment.msr(m, sigma=0.08) 154s + ua <- update(am) 154s + 154s + rr <- residuals(ppm(cells ~ x)) 154s + mm <- residuals(ppm(amacrine ~ x)) 154s + ss <- residuals(ppm(amacrine ~ x), type="score") 154s + gg <- rescale(ss, 1/662, c("micron", "microns")) 154s + 154s + plot(mm) 154s + plot(mm, multiplot=FALSE) 154s + plot(mm, equal.markscale=TRUE, equal.ribbon=TRUE) 154s + plot(ss) 154s + plot(ss, multiplot=FALSE) 154s + }) 154s + } 154s > 154s BEGIN TEST testsNtoO.R 154s 154s R version 4.4.3 (2025-02-28) -- "Trophy Case" 154s Copyright (C) 2025 The R Foundation for Statistical Computing 154s Platform: x86_64-pc-linux-gnu 154s 154s R is free software and comes with ABSOLUTELY NO WARRANTY. 154s You are welcome to redistribute it under certain conditions. 154s Type 'license()' or 'licence()' for distribution details. 154s 154s R is a collaborative project with many contributors. 154s Type 'contributors()' for more information and 154s 'citation()' on how to cite R or R packages in publications. 154s 154s Type 'demo()' for some demos, 'help()' for on-line help, or 154s 'help.start()' for an HTML browser interface to help. 154s Type 'q()' to quit R. 154s 154s > #' 154s > #' Header for all (concatenated) test files 154s > #' 154s > #' Require spatstat.model 154s > #' Obtain environment variable controlling tests. 154s > #' 154s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 154s > 154s > require(spatstat.model) 154s Loading required package: spatstat.model 154s Loading required package: spatstat.data 155s Loading required package: spatstat.univar 155s spatstat.univar 3.1-2 155s Loading required package: spatstat.geom 155s spatstat.geom 3.3-6 155s Loading required package: spatstat.random 155s spatstat.random 3.3-3 155s Loading required package: spatstat.explore 155s Loading required package: nlme 155s spatstat.explore 3.3-4 155s Loading required package: rpart 155s spatstat.model 3.3-4 155s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 155s > ALWAYS <- TRUE 155s > cat(paste("--------- Executing", 155s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 155s + "test code -----------\n")) 155s --------- Executing **RESTRICTED** subset of test code ----------- 155s > # 155s > # tests/NAinCov.R 155s > # 155s > # Testing the response to the presence of NA's in covariates 155s > # 155s > # $Revision: 1.10 $ $Date: 2024/09/30 23:13:54 $ 155s > 155s > if(FULLTEST) { 155s + local({ 155s + X <- runifpoint(42) 155s + Y <- as.im(function(x,y) { x+y }, owin()) 155s + Y[owin(c(0.2,0.4),c(0.2,0.4))] <- NA 155s + ## ..... ppm ...................................... 155s + ## fit model: should produce a warning but no failure 155s + misfit <- ppm(X ~ Y) 155s + ## prediction 155s + Z <- predict(misfit, type="trend", se=TRUE) 155s + ## canonical covariates 155s + M <- model.images(misfit) 155s + ## covariance matrix: all should be silent 155s + v <- vcov(misfit) 155s + ss <- vcov(misfit, what="internals") 155s + ## ..... kppm ...................................... 155s + ## should produce warnings but no failures 155s + misfit <- kppm(X ~Y) 155s + V <- predict(misfit, type="trend", se=TRUE) 155s + M <- model.images(misfit) 155s + refit <- improve.kppm(misfit, dimyx=20) 155s + }) 155s + } 155s > 155s BEGIN TEST testsP1.R 155s 155s R version 4.4.3 (2025-02-28) -- "Trophy Case" 155s Copyright (C) 2025 The R Foundation for Statistical Computing 155s Platform: x86_64-pc-linux-gnu 155s 155s R is free software and comes with ABSOLUTELY NO WARRANTY. 155s You are welcome to redistribute it under certain conditions. 155s Type 'license()' or 'licence()' for distribution details. 155s 155s R is a collaborative project with many contributors. 155s Type 'contributors()' for more information and 155s 'citation()' on how to cite R or R packages in publications. 155s 155s Type 'demo()' for some demos, 'help()' for on-line help, or 155s 'help.start()' for an HTML browser interface to help. 155s Type 'q()' to quit R. 155s 155s > #' 155s > #' Header for all (concatenated) test files 155s > #' 155s > #' Require spatstat.model 155s > #' Obtain environment variable controlling tests. 155s > #' 155s Loading required package: spatstat.model 155s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 155s > 155s > require(spatstat.model) 155s Loading required package: spatstat.data 156s Loading required package: spatstat.univar 156s spatstat.univar 3.1-2 156s Loading required package: spatstat.geom 156s spatstat.geom 3.3-6 156s Loading required package: spatstat.random 156s spatstat.random 3.3-3 156s Loading required package: spatstat.explore 156s Loading required package: nlme 156s spatstat.explore 3.3-4 156s Loading required package: rpart 157s spatstat.model 3.3-4 157s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 157s > ALWAYS <- TRUE 157s > cat(paste("--------- Executing", 157s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 157s + "test code -----------\n")) 157s --------- Executing **RESTRICTED** subset of test code ----------- 157s > ## 157s > ## tests/percy.R 157s > ## 157s > ## Tests of Percus-Yevick approximations 157s > ## 157s > ## $Revision: 1.3 $ $Date: 2020/04/30 05:23:52 $ 157s > 157s > if(FULLTEST) { 157s + local({ 157s + fit <- ppm(swedishpines ~1, DiggleGatesStibbard(6)) 157s + K <- Kmodel(fit) 157s + }) 157s + } 157s > 157s > ## 157s > ## tests/pixelgripes.R 157s > ## Problems related to pixellation of windows 157s > ## 157s > ## $Revision: 1.8 $ $Date: 2022/10/23 06:21:10 $ 157s > 157s > if(FULLTEST) { 157s + local({ 157s + 157s + ## From Philipp Hunziker: bug in rNeymanScott (etc) 157s + ## Create an irregular window 157s + PM <- matrix(c(1,0,0.5,1,0,0), 3, 2, byrow=TRUE) 157s + P <- owin(poly=PM) 157s + ## Generate Matern points 157s + X <- rMatClust(50, 0.05, 5, win=P) 157s + ## Some distance function as a covariate 157s + distorigin <- function(x, y) { sqrt(x^2 + y^2) } 157s + ## No covariates: works fine 157s + fit0 <- kppm(X ~ 1, clusters="MatClust") 157s + Y0 <- simulate(fit0, retry=0) 157s + ## Covariates: Simulation fails 157s + fit1 <- kppm(X ~ distorigin, clusters="MatClust") 157s + Y1 <- simulate(fit1, retry=0) 157s + 157s + }) 157s + } 157s > 157s BEGIN TEST testsP2.R 157s 157s R version 4.4.3 (2025-02-28) -- "Trophy Case" 157s Copyright (C) 2025 The R Foundation for Statistical Computing 157s Platform: x86_64-pc-linux-gnu 157s 157s R is free software and comes with ABSOLUTELY NO WARRANTY. 157s You are welcome to redistribute it under certain conditions. 157s Type 'license()' or 'licence()' for distribution details. 157s 157s R is a collaborative project with many contributors. 157s Type 'contributors()' for more information and 157s 'citation()' on how to cite R or R packages in publications. 157s 157s Type 'demo()' for some demos, 'help()' for on-line help, or 157s 'help.start()' for an HTML browser interface to help. 157s Type 'q()' to quit R. 157s 157s > #' 157s > #' Header for all (concatenated) test files 157s > #' 157s > #' Require spatstat.model 157s > #' Obtain environment variable controlling tests. 157s > #' 157s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 157s > 157s > require(spatstat.model) 157s Loading required package: spatstat.model 157s Loading required package: spatstat.data 158s Loading required package: spatstat.univar 158s spatstat.univar 3.1-2 158s Loading required package: spatstat.geom 158s spatstat.geom 3.3-6 158s Loading required package: spatstat.random 158s spatstat.random 3.3-3 158s Loading required package: spatstat.explore 158s Loading required package: nlme 158s spatstat.explore 3.3-4 158s Loading required package: rpart 158s spatstat.model 3.3-4 158s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 158s > ALWAYS <- TRUE 158s > cat(paste("--------- Executing", 158s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 158s + "test code -----------\n")) 158s --------- Executing **RESTRICTED** subset of test code ----------- 158s > # 158s > # tests/ppmBadData.R 158s > # 158s > # $Revision: 1.6 $ $Date: 2020/04/30 05:23:52 $ 158s > 158s > # Testing robustness of ppm and support functions 158s > # when data are rubbish 158s > 158s > local({ 158s + if(ALWAYS) { 158s + ## from Rolf: very large proportion of data is NA 158s + SEED <- 42 158s + K <- 101 158s + A <- 500 158s + X <- seq(0, A, length=K) 158s + G <- expand.grid(x=X, y=X) 158s + FOO <- function(x,y) { sin(x)^2 + cos(y)^2 } 158s + M1 <- im(matrix(FOO(G$x, G$y), K, K), xcol=X, yrow=X) 158s + M <- im(matrix(FOO(G$x, G$y), K, K)) 158s + BAR <- function(x) { exp(-6.618913 + 5.855337 * x - 8.432483 * x^2) } 158s + V <- im(BAR(M$v), xcol=X, yrow=X) 158s + # V <- eval.im(exp(-6.618913 + 5.855337 * M - 8.432483 * M^2)) 158s + set.seed(SEED) 158s + Y <- rpoispp(V) 158s + fY <- ppm(Y ~cv + I(cv^2), data=list(cv=M), correction="translate") 158s + diagnose.ppm(fY) 158s + lurking(fY, covariate=as.im(function(x,y){x}, square(A)), type="raw") 158s + } 158s + 158s + if(ALWAYS) { 158s + ## from Andrew Bevan: numerical overflow, ill-conditioned Fisher information 158s + SEED <- 42 158s + nongranite<- owin(poly = list(x = c(0, 8500, 7000, 6400, 6400, 6700, 7000, 7200, 7300, 8000, 8100, 8800, 9500, 10000, 10000, 0), y = c(0, 0, 2000, 3800, 4000, 5000, 6500, 7400, 7500, 8000, 8100, 9000, 9500, 9600, 10000, 10000))) 158s + ## Trend on raster grid 158s + rain <- as.im(X=function(x,y) { x^2 + y^2 }, W=nongranite, dimyx=100) 158s + ## Generate a point pattern via a Lennard-Jones process 158s + set.seed(SEED) 158s + mod4<- rmhmodel(cif="lennard", 158s + par=list(beta=1, sigma=250, epsilon=2.2), 158s + trend=rain, w=nongranite) 158s + ljtr<- rmh(mod4, start=list(n.start=80), control=list(p=1, nrep=1e5)) 158s + 158s + ## Fit a point process model to the pattern with rain as a covariate 158s + ## NOTE INCORRECT TREND FORMULA 158s + ljtrmod <- ppm(ljtr, trend= ~ Z, interaction=NULL, data=list(Z=rain)) 158s + ss <- summary(ljtrmod) 158s + } 158s + 158s + if(FULLTEST) { 158s + ## From Ege 158s + ## Degenerate but non-null argument 'covariates' 158s + xx <- list() 158s + names(xx) <- character(0) 158s + fit <- ppm(cells ~x, covariates = xx) 158s + st <- summary(fit) 158s + } 158s + 158s + }) 158s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 158s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 158s Error in solve.default(M) : 158s system is computationally singular: reciprocal condition number = 5.72218e-18 158s In addition: Warning messages: 158s 1: Values of the covariate ‘cv’ were NA or undefined at 96% (1774 out of 1845) of the quadrature points. Occurred while executing: ppm.ppp(Q = Y, trend = ~cv + I(cv^2), data = list(list(c(1, 1.91953576453823, 158s 2: Some infinite, NA or NaN increments were removed 158s 3: Numerical underflow detected: sigma is probably too small 158s 4: Some infinite, NA or NaN increments were removed 158s Error in solve.default(M) : 158s system is computationally singular: reciprocal condition number = 5.72218e-18 158s In addition: Warning message: 158s Cannot compute variance: Fisher information matrix is singular 158s Warning message: 158s Cannot compute variance: Fisher information matrix is singular 158s > 158s > 158s > 158s > #' tests/ppmclass.R 158s > #' 158s > #' Class support for ppm 158s > #' 158s > #' $Revision: 1.9 $ $Date: 2022/03/07 03:26:09 $ 158s > 158s > if(FULLTEST) { 158s + local({ 158s + #' (1) print.ppm, summary.ppm, print.summary.ppm 158s + Z <- as.im(function(x,y){x}, Window(cells)) 158s + fitZ <- ppm(cells ~ Z) 158s + print(fitZ) 158s + print(summary(fitZ)) 158s + #' logistic 158s + fitl <- ppm(swedishpines ~ x+y, method="logi") 158s + print(fitl) 158s + print(summary(fitl)) 158s + #' Model with covariate arguments 158s + f <- function(x,y,b) { x+b } 158s + fitf <- ppm(cells ~ f, covfunargs=list(b=1)) 158s + print(fitf) 158s + print(summary(fitf)) 158s + #' Invalid model 158s + fitN <- ppm(redwood ~ 1, Strauss(0.1)) 158s + print(fitN) 158s + print(summary(fitN)) 158s + #' standard errors in output 158s + fat <- ppm(cells ~ x, Strauss(0.12)) 158s + op <- spatstat.options(print.ppm.SE='always') 158s + print(fat) 158s + spatstat.options(print.ppm.SE='never') 158s + print(fat) 158s + print(fitZ) 158s + spatstat.options(op) 158s + 158s + ## (2) plot.ppm 158s + plot(fitZ) 158s + plot(fat, trend=FALSE, cif=FALSE, se=FALSE) 158s + 158s + ## (3) emend.ppm 158s + fitZe <- emend(fitZ, trace=TRUE) 158s + ZZ <- Z 158s + fitZZ <- ppm(cells ~ Z + ZZ) 158s + fitZZe <- emend(fitZZ, trace=TRUE) 158s + fitOK <- ppm(redwood ~1, Strauss(0.1), emend=TRUE) 158s + print(fitOK) 158s + fitNot <- ppm(redwood ~1, Strauss(0.1)) 158s + fitSlow <- emend(fitNot, trace=TRUE) 158s + print(fitSlow) 158s + op <- spatstat.options(project.fast=TRUE) 158s + fitFast <- emend(fitNot, trace=TRUE) 158s + print(fitFast) 158s + fitZZe <- emend(fitZZ, trace=TRUE) 158s + spatstat.options(op) 158s + 158s + #' (4) methods for other generics 158s + logLik(fitZ, absolute=TRUE) 158s + unitname(fitZ) 158s + unitname(fat) <- c("metre", "metres") 158s + is.expandable(fitf) 158s + fit0 <- update(fitZ, . ~ 1) 158s + anova(fit0, fitZ, override=TRUE) 158s + interactionfamilyname(fat) 158s + interactionorder(fat) 158s + hardcoredist(fat) 158s + 158s + #' (5) miscellaneous 158s + 158s + ## example from Robert Aue - handling offsets 158s + X <- demohyper$Points[[1]] 158s + GH <- Hybrid(G=Geyer(r=0.1, sat=3), H=Hardcore(0.01)) 158s + fit <- ppm(X ~ 1, GH) 158s + valid.ppm(fit) 158s + 158s + #' hard core distance of hybrid 158s + hardcoredist(fit) 158s + #' interaction order of hybrid 158s + interactionorder(fit) 158s + 158s + #' case of boundingbox 158s + boundingbox(cells, ppm(cells ~ 1)) 158s + }) 158s + 158s + reset.spatstat.options() 158s + } 158s > # 158s > # tests/ppmgam.R 158s > # 158s > # Test ppm with use.gam=TRUE 158s > # 158s > # $Revision: 1.4 $ $Date: 2020/04/30 05:23:52 $ 158s > # 158s > 158s > if(FULLTEST) { 158s + local({ 158s + fit <- ppm(nztrees ~s(x,y), use.gam=TRUE) 158s + mm <- model.matrix(fit) 158s + mf <- model.frame(fit) 158s + v <- vcov(fit) 158s + prd <- predict(fit) 158s + }) 158s + } 158s > #' 158s > #' tests/ppmlogi.R 158s > #' 158s > #' Tests of ppm(method='logi') 158s > #' and related code (predict, leverage etc) 158s > #' 158s > #' $Revision: 1.15 $ $Date: 2020/04/30 05:23:52 $ 158s > #' 158s > 158s > local({ 158s + if(FULLTEST) { 158s + fit <- ppm(cells ~x, method="logi") 158s + f <- fitted(fit) 158s + p <- predict(fit) 158s + u <- summary(fit) 158s + fitS <- ppm(cells ~x, Strauss(0.12), method="logi") 158s + fS <- fitted(fitS) 158s + pS <- predict(fitS) 158s + uS <- summary(fitS) 158s + print(uS) 158s + 158s + plot(leverage(fit)) 158s + plot(influence(fit)) 158s + plot(dfbetas(fit)) 158s + plot(leverage(fitS)) 158s + plot(influence(fitS)) 158s + plot(dfbetas(fitS)) 158s + } 158s + 158s + if(FULLTEST) { 158s + #' same with hard core - A1 is singular 158s + fitH <- ppm(cells ~x, Strauss(0.08), method="logi") 158s + print(fitH) 158s + fH <- fitted(fitH) 158s + pH <- predict(fitH) 158s + uH <- summary(fitH) 158s + print(uH) 158s + plot(leverage(fitH)) 158s + plot(influence(fitH)) 158s + plot(dfbetas(fitH)) 158s + } 158s + 158s + if(FULLTEST) { 158s + #' logistic fit to data frame of covariates 158s + z <- c(rep(TRUE, 5), rep(FALSE, 5)) 158s + df <- data.frame(A=z + 2* runif(10), 158s + B=runif(10)) 158s + Y <- quadscheme.logi(runifpoint(5), runifpoint(5)) 158s + fut <- ppm(Y ~ A+B, data=df, method="logi") 158s + sf <- summary(fut) 158s + print(sf) 158s + } 158s + 158s + if(FULLTEST) { 158s + #' vblogit code, just to check that it runs. 158s + fee <- ppm(cells ~ x, method="VBlogi", nd=21) 158s + print(fee) 158s + summary(fee) 158s + logLik(fee) 158s + AIC(fee) 158s + extractAIC(fee) 158s + Z <- predict(fee) 158s + summary(Z) 158s + print(fee$internal$glmfit) # print.vblogit 158s + } 158s + }) 158s > 158s > # 158s > # tests/ppmmarkorder.R 158s > # 158s > # $Revision: 1.4 $ $Date: 2020/04/30 05:23:52 $ 158s > # 158s > # Test that predict.ppm, plot.ppm and plot.fitin 158s > # tolerate marks with levels that are not in alpha order 158s > # 158s > if(ALWAYS) { # locale-dependent? 158s + local({ 158s + X <- amacrine 158s + levels(marks(X)) <- c("ZZZ", "AAA") 158s + fit <- ppm(X ~marks, MultiStrauss(c("ZZZ","AAA"), matrix(0.06, 2, 2))) 158s + aa <- predict(fit, type="trend") 158s + bb <- predict(fit, type="cif") 158s + plot(fit) 158s + plot(fitin(fit)) 158s + }) 158s + } 161s > 161s > 161s > # 161s > # tests/ppmscope.R 161s > # 161s > # Test things that might corrupt the internal format of ppm objects 161s > # 161s > # $Revision: 1.7 $ $Date: 2022/01/19 09:18:20 $ 161s > # 161s > 161s > if(ALWAYS) { # dependent on R version? 161s + local({ 161s + 161s + ## (1) Scoping problem that can arise when ppm splits the data 161s + fit <- ppm(bei ~elev, data=bei.extra) 161s + mm <- model.matrix(fit) 161s + 161s + ## (2) Fast update mechanism 161s + fit1 <- ppm(cells ~x+y, Strauss(0.07)) 161s + fit2 <- update(fit1, ~y) 161s + fit3 <- update(fit2, ~x) 161s + 161s + ## (3) New formula-based syntax 161s + attach(bei.extra) 161s + slfit <- ppm(bei ~ grad) 161s + sl2fit <- update(slfit, ~grad + I(grad^2)) 161s + slfitup <- update(slfit, use.internal=TRUE) 161s + sl2fitup <- update(sl2fit, use.internal=TRUE) 161s + 161s + ## (4) anova.ppm 161s + fut1 <- ppm(cells ~ 1, Strauss(0.1)) 161s + futx <- ppm(cells ~ x, Strauss(0.1)) 161s + anova(fut1, test="Chi") 161s + anova(futx, test="Chi") 161s + fut1a <- ppm(cells ~ 1, Strauss(0.1), rbord=0) 161s + anova(fut1a, futx, test="Chi") 161s + fut1d <- ppm(cells ~ 1, Strauss(0.1), nd=23) 161s + anova(fut1d, futx, test="Chi") 161s + ## This now works! 161s + futxyg <- ppm(cells ~ x + s(y), Strauss(0.1), use.gam=TRUE) 161s + anova(futx, futxyg) 161s + ## marked 161s + fatP <- ppm(amacrine ~ marks) 161s + fatM <- ppm(amacrine ~ marks, MultiStrauss(matrix(0.07, 2, 2))) 161s + anova(fatP, fatM, test="Chi") 161s + 161s + ## (5) expansion of "." in update.ppm 161s + fitb <- ppm(bei ~ . , data=bei.extra) 161s + step(fitb) 161s + }) 161s + } 162s Start: AIC=42295.11 162s ~elev + grad 162s 162s Df AIC 162s 42295 162s - elev 1 42383 162s - grad 1 42760 162s Nonstationary Poisson process 162s Fitted to point pattern dataset ‘bei’ 162s Warning messages: 162s 1: anova.ppm now computes the *adjusted* deviances when the models are not Poisson processes. 162s 2: Models were re-fitted using a common value of 'rbord' 162s 3: Models were re-fitted using a common quadrature scheme 162s 4: Models were re-fitted with use.gam=TRUE 162s 5: Deviance adjustment is not available for gam fits; unadjusted composite deviance calculated. 162s 6: Models were re-fitted using a common value of 'rbord' 162s 162s Log intensity: ~elev + grad 162s 162s Fitted trend coefficients: 162s (Intercept) elev grad 162s -8.56355220 0.02143995 5.84646680 162s 162s Estimate S.E. CI95.lo CI95.hi Ztest Zval 162s (Intercept) -8.56355220 0.341113849 -9.23212306 -7.89498134 *** -25.104675 162s elev 0.02143995 0.002287866 0.01695581 0.02592408 *** 9.371155 162s grad 5.84646680 0.255781018 5.34514522 6.34778838 *** 22.857313 162s > grep# 162s function (pattern, x, ignore.case = FALSE, perl = FALSE, value = FALSE, 162s fixed = FALSE, useBytes = FALSE, invert = FALSE) 162s { 162s pattern <- as.character(pattern) 162s if (is.factor(x) && length(levx <- levels(x)) < length(x) && 162s !is.na(pattern[1L])) { 162s value <- is.character(idxna <- suppressWarnings(grep(pattern, 162s NA_character_, ignore.case, perl, value, fixed, useBytes, 162s invert))) 162s idx <- logical(length(levx)) 162s idx[grep(pattern, levx, ignore.case, perl, FALSE, fixed, 162s useBytes, invert)] <- TRUE 162s idx <- idx[x] 162s if (length(idxna)) 162s idx[is.na(x)] <- TRUE 162s idx <- which(idx) 162s if (value) { 162s idx <- x[idx] 162s structure(as.character(idx), names = names(idx)) 162s } 162s else idx 162s } 162s else { 162s if (!is.character(x)) 162s x <- structure(as.character(x), names = names(x)) 162s .Internal(grep(pattern, x, ignore.case, value, perl, 162s fixed, useBytes, invert)) 162s } 162s } 162s 162s 162s > # tests/ppmtricks.R 162s > # 162s > # Test backdoor exits, hidden options, internals and tricks in ppm 162s > # 162s > # $Revision: 1.19 $ $Date: 2020/04/30 05:23:52 $ 162s > # 162s > local({ 162s + 162s + ## (1) skip.border 162s + if(ALWAYS) { # needed below 162s + fit <- ppm(cells, ~1, Strauss(0.1), skip.border=TRUE) 162s + } 162s + 162s + ## (2) subset arguments of different kinds 162s + if(FULLTEST) { 162s + fut <- ppm(cells ~ x, subset=(x > 0.5)) 162s + fot <- ppm(cells ~ x, subset=(x > 0.5), method="logi") 162s + W <- owin(c(0.4, 0.8), c(0.2, 0.7)) 162s + fut <- ppm(cells ~ x, subset=W) 162s + fot <- ppm(cells ~ x, subset=W, method="logi") 162s + V <- as.im(inside.owin, Window(cells), w=W) 162s + fet <- ppm(cells ~ x, subset=V) 162s + fet <- ppm(cells ~ x, subset=V, method="logi") 162s + } 162s + 162s + ## (3) profilepl -> ppm 162s + ## uses 'skip.border' and 'precomputed' 162s + ## also tests scoping for covariates 162s + if(FULLTEST) { 162s + splants <- split(ants) 162s + mess <- splants[["Messor"]] 162s + cats <- splants[["Cataglyphis"]] 162s + ss <- data.frame(r=seq(60,120,by=20),hc=29/6) 162s + dM <- distmap(mess,dimyx=256) 162s + mungf <- profilepl(ss, StraussHard, cats ~ dM) 162s + mungp <- profilepl(ss, StraussHard, trend=~dM, Q=cats) 162s + } 162s + 162s + ## (4) splitting large quadschemes into blocks 162s + if(FULLTEST) { 162s + mop <- spatstat.options(maxmatrix=5000) 162s + qr <- quadBlockSizes(quadscheme(cells)) 162s + pr <- predict(ppm(cells ~ x, AreaInter(0.05))) 162s + spatstat.options(mop) 162s + qr <- quadBlockSizes(quadscheme(cells)) 162s + } 162s + 162s + ## (5) shortcuts in summary.ppm 162s + ## and corresponding behaviour of print.summary.ppm 162s + if(FULLTEST) { 162s + print(summary(fit, quick=TRUE)) 162s + print(summary(fit, quick="entries")) 162s + print(summary(fit, quick="no prediction")) 162s + print(summary(fit, quick="no variances")) 162s + } 162s + 162s + ## (6) suffstat.R 162s + if(ALWAYS) { 162s + fitP <- update(fit, Poisson()) 162s + suffstat.poisson(fitP, cells) 162s + fit0 <- killinteraction(fit) 162s + suffstat.poisson(fit0, cells) 162s + } 162s + 162s + ## (7) various support for class ppm 162s + if(FULLTEST) { 162s + fut <- kppm(redwood ~ x) 162s + A <- quad.ppm(fut) 162s + Z <- as.im(function(x,y){x}, Window(cells)) 162s + fitZ <- ppm(cells ~ Z) 162s + U <- getppmOriginalCovariates(fitZ) 162s + } 162s + 162s + ## (8) support for class profilepl 162s + if(FULLTEST) { 162s + rr <- data.frame(r=seq(0.05, 0.15, by=0.02)) 162s + ps <- profilepl(rr, Strauss, cells) 162s + ## plot(ps) ## covered in plot.profilepl.Rd 162s + simulate(ps, nrep=1e4) 162s + parameters(ps) 162s + fitin(ps) 162s + predict(ps, type="cif") 162s + } 162s + 162s + ## (9) class 'plotppm' 162s + if(FULLTEST) { 162s + fut <- ppm(amacrine ~ marks + polynom(x,y,2), Strauss(0.07)) 162s + p <- plot(fut, plot.it=FALSE) 162s + print(p) 162s + plot(p, how="contour") 162s + plot(p, how="persp") 162s + } 162s + 162s + ## (10) ppm -> mpl.engine -> mpl.prepare 162s + if(ALWAYS) { # includes C code 162s + fit <- ppm(cells, NULL) 162s + fit <- ppm(cells ~ x, clipwin=square(0.7)) 162s + fit <- ppm(cells ~ x, subset=square(0.7)) 162s + DG <- as.im(function(x,y){x+y < 1}, square(1)) 162s + fit <- ppm(cells ~ x, subset=DG) 162s + fit <- ppm(cells ~ x, GLM=glm) 162s + fit <- ppm(cells ~ x, famille=quasi(link='log', variance='mu')) 162s + fit <- ppm(cells ~ x, Hardcore(0.07), skip.border=TRUE, splitInf=TRUE) 162s + } 162s + 162s + ## (11) unidentifiable model (triggers an error in ppm) 162s + if(FULLTEST) { 162s + Q <- quadscheme(cells) 162s + M <- mpl.prepare(Q, cells, as.ppp(Q), trend=~1, covariates=NULL, 162s + interaction=Hardcore(0.3), correction="none") 162s + } 162s + }) 162s > 162s > reset.spatstat.options() 162s > # 162s > # tests/prediction.R 162s > # 162s > # Things that might go wrong with predict() 162s > # 162s > # $Revision: 1.23 $ $Date: 2024/04/13 03:37:42 $ 162s > # 162s > 162s > local({ 162s + if(ALWAYS) { 162s + ## test of 'covfunargs' - platform dependent? 162s + f <- function(x,y,a){ y - a } 162s + fit <- ppm(cells ~x + f, covariates=list(f=f), covfunargs=list(a=1/2)) 162s + p <- predict(fit) 162s + 162s + ## prediction involving 0 * NA 162s + qc <- quadscheme(cells, nd=10) 162s + r <- minnndist(as.ppp(qc))/10 162s + fit <- ppm(qc ~ 1, Strauss(r)) # model has NA for interaction coefficient 162s + p1 <- predict(fit) 162s + p2 <- predict(fit, type="cif", ngrid=10) 162s + stopifnot(all(is.finite(as.matrix(p1)))) 162s + stopifnot(all(is.finite(as.matrix(p2)))) 162s + } 162s + 162s + if(FULLTEST) { 162s + ## test of 'new.coef' mechanism 162s + fut <- ppm(cells ~ x, Strauss(0.15), rbord=0) 162s + p0 <- predict(fut, type="cif") 162s + pe <- predict(fut, type="cif", new.coef=coef(fut)) 162s + pn <- predict(fut, type="cif", new.coef=unname(coef(fut))) 162s + if(max(abs(pe-p0)) > 0.01) 162s + stop("new.coef mechanism is broken!") 162s + if(max(abs(pn-p0)) > 0.01) 162s + stop("new.coef mechanism gives wrong answer, for unnamed vectors") 162s + #' adaptcoef 162s + a <- c(A=1,B=2,Z=42) 162s + b <- c(B=41,A=0) 162s + ab <- adaptcoef(a, b, drop=TRUE) 162s + #' check that grid parameters 'dimyx' and 'eps' are respected 162s + pyx <- predict(fut, type="cif", dimyx=7) 162s + if(all(dim(pyx) == dim(p0))) 162s + stop("predict.ppm ignores argument dimyx") 162s + peps <- predict(fut, type="cif", eps=0.14) 162s + if(all(dim(peps) == dim(p0))) 162s + stop("predict.ppm ignores argument eps") 162s + } 162s + 162s + if(FULLTEST) { 162s + ## tests of relrisk.ppm 162s + fut <- ppm(amacrine ~ x * marks) 162s + a <- relrisk(fut, control=2, relative=TRUE) 162s + a <- relrisk(fut, se=TRUE) 162s + a <- relrisk(fut, relative=TRUE, se=TRUE) 162s + fut <- ppm(sporophores ~ marks + x) 162s + a <- relrisk(fut, control=2, relative=TRUE) 162s + a <- relrisk(fut, se=TRUE) 162s + a <- relrisk(fut, relative=TRUE, se=TRUE) 162s + 162s + ## untested cases of predict.ppm 162s + fit0 <- ppm(cells) 162s + a <- predict(fit0, interval="confidence") 162s + a <- predict(fit0, interval="confidence", type="count") 162s + fit <- ppm(cells ~ x) 162s + b <- predict(fit, se=TRUE, locations=cells) 162s + b <- predict(fit, se=TRUE, interval="confidence") 162s + b <- predict(fit, type="count", se=TRUE) 162s + b <- predict(fit, type="count", window=square(0.5), se=TRUE) 162s + b <- predict(fit, type="count", window=quadrats(cells, 3), se=TRUE) 162s + d <- predict(fit, type="count", interval="prediction", se=TRUE) 162s + d <- predict(fit, type="count", interval="confidence", se=TRUE) 162s + d <- predict(fit, interval="confidence", se=TRUE) 162s + foot <- ppm(cells ~ x, StraussHard(0.12)) 162s + d <- predict(foot, ignore.hardcore=TRUE) 162s + dX <- predict(foot, ignore.hardcore=TRUE, locations=cells) 162s + 162s + ## superseded usages 162s + b <- predict(fit, type="se", getoutofjail=TRUE) 162s + b <- predict(fit, type="se", locations=cells) # warning 162s + b <- predict(fit, total=TRUE) 162s + b <- predict(fit, total=square(0.5)) 162s + b <- predict(fit, total=quadrats(cells, 3)) 162s + 162s + ## supporting code 162s + u <- model.se.image(fit, square(0.5)) 162s + u <- model.se.image(fit, square(0.5), what="cv") 162s + u <- model.se.image(fit, square(0.5), what="ce") 162s + co <- c(Intercept=5, slope=3, kink=2) 162s + re <- c("Intercept", "slope") 162s + a <- fill.coefs(co, re) # warning 162s + b <- fill.coefs(co, rev(names(co))) 162s + d <- fill.coefs(co, letters[1:3]) 162s + ## model matrix etc 162s + v <- model.frame(ppm(cells)) 162s + fut <- ppm(cells ~ x, Strauss(0.1)) 162s + v <- model.matrix(fut, subset=(x<0.5), keepNA=FALSE) 162s + df <- data.frame(x=runif(10), y=runif(10), 162s + Interaction=sample(0:1, 10, TRUE)) 162s + m10 <- PPMmodelmatrix(fut, data=df) 162s + mmm <- PPMmodelmatrix(fut, Q=quad.ppm(fut)) 163s + #' effectfun for Gibbs 163s + effectfun(fut, "x") 163s + effectfun(fut, "x", se.fit=TRUE) 163s + #' implicit covariate when there is only one 163s + effectfun(fut) 163s + effectfun(fut, se.fit=TRUE) 163s + #' given covariate 163s + dlin <- distfun(copper$SouthLines) 163s + copfit <- ppm(copper$SouthPoints ~ dlin, Geyer(1,1)) 163s + effectfun(copfit, "dlin") 163s + effectfun(copfit) 163s + #' covariate that is not used in model 163s + effectfun(fut, "y", x=0) 163s + futS <- ppm(cells ~ 1, Strauss(0.1)) 163s + effectfun(futS, "x") 163s + effectfun(futS, "y") 163s + #' factor covariate 163s + fot <- ppm(amacrine~x+marks) 163s + effectfun(fot, "marks", x=0.5, se.fit=TRUE) 163s + #' covariate retained but not used 163s + W <- Window(swedishpines) 163s + a <- solist(A=funxy(function(x,y){x < 20}, W), 163s + B=funxy(function(x,y){factor(x < 20)}, W)) 163s + fvt <- ppm(swedishpines ~ A, data=a, allcovar=TRUE) 163s + effectfun(fvt, "A", se.fit=TRUE) 163s + effectfun(fvt, "B", A=TRUE, se.fit=TRUE) 163s + 163s + ## ppm with covariate values in data frame 163s + X <- rpoispp(42) 163s + Q <- quadscheme(X) 163s + weirdfunction <- function(x,y){ 10 * x^2 + 5 * sin(10 * y) } 163s + Zvalues <- weirdfunction(x.quad(Q), y.quad(Q)) 163s + fot <- ppm(Q ~ y + Z, data=data.frame(Z=Zvalues)) 163s + effectfun(fot, "y", Z=0) 163s + effectfun(fot, "Z", y=0) 163s + 163s + #' multitype 163s + modX <- ppm(amacrine ~ polynom(x,2)) 163s + effectfun(modX) 163s + effectfun(modX, "x") 163s + modXM <- ppm(amacrine ~ marks*polynom(x,2)) 163s + effectfun(modXM, "x", marks="on") 163s + modXYM <- ppm(amacrine ~ marks*polynom(x,y,2)) 163s + effectfun(modXYM, "x", y=0, marks="on") 163s + 163s + df <- as.data.frame(simulate(modXM, drop=TRUE)) 163s + df$marks <- as.character(df$marks) 163s + dfpr <- predict(modXM, locations=df) 163s + } 163s + }) 163s > 163s > # 163s > # tests/project.ppm.R 163s > # 163s > # $Revision: 1.7 $ $Date: 2020/04/30 05:41:59 $ 163s > # 163s > # Tests of projection mechanism 163s > # 163s > 163s > local({ 163s + chk <- function(m) { 163s + if(!valid.ppm(m)) stop("Projected model was still not valid") 163s + return(invisible(NULL)) 163s + } 163s + 163s + if(FULLTEST) { 163s + ## a very unidentifiable model 163s + fit <- ppm(cells ~Z, Strauss(1e-06), covariates=list(Z=0)) 163s + chk(emend(fit)) 163s + ## multitype 163s + r <- matrix(1e-06, 2, 2) 163s + fit2 <- ppm(amacrine ~1, MultiStrauss(types=c("off", "on"), radii=r)) 163s + chk(emend(fit2)) 163s + ## complicated multitype 163s + fit3 <- ppm(amacrine ~1, MultiStraussHard(types=c("off", "on"), 163s + iradii=r, hradii=r/5)) 163s + chk(emend(fit3)) 163s + 163s + #' code coverage 163s + op <- spatstat.options(project.fast=TRUE) 163s + fut <- emend(fit, trace=TRUE) 163s + chk(fut) 163s + spatstat.options(op) 163s + 163s + #' hierarchical 163s + ra <- r 163s + r[2,1] <- NA 163s + fit4 <- ppm(amacrine ~1, HierStrauss(types=c("off", "on"), radii=r)) 163s + chk(emend(fit4)) 163s + #' complicated hierarchical 163s + fit5 <- ppm(amacrine ~1, HierStraussHard(types=c("off", "on"), 163s + iradii=r, hradii=r/5)) 163s + chk(emend(fit5)) 163s + 163s + ## hybrids 163s + r0 <- min(nndist(redwood)) 163s + ra <- 1.25 * r0 163s + rb <- 0.8 * r0 163s + f1 <- ppm(redwood ~1, Hybrid(A=Strauss(ra), B=Geyer(0.1, 2)), project=TRUE) 163s + chk(f1) 163s + f2 <- ppm(redwood ~1, Hybrid(A=Strauss(rb), B=Geyer(0.1, 2)), project=TRUE) 163s + chk(f2) 163s + f3 <- ppm(redwood ~1, Hybrid(A=Strauss(ra), B=Strauss(0.1)), project=TRUE) 163s + chk(f3) 163s + f4 <- ppm(redwood ~1, Hybrid(A=Strauss(rb), B=Strauss(0.1)), project=TRUE) 163s + chk(f4) 163s + f5 <- ppm(redwood ~1, Hybrid(A=Hardcore(rb), B=Strauss(0.1)), project=TRUE) 163s + chk(f5) 163s + f6 <- ppm(redwood ~1, Hybrid(A=Hardcore(rb), B=Geyer(0.1, 2)), project=TRUE) 163s + chk(f6) 163s + f7 <- ppm(redwood ~1, Hybrid(A=Geyer(rb, 1), B=Strauss(0.1)), project=TRUE) 163s + chk(f7) 163s + } 163s + }) 163s > 163s > reset.spatstat.options() 163s > 163s BEGIN TEST testsQ.R 163s 163s R version 4.4.3 (2025-02-28) -- "Trophy Case" 163s Copyright (C) 2025 The R Foundation for Statistical Computing 163s Platform: x86_64-pc-linux-gnu 163s 163s R is free software and comes with ABSOLUTELY NO WARRANTY. 163s You are welcome to redistribute it under certain conditions. 163s Type 'license()' or 'licence()' for distribution details. 163s 163s R is a collaborative project with many contributors. 163s Type 'contributors()' for more information and 163s 'citation()' on how to cite R or R packages in publications. 163s 163s Type 'demo()' for some demos, 'help()' for on-line help, or 163s 'help.start()' for an HTML browser interface to help. 163s Type 'q()' to quit R. 163s 163s Loading required package: spatstat.model 163s > #' 163s > #' Header for all (concatenated) test files 163s > #' 163s > #' Require spatstat.model 163s > #' Obtain environment variable controlling tests. 163s > #' 163s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 163s > 163s > require(spatstat.model) 163s Loading required package: spatstat.data 164s Loading required package: spatstat.univar 164s spatstat.univar 3.1-2 164s Loading required package: spatstat.geom 164s spatstat.geom 3.3-6 164s Loading required package: spatstat.random 164s spatstat.random 3.3-3 164s Loading required package: spatstat.explore 164s Loading required package: nlme 164s spatstat.explore 3.3-4 164s Loading required package: rpart 164s spatstat.model 3.3-4 164s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 164s > ALWAYS <- TRUE 164s > cat(paste("--------- Executing", 164s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 164s + "test code -----------\n")) 164s --------- Executing **RESTRICTED** subset of test code ----------- 164s > 164s BEGIN TEST testsR1.R 164s 164s R version 4.4.3 (2025-02-28) -- "Trophy Case" 164s Copyright (C) 2025 The R Foundation for Statistical Computing 164s Platform: x86_64-pc-linux-gnu 164s 164s R is free software and comes with ABSOLUTELY NO WARRANTY. 164s You are welcome to redistribute it under certain conditions. 164s Type 'license()' or 'licence()' for distribution details. 164s 164s R is a collaborative project with many contributors. 164s Type 'contributors()' for more information and 164s 'citation()' on how to cite R or R packages in publications. 164s 164s Type 'demo()' for some demos, 'help()' for on-line help, or 164s 'help.start()' for an HTML browser interface to help. 164s Type 'q()' to quit R. 164s 164s > #' 164s > #' Header for all (concatenated) test files 164s > #' 164s > #' Require spatstat.model 164s > #' Obtain environment variable controlling tests. 164s > #' 164s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 164s > 164s > require(spatstat.model) 164s Loading required package: spatstat.model 164s Loading required package: spatstat.data 165s Loading required package: spatstat.univar 165s spatstat.univar 3.1-2 165s Loading required package: spatstat.geom 165s spatstat.geom 3.3-6 165s Loading required package: spatstat.random 165s spatstat.random 3.3-3 165s Loading required package: spatstat.explore 165s Loading required package: nlme 165s spatstat.explore 3.3-4 165s Loading required package: rpart 165s spatstat.model 3.3-4 165s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 165s > ALWAYS <- TRUE 165s > cat(paste("--------- Executing", 165s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 165s + "test code -----------\n")) 165s --------- Executing **RESTRICTED** subset of test code ----------- 165s > #' tests/resid.R 165s > #' 165s > #' Stuff related to residuals and residual diagnostics 165s > #' including residual summary functions 165s > #' 165s > #' $Revision: 1.7 $ $Date: 2022/05/22 08:43:31 $ 165s > #' 165s > 165s > local({ 165s + fit <- ppm(cells ~x, Strauss(r=0.15)) 165s + rr <- residuals(fit, quad=quadscheme(cells, nd=128)) 165s + diagnose.ppm(fit, cumulative=FALSE, type="pearson") 165s + 165s + if(FULLTEST) { 165s + diagnose.ppm(fit, cumulative=FALSE) 165s + 165s + fitoff <- ppm(cells ~ sin(x) + offset(y)) 165s + plot(a <- parres(fitoff, "x")) 165s + plot(b <- parres(fitoff, "y")) 165s + print(a) 165s + print(b) 165s + 165s + d <- diagnose.ppm(fit, which="marks") 165s + plot(d, plot.neg="discrete") 165s + plot(d, plot.neg="imagecontour") 165s + 165s + d <- diagnose.ppm(fit, type="pearson", which="smooth") 165s + plot(d, plot.smooth="image") 165s + plot(d, plot.smooth="contour") 165s + plot(d, plot.smooth="imagecontour") 165s + 165s + d <- diagnose.ppm(fit, type="pearson", which="x") 165s + plot(d) 165s + d <- diagnose.ppm(fit, type="pearson", which="y") 165s + plot(d) 165s + 165s + diagnose.ppm(fit, type="pearson", which="x", cumulative=FALSE) 165s + diagnose.ppm(fit, type="pearson", which="x", cumulative=FALSE) 165s + diagnose.ppm(fit, type="raw", plot.neg="discrete", plot.smooth="image") 165s + diagnose.ppm(fit, type="pearson", plot.neg="contour", plot.smooth="contour") 165s + 165s + diagnose.ppm(fitoff, type="raw", which="smooth", plot.smooth="persp") 165s + diagnose.ppm(fitoff, type="pearson", plot.neg="imagecontour") 165s + 165s + plot(Frame(letterR), main="") 165s + ploterodewin(letterR, erosion(letterR, 0.05), main="jeans") 165s + W <- as.mask(letterR) 165s + plot(Frame(W), main="") 165s + ploterodewin(W, erosion(W, 0.05), main="JeAnS") 165s + 165s + #' entangled terms in model 165s + U <- as.im(1, owin()) 165s + Z <- as.im(function(x,y) x, owin()) 165s + X <- runifpoint(40) 165s + fut <- ppm(X ~ Z:U) 165s + a <- parres(fut, "Z") 165s + futoff <- ppm(X ~ offset(Z*U)) 165s + a <- parres(futoff, "Z") 165s + 165s + #' residual summary functions 165s + pt <- psst(cells, interaction=Strauss(0.1), fun=nndcumfun) 165s + } 165s + }) 165s > 165s > 165s > 165s > ## 165s > ## tests/rhohat.R 165s > ## 165s > ## Test all combinations of options for rhohatCalc 165s > ## 165s > ## $Revision: 1.6 $ $Date: 2022/05/22 08:03:48 $ 165s > 165s > local({ 165s + if(FULLTEST) { 165s + X <- rpoispp(function(x,y){exp(3+3*x)}) 165s + Z <- as.im(function(x,y) { x }, Window(X)) 165s + f <- funxy(function(x,y) { y + 1 }, Window(X)) 165s + 165s + 165s + ## rhohat.ppm 165s + fit <- ppm(X ~x) 166s + rhofitA <- rhohat(fit, "x") 166s + rhofitB <- rhohat(fit, "x", method="reweight") 166s + rhofitC <- rhohat(fit, "x", method="transform") 166s + rhofitD <- rhohat(fit, Z) 166s + rhofitD <- rhohat(fit, Z, positiveCI=TRUE) 166s + lam <- predict(fit) 166s + 166s + 166s + ## Horvitz-Thompson 166s + rhofitAH <- rhohat(fit, "x", horvitz=TRUE) 166s + rhofitBH <- rhohat(fit, "x", method="reweight", horvitz=TRUE) 166s + rhofitCH <- rhohat(fit, "x", method="transform", horvitz=TRUE) 166s + 166s + r2myx <- rho2hat(fit, "y", "x") 166s + r2myxw <- rho2hat(fit, "y", "x", method="reweight") 166s + plot(r2myx) 166s + plot(r2myxw) 166s + print(r2myxw) 166s + predict(r2myxw) 166s + predict(r2myxw, relative=TRUE) 166s + } 166s + }) 166s > 166s BEGIN TEST testsR2.R 166s 166s R version 4.4.3 (2025-02-28) -- "Trophy Case" 166s Copyright (C) 2025 The R Foundation for Statistical Computing 166s Platform: x86_64-pc-linux-gnu 166s 166s R is free software and comes with ABSOLUTELY NO WARRANTY. 166s You are welcome to redistribute it under certain conditions. 166s Type 'license()' or 'licence()' for distribution details. 166s 166s R is a collaborative project with many contributors. 166s Type 'contributors()' for more information and 166s 'citation()' on how to cite R or R packages in publications. 166s 166s Type 'demo()' for some demos, 'help()' for on-line help, or 166s 'help.start()' for an HTML browser interface to help. 166s Type 'q()' to quit R. 166s 166s > #' 166s > #' Header for all (concatenated) test files 166s > #' 166s > #' Require spatstat.model 166s > #' Obtain environment variable controlling tests. 166s > #' 166s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 166s > 166s > require(spatstat.model) 166s Loading required package: spatstat.model 166s Loading required package: spatstat.data 166s Loading required package: spatstat.univar 166s spatstat.univar 3.1-2 166s Loading required package: spatstat.geom 167s spatstat.geom 3.3-6 167s Loading required package: spatstat.random 167s spatstat.random 3.3-3 167s Loading required package: spatstat.explore 167s Loading required package: nlme 167s spatstat.explore 3.3-4 167s Loading required package: rpart 167s spatstat.model 3.3-4 167s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 167s > ALWAYS <- TRUE 167s > cat(paste("--------- Executing", 167s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 167s + "test code -----------\n")) 167s --------- Executing **RESTRICTED** subset of test code ----------- 167s > # 167s > # tests/rmhExpand.R 167s > # 167s > # test decisions about expansion of simulation window 167s > # 167s > # $Revision: 1.9 $ $Date: 2022/10/23 01:17:33 $ 167s > # 167s > 167s > local({ 167s + if(FULLTEST) { 167s + ## check expansion in rmhmodel.ppm 167s + fit <- ppm(cells ~x) 167s + mod <- rmhmodel(fit) 167s + is.expandable(mod) 167s + wsim <- as.rectangle(mod$trend) 167s + ## work around changes in 'unitname' 167s + wcel <- as.owin(cells) 167s + unitname(wcel) <- unitname(cells) 167s + ## test 167s + if(!identical(wsim, wcel)) 167s + stop("Expansion occurred improperly in rmhmodel.ppm") 167s + } 167s + }) 167s > 167s > 167s > 167s > # 167s > # tests/rmhTrend.R 167s > # 167s > # Problems with trend images (rmhmodel.ppm or rmhEngine) 167s > # 167s > 167s > if(ALWAYS) { 167s + local({ 167s + set.seed(42) 167s + 167s + # Bug folder 37 of 8 feb 2011 167s + # rmhmodel.ppm -> predict.ppm 167s + # + rmhResolveTypes -> is.subset.owin 167s + 167s + Z <- rescale(demopat, 7000) 167s + X <- unmark(Z) 167s + X1 <- split(Z)[[1]] 167s + Int <- density(X,dimyx=200) 167s + Lint <- eval.im(log(npoints(X1)*Int/npoints(X))) 167s + M <- as.owin(Int) 167s + MR <- intersect.owin(M,scalardilate(M,0.5,origin="midpoint")) 167s + X1 <- X1[MR] 167s + Fut <- ppm(X1~offset(Lint),covariates=list(Lint=Lint), 167s + inter=BadGey(r=c(0.03,0.05),sat=3)) 167s + Y <- rmh(Fut,control=list(expand=M,nrep=1e3), verbose=FALSE) 167s + 167s + }) 167s + } 167s > # 167s > # tests/rmhmodel.ppm.R 167s > # 167s > # $Revision: 1.10 $ $Date: 2020/05/01 05:29:42 $ 167s > # 167s > # Case-by-case tests of rmhmodel.ppm 167s > # 167s > 167s > if(FULLTEST) { 167s + local({ 167s + f <- ppm(cells) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~x) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~1, Strauss(0.1)) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~1, StraussHard(r=0.1,hc=0.05)) 167s + m <- rmhmodel(f) 167s + print(m) 167s + 167s + f <- ppm(cells ~1, Hardcore(0.07)) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~1, DiggleGratton(0.05,0.1)) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~1, Softcore(0.5), correction="isotropic") 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~1, Geyer(0.07,2)) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~1, BadGey(c(0.07,0.1,0.13),2)) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~1, PairPiece(r = c(0.05, 0.1, 0.2))) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~1, AreaInter(r=0.06)) 167s + m <- rmhmodel(f) 167s + print(m) 167s + 167s + # multitype 167s + 167s + r <- matrix(0.07, 2, 2) 167s + f <- ppm(amacrine ~1, MultiStrauss(c("off","on"),r)) 167s + m <- rmhmodel(f) 167s + print(m) 167s + 167s + h <- matrix(min(nndist(amacrine))/2, 2, 2) 167s + f <- ppm(amacrine ~1, MultiStraussHard(c("off","on"),r, h)) 167s + m <- rmhmodel(f) 167s + 167s + diag(r) <- NA 167s + diag(h) <- NA 167s + f <- ppm(amacrine ~1, MultiStrauss(c("off","on"),r)) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(amacrine ~1, MultiStraussHard(c("off","on"),r, h)) 167s + m <- rmhmodel(f) 167s + 167s + # multitype data, interaction not dependent on type 167s + 167s + f <- ppm(amacrine ~marks, Strauss(0.05)) 167s + m <- rmhmodel(f) 167s + print(m) 167s + 167s + # trends 167s + 167s + f <- ppm(cells ~x, Strauss(0.1)) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~y, StraussHard(r=0.1,hc=0.05)) 167s + m <- rmhmodel(f) 167s + 167s + f <- ppm(cells ~x+y, Hardcore(0.07)) 167s + m <- rmhmodel(f) 167s + print(m) 167s + 167s + f <- ppm(cells ~polynom(x,y,2), Softcore(0.5), correction="isotropic") 167s + m <- rmhmodel(f) 167s + 167s + # covariates 167s + 167s + Z <- as.im(function(x,y){ x^2+y^2 }, as.owin(cells)) 167s + f <- ppm(cells ~z, covariates=list(z=Z)) 167s + m <- rmhmodel(f) 167s + m <- rmhmodel(f, control=list(p=1)) 167s + print(m) 167s + 167s + Zim <- as.im(Z, as.owin(cells)) 167s + f <- ppm(cells ~z, covariates=list(z=Zim)) 167s + m <- rmhmodel(f) 167s + 167s + Z <- as.im(function(x,y){ x^2+y }, as.owin(amacrine)) 167s + f <- ppm(amacrine ~z + marks, covariates=list(z=Z)) 167s + m <- rmhmodel(f) 167s + print(m) 167s + m <- rmhmodel(f, control=list(p=1)) 167s + m <- rmhmodel(f, control=list(p=1,fixall=TRUE)) 167s + print(m) 167s + 167s + Zim <- as.im(Z, as.owin(amacrine)) 167s + f <- ppm(amacrine ~z + marks, covariates=list(z=Zim)) 167s + m <- rmhmodel(f) 167s + print(m) 167s + 167s + }) 167s + } 167s > # 167s > # tests/rmhmodelHybrids.R 167s > # 167s > # Test that rmhmodel.ppm and rmhmodel.default 167s > # work on Hybrid interaction models 167s > # 167s > # $Revision: 1.6 $ $Date: 2022/10/23 01:17:56 $ 167s > # 167s > 167s > if(ALWAYS) { # involves C code 167s + local({ 167s + 167s + ## ......... rmhmodel.ppm ....................... 167s + fit1 <- ppm(redwood ~1, 167s + Hybrid(A=Strauss(0.02), B=Geyer(0.1, 2), C=Geyer(0.15, 1))) 167s + m1 <- rmhmodel(fit1) 167s + m1 167s + reach(m1) 167s + 167s + ## Test of handling 'IsOffset' 167s + fit2 <- ppm(cells ~1, Hybrid(H=Hardcore(0.05), G=Geyer(0.15, 2))) 167s + m2 <- rmhmodel(fit2) 167s + ## also test C code for hybrid interaction with hard core 167s + fakecells <- rmh(fit2, nrep=1e4) 167s + 167s + ## Test of handling Poisson components 167s + fit3 <- ppm(cells ~1, Hybrid(P=Poisson(), S=Strauss(0.05))) 167s + X3 <- rmh(fit3, control=list(nrep=1e3,expand=1), verbose=FALSE) 167s + 167s + 167s + }) 167s + } 167s Extracting model information...Evaluating trend...done. 167s Extracting model information...Evaluating trend...done. 167s Extracting model information...Evaluating trend...done. 167s Checking arguments..determining simulation windows...Starting simulation. 167s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 167s > 167s > # 167s > # tests/rmh.ppm.R 167s > # 167s > # $Revision: 1.5 $ $Date: 2020/05/01 05:29:42 $ 167s > # 167s > # Examples removed from rmh.ppm.Rd 167s > # stripped down to minimal tests of validity 167s > # 167s > 167s > local({ 167s + op <- spatstat.options() 167s + spatstat.options(rmh.nrep=10, npixel=10, ndummy.min=10) 167s + spatstat.options(project.fast=TRUE) 167s + Nrep <- 10 167s + 167s + X <- swedishpines 167s + if(FULLTEST) { 167s + ## Poisson process 167s + fit <- ppm(X ~1, Poisson()) 167s + Xsim <- rmh(fit) 167s + } 167s + if(ALWAYS) { # Gibbs model => C code 167s + ## Strauss process 167s + fit <- ppm(X ~1, Strauss(r=7)) 167s + Xsim <- rmh(fit) 167s + 167s + ## Strauss process simulated on a larger window 167s + ## then clipped to original window 167s + Xsim <- rmh(fit, control=list(nrep=Nrep, expand=1.1, periodic=TRUE)) 167s + 167s + ## Extension of model to another window (thanks to Tuomas Rajala) 167s + Xsim <- rmh(fit, w=square(2)) 167s + Xsim <- simulate(fit, w=square(2)) 167s + 167s + ## Strauss - hard core process 167s + ## fit <- ppm(X ~1, StraussHard(r=7,hc=2)) 167s + ## Xsim <- rmh(fit, start=list(n.start=X$n)) 167s + 167s + ## Geyer saturation process 167s + ## fit <- ppm(X ~1, Geyer(r=7,sat=2)) 167s + ## Xsim <- rmh(fit, start=list(n.start=X$n)) 167s + 167s + ## Area-interaction process 167s + fit <- ppm(X ~1, AreaInter(r=7)) 167s + Xsim <- rmh(fit, start=list(n.start=X$n)) 167s + 167s + ## Penttinen process 167s + fit <- ppm(X ~1, Penttinen(r=7)) 167s + Xsim <- rmh(fit, start=list(n.start=X$n)) 167s + 167s + ## soft core interaction process 167s + ## X <- quadscheme(X, nd=50) 167s + ## fit <- ppm(X ~1, Softcore(kappa=0.1), correction="isotropic") 167s + ## Xsim <- rmh(fit, start=list(n.start=X$n)) 167s + 167s + ## Diggle-Gratton pairwise interaction model 167s + ## fit <- ppm(cells ~1, DiggleGratton(0.05, 0.1)) 167s + ## Xsim <- rmh(fit, start=list(n.start=cells$n)) 167s + ## plot(Xsim, main="simulation from fitted Diggle-Gratton model") 167s + 167s + 167s + ## piecewise-constant pairwise interaction function 167s + X <- rSSI(0.05, 100) 167s + fit <- ppm(X ~1, PairPiece(seq(0.02, 0.1, by=0.01))) 167s + Xsim <- rmh(fit) 167s + } 167s + 167s + ## marked point pattern 167s + Y <- amacrine 167s + 167s + if(FULLTEST) { 167s + #' marked Poisson models 167s + fit <- ppm(Y) 167s + Ysim <- rmh(fit) 167s + 167s + fit <- ppm(Y~marks) 167s + Ysim <- rmh(fit) 167s + 167s + fit <- ppm(Y~x) 167s + Ysim <- rmh(fit) 167s + 167s + fit <- ppm(Y~marks+x) 167s + Ysim <- rmh(fit) 167s + } 167s + 167s + if(ALWAYS) { 167s + #' multitype Strauss 167s + typ <- levels(Y$marks) 167s + MS <- MultiStrauss(types = typ, 167s + radii=matrix(0.07, ncol=2, nrow=2)) 167s + 167s + fit <- ppm(Y~marks*x, MS) 167s + Ysim <- rmh(fit) 167s + 167s + #' multitype Hardcore 167s + h0 <- minnndist(unmark(Y)) * 0.95 167s + MH <- MultiHard(types = typ, 167s + hradii=matrix(h0, ncol=2, nrow=2)) 167s + fit <- ppm(Y ~ marks+x, MH) 167s + Ysim <- rmh(fit) 167s + #' other code blocks 167s + Ysim <- rmh(fit, control=list(periodic=TRUE, expand=1)) 167s + Ysim <- rmh(fit, control=list(periodic=FALSE, expand=1)) 167s + #' multihard core with invalid initial state 167s + Ydouble <- superimpose(Y, rjitter(Y, h0/10)) 167s + Ysim <- rmh(fit, start=list(x.start=Ydouble)) 167s + 167s + #' Lennard-Jones 167s + fut <- ppm(unmark(longleaf) ~ 1, LennardJones(), rbord=1) 167s + Ysim <- rmh(fut) 167s + Ysim <- rmh(fut, control=list(periodic=TRUE, expand=1)) 167s + } 167s + 167s + spatstat.options(op) 167s + }) 167s Extracting model information...Evaluating trend...done. 167s Checking arguments..determining simulation windows...Starting simulation. 167s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 167s Extracting model information...Evaluating trend...done. 167s Checking arguments..determining simulation windows...Starting simulation. 167s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 167s Extracting model information...Evaluating trend...done. 167s Checking arguments..determining simulation windows...Starting simulation. 167s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 170s Extracting model information...Evaluating trend...done. 170s Checking arguments..determining simulation windows...Starting simulation. 170s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 170s Extracting model information...Evaluating trend...done. 170s Checking arguments..determining simulation windows...Starting simulation. 170s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 170s Model is invalid - projecting it 170s Extracting model information...Evaluating trend...done. 170s Checking arguments..determining simulation windows...Starting simulation. 170s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 171s Extracting model information...Evaluating trend...done. 171s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 171s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 171s Extracting model information...Evaluating trend...done. 171s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 171s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 171s Extracting model information...Evaluating trend...done. 171s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 171s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 171s Extracting model information...Evaluating trend...done. 171s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 171s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 171s Extracting model information...Evaluating trend...done. 171s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 171s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 171s Extracting model information...Evaluating trend...done. 171s Checking arguments..determining simulation windows...Starting simulation. 171s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 172s Extracting model information...Evaluating trend...done. 172s Checking arguments..determining simulation windows...Starting simulation. 172s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 172s > 172s > 172s > reset.spatstat.options() 172s > #' 172s > #' tests/rmhsnoopy.R 172s > #' 172s > #' Test the rmh interactive debugger 172s > #' 172s > #' $Revision: 1.11 $ $Date: 2022/10/23 01:19:00 $ 172s > 172s > if(ALWAYS) { # may depend on platform 172s + local({ 172s + R <- 0.1 172s + ## fit a model and prepare to simulate 172s + model <- ppm(amacrine ~ marks + x, Strauss(R)) 172s + siminfo <- rmh(model, preponly=TRUE) 172s + Wsim <- siminfo$control$internal$w.sim 172s + Wclip <- siminfo$control$internal$w.clip 172s + if(is.null(Wclip)) Wclip <- Window(cells) 172s + 172s + ## determine debugger interface panel geometry 172s + Xinit <- runifpoint(ex=amacrine)[1:40] 172s + P <- rmhsnoop(Wsim=Wsim, Wclip=Wclip, R=R, 172s + xcoords=Xinit$x, 172s + ycoords=Xinit$y, 172s + mlevels=levels(marks(Xinit)), 172s + mcodes=as.integer(marks(Xinit)) - 1L, 172s + irep=3L, itype=1L, 172s + proptype=1, proplocn=c(0.5, 0.5), propmark=0, propindx=0, 172s + numerator=42, denominator=24, 172s + panel.only=TRUE) 172s + boxes <- P$boxes 172s + clicknames <- names(P$clicks) 172s + boxcentres <- do.call(concatxy, lapply(boxes, centroid.owin)) 172s + 172s + ## design a sequence of clicks 172s + actionsequence <- c("Up", "Down", "Left", "Right", 172s + "At Proposal", "Zoom Out", "Zoom In", "Reset", 172s + "Accept", "Reject", "Print Info", 172s + "Next Iteration", "Next Shift", "Next Death", 172s + "Skip 10", "Skip 100", "Skip 1000", "Skip 10,000", 172s + "Skip 100,000", "Exit Debugger") 172s + actionsequence <- match(actionsequence, clicknames) 172s + actionsequence <- actionsequence[!is.na(actionsequence)] 172s + xy <- lapply(boxcentres, "[", actionsequence) 172s + 172s + ## queue the click sequence 172s + spatstat.utils::queueSpatstatLocator(xy$x,xy$y) 172s + 172s + ## go 172s + rmh(model, snoop=TRUE) 172s + }) 172s + } 172s Extracting model information...Evaluating trend...done. 172s Checking arguments..determining simulation windows...Evaluating trend integral...Extracting model information...Evaluating trend...done. 172s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 172s Initial state... 172s Creating debugger environment..Done. 172s Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 172s 172s 172s ------------------- 172s Iteration 0 172s Simulation window: 172s window: rectangle = [0, 1.6012085] x [0, 1] units (one unit = 662 microns) 172s Clipping window: 172s window: rectangle = [0, 1.6012085] x [0, 1] units (one unit = 662 microns) 172s Current state: 172s Marked planar point pattern: 72 points 172s Multitype, with levels = off, on 172s window: rectangle = [0, 1.6012085] x [0, 1] units (one unit = 662 microns) 172s Proposal type: Shift 172s Shift data point 18 from current location (0.290108, 0.0160037, “off”) to 172s new location (0.620599, 0.378428, “off”) 172s Hastings ratio = 6831.92992943083 / 14545.6615344214 = 0.469688498750194 172s Fate of proposal: Rejected 174s Marked planar point pattern: 350 points 174s Multitype, with levels = off, on 174s window: rectangle = [0, 1.6012085] x [0, 1] units (one unit = 662 microns) 174s Pattern was generated by Metropolis-Hastings simulation. 174s > 174s BEGIN TEST testsS.R 174s 174s R version 4.4.3 (2025-02-28) -- "Trophy Case" 174s Copyright (C) 2025 The R Foundation for Statistical Computing 174s Platform: x86_64-pc-linux-gnu 174s 174s R is free software and comes with ABSOLUTELY NO WARRANTY. 174s You are welcome to redistribute it under certain conditions. 174s Type 'license()' or 'licence()' for distribution details. 174s 174s R is a collaborative project with many contributors. 174s Type 'contributors()' for more information and 174s 'citation()' on how to cite R or R packages in publications. 174s 174s Type 'demo()' for some demos, 'help()' for on-line help, or 174s 'help.start()' for an HTML browser interface to help. 174s Type 'q()' to quit R. 174s 174s > #' 174s > #' Header for all (concatenated) test files 174s > #' 174s > #' Require spatstat.model 174s > #' Obtain environment variable controlling tests. 174s > #' 174s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 174s > 174s > require(spatstat.model) 174s Loading required package: spatstat.model 174s Loading required package: spatstat.data 175s Loading required package: spatstat.univar 175s spatstat.univar 3.1-2 175s Loading required package: spatstat.geom 175s spatstat.geom 3.3-6 175s Loading required package: spatstat.random 175s spatstat.random 3.3-3 175s Loading required package: spatstat.explore 175s Loading required package: nlme 175s spatstat.explore 3.3-4 175s Loading required package: rpart 175s spatstat.model 3.3-4 175s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 175s > ALWAYS <- TRUE 175s > cat(paste("--------- Executing", 175s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 175s + "test code -----------\n")) 175s --------- Executing **RESTRICTED** subset of test code ----------- 175s > # 175s > # tests/slrm.R 175s > # 175s > # $Revision: 1.3 $ $Date: 2020/05/01 09:59:59 $ 175s > # 175s > # Test slrm fitting and prediction when there are NA's 175s > # 175s > 175s > if(ALWAYS) { 175s + local({ 175s + X <- copper$SouthPoints 175s + W <- owin(poly=list(x=c(0,35,35,1),y=c(1,1,150,150))) 175s + Y <- X[W] 175s + fit <- slrm(Y ~ x+y) 175s + pred <- predict(fit) 175s + extractAIC(fit) 175s + fitx <- update(fit, . ~ x) 175s + simulate(fitx, seed=42) 175s + if(FULLTEST) { 175s + unitname(fitx) 175s + unitname(fitx) <- "km" 175s + 175s + mur <- solapply(murchison,rescale, 1000, "km") 175s + mur$dfault <- distfun(mur$faults) 175s + fut <- slrm(gold ~ dfault, data=mur, splitby="greenstone") 175s + A <- model.images(fut) 175s + } 175s + }) 175s + } 175s > 175s > 175s > # 175s > # tests/step.R 175s > # 175s > # $Revision: 1.5 $ $Date: 2020/05/01 09:59:59 $ 175s > # 175s > # test for step() operation 175s > # 175s > if(FULLTEST) { 175s + local({ 175s + Z <- as.im(function(x,y){ x^3 - y^2 }, nztrees$window) 175s + fitP <- ppm(nztrees ~x+y+Z, covariates=list(Z=Z)) 175s + step(fitP) 175s + fitS <- update(fitP, Strauss(7)) 175s + step(fitS) 175s + fitM <- ppm(amacrine ~ marks*(x+y), 175s + MultiStrauss(types=levels(marks(amacrine)), radii=matrix(0.04, 2, 2))) 175s + step(fitM) 175s + }) 175s + } 175s > 175s > 175s > 175s > 175s BEGIN TEST testsT.R 175s 175s R version 4.4.3 (2025-02-28) -- "Trophy Case" 175s Copyright (C) 2025 The R Foundation for Statistical Computing 175s Platform: x86_64-pc-linux-gnu 175s 175s R is free software and comes with ABSOLUTELY NO WARRANTY. 175s You are welcome to redistribute it under certain conditions. 175s Type 'license()' or 'licence()' for distribution details. 175s 175s R is a collaborative project with many contributors. 175s Type 'contributors()' for more information and 175s 'citation()' on how to cite R or R packages in publications. 175s 175s Type 'demo()' for some demos, 'help()' for on-line help, or 175s 'help.start()' for an HTML browser interface to help. 175s Type 'q()' to quit R. 175s 175s > #' 175s > #' Header for all (concatenated) test files 175s > #' 175s > #' Require spatstat.model 175s > #' Obtain environment variable controlling tests. 175s > #' 175s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 175s > 175s > require(spatstat.model) 175s Loading required package: spatstat.model 175s Loading required package: spatstat.data 176s Loading required package: spatstat.univar 176s spatstat.univar 3.1-2 176s Loading required package: spatstat.geom 176s spatstat.geom 3.3-6 176s Loading required package: spatstat.random 176s spatstat.random 3.3-3 176s Loading required package: spatstat.explore 176s Loading required package: nlme 176s spatstat.explore 3.3-4 176s Loading required package: rpart 176s spatstat.model 3.3-4 176s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 176s > ALWAYS <- TRUE 176s > cat(paste("--------- Executing", 176s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 176s + "test code -----------\n")) 176s --------- Executing **RESTRICTED** subset of test code ----------- 176s > # 176s > # tests/testaddvar.R 176s > # 176s > # test addvar options 176s > # 176s > # $Revision: 1.3 $ $Date: 2020/05/02 01:32:58 $ 176s > 176s > if(FULLTEST) { 176s + local({ 176s + X <- rpoispp(function(x,y){exp(3+3*x)}) 176s + model <- ppm(X ~y) 176s + addvar(model, "x", crosscheck=TRUE) 176s + addvar(model, "x", bw.input="quad") 176s + w <- square(0.5) 176s + addvar(model, "x", subregion=w) 176s + addvar(model, "x", subregion=w, bw.input="points") 176s + Z <- as.im(function(x,y) { x }, Window(X)) 176s + addvar(model, Z) 176s + }) 176s + } 176s > # 176s > # tests/testparres.R 176s > # 176s > # additional test of parres 176s > # 176s > # $Revision: 1.8 $ $Date: 2022/05/20 06:59:59 $ 176s > # 176s > 176s > if(FULLTEST) { 176s + local({ 176s + X <- rpoispp(function(x,y){exp(3+x+2*x^2)}) 176s + model <- ppm(X ~x+y) 176s + 176s + # options in parres (and code blocks in print.parres) 176s + parres(model, "x") 176s + parres(model, "x", smooth.effect=TRUE) 176s + parres(model, "x", bw.input="quad") 176s + w <- square(0.5) 176s + parres(model, "x", subregion=w) 176s + parres(model, "x", subregion=w, bw.input="quad") 176s + f <- function(x,y) { x + y } 176s + parres(model, f) 176s + 176s + # check whether 'update.ppm' has messed up internals 176s + mod2 <- update(model, ~x) 176s + parres(mod2, "x") 176s + 176s + #' other kinds of covariates 176s + mod3 <- ppm(X ~ x + offset(y)) 176s + parres(mod3, "offset(y)") 176s + Z <- distmap(runifpoint(3)) 176s + parres(mod3, Z) 176s + mod4 <- ppm(X ~ sin(x), data=solist(B=Z)) 176s + parres(mod4, "sin(x)") 176s + parres(mod4, "B") 176s + 176s + #' models with interaction 176s + mod5 <- ppm(cells ~ x, AreaInter(0.06)) 176s + parres(mod5, "x") 176s + dlin <- distfun(copper$SouthLines) 176s + copfit <- ppm(copper$SouthPoints ~ dlin, Geyer(1,1)) 176s + parres(copfit, "dlin") 176s + 176s + #' covariate need not be specified if there is only one. 176s + parres(mod5) 176s + parres(copfit) 176s + 176s + #' infrastructure 176s + ltuae <- evaluateCovariate(42, cells) 176s + LTUAE <- evaluateCovariate(ltuae, cells) 176s + 176s + fit <- ppm(amacrine ~ x * marks, nd=16) 176s + dmat <- model.depends(fit) 176s + check.separable(dmat, "x", c(x=FALSE, marks=FALSE), FALSE) 176s + check.separable(dmat, "x", c(FALSE, FALSE), FALSE) 176s + check.separable(dmat, "x", c(x=FALSE, marks=TRUE), FALSE) 176s + }) 176s + } 176s > #' 176s > #' tests/threedee.R 176s > #' 176s > #' Tests of 3D code 176s > #' 176s > #' $Revision: 1.8 $ $Date: 2020/05/02 01:32:58 $ 176s > #' 176s > 176s > local({ 176s + X <- runifpoint3(30) 176s + Y <- runifpoint3(20) 176s + if(FULLTEST) { 176s + A <- runifpoint3(10, nsim=2) 176s + Z <- ppsubset(X, 2:4) 176s + } 176s + ## 176s + if(ALWAYS) { # includes C code 176s + d <- pairdist(X, periodic=TRUE, squared=TRUE) 176s + d <- crossdist(X, Y, squared=TRUE) 176s + d <- crossdist(X, Y, squared=TRUE, periodic=TRUE) 176s + #' 176s + h <- has.close(X, 0.2) 176s + h <- has.close(X, 0.2, periodic=TRUE) 176s + h <- has.close(X, 0.2, Y=Y) 176s + h <- has.close(X, 0.2, Y=Y, periodic=TRUE) 176s + #' code blocks not otherwise reached 176s + rmax <- 0.6 * max(nndist(X)) 176s + g <- G3est(X, rmax=rmax, correction="rs") 176s + g <- G3est(X, rmax=rmax, correction="km") 176s + g <- G3est(X, rmax=rmax, correction="Hanisch") 176s + g <- G3est(X, rmax=rmax, sphere="ideal") 176s + g <- G3est(X, rmax=rmax, sphere="digital") 176s + v <- sphere.volume() 176s + v <- digital.volume() 176s + #' older code 176s + co <- coords(X) 176s + xx <- co$x 176s + yy <- co$y 176s + zz <- co$z 176s + gg1 <- g3engine(xx, yy, zz, correction="Hanisch G3") 176s + gg2 <- g3engine(xx, yy, zz, correction="minus sampling") 176s + ff1 <- f3engine(xx, yy, zz, correction="no") 176s + ff2 <- f3engine(xx, yy, zz, correction="minus sampling") 176s + } 176s + ## 176s + if(ALWAYS) { 176s + #'class support 176s + X <- runifpoint3(10) 176s + print(X) 176s + print(X %mark% runif(10)) 176s + print(X %mark% factor(letters[c(1:5,5:1)])) 176s + print(X %mark% data.frame(a=1:10, b=runif(10))) 176s + da <- as.Date(paste0("2020-01-0", c(1:5,5:1))) 176s + print(X %mark% da) 176s + print(X %mark% data.frame(a=1:10, b=da)) 176s + } 176s + }) 176s Three-dimensional point pattern: 10 points 176s Box: [0, 1] x [0, 1] x [0, 1] units 176s Marked three-dimensional point pattern: 10 points 176s marks are numeric, of storage type ‘double’ 176s Box: [0, 1] x [0, 1] x [0, 1] units 176s Marked three-dimensional point pattern: 10 points 176s Multitype, with levels = a, b, c, d, e 176s Box: [0, 1] x [0, 1] x [0, 1] units 176s Marked three-dimensional point pattern: 10 points 176s Mark variables: a, b 176s Box: [0, 1] x [0, 1] x [0, 1] units 176s Marked three-dimensional point pattern: 10 points 176s marks are dates, of class ‘Date’ 176s Box: [0, 1] x [0, 1] x [0, 1] units 176s Marked three-dimensional Warning messages: 176s 1: In G3est: unrecognised argument ‘sphere’ was ignored 176s 2: In G3est: unrecognised argument ‘sphere’ was ignored 176s point pattern: 10 points 176s Mark variables: a, b 176s Box: [0, 1] x [0, 1] x [0, 1] units 176s > # 176s > # tests/triplets.R 176s > # 176s > # test code for triplet interaction 176s > # 176s > # $Revision: 1.9 $ $Date: 2022/05/22 08:45:38 $ 176s > # 176s > if(ALWAYS) { # C code, platform dependence 176s + local({ 176s + #' valid model 176s + fit <- ppm(cells ~1, Triplets(0.1)) 176s + fit 176s + suffstat(fit) 176s + #' invalid model 176s + fitR <- ppm(redwood ~1, Triplets(0.1)) 176s + fitR 176s + suffstat(fitR) 176s + #' hard core (zero triangles, coefficient is NA) 176s + fit0 <- ppm(cells ~1, Triplets(0.05)) 176s + fit0 176s + suffstat(fit0) 176s + #' bug case (1 triangle in data) 176s + fit1 <- ppm(cells ~1, Triplets(0.15)) 176s + fit1 176s + suffstat(fit1) 176s + #' simulation 176s + X <- simulate(fit) 176s + mod <- list(cif="triplets",par=list(beta=50,gamma=0.2,r=0.07), w=square(1)) 176s + Xm <- rmh(model=mod,start=list(n.start=5), control=list(nrep=1e5)) 176s + #' hard core 176s + mod$par$gamma <- 0 176s + XmHard <- rmh(model=mod,start=list(n.start=5), control=list(nrep=1e5)) 176s + }) 176s + } 177s Checking arguments..determining simulation windows...Starting simulation. 177s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 177s Checking arguments..determining simulation windows...Starting simulation. 177s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 177s > 177s BEGIN TEST testsUtoZ.R 177s 177s R version 4.4.3 (2025-02-28) -- "Trophy Case" 177s Copyright (C) 2025 The R Foundation for Statistical Computing 177s Platform: x86_64-pc-linux-gnu 177s 177s R is free software and comes with ABSOLUTELY NO WARRANTY. 177s You are welcome to redistribute it under certain conditions. 177s Type 'license()' or 'licence()' for distribution details. 177s 177s R is a collaborative project with many contributors. 177s Type 'contributors()' for more information and 177s 'citation()' on how to cite R or R packages in publications. 177s 177s Type 'demo()' for some demos, 'help()' for on-line help, or 177s 'help.start()' for an HTML browser interface to help. 177s Type 'q()' to quit R. 177s 178s > #' 178s > #' Header for all (concatenated) test files 178s > #' 178s > #' Require spatstat.model 178s > #' Obtain environment variable controlling tests. 178s > #' 178s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 178s > 178s > require(spatstat.model) 178s Loading required package: spatstat.model 178s Loading required package: spatstat.data 178s Loading required package: spatstat.univar 178s spatstat.univar 3.1-2 178s Loading required package: spatstat.geom 178s spatstat.geom 3.3-6 178s Loading required package: spatstat.random 178s spatstat.random 3.3-3 178s Loading required package: spatstat.explore 178s Loading required package: nlme 179s spatstat.explore 3.3-4 179s Loading required package: rpart 179s spatstat.model 3.3-4 179s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 179s > ALWAYS <- TRUE 179s > cat(paste("--------- Executing", 179s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 179s + "test code -----------\n")) 179s --------- Executing **RESTRICTED** subset of test code ----------- 179s > # 179s > # tests/undoc.R 179s > # 179s > # $Revision: 1.16 $ $Date: 2020/11/02 07:06:49 $ 179s > # 179s > # Test undocumented hacks, experimental code, etc 179s > 179s > 179s > local({ 179s + if(FULLTEST) { 179s + ## cases of 'pickoption' 179s + aliases <- c(Lenin="Ulyanov", Stalin="Djugashvili", Trotsky="Bronstein") 179s + surname <- "Trot" 179s + pickoption("leader", surname, aliases) 179s + pickoption("leader", surname, aliases, exact=TRUE, die=FALSE) 179s + } 179s + if(ALWAYS) { 179s + ## pixellate.ppp accepts a data frame of weights 179s + pixellate(cells, weights=data.frame(a=1:42, b=42:1)) 179s + ## test parts of 'rmhsnoop' that don't require interaction with user 179s + rmhSnoopEnv(cells, Window(cells), 0.1) 179s + } 179s + if(FULLTEST) { 179s + ## Berman-Turner frame 179s + A <- bt.frame(quadscheme(cells), ~x, Strauss(0.07), rbord=0.07) 179s + print(A) 179s + ## digestCovariates 179s + D <- distfun(cells) 179s + Z <- distmap(cells) 179s + U <- dirichlet(cells) 179s + stopifnot(is.scov(D)) 179s + stopifnot(is.scov(Z)) 179s + stopifnot(is.scov(U)) 179s + stopifnot(is.scov("x")) 179s + dg <- digestCovariates(D=D,Z=Z,U=U,"x",list(A="x", B=D)) 179s + ## 179s + a <- getfields(dg, c("A", "D", "niets"), fatal=FALSE) 179s + ## util.R 179s + gg <- pointgrid(owin(), 7) 179s + checkbigmatrix(1000000L, 1000000L, FALSE, TRUE) 179s + spatstatDiagnostic("whatever") 179s + M <- list(list(a=2, b=FALSE), 179s + list(a=2, b=TRUE)) 179s + stopifnot(!allElementsIdentical(M)) 179s + stopifnot(allElementsIdentical(M, "a")) 179s + ## 179s + A <- Strauss(0.1) 179s + A <- reincarnate.interact(A) 179s + ## 179s + ## special lists 179s + B <- solist(a=cells, b=redwood, c=japanesepines) 179s + BB <- as.ppplist(B) 179s + BL <- as.layered(B) 179s + DB <- as.imlist(lapply(B, density)) 179s + is.solist(B) 179s + is.ppplist(B) 179s + is.imlist(DB) 179s + ## case of density.ppplist 179s + DEB <- density(BB, se=TRUE) 179s + } 179s + 179s + if(ALWAYS) { 179s + ## fft 179s + z <- matrix(1:16, 4, 4) 179s + a <- fft2D(z, west=FALSE) 179s + if(fftwAvailable()) 179s + b <- fft2D(z, west=TRUE) 179s + } 179s + 179s + if(ALWAYS) { 179s + ## experimental interactions 179s + pot <- function(d, par) { d <= 0.1 } 179s + A <- Saturated(pot) 179s + print(A) 179s + A <- update(A, name="something") 179s + ppm(amacrine ~ x, A, rbord=0.1) 179s + } 179s + 179s + if(ALWAYS) { # platform dependent 179s + #' version-checking 179s + now <- Sys.Date() 179s + versioncurrency.spatstat(now + 80, FALSE) 179s + versioncurrency.spatstat(now + 140, FALSE) 179s + versioncurrency.spatstat(now + 400, FALSE) 179s + versioncurrency.spatstat(now + 1000) 179s + } 179s + 179s + if(FULLTEST) { 179s + #' general Ord interaction 179s + gradual <- function(d, pars) { 179s + y <- pmax(0, 0.005 - d)/0.005 179s + if(is.matrix(d)) y <- matrix(y, nrow(d), ncol(d)) 179s + return(y) 179s + } 179s + B <- Ord(gradual, "gradual Ord process") 179s + } 179s + }) 179s Saturated pairwise interaction family 179s Interaction:Saturated process with user-defined potential 179s Potential function: 179s function (d, par) 179s { 179s d <= 0.1 179s } 179s 179s > 179s > 179s > ## 179s > ## tests/updateppm.R 179s > ## 179s > ## Check validity of update.ppm 179s > ## 179s > ## $Revision: 1.8 $ $Date: 2022/10/23 01:19:19 $ 179s > 179s > local({ 179s + if(ALWAYS) { 179s + require(spatstat.utils) 179s + h <- function(m1, m2) { 179s + mc <- short.deparse(sys.call()) 179s + cat(paste(mc, "\t... ")) 179s + m1name <- short.deparse(substitute(m1)) 179s + m2name <- short.deparse(substitute(m2)) 179s + if(!identical(names(coef(m1)), names(coef(m2)))) 179s + stop(paste("Differing results for", m1name, "and", m2name, 179s + "in updateppm.R"), 179s + call.=FALSE) 179s + cat("OK\n") 179s + } 179s + 179s + X <- redwood[c(TRUE,FALSE)] 179s Loading required package: spatstat.utils 179s + Y <- redwood[c(FALSE,TRUE)] 179s + fit0f <- ppm(X ~ 1, nd=8) 179s + fit0p <- ppm(X, ~1, nd=8) 179s + fitxf <- ppm(X ~ x, nd=8) 179s + fitxp <- ppm(X, ~x, nd=8) 179s + 179s + cat("Basic consistency ...\n") 179s + h(fit0f, fit0p) 179s + h(fitxf, fitxp) 179s + 179s + cat("\nTest correct handling of model formulas ...\n") 179s + h(update(fitxf, Y), fitxf) 179s + h(update(fitxf, Q=Y), fitxf) 179s + h(update(fitxf, Y~x), fitxf) 179s + h(update(fitxf, Q=Y~x), fitxf) 179s + h(update(fitxf, ~x), fitxf) 179s + } 179s + 179s + if(FULLTEST) { 179s + h(update(fitxf, Y~1), fit0f) 179s + h(update(fitxf, ~1), fit0f) 179s + h(update(fit0f, Y~x), fitxf) 179s + h(update(fit0f, ~x), fitxf) 179s + 179s + h(update(fitxp, Y), fitxp) 179s + h(update(fitxp, Q=Y), fitxp) 179s + h(update(fitxp, Y~x), fitxp) 179s + h(update(fitxp, Q=Y~x), fitxp) 179s + h(update(fitxp, ~x), fitxp) 179s + 179s + h(update(fitxp, Y~1), fit0p) 179s + h(update(fitxp, ~1), fit0p) 179s + h(update(fit0p, Y~x), fitxp) 179s + h(update(fit0p, ~x), fitxp) 179s + } 179s + 179s + if(ALWAYS) { 179s + cat("\nTest scope handling for left hand side ...\n") 179s + X <- Y 179s + h(update(fitxf), fitxf) 179s + } 179s + 179s + if(ALWAYS) { 179s + cat("\nTest scope handling for right hand side ...\n") 179s + Z <- distmap(X) 179s + fitZf <- ppm(X ~ Z) 179s + fitZp <- ppm(X, ~ Z) 179s + h(update(fitxf, X ~ Z), fitZf) 179s + } 179s + if(FULLTEST) { 179s + h(update(fitxp, X ~ Z), fitZp) 179s + h(update(fitxf, . ~ Z), fitZf) 179s + h(update(fitZf, . ~ x), fitxf) 179s + h(update(fitZf, . ~ . - Z), fit0f) 179s + h(update(fitxp, . ~ Z), fitZp) 179s + h(update(fitZp, . ~ . - Z), fit0p) 179s + h(update(fit0p, . ~ . + Z), fitZp) 179s + h(update(fitZf, . ~ . ), fitZf) 179s + h(update(fitZp, . ~ . ), fitZp) 179s + } 179s + if(ALWAYS) { 179s + cat("\nTest use of internal data ...\n") 179s + h(update(fitZf, ~ x, use.internal=TRUE), fitxf) 179s + fitsin <- update(fitZf, X~sin(Z)) 179s + h(update(fitZf, ~ sin(Z), use.internal=TRUE), fitsin) 179s + } 179s + if(FULLTEST) { 179s + cat("\nTest step() ... ") 179s + fut <- ppm(X ~ Z + x + y, nd=8) 179s + fut0 <- step(fut, trace=0) 179s + cat("OK\n") 179s + } 179s + 179s + }) 179s Basic consistency ... 179s h(fit0f, fit0p) ... OK 179s h(fitxf, fitxp) ... OK 179s 179s Test correct handling of model formulas ... 179s h(update(fitxf, Y), fitxf) ... OK 179s h(update(fitxf, Q = Y), fitxf) ... OK 179s h(update(fitxf, Y ~ x), fitxf) ... OK 179s h(update(fitxf, Q = Y ~ x), fitxf) ... OK 179s h(update(fitxf, ~x), fitxf) ... OK 179s 179s Test scope handling for left hand side ... 179s h(update(fitxf), fitxf) ... OK 179s 179s Test scope handling for right hand side ... 179s h(update(fitxf, X ~ Z), fitZf) ... OK 179s 179s Test use of internal data ... 179s h(update(fitZf, ~x, use.internal = TRUE), fitxf) ... OK 179s h(update(fitZf, ~sin(Z), use.internal = TRUE), fitsin) ... OK 179s > # 179s > # tests/vcovppm.R 179s > # 179s > # Check validity of vcov.ppm algorithms 179s > # 179s > # Thanks to Ege Rubak 179s > # 179s > # $Revision: 1.12 $ $Date: 2020/05/02 01:32:58 $ 179s > # 179s > 179s > local({ 179s + 179s + set.seed(42) 179s + X <- rStrauss(200, .5, .05) 179s + model <- ppm(X, inter = Strauss(.05)) 179s + 179s + if(ALWAYS) { 179s + b <- vcov(model, generic = TRUE, algorithm = "basic") 179s + v <- vcov(model, generic = TRUE, algorithm = "vector") 179s + vc <- vcov(model, generic = TRUE, algorithm = "vectorclip") 179s + vn <- vcov(model, generic = FALSE) 179s + 179s + disagree <- function(x, y, tol=1e-7) { max(abs(x-y)) > tol } 179s + asymmetric <- function(x) { disagree(x, t(x)) } 179s + 179s + if(asymmetric(b)) 179s + stop("Non-symmetric matrix produced by vcov.ppm 'basic' algorithm") 179s + if(asymmetric(v)) 179s + stop("Non-symmetric matrix produced by vcov.ppm 'vector' algorithm") 179s + if(asymmetric(vc)) 179s + stop("Non-symmetric matrix produced by vcov.ppm 'vectorclip' algorithm") 179s + if(asymmetric(vn)) 179s + stop("Non-symmetric matrix produced by vcov.ppm Strauss algorithm") 179s + 179s + if(disagree(v, b)) 179s + stop("Disagreement between vcov.ppm algorithms 'vector' and 'basic' ") 179s + if(disagree(v, vc)) 179s + stop("Disagreement between vcov.ppm algorithms 'vector' and 'vectorclip' ") 179s + if(disagree(vn, vc)) 179s + stop("Disagreement between vcov.ppm generic and Strauss algorithms") 179s + } 179s + 179s + if(ALWAYS) { # C code 179s + ## Geyer code 179s + xx <- c(0.7375956, 0.6851697, 0.6399788, 0.6188382) 179s + yy <- c(0.5816040, 0.6456319, 0.5150633, 0.6191592) 179s + Y <- ppp(xx, yy, window=square(1)) 179s + modelY <- ppm(Y ~1, Geyer(0.1, 1)) 179s + 179s + b <- vcov(modelY, generic = TRUE, algorithm = "basic") 179s + v <- vcov(modelY, generic = TRUE, algorithm = "vector") 179s + vc <- vcov(modelY, generic = TRUE, algorithm = "vectorclip") 179s + 179s + if(asymmetric(b)) 179s + stop("Non-symmetric matrix produced by vcov.ppm 'basic' algorithm for Geyer model") 179s + if(asymmetric(v)) 179s + stop("Non-symmetric matrix produced by vcov.ppm 'vector' algorithm for Geyer model") 179s + if(asymmetric(vc)) 179s + stop("Non-symmetric matrix produced by vcov.ppm 'vectorclip' algorithm for Geyer model") 179s + 179s + if(disagree(v, b)) 179s + stop("Disagreement between vcov.ppm algorithms 'vector' and 'basic' for Geyer model") 179s + if(disagree(v, vc)) 179s + stop("Disagreement between vcov.ppm algorithms 'vector' and 'vectorclip' for Geyer model") 179s + } 179s + 179s + if(ALWAYS) { # C code 179s + ## tests of 'deltasuffstat' code 179s + ## Handling of offset terms 179s + modelH <- ppm(cells ~x, Hardcore(0.05)) 179s + a <- vcov(modelH, generic=TRUE) ## may fall over 179s + b <- vcov(modelH, generic=FALSE) 179s + if(disagree(a, b)) 179s + stop("Disagreement between vcov.ppm algorithms for Hardcore model") 179s + 179s + ## Correctness of pairwise.family$delta2 179s + modelZ <- ppm(amacrine ~1, MultiStrauss(radii=matrix(0.1, 2, 2))) 179s + b <- vcov(modelZ, generic=FALSE) 179s + g <- vcov(modelZ, generic=TRUE) 179s + if(disagree(b, g)) 179s + stop("Disagreement between vcov.ppm algorithms for MultiStrauss model") 179s + 179s + ## Test that 'deltasuffstat' works for Hybrids 179s + modelHyb <- ppm(japanesepines ~ 1, Hybrid(Strauss(0.05), Strauss(0.1))) 179s + vHyb <- vcov(modelHyb) 179s + } 179s + 179s + if(FULLTEST) { 179s + ## Code blocks for other choices of 'what' 179s + model <- ppm(X ~ 1, Strauss(.05)) 179s + cG <- vcov(model, what="corr") 179s + cP <- vcov(update(model, Poisson()), what="corr") 179s + ## outdated usage 179s + cX <- vcov(model, A1dummy=TRUE) 179s + 179s + ## Model with zero-length coefficient vector 179s + lam <- intensity(X) 179s + f <- function(x,y) { rep(lam, length(x)) } 179s + model0 <- ppm(X ~ offset(log(f)) - 1) 179s + dd <- vcov(model0) 179s + cc <- vcov(model0, what="corr") 179s + 179s + ## Model with NA coefficients 179s + fit <- ppm(X ~ log(f)) 179s + vcov(fit) 179s + fitE <- emend(fit, trace=TRUE) 179s + 179s + ## Other weird stuff 179s + su <- suffloc(ppm(X ~ x)) 179s + } 179s + }) 181s > 181s autopkgtest [18:57:14]: test run-unit-test: -----------------------] 182s run-unit-test PASS 182s autopkgtest [18:57:15]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 182s autopkgtest [18:57:15]: test pkg-r-autopkgtest: preparing testbed 271s autopkgtest [18:58:44]: testbed dpkg architecture: amd64 271s autopkgtest [18:58:44]: testbed apt version: 3.0.0 272s autopkgtest [18:58:45]: @@@@@@@@@@@@@@@@@@@@ test bed setup 272s autopkgtest [18:58:45]: testbed release detected to be: questing 273s autopkgtest [18:58:46]: updating testbed package index (apt update) 273s Get:1 http://ftpmaster.internal/ubuntu questing-proposed InRelease [110 kB] 273s Hit:2 http://ftpmaster.internal/ubuntu questing InRelease 273s Hit:3 http://ftpmaster.internal/ubuntu questing-updates InRelease 273s Hit:4 http://ftpmaster.internal/ubuntu questing-security InRelease 273s Get:5 http://ftpmaster.internal/ubuntu questing-proposed/multiverse Sources [33.7 kB] 273s Get:6 http://ftpmaster.internal/ubuntu questing-proposed/universe Sources [1442 kB] 274s Get:7 http://ftpmaster.internal/ubuntu questing-proposed/main Sources [149 kB] 274s Get:8 http://ftpmaster.internal/ubuntu questing-proposed/main i386 Packages [146 kB] 274s Get:9 http://ftpmaster.internal/ubuntu questing-proposed/main amd64 Packages [203 kB] 274s Get:10 http://ftpmaster.internal/ubuntu questing-proposed/universe amd64 Packages [1424 kB] 274s Get:11 http://ftpmaster.internal/ubuntu questing-proposed/universe i386 Packages [576 kB] 274s Get:12 http://ftpmaster.internal/ubuntu questing-proposed/multiverse i386 Packages [23.1 kB] 274s Get:13 http://ftpmaster.internal/ubuntu questing-proposed/multiverse amd64 Packages [48.6 kB] 274s Fetched 4155 kB in 1s (3670 kB/s) 275s Reading package lists... 276s autopkgtest [18:58:49]: upgrading testbed (apt dist-upgrade and autopurge) 276s Reading package lists... 276s Building dependency tree... 276s Reading state information... 276s Calculating upgrade...Starting pkgProblemResolver with broken count: 0 276s Starting 2 pkgProblemResolver with broken count: 0 276s Done 277s Entering ResolveByKeep 277s 277s Calculating upgrade... 277s The following packages will be upgraded: 277s cloud-init cloud-init-base debianutils libmbim-glib4 libmbim-proxy 277s libnftnl11 libqmi-glib5 libqmi-proxy libsepol2 python3-lazr.restfulclient 277s sos 278s 11 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 278s Need to get 2693 kB of archives. 278s After this operation, 104 kB disk space will be freed. 278s Get:1 http://ftpmaster.internal/ubuntu questing/main amd64 debianutils amd64 5.22 [93.0 kB] 278s Get:2 http://ftpmaster.internal/ubuntu questing/main amd64 libsepol2 amd64 3.8.1-1 [327 kB] 278s Get:3 http://ftpmaster.internal/ubuntu questing/main amd64 libnftnl11 amd64 1.2.9-1 [69.1 kB] 278s Get:4 http://ftpmaster.internal/ubuntu questing/main amd64 cloud-init-base all 25.2~1g7a0265d3-0ubuntu1 [619 kB] 278s Get:5 http://ftpmaster.internal/ubuntu questing/main amd64 libmbim-proxy amd64 1.32.0-1 [6276 B] 278s Get:6 http://ftpmaster.internal/ubuntu questing/main amd64 libmbim-glib4 amd64 1.32.0-1 [233 kB] 278s Get:7 http://ftpmaster.internal/ubuntu questing/main amd64 libqmi-proxy amd64 1.36.0-1 [6220 B] 278s Get:8 http://ftpmaster.internal/ubuntu questing/main amd64 libqmi-glib5 amd64 1.36.0-1 [920 kB] 278s Get:9 http://ftpmaster.internal/ubuntu questing/main amd64 python3-lazr.restfulclient all 0.14.6-3 [51.0 kB] 278s Get:10 http://ftpmaster.internal/ubuntu questing/main amd64 sos all 4.9.1-1 [367 kB] 278s Get:11 http://ftpmaster.internal/ubuntu questing/main amd64 cloud-init all 25.2~1g7a0265d3-0ubuntu1 [2106 B] 278s Preconfiguring packages ... 278s Fetched 2693 kB in 1s (4394 kB/s) 279s (Reading database ... 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python3-lazr.restfulclient (0.14.6-3) ... 283s Setting up libmbim-glib4:amd64 (1.32.0-1) ... 283s Setting up cloud-init (25.2~1g7a0265d3-0ubuntu1) ... 283s Setting up libmbim-proxy (1.32.0-1) ... 283s Setting up libqmi-glib5:amd64 (1.36.0-1) ... 283s Setting up libqmi-proxy (1.36.0-1) ... 283s Processing triggers for libc-bin (2.41-6ubuntu1) ... 283s Processing triggers for rsyslog (8.2412.0-2ubuntu2) ... 283s Processing triggers for man-db (2.13.0-1) ... 285s Reading package lists... 285s Building dependency tree... 285s Reading state information... 286s Starting pkgProblemResolver with broken count: 0 286s Starting 2 pkgProblemResolver with broken count: 0 286s Done 286s Solving dependencies... 286s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 287s autopkgtest [18:59:00]: rebooting testbed after setup commands that affected boot 313s Reading package lists... 313s Building dependency tree... 313s Reading state information... 313s Starting pkgProblemResolver with broken count: 0 313s Starting 2 pkgProblemResolver with broken count: 0 313s Done 314s The following NEW packages will be installed: 314s build-essential cpp cpp-14 cpp-14-x86-64-linux-gnu cpp-x86-64-linux-gnu 314s dctrl-tools fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono 314s fonts-mathjax g++ g++-14 g++-14-x86-64-linux-gnu g++-x86-64-linux-gnu gcc 314s gcc-14 gcc-14-x86-64-linux-gnu gcc-x86-64-linux-gnu gfortran gfortran-14 314s gfortran-14-x86-64-linux-gnu gfortran-x86-64-linux-gnu icu-devtools libasan8 314s libblas-dev libblas3 libbz2-dev libcairo2 libcc1-0 libdatrie1 libdeflate-dev 314s libdeflate0 libfontconfig1 libgcc-14-dev libgfortran-14-dev libgfortran5 314s libgomp1 libgraphite2-3 libgsl28 libgslcblas0 libharfbuzz0b libhwasan0 314s libice6 libicu-dev libisl23 libitm1 libjbig0 libjpeg-dev libjpeg-turbo8 314s libjpeg-turbo8-dev libjpeg8 libjpeg8-dev libjs-mathjax liblapack-dev 314s liblapack3 liblerc4 liblsan0 liblzma-dev libmpc3 libncurses-dev 314s libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 libpaper-utils 314s libpaper2 libpcre2-16-0 libpcre2-32-0 libpcre2-dev libpcre2-posix3 314s libpixman-1-0 libpkgconf3 libpng-dev libquadmath0 libreadline-dev 314s libsharpyuv0 libsm6 libstdc++-14-dev libtcl8.6 libthai-data libthai0 314s libtiff6 libtirpc-dev libtk8.6 libtsan2 libubsan1 libwebp7 libxcb-render0 314s libxcb-shm0 libxft2 libxrender1 libxss1 libxt6t64 littler pkg-r-autopkgtest 314s pkgconf pkgconf-bin r-base-core r-base-dev r-cran-abind r-cran-codetools 314s r-cran-deldir r-cran-foreach r-cran-glmnet r-cran-goftest r-cran-gsl 314s r-cran-iterators r-cran-lattice r-cran-littler r-cran-matrix r-cran-mgcv 314s r-cran-nleqslv r-cran-nlme r-cran-pkgkitten r-cran-polyclip r-cran-rcpp 314s r-cran-rcppeigen r-cran-rpart r-cran-shape r-cran-sm r-cran-spatial 314s r-cran-spatstat r-cran-spatstat.data r-cran-spatstat.explore 314s r-cran-spatstat.geom r-cran-spatstat.linnet r-cran-spatstat.model 314s r-cran-spatstat.random r-cran-spatstat.sparse r-cran-spatstat.univar 314s r-cran-spatstat.utils r-cran-survival r-cran-tensor unzip x11-common 314s xdg-utils zip zlib1g-dev 314s 0 upgraded, 138 newly installed, 0 to remove and 0 not upgraded. 314s Need to get 205 MB of archives. 314s After this operation, 580 MB of additional disk space will be used. 314s Get:1 http://ftpmaster.internal/ubuntu questing/main amd64 libisl23 amd64 0.27-1 [685 kB] 314s Get:2 http://ftpmaster.internal/ubuntu questing/main amd64 libmpc3 amd64 1.3.1-1build2 [55.3 kB] 314s Get:3 http://ftpmaster.internal/ubuntu questing/main amd64 cpp-14-x86-64-linux-gnu amd64 14.2.0-19ubuntu2 [11.9 MB] 315s Get:4 http://ftpmaster.internal/ubuntu questing/main amd64 cpp-14 amd64 14.2.0-19ubuntu2 [1030 B] 315s Get:5 http://ftpmaster.internal/ubuntu questing/main amd64 cpp-x86-64-linux-gnu amd64 4:14.2.0-1ubuntu1 [5586 B] 315s Get:6 http://ftpmaster.internal/ubuntu questing/main amd64 cpp amd64 4:14.2.0-1ubuntu1 [22.4 kB] 315s Get:7 http://ftpmaster.internal/ubuntu questing/main amd64 libcc1-0 amd64 15-20250404-0ubuntu1 [47.1 kB] 315s Get:8 http://ftpmaster.internal/ubuntu questing/main amd64 libgomp1 amd64 15-20250404-0ubuntu1 [151 kB] 315s Get:9 http://ftpmaster.internal/ubuntu questing/main amd64 libitm1 amd64 15-20250404-0ubuntu1 [29.5 kB] 315s Get:10 http://ftpmaster.internal/ubuntu questing/main amd64 libasan8 amd64 15-20250404-0ubuntu1 [3076 kB] 315s Get:11 http://ftpmaster.internal/ubuntu questing/main amd64 liblsan0 amd64 15-20250404-0ubuntu1 [1362 kB] 315s Get:12 http://ftpmaster.internal/ubuntu questing/main amd64 libtsan2 amd64 15-20250404-0ubuntu1 [2760 kB] 315s Get:13 http://ftpmaster.internal/ubuntu questing/main amd64 libubsan1 amd64 15-20250404-0ubuntu1 [1211 kB] 315s Get:14 http://ftpmaster.internal/ubuntu questing/main amd64 libhwasan0 amd64 15-20250404-0ubuntu1 [1687 kB] 315s Get:15 http://ftpmaster.internal/ubuntu questing/main amd64 libquadmath0 amd64 15-20250404-0ubuntu1 [153 kB] 315s Get:16 http://ftpmaster.internal/ubuntu questing/main amd64 libgcc-14-dev amd64 14.2.0-19ubuntu2 [2815 kB] 315s Get:17 http://ftpmaster.internal/ubuntu questing/main amd64 gcc-14-x86-64-linux-gnu amd64 14.2.0-19ubuntu2 [23.3 MB] 316s Get:18 http://ftpmaster.internal/ubuntu questing/main amd64 gcc-14 amd64 14.2.0-19ubuntu2 [540 kB] 316s Get:19 http://ftpmaster.internal/ubuntu questing/main amd64 gcc-x86-64-linux-gnu amd64 4:14.2.0-1ubuntu1 [1208 B] 316s Get:20 http://ftpmaster.internal/ubuntu questing/main amd64 gcc amd64 4:14.2.0-1ubuntu1 [5004 B] 316s Get:21 http://ftpmaster.internal/ubuntu questing/main amd64 libstdc++-14-dev amd64 14.2.0-19ubuntu2 [2510 kB] 316s Get:22 http://ftpmaster.internal/ubuntu questing/main amd64 g++-14-x86-64-linux-gnu amd64 14.2.0-19ubuntu2 [13.4 MB] 316s Get:23 http://ftpmaster.internal/ubuntu questing/main amd64 g++-14 amd64 14.2.0-19ubuntu2 [23.0 kB] 316s Get:24 http://ftpmaster.internal/ubuntu questing/main amd64 g++-x86-64-linux-gnu amd64 4:14.2.0-1ubuntu1 [968 B] 316s Get:25 http://ftpmaster.internal/ubuntu questing/main amd64 g++ amd64 4:14.2.0-1ubuntu1 [1100 B] 316s Get:26 http://ftpmaster.internal/ubuntu questing/main amd64 build-essential amd64 12.12ubuntu1 [5080 B] 316s Get:27 http://ftpmaster.internal/ubuntu questing/main amd64 dctrl-tools amd64 2.24-3build3 [106 kB] 316s Get:28 http://ftpmaster.internal/ubuntu questing/main amd64 fonts-dejavu-mono all 2.37-8 [502 kB] 316s Get:29 http://ftpmaster.internal/ubuntu questing/main amd64 fonts-dejavu-core all 2.37-8 [835 kB] 316s Get:30 http://ftpmaster.internal/ubuntu questing/main amd64 fontconfig-config amd64 2.15.0-2.2ubuntu1 [37.8 kB] 316s Get:31 http://ftpmaster.internal/ubuntu questing/main amd64 libfontconfig1 amd64 2.15.0-2.2ubuntu1 [164 kB] 316s Get:32 http://ftpmaster.internal/ubuntu questing/main amd64 fontconfig amd64 2.15.0-2.2ubuntu1 [180 kB] 316s Get:33 http://ftpmaster.internal/ubuntu questing/main amd64 fonts-mathjax all 2.7.9+dfsg-1 [2208 kB] 316s Get:34 http://ftpmaster.internal/ubuntu questing/main amd64 libgfortran5 amd64 15-20250404-0ubuntu1 [926 kB] 316s Get:35 http://ftpmaster.internal/ubuntu questing/main amd64 libgfortran-14-dev amd64 14.2.0-19ubuntu2 [967 kB] 316s Get:36 http://ftpmaster.internal/ubuntu questing/main amd64 gfortran-14-x86-64-linux-gnu amd64 14.2.0-19ubuntu2 [12.5 MB] 317s Get:37 http://ftpmaster.internal/ubuntu questing/main amd64 gfortran-14 amd64 14.2.0-19ubuntu2 [14.2 kB] 317s Get:38 http://ftpmaster.internal/ubuntu questing/main amd64 gfortran-x86-64-linux-gnu amd64 4:14.2.0-1ubuntu1 [1022 B] 317s Get:39 http://ftpmaster.internal/ubuntu questing/main amd64 gfortran amd64 4:14.2.0-1ubuntu1 [1174 B] 317s Get:40 http://ftpmaster.internal/ubuntu questing/main amd64 icu-devtools amd64 76.1-1ubuntu2 [237 kB] 317s Get:41 http://ftpmaster.internal/ubuntu questing/main amd64 libblas3 amd64 3.12.1-2 [359 kB] 317s Get:42 http://ftpmaster.internal/ubuntu questing/main amd64 libblas-dev amd64 3.12.1-2 [338 kB] 317s Get:43 http://ftpmaster.internal/ubuntu questing/main amd64 libbz2-dev amd64 1.0.8-6 [33.8 kB] 317s Get:44 http://ftpmaster.internal/ubuntu questing/main amd64 libpixman-1-0 amd64 0.44.0-3 [427 kB] 317s Get:45 http://ftpmaster.internal/ubuntu questing/main amd64 libxcb-render0 amd64 1.17.0-2 [16.2 kB] 317s Get:46 http://ftpmaster.internal/ubuntu questing/main amd64 libxcb-shm0 amd64 1.17.0-2 [5758 B] 317s Get:47 http://ftpmaster.internal/ubuntu questing/main amd64 libxrender1 amd64 1:0.9.10-1.1build1 [19.0 kB] 317s Get:48 http://ftpmaster.internal/ubuntu questing/main amd64 libcairo2 amd64 1.18.4-1 [662 kB] 317s Get:49 http://ftpmaster.internal/ubuntu questing/main amd64 libdatrie1 amd64 0.2.13-3build1 [19.0 kB] 317s Get:50 http://ftpmaster.internal/ubuntu questing/main amd64 libdeflate0 amd64 1.23-2 [49.9 kB] 317s Get:51 http://ftpmaster.internal/ubuntu questing/main amd64 libdeflate-dev amd64 1.23-2 [56.8 kB] 317s Get:52 http://ftpmaster.internal/ubuntu questing/main amd64 libgraphite2-3 amd64 1.3.14-2ubuntu1 [73.1 kB] 317s Get:53 http://ftpmaster.internal/ubuntu questing/universe amd64 libgslcblas0 amd64 2.8+dfsg-5ubuntu1 [113 kB] 317s Get:54 http://ftpmaster.internal/ubuntu questing/universe amd64 libgsl28 amd64 2.8+dfsg-5ubuntu1 [1043 kB] 317s Get:55 http://ftpmaster.internal/ubuntu questing/main amd64 libharfbuzz0b amd64 10.2.0-1 [543 kB] 317s Get:56 http://ftpmaster.internal/ubuntu questing/main amd64 x11-common all 1:7.7+23ubuntu4 [21.8 kB] 317s Get:57 http://ftpmaster.internal/ubuntu questing/main amd64 libice6 amd64 2:1.1.1-1 [44.1 kB] 317s Get:58 http://ftpmaster.internal/ubuntu questing/main amd64 libicu-dev amd64 76.1-1ubuntu2 [12.6 MB] 317s Get:59 http://ftpmaster.internal/ubuntu questing/main amd64 libjpeg-turbo8 amd64 2.1.5-3ubuntu2 [179 kB] 317s Get:60 http://ftpmaster.internal/ubuntu questing/main amd64 libjpeg-turbo8-dev amd64 2.1.5-3ubuntu2 [324 kB] 317s Get:61 http://ftpmaster.internal/ubuntu questing/main amd64 libjpeg8 amd64 8c-2ubuntu11 [2148 B] 317s Get:62 http://ftpmaster.internal/ubuntu questing/main amd64 libjpeg8-dev amd64 8c-2ubuntu11 [1484 B] 317s Get:63 http://ftpmaster.internal/ubuntu questing/main amd64 libjpeg-dev amd64 8c-2ubuntu11 [1482 B] 317s Get:64 http://ftpmaster.internal/ubuntu questing/main amd64 liblapack3 amd64 3.12.1-2 [3179 kB] 317s Get:65 http://ftpmaster.internal/ubuntu questing/main amd64 liblapack-dev amd64 3.12.1-2 [6489 kB] 317s Get:66 http://ftpmaster.internal/ubuntu questing/main amd64 liblerc4 amd64 4.0.0+ds-5ubuntu1 [271 kB] 317s Get:67 http://ftpmaster.internal/ubuntu questing/main amd64 libncurses-dev amd64 6.5+20250216-2 [424 kB] 317s Get:68 http://ftpmaster.internal/ubuntu questing/main amd64 libthai-data all 0.1.29-2build1 [158 kB] 317s Get:69 http://ftpmaster.internal/ubuntu questing/main amd64 libthai0 amd64 0.1.29-2build1 [18.9 kB] 317s Get:70 http://ftpmaster.internal/ubuntu questing/main amd64 libpango-1.0-0 amd64 1.56.3-1 [256 kB] 317s Get:71 http://ftpmaster.internal/ubuntu questing/main amd64 libpangoft2-1.0-0 amd64 1.56.3-1 [52.9 kB] 317s Get:72 http://ftpmaster.internal/ubuntu questing/main amd64 libpangocairo-1.0-0 amd64 1.56.3-1 [29.1 kB] 317s Get:73 http://ftpmaster.internal/ubuntu questing/main amd64 libpaper2 amd64 2.2.5-0.3 [17.4 kB] 317s Get:74 http://ftpmaster.internal/ubuntu questing/main amd64 libpaper-utils amd64 2.2.5-0.3 [15.5 kB] 317s Get:75 http://ftpmaster.internal/ubuntu questing/main amd64 libpcre2-16-0 amd64 10.45-1 [268 kB] 317s Get:76 http://ftpmaster.internal/ubuntu questing/main amd64 libpcre2-32-0 amd64 10.45-1 [251 kB] 317s Get:77 http://ftpmaster.internal/ubuntu questing/main amd64 libpcre2-posix3 amd64 10.45-1 [7204 B] 317s Get:78 http://ftpmaster.internal/ubuntu questing/main amd64 libpcre2-dev amd64 10.45-1 [908 kB] 317s Get:79 http://ftpmaster.internal/ubuntu questing/main amd64 libpkgconf3 amd64 1.8.1-4 [32.3 kB] 317s Get:80 http://ftpmaster.internal/ubuntu questing/main amd64 zlib1g-dev amd64 1:1.3.dfsg+really1.3.1-1ubuntu1 [895 kB] 318s Get:81 http://ftpmaster.internal/ubuntu questing/main amd64 libpng-dev amd64 1.6.47-1.1 [298 kB] 318s Get:82 http://ftpmaster.internal/ubuntu questing/main amd64 libreadline-dev amd64 8.2-6 [184 kB] 318s Get:83 http://ftpmaster.internal/ubuntu questing/main amd64 libsharpyuv0 amd64 1.5.0-0.1 [25.9 kB] 318s Get:84 http://ftpmaster.internal/ubuntu questing/main amd64 libsm6 amd64 2:1.2.4-1 [17.4 kB] 318s Get:85 http://ftpmaster.internal/ubuntu questing/main amd64 libtcl8.6 amd64 8.6.16+dfsg-1 [1086 kB] 318s Get:86 http://ftpmaster.internal/ubuntu questing/main amd64 libjbig0 amd64 2.1-6.1ubuntu2 [29.7 kB] 318s Get:87 http://ftpmaster.internal/ubuntu questing/main amd64 libwebp7 amd64 1.5.0-0.1 [378 kB] 318s Get:88 http://ftpmaster.internal/ubuntu questing/main amd64 libtiff6 amd64 4.7.0-3ubuntu1 [204 kB] 318s Get:89 http://ftpmaster.internal/ubuntu questing/main amd64 libxft2 amd64 2.3.6-1build1 [45.3 kB] 318s Get:90 http://ftpmaster.internal/ubuntu questing/main amd64 libxss1 amd64 1:1.2.3-1build3 [7204 B] 318s Get:91 http://ftpmaster.internal/ubuntu questing/main amd64 libtk8.6 amd64 8.6.16-1 [868 kB] 318s Get:92 http://ftpmaster.internal/ubuntu questing/main amd64 libxt6t64 amd64 1:1.2.1-1.2build1 [171 kB] 318s Get:93 http://ftpmaster.internal/ubuntu questing/main amd64 zip amd64 3.0-14ubuntu2 [185 kB] 318s Get:94 http://ftpmaster.internal/ubuntu questing/main amd64 unzip amd64 6.0-28ubuntu6 [181 kB] 318s Get:95 http://ftpmaster.internal/ubuntu questing/main amd64 xdg-utils all 1.2.1-2ubuntu1 [66.0 kB] 318s Get:96 http://ftpmaster.internal/ubuntu questing/universe amd64 r-base-core amd64 4.4.3-1 [28.9 MB] 318s Get:97 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-littler amd64 0.3.20-2 [96.6 kB] 318s Get:98 http://ftpmaster.internal/ubuntu questing/universe amd64 littler all 0.3.20-2 [2554 B] 318s Get:99 http://ftpmaster.internal/ubuntu questing/main amd64 liblzma-dev amd64 5.6.4-1ubuntu1 [189 kB] 318s Get:100 http://ftpmaster.internal/ubuntu questing/main amd64 pkgconf-bin amd64 1.8.1-4 [21.6 kB] 318s Get:101 http://ftpmaster.internal/ubuntu questing/main amd64 pkgconf amd64 1.8.1-4 [16.8 kB] 319s Get:102 http://ftpmaster.internal/ubuntu questing/main amd64 libtirpc-dev amd64 1.3.4+ds-1.3 [193 kB] 319s Get:103 http://ftpmaster.internal/ubuntu questing/universe amd64 r-base-dev all 4.4.3-1 [4176 B] 319s Get:104 http://ftpmaster.internal/ubuntu questing/universe amd64 pkg-r-autopkgtest all 20231212ubuntu1 [6448 B] 319s Get:105 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-abind all 1.4-8-1 [66.9 kB] 319s Get:106 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-codetools all 0.2-20-1 [90.5 kB] 319s Get:107 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-deldir amd64 2.0-4-1build1 [270 kB] 319s Get:108 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-iterators all 1.0.14-1 [336 kB] 319s Get:109 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-foreach all 1.5.2-1 [124 kB] 319s Get:110 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-lattice amd64 0.22-6-1 [1340 kB] 319s Get:111 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-matrix amd64 1.7-3-1 [4349 kB] 319s Get:112 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-shape all 1.4.6.1-1 [749 kB] 319s Get:113 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-survival amd64 3.8-3-1 [8239 kB] 319s Get:114 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-pkgkitten all 0.2.4-1 [27.2 kB] 319s Get:115 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-rcpp amd64 1.0.14-1 [1998 kB] 319s Get:116 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-rcppeigen amd64 0.3.4.0.2-1 [1428 kB] 319s Get:117 http://ftpmaster.internal/ubuntu questing/main amd64 libjs-mathjax all 2.7.9+dfsg-1 [5665 kB] 320s Get:118 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-glmnet amd64 4.1-8-1 [1926 kB] 320s Get:119 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-goftest amd64 1.2-3-1 [59.5 kB] 320s Get:120 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-gsl amd64 2.1-8-1build1 [486 kB] 320s Get:121 http://ftpmaster.internal/ubuntu questing-proposed/universe amd64 r-cran-nlme amd64 3.1.168-1 [2320 kB] 320s Get:122 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-mgcv amd64 1.9-1-1 [3252 kB] 320s Get:123 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-nleqslv amd64 3.3.5-1 [102 kB] 320s Get:124 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-polyclip amd64 1.10-7-1 [116 kB] 320s Get:125 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-rpart amd64 4.1.24-1 [670 kB] 320s Get:126 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-sm amd64 2.2-6.0-1 [788 kB] 320s Get:127 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatial amd64 7.3-18-1 [137 kB] 320s Get:128 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.utils amd64 3.1-3-1 [387 kB] 320s Get:129 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.data all 3.1-6-1 [4153 kB] 320s Get:130 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.univar amd64 3.1-2-1 [315 kB] 320s Get:131 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.geom amd64 3.3-6-1 [3968 kB] 320s Get:132 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.random amd64 3.3-3-1 [1177 kB] 320s Get:133 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-tensor all 1.5-4 [15.7 kB] 320s Get:134 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.sparse amd64 3.1-0-1 [221 kB] 320s Get:135 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.explore amd64 3.3-4-1 [3347 kB] 320s Get:136 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.model amd64 3.3-4-1 [3397 kB] 320s Get:137 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat.linnet amd64 3.2-5-1 [1509 kB] 320s Get:138 http://ftpmaster.internal/ubuntu questing/universe amd64 r-cran-spatstat amd64 3.3-1-1 [4121 kB] 321s Preconfiguring packages ... 321s Fetched 205 MB in 7s (31.5 MB/s) 321s Selecting previously unselected package libisl23:amd64. 321s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 80518 files and directories currently installed.) 321s Preparing to unpack .../000-libisl23_0.27-1_amd64.deb ... 321s Unpacking libisl23:amd64 (0.27-1) ... 321s Selecting previously unselected package libmpc3:amd64. 321s Preparing to unpack .../001-libmpc3_1.3.1-1build2_amd64.deb ... 321s Unpacking libmpc3:amd64 (1.3.1-1build2) ... 321s Selecting previously unselected package cpp-14-x86-64-linux-gnu. 321s Preparing to unpack .../002-cpp-14-x86-64-linux-gnu_14.2.0-19ubuntu2_amd64.deb ... 321s Unpacking cpp-14-x86-64-linux-gnu (14.2.0-19ubuntu2) ... 321s Selecting previously unselected package cpp-14. 321s Preparing to unpack .../003-cpp-14_14.2.0-19ubuntu2_amd64.deb ... 321s Unpacking cpp-14 (14.2.0-19ubuntu2) ... 321s Selecting previously unselected package cpp-x86-64-linux-gnu. 321s Preparing to unpack .../004-cpp-x86-64-linux-gnu_4%3a14.2.0-1ubuntu1_amd64.deb ... 321s Unpacking cpp-x86-64-linux-gnu (4:14.2.0-1ubuntu1) ... 321s Selecting previously unselected package cpp. 321s Preparing to unpack .../005-cpp_4%3a14.2.0-1ubuntu1_amd64.deb ... 321s Unpacking cpp (4:14.2.0-1ubuntu1) ... 322s Selecting previously unselected package libcc1-0:amd64. 322s Preparing to unpack .../006-libcc1-0_15-20250404-0ubuntu1_amd64.deb ... 322s Unpacking libcc1-0:amd64 (15-20250404-0ubuntu1) ... 322s Selecting previously unselected package libgomp1:amd64. 322s Preparing to unpack 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unselected package libgfortran5:amd64. 324s Preparing to unpack .../033-libgfortran5_15-20250404-0ubuntu1_amd64.deb ... 324s Unpacking libgfortran5:amd64 (15-20250404-0ubuntu1) ... 324s Selecting previously unselected package libgfortran-14-dev:amd64. 324s Preparing to unpack .../034-libgfortran-14-dev_14.2.0-19ubuntu2_amd64.deb ... 324s Unpacking libgfortran-14-dev:amd64 (14.2.0-19ubuntu2) ... 324s Selecting previously unselected package gfortran-14-x86-64-linux-gnu. 324s Preparing to unpack .../035-gfortran-14-x86-64-linux-gnu_14.2.0-19ubuntu2_amd64.deb ... 324s Unpacking gfortran-14-x86-64-linux-gnu (14.2.0-19ubuntu2) ... 324s Selecting previously unselected package gfortran-14. 324s Preparing to unpack .../036-gfortran-14_14.2.0-19ubuntu2_amd64.deb ... 324s Unpacking gfortran-14 (14.2.0-19ubuntu2) ... 324s Selecting previously unselected package gfortran-x86-64-linux-gnu. 324s Preparing to unpack .../037-gfortran-x86-64-linux-gnu_4%3a14.2.0-1ubuntu1_amd64.deb ... 324s Unpacking gfortran-x86-64-linux-gnu (4:14.2.0-1ubuntu1) ... 324s Selecting previously unselected package gfortran. 324s Preparing to unpack .../038-gfortran_4%3a14.2.0-1ubuntu1_amd64.deb ... 324s Unpacking gfortran (4:14.2.0-1ubuntu1) ... 324s Selecting previously unselected package icu-devtools. 324s Preparing to unpack .../039-icu-devtools_76.1-1ubuntu2_amd64.deb ... 324s Unpacking icu-devtools (76.1-1ubuntu2) ... 324s Selecting previously unselected package libblas3:amd64. 324s Preparing to unpack .../040-libblas3_3.12.1-2_amd64.deb ... 324s Unpacking libblas3:amd64 (3.12.1-2) ... 324s Selecting previously unselected package libblas-dev:amd64. 324s Preparing to unpack .../041-libblas-dev_3.12.1-2_amd64.deb ... 324s Unpacking libblas-dev:amd64 (3.12.1-2) ... 324s Selecting previously unselected package libbz2-dev:amd64. 324s Preparing to unpack .../042-libbz2-dev_1.0.8-6_amd64.deb ... 324s Unpacking libbz2-dev:amd64 (1.0.8-6) ... 324s Selecting previously unselected package libpixman-1-0:amd64. 324s Preparing to unpack .../043-libpixman-1-0_0.44.0-3_amd64.deb ... 324s Unpacking libpixman-1-0:amd64 (0.44.0-3) ... 324s Selecting previously unselected package libxcb-render0:amd64. 325s Preparing to unpack .../044-libxcb-render0_1.17.0-2_amd64.deb ... 325s Unpacking libxcb-render0:amd64 (1.17.0-2) ... 325s Selecting previously unselected package libxcb-shm0:amd64. 325s Preparing to unpack .../045-libxcb-shm0_1.17.0-2_amd64.deb ... 325s Unpacking libxcb-shm0:amd64 (1.17.0-2) ... 325s Selecting previously unselected package libxrender1:amd64. 325s Preparing to unpack .../046-libxrender1_1%3a0.9.10-1.1build1_amd64.deb ... 325s Unpacking libxrender1:amd64 (1:0.9.10-1.1build1) ... 325s Selecting previously unselected package libcairo2:amd64. 325s Preparing to unpack .../047-libcairo2_1.18.4-1_amd64.deb ... 325s Unpacking libcairo2:amd64 (1.18.4-1) ... 325s Selecting previously unselected package libdatrie1:amd64. 325s Preparing to unpack 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325s Unpacking libgsl28:amd64 (2.8+dfsg-5ubuntu1) ... 325s Selecting previously unselected package libharfbuzz0b:amd64. 325s Preparing to unpack .../054-libharfbuzz0b_10.2.0-1_amd64.deb ... 325s Unpacking libharfbuzz0b:amd64 (10.2.0-1) ... 325s Selecting previously unselected package x11-common. 325s Preparing to unpack .../055-x11-common_1%3a7.7+23ubuntu4_all.deb ... 325s Unpacking x11-common (1:7.7+23ubuntu4) ... 325s Selecting previously unselected package libice6:amd64. 325s Preparing to unpack .../056-libice6_2%3a1.1.1-1_amd64.deb ... 325s Unpacking libice6:amd64 (2:1.1.1-1) ... 325s Selecting previously unselected package libicu-dev:amd64. 325s Preparing to unpack .../057-libicu-dev_76.1-1ubuntu2_amd64.deb ... 325s Unpacking libicu-dev:amd64 (76.1-1ubuntu2) ... 325s Selecting previously unselected package libjpeg-turbo8:amd64. 325s Preparing to unpack .../058-libjpeg-turbo8_2.1.5-3ubuntu2_amd64.deb ... 325s Unpacking libjpeg-turbo8:amd64 (2.1.5-3ubuntu2) ... 325s Selecting previously unselected package libjpeg-turbo8-dev:amd64. 325s Preparing to unpack .../059-libjpeg-turbo8-dev_2.1.5-3ubuntu2_amd64.deb ... 325s Unpacking libjpeg-turbo8-dev:amd64 (2.1.5-3ubuntu2) ... 325s Selecting previously unselected package libjpeg8:amd64. 325s Preparing to unpack .../060-libjpeg8_8c-2ubuntu11_amd64.deb ... 325s Unpacking libjpeg8:amd64 (8c-2ubuntu11) ... 325s Selecting previously unselected package libjpeg8-dev:amd64. 325s Preparing to unpack .../061-libjpeg8-dev_8c-2ubuntu11_amd64.deb ... 325s Unpacking libjpeg8-dev:amd64 (8c-2ubuntu11) ... 325s Selecting previously unselected package libjpeg-dev:amd64. 325s Preparing to unpack .../062-libjpeg-dev_8c-2ubuntu11_amd64.deb ... 325s Unpacking libjpeg-dev:amd64 (8c-2ubuntu11) ... 325s Selecting previously unselected package liblapack3:amd64. 325s Preparing to unpack .../063-liblapack3_3.12.1-2_amd64.deb ... 325s Unpacking liblapack3:amd64 (3.12.1-2) ... 326s Selecting previously unselected package liblapack-dev:amd64. 326s Preparing to unpack .../064-liblapack-dev_3.12.1-2_amd64.deb ... 326s Unpacking liblapack-dev:amd64 (3.12.1-2) ... 326s Selecting previously unselected package liblerc4:amd64. 326s Preparing to unpack .../065-liblerc4_4.0.0+ds-5ubuntu1_amd64.deb ... 326s Unpacking liblerc4:amd64 (4.0.0+ds-5ubuntu1) ... 326s Selecting previously unselected package libncurses-dev:amd64. 326s Preparing to unpack .../066-libncurses-dev_6.5+20250216-2_amd64.deb ... 326s Unpacking libncurses-dev:amd64 (6.5+20250216-2) ... 326s Selecting previously unselected package libthai-data. 326s Preparing to unpack .../067-libthai-data_0.1.29-2build1_all.deb ... 326s Unpacking libthai-data (0.1.29-2build1) ... 326s Selecting previously unselected package libthai0:amd64. 326s Preparing to unpack .../068-libthai0_0.1.29-2build1_amd64.deb ... 326s Unpacking libthai0:amd64 (0.1.29-2build1) ... 326s Selecting previously unselected package libpango-1.0-0:amd64. 326s Preparing to unpack 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... 326s Selecting previously unselected package libpng-dev:amd64. 326s Preparing to unpack .../080-libpng-dev_1.6.47-1.1_amd64.deb ... 326s Unpacking libpng-dev:amd64 (1.6.47-1.1) ... 326s Selecting previously unselected package libreadline-dev:amd64. 326s Preparing to unpack .../081-libreadline-dev_8.2-6_amd64.deb ... 326s Unpacking libreadline-dev:amd64 (8.2-6) ... 326s Selecting previously unselected package libsharpyuv0:amd64. 326s Preparing to unpack .../082-libsharpyuv0_1.5.0-0.1_amd64.deb ... 326s Unpacking libsharpyuv0:amd64 (1.5.0-0.1) ... 326s Selecting previously unselected package libsm6:amd64. 326s Preparing to unpack .../083-libsm6_2%3a1.2.4-1_amd64.deb ... 326s Unpacking libsm6:amd64 (2:1.2.4-1) ... 326s Selecting previously unselected package libtcl8.6:amd64. 327s Preparing to unpack .../084-libtcl8.6_8.6.16+dfsg-1_amd64.deb ... 327s Unpacking libtcl8.6:amd64 (8.6.16+dfsg-1) ... 327s Selecting previously unselected package libjbig0:amd64. 327s Preparing to unpack .../085-libjbig0_2.1-6.1ubuntu2_amd64.deb ... 327s Unpacking libjbig0:amd64 (2.1-6.1ubuntu2) ... 327s Selecting previously unselected package libwebp7:amd64. 327s Preparing to unpack .../086-libwebp7_1.5.0-0.1_amd64.deb ... 327s Unpacking libwebp7:amd64 (1.5.0-0.1) ... 327s Selecting previously unselected package libtiff6:amd64. 327s Preparing to unpack .../087-libtiff6_4.7.0-3ubuntu1_amd64.deb ... 327s Unpacking libtiff6:amd64 (4.7.0-3ubuntu1) ... 327s Selecting previously unselected package libxft2:amd64. 327s Preparing to unpack .../088-libxft2_2.3.6-1build1_amd64.deb ... 327s Unpacking libxft2:amd64 (2.3.6-1build1) ... 327s Selecting previously unselected package libxss1:amd64. 327s Preparing to unpack .../089-libxss1_1%3a1.2.3-1build3_amd64.deb ... 327s Unpacking libxss1:amd64 (1:1.2.3-1build3) ... 327s Selecting previously unselected package libtk8.6:amd64. 327s Preparing to unpack .../090-libtk8.6_8.6.16-1_amd64.deb ... 327s Unpacking libtk8.6:amd64 (8.6.16-1) ... 327s Selecting previously unselected package libxt6t64:amd64. 327s Preparing to unpack .../091-libxt6t64_1%3a1.2.1-1.2build1_amd64.deb ... 327s Unpacking libxt6t64:amd64 (1:1.2.1-1.2build1) ... 327s Selecting previously unselected package zip. 327s Preparing to unpack .../092-zip_3.0-14ubuntu2_amd64.deb ... 327s Unpacking zip (3.0-14ubuntu2) ... 327s Selecting previously unselected package unzip. 327s Preparing to unpack .../093-unzip_6.0-28ubuntu6_amd64.deb ... 327s Unpacking unzip (6.0-28ubuntu6) ... 327s Selecting previously unselected package xdg-utils. 327s Preparing to unpack .../094-xdg-utils_1.2.1-2ubuntu1_all.deb ... 327s Unpacking xdg-utils (1.2.1-2ubuntu1) ... 327s Selecting previously unselected package r-base-core. 327s Preparing to unpack .../095-r-base-core_4.4.3-1_amd64.deb ... 327s Unpacking r-base-core (4.4.3-1) ... 327s Selecting previously unselected package r-cran-littler. 327s Preparing to unpack .../096-r-cran-littler_0.3.20-2_amd64.deb ... 327s Unpacking r-cran-littler (0.3.20-2) ... 327s Selecting previously unselected package littler. 327s Preparing to unpack .../097-littler_0.3.20-2_all.deb ... 327s Unpacking littler (0.3.20-2) ... 327s Selecting previously unselected package liblzma-dev:amd64. 327s Preparing to unpack .../098-liblzma-dev_5.6.4-1ubuntu1_amd64.deb ... 327s Unpacking liblzma-dev:amd64 (5.6.4-1ubuntu1) ... 327s Selecting previously unselected package pkgconf-bin. 327s Preparing to unpack .../099-pkgconf-bin_1.8.1-4_amd64.deb ... 327s Unpacking pkgconf-bin (1.8.1-4) ... 327s Selecting previously unselected package pkgconf:amd64. 327s Preparing to unpack .../100-pkgconf_1.8.1-4_amd64.deb ... 327s Unpacking pkgconf:amd64 (1.8.1-4) ... 327s Selecting previously unselected package libtirpc-dev:amd64. 327s Preparing to unpack .../101-libtirpc-dev_1.3.4+ds-1.3_amd64.deb ... 327s Unpacking libtirpc-dev:amd64 (1.3.4+ds-1.3) ... 327s Selecting previously unselected package r-base-dev. 327s Preparing to unpack .../102-r-base-dev_4.4.3-1_all.deb 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(4:14.2.0-1ubuntu1) ... 333s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f95 (f95) in auto mode 333s update-alternatives: warning: skip creation of /usr/share/man/man1/f95.1.gz because associated file /usr/share/man/man1/gfortran.1.gz (of link group f95) doesn't exist 333s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f77 (f77) in auto mode 333s update-alternatives: warning: skip creation of /usr/share/man/man1/f77.1.gz because associated file /usr/share/man/man1/gfortran.1.gz (of link group f77) doesn't exist 333s Setting up r-cran-spatstat.data (3.1-6-1) ... 333s Setting up r-cran-spatstat.geom (3.3-6-1) ... 333s Setting up r-cran-glmnet (4.1-8-1) ... 333s Setting up r-base-dev (4.4.3-1) ... 333s Setting up r-cran-rpart (4.1.24-1) ... 333s Setting up r-cran-spatstat.random (3.3-3-1) ... 333s Setting up r-cran-spatstat.explore (3.3-4-1) ... 333s Setting up pkg-r-autopkgtest (20231212ubuntu1) ... 333s Setting up r-cran-spatstat.model (3.3-4-1) ... 333s Setting up r-cran-spatstat.linnet (3.2-5-1) ... 333s Setting up r-cran-spatstat (3.3-1-1) ... 333s Processing triggers for install-info (7.1.1-1) ... 333s Processing triggers for libc-bin (2.41-6ubuntu1) ... 333s Processing triggers for man-db (2.13.0-1) ... 337s autopkgtest [18:59:50]: test pkg-r-autopkgtest: /usr/share/dh-r/pkg-r-autopkgtest 337s autopkgtest [18:59:50]: test pkg-r-autopkgtest: [----------------------- 337s Test: Try to load the R library spatstat.model 337s 337s R version 4.4.3 (2025-02-28) -- "Trophy Case" 337s Copyright (C) 2025 The R Foundation for Statistical Computing 337s Platform: x86_64-pc-linux-gnu 337s 337s R is free software and comes with ABSOLUTELY NO WARRANTY. 337s You are welcome to redistribute it under certain conditions. 337s Type 'license()' or 'licence()' for distribution details. 337s 337s R is a collaborative project with many contributors. 337s Type 'contributors()' for more information and 337s 'citation()' on how to cite R or R packages in publications. 337s 337s Type 'demo()' for some demos, 'help()' for on-line help, or 337s 'help.start()' for an HTML browser interface to help. 337s Type 'q()' to quit R. 337s 337s > library('spatstat.model') 337s Loading required package: spatstat.data 338s Loading required package: spatstat.univar 338s spatstat.univar 3.1-2 338s Loading required package: spatstat.geom 338s spatstat.geom 3.3-6 338s Loading required package: spatstat.random 338s spatstat.random 3.3-3 338s Loading required package: spatstat.explore 338s Loading required package: nlme 339s spatstat.explore 3.3-4 339s Loading required package: rpart 339s spatstat.model 3.3-4 339s > 339s > 339s Other tests are currently unsupported! 339s They will be progressively added. 339s autopkgtest [18:59:52]: test pkg-r-autopkgtest: -----------------------] 339s pkg-r-autopkgtest PASS 339s autopkgtest [18:59:52]: test pkg-r-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 340s autopkgtest [18:59:53]: @@@@@@@@@@@@@@@@@@@@ summary 340s run-unit-test PASS 340s pkg-r-autopkgtest PASS 356s nova [W] Skipping flock for amd64 356s Creating nova instance adt-questing-amd64-r-cran-spatstat.model-20250503-185413-juju-7f2275-prod-proposed-migration-environment-23-8c037848-b444-46e2-9465-2a592f07f3ae from image adt/ubuntu-questing-amd64-server-20250503.img (UUID 57b7c1b6-ad80-4bdb-b031-36f045f7f3b3)... 356s nova [W] Timed out waiting for d79c76d6-5148-4bd3-a89f-901e6fc2ccb9 to get deleted. 356s nova [W] Skipping flock for amd64 356s Creating nova instance adt-questing-amd64-r-cran-spatstat.model-20250503-185413-juju-7f2275-prod-proposed-migration-environment-23-8c037848-b444-46e2-9465-2a592f07f3ae from image adt/ubuntu-questing-amd64-server-20250503.img (UUID 57b7c1b6-ad80-4bdb-b031-36f045f7f3b3)... 356s nova [W] Timed out waiting for d8e930c2-02b1-4bfa-ad2f-4ae2754b23d7 to get deleted.