0s autopkgtest [10:49:03]: starting date and time: 2025-05-02 10:49:03+0000 0s autopkgtest [10:49:03]: git checkout: 9986aa8c Merge branch 'skia/fix_network_interface' into 'ubuntu/production' 0s autopkgtest [10:49:03]: host juju-7f2275-prod-proposed-migration-environment-15; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.gpwhmhii/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 autopkgtest --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-15@bos03-arm64-24.secgroup --name adt-questing-arm64-r-cran-spatstat.model-20250502-104903-juju-7f2275-prod-proposed-migration-environment-15-c6c746e0-499e-4499-b7d0-dcf388ff46f9 --image adt/ubuntu-questing-arm64-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-15 --net-id=net_prod-proposed-migration -e TERM=linux --mirror=http://ftpmaster.internal/ubuntu/ 96s autopkgtest [10:50:39]: testbed dpkg architecture: arm64 96s autopkgtest [10:50:39]: testbed apt version: 3.0.0 96s autopkgtest [10:50:39]: @@@@@@@@@@@@@@@@@@@@ test bed setup 97s autopkgtest [10:50:40]: testbed release detected to be: None 97s autopkgtest [10:50:40]: updating testbed package index (apt update) 98s Get:1 http://ftpmaster.internal/ubuntu questing-proposed InRelease [110 kB] 98s Hit:2 http://ftpmaster.internal/ubuntu questing InRelease 98s Hit:3 http://ftpmaster.internal/ubuntu questing-updates InRelease 98s Hit:4 http://ftpmaster.internal/ubuntu questing-security InRelease 98s Get:5 http://ftpmaster.internal/ubuntu questing-proposed/main Sources [175 kB] 98s Get:6 http://ftpmaster.internal/ubuntu questing-proposed/universe Sources [2076 kB] 99s Get:7 http://ftpmaster.internal/ubuntu questing-proposed/multiverse Sources [44.4 kB] 99s Get:8 http://ftpmaster.internal/ubuntu questing-proposed/main arm64 Packages [219 kB] 99s Get:9 http://ftpmaster.internal/ubuntu questing-proposed/universe arm64 Packages [1509 kB] 99s Get:10 http://ftpmaster.internal/ubuntu questing-proposed/multiverse arm64 Packages [15.4 kB] 99s Fetched 4149 kB in 1s (3312 kB/s) 100s Reading package lists... 100s autopkgtest [10:50:43]: upgrading testbed (apt dist-upgrade and autopurge) 101s Reading package lists... 101s Building dependency tree... 101s Reading state information... 101s Calculating upgrade...Starting pkgProblemResolver with broken count: 0 102s Starting 2 pkgProblemResolver with broken count: 0 102s Done 102s Entering ResolveByKeep 103s 103s Calculating upgrade... 103s The following packages will be upgraded: 103s htop mtd-utils nano 103s 3 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 103s Need to get 936 kB of archives. 103s After this operation, 727 kB of additional disk space will be used. 103s Get:1 http://ftpmaster.internal/ubuntu questing/main arm64 nano arm64 8.4-1 [290 kB] 104s Get:2 http://ftpmaster.internal/ubuntu questing/main arm64 htop arm64 3.4.1-4 [177 kB] 104s Get:3 http://ftpmaster.internal/ubuntu questing/main arm64 mtd-utils arm64 1:2.3.0-1ubuntu1 [469 kB] 104s Fetched 936 kB in 1s (1604 kB/s) 105s (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 ... 117820 files and directories currently installed.) 105s Preparing to unpack .../archives/nano_8.4-1_arm64.deb ... 105s Unpacking nano (8.4-1) over (8.3-1) ... 105s Preparing to unpack .../htop_3.4.1-4_arm64.deb ... 105s Unpacking htop (3.4.1-4) over (3.4.0-2) ... 105s Preparing to unpack .../mtd-utils_1%3a2.3.0-1ubuntu1_arm64.deb ... 105s Unpacking mtd-utils (1:2.3.0-1ubuntu1) over (1:2.2.0-2ubuntu2) ... 105s Setting up htop (3.4.1-4) ... 105s Setting up mtd-utils (1:2.3.0-1ubuntu1) ... 105s Setting up nano (8.4-1) ... 105s Installing new version of config file /etc/nanorc ... 105s Processing triggers for man-db (2.13.0-1) ... 106s Processing triggers for install-info (7.1.1-1) ... 107s Reading package lists... 107s Building dependency tree... 107s Reading state information... 107s Starting pkgProblemResolver with broken count: 0 107s Starting 2 pkgProblemResolver with broken count: 0 107s Done 108s Solving dependencies... 108s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 111s autopkgtest [10:50:54]: testbed running kernel: Linux 6.14.0-15-generic #15-Ubuntu SMP PREEMPT_DYNAMIC Sun Apr 6 14:37:51 UTC 2025 112s autopkgtest [10:50:55]: @@@@@@@@@@@@@@@@@@@@ apt-source r-cran-spatstat.model 113s Get:1 http://ftpmaster.internal/ubuntu questing/universe r-cran-spatstat.model 3.3-4-1 (dsc) [2601 B] 113s Get:2 http://ftpmaster.internal/ubuntu questing/universe r-cran-spatstat.model 3.3-4-1 (tar) [808 kB] 113s Get:3 http://ftpmaster.internal/ubuntu questing/universe r-cran-spatstat.model 3.3-4-1 (diff) [3508 B] 113s gpgv: Signature made Fri Jan 31 08:13:11 2025 UTC 113s gpgv: using RSA key 73471499CC60ED9EEE805946C5BD6C8F2295D502 113s gpgv: issuer "plessy@debian.org" 113s gpgv: Can't check signature: No public key 113s dpkg-source: warning: cannot verify inline signature for ./r-cran-spatstat.model_3.3-4-1.dsc: no acceptable signature found 114s autopkgtest [10:50:57]: testing package r-cran-spatstat.model version 3.3-4-1 114s autopkgtest [10:50:57]: build not needed 118s autopkgtest [10:51:01]: test run-unit-test: preparing testbed 119s Reading package lists... 119s Building dependency tree... 119s Reading state information... 120s Starting pkgProblemResolver with broken count: 0 120s Starting 2 pkgProblemResolver with broken count: 0 120s Done 120s The following NEW packages will be installed: 120s fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono 120s fonts-mathjax libblas3 libcairo2 libdatrie1 libdeflate0 libfontconfig1 120s libgfortran5 libgomp1 libgraphite2-3 libgsl28 libgslcblas0 libharfbuzz0b 120s libice6 libjbig0 libjpeg-turbo8 libjpeg8 libjs-mathjax liblapack3 liblerc4 120s libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 libpaper-utils 120s libpaper2 libpixman-1-0 libsharpyuv0 libsm6 libtcl8.6 libthai-data libthai0 120s libtiff6 libtk8.6 libwebp7 libxcb-render0 libxcb-shm0 libxft2 libxrender1 120s libxss1 libxt6t64 littler r-base-core r-cran-abind r-cran-codetools 120s r-cran-deldir r-cran-foreach r-cran-glmnet r-cran-goftest r-cran-gsl 120s r-cran-iterators r-cran-lattice r-cran-littler r-cran-locfit r-cran-matrix 120s r-cran-mgcv r-cran-nleqslv r-cran-nlme r-cran-pkgkitten r-cran-polyclip 120s r-cran-rcpp r-cran-rcppeigen r-cran-rpart r-cran-shape r-cran-sm 120s r-cran-spatial r-cran-spatstat r-cran-spatstat.data r-cran-spatstat.explore 120s r-cran-spatstat.geom r-cran-spatstat.linnet r-cran-spatstat.model 120s r-cran-spatstat.random r-cran-spatstat.sparse r-cran-spatstat.univar 120s r-cran-spatstat.utils r-cran-survival r-cran-tensor unzip x11-common 120s xdg-utils zip 121s 0 upgraded, 84 newly installed, 0 to remove and 0 not upgraded. 121s Need to get 98.9 MB of archives. 121s After this operation, 211 MB of additional disk space will be used. 121s Get:1 http://ftpmaster.internal/ubuntu questing/main arm64 fonts-dejavu-mono all 2.37-8 [502 kB] 121s Get:2 http://ftpmaster.internal/ubuntu questing/main arm64 fonts-dejavu-core all 2.37-8 [835 kB] 122s Get:3 http://ftpmaster.internal/ubuntu questing/main arm64 fontconfig-config arm64 2.15.0-2.2ubuntu1 [37.9 kB] 122s Get:4 http://ftpmaster.internal/ubuntu questing/main arm64 libfontconfig1 arm64 2.15.0-2.2ubuntu1 [144 kB] 122s Get:5 http://ftpmaster.internal/ubuntu questing/main arm64 fontconfig arm64 2.15.0-2.2ubuntu1 [191 kB] 122s Get:6 http://ftpmaster.internal/ubuntu questing/main arm64 fonts-mathjax all 2.7.9+dfsg-1 [2208 kB] 123s Get:7 http://ftpmaster.internal/ubuntu questing/main arm64 libblas3 arm64 3.12.1-2 [161 kB] 123s Get:8 http://ftpmaster.internal/ubuntu questing/main arm64 libpixman-1-0 arm64 0.44.0-3 [197 kB] 123s Get:9 http://ftpmaster.internal/ubuntu questing/main arm64 libxcb-render0 arm64 1.17.0-2 [16.6 kB] 123s Get:10 http://ftpmaster.internal/ubuntu questing/main arm64 libxcb-shm0 arm64 1.17.0-2 [5884 B] 123s Get:11 http://ftpmaster.internal/ubuntu questing/main arm64 libxrender1 arm64 1:0.9.10-1.1build1 [18.8 kB] 123s Get:12 http://ftpmaster.internal/ubuntu questing/main arm64 libcairo2 arm64 1.18.4-1 [560 kB] 123s Get:13 http://ftpmaster.internal/ubuntu questing/main arm64 libdatrie1 arm64 0.2.13-3build1 [19.2 kB] 123s Get:14 http://ftpmaster.internal/ubuntu questing/main arm64 libdeflate0 arm64 1.23-1 [46.2 kB] 123s Get:15 http://ftpmaster.internal/ubuntu questing/main arm64 libgfortran5 arm64 15-20250404-0ubuntu1 [444 kB] 123s Get:16 http://ftpmaster.internal/ubuntu questing/main arm64 libgomp1 arm64 15-20250404-0ubuntu1 [147 kB] 123s Get:17 http://ftpmaster.internal/ubuntu questing/main arm64 libgraphite2-3 arm64 1.3.14-2ubuntu1 [70.6 kB] 123s Get:18 http://ftpmaster.internal/ubuntu questing/universe arm64 libgslcblas0 arm64 2.8+dfsg-5ubuntu1 [87.4 kB] 123s Get:19 http://ftpmaster.internal/ubuntu questing/universe arm64 libgsl28 arm64 2.8+dfsg-5ubuntu1 [982 kB] 124s Get:20 http://ftpmaster.internal/ubuntu questing/main arm64 libharfbuzz0b arm64 10.2.0-1 [490 kB] 124s Get:21 http://ftpmaster.internal/ubuntu questing/main arm64 x11-common all 1:7.7+23ubuntu4 [21.8 kB] 124s Get:22 http://ftpmaster.internal/ubuntu questing/main arm64 libice6 arm64 2:1.1.1-1 [42.3 kB] 124s Get:23 http://ftpmaster.internal/ubuntu questing/main arm64 libjpeg-turbo8 arm64 2.1.5-3ubuntu2 [165 kB] 124s Get:24 http://ftpmaster.internal/ubuntu questing/main arm64 libjpeg8 arm64 8c-2ubuntu11 [2148 B] 124s Get:25 http://ftpmaster.internal/ubuntu questing/main arm64 liblapack3 arm64 3.12.1-2 [2307 kB] 124s Get:26 http://ftpmaster.internal/ubuntu questing/main arm64 liblerc4 arm64 4.0.0+ds-5ubuntu1 [167 kB] 124s Get:27 http://ftpmaster.internal/ubuntu questing/main arm64 libthai-data all 0.1.29-2build1 [158 kB] 124s Get:28 http://ftpmaster.internal/ubuntu questing/main arm64 libthai0 arm64 0.1.29-2build1 [18.2 kB] 124s Get:29 http://ftpmaster.internal/ubuntu questing/main arm64 libpango-1.0-0 arm64 1.56.3-1 [238 kB] 124s Get:30 http://ftpmaster.internal/ubuntu questing/main arm64 libpangoft2-1.0-0 arm64 1.56.3-1 [49.8 kB] 124s Get:31 http://ftpmaster.internal/ubuntu questing/main arm64 libpangocairo-1.0-0 arm64 1.56.3-1 [27.6 kB] 124s Get:32 http://ftpmaster.internal/ubuntu questing/main arm64 libpaper2 arm64 2.2.5-0.3 [17.3 kB] 124s Get:33 http://ftpmaster.internal/ubuntu questing/main arm64 libpaper-utils arm64 2.2.5-0.3 [15.4 kB] 124s Get:34 http://ftpmaster.internal/ubuntu questing/main arm64 libsharpyuv0 arm64 1.5.0-0.1 [16.9 kB] 124s Get:35 http://ftpmaster.internal/ubuntu questing/main arm64 libsm6 arm64 2:1.2.4-1 [16.4 kB] 124s Get:36 http://ftpmaster.internal/ubuntu questing/main arm64 libtcl8.6 arm64 8.6.16+dfsg-1 [987 kB] 124s Get:37 http://ftpmaster.internal/ubuntu questing/main arm64 libjbig0 arm64 2.1-6.1ubuntu2 [29.3 kB] 124s Get:38 http://ftpmaster.internal/ubuntu questing/main arm64 libwebp7 arm64 1.5.0-0.1 [194 kB] 124s Get:39 http://ftpmaster.internal/ubuntu questing/main arm64 libtiff6 arm64 4.5.1+git230720-4ubuntu4 [193 kB] 124s Get:40 http://ftpmaster.internal/ubuntu questing/main arm64 libxft2 arm64 2.3.6-1build1 [44.1 kB] 124s Get:41 http://ftpmaster.internal/ubuntu questing/main arm64 libxss1 arm64 1:1.2.3-1build3 [7244 B] 124s Get:42 http://ftpmaster.internal/ubuntu questing/main arm64 libtk8.6 arm64 8.6.16-1 [776 kB] 124s Get:43 http://ftpmaster.internal/ubuntu questing/main arm64 libxt6t64 arm64 1:1.2.1-1.2build1 [168 kB] 124s Get:44 http://ftpmaster.internal/ubuntu questing/main arm64 zip arm64 3.0-14ubuntu2 [173 kB] 124s Get:45 http://ftpmaster.internal/ubuntu questing/main arm64 unzip arm64 6.0-28ubuntu6 [178 kB] 124s Get:46 http://ftpmaster.internal/ubuntu questing/main arm64 xdg-utils all 1.2.1-2ubuntu1 [66.0 kB] 124s Get:47 http://ftpmaster.internal/ubuntu questing/universe arm64 r-base-core arm64 4.4.3-1 [28.4 MB] 126s Get:48 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-littler arm64 0.3.20-2 [96.1 kB] 126s Get:49 http://ftpmaster.internal/ubuntu questing/universe arm64 littler all 0.3.20-2 [2554 B] 126s Get:50 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-abind all 1.4-8-1 [66.9 kB] 126s Get:51 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-codetools all 0.2-20-1 [90.5 kB] 126s Get:52 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-deldir arm64 2.0-4-1build1 [270 kB] 126s Get:53 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-iterators all 1.0.14-1 [336 kB] 126s Get:54 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-foreach all 1.5.2-1 [124 kB] 126s Get:55 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-lattice arm64 0.22-6-1 [1363 kB] 126s Get:56 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-matrix arm64 1.7-3-1 [4045 kB] 126s Get:57 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-shape all 1.4.6.1-1 [749 kB] 126s Get:58 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-survival arm64 3.8-3-1 [8213 kB] 127s Get:59 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-pkgkitten all 0.2.4-1 [27.2 kB] 127s Get:60 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-rcpp arm64 1.0.14-1 [1978 kB] 127s Get:61 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-rcppeigen arm64 0.3.4.0.2-1 [1422 kB] 127s Get:62 http://ftpmaster.internal/ubuntu questing/main arm64 libjs-mathjax all 2.7.9+dfsg-1 [5665 kB] 127s Get:63 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-glmnet arm64 4.1-8-1 [1898 kB] 127s Get:64 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-goftest arm64 1.2-3-1 [60.2 kB] 127s Get:65 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-gsl arm64 2.1-8-1build1 [485 kB] 127s Get:66 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-locfit arm64 1.5-9.12-1 [514 kB] 127s Get:67 http://ftpmaster.internal/ubuntu questing-proposed/universe arm64 r-cran-nlme arm64 3.1.168-1 [2310 kB] 127s Get:68 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-mgcv arm64 1.9-1-1 [3248 kB] 127s Get:69 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-nleqslv arm64 3.3.5-1 [101 kB] 127s Get:70 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-polyclip arm64 1.10-7-1 [113 kB] 127s Get:71 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-rpart arm64 4.1.24-1 [665 kB] 127s Get:72 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-sm arm64 2.2-6.0-1 [787 kB] 128s Get:73 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatial arm64 7.3-18-1 [133 kB] 128s Get:74 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.utils arm64 3.1-3-1 [386 kB] 128s Get:75 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.data all 3.1-6-1 [4153 kB] 128s Get:76 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.univar arm64 3.1-2-1 [314 kB] 128s Get:77 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.geom arm64 3.3-6-1 [3941 kB] 128s Get:78 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.random arm64 3.3-3-1 [1163 kB] 128s Get:79 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-tensor all 1.5-4 [15.7 kB] 128s Get:80 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.sparse arm64 3.1-0-1 [218 kB] 128s Get:81 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.explore arm64 3.3-4-1 [3272 kB] 128s Get:82 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.model arm64 3.3-4-1 [3398 kB] 128s Get:83 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.linnet arm64 3.2-5-1 [1507 kB] 128s Get:84 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat arm64 3.3-1-1 [4120 kB] 129s Preconfiguring packages ... 130s Fetched 98.9 MB in 8s (12.5 MB/s) 130s Selecting previously unselected package fonts-dejavu-mono. 130s (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 ... 117821 files and directories currently installed.) 130s Preparing to unpack .../00-fonts-dejavu-mono_2.37-8_all.deb ... 130s Unpacking fonts-dejavu-mono (2.37-8) ... 130s Selecting previously unselected package fonts-dejavu-core. 130s Preparing to unpack .../01-fonts-dejavu-core_2.37-8_all.deb ... 130s Unpacking fonts-dejavu-core (2.37-8) ... 130s Selecting previously unselected package fontconfig-config. 130s Preparing to unpack .../02-fontconfig-config_2.15.0-2.2ubuntu1_arm64.deb ... 130s Unpacking fontconfig-config (2.15.0-2.2ubuntu1) ... 130s Selecting previously unselected package libfontconfig1:arm64. 130s Preparing to unpack .../03-libfontconfig1_2.15.0-2.2ubuntu1_arm64.deb ... 130s Unpacking libfontconfig1:arm64 (2.15.0-2.2ubuntu1) ... 130s Selecting previously unselected package fontconfig. 130s Preparing to unpack .../04-fontconfig_2.15.0-2.2ubuntu1_arm64.deb ... 130s Unpacking fontconfig (2.15.0-2.2ubuntu1) ... 130s Selecting previously unselected package fonts-mathjax. 130s Preparing to unpack .../05-fonts-mathjax_2.7.9+dfsg-1_all.deb ... 130s Unpacking fonts-mathjax (2.7.9+dfsg-1) ... 130s Selecting previously unselected package libblas3:arm64. 130s Preparing to unpack .../06-libblas3_3.12.1-2_arm64.deb ... 130s Unpacking libblas3:arm64 (3.12.1-2) ... 130s Selecting previously unselected package libpixman-1-0:arm64. 130s Preparing to unpack .../07-libpixman-1-0_0.44.0-3_arm64.deb ... 130s Unpacking libpixman-1-0:arm64 (0.44.0-3) ... 130s Selecting previously unselected package libxcb-render0:arm64. 130s Preparing to unpack .../08-libxcb-render0_1.17.0-2_arm64.deb ... 130s Unpacking libxcb-render0:arm64 (1.17.0-2) ... 130s Selecting previously unselected package libxcb-shm0:arm64. 130s Preparing to unpack .../09-libxcb-shm0_1.17.0-2_arm64.deb ... 130s Unpacking libxcb-shm0:arm64 (1.17.0-2) ... 130s Selecting previously unselected package libxrender1:arm64. 130s Preparing to unpack .../10-libxrender1_1%3a0.9.10-1.1build1_arm64.deb ... 130s Unpacking libxrender1:arm64 (1:0.9.10-1.1build1) ... 130s Selecting previously unselected package libcairo2:arm64. 130s Preparing to unpack .../11-libcairo2_1.18.4-1_arm64.deb ... 130s Unpacking libcairo2:arm64 (1.18.4-1) ... 130s Selecting previously unselected package libdatrie1:arm64. 130s Preparing to unpack .../12-libdatrie1_0.2.13-3build1_arm64.deb ... 130s Unpacking libdatrie1:arm64 (0.2.13-3build1) ... 130s Selecting previously unselected package libdeflate0:arm64. 130s Preparing to unpack .../13-libdeflate0_1.23-1_arm64.deb ... 130s Unpacking libdeflate0:arm64 (1.23-1) ... 130s Selecting previously unselected package libgfortran5:arm64. 130s Preparing to unpack .../14-libgfortran5_15-20250404-0ubuntu1_arm64.deb ... 130s Unpacking libgfortran5:arm64 (15-20250404-0ubuntu1) ... 130s Selecting previously unselected package libgomp1:arm64. 130s Preparing to unpack .../15-libgomp1_15-20250404-0ubuntu1_arm64.deb ... 130s Unpacking libgomp1:arm64 (15-20250404-0ubuntu1) ... 130s Selecting previously unselected package libgraphite2-3:arm64. 130s Preparing to unpack .../16-libgraphite2-3_1.3.14-2ubuntu1_arm64.deb ... 130s Unpacking libgraphite2-3:arm64 (1.3.14-2ubuntu1) ... 130s Selecting previously unselected package libgslcblas0:arm64. 130s Preparing to unpack .../17-libgslcblas0_2.8+dfsg-5ubuntu1_arm64.deb ... 130s Unpacking libgslcblas0:arm64 (2.8+dfsg-5ubuntu1) ... 130s Selecting previously unselected package libgsl28:arm64. 130s Preparing to unpack .../18-libgsl28_2.8+dfsg-5ubuntu1_arm64.deb ... 130s Unpacking libgsl28:arm64 (2.8+dfsg-5ubuntu1) ... 130s Selecting previously unselected package libharfbuzz0b:arm64. 130s Preparing to unpack .../19-libharfbuzz0b_10.2.0-1_arm64.deb ... 130s Unpacking libharfbuzz0b:arm64 (10.2.0-1) ... 130s Selecting previously unselected package x11-common. 130s Preparing to unpack .../20-x11-common_1%3a7.7+23ubuntu4_all.deb ... 130s Unpacking x11-common (1:7.7+23ubuntu4) ... 130s Selecting previously unselected package libice6:arm64. 130s Preparing to unpack .../21-libice6_2%3a1.1.1-1_arm64.deb ... 130s Unpacking libice6:arm64 (2:1.1.1-1) ... 130s Selecting previously unselected package libjpeg-turbo8:arm64. 130s Preparing to unpack .../22-libjpeg-turbo8_2.1.5-3ubuntu2_arm64.deb ... 130s Unpacking libjpeg-turbo8:arm64 (2.1.5-3ubuntu2) ... 131s Selecting previously unselected package libjpeg8:arm64. 131s Preparing to unpack .../23-libjpeg8_8c-2ubuntu11_arm64.deb ... 131s 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Setting up r-cran-rcppeigen (0.3.4.0.2-1) ... 139s Setting up r-cran-survival (3.8-3-1) ... 139s Setting up r-cran-spatstat.data (3.1-6-1) ... 139s Setting up r-cran-spatstat.geom (3.3-6-1) ... 139s Setting up r-cran-glmnet (4.1-8-1) ... 139s Setting up r-cran-rpart (4.1.24-1) ... 139s Setting up r-cran-spatstat.random (3.3-3-1) ... 139s Setting up r-cran-spatstat.explore (3.3-4-1) ... 139s Setting up r-cran-spatstat.model (3.3-4-1) ... 139s Setting up r-cran-spatstat.linnet (3.2-5-1) ... 139s Setting up r-cran-spatstat (3.3-1-1) ... 139s Processing triggers for install-info (7.1.1-1) ... 139s Processing triggers for libc-bin (2.41-6ubuntu1) ... 139s Processing triggers for man-db (2.13.0-1) ... 140s autopkgtest [10:51:23]: test run-unit-test: [----------------------- 140s BEGIN TEST testsAtoC.R 140s 140s R version 4.4.3 (2025-02-28) -- "Trophy Case" 140s Copyright (C) 2025 The R Foundation for Statistical Computing 140s Platform: aarch64-unknown-linux-gnu 140s 140s R is free software and comes with ABSOLUTELY NO WARRANTY. 140s You are welcome to redistribute it under certain conditions. 140s Type 'license()' or 'licence()' for distribution details. 140s 140s R is a collaborative project with many contributors. 140s Type 'contributors()' for more information and 140s 'citation()' on how to cite R or R packages in publications. 140s 140s Type 'demo()' for some demos, 'help()' for on-line help, or 140s 'help.start()' for an HTML browser interface to help. 140s Type 'q()' to quit R. 140s 141s > #' 141s > #' Header for all (concatenated) test files 141s > #' 141s > #' Require spatstat.model 141s > #' Obtain environment variable controlling tests. 141s > #' 141s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 141s > 141s > require(spatstat.model) 141s Loading required package: spatstat.model 141s Loading required package: spatstat.data 142s Loading required package: spatstat.univar 142s spatstat.univar 3.1-2 142s Loading required package: spatstat.geom 142s spatstat.geom 3.3-6 142s Loading required package: spatstat.random 142s spatstat.random 3.3-3 142s Loading required package: spatstat.explore 142s Loading required package: nlme 142s spatstat.explore 3.3-4 142s Loading required package: rpart 142s spatstat.model 3.3-4 142s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 142s > ALWAYS <- TRUE 142s > cat(paste("--------- Executing", 142s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 142s + "test code -----------\n")) 142s --------- Executing **RESTRICTED** subset of test code ----------- 142s > #' tests/aucroc.R 142s > #' 142s > #' AUC and ROC code 142s > #' 142s > #' $Revision: 1.6 $ $Date: 2020/11/02 06:26:45 $ 142s > 142s > local({ 142s + if(FULLTEST) { 142s + fit <- kppm(redwood ~ I(y-x)) 142s + a <- roc(fit) 142s + b <- auc(fit) 142s + fet <- ppm(amacrine~x+y+marks) 142s + d <- roc(fet) 142s + e <- auc(fet) 142s + } 142s + }) 142s > ## tests/cdf.test.R 142s > 142s > 142s > local({ 142s + NSIM <- 9 142s + op <- spatstat.options(ndummy.min=16, npixel=32) 142s + if(FULLTEST) { 142s + ## Monte Carlo test for Gibbs model 142s + fit <- ppm(cells ~ 1, Strauss(0.07)) 142s + cdf.test(fit, "x", nsim=NSIM) 142s + 142s + ## cdf.test.slrm 142s + fut <- slrm(japanesepines ~ x + y) 142s + Z <- distmap(japanesepines) 142s + cdf.test(fut, Z) 142s + } 142s + reset.spatstat.options() 142s + }) 142s > 142s > 142s > #' 142s > #' tests/contrib.R 142s > #' 142s > #' Tests for user-contributed code in spatstat 142s > #' 142s > #' $Revision: 1.4 $ $Date: 2021/04/17 02:32:24 $ 142s > 142s > local({ 142s + #' Jinhom 142s + #' Marie-Colette van Lieshout and Ottmar Cronie 142s + X <- redwood3 142s + if(FULLTEST) { 142s + fit <- ppm(X ~ polynom(x,y,2)) 142s + } else { 142s + X <- X[c(TRUE,FALSE)] 142s + spatstat.options(npixel=32, ndummy.min=16) 142s + fit <- ppm(X ~ x) 142s + } 142s + lam <- predict(fit) 142s + lamX <- fitted(fit, dataonly=TRUE) 142s + lmin <- 0.9 * min(lam) 142s + g1 <- Ginhom(X, lambda=fit, update=TRUE) 142s + if(FULLTEST) { 142s + g2 <- Ginhom(X, lambda=fit, update=FALSE, lmin = lmin) 142s + g3 <- Ginhom(X, lambda=lam, lmin=lmin) 142s + g4 <- Ginhom(X, lambda=lamX, lmin=lmin) 142s + } 142s + if(ALWAYS) { 142s + f2 <- Finhom(X, lambda=fit, update=FALSE) 142s + } 142s + if(FULLTEST) { 142s + f1 <- Finhom(X, lambda=fit, update=TRUE) 142s + f3 <- Finhom(X, lambda=lam, lmin=lmin) 142s + } 142s + if(!FULLTEST) reset.spatstat.options() 142s + }) 142s > 142s BEGIN TEST testsD.R 142s 142s R version 4.4.3 (2025-02-28) -- "Trophy Case" 142s Copyright (C) 2025 The R Foundation for Statistical Computing 142s Platform: aarch64-unknown-linux-gnu 142s 142s R is free software and comes with ABSOLUTELY NO WARRANTY. 142s You are welcome to redistribute it under certain conditions. 142s Type 'license()' or 'licence()' for distribution details. 142s 142s R is a collaborative project with many contributors. 142s Type 'contributors()' for more information and 142s 'citation()' on how to cite R or R packages in publications. 142s 142s Type 'demo()' for some demos, 'help()' for on-line help, or 142s 'help.start()' for an HTML browser interface to help. 142s Type 'q()' to quit R. 142s 142s > #' 142s > #' Header for all (concatenated) test files 142s > #' 142s > #' Require spatstat.model 142s > #' Obtain environment variable controlling tests. 142s > #' 142s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 142s > 142s > require(spatstat.model) 142s Loading required package: spatstat.model 142s Loading required package: spatstat.data 143s Loading required package: spatstat.univar 143s spatstat.univar 3.1-2 143s Loading required package: spatstat.geom 143s spatstat.geom 3.3-6 143s Loading required package: spatstat.random 143s spatstat.random 3.3-3 143s Loading required package: spatstat.explore 143s Loading required package: nlme 143s spatstat.explore 3.3-4 143s Loading required package: rpart 144s spatstat.model 3.3-4 144s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 144s > ALWAYS <- TRUE 144s > cat(paste("--------- Executing", 144s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 144s + "test code -----------\n")) 144s --------- Executing **RESTRICTED** subset of test code ----------- 144s > #' 144s > #' tests/deltasuffstat.R 144s > #' 144s > #' Explicit tests of 'deltasuffstat' 144s > #' 144s > #' $Revision: 1.4 $ $Date: 2021/01/22 08:08:48 $ 144s > 144s > if(!FULLTEST) 144s + spatstat.options(npixel=32, ndummy.min=16) 144s > 144s > if(ALWAYS) { # depends on C code 144s + local({ 144s + 144s + disagree <- function(x, y, tol=1e-7) { !is.null(x) && !is.null(y) && max(abs(x-y)) > tol } 144s + 144s + flydelta <- function(model, modelname="") { 144s + ## Check execution of different algorithms for 'deltasuffstat' 144s + dSS <- deltasuffstat(model, sparseOK=TRUE) 144s + dBS <- deltasuffstat(model, sparseOK=TRUE, use.special=FALSE, force=TRUE) 144s + dBF <- deltasuffstat(model, sparseOK=FALSE, use.special=FALSE, force=TRUE) 144s + ## Compare results 144s + if(disagree(dBS, dSS)) 144s + stop(paste(modelname, "model: Brute force algorithm disagrees with special algorithm")) 144s + if(disagree(dBF, dBS)) 144s + stop(paste(modelname, "model: Sparse and full versions of brute force algorithm disagree")) 144s + return(invisible(NULL)) 144s + } 144s + 144s + modelS <- ppm(cells ~ x, Strauss(0.13), nd=10) 144s + flydelta(modelS, "Strauss") 144s + 144s + antsub <- ants[c(FALSE,TRUE,FALSE)] 144s + rmat <- matrix(c(130, 90, 90, 60), 2, 2) 144s + 144s + modelM <- ppm(antsub ~ 1, MultiStrauss(rmat), nd=16) 144s + flydelta(modelM, "MultiStrauss") 144s + 144s + modelA <- ppm(antsub ~ 1, HierStrauss(rmat, archy=c(2,1)), nd=16) 144s + flydelta(modelA, "HierStrauss") 144s + }) 144s + 144s + } 148s > 148s > reset.spatstat.options() 148s > #' 148s > #' tests/density.R 148s > #' 148s > #' Test behaviour of density() methods, 148s > #' relrisk(), Smooth() 148s > #' and inhomogeneous summary functions 148s > #' and idw, adaptive.density, intensity 148s > #' and SpatialMedian, SpatialQuantile 148s > #' 148s > #' $Revision: 1.67 $ $Date: 2024/01/29 07:07:16 $ 148s > #' 148s > 148s > if(!FULLTEST) 148s + spatstat.options(npixel=32, ndummy.min=16) 148s > 148s > 148s > local({ 148s + ## likewise 'relrisk.ppm' 148s + fit <- ppm(ants ~ x) 148s + rants <- function(..., model=fit) { 148s + a <- relrisk(model, sigma=100, se=TRUE, ...) 148s + return(TRUE) 148s + } 148s + if(ALWAYS) { 148s + rants() 148s + rants(diggle=TRUE) 148s + rants(edge=FALSE) 148s + rants(at="points") 148s + rants(casecontrol=FALSE) 148s + rants(relative=TRUE) 148s + } 148s + if(FULLTEST) { 148s + rants(diggle=TRUE, at="points") 148s + rants(edge=FALSE, at="points") 148s + rants(casecontrol=FALSE, relative=TRUE) 148s + rants(casecontrol=FALSE,at="points") 148s + rants(relative=TRUE,at="points") 148s + rants(casecontrol=FALSE, relative=TRUE,at="points") 148s + rants(relative=TRUE, control="Cataglyphis", case="Messor") 148s + rants(relative=TRUE, control="Cataglyphis", case="Messor", at="points") 148s + } 148s + ## more than 2 types 148s + fut <- ppm(sporophores ~ x) 148s + if(ALWAYS) { 148s + rants(model=fut) 148s + } 148s + if(FULLTEST) { 148s + rants(model=fut, at="points") 148s + rants(model=fut, relative=TRUE, at="points") 148s + } 148s + if(FULLTEST) { 148s + ## cases of 'intensity' etc 148s + a <- intensity(ppm(amacrine ~ 1)) 148s + } 148s + }) 149s > 149s > reset.spatstat.options() 149s > 149s > #' 149s > #' tests/diagnostique.R 149s > #' 149s > #' Diagnostic tools such as diagnose.ppm, qqplot.ppm 149s > #' 149s > #' $Revision: 1.6 $ $Date: 2020/04/28 12:58:26 $ 149s > #' 149s > 149s > if(FULLTEST) { 149s + local({ 149s + fit <- ppm(cells ~ x) 149s + diagE <- diagnose.ppm(fit, type="eem") 149s + diagI <- diagnose.ppm(fit, type="inverse") 149s + diagP <- diagnose.ppm(fit, type="Pearson") 149s + plot(diagE, which="all") 149s + plot(diagI, which="smooth") 149s + plot(diagP, which="x") 149s + plot(diagP, which="marks", plot.neg="discrete") 149s + plot(diagP, which="marks", plot.neg="contour") 149s + plot(diagP, which="smooth", srange=c(-5,5)) 149s + plot(diagP, which="smooth", plot.smooth="contour") 149s + plot(diagP, which="smooth", plot.smooth="image") 149s + 149s + fitS <- ppm(cells ~ x, Strauss(0.08)) 149s + diagES <- diagnose.ppm(fitS, type="eem", clip=FALSE) 149s + diagIS <- diagnose.ppm(fitS, type="inverse", clip=FALSE) 149s + diagPS <- diagnose.ppm(fitS, type="Pearson", clip=FALSE) 149s + plot(diagES, which="marks", plot.neg="imagecontour") 149s + plot(diagPS, which="marks", plot.neg="discrete") 149s + plot(diagPS, which="marks", plot.neg="contour") 149s + plot(diagPS, which="smooth", plot.smooth="image") 149s + plot(diagPS, which="smooth", plot.smooth="contour") 149s + plot(diagPS, which="smooth", plot.smooth="persp") 149s + 149s + #' infinite reach, not border-corrected 149s + fut <- ppm(cells ~ x, Softcore(0.5), correction="isotropic") 149s + diagnose.ppm(fut) 149s + 149s + #' 149s + diagPX <- diagnose.ppm(fit, type="Pearson", cumulative=FALSE) 149s + plot(diagPX, which="y") 149s + 149s + #' simulation based 149s + e <- envelope(cells, nsim=4, savepatterns=TRUE, savefuns=TRUE) 149s + Plist <- rpoispp(40, nsim=5) 149s + 149s + qf <- qqplot.ppm(fit, nsim=4, expr=e, plot.it=FALSE) 149s + print(qf) 149s + qp <- qqplot.ppm(fit, nsim=5, expr=Plist, fast=FALSE) 149s + print(qp) 149s + qp <- qqplot.ppm(fit, nsim=5, expr=expression(rpoispp(40)), plot.it=FALSE) 149s + print(qp) 149s + qg <- qqplot.ppm(fit, nsim=5, style="classical", plot.it=FALSE) 149s + print(qg) 149s + 149s + #' lurking.ppm 149s + #' covariate is numeric vector 149s + fitx <- ppm(cells ~ x) 149s + yvals <- coords(as.ppp(quad.ppm(fitx)))[,"y"] 149s + lurking(fitx, yvals) 149s + #' covariate is stored but is not used in model 149s + Z <- as.im(function(x,y){ x+y }, Window(cells)) 149s + fitxx <- ppm(cells ~ x, data=solist(Zed=Z), allcovar=TRUE) 149s + lurking(fitxx, expression(Zed)) 149s + #' envelope is a ppplist; length < nsim; glmdata=NULL 149s + fit <- ppm(cells ~ 1) 149s + stuff <- lurking(fit, expression(x), envelope=Plist, plot.sd=FALSE) 149s + #' plot.lurk 149s + plot(stuff, shade=NULL) 149s + }) 149s + } 149s > 149s > #' 149s > #' tests/deepeepee.R 149s > #' 149s > #' Tests for determinantal point process models 149s > #' 149s > #' $Revision: 1.9 $ $Date: 2022/04/24 09:14:46 $ 149s > 149s > local({ 149s + if(ALWAYS) { 149s + #' simulate.dppm 149s + jpines <- residualspaper$Fig1 149s + fit <- dppm(jpines ~ 1, dppGauss) 149s + set.seed(10981) 149s + simulate(fit, W=square(5)) 149s + } 149s + if(FULLTEST) { 149s + #' simulate.detpointprocfamily - code blocks 149s + model <- dppGauss(lambda=100, alpha=.05, d=2) 149s + simulate(model, seed=1999, correction="border") 149s + u <- is.stationary(model) 149s + #' other methods for dppm 149s + kay <- Kmodel(fit) 149s + gee <- pcfmodel(fit) 149s + lam <- intensity(fit) 149s + arr <- reach(fit) 149s + pah <- parameters(fit) 149s + #' a user bug report - matrix dimension error 149s + set.seed(256) 149s + dat <- simulate( dppGauss(lambda = 8.5, alpha = 0.1, d = 2), nsim = 1) 149s + } 149s + if(FULLTEST) { 149s + ## cover print.summary.dppm 149s + jpines <- japanesepines[c(TRUE,FALSE,FALSE,FALSE)] 149s + print(summary(dppm(jpines ~ 1, dppGauss))) 149s + print(summary(dppm(jpines ~ 1, dppGauss, method="c"))) 149s + print(summary(dppm(jpines ~ 1, dppGauss, method="p"))) 149s + print(summary(dppm(jpines ~ 1, dppGauss, method="a"))) 149s + } 149s + #' dppeigen code blocks 149s + if(ALWAYS) { 149s + mod <- dppMatern(lambda=2, alpha=0.01, nu=1, d=2) 149s + uT <- dppeigen(mod, trunc=1.1, Wscale=c(1,1), stationary=TRUE) 149s + } 149s + if(FULLTEST) { 149s + uF <- dppeigen(mod, trunc=1.1, Wscale=c(1,1), stationary=FALSE) 149s + vT <- dppeigen(mod, trunc=0.98, Wscale=c(1,1), stationary=TRUE) 149s + vF <- dppeigen(mod, trunc=0.98, Wscale=c(1,1), stationary=FALSE) 149s + } 149s + }) 150s > 150s BEGIN TEST testsEtoF.R 150s 150s R version 4.4.3 (2025-02-28) -- "Trophy Case" 150s Copyright (C) 2025 The R Foundation for Statistical Computing 150s Platform: aarch64-unknown-linux-gnu 150s 150s R is free software and comes with ABSOLUTELY NO WARRANTY. 150s You are welcome to redistribute it under certain conditions. 150s Type 'license()' or 'licence()' for distribution details. 150s 150s R is a collaborative project with many contributors. 150s Type 'contributors()' for more information and 150s 'citation()' on how to cite R or R packages in publications. 150s 150s Type 'demo()' for some demos, 'help()' for on-line help, or 150s 'help.start()' for an HTML browser interface to help. 150s Type 'q()' to quit R. 150s 150s > #' 150s > #' Header for all (concatenated) test files 150s > #' 150s > #' Require spatstat.model 150s > #' Obtain environment variable controlling tests. 150s > #' 150s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 150s > 150s > require(spatstat.model) 150s Loading required package: spatstat.model 150s Loading required package: spatstat.data 151s Loading required package: spatstat.univar 151s spatstat.univar 3.1-2 151s Loading required package: spatstat.geom 151s spatstat.geom 3.3-6 151s Loading required package: spatstat.random 151s spatstat.random 3.3-3 151s Loading required package: spatstat.explore 151s Loading required package: nlme 151s spatstat.explore 3.3-4 151s Loading required package: rpart 151s spatstat.model 3.3-4 151s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 151s > ALWAYS <- TRUE 151s > cat(paste("--------- Executing", 151s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 151s + "test code -----------\n")) 151s --------- Executing **RESTRICTED** subset of test code ----------- 151s > # 151s > # tests/envelopes.R 151s > # 151s > # Test validity of envelope data 151s > # 151s > # $Revision: 1.29 $ $Date: 2024/01/10 13:45:29 $ 151s > # 152s > 152s > local({ 152s + 152s + 152s + checktheo <- function(fit) { 152s + fitname <- deparse(substitute(fit)) 152s + en <- envelope(fit, nsim=4, verbose=FALSE, nrep=1e3) 152s + nama <- names(en) 152s + expecttheo <- is.poisson(fit) && is.stationary(fit) 152s + context <- paste("Envelope of", fitname) 152s + if(expecttheo) { 152s + if(!("theo" %in% nama)) 152s + stop(paste(context, "did not contain", sQuote("theo"))) 152s + if("mmean" %in% nama) 152s + stop(paste(context, "unexpectedly contained", sQuote("mmean"))) 152s + } else { 152s + if("theo" %in% nama) 152s + stop(paste(context, "unexpectedly contained", sQuote("theo"))) 152s + if(!("mmean" %in% nama)) 152s + stop(paste(context, "did not contain", sQuote("mmean"))) 152s + } 152s + cat(paste(context, "has correct format\n")) 152s + } 152s + 152s + if(ALWAYS) { 152s + checktheo(ppm(cells ~x)) 152s + } 152s + if(FULLTEST) { 152s + checktheo(ppm(cells)) 152s + checktheo(ppm(cells ~1, Strauss(0.1))) 152s + } 152s + 152s + 152s + #' check savefuns/savepatterns with global 152s + fit <- ppm(cells~x) 152s + if(ALWAYS) Ef <- envelope(fit, Kest, nsim=4, savefuns=TRUE, global=TRUE) 152s + if(FULLTEST) Ep <- envelope(fit, Kest, nsim=4, savepatterns=TRUE, global=TRUE) 152s + #' check handling of 'dangerous' cases 152s + if(FULLTEST) { 152s + fut <- ppm(redwood ~ x) 152s + Ek <- envelope(fut, Kinhom, update=FALSE, nsim=4) 152s + kfut <- kppm(redwood3 ~ x) 152s + Ekk <- envelope(kfut, Kinhom, lambda=density(redwood3), nsim=7) 152s + } 152s + 152s + 152s + if(ALWAYS) { # invokes C code 152s + fit <- ppm(japanesepines ~ 1, Strauss(0.04)) 152s + e6 <- envelope(fit, Kest, nsim=4, fix.n=TRUE) 152s + fit2 <- ppm(amacrine ~ 1, Strauss(0.03)) 152s + e7 <- envelope(fit2, Gcross, nsim=4, fix.marks=TRUE) 152s + } 152s + 152s + 152s + if(FULLTEST) { 152s + fit <- ppm(cells ~ 1, Strauss(0.07)) 152s + U <- envelope(fit, nsim=3, simulate=expression(runifpoint(20))) 152s + kfit <- kppm(redwood3 ~ x) 152s + UU <- envelope(kfit, nsim=7, simulate=expression(simulate(kfit, drop=TRUE))) 152s + VV <- envelope(kfit, nsim=7, weights=1:7) 152s + MM <- envelope(kfit, nsim=7, Kinhom, lambda=density(redwood3)) 152s + } 152s + 152s + if(FULLTEST) { 152s + ## from Marcelino de la Cruz - scoping in update.ppm 152s + X <- cells 152s + Z <- density(X) 152s + pfit <- ppm(X ~ Z) 152s + cat("Fitted ppm(X~Z)", fill=TRUE) 152s + penv <- envelope(pfit, Kinhom, lambda=pfit, nsim=3) 152s + RX <- rotate(X, pi/3, centre="centroid") 152s + RZ <- density(RX) 152s + Rpfit <- ppm(RX ~ RZ) 152s + cat("Fitted ppm(RX~RZ)", fill=TRUE) 152s + Rpenv <- envelope(Rpfit, Kinhom, lambda=Rpfit, nsim=3) 152s + } 152s + 152s + if(FULLTEST) { 152s + #' envelope computations in other functions 152s + P <- lurking(cells, expression(x), envelope=TRUE, nsim=9) 152s + print(P) 152s + #' re-using envelope objects in other functions 152s + A <- envelope(cells, nsim=9, savepatterns=TRUE, savefuns=TRUE) 152s + S <- lurking(cells, expression(x), envelope=A, nsim=9) 152s + #' envelope.envelope 152s + B <- envelope(cells, nsim=5, savepatterns=TRUE, savefuns=FALSE) 152s + envelope(B) 152s + } 152s + 152s + 152s + 152s + ## close 'local' 152s + }) 152s Envelope of ppm(cells ~ x) has correct format 152s Generating 8 simulated realisations of fitted Poisson model (4 to estimate the 152s mean and 4 to calculate envelopes) ... 152s 1, 2, 3, 4, 5, 6, 7, 152s 8. 152s 152s Done. 152s Generating 4 simulated realisations of fitted Gibbs model with fixed number of 152s points ... 152s 1, 2, 3, 152s 4. 152s 152s Done. 152s Generating 4 simulated realisations of fitted Gibbs model with fixed number of 152s points of each type ... 152s 1, 2, 3, 152s 4. 152s 152s Done. 152s > #' tests/enveltest.R 152s > #' Envelope tests (dclf.test, mad.test) 152s > #' and two-stage tests (bits.test, dg.test, bits.envelope, dg.envelope) 152s > #' 152s > #' $Revision: 1.3 $ $Date: 2020/04/28 12:58:26 $ 152s > #' 152s > if(FULLTEST) { 152s + local({ 152s + #' handling of NA function values (due to empty point patterns) 152s + set.seed(1234) 152s + X <- rThomas(5, 0.05, 10) 152s + fit <- kppm(X ~ 1, "Thomas") 152s + set.seed(100000) 152s + dclf.test(fit) 152s + set.seed(909) 152s + dg.test(fit, nsim=9) 152s + #' other code blocks 152s + dclf.test(fit, rinterval=c(0, 3), nsim=9) 152s + envelopeTest(X, exponent=3, clamp=TRUE, nsim=9) 152s + }) 152s + } 152s > # 152s > # tests/fastgeyer.R 152s > # 152s > # checks validity of fast C implementation of Geyer interaction 152s > # 152s > # $Revision: 1.4 $ $Date: 2020/04/28 12:58:26 $ 152s > # 152s > if(FULLTEST) { # depends on hardware 152s + local({ 152s + X <- redwood 152s + Q <- quadscheme(X) 152s + U <- union.quad(Q) 152s + EP <- equalpairs.quad(Q) 152s + G <- Geyer(0.11, 2) 152s + # The value r=0.11 is chosen to avoid hardware numerical effects (gcc bug 323). 152s + # It avoids being close any value of pairdist(redwood). 152s + # The nearest such values are 0.1077.. and 0.1131.. 152s + # By contrast if r = 0.1 there are values differing from 0.1 by 3e-17 152s + a <- pairsat.family$eval(X,U,EP,G$pot,G$par,"border") 152s + b <- G$fasteval(X,U,EP,G$pot,G$par,"border") 152s + if(!all(a==b)) 152s + stop("Results of Geyer()$fasteval and pairsat.family$eval do not match") 152s + # ... 152s + # and again for a non-integer value of 'sat' 152s + # (spotted by Thordis Linda Thorarinsdottir) 152s + G <- Geyer(0.11, 2.5) 152s + a <- pairsat.family$eval(X,U,EP,G$pot,G$par,"border") 152s + b <- G$fasteval(X,U,EP,G$pot,G$par,"border") 152s + if(!all(a==b)) 152s + stop("Results of Geyer()$fasteval and pairsat.family$eval do not match when sat is not an integer") 152s + # and again for sat < 1 152s + # (spotted by Rolf) 152s + G <- Geyer(0.11, 0.5) 152s + a <- pairsat.family$eval(X,U,EP,G$pot,G$par,"border") 152s + b <- G$fasteval(X,U,EP,G$pot,G$par,"border") 152s + if(!all(a==b)) 152s + stop("Results of Geyer()$fasteval and pairsat.family$eval do not match when sat < 1") 152s + }) 152s + } 152s > 152s > #' tests/formuli.R 152s > #' 152s > #' Test machinery for manipulating formulae 152s > #' 152s > #' $Revision: 1.7 $ $Date: 2020/04/28 12:58:26 $ 152s > 152s > local({ 152s + 152s + ff <- function(A, deletevar, B) { 152s + D <- reduceformula(A, deletevar) 152s + if(!spatstat.utils::identical.formulae(D, B)) { 152s + AD <- as.expression(substitute(reduceformula(A,d), 152s + list(A=A, d=deletevar))) 152s + stop(paste(AD, "\n\tyields ", spatstat.utils::pasteFormula(D), 152s + " instead of ", spatstat.utils::pasteFormula(B)), 152s + call.=FALSE) 152s + } 152s + invisible(NULL) 152s + } 152s + 152s + ff(~ x + z, "x", ~z) 152s + 152s + ff(y ~ x + z, "x", y~z) 152s + 152s + ff(~ I(x^2) + z, "x", ~z) 152s + 152s + ff(y ~ poly(x,2) + poly(z,3), "x", y ~poly(z,3)) 152s + 152s + ff(y ~ x + z, "g", y ~ x + z) 152s + 152s + reduceformula(y ~ x+z, "g", verbose=TRUE) 152s + reduceformula(y ~ sin(x-z), "z", verbose=TRUE) 152s + 152s + illegal.iformula(~str*g, itags="str", dfvarnames=c("marks", "g", "x", "y")) 152s + }) 152s The formula does not involve “g” and is therefore unchanged 152s Don't know how to reduce the term “sin(x - z)” 152s NULL 152s > 152s > 152s > 152s > ## 152s > ## tests/funnymarks.R 152s > ## 152s > ## tests involving strange mark values 152s > ## $Revision: 1.7 $ $Date: 2020/04/28 12:58:26 $ 152s > 152s > if(ALWAYS) { # depends on locale 152s + local({ 152s + ## ppm() where mark levels contain illegal characters 152s + hyphenated <- c("a", "not-a") 152s + spaced <- c("U", "non U") 152s + suffixed <- c("a+", "a*") 152s + charred <- c("+", "*") 152s + 152s + irad <- matrix(0.1, 2,2) 152s + hrad <- matrix(0.005, 2, 2) 152s + 152s + tryit <- function(types, X, irad, hrad) { 152s + levels(marks(X)) <- types 152s + fit <- ppm(X ~marks + polynom(x,y,2), 153s + MultiStraussHard(types=types,iradii=irad,hradii=hrad)) 153s + print(fit) 153s + print(coef(fit)) 153s + val <- fitted(fit) 153s + pred <- predict(fit) 153s + return(invisible(NULL)) 153s + } 153s + 153s + tryit(hyphenated, amacrine, irad, hrad) 153s + tryit(spaced, amacrine, irad, hrad) 153s + tryit(suffixed, amacrine, irad, hrad) 153s + tryit(charred, amacrine, irad, hrad) 153s + 153s + ## marks which are dates 153s + X <- cells 153s + n <- npoints(X) 153s + endoftime <- rep(ISOdate(2001,1,1), n) 153s + eotDate <- rep(as.Date("2001-01-01"), n) 153s + markformat(endoftime) 153s + markformat(eotDate) 153s + marks(X) <- endoftime 153s + print(X) 153s + Y <- X %mark% data.frame(id=1:42, date=endoftime, dd=eotDate) 153s + print(Y) 153s + md <- markformat(endoftime) 153s + 153s + ## mark formats 153s + Z <- Y 153s + marks(Z) <- marks(Z)[1,,drop=FALSE] 153s + ms <- markformat(solist(cells, redwood)) 153s + marks(Z) <- factor(1:npoints(Z)) 153s + marks(Z)[12] <- NA 153s + mz <- is.multitype(Z) 153s + cZ <- coerce.marks.numeric(Z) 153s + marks(Z) <- data.frame(n=1:npoints(Z), 153s + a=factor(sample(letters, npoints(Z), replace=TRUE))) 153s + cZ <- coerce.marks.numeric(Z) 153s + stopifnot(is.multitype(cells %mark% data.frame(a=factor(1:npoints(cells))))) 153s + 153s + a <- numeric.columns(finpines) 153s + b1 <- numeric.columns(amacrine) 153s + b2 <- coerce.marks.numeric(amacrine) 153s + d <- numeric.columns(cells) 153s + f <- numeric.columns(longleaf) 153s + ff <- data.frame(a=factor(letters[1:10]), y=factor(sample(letters, 10))) 153s + numeric.columns(ff) 153s + 153s + ## mark operations 153s + df <- data.frame(x=1:2, y=sample(letters, 2)) 153s + h <- hyperframe(z=1:2, p=solist(cells, cells)) 153s + a <- NULL %mrep% 3 153s + a <- 1:4 %mrep% 3 153s + a <- df %mrep% 3 153s + a <- h %mrep% 3 153s + b <- markcbind(df, h) 153s + b <- markcbind(h, df) 153s + }) 153s + } 153s Nonstationary Multitype Strauss Hardcore process 153s Fitted to point pattern dataset ‘X’ 153s 153s Possible marks: ‘a’ and ‘not-a’ 153s 153s Log trend: ~marks + (x + y + I(x^2) + I(x * y) + I(y^2)) 153s 153s Fitted trend coefficients: 153s (Intercept) marksnot-a x y I(x^2) I(x * y) 153s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 0.3384324 153s I(y^2) 153s -0.5425654 153s 153s 2 types of points 153s Possible types: 153s [1] a not-a 153s Interaction radii: 153s a not-a 153s a 0.1 0.1 153s not-a 0.1 0.1 153s Hardcore radii: 153s a not-a 153s a 0.005 0.005 153s not-a 0.005 0.005 153s Fitted interaction parameters gamma_ij 153s a not-a 153s a 0.2699920 0.8920719 153s not-a 0.8920719 0.2694374 153s 153s Relevant coefficients: 153s markaxa markaxnot.a marknot.axnot.a 153s -1.3093629 -0.1142086 -1.3114192 153s 153s For standard errors, type coef(summary(x)) 153s (Intercept) marksnot-a x y I(x^2) 153s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 153s I(x * y) I(y^2) markaxa markaxnot.a marknot.axnot.a 153s 0.3384324 -0.5425654 -1.3093629 -0.1142086 -1.3114192 153s Nonstationary Multitype Strauss Hardcore process 153s Fitted to point pattern dataset ‘X’ 153s 153s Possible marks: ‘U’ and ‘non U’ 153s 153s Log trend: ~marks + (x + y + I(x^2) + I(x * y) + I(y^2)) 153s 153s Fitted trend coefficients: 153s (Intercept) marksnon U x y I(x^2) I(x * y) 153s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 0.3384324 153s I(y^2) 153s -0.5425654 153s 153s 2 types of points 153s Possible types: 153s [1] U non U 153s Interaction radii: 153s U non U 153s U 0.1 0.1 153s non U 0.1 0.1 153s Hardcore radii: 153s U non U 153s U 0.005 0.005 153s non U 0.005 0.005 153s Fitted interaction parameters gamma_ij 153s U non U 153s U 0.2699920 0.8920719 153s non U 0.8920719 0.2694374 153s 153s Relevant coefficients: 153s markUxU markUxnon.U marknon.Uxnon.U 153s -1.3093629 -0.1142086 -1.3114192 153s 153s For standard errors, type coef(summary(x)) 153s (Intercept) marksnon U x y I(x^2) 153s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 153s I(x * y) I(y^2) markUxU markUxnon.U marknon.Uxnon.U 153s 0.3384324 -0.5425654 -1.3093629 -0.1142086 -1.3114192 154s Nonstationary Multitype Strauss Hardcore process 154s Fitted to point pattern dataset ‘X’ 154s 154s Possible marks: ‘a+’ and ‘a*’ 154s 154s Log trend: ~marks + (x + y + I(x^2) + I(x * y) + I(y^2)) 154s 154s Fitted trend coefficients: 154s (Intercept) marksa* x y I(x^2) I(x * y) 154s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 0.3384324 154s I(y^2) 154s -0.5425654 154s 154s 2 types of points 154s Possible types: 154s [1] a+ a* 154s Interaction radii: 154s a+ a* 154s a+ 0.1 0.1 154s a* 0.1 0.1 154s Hardcore radii: 154s a+ a* 154s a+ 0.005 0.005 154s a* 0.005 0.005 154s Fitted interaction parameters gamma_ij 154s a+ a* 154s a+ 0.2699920 0.8920719 154s a* 0.8920719 0.2694374 154s 154s Relevant coefficients: 154s marka.xa. marka.xa..1 marka..1xa..1 154s -1.3093629 -0.1142086 -1.3114192 154s 154s For standard errors, type coef(summary(x)) 154s (Intercept) marksa* x y I(x^2) 154s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 154s I(x * y) I(y^2) marka.xa. marka.xa..1 marka..1xa..1 154s 0.3384324 -0.5425654 -1.3093629 -0.1142086 -1.3114192 154s Nonstationary Multitype Strauss Hardcore process 154s Fitted to point pattern dataset ‘X’ 154s 154s Possible marks: ‘+’ and ‘*’ 154s 154s Log trend: ~marks + (x + y + I(x^2) + I(x * y) + I(y^2)) 154s 154s Fitted trend coefficients: 154s (Intercept) marks* x y I(x^2) I(x * y) 154s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 0.3384324 154s I(y^2) 154s -0.5425654 154s 154s 2 types of points 154s Possible types: 154s [1] + * 154s Interaction radii: 154s + * 154s + 0.1 0.1 154s * 0.1 0.1 154s Hardcore radii: 154s + * 154s + 0.005 0.005 154s * 0.005 0.005 154s Fitted interaction parameters gamma_ij 154s + * 154s + 0.2699920 0.8920719 154s * 0.8920719 0.2694374 154s 154s Relevant coefficients: 154s markX.xX. markX.xX..1 markX..1xX..1 154s -1.3093629 -0.1142086 -1.3114192 154s 154s For standard errors, type coef(summary(x)) 154s (Intercept) marks* x y I(x^2) 154s 7.3741600 0.1223023 1.2302865 0.2403500 -0.7560707 154s I(x * y) I(y^2) markX.xX. markX.xX..1 markX..1xX..1 154s 0.3384324 -0.5425654 -1.3093629 -0.1142086 -1.3114192 154s Marked planar point pattern: 42 points 154s marks are dates, of class ‘POSIXt’ 154s window: rectangle = [0, 1] x [0, 1] units 154s Marked planar point pattern: 42 points 154s Mark variables: id, date, dd 154s window: rectangle = [0, 1] x [0, 1] units 154s > 154s BEGIN TEST testsGtoJ.R 154s Warning messages: 154s 1: In is.multitype.ppp(Z) : some mark values are NA in the point pattern Z 154s 2: Factor-valued marks were converted to integer codes 154s 3: Factor-valued mark variable ‘a’ was converted to integer codes 154s 4: Factor-valued marks were converted to integer codes 154s 154s R version 4.4.3 (2025-02-28) -- "Trophy Case" 154s Copyright (C) 2025 The R Foundation for Statistical Computing 154s Platform: aarch64-unknown-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/hobjects.R 155s > #' 155s > #' Validity of methods for ppm(... method="ho") 155s > #' 155s > #' $Revision: 1.4 $ $Date: 2022/06/18 10:14:44 $ 155s > 155s > 155s > if(FULLTEST) { 155s + local({ 155s + set.seed(42) 155s + fit <- ppm(cells ~1, Strauss(0.1), improve.type="ho", nsim=10) 155s + fitx <- ppm(cells ~offset(x), Strauss(0.1), improve.type="ho", nsim=10) 155s + 155s + a <- AIC(fit) 155s + ax <- AIC(fitx) 155s + 155s + f <- fitted(fit) 155s + fx <- fitted(fitx) 155s + 155s + p <- predict(fit) 155s + px <- predict(fitx) 155s + }) 155s + } 155s > 155s > 155s > #' tests/hypotests.R 155s > #' Hypothesis tests 155s > #' 155s > #' $Revision: 1.10 $ $Date: 2023/07/17 07:30:48 $ 155s > 155s > if(FULLTEST) { 155s + local({ 155s + 155s + #' scan test with baseline 155s + fit <- ppm(cells ~ x) 155s + lam <- predict(fit) 155s + rr <- c(0.05, 1) 155s + scan.test(cells, rr, nsim=5, 155s + method="poisson", baseline=fit, alternative="less") 155s + scan.test(cells, rr, nsim=5, 155s + method="poisson", baseline=lam, alternative="less") 155s + }) 155s + } 155s > #' 155s > #' tests/interact.R 155s > #' 155s > #' Support for interaction objects 155s > #' 155s > #' $Revision: 1.2 $ $Date: 2020/04/28 12:58:26 $ 155s > 155s > if(FULLTEST) { 155s + local({ 155s + #' print.intermaker 155s + Strauss 155s + Geyer 155s + Ord 155s + #' intermaker 155s + BS <- get("BlankStrauss", envir=environment(Strauss)) 155s + BD <- function(r) { instantiate.interact(BS, list(r=r)) } 155s + BlueDanube <- intermaker(BD, BS) 155s + }) 155s + } 155s > 155s > #' tests/ippm.R 155s > #' Tests of 'ippm' class 155s > #' $Revision: 1.6 $ $Date: 2020/04/28 12:58:26 $ 155s > 155s > if(FULLTEST) { 155s + local({ 155s + # .......... set up example from help file ................. 155s + nd <- 10 155s + gamma0 <- 3 155s + delta0 <- 5 155s + POW <- 3 155s + # Terms in intensity 155s + Z <- function(x,y) { -2*y } 155s + f <- function(x,y,gamma,delta) { 1 + exp(gamma - delta * x^POW) } 155s + # True intensity 155s + lamb <- function(x,y,gamma,delta) { 200 * exp(Z(x,y)) * f(x,y,gamma,delta) } 155s + # Simulate realisation 155s + lmax <- max(lamb(0,0,gamma0,delta0), lamb(1,1,gamma0,delta0)) 155s + set.seed(42) 155s + X <- rpoispp(lamb, lmax=lmax, win=owin(), gamma=gamma0, delta=delta0) 155s + # Partial derivatives of log f 155s + DlogfDgamma <- function(x,y, gamma, delta) { 155s + topbit <- exp(gamma - delta * x^POW) 155s + topbit/(1 + topbit) 155s + } 155s + DlogfDdelta <- function(x,y, gamma, delta) { 155s + topbit <- exp(gamma - delta * x^POW) 155s + - (x^POW) * topbit/(1 + topbit) 155s + } 155s + # irregular score 155s + Dlogf <- list(gamma=DlogfDgamma, delta=DlogfDdelta) 155s + # fit model 155s + fit <- ippm(X ~Z + offset(log(f)), 155s + covariates=list(Z=Z, f=f), 155s + iScore=Dlogf, 155s + start=list(gamma=1, delta=1), 155s + nd=nd) 155s + # fit model with logistic likelihood but without iScore 155s + fitlo <- ippm(X ~Z + offset(log(f)), 155s + method="logi", 155s + covariates=list(Z=Z, f=f), 155s + start=list(gamma=1, delta=1), 155s + nd=nd) 155s + 155s + ## ............. test ippm class support ...................... 155s + Ar <- model.matrix(fit) 155s + Ai <- model.matrix(fit, irregular=TRUE) 155s + An <- model.matrix(fit, irregular=TRUE, keepNA=FALSE) 155s + AS <- model.matrix(fit, irregular=TRUE, subset=(abs(Z) < 0.5)) 155s + 155s + Zr <- model.images(fit) 155s + Zi <- model.images(fit, irregular=TRUE) 155s + ## update.ippm 155s + fit2 <- update(fit, . ~ . + I(Z^2)) 155s + fit0 <- update(fit, 155s + . ~ . - Z, 155s + start=list(gamma=2, delta=4)) 155s + oldfit <- ippm(X, 155s + ~Z + offset(log(f)), 155s + covariates=list(Z=Z, f=f), 155s + iScore=Dlogf, 155s + start=list(gamma=1, delta=1), 155s + nd=nd) 155s + oldfit2 <- update(oldfit, . ~ . + I(Z^2)) 155s + oldfit0 <- update(oldfit, 155s + . ~ . - Z, 155s + start=list(gamma=2, delta=4)) 155s + ## again with logistic 155s + fitlo2 <- update(fitlo, . ~ . + I(Z^2)) 155s + fitlo0 <- update(fitlo, 155s + . ~ . - Z, 155s + start=list(gamma=2, delta=4)) 155s + oldfitlo <- ippm(X, 155s + ~Z + offset(log(f)), 155s + method="logi", 155s + covariates=list(Z=Z, f=f), 155s + start=list(gamma=1, delta=1), 155s + nd=nd) 155s + oldfitlo2 <- update(oldfitlo, . ~ . + I(Z^2)) 155s + oldfitlo0 <- update(oldfitlo, 155s + . ~ . - Z, 155s + start=list(gamma=2, delta=4)) 155s + ## anova.ppm including ippm objects 155s + fit0 <- update(fit, . ~ Z) 155s + fit0lo <- update(fitlo, . ~ Z) 155s + A <- anova(fit0, fit) 155s + Alo <- anova(fit0lo, fitlo) 155s + }) 155s + } 155s > 155s BEGIN TEST testsK.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: aarch64-unknown-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 156s > #' 156s > #' Header for all (concatenated) test files 156s > #' 156s > #' Require spatstat.model 156s > #' Obtain environment variable controlling tests. 156s > #' 156s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 156s > 156s > require(spatstat.model) 156s Loading required package: spatstat.model 156s Loading required package: spatstat.data 157s Loading required package: spatstat.univar 157s spatstat.univar 3.1-2 157s Loading required package: spatstat.geom 157s spatstat.geom 3.3-6 157s Loading required package: spatstat.random 157s spatstat.random 3.3-3 157s Loading required package: spatstat.explore 157s Loading required package: nlme 157s spatstat.explore 3.3-4 157s 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/kppm.R 157s > # 157s > # $Revision: 1.40 $ $Date: 2024/02/26 05:44:02 $ 157s > # 157s > # Test functionality of kppm that once depended on RandomFields 157s > # Test update.kppm for old style kppm objects 157s > 157s > if(!FULLTEST) 157s + spatstat.options(npixel=32, ndummy.min=16) 157s > 157s > local({ 157s + 157s + fit <- kppm(redwood ~1, "Thomas") # sic 157s + fitx <- kppm(redwood ~x, "Thomas", verbose=TRUE) 157s + if(FULLTEST) { 157s + fitx <- update(fit, ~ . + x) 157s + fitM <- update(fit, clusters="MatClust") 157s + fitC <- update(fit, cells) 157s + fitCx <- update(fit, cells ~ x) 157s + #' 157s + Wsub <- owin(c(0, 0.5), c(-0.5, 0)) 157s + Zsub <- (bdist.pixels(Window(redwood)) > 0.1) 157s + fitWsub <- kppm(redwood ~1, "Thomas", subset=Wsub) 157s + fitZsub <- kppm(redwood ~1, "Thomas", subset=Zsub) 157s + fitWsub 157s + 157s + #' various methods 157s + ff <- as.fv(fitx) 157s + uu <- unitname(fitx) 157s + unitname(fitCx) <- "furlong" 157s + mo <- model.images(fitCx) 157s + p <- psib(fit) 157s + px <- psib(fitx) 157s + } 157s + if(ALWAYS) { 157s + Y <- simulate(fitx, seed=42, saveLambda=TRUE)[[1]] 157s + } 157s + 157s + if(FULLTEST) { 157s + #' vcov.kppm different algorithms 157s + vc <- vcov(fitx) 157s + vc2 <- vcov(fitx, fast=TRUE) 157s + vc3 <- vcov(fitx, fast=TRUE, splitup=TRUE) 157s + vc4 <- vcov(fitx, splitup=TRUE) 157s + 157s + ## other code blocks 157s + a <- varcount(fitx, function(x,y){x+1}) # always positive 157s + a <- varcount(fitx, function(x,y){y-1}) # always negative 157s + a <- varcount(fitx, function(x,y){x+y}) # positive or negative 157s + 157s + #' improve.kppm 157s + fitI <- update(fit, improve.type="quasi") 157s + fitxI <- update(fitx, improve.type="quasi") 157s + fitxIs <- update(fitx, improve.type="quasi", fast=FALSE) 157s + #' vcov.kppm 157s + vcI <- vcov(fitxI) 157s + } 157s + 157s + ## plot.kppm including predict.kppm 157s + if(ALWAYS) { 157s + fitMC <- kppm(redwood ~ x, "Thomas") 157s + plot(fitMC) 157s + } 157s + if(FULLTEST) { 157s + fitCL <- kppm(redwood ~ x, "Thomas", method="c") 157s + fitPA <- kppm(redwood ~ x, "Thomas", method="p") 157s + plot(fitCL) 157s + plot(fitPA) 157s + 157s + ## fit with composite likelihood method [thanks to Abdollah Jalilian] 157s + fut <- kppm(redwood ~ x, "VarGamma", method="clik2", nu.ker=-3/8) 157s + kfut <- as.fv(fut) 157s + } 157s + 157s + if(ALWAYS) { 157s + fit0 <- kppm(redwood ~1, "LGCP") 157s + is.poisson(fit0) 157s + Y0 <- simulate(fit0, saveLambda=TRUE)[[1]] 157s + stopifnot(is.ppp(Y0)) 157s + p0 <- psib(fit0) # issues a warning 157s + 157s + if(FULLTEST) { 157s + ## fit LGCP using K function: slow 157s + fit1 <- kppm(redwood ~x, "LGCP", 157s + covmodel=list(model="matern", nu=0.3), 157s + control=list(maxit=3)) 157s + Y1 <- simulate(fit1, saveLambda=TRUE)[[1]] 157s + stopifnot(is.ppp(Y1)) 157s + } 157s + 157s + ## fit LGCP using pcf 157s + fit1p <- kppm(redwood ~x, "LGCP", 157s + covmodel=list(model="matern", nu=0.3), 157s + statistic="pcf") 157s + Y1p <- simulate(fit1p, saveLambda=TRUE)[[1]] 157s + stopifnot(is.ppp(Y1p)) 157s + 157s + ## .. and using different fitting methods 157s + if(FULLTEST) { 157s + fit1pClik <- update(fit1p, method="clik") 157s + fit1pPalm <- update(fit1p, method="palm") 157s + } 157s + 157s + ## shortcut evaluation of pcf 157s + ## (the code being tested is in spatstat.random::clusterinfo.R) 157s + if(FULLTEST) { 157s + putSpatstatVariable("RFshortcut", TRUE) 157s + fitGshort <- kppm(redwood ~ 1, "LGCP", covmodel=list(model="gauss")) 157s + fitSshort <- kppm(redwood ~ 1, "LGCP", covmodel=list(model="stable", alpha=1)) 157s + putSpatstatVariable("RFshortcut", FALSE) 157s + fitGlong <- kppm(redwood ~ 1, "LGCP", covmodel=list(model="gauss")) 157s + fitSlong <- kppm(redwood ~ 1, "LGCP", covmodel=list(model="stable", alpha=1)) 157s + discrepG <- unlist(parameters(fitGshort)) - unlist(parameters(fitGlong)) 157s + discrepS <- unlist(parameters(fitSshort)) - unlist(parameters(fitSlong)) 157s + print(discrepG) 157s + print(discrepS) 157s + if(max(abs(discrepG) > 0.01)) 157s + stop("Discrepancy in short-cut fitting of Gaussian LGCP") 157s + if(max(abs(discrepS) > 0.01)) 157s + stop("Discrepancy in short-cut fitting of stable LGCP") 157s + } 157s + 157s + ## image covariate (a different code block) 157s + xx <- as.im(function(x,y) x, Window(redwood)) 157s + fit1xx <- update(fit1p, . ~ xx, data=solist(xx=xx)) 157s + Y1xx <- simulate(fit1xx, saveLambda=TRUE)[[1]] 157s + stopifnot(is.ppp(Y1xx)) 157s + if(FULLTEST) { 157s + fit1xxVG <- update(fit1xx, clusters="VarGamma", nu=-1/4) 157s + Y1xxVG <- simulate(fit1xxVG, saveLambda=TRUE)[[1]] 157s + stopifnot(is.ppp(Y1xxVG)) 157s + } 157s + fit1xxLG <- update(fit1xx, clusters="LGCP", 157s + covmodel=list(model="matern", nu=0.3), 157s + statistic="pcf") 157s + Y1xxLG <- simulate(fit1xxLG, saveLambda=TRUE, drop=TRUE) 157s + stopifnot(is.ppp(Y1xxLG)) 157s + 157s + # ... and Abdollah's code 157s + if(FULLTEST) { 157s + fit2 <- kppm(redwood ~x, cluster="Cauchy", statistic="K") 157s + Y2 <- simulate(fit2, saveLambda=TRUE)[[1]] 157s + stopifnot(is.ppp(Y2)) 157s + } 157s + } 157s + 157s + }) 157s Fitting cluster model 157s Retrieved cluster model information 157s Algorithm parameters: 157s $rmax 157s NULL 157s 157s $q 157s [1] 0.25 157s 157s $p 157s [1] 2 157s 157s $rmin 157s NULL 157s 157s Using point pattern data 157s Starting parameters: 157s kappa sigma2 157s 62.000000000 0.006173033 157s Calculating summary function...Done. 157s Starting minimum contrast fit 157s Returned from minimum contrast fit 157s Returning from clusterfit 159s > 159s > if(FULLTEST) { 159s + local({ 159s + #' various code blocks 159s + fut <- kppm(redwood, ~x) 159s + fet <- update(fut, redwood3) 159s + fot <- update(fut, trend=~y) 159s Warning messages: 159s 1: Internal error: fvlabels truncated the function name 159s 2: Internal error: fvlabels truncated the function name 159s 3: Internal error: fvlabels truncated the function name 159s 4: In psib.kppm(fit0) : The model is not a cluster process 159s 5: The value of the empirical function ‘pcf’ for r= 0 was Inf. Range of r values was reset to [0.00048828125, 0.25] 159s 6: The value of the empirical function ‘pcf’ for r= 0 was Inf. Range of r values was reset to [0.00048828125, 0.25] 159s 7: The value of the empirical function ‘pcf’ for r= 0 was Inf. Range of r values was reset to [0.00048828125, 0.25] 159s + fit <- kppm(redwoodfull ~ x) 159s + Y <- simulate(fit, window=redwoodfull.extra$regionII, saveLambda=TRUE) 159s + gut <- improve.kppm(fit, type="wclik1") 159s + gut <- improve.kppm(fit, vcov=TRUE, fast.vcov=TRUE, save.internals=TRUE) 159s + hut <- kppm(redwood ~ x, method="clik", weightfun=NULL) 159s + hut <- kppm(redwood ~ x, method="palm", weightfun=NULL) 159s + mut <- kppm(redwood) 159s + nut <- update(mut, Y) 159s + }) 159s + } 159s > 159s > if(FULLTEST) { 159s + local({ 159s + #' minimum contrast code 159s + K <- Kest(redwood) 159s + a <- matclust.estK(K) 159s + a <- thomas.estK(K) 159s + a <- cauchy.estK(K) 159s + a <- vargamma.estK(K) 159s + a <- lgcp.estK(K) 159s + 159s + print(a) 159s + u <- unitname(a) 159s + 159s + g <- pcf(redwood) 159s + a <- matclust.estpcf(g) 159s + a <- thomas.estpcf(g) 159s + a <- cauchy.estpcf(g) 159s + a <- vargamma.estpcf(g) 159s + a <- lgcp.estpcf(g) 159s + 159s + #' auxiliary functions 159s + b <- resolve.vargamma.shape(nu.pcf=1.5) 159s + Z <- clusterfield("Thomas", kappa=1, scale=0.2) 159s + 159s + aa <- NULL 159s + aa <- accumulateStatus(simpleMessage("Woof"), aa) 159s + aa <- accumulateStatus(simpleMessage("Sit"), aa) 159s + aa <- accumulateStatus(simpleMessage("Woof"), aa) 159s + printStatusList(aa) 159s + 159s + RMIN <- 0.01 159s + fit <- kppm(redwood ~ 1, ctrl=list(rmin=RMIN,q=1/2)) 159s + if(fit$Fit$mcfit$ctrl$rmin != RMIN) 159s + stop("kppm did not handle parameter 'rmin' in argument 'ctrl' ") 159s + fit <- kppm(redwood ~ 1, ctrl=list(rmin=0,q=1/2), rmin=RMIN) 159s + if(fit$Fit$mcfit$ctrl$rmin != RMIN) 159s + stop("kppm did not handle parameter 'rmin' in argument 'ctrl'") 159s + 159s + RMIN <- 2 159s + fit <- dppm(swedishpines~1, dppGauss(), ctrl=list(rmin=RMIN,q=1)) 159s + if(fit$Fit$mcfit$ctrl$rmin != RMIN) 159s + stop("dppm did not handle parameter 'rmin' in argument 'ctrl'") 159s + fit <- dppm(swedishpines~1, dppGauss(), ctrl=list(rmin=0,q=1), rmin=RMIN) 159s + if(fit$Fit$mcfit$ctrl$rmin != RMIN) 159s + stop("dppm did not handle argument 'rmin'") 159s + }) 159s + } 159s > 159s > 159s > 159s > if(FULLTEST) { 159s + local({ 159s + #' cover a few code blocks 159s + fut <- kppm(redwood ~ x, method="clik") 159s + print(summary(fut)) 159s + a <- residuals(fut) 159s + fut2 <- kppm(redwood ~ x, "LGCP", method="palm") 159s + print(summary(fut2)) 159s + b <- residuals(fut2) 159s + #' 159s + po <- ppm(redwood ~ 1) 159s + A <- kppmComLik(redwood, Xname="redwood", po=po, clusters="Thomas", 159s + statistic="pcf", statargs=list(), control=list(), 159s + weightfun=NULL, rmax=0.1) 159s + A <- kppmPalmLik(redwood, Xname="redwood", po=po, clusters="Thomas", 159s + statistic="pcf", statargs=list(), control=list(), 159s + weightfun=NULL, rmax=0.1) 159s + }) 159s + } 159s > 159s > reset.spatstat.options() 159s > 159s > #' 159s > #' tests/Kfuns.R 159s > #' 159s > #' Various K and L functions and pcf 159s > #' 159s > #' $Revision: 1.43 $ $Date: 2022/06/17 01:47:08 $ 159s > #' 159s > #' Assumes 'EveryStart.R' was run 159s > 159s > if(FULLTEST) { 159s + Cells <- cells 159s + Amacrine <- amacrine 159s + Redwood <- redwood 159s + } else { 159s + ## reduce numbers of data + dummy points 159s + spatstat.options(npixel=32, ndummy.min=16) 159s + Cells <- cells[c(FALSE, TRUE)] 159s + Amacrine <- amacrine[c(FALSE, TRUE)] 159s + Redwood <- redwood[c(FALSE, TRUE)] 159s + } 159s > 159s > 159s > if(FULLTEST) { 159s + local({ 159s + #' code blocks using fitted model to determine intensity 159s + #' Kinhom 159s + X <- rpoispp(function(x,y) { 100 * x }, 100, square(1)) 159s + fut <- ppm(X ~ x) 159s + Kio <- Kinhom(X, fut, update=FALSE) 159s + Kiu <- Kinhom(X, fut, update=TRUE, diagonal=FALSE) 159s + fit <- ppm(Amacrine ~ marks) 159s + #' lohboot Linhom 159s + Zred <- predict(ppm(Redwood ~ x+y)) 159s + Lred <- lohboot(Redwood, Linhom, lambda=Zred) 159s + #' Kmulti.inhom 159s + K1 <- Kcross.inhom(Amacrine, lambdaX=fit) 159s + On <- split(Amacrine)$on 159s + Off <- split(Amacrine)$off 159s + K4 <- Kcross.inhom(Amacrine, lambdaI=ppm(On), lambdaJ=ppm(Off)) 159s + #' local K functions 159s + fut <- ppm(swedishpines ~ polynom(x,y,2)) 159s + Z <- predict(fut) 159s + Lam <- fitted(fut, dataonly=TRUE) 159s + a <- localLinhom(swedishpines, lambda=fut) 159s + a <- localLinhom(swedishpines, lambda=Z) 159s + a <- localLinhom(swedishpines, lambda=Lam) 159s + a <- localLinhom(swedishpines, lambda=Z, correction="none") 159s + a <- localLinhom(swedishpines, lambda=Z, correction="translate") 159s + #' local cross K functions 159s + fat <- ppm(Amacrine ~ x * marks) 159s + Zed <- predict(fat) 159s + Lum <- fitted(fat, dataonly=TRUE) 159s + moff <- (marks(Amacrine) == "off") 159s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=Zed) 159s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=Lum) 159s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=fat) 159s + a <- localLcross.inhom(Amacrine, from="off", to="on", 159s + lambdaFrom=Lum[moff], lambdaTo=Lum[!moff]) 159s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=Zed, 159s + correction="none") 159s + a <- localLcross.inhom(Amacrine, from="off", to="on", lambdaX=Zed, 159s + correction="translate") 159s + #' cases of resolve.lambdacross 159s + h <- resolve.lambdacross(Amacrine, moff, !moff, lambdaX=fat) 159s + h <- resolve.lambdacross(Amacrine, moff, !moff, lambdaX=fat, update=FALSE) 159s + h <- resolve.lambdacross(Amacrine, moff, !moff, 159s + lambdaI=fat, lambdaJ=fat) 159s + h <- resolve.lambdacross(Amacrine, moff, !moff, 159s + lambdaI=fat, lambdaJ=fat, 159s + update=FALSE) 159s + #' lohboot 159s + b <- lohboot(Amacrine, Lcross.inhom, from="off", to="on", lambdaX=Zed) 159s + b <- lohboot(Amacrine, Lcross.inhom, from="off", to="on", lambdaX=Lum) 159s + b <- lohboot(Amacrine, Lcross.inhom, from="off", to="on", lambdaX=fat) 159s + b <- lohboot(Amacrine, Lcross.inhom, from="off", to="on", 159s + lambdaFrom=Lum[moff], lambdaTo=Lum[!moff]) 159s + #' 159s + #' residual K functions etc 159s + #' 159s + rco <- compareFit(Cells, Kcom, 159s + interaction=anylist(P=Poisson(), S=Strauss(0.08)), 159s + same="trans", different="tcom") 159s + fit <- ppm(Cells ~ x, Strauss(0.07)) 159s + K <- Kcom(Cells, model=fit, restrict=TRUE) 159s + }) 159s + } 159s > 159s > reset.spatstat.options() 159s > 159s BEGIN TEST testsL.R 159s 159s R version 4.4.3 (2025-02-28) -- "Trophy Case" 159s Copyright (C) 2025 The R Foundation for Statistical Computing 159s Platform: aarch64-unknown-linux-gnu 159s 159s R is free software and comes with ABSOLUTELY NO WARRANTY. 159s You are welcome to redistribute it under certain conditions. 159s Type 'license()' or 'licence()' for distribution details. 159s 159s R is a collaborative project with many contributors. 159s Type 'contributors()' for more information and 159s 'citation()' on how to cite R or R packages in publications. 159s 159s Type 'demo()' for some demos, 'help()' for on-line help, or 159s 'help.start()' for an HTML browser interface to help. 159s Type 'q()' to quit R. 159s 159s > #' 159s > #' Header for all (concatenated) test files 159s > #' 159s > #' Require spatstat.model 159s > #' Obtain environment variable controlling tests. 159s > #' 159s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 159s > 159s > require(spatstat.model) 159s Loading required package: spatstat.model 159s Loading required package: spatstat.data 160s Loading required package: spatstat.univar 160s spatstat.univar 3.1-2 160s Loading required package: spatstat.geom 160s spatstat.geom 3.3-6 160s Loading required package: spatstat.random 160s spatstat.random 3.3-3 160s Loading required package: spatstat.explore 160s Loading required package: nlme 160s spatstat.explore 3.3-4 160s Loading required package: rpart 160s spatstat.model 3.3-4 160s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 160s > ALWAYS <- TRUE 160s > cat(paste("--------- Executing", 160s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 160s + "test code -----------\n")) 160s --------- Executing **RESTRICTED** subset of test code ----------- 160s > ## 160s > ## tests/legacy.R 160s > ## 160s > ## Test that current version of spatstat is compatible with outmoded usage 160s > ## $Revision: 1.3 $ $Date: 2020/04/29 08:55:17 $ 160s > 160s > if(FULLTEST) { 160s + local({ 160s + 160s + ## (1) Old syntax of ppm 160s + ppm(cells, ~x) 160s + 160s + ## (2) Old syntax of MultiStrauss etc. 160s + r <- matrix(3, 2, 2) 160s + a <- MultiStrauss( , r) 160s + a <- MultiStrauss(NULL, r) 160s + a <- MultiHard(, r) 160s + 160s + h <- r/2 160s + a <- MultiStraussHard( , r, h) 160s + 160s + NULL 160s + }) 160s + } 160s > #' 160s > #' tests/leverinf.R 160s > #' 160s > #' leverage and influence for Gibbs models 160s > #' 160s > #' $Revision: 1.35 $ $Date: 2022/06/18 10:15:17 $ 160s > #' 160s > 160s > if(FULLTEST) { 160s + Cells <- cells 160s + Amacrine <- amacrine 160s + Redwood <- redwood 160s + } else { 160s + ## reduce number of data + dummy points 160s + spatstat.options(npixel=32, ndummy.min=16) 160s + Cells <- cells[c(FALSE,TRUE)] 160s + Redwood <- redwood[c(FALSE, TRUE)] 160s + Amacrine <- amacrine[c(FALSE, TRUE)] 160s + } 160s > 160s > local({ 160s + cat("Running non-sparse algorithm...", fill=TRUE) 160s + # original non-sparse algorithm 160s + Leverage <- function(...) leverage(..., sparseOK=FALSE) 160s + Influence <- function(...) influence(..., sparseOK=FALSE) 160s + Dfbetas <- function(...) dfbetas(..., sparseOK=FALSE) 160s + if(ALWAYS) { 160s + ## Strauss()$delta2 160s + fitS <- ppm(Cells ~ x, Strauss(0.12), rbord=0) 160s + levS <- Leverage(fitS) 160s + infS <- Influence(fitS) 160s + dfbS <- Dfbetas(fitS) 160s + ## Geyer()$delta2 160s + fitG <- ppm(Redwood ~ 1, Geyer(0.1, 2), rbord=0) 160s + levG <- Leverage(fitG) 160s + infG <- Influence(fitG) 160s + ## AreaInter()$delta2 160s + fitA <- ppm(Cells ~ 1, AreaInter(0.06), rbord=0, nd=11) 160s + levA <- Leverage(fitA) 160s + infA <- Influence(fitA) 160s + ## pairwise.family$delta2 160s + fitD <- ppm(Cells ~ 1, DiggleGatesStibbard(0.12), rbord=0) 160s + levD <- Leverage(fitD) 160s + infD <- Influence(fitD) 160s + ## DiggleGratton() special code 160s + fitDG <- ppm(Cells ~ 1, DiggleGratton(0.05, 0.12), rbord=0) 160s + levDG <- Leverage(fitDG) 160s + infDG <- Influence(fitDG) 160s + ## ppmInfluence; offset is present; coefficient vector has length 0 160s + fitH <- ppm(Cells ~ 1, Hardcore(0.07)) 160s + levH <- Leverage(fitH) 160s + infH <- Influence(fitH) 160s + ## ppmInfluence; hard core 160s + fitSH <- ppm(Cells ~ 1, StraussHard(0.07, 0.01)) 160s + levSH <- Leverage(fitSH) 160s + infSH <- Influence(fitSH) 160s + ## ppmInfluence; offset is present; coefficient vector has length 1 160s + fitHx <- ppm(Cells ~ x, Hardcore(0.07), rbord=0) 160s + levHx <- Leverage(fitHx) 160s + infHx <- Influence(fitHx) 160s + ## multitype 160s + futAm <- ppm(Amacrine ~ x + marks, Strauss(0.07)) 160s + levAm <- leverage(futAm) 160s + } 160s + 160s + if(FULLTEST) { 160s + ## ......... class support ............................. 160s + ## other methods for classes leverage.ppm and influence.ppm 160s + ## not elsewhere tested 160s + cat("Testing class support...", fill=TRUE) 160s + w <- domain(levS) 160s + w <- Window(infS) 160s + vv <- shift(levS, c(1.2, 1.3)) 160s + vv <- shift(infS, c(1.2, 1.3)) 160s + A <- quadrats(Window(Cells), 2) 160s + a <- integral(levS,domain=A) 160s + b <- integral(infS,domain=A) 160s + u <- Smooth(levS, sigma=0.07) 160s + v <- Smooth(infS, sigma=0.1) 160s + ## plot options 160s + plot(levS, what="exact") 160s + plot(levS, what="nearest") 160s + contour(levS, what="nearest") 160s + persp(levS, what="nearest") 160s + ## plotting for multitype models 160s + plot(levAm) 160s + contour(levAm) 160s + persp(levAm) 160s + plot(levAm, multiplot=FALSE) 160s + contour(levAm, multiplot=FALSE) 160s + } 160s + 160s + if(ALWAYS) { 160s + ## .......... compare algorithms ......................... 160s + ## divide and recombine algorithm 160s + cat("Reduce maximum block side to 50,000 ...", fill=TRUE) 160s + op <- spatstat.options(maxmatrix=50000) 160s + ## non-sparse 160s + levSB <- Leverage(fitS) 160s + infSB <- Influence(fitS) 160s + dfbSB <- Dfbetas(fitS) 160s + } 160s + 160s + chk <- function(x, y, what, 160s + from="single-block and multi-block", 160s + thresh=1e-12) { 160s + if(max(abs(x-y)) > thresh) 160s + stop(paste("Different results for", what, "obtained from", 160s + from, "algorithms"), 160s + call.=FALSE) 160s + invisible(NULL) 160s + } 160s + 160s + if(ALWAYS) { 160s + cat("Compare single-block to multi-block...", fill=TRUE) 160s + chk(marks(as.ppp(infS)), marks(as.ppp(infSB)), "influence") 160s + chk(as.im(levS), as.im(levSB), "leverage") 160s + chk(dfbS$val, dfbSB$val, "dfbetas$value") 160s + chk(dfbS$density, dfbSB$density, "dfbetas$density") 160s + } 160s + 160s + if(FULLTEST) { 160s + ## also check case of zero cif 160s + cat("Check zero cif cases...", fill=TRUE) 160s + levHB <- Leverage(fitH) 160s + infHB <- Influence(fitH) 160s + dfbHB <- Dfbetas(fitH) 160s + levHxB <- Leverage(fitHx) 160s + infHxB <- Influence(fitHx) 160s + dfbHxB <- Dfbetas(fitHx) 160s + } 160s + 160s + ## run all code segments 160s + Everything <- function(model, ...) { ppmInfluence(model, ..., what="all") } 160s + 160s + if(FULLTEST) { 160s + cat("Run full code on AreaInteraction model...", fill=TRUE) 160s + pmiA <- Everything(fitA) 160s + 160s + ## sparse algorithm, with blocks 160s + cat("Run sparse algorithm with blocks...", fill=TRUE) 160s + pmiSSB <- Everything(fitS, sparseOK=TRUE) 160s + ## also check case of zero cif 160s + pmiHSB <- Everything(fitH, sparseOK=TRUE) 160s + pmiSHSB <- Everything(fitSH, sparseOK=TRUE) 160s + pmiHxSB <- Everything(fitHx, sparseOK=TRUE) 160s + 160s + cat("Reinstate maxmatrix...", fill=TRUE) 160s + spatstat.options(op) 160s + } 160s + 160s + if(ALWAYS) { 160s + ## sparse algorithm, no blocks 160s + cat("Compare sparse and non-sparse results...", fill=TRUE) 160s + pmi <- Everything(fitS, sparseOK=TRUE) 160s + levSp <- pmi$leverage 160s + infSp <- pmi$influence 160s + dfbSp <- pmi$dfbetas 160s + chks <- function(...) chk(..., from="sparse and non-sparse") 160s + 160s + chks(marks(as.ppp(infS)), marks(as.ppp(infSp)), "influence") 160s + chks(as.im(levS), as.im(levSp), "leverage") 160s + chks(dfbS$val, dfbSp$val, "dfbetas$value") 160s + chks(dfbS$density, dfbSp$density, "dfbetas$density") 160s + } 160s + 160s + if(ALWAYS) { 160s + #' case of zero cif 160s + cat("zero cif...", fill=TRUE) 160s + pmiH <- Everything(fitH, sparseOK=TRUE) 160s + pmiSH <- Everything(fitSH, sparseOK=TRUE) 160s + pmiHx <- Everything(fitHx, sparseOK=TRUE) 160s + } 160s + if(FULLTEST) { 160s + #' other code blocks - check execution only 160s + cat("other code blocks...", fill=TRUE) 160s + a <- Everything(fitS) 160s + a <- Everything(fitS, method="interpreted") 160s + a <- Everything(fitS, method="interpreted", entrywise=FALSE) 160s + a <- Everything(fitS, entrywise=FALSE) 160s + #' zero cif 160s + b <- Everything(fitSH) 160s + b <- Everything(fitSH, method="interpreted") 160s + b <- Everything(fitSH, method="interpreted", entrywise=FALSE) 160s + b <- Everything(fitSH, entrywise=FALSE) 160s + } 160s + #' NOTE: code for irregular parameters is tested below, and in 'make bookcheck' 160s + 160s + ## ........... logistic fits ....................... 160s + cat("Logistic fits...", fill=TRUE) 160s + #' special algorithm for delta2 160s + fitSlogi <- ppm(Cells ~ x, Strauss(0.12), rbord=0, method="logi") 160s + 160s + if(FULLTEST) { 160s + pmiSlogi <- Everything(fitSlogi) 160s + #' special algorithm for delta2 160s + fitGlogi <- ppm(Redwood ~ 1, Geyer(0.1, 2), rbord=0, method="logi") 160s + pmiGlogi <- Everything(fitGlogi) 160s + #' generic algorithm for delta2 160s + fitDlogi <- ppm(Cells ~ 1, DiggleGatesStibbard(0.12), 160s + rbord=0, method="logi") 160s + pmiDlogi <- Everything(fitDlogi) 160s + #' generic algorithm for delta2 : offset; zero-dimensional 160s + fitHlogi <- ppm(Cells ~ 1, Hardcore(0.07), method="logi") 160s + pmiHlogi <- Everything(fitHlogi) 160s + #' generic algorithm for delta2 : offset; 1-dimensional 160s + fitHxlogi <- ppm(Cells ~ x, Hardcore(0.07), rbord=0, method="logi") 160s + pmiHxlogi <- Everything(fitHxlogi) 160s + #' plotting 160s + plot(leverage(fitSlogi)) 160s + plot(influence(fitSlogi)) 160s + plot(dfbetas(fitSlogi)) 160s + } 160s + 160s + if(ALWAYS) { 160s + #' other code blocks - check execution only 160s + cat("Other code blocks...", fill=TRUE) 160s + b <- Everything(fitSlogi) # i.e. full set of results 160s + b <- Everything(fitSlogi, method="interpreted") 160s + b <- Everything(fitSlogi, method="interpreted", entrywise=FALSE) 160s + b <- Everything(fitSlogi, entrywise=FALSE) 160s + } 160s + 160s + #' irregular parameters 160s + cat("Irregular parameters...", fill=TRUE) 160s + ytoa <- function(x,y, alpha=1) { y^alpha } 160s + lam <- function(x,y,alpha=1) { exp(4 + y^alpha) } 160s + set.seed(90210) 160s + X <- rpoispp(lam, alpha=2) 160s + iScor <- list(alpha=function(x,y,alpha) { alpha * y^(alpha-1) } ) 160s + iHess <- list(alpha=function(x,y,alpha) { alpha * (alpha-1) * y^(alpha-2) } ) 160s + gogo <- function(tag, ..., iS=iScor, iH=iHess) { 160s + cat(tag, fill=TRUE) 160s + #' compute all leverage+influence terms 160s + ppmInfluence(..., what="all", iScore=iS, iHessian=iH) 160s + } 160s + gogogo <- function(hdr, fit) { 160s + cat(hdr, fill=TRUE) 160s + force(fit) 160s + #' try all code options 160s + d <- gogo("a", fit) 160s + d <- gogo("b", fit, method="interpreted") 160s + d <- gogo("c", fit, method="interpreted", entrywise=FALSE) 160s + d <- gogo("d", fit, entrywise=FALSE) 160s + invisible(NULL) 160s + } 160s + gogogo("Offset model...", 160s + ippm(X ~ offset(ytoa), start=list(alpha=1), iterlim=40)) 160s + gogogo("Offset model (logistic) ...", 160s + ippm(X ~ offset(ytoa), start=list(alpha=1), 160s + method="logi", iterlim=40)) 160s + gogogo("Offset+x model...", 160s + ippm(X ~ x + offset(ytoa), start=list(alpha=1), iterlim=40)) 160s + gogogo("Offset+x model (logistic) ...", 160s + ippm(X ~ x + offset(ytoa), start=list(alpha=1), 160s + method="logi", iterlim=40)) 160s + gogogo("Offset model Strauss ...", 160s + ippm(X ~ offset(ytoa), Strauss(0.07), start=list(alpha=1), iterlim=40)) 160s + gogogo("Offset model Strauss (logistic) ...", 160s + ippm(X ~ offset(ytoa), Strauss(0.07), start=list(alpha=1), 160s + method="logi", iterlim=40)) 160s + if(FULLTEST) { 160s + gogogo("Offset+x model Strauss ...", 160s + ippm(X ~ x + offset(ytoa), Strauss(0.07), start=list(alpha=1), 160s + iterlim=40)) 160s + gogogo("Offset+x model Strauss (logistic)...", 160s + ippm(X ~ x + offset(ytoa), Strauss(0.07), start=list(alpha=1), 160s + method="logi", iterlim=40)) 160s + } 160s + #' 160s + if(FULLTEST) { 160s + set.seed(452) 160s + foo <- ppm(Cells ~ 1, Strauss(0.15), improve.type="ho", nsim=5) 160s + aa <- Everything(foo) 160s + 160s + #' Gradient and Hessian obtained by symbolic differentiation 160s + f <- deriv(expression((1+x)^a), 160s + "a", function.arg=c("x", "y", "a"), 160s + hessian=TRUE) 160s + #' check they can be extracted 160s + fit <- ippm(Cells ~offset(f), start=list(a=0.7)) 160s + Everything(fit) 160s + } 160s + }) 160s Running non-sparse algorithm... 168s Reduce maximum block side to 50,000 ... 169s Compare single-block to multi-block... 170s Compare sparse and non-sparse results... 170s zero cif... 173s Logistic fits... 173s Other code blocks... 177s Irregular parameters... 177s Offset model... 177s a 178s b 178s c 179s d 180s Offset model (logistic) ... 180s a 181s b 181s c 182s d 183s Offset+x model... 183s a 183s b 184s c 185s d 185s Offset+x model (logistic) ... 186s a 187s b 187s c 188s d 189s Offset model Strauss ... 189s a 189s 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 190s b 190s 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 190s c 190s 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 191s d 191s 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 192s Offset model Strauss (logistic) ... 193s a 193s 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 194s b 194s 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 194s c 195s 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 195s d 195s 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 196s There were 11 warnings (use warnings() to see them) 196s > 196s > reset.spatstat.options() 196s > 196s BEGIN TEST testsM.R 196s 196s R version 4.4.3 (2025-02-28) -- "Trophy Case" 196s Copyright (C) 2025 The R Foundation for Statistical Computing 196s Platform: aarch64-unknown-linux-gnu 196s 196s R is free software and comes with ABSOLUTELY NO WARRANTY. 196s You are welcome to redistribute it under certain conditions. 196s Type 'license()' or 'licence()' for distribution details. 196s 196s R is a collaborative project with many contributors. 196s Type 'contributors()' for more information and 196s 'citation()' on how to cite R or R packages in publications. 196s 196s Type 'demo()' for some demos, 'help()' for on-line help, or 196s 'help.start()' for an HTML browser interface to help. 196s Type 'q()' to quit R. 196s 196s > #' 196s > #' Header for all (concatenated) test files 196s > #' 196s > #' Require spatstat.model 196s > #' Obtain environment variable controlling tests. 196s > #' 196s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 196s > 196s > require(spatstat.model) 196s Loading required package: spatstat.model 196s Loading required package: spatstat.data 197s Loading required package: spatstat.univar 197s spatstat.univar 3.1-2 197s Loading required package: spatstat.geom 197s spatstat.geom 3.3-6 197s Loading required package: spatstat.random 197s spatstat.random 3.3-3 197s Loading required package: spatstat.explore 197s Loading required package: nlme 197s spatstat.explore 3.3-4 197s Loading required package: rpart 198s spatstat.model 3.3-4 198s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 198s > ALWAYS <- TRUE 198s > cat(paste("--------- Executing", 198s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 198s + "test code -----------\n")) 198s --------- Executing **RESTRICTED** subset of test code ----------- 198s > ## 198s > ## tests/marcelino.R 198s > ## 198s > ## $Revision: 1.4 $ $Date: 2020/04/30 02:18:23 $ 198s > ## 198s > 198s > local({ 198s + if(FULLTEST) { 198s + Y <- split(urkiola) 198s + B <- Y$birch 198s + O <- Y$oak 198s + B.lam <- predict (ppm(B ~polynom(x,y,2)), type="trend") 198s + O.lam <- predict (ppm(O ~polynom(x,y,2)), type="trend") 198s + 198s + Kinhom(B, lambda=B.lam, correction="iso") 198s + Kinhom(B, lambda=B.lam, correction="border") 198s + 198s + Kcross.inhom(urkiola, i="birch", j="oak", B.lam, O.lam) 198s + Kcross.inhom(urkiola, i="birch", j="oak", B.lam, O.lam, correction = "iso") 198s + Kcross.inhom(urkiola, i="birch", j="oak", B.lam, O.lam, correction = "border") 198s + } 198s + }) 198s > 198s > 198s > #' tests/mctests.R 198s > #' Monte Carlo tests 198s > #' (mad.test, dclf.test, envelopeTest, hasenvelope) 198s > #' $Revision: 1.5 $ $Date: 2022/05/23 04:09:49 $ 198s > 198s > 198s > local({ 198s + if(FULLTEST) { 198s + fitx <- ppm(redwood~x) 198s + ax <- envelopeTest(fitx, exponent=2, nsim=9, savefuns=TRUE) 198s + print(ax) 198s + } 198s + }) 198s > 198s > 198s > # 198s > # tests/mppm.R 198s > # 198s > # Basic tests of mppm 198s > # 198s > # $Revision: 1.23 $ $Date: 2022/07/08 04:55:13 $ 198s > # 198s > 198s > if(!FULLTEST) 198s + spatstat.options(npixel=32, ndummy.min=16) 198s > 198s > local({ 198s + ## test interaction formulae and subfits 198s + fit1 <- mppm(Points ~ group, simba, 198s + hyperframe(po=Poisson(), str=Strauss(0.1)), 198s + iformula=~ifelse(group=="control", po, str)) 198s + fit2 <- mppm(Points ~ group, simba, 198s + hyperframe(po=Poisson(), str=Strauss(0.1)), 198s + iformula=~str/id) 198s + fit2w <- mppm(Points ~ group, simba, 198s + hyperframe(po=Poisson(), str=Strauss(0.1)), 198s + iformula=~str/id, weights=runif(nrow(simba))) 198s + # currently invalid 198s + # fit3 <- mppm(Points ~ group, simba, 198s + # hyperframe(po=Poisson(), pie=PairPiece(c(0.05,0.1))), 198s + # iformula=~I((group=="control") * po) + I((group=="treatment") * pie)) 198s + 198s + fit1 198s + fit2 198s + fit2w 198s + # fit3 198s + 198s + if(FULLTEST) { 198s + ## run summary.mppm which currently sits in spatstat-internal.Rd 198s + summary(fit1) 198s + summary(fit2) 198s + summary(fit2w) 198s + # summary(fit3) 198s + } 198s + 198s + ## test vcov algorithm 198s + vcov(fit1) 198s + vcov(fit2) 198s + # vcov(fit3) 198s + 198s + if(FULLTEST) { 198s + fit4 <- mppm(Points ~ group, simba, hyperframe(str=Strauss(0.1)), iformula=~str/group) 198s + fit4 198s + summary(fit4) 198s + vcov(fit4) 198s + fit0 <- mppm(Points ~ group, simba) 198s + anova(fit0, fit4, test="Chi") 198s + ## [bug from Fernando Milesi] 198s + fit5 <- mppm(Wat ~ id, 198s + data=hyperframe(Wat=waterstriders), 198s + interaction=StraussHard(4.5, 1.5), 198s + iformula=~Interaction:id) 198s + fit5 198s + summary(fit5) 198s + vcov(fit5) 198s + } 198s + 198s + ## test subfits algorithm 198s + if(FULLTEST) { 198s + s1 <- subfits(fit1) 198s + s2 <- subfits(fit2) 198s + # s3 <- subfits(fit3) 198s + s4 <- subfits(fit4) 198s + s5 <- subfits(fit5) 198s + 198s + ## validity of results of subfits() 198s + p1 <- solapply(s1, predict) 198s + p2 <- solapply(s2, predict) 198s + # p3 <- solapply(s3, predict) 198s + p4 <- solapply(s4, predict) 198s + p5 <- solapply(s5, predict) 198s + } 198s + }) 200s > 200s > local({ 200s + if(FULLTEST) { 200s + ## cases of predict.mppm 200s + W <- solapply(waterstriders, Window) 200s + Fakes <- solapply(W, runifpoint, n=30) 200s + FakeDist <- solapply(Fakes, distfun) 200s + H <- hyperframe(Bugs=waterstriders, 200s + D=FakeDist) 200s + fit <- mppm(Bugs ~ D, data=H) 200s + p1 <- predict(fit) 200s + p2 <- predict(fit, locations=Fakes) 200s + p3 <- predict(fit, locations=solapply(W, erosion, r=4)) 200s + locn <- as.data.frame(do.call(cbind, lapply(Fakes, coords))) 200s + df <- data.frame(id=sample(1:3, nrow(locn), replace=TRUE), 200s + D=runif(nrow(locn))) 200s + p4 <- predict(fit, locations=locn, newdata=df) 200s + 200s + fitG <- mppm(Bugs ~ D, data=H, use.gam=TRUE) 200s + p1G <- predict(fitG) 200s + p2G <- predict(fitG, locations=Fakes) 200s + p3G <- predict(fitG, locations=solapply(W, erosion, r=4)) 200s + p4G <- predict(fitG, locations=locn, newdata=df) 200s + } 200s + }) 200s > 200s > local({ 200s + ## [thanks to Sven Wagner] 200s + ## factor covariate, with some levels unused in some rows 200s + if(FULLTEST) { 200s + set.seed(14921788) 200s + H <- hyperframe(X=replicate(3, runifpoint(20), simplify=FALSE), 200s + Z=solist(as.im(function(x,y){x}, owin()), 200s + as.im(function(x,y){y}, owin()), 200s + as.im(function(x,y){x+y}, owin()))) 200s + H$Z <- solapply(H$Z, cut, breaks=(0:4)/2) 200s + 200s + fit6 <- mppm(X ~ Z, H) 200s + v6 <- vcov(fit6) 200s + s6 <- subfits(fit6) 200s + p6 <- solapply(s6, predict) 200s + 200s + ## random effects 200s + fit7 <- mppm(X ~ Z, H, random=~1|id) 200s + v7 <- vcov(fit7) 200s + s7 <- subfits(fit7) 200s + p7 <- solapply(s7, predict) 200s + 200s + fit7a <- mppm(X ~ Z, H, random=~x|id) 200s + v7a <- vcov(fit7a) 200s + s7a <- subfits(fit7a) 200s + p7a <- solapply(s7a, predict) 200s + 200s + ## multitype: collisions in vcov.ppm, predict.ppm 200s + H$X <- lapply(H$X, rlabel, labels=factor(c("a","b")), permute=FALSE) 200s + M <- MultiStrauss(matrix(0.1, 2, 2), c("a","b")) 200s + fit8 <- mppm(X ~ Z, H, M) 200s + v8 <- vcov(fit8, fine=TRUE) 200s + s8 <- subfits(fit8) 200s + p8 <- lapply(s8, predict) 200s + c8 <- lapply(s8, predict, type="cif") 200s + 200s + fit9 <- mppm(X ~ Z, H, M, iformula=~Interaction * id) 200s + v9 <- vcov(fit9, fine=TRUE) 200s + s9 <- subfits(fit9) 200s + p9 <- lapply(s9, predict) 200s + c9 <- lapply(s9, predict, type="cif") 200s + 200s + ## and a simple error in recognising 'marks' 200s + fit10 <- mppm(X ~ marks, H) 200s + } 200s + }) 200s > 200s > local({ 200s + if(FULLTEST) { 200s + ## test handling of offsets and zero cif values in mppm 200s + H <- hyperframe(Y = waterstriders) 200s + (fit1 <- mppm(Y ~ 1, data=H, Hardcore(1.5))) 200s + (fit2 <- mppm(Y ~ 1, data=H, StraussHard(7, 1.5))) 200s + (fit3 <- mppm(Y ~ 1, data=H, Hybrid(S=Strauss(7), H=Hardcore(1.5)))) 200s + s1 <- subfits(fit1) 200s + s2 <- subfits(fit2) 200s + s3 <- subfits(fit3) 200s + 200s + ## prediction, in training/testing context 200s + ## (example from Markus Herrmann and Ege Rubak) 200s + X <- waterstriders 200s + dist <- solapply(waterstriders, 200s + function(z) distfun(runifpoint(1, Window(z)))) 200s + i <- 3 200s + train <- hyperframe(pattern = X[-i], dist = dist[-i]) 200s + test <- hyperframe(pattern = X[i], dist = dist[i]) 200s + fit <- mppm(pattern ~ dist, data = train) 200s + pred <- predict(fit, type="cif", newdata=test, verbose=TRUE) 200s + 200s + ## examples from Robert Aue 200s + GH <- Hybrid(G=Geyer(r=0.1, sat=3), H=Hardcore(0.01)) 200s + res <- mppm(Points ~ 1, interaction = GH, data=demohyper) 200s + print(summary(res)) 200s + sub <- subfits(res, verbose=TRUE) 200s + print(sub) 200s + } 200s + }) 200s > 200s > local({ 200s + if(FULLTEST) { 200s + ## test handling of interaction coefficients in multitype case 200s + set.seed(42) 200s + XX <- as.solist(replicate(3, rthin(amacrine, 0.8), simplify=FALSE)) 200s + H <- hyperframe(X=XX) 200s + M <- MultiStrauss(matrix(0.1, 2, 2), levels(marks(amacrine))) 200s + fit <- mppm(X ~ 1, H, M) 200s + co <- coef(fit) 200s + subco <- sapply(subfits(fit), coef) 200s + if(max(abs(subco - co)) > 0.001) 200s + stop("Wrong coefficient values in subfits, for multitype interaction") 200s + } 200s + }) 200s > 200s > local({ 200s + if(FULLTEST) { 200s + ## test lurking.mppm 200s + ## example from 'mppm' 200s + n <- 7 200s + H <- hyperframe(V=1:n, 200s + U=runif(n, min=-1, max=1)) 200s + H$Z <- setcov(square(1)) 200s + H$U <- with(H, as.im(U, as.rectangle(Z))) 200s + H$Y <- with(H, rpoispp(eval.im(exp(2+3*Z)))) 200s + fit <- mppm(Y ~ Z + U + V, data=H) 200s + 200s + lurking(fit, expression(Z), type="P") 200s + lurking(fit, expression(V), type="raw") # design covariate 200s + lurking(fit, expression(U), type="raw") # image, constant in each row 200s + lurking(fit, H$Z, type="P") # list of images 200s + } 200s + }) 200s > 200s > local({ 200s + if(FULLTEST) { 200s + ## test anova.mppm code blocks and scoping problem 200s + H <- hyperframe(X=waterstriders) 200s + mod0 <- mppm(X~1, data=H, Poisson()) 200s + modxy <- mppm(X~x+y, data=H, Poisson()) 200s + mod0S <- mppm(X~1, data=H, Strauss(2)) 200s + modxyS <- mppm(X~x+y, data=H, Strauss(2)) 200s + anova(mod0, modxy, test="Chi") 200s + anova(mod0S, modxyS, test="Chi") 200s + anova(modxy, test="Chi") 200s + anova(modxyS, test="Chi") 200s + #' models with random effects (example from Marcelino de la Cruz) 200s + mod0r <- mppm(X~1, data=H, Poisson(), random = ~1|id) 200s + modxr <- mppm(X~x, data=H, Poisson(), random = ~1|id) 200s + anova(mod0r, modxr, test="Chi") 200s + } 200s + }) 200s > 200s > local({ 200s + if(FULLTEST) { 200s + ## test multitype stuff 200s + foo <- flu[1:3,] 200s + msh <- MultiStraussHard(iradii=matrix(100, 2, 2), 200s + hradii=matrix(10,2,2), 200s + types=levels(marks(foo$pattern[[1]]))) 200s + msh0 <- MultiStraussHard(iradii=matrix(100, 2, 2), 200s + hradii=matrix(10,2,2)) 200s + fit <- mppm(pattern ~ 1, data=foo, interaction=msh0) 200s + print(fit) 200s + print(summary(fit)) 200s + v <- vcov(fit) 200s + } 200s + }) 200s > 200s > reset.spatstat.options() 200s > #' 200s > #' tests/msr.R 200s > #' 200s > #' $Revision: 1.5 $ $Date: 2020/11/30 07:27:44 $ 200s > #' 200s > #' Tests of code for measures 200s > #' 200s > 200s > if(FULLTEST) { 200s + local({ 200s + 200s + ## cases of 'msr' 200s + Q <- quadscheme(cells) 200s + nQ <- n.quad(Q) 200s + nX <- npoints(cells) 200s + A <- matrix(nX * 3, nX, 3) 200s + B <- matrix(nQ * 3, nQ, 3) 200s + 200s + m <- msr(Q, A, B) 200s + 200s + M <- msr(Q, A, 1) 200s + M <- msr(Q, 1, B) 200s + M <- msr(Q, A, B[,1]) 200s + M <- msr(Q, A[,1], B) 200s + M <- msr(Q, A, B[,1,drop=FALSE]) 200s + M <- msr(Q, A[,1,drop=FALSE], B) 200s + 200s + ## methods 200s + a <- summary(m) 200s + b <- is.marked(m) 200s + w <- as.owin(m) 200s + z <- domain(m) 200s + ss <- scalardilate(m, 2) 200s + tt <- rescale(m, 2) 200s + ee <- rotate(m, pi/4) 200s + aa <- affine(m, mat=diag(c(1,2)), vec=c(0,1)) 200s + ff <- flipxy(m) 200s + 200s + am <- augment.msr(m, sigma=0.08) 200s + ua <- update(am) 200s + 200s + rr <- residuals(ppm(cells ~ x)) 200s + mm <- residuals(ppm(amacrine ~ x)) 200s + ss <- residuals(ppm(amacrine ~ x), type="score") 200s + gg <- rescale(ss, 1/662, c("micron", "microns")) 200s + 200s + plot(mm) 200s + plot(mm, multiplot=FALSE) 200s + plot(mm, equal.markscale=TRUE, equal.ribbon=TRUE) 200s + plot(ss) 200s + plot(ss, multiplot=FALSE) 200s + }) 200s + } 200s > 200s BEGIN TEST testsNtoO.R 200s 200s R version 4.4.3 (2025-02-28) -- "Trophy Case" 200s Copyright (C) 2025 The R Foundation for Statistical Computing 200s Platform: aarch64-unknown-linux-gnu 200s 200s R is free software and comes with ABSOLUTELY NO WARRANTY. 200s You are welcome to redistribute it under certain conditions. 200s Type 'license()' or 'licence()' for distribution details. 200s 200s R is a collaborative project with many contributors. 200s Type 'contributors()' for more information and 200s 'citation()' on how to cite R or R packages in publications. 200s 200s Type 'demo()' for some demos, 'help()' for on-line help, or 200s 'help.start()' for an HTML browser interface to help. 200s Type 'q()' to quit R. 200s 200s > #' 200s > #' Header for all (concatenated) test files 200s > #' 200s > #' Require spatstat.model 200s > #' Obtain environment variable controlling tests. 200s > #' 200s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 200s > 200s > require(spatstat.model) 200s Loading required package: spatstat.model 200s Loading required package: spatstat.data 201s Loading required package: spatstat.univar 201s spatstat.univar 3.1-2 201s Loading required package: spatstat.geom 201s spatstat.geom 3.3-6 201s Loading required package: spatstat.random 201s spatstat.random 3.3-3 201s Loading required package: spatstat.explore 201s Loading required package: nlme 201s spatstat.explore 3.3-4 201s Loading required package: rpart 201s spatstat.model 3.3-4 201s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 201s > ALWAYS <- TRUE 201s > cat(paste("--------- Executing", 201s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 201s + "test code -----------\n")) 201s --------- Executing **RESTRICTED** subset of test code ----------- 201s > # 201s > # tests/NAinCov.R 201s > # 201s > # Testing the response to the presence of NA's in covariates 201s > # 201s > # $Revision: 1.10 $ $Date: 2024/09/30 23:13:54 $ 201s > 201s > if(FULLTEST) { 201s + local({ 201s + X <- runifpoint(42) 201s + Y <- as.im(function(x,y) { x+y }, owin()) 201s + Y[owin(c(0.2,0.4),c(0.2,0.4))] <- NA 201s + ## ..... ppm ...................................... 201s + ## fit model: should produce a warning but no failure 201s + misfit <- ppm(X ~ Y) 201s + ## prediction 201s + Z <- predict(misfit, type="trend", se=TRUE) 201s + ## canonical covariates 201s + M <- model.images(misfit) 201s + ## covariance matrix: all should be silent 201s + v <- vcov(misfit) 201s + ss <- vcov(misfit, what="internals") 201s + ## ..... kppm ...................................... 201s + ## should produce warnings but no failures 201s + misfit <- kppm(X ~Y) 201s + V <- predict(misfit, type="trend", se=TRUE) 201s + M <- model.images(misfit) 201s + refit <- improve.kppm(misfit, dimyx=20) 201s + }) 201s + } 201s > 201s BEGIN TEST testsP1.R 202s 202s R version 4.4.3 (2025-02-28) -- "Trophy Case" 202s Copyright (C) 2025 The R Foundation for Statistical Computing 202s Platform: aarch64-unknown-linux-gnu 202s 202s R is free software and comes with ABSOLUTELY NO WARRANTY. 202s You are welcome to redistribute it under certain conditions. 202s Type 'license()' or 'licence()' for distribution details. 202s 202s R is a collaborative project with many contributors. 202s Type 'contributors()' for more information and 202s 'citation()' on how to cite R or R packages in publications. 202s 202s Type 'demo()' for some demos, 'help()' for on-line help, or 202s 'help.start()' for an HTML browser interface to help. 202s Type 'q()' to quit R. 202s 202s > #' 202s > #' Header for all (concatenated) test files 202s > #' 202s > #' Require spatstat.model 202s > #' Obtain environment variable controlling tests. 202s > #' 202s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 202s > 202s > require(spatstat.model) 202s Loading required package: spatstat.model 202s Loading required package: spatstat.data 203s Loading required package: spatstat.univar 203s spatstat.univar 3.1-2 203s Loading required package: spatstat.geom 203s spatstat.geom 3.3-6 203s Loading required package: spatstat.random 203s spatstat.random 3.3-3 203s Loading required package: spatstat.explore 203s Loading required package: nlme 203s spatstat.explore 3.3-4 203s Loading required package: rpart 203s spatstat.model 3.3-4 203s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 203s > ALWAYS <- TRUE 203s > cat(paste("--------- Executing", 203s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 203s + "test code -----------\n")) 203s --------- Executing **RESTRICTED** subset of test code ----------- 203s > ## 203s > ## tests/percy.R 203s > ## 203s > ## Tests of Percus-Yevick approximations 203s > ## 203s > ## $Revision: 1.3 $ $Date: 2020/04/30 05:23:52 $ 203s > 203s > if(FULLTEST) { 203s + local({ 203s + fit <- ppm(swedishpines ~1, DiggleGatesStibbard(6)) 203s + K <- Kmodel(fit) 203s + }) 203s + } 203s > 203s > ## 203s > ## tests/pixelgripes.R 203s > ## Problems related to pixellation of windows 203s > ## 203s > ## $Revision: 1.8 $ $Date: 2022/10/23 06:21:10 $ 203s > 203s > if(FULLTEST) { 203s + local({ 203s + 203s + ## From Philipp Hunziker: bug in rNeymanScott (etc) 203s + ## Create an irregular window 203s + PM <- matrix(c(1,0,0.5,1,0,0), 3, 2, byrow=TRUE) 203s + P <- owin(poly=PM) 203s + ## Generate Matern points 203s + X <- rMatClust(50, 0.05, 5, win=P) 203s + ## Some distance function as a covariate 203s + distorigin <- function(x, y) { sqrt(x^2 + y^2) } 203s + ## No covariates: works fine 203s + fit0 <- kppm(X ~ 1, clusters="MatClust") 203s + Y0 <- simulate(fit0, retry=0) 203s + ## Covariates: Simulation fails 203s + fit1 <- kppm(X ~ distorigin, clusters="MatClust") 203s + Y1 <- simulate(fit1, retry=0) 203s + 203s + }) 203s + } 203s > 203s BEGIN TEST testsP2.R 203s 203s R version 4.4.3 (2025-02-28) -- "Trophy Case" 203s Copyright (C) 2025 The R Foundation for Statistical Computing 203s Platform: aarch64-unknown-linux-gnu 203s 203s R is free software and comes with ABSOLUTELY NO WARRANTY. 203s You are welcome to redistribute it under certain conditions. 203s Type 'license()' or 'licence()' for distribution details. 203s 203s R is a collaborative project with many contributors. 203s Type 'contributors()' for more information and 203s 'citation()' on how to cite R or R packages in publications. 203s 203s Type 'demo()' for some demos, 'help()' for on-line help, or 203s 'help.start()' for an HTML browser interface to help. 203s Type 'q()' to quit R. 203s 203s > #' 203s > #' Header for all (concatenated) test files 203s > #' 203s > Loading required package: spatstat.model 203s #' Require spatstat.model 203s > #' Obtain environment variable controlling tests. 203s > #' 203s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 203s > 203s > require(spatstat.model) 203s Loading required package: spatstat.data 204s Loading required package: spatstat.univar 204s spatstat.univar 3.1-2 204s Loading required package: spatstat.geom 204s spatstat.geom 3.3-6 204s Loading required package: spatstat.random 204s spatstat.random 3.3-3 204s Loading required package: spatstat.explore 204s Loading required package: nlme 204s spatstat.explore 3.3-4 204s Loading required package: rpart 204s spatstat.model 3.3-4 204s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 204s > ALWAYS <- TRUE 204s > cat(paste("--------- Executing", 204s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 204s + "test code -----------\n")) 204s --------- Executing **RESTRICTED** subset of test code ----------- 204s > # 204s > # tests/ppmBadData.R 204s > # 204s > # $Revision: 1.6 $ $Date: 2020/04/30 05:23:52 $ 204s > 204s > # Testing robustness of ppm and support functions 204s > # when data are rubbish 204s > 204s > local({ 204s + if(ALWAYS) { 204s + ## from Rolf: very large proportion of data is NA 204s + SEED <- 42 204s + K <- 101 204s + A <- 500 204s + X <- seq(0, A, length=K) 204s + G <- expand.grid(x=X, y=X) 204s + FOO <- function(x,y) { sin(x)^2 + cos(y)^2 } 204s + M1 <- im(matrix(FOO(G$x, G$y), K, K), xcol=X, yrow=X) 204s + M <- im(matrix(FOO(G$x, G$y), K, K)) 204s + BAR <- function(x) { exp(-6.618913 + 5.855337 * x - 8.432483 * x^2) } 204s + V <- im(BAR(M$v), xcol=X, yrow=X) 204s + # V <- eval.im(exp(-6.618913 + 5.855337 * M - 8.432483 * M^2)) 204s + set.seed(SEED) 204s + Y <- rpoispp(V) 204s + fY <- ppm(Y ~cv + I(cv^2), data=list(cv=M), correction="translate") 204s + diagnose.ppm(fY) 204s + lurking(fY, covariate=as.im(function(x,y){x}, square(A)), type="raw") 204s + } 204s + 204s + if(ALWAYS) { 204s + ## from Andrew Bevan: numerical overflow, ill-conditioned Fisher information 204s + SEED <- 42 204s + 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))) 204s + ## Trend on raster grid 204s + rain <- as.im(X=function(x,y) { x^2 + y^2 }, W=nongranite, dimyx=100) 204s + ## Generate a point pattern via a Lennard-Jones process 204s + set.seed(SEED) 204s + mod4<- rmhmodel(cif="lennard", 204s + par=list(beta=1, sigma=250, epsilon=2.2), 204s + trend=rain, w=nongranite) 204s + ljtr<- rmh(mod4, start=list(n.start=80), control=list(p=1, nrep=1e5)) 204s + 204s + ## Fit a point process model to the pattern with rain as a covariate 204s + ## NOTE INCORRECT TREND FORMULA 204s + ljtrmod <- ppm(ljtr, trend= ~ Z, interaction=NULL, data=list(Z=rain)) 204s + ss <- summary(ljtrmod) 204s + } 204s + 204s + if(FULLTEST) { 204s + ## From Ege 204s + ## Degenerate but non-null argument 'covariates' 204s + xx <- list() 204s + names(xx) <- character(0) 204s + fit <- ppm(cells ~x, covariates = xx) 204s + st <- summary(fit) 204s + } 204s + 204s + }) 205s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 205s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 205s > 205s > 205s > 205s > Error in solve.default(M) : 205s system is computationally singular: reciprocal condition number = 5.72254e-18 205s In addition: Warning messages: 205s 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, 205s 2: Some infinite, NA or NaN increments were removed 205s 3: Numerical underflow detected: sigma is probably too small 205s 4: Some infinite, NA or NaN increments were removed 205s Error in solve.default(M) : 205s system is computationally singular: reciprocal condition number = 5.72254e-18 205s In addition: Warning message: 205s Cannot compute variance: Fisher information matrix is singular 205s Warning message: 205s Cannot compute variance: Fisher information matrix is singular 205s #' tests/ppmclass.R 205s > #' 205s > #' Class support for ppm 205s > #' 205s > #' $Revision: 1.9 $ $Date: 2022/03/07 03:26:09 $ 205s > 205s > if(FULLTEST) { 205s + local({ 205s + #' (1) print.ppm, summary.ppm, print.summary.ppm 205s + Z <- as.im(function(x,y){x}, Window(cells)) 205s + fitZ <- ppm(cells ~ Z) 205s + print(fitZ) 205s + print(summary(fitZ)) 205s + #' logistic 205s + fitl <- ppm(swedishpines ~ x+y, method="logi") 205s + print(fitl) 205s + print(summary(fitl)) 205s + #' Model with covariate arguments 205s + f <- function(x,y,b) { x+b } 205s + fitf <- ppm(cells ~ f, covfunargs=list(b=1)) 205s + print(fitf) 205s + print(summary(fitf)) 205s + #' Invalid model 205s + fitN <- ppm(redwood ~ 1, Strauss(0.1)) 205s + print(fitN) 205s + print(summary(fitN)) 205s + #' standard errors in output 205s + fat <- ppm(cells ~ x, Strauss(0.12)) 205s + op <- spatstat.options(print.ppm.SE='always') 205s + print(fat) 205s + spatstat.options(print.ppm.SE='never') 205s + print(fat) 205s + print(fitZ) 205s + spatstat.options(op) 205s + 205s + ## (2) plot.ppm 205s + plot(fitZ) 205s + plot(fat, trend=FALSE, cif=FALSE, se=FALSE) 205s + 205s + ## (3) emend.ppm 205s + fitZe <- emend(fitZ, trace=TRUE) 205s + ZZ <- Z 205s + fitZZ <- ppm(cells ~ Z + ZZ) 205s + fitZZe <- emend(fitZZ, trace=TRUE) 205s + fitOK <- ppm(redwood ~1, Strauss(0.1), emend=TRUE) 205s + print(fitOK) 205s + fitNot <- ppm(redwood ~1, Strauss(0.1)) 205s + fitSlow <- emend(fitNot, trace=TRUE) 205s + print(fitSlow) 205s + op <- spatstat.options(project.fast=TRUE) 205s + fitFast <- emend(fitNot, trace=TRUE) 205s + print(fitFast) 205s + fitZZe <- emend(fitZZ, trace=TRUE) 205s + spatstat.options(op) 205s + 205s + #' (4) methods for other generics 205s + logLik(fitZ, absolute=TRUE) 205s + unitname(fitZ) 205s + unitname(fat) <- c("metre", "metres") 205s + is.expandable(fitf) 205s + fit0 <- update(fitZ, . ~ 1) 205s + anova(fit0, fitZ, override=TRUE) 205s + interactionfamilyname(fat) 205s + interactionorder(fat) 205s + hardcoredist(fat) 205s + 205s + #' (5) miscellaneous 205s + 205s + ## example from Robert Aue - handling offsets 205s + X <- demohyper$Points[[1]] 205s + GH <- Hybrid(G=Geyer(r=0.1, sat=3), H=Hardcore(0.01)) 205s + fit <- ppm(X ~ 1, GH) 205s + valid.ppm(fit) 205s + 205s + #' hard core distance of hybrid 205s + hardcoredist(fit) 205s + #' interaction order of hybrid 205s + interactionorder(fit) 205s + 205s + #' case of boundingbox 205s + boundingbox(cells, ppm(cells ~ 1)) 205s + }) 205s + 205s + reset.spatstat.options() 205s + } 205s > # 205s > # tests/ppmgam.R 205s > # 205s > # Test ppm with use.gam=TRUE 205s > # 205s > # $Revision: 1.4 $ $Date: 2020/04/30 05:23:52 $ 205s > # 205s > 205s > if(FULLTEST) { 205s + local({ 205s + fit <- ppm(nztrees ~s(x,y), use.gam=TRUE) 205s + mm <- model.matrix(fit) 205s + mf <- model.frame(fit) 205s + v <- vcov(fit) 205s + prd <- predict(fit) 205s + }) 205s + } 205s > #' 205s > #' tests/ppmlogi.R 205s > #' 205s > #' Tests of ppm(method='logi') 205s > #' and related code (predict, leverage etc) 205s > #' 205s > #' $Revision: 1.15 $ $Date: 2020/04/30 05:23:52 $ 205s > #' 205s > 205s > local({ 205s + if(FULLTEST) { 205s + fit <- ppm(cells ~x, method="logi") 205s + f <- fitted(fit) 205s + p <- predict(fit) 205s + u <- summary(fit) 205s + fitS <- ppm(cells ~x, Strauss(0.12), method="logi") 205s + fS <- fitted(fitS) 205s + pS <- predict(fitS) 205s + uS <- summary(fitS) 205s + print(uS) 205s + 205s + plot(leverage(fit)) 205s + plot(influence(fit)) 205s + plot(dfbetas(fit)) 205s + plot(leverage(fitS)) 205s + plot(influence(fitS)) 205s + plot(dfbetas(fitS)) 205s + } 205s + 205s + if(FULLTEST) { 205s + #' same with hard core - A1 is singular 205s + fitH <- ppm(cells ~x, Strauss(0.08), method="logi") 205s + print(fitH) 205s + fH <- fitted(fitH) 205s + pH <- predict(fitH) 205s + uH <- summary(fitH) 205s + print(uH) 205s + plot(leverage(fitH)) 205s + plot(influence(fitH)) 205s + plot(dfbetas(fitH)) 205s + } 205s + 205s + if(FULLTEST) { 205s + #' logistic fit to data frame of covariates 205s + z <- c(rep(TRUE, 5), rep(FALSE, 5)) 205s + df <- data.frame(A=z + 2* runif(10), 205s + B=runif(10)) 205s + Y <- quadscheme.logi(runifpoint(5), runifpoint(5)) 205s + fut <- ppm(Y ~ A+B, data=df, method="logi") 205s + sf <- summary(fut) 205s + print(sf) 205s + } 205s + 205s + if(FULLTEST) { 205s + #' vblogit code, just to check that it runs. 205s + fee <- ppm(cells ~ x, method="VBlogi", nd=21) 205s + print(fee) 205s + summary(fee) 205s + logLik(fee) 205s + AIC(fee) 205s + extractAIC(fee) 205s + Z <- predict(fee) 205s + summary(Z) 205s + print(fee$internal$glmfit) # print.vblogit 205s + } 205s + }) 205s > 205s > # 205s > # tests/ppmmarkorder.R 205s > # 205s > # $Revision: 1.4 $ $Date: 2020/04/30 05:23:52 $ 205s > # 205s > # Test that predict.ppm, plot.ppm and plot.fitin 205s > # tolerate marks with levels that are not in alpha order 205s > # 205s > if(ALWAYS) { # locale-dependent? 205s + local({ 205s + X <- amacrine 205s + levels(marks(X)) <- c("ZZZ", "AAA") 205s + fit <- ppm(X ~marks, MultiStrauss(c("ZZZ","AAA"), matrix(0.06, 2, 2))) 205s + aa <- predict(fit, type="trend") 205s + bb <- predict(fit, type="cif") 205s + plot(fit) 205s + plot(fitin(fit)) 205s + }) 205s + } 207s > 207s > 207s > # 207s > # tests/ppmscope.R 207s > # 207s > # Test things that might corrupt the internal format of ppm objects 207s > # 207s > # $Revision: 1.7 $ $Date: 2022/01/19 09:18:20 $ 207s > # 207s > 207s > if(ALWAYS) { # dependent on R version? 207s + local({ 207s + 207s + ## (1) Scoping problem that can arise when ppm splits the data 207s + fit <- ppm(bei ~elev, data=bei.extra) 207s + mm <- model.matrix(fit) 207s + 207s + ## (2) Fast update mechanism 207s + fit1 <- ppm(cells ~x+y, Strauss(0.07)) 207s + fit2 <- update(fit1, ~y) 207s + fit3 <- update(fit2, ~x) 207s + 207s + ## (3) New formula-based syntax 207s + attach(bei.extra) 207s + slfit <- ppm(bei ~ grad) 207s + sl2fit <- update(slfit, ~grad + I(grad^2)) 207s + slfitup <- update(slfit, use.internal=TRUE) 207s + sl2fitup <- update(sl2fit, use.internal=TRUE) 207s + 207s + ## (4) anova.ppm 207s + fut1 <- ppm(cells ~ 1, Strauss(0.1)) 207s + futx <- ppm(cells ~ x, Strauss(0.1)) 207s + anova(fut1, test="Chi") 207s + anova(futx, test="Chi") 207s + fut1a <- ppm(cells ~ 1, Strauss(0.1), rbord=0) 207s + anova(fut1a, futx, test="Chi") 207s + fut1d <- ppm(cells ~ 1, Strauss(0.1), nd=23) 207s + anova(fut1d, futx, test="Chi") 207s + ## This now works! 207s + futxyg <- ppm(cells ~ x + s(y), Strauss(0.1), use.gam=TRUE) 207s + anova(futx, futxyg) 207s + ## marked 207s + fatP <- ppm(amacrine ~ marks) 207s + fatM <- ppm(amacrine ~ marks, MultiStrauss(matrix(0.07, 2, 2))) 207s + anova(fatP, fatM, test="Chi") 207s + 207s + ## (5) expansion of "." in update.ppm 207s + fitb <- ppm(bei ~ . , data=bei.extra) 207s + step(fitb) 207s + }) 207s + } 210s Start: AIC=42295.11 210s ~elev + grad 210s 210s Warning messages: 210s 1: anova.ppm now computes the *adjusted* deviances when the models are not Poisson processes. 210s 2: Models were re-fitted using a common value of 'rbord' 210s 3: Models were re-fitted using a common quadrature scheme 210s 4: Models were re-fitted with use.gam=TRUE 210s 5: Deviance adjustment is not available for gam fits; unadjusted composite deviance calculated. 210s 6: Models were re-fitted using a common value of 'rbord' 210s Df AIC 210s 42295 210s - elev 1 42383 210s - grad 1 42760 210s Nonstationary Poisson process 210s Fitted to point pattern dataset ‘bei’ 210s 210s Log intensity: ~elev + grad 210s 210s Fitted trend coefficients: 210s (Intercept) elev grad 210s -8.56355220 0.02143995 5.84646680 210s 210s Estimate S.E. CI95.lo CI95.hi Ztest Zval 210s (Intercept) -8.56355220 0.341113849 -9.23212306 -7.89498134 *** -25.104675 210s elev 0.02143995 0.002287866 0.01695581 0.02592408 *** 9.371155 210s grad 5.84646680 0.255781018 5.34514522 6.34778838 *** 22.857313 210s > grep# 210s function (pattern, x, ignore.case = FALSE, perl = FALSE, value = FALSE, 210s fixed = FALSE, useBytes = FALSE, invert = FALSE) 210s { 210s pattern <- as.character(pattern) 210s if (is.factor(x) && length(levx <- levels(x)) < length(x) && 210s !is.na(pattern[1L])) { 210s value <- is.character(idxna <- suppressWarnings(grep(pattern, 210s NA_character_, ignore.case, perl, value, fixed, useBytes, 210s invert))) 210s idx <- logical(length(levx)) 210s idx[grep(pattern, levx, ignore.case, perl, FALSE, fixed, 210s useBytes, invert)] <- TRUE 210s idx <- idx[x] 210s if (length(idxna)) 210s idx[is.na(x)] <- TRUE 210s idx <- which(idx) 210s if (value) { 210s idx <- x[idx] 210s structure(as.character(idx), names = names(idx)) 210s } 210s else idx 210s } 210s else { 210s if (!is.character(x)) 210s x <- structure(as.character(x), names = names(x)) 210s .Internal(grep(pattern, x, ignore.case, value, perl, 210s fixed, useBytes, invert)) 210s } 210s } 210s 210s 210s > # tests/ppmtricks.R 210s > # 210s > # Test backdoor exits, hidden options, internals and tricks in ppm 210s > # 210s > # $Revision: 1.19 $ $Date: 2020/04/30 05:23:52 $ 210s > # 210s > local({ 210s + 210s + ## (1) skip.border 210s + if(ALWAYS) { # needed below 210s + fit <- ppm(cells, ~1, Strauss(0.1), skip.border=TRUE) 210s + } 210s + 210s + ## (2) subset arguments of different kinds 210s + if(FULLTEST) { 210s + fut <- ppm(cells ~ x, subset=(x > 0.5)) 210s + fot <- ppm(cells ~ x, subset=(x > 0.5), method="logi") 210s + W <- owin(c(0.4, 0.8), c(0.2, 0.7)) 210s + fut <- ppm(cells ~ x, subset=W) 210s + fot <- ppm(cells ~ x, subset=W, method="logi") 210s + V <- as.im(inside.owin, Window(cells), w=W) 210s + fet <- ppm(cells ~ x, subset=V) 210s + fet <- ppm(cells ~ x, subset=V, method="logi") 210s + } 210s + 210s + ## (3) profilepl -> ppm 210s + ## uses 'skip.border' and 'precomputed' 210s + ## also tests scoping for covariates 210s + if(FULLTEST) { 210s + splants <- split(ants) 210s + mess <- splants[["Messor"]] 210s + cats <- splants[["Cataglyphis"]] 210s + ss <- data.frame(r=seq(60,120,by=20),hc=29/6) 210s + dM <- distmap(mess,dimyx=256) 210s + mungf <- profilepl(ss, StraussHard, cats ~ dM) 210s + mungp <- profilepl(ss, StraussHard, trend=~dM, Q=cats) 210s + } 210s + 210s + ## (4) splitting large quadschemes into blocks 210s + if(FULLTEST) { 210s + mop <- spatstat.options(maxmatrix=5000) 210s + qr <- quadBlockSizes(quadscheme(cells)) 210s + pr <- predict(ppm(cells ~ x, AreaInter(0.05))) 210s + spatstat.options(mop) 210s + qr <- quadBlockSizes(quadscheme(cells)) 210s + } 210s + 210s + ## (5) shortcuts in summary.ppm 210s + ## and corresponding behaviour of print.summary.ppm 210s + if(FULLTEST) { 210s + print(summary(fit, quick=TRUE)) 210s + print(summary(fit, quick="entries")) 210s + print(summary(fit, quick="no prediction")) 210s + print(summary(fit, quick="no variances")) 210s + } 210s + 210s + ## (6) suffstat.R 210s + if(ALWAYS) { 210s + fitP <- update(fit, Poisson()) 210s + suffstat.poisson(fitP, cells) 210s + fit0 <- killinteraction(fit) 210s + suffstat.poisson(fit0, cells) 210s + } 210s + 210s + ## (7) various support for class ppm 210s + if(FULLTEST) { 210s + fut <- kppm(redwood ~ x) 210s + A <- quad.ppm(fut) 210s + Z <- as.im(function(x,y){x}, Window(cells)) 210s + fitZ <- ppm(cells ~ Z) 210s + U <- getppmOriginalCovariates(fitZ) 210s + } 210s + 210s + ## (8) support for class profilepl 210s + if(FULLTEST) { 210s + rr <- data.frame(r=seq(0.05, 0.15, by=0.02)) 210s + ps <- profilepl(rr, Strauss, cells) 210s + ## plot(ps) ## covered in plot.profilepl.Rd 210s + simulate(ps, nrep=1e4) 210s + parameters(ps) 210s + fitin(ps) 210s + predict(ps, type="cif") 210s + } 210s + 210s + ## (9) class 'plotppm' 210s + if(FULLTEST) { 210s + fut <- ppm(amacrine ~ marks + polynom(x,y,2), Strauss(0.07)) 210s + p <- plot(fut, plot.it=FALSE) 210s + print(p) 210s + plot(p, how="contour") 210s + plot(p, how="persp") 210s + } 210s + 210s + ## (10) ppm -> mpl.engine -> mpl.prepare 210s + if(ALWAYS) { # includes C code 210s + fit <- ppm(cells, NULL) 210s + fit <- ppm(cells ~ x, clipwin=square(0.7)) 210s + fit <- ppm(cells ~ x, subset=square(0.7)) 210s + DG <- as.im(function(x,y){x+y < 1}, square(1)) 210s + fit <- ppm(cells ~ x, subset=DG) 210s + fit <- ppm(cells ~ x, GLM=glm) 210s + fit <- ppm(cells ~ x, famille=quasi(link='log', variance='mu')) 210s + fit <- ppm(cells ~ x, Hardcore(0.07), skip.border=TRUE, splitInf=TRUE) 210s + } 210s + 210s + ## (11) unidentifiable model (triggers an error in ppm) 210s + if(FULLTEST) { 210s + Q <- quadscheme(cells) 210s + M <- mpl.prepare(Q, cells, as.ppp(Q), trend=~1, covariates=NULL, 210s + interaction=Hardcore(0.3), correction="none") 210s + } 210s + }) 210s > 210s > reset.spatstat.options() 210s > # 210s > # tests/prediction.R 210s > # 210s > # Things that might go wrong with predict() 210s > # 210s > # $Revision: 1.23 $ $Date: 2024/04/13 03:37:42 $ 210s > # 210s > 210s > local({ 210s + if(ALWAYS) { 210s + ## test of 'covfunargs' - platform dependent? 210s + f <- function(x,y,a){ y - a } 210s + fit <- ppm(cells ~x + f, covariates=list(f=f), covfunargs=list(a=1/2)) 210s + p <- predict(fit) 210s + 210s + ## prediction involving 0 * NA 210s + qc <- quadscheme(cells, nd=10) 210s + r <- minnndist(as.ppp(qc))/10 210s + fit <- ppm(qc ~ 1, Strauss(r)) # model has NA for interaction coefficient 210s + p1 <- predict(fit) 210s + p2 <- predict(fit, type="cif", ngrid=10) 210s + stopifnot(all(is.finite(as.matrix(p1)))) 210s + stopifnot(all(is.finite(as.matrix(p2)))) 210s + } 210s + 210s + if(FULLTEST) { 210s + ## test of 'new.coef' mechanism 210s + fut <- ppm(cells ~ x, Strauss(0.15), rbord=0) 210s + p0 <- predict(fut, type="cif") 210s + pe <- predict(fut, type="cif", new.coef=coef(fut)) 210s + pn <- predict(fut, type="cif", new.coef=unname(coef(fut))) 210s + if(max(abs(pe-p0)) > 0.01) 210s + stop("new.coef mechanism is broken!") 210s + if(max(abs(pn-p0)) > 0.01) 210s + stop("new.coef mechanism gives wrong answer, for unnamed vectors") 210s + #' adaptcoef 210s + a <- c(A=1,B=2,Z=42) 210s + b <- c(B=41,A=0) 210s + ab <- adaptcoef(a, b, drop=TRUE) 210s + #' check that grid parameters 'dimyx' and 'eps' are respected 210s + pyx <- predict(fut, type="cif", dimyx=7) 210s + if(all(dim(pyx) == dim(p0))) 210s + stop("predict.ppm ignores argument dimyx") 210s + peps <- predict(fut, type="cif", eps=0.14) 210s + if(all(dim(peps) == dim(p0))) 210s + stop("predict.ppm ignores argument eps") 210s + } 210s + 210s + if(FULLTEST) { 210s + ## tests of relrisk.ppm 210s + fut <- ppm(amacrine ~ x * marks) 210s + a <- relrisk(fut, control=2, relative=TRUE) 210s + a <- relrisk(fut, se=TRUE) 210s + a <- relrisk(fut, relative=TRUE, se=TRUE) 210s + fut <- ppm(sporophores ~ marks + x) 210s + a <- relrisk(fut, control=2, relative=TRUE) 210s + a <- relrisk(fut, se=TRUE) 210s + a <- relrisk(fut, relative=TRUE, se=TRUE) 210s + 210s + ## untested cases of predict.ppm 210s + fit0 <- ppm(cells) 210s + a <- predict(fit0, interval="confidence") 210s + a <- predict(fit0, interval="confidence", type="count") 210s + fit <- ppm(cells ~ x) 210s + b <- predict(fit, se=TRUE, locations=cells) 210s + b <- predict(fit, se=TRUE, interval="confidence") 210s + b <- predict(fit, type="count", se=TRUE) 210s + b <- predict(fit, type="count", window=square(0.5), se=TRUE) 210s + b <- predict(fit, type="count", window=quadrats(cells, 3), se=TRUE) 210s + d <- predict(fit, type="count", interval="prediction", se=TRUE) 210s + d <- predict(fit, type="count", interval="confidence", se=TRUE) 210s + d <- predict(fit, interval="confidence", se=TRUE) 210s + foot <- ppm(cells ~ x, StraussHard(0.12)) 210s + d <- predict(foot, ignore.hardcore=TRUE) 210s + dX <- predict(foot, ignore.hardcore=TRUE, locations=cells) 210s + 210s + ## superseded usages 210s + b <- predict(fit, type="se", getoutofjail=TRUE) 210s + b <- predict(fit, type="se", locations=cells) # warning 210s + b <- predict(fit, total=TRUE) 210s + b <- predict(fit, total=square(0.5)) 210s + b <- predict(fit, total=quadrats(cells, 3)) 210s + 210s + ## supporting code 210s + u <- model.se.image(fit, square(0.5)) 210s + u <- model.se.image(fit, square(0.5), what="cv") 210s + u <- model.se.image(fit, square(0.5), what="ce") 210s + co <- c(Intercept=5, slope=3, kink=2) 210s + re <- c("Intercept", "slope") 210s + a <- fill.coefs(co, re) # warning 210s + b <- fill.coefs(co, rev(names(co))) 210s + d <- fill.coefs(co, letters[1:3]) 210s + ## model matrix etc 210s + v <- model.frame(ppm(cells)) 210s + fut <- ppm(cells ~ x, Strauss(0.1)) 210s + v <- model.matrix(fut, subset=(x<0.5), keepNA=FALSE) 210s + df <- data.frame(x=runif(10), y=runif(10), 210s + Interaction=sample(0:1, 10, TRUE)) 210s + m10 <- PPMmodelmatrix(fut, data=df) 210s + mmm <- PPMmodelmatrix(fut, Q=quad.ppm(fut)) 210s + #' effectfun for Gibbs 210s + effectfun(fut, "x") 210s + effectfun(fut, "x", se.fit=TRUE) 210s + #' implicit covariate when there is only one 210s + effectfun(fut) 210s + effectfun(fut, se.fit=TRUE) 210s + #' given covariate 210s + dlin <- distfun(copper$SouthLines) 210s + copfit <- ppm(copper$SouthPoints ~ dlin, Geyer(1,1)) 210s + effectfun(copfit, "dlin") 210s + effectfun(copfit) 210s + #' covariate that is not used in model 210s + effectfun(fut, "y", x=0) 210s + futS <- ppm(cells ~ 1, Strauss(0.1)) 210s + effectfun(futS, "x") 210s + effectfun(futS, "y") 210s + #' factor covariate 210s + fot <- ppm(amacrine~x+marks) 210s + effectfun(fot, "marks", x=0.5, se.fit=TRUE) 210s + #' covariate retained but not used 210s + W <- Window(swedishpines) 210s + a <- solist(A=funxy(function(x,y){x < 20}, W), 210s + B=funxy(function(x,y){factor(x < 20)}, W)) 210s + fvt <- ppm(swedishpines ~ A, data=a, allcovar=TRUE) 210s + effectfun(fvt, "A", se.fit=TRUE) 210s + effectfun(fvt, "B", A=TRUE, se.fit=TRUE) 210s + 210s + ## ppm with covariate values in data frame 210s + X <- rpoispp(42) 210s + Q <- quadscheme(X) 210s + weirdfunction <- function(x,y){ 10 * x^2 + 5 * sin(10 * y) } 210s + Zvalues <- weirdfunction(x.quad(Q), y.quad(Q)) 210s + fot <- ppm(Q ~ y + Z, data=data.frame(Z=Zvalues)) 210s + effectfun(fot, "y", Z=0) 210s + effectfun(fot, "Z", y=0) 210s + 210s + #' multitype 210s + modX <- ppm(amacrine ~ polynom(x,2)) 210s + effectfun(modX) 210s + effectfun(modX, "x") 210s + modXM <- ppm(amacrine ~ marks*polynom(x,2)) 210s + effectfun(modXM, "x", marks="on") 210s + modXYM <- ppm(amacrine ~ marks*polynom(x,y,2)) 210s + effectfun(modXYM, "x", y=0, marks="on") 210s + 210s + df <- as.data.frame(simulate(modXM, drop=TRUE)) 210s + df$marks <- as.character(df$marks) 210s + dfpr <- predict(modXM, locations=df) 210s + } 210s + }) 210s > 210s > # 210s > # tests/project.ppm.R 210s > # 210s > # $Revision: 1.7 $ $Date: 2020/04/30 05:41:59 $ 210s > # 210s > # Tests of projection mechanism 210s > # 210s > 210s > local({ 210s + chk <- function(m) { 210s + if(!valid.ppm(m)) stop("Projected model was still not valid") 210s + return(invisible(NULL)) 210s + } 210s + 210s + if(FULLTEST) { 210s + ## a very unidentifiable model 210s + fit <- ppm(cells ~Z, Strauss(1e-06), covariates=list(Z=0)) 210s + chk(emend(fit)) 210s + ## multitype 210s + r <- matrix(1e-06, 2, 2) 210s + fit2 <- ppm(amacrine ~1, MultiStrauss(types=c("off", "on"), radii=r)) 210s + chk(emend(fit2)) 210s + ## complicated multitype 210s + fit3 <- ppm(amacrine ~1, MultiStraussHard(types=c("off", "on"), 210s + iradii=r, hradii=r/5)) 210s + chk(emend(fit3)) 210s + 210s + #' code coverage 210s + op <- spatstat.options(project.fast=TRUE) 210s + fut <- emend(fit, trace=TRUE) 210s + chk(fut) 210s + spatstat.options(op) 210s + 210s + #' hierarchical 210s + ra <- r 210s + r[2,1] <- NA 210s + fit4 <- ppm(amacrine ~1, HierStrauss(types=c("off", "on"), radii=r)) 210s + chk(emend(fit4)) 210s + #' complicated hierarchical 210s + fit5 <- ppm(amacrine ~1, HierStraussHard(types=c("off", "on"), 210s + iradii=r, hradii=r/5)) 210s + chk(emend(fit5)) 210s + 210s + ## hybrids 210s + r0 <- min(nndist(redwood)) 210s + ra <- 1.25 * r0 210s + rb <- 0.8 * r0 210s + f1 <- ppm(redwood ~1, Hybrid(A=Strauss(ra), B=Geyer(0.1, 2)), project=TRUE) 210s + chk(f1) 210s + f2 <- ppm(redwood ~1, Hybrid(A=Strauss(rb), B=Geyer(0.1, 2)), project=TRUE) 210s + chk(f2) 210s + f3 <- ppm(redwood ~1, Hybrid(A=Strauss(ra), B=Strauss(0.1)), project=TRUE) 210s + chk(f3) 210s + f4 <- ppm(redwood ~1, Hybrid(A=Strauss(rb), B=Strauss(0.1)), project=TRUE) 210s + chk(f4) 210s + f5 <- ppm(redwood ~1, Hybrid(A=Hardcore(rb), B=Strauss(0.1)), project=TRUE) 210s + chk(f5) 210s + f6 <- ppm(redwood ~1, Hybrid(A=Hardcore(rb), B=Geyer(0.1, 2)), project=TRUE) 210s + chk(f6) 210s + f7 <- ppm(redwood ~1, Hybrid(A=Geyer(rb, 1), B=Strauss(0.1)), project=TRUE) 210s + chk(f7) 210s + } 210s + }) 210s > 210s > reset.spatstat.options() 210s > 210s BEGIN TEST testsQ.R 210s 210s R version 4.4.3 (2025-02-28) -- "Trophy Case" 210s Copyright (C) 2025 The R Foundation for Statistical Computing 210s Platform: aarch64-unknown-linux-gnu 210s 210s R is free software and comes with ABSOLUTELY NO WARRANTY. 210s You are welcome to redistribute it under certain conditions. 210s Type 'license()' or 'licence()' for distribution details. 210s 210s R is a collaborative project with many contributors. 210s Type 'contributors()' for more information and 210s 'citation()' on how to cite R or R packages in publications. 210s 210s Type 'demo()' for some demos, 'help()' for on-line help, or 210s 'help.start()' for an HTML browser interface to help. 210s Type 'q()' to quit R. 210s 210s > #' 210s > #' Header for all (concatenated) test files 210s > #' 210s > #' Require spatstat.model 210s > #' Obtain environment variable controlling tests. 210s > #' 210s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 210s > 210s > require(spatstat.model) 210s Loading required package: spatstat.model 210s Loading required package: spatstat.data 211s Loading required package: spatstat.univar 211s spatstat.univar 3.1-2 211s Loading required package: spatstat.geom 211s spatstat.geom 3.3-6 211s Loading required package: spatstat.random 211s spatstat.random 3.3-3 211s Loading required package: spatstat.explore 211s Loading required package: nlme 211s spatstat.explore 3.3-4 211s Loading required package: rpart 211s spatstat.model 3.3-4 211s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 211s > ALWAYS <- TRUE 211s > cat(paste("--------- Executing", 211s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 211s + "test code -----------\n")) 211s --------- Executing **RESTRICTED** subset of test code ----------- 211s > 211s BEGIN TEST testsR1.R 211s 211s R version 4.4.3 (2025-02-28) -- "Trophy Case" 211s Copyright (C) 2025 The R Foundation for Statistical Computing 211s Platform: aarch64-unknown-linux-gnu 211s 211s R is free software and comes with ABSOLUTELY NO WARRANTY. 211s You are welcome to redistribute it under certain conditions. 211s Type 'license()' or 'licence()' for distribution details. 211s 211s R is a collaborative project with many contributors. 211s Type 'contributors()' for more information and 211s 'citation()' on how to cite R or R packages in publications. 211s 211s Type 'demo()' for some demos, 'help()' for on-line help, or 211s 'help.start()' for an HTML browser interface to help. 211s Type 'q()' to quit R. 211s 211s > #' 211s > #' Header for all (concatenated) test files 211s > #' 211s > #' Require spatstat.model 211s > #' Obtain environment variable controlling tests. 211s > #' 211s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 211s > 211s > require(spatstat.model) 211s Loading required package: spatstat.model 211s Loading required package: spatstat.data 212s Loading required package: spatstat.univar 212s spatstat.univar 3.1-2 212s Loading required package: spatstat.geom 213s spatstat.geom 3.3-6 213s Loading required package: spatstat.random 213s spatstat.random 3.3-3 213s Loading required package: spatstat.explore 213s Loading required package: nlme 213s spatstat.explore 3.3-4 213s Loading required package: rpart 213s spatstat.model 3.3-4 213s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 213s > ALWAYS <- TRUE 213s > cat(paste("--------- Executing", 213s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 213s + "test code -----------\n")) 213s --------- Executing **RESTRICTED** subset of test code ----------- 213s > #' tests/resid.R 213s > #' 213s > #' Stuff related to residuals and residual diagnostics 213s > #' including residual summary functions 213s > #' 213s > #' $Revision: 1.7 $ $Date: 2022/05/22 08:43:31 $ 213s > #' 213s > 213s > local({ 213s + fit <- ppm(cells ~x, Strauss(r=0.15)) 213s + rr <- residuals(fit, quad=quadscheme(cells, nd=128)) 213s + diagnose.ppm(fit, cumulative=FALSE, type="pearson") 213s + 213s + if(FULLTEST) { 213s + diagnose.ppm(fit, cumulative=FALSE) 213s + 213s + fitoff <- ppm(cells ~ sin(x) + offset(y)) 213s + plot(a <- parres(fitoff, "x")) 213s + plot(b <- parres(fitoff, "y")) 213s + print(a) 213s + print(b) 213s + 213s + d <- diagnose.ppm(fit, which="marks") 213s + plot(d, plot.neg="discrete") 213s + plot(d, plot.neg="imagecontour") 213s + 213s + d <- diagnose.ppm(fit, type="pearson", which="smooth") 213s + plot(d, plot.smooth="image") 213s + plot(d, plot.smooth="contour") 213s + plot(d, plot.smooth="imagecontour") 213s + 213s + d <- diagnose.ppm(fit, type="pearson", which="x") 213s + plot(d) 213s + d <- diagnose.ppm(fit, type="pearson", which="y") 213s + plot(d) 213s + 213s + diagnose.ppm(fit, type="pearson", which="x", cumulative=FALSE) 213s + diagnose.ppm(fit, type="pearson", which="x", cumulative=FALSE) 213s + diagnose.ppm(fit, type="raw", plot.neg="discrete", plot.smooth="image") 213s + diagnose.ppm(fit, type="pearson", plot.neg="contour", plot.smooth="contour") 213s + 213s + diagnose.ppm(fitoff, type="raw", which="smooth", plot.smooth="persp") 213s + diagnose.ppm(fitoff, type="pearson", plot.neg="imagecontour") 213s + 213s + plot(Frame(letterR), main="") 213s + ploterodewin(letterR, erosion(letterR, 0.05), main="jeans") 213s + W <- as.mask(letterR) 213s + plot(Frame(W), main="") 213s + ploterodewin(W, erosion(W, 0.05), main="JeAnS") 213s + 213s + #' entangled terms in model 213s + U <- as.im(1, owin()) 213s + Z <- as.im(function(x,y) x, owin()) 213s + X <- runifpoint(40) 213s + fut <- ppm(X ~ Z:U) 213s + a <- parres(fut, "Z") 213s + futoff <- ppm(X ~ offset(Z*U)) 213s + a <- parres(futoff, "Z") 213s + 213s + #' residual summary functions 213s + pt <- psst(cells, interaction=Strauss(0.1), fun=nndcumfun) 213s + } 213s + }) 213s > 213s > 213s > 213s > ## 213s > ## tests/rhohat.R 213s > ## 213s > ## Test all combinations of options for rhohatCalc 213s > ## 213s > ## $Revision: 1.6 $ $Date: 2022/05/22 08:03:48 $ 213s > 213s > local({ 213s + if(FULLTEST) { 213s + X <- rpoispp(function(x,y){exp(3+3*x)}) 213s + Z <- as.im(function(x,y) { x }, Window(X)) 213s + f <- funxy(function(x,y) { y + 1 }, Window(X)) 213s + 213s + 213s + ## rhohat.ppm 213s + fit <- ppm(X ~x) 213s + rhofitA <- rhohat(fit, "x") 213s + rhofitB <- rhohat(fit, "x", method="reweight") 213s + rhofitC <- rhohat(fit, "x", method="transform") 213s + rhofitD <- rhohat(fit, Z) 213s + rhofitD <- rhohat(fit, Z, positiveCI=TRUE) 213s + lam <- predict(fit) 213s + 213s + 213s + ## Horvitz-Thompson 213s + rhofitAH <- rhohat(fit, "x", horvitz=TRUE) 213s + rhofitBH <- rhohat(fit, "x", method="reweight", horvitz=TRUE) 213s + rhofitCH <- rhohat(fit, "x", method="transform", horvitz=TRUE) 213s + 213s + r2myx <- rho2hat(fit, "y", "x") 213s + r2myxw <- rho2hat(fit, "y", "x", method="reweight") 213s + plot(r2myx) 213s + plot(r2myxw) 213s + print(r2myxw) 213s + predict(r2myxw) 213s + predict(r2myxw, relative=TRUE) 213s + } 213s + }) 213s > 213s BEGIN TEST testsR2.R 213s 213s R version 4.4.3 (2025-02-28) -- "Trophy Case" 213s Copyright (C) 2025 The R Foundation for Statistical Computing 213s Platform: aarch64-unknown-linux-gnu 213s 213s R is free software and comes with ABSOLUTELY NO WARRANTY. 213s You are welcome to redistribute it under certain conditions. 213s Type 'license()' or 'licence()' for distribution details. 213s 213s R is a collaborative project with many contributors. 213s Type 'contributors()' for more information and 213s 'citation()' on how to cite R or R packages in publications. 213s 213s Type 'demo()' for some demos, 'help()' for on-line help, or 213s 'help.start()' for an HTML browser interface to help. 213s Type 'q()' to quit R. 213s 213s > #' 213s > #' Header for all (concatenated) test files 213s > #' 213s > #' Require spatstat.model 213s > #' Obtain environment variable controlling tests. 213s > #' 214s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 214s > 214s > require(spatstat.model) 214s Loading required package: spatstat.model 214s Loading required package: spatstat.data 215s Loading required package: spatstat.univar 215s spatstat.univar 3.1-2 215s Loading required package: spatstat.geom 215s spatstat.geom 3.3-6 215s Loading required package: spatstat.random 215s spatstat.random 3.3-3 215s Loading required package: spatstat.explore 215s Loading required package: nlme 215s spatstat.explore 3.3-4 215s Loading required package: rpart 215s spatstat.model 3.3-4 215s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 215s > ALWAYS <- TRUE 215s > cat(paste("--------- Executing", 215s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 215s + "test code -----------\n")) 215s --------- Executing **RESTRICTED** subset of test code ----------- 215s > # 215s > # tests/rmhExpand.R 215s > # 215s > # test decisions about expansion of simulation window 215s > # 215s > # $Revision: 1.9 $ $Date: 2022/10/23 01:17:33 $ 215s > # 215s > 215s > local({ 215s + if(FULLTEST) { 215s + ## check expansion in rmhmodel.ppm 215s + fit <- ppm(cells ~x) 215s + mod <- rmhmodel(fit) 215s + is.expandable(mod) 215s + wsim <- as.rectangle(mod$trend) 215s + ## work around changes in 'unitname' 215s + wcel <- as.owin(cells) 215s + unitname(wcel) <- unitname(cells) 215s + ## test 215s + if(!identical(wsim, wcel)) 215s + stop("Expansion occurred improperly in rmhmodel.ppm") 215s + } 215s + }) 215s > 215s > 215s > 215s > # 215s > # tests/rmhTrend.R 215s > # 215s > # Problems with trend images (rmhmodel.ppm or rmhEngine) 215s > # 215s > 215s > if(ALWAYS) { 215s + local({ 215s + set.seed(42) 215s + 215s + # Bug folder 37 of 8 feb 2011 215s + # rmhmodel.ppm -> predict.ppm 215s + # + rmhResolveTypes -> is.subset.owin 215s + 215s + Z <- rescale(demopat, 7000) 215s + X <- unmark(Z) 215s + X1 <- split(Z)[[1]] 215s + Int <- density(X,dimyx=200) 215s + Lint <- eval.im(log(npoints(X1)*Int/npoints(X))) 215s + M <- as.owin(Int) 215s + MR <- intersect.owin(M,scalardilate(M,0.5,origin="midpoint")) 215s + X1 <- X1[MR] 215s + Fut <- ppm(X1~offset(Lint),covariates=list(Lint=Lint), 215s + inter=BadGey(r=c(0.03,0.05),sat=3)) 215s + Y <- rmh(Fut,control=list(expand=M,nrep=1e3), verbose=FALSE) 215s + 215s + }) 215s + } 215s > # 215s > # tests/rmhmodel.ppm.R 215s > # 215s > # $Revision: 1.10 $ $Date: 2020/05/01 05:29:42 $ 215s > # 215s > # Case-by-case tests of rmhmodel.ppm 215s > # 215s > 215s > if(FULLTEST) { 215s + local({ 215s + f <- ppm(cells) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~x) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~1, Strauss(0.1)) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~1, StraussHard(r=0.1,hc=0.05)) 215s + m <- rmhmodel(f) 215s + print(m) 215s + 215s + f <- ppm(cells ~1, Hardcore(0.07)) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~1, DiggleGratton(0.05,0.1)) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~1, Softcore(0.5), correction="isotropic") 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~1, Geyer(0.07,2)) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~1, BadGey(c(0.07,0.1,0.13),2)) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~1, PairPiece(r = c(0.05, 0.1, 0.2))) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~1, AreaInter(r=0.06)) 215s + m <- rmhmodel(f) 215s + print(m) 215s + 215s + # multitype 215s + 215s + r <- matrix(0.07, 2, 2) 215s + f <- ppm(amacrine ~1, MultiStrauss(c("off","on"),r)) 215s + m <- rmhmodel(f) 215s + print(m) 215s + 215s + h <- matrix(min(nndist(amacrine))/2, 2, 2) 215s + f <- ppm(amacrine ~1, MultiStraussHard(c("off","on"),r, h)) 215s + m <- rmhmodel(f) 215s + 215s + diag(r) <- NA 215s + diag(h) <- NA 215s + f <- ppm(amacrine ~1, MultiStrauss(c("off","on"),r)) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(amacrine ~1, MultiStraussHard(c("off","on"),r, h)) 215s + m <- rmhmodel(f) 215s + 215s + # multitype data, interaction not dependent on type 215s + 215s + f <- ppm(amacrine ~marks, Strauss(0.05)) 215s + m <- rmhmodel(f) 215s + print(m) 215s + 215s + # trends 215s + 215s + f <- ppm(cells ~x, Strauss(0.1)) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~y, StraussHard(r=0.1,hc=0.05)) 215s + m <- rmhmodel(f) 215s + 215s + f <- ppm(cells ~x+y, Hardcore(0.07)) 215s + m <- rmhmodel(f) 215s + print(m) 215s + 215s + f <- ppm(cells ~polynom(x,y,2), Softcore(0.5), correction="isotropic") 215s + m <- rmhmodel(f) 215s + 215s + # covariates 215s + 215s + Z <- as.im(function(x,y){ x^2+y^2 }, as.owin(cells)) 215s + f <- ppm(cells ~z, covariates=list(z=Z)) 215s + m <- rmhmodel(f) 215s + m <- rmhmodel(f, control=list(p=1)) 215s + print(m) 215s + 215s + Zim <- as.im(Z, as.owin(cells)) 215s + f <- ppm(cells ~z, covariates=list(z=Zim)) 215s + m <- rmhmodel(f) 215s + 215s + Z <- as.im(function(x,y){ x^2+y }, as.owin(amacrine)) 215s + f <- ppm(amacrine ~z + marks, covariates=list(z=Z)) 215s + m <- rmhmodel(f) 215s + print(m) 215s + m <- rmhmodel(f, control=list(p=1)) 215s + m <- rmhmodel(f, control=list(p=1,fixall=TRUE)) 215s + print(m) 215s + 215s + Zim <- as.im(Z, as.owin(amacrine)) 215s + f <- ppm(amacrine ~z + marks, covariates=list(z=Zim)) 215s + m <- rmhmodel(f) 215s + print(m) 215s + 215s + }) 215s + } 215s > # 215s > # tests/rmhmodelHybrids.R 215s > # 215s > # Test that rmhmodel.ppm and rmhmodel.default 215s > # work on Hybrid interaction models 215s > # 215s > # $Revision: 1.6 $ $Date: 2022/10/23 01:17:56 $ 215s > # 215s > 215s > if(ALWAYS) { # involves C code 215s + local({ 215s + 215s + ## ......... rmhmodel.ppm ....................... 215s + fit1 <- ppm(redwood ~1, 215s + Hybrid(A=Strauss(0.02), B=Geyer(0.1, 2), C=Geyer(0.15, 1))) 215s + m1 <- rmhmodel(fit1) 215s + m1 215s + reach(m1) 215s + 215s + ## Test of handling 'IsOffset' 215s + fit2 <- ppm(cells ~1, Hybrid(H=Hardcore(0.05), G=Geyer(0.15, 2))) 215s + m2 <- rmhmodel(fit2) 215s + ## also test C code for hybrid interaction with hard core 215s + fakecells <- rmh(fit2, nrep=1e4) 215s + 215s + ## Test of handling Poisson components 215s + fit3 <- ppm(cells ~1, Hybrid(P=Poisson(), S=Strauss(0.05))) 215s + X3 <- rmh(fit3, control=list(nrep=1e3,expand=1), verbose=FALSE) 215s + 215s + 215s + }) 215s + } 215s Extracting model information...Evaluating trend...done. 215s Extracting model information...Evaluating trend...done. 215s Extracting model information...Evaluating trend...done. 215s Checking arguments..determining simulation windows...Starting simulation. 215s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 215s > 215s > # 215s > # tests/rmh.ppm.R 215s > # 215s > # $Revision: 1.5 $ $Date: 2020/05/01 05:29:42 $ 215s > # 215s > # Examples removed from rmh.ppm.Rd 215s > # stripped down to minimal tests of validity 215s > # 215s > 215s > local({ 215s + op <- spatstat.options() 215s + spatstat.options(rmh.nrep=10, npixel=10, ndummy.min=10) 215s + spatstat.options(project.fast=TRUE) 215s + Nrep <- 10 215s + 215s + X <- swedishpines 215s + if(FULLTEST) { 215s + ## Poisson process 215s + fit <- ppm(X ~1, Poisson()) 215s + Xsim <- rmh(fit) 215s + } 215s + if(ALWAYS) { # Gibbs model => C code 215s + ## Strauss process 215s + fit <- ppm(X ~1, Strauss(r=7)) 215s + Xsim <- rmh(fit) 215s + 215s + ## Strauss process simulated on a larger window 215s + ## then clipped to original window 215s + Xsim <- rmh(fit, control=list(nrep=Nrep, expand=1.1, periodic=TRUE)) 215s + 215s + ## Extension of model to another window (thanks to Tuomas Rajala) 215s + Xsim <- rmh(fit, w=square(2)) 215s + Xsim <- simulate(fit, w=square(2)) 215s + 215s + ## Strauss - hard core process 215s + ## fit <- ppm(X ~1, StraussHard(r=7,hc=2)) 215s + ## Xsim <- rmh(fit, start=list(n.start=X$n)) 215s + 215s + ## Geyer saturation process 215s + ## fit <- ppm(X ~1, Geyer(r=7,sat=2)) 215s + ## Xsim <- rmh(fit, start=list(n.start=X$n)) 215s + 215s + ## Area-interaction process 215s + fit <- ppm(X ~1, AreaInter(r=7)) 215s + Xsim <- rmh(fit, start=list(n.start=X$n)) 215s + 215s + ## Penttinen process 215s + fit <- ppm(X ~1, Penttinen(r=7)) 215s + Xsim <- rmh(fit, start=list(n.start=X$n)) 215s + 215s + ## soft core interaction process 215s + ## X <- quadscheme(X, nd=50) 215s + ## fit <- ppm(X ~1, Softcore(kappa=0.1), correction="isotropic") 215s + ## Xsim <- rmh(fit, start=list(n.start=X$n)) 215s + 215s + ## Diggle-Gratton pairwise interaction model 215s + ## fit <- ppm(cells ~1, DiggleGratton(0.05, 0.1)) 215s + ## Xsim <- rmh(fit, start=list(n.start=cells$n)) 215s + ## plot(Xsim, main="simulation from fitted Diggle-Gratton model") 215s + 215s + 215s + ## piecewise-constant pairwise interaction function 215s + X <- rSSI(0.05, 100) 215s + fit <- ppm(X ~1, PairPiece(seq(0.02, 0.1, by=0.01))) 215s + Xsim <- rmh(fit) 215s + } 215s + 215s + ## marked point pattern 215s + Y <- amacrine 215s + 215s + if(FULLTEST) { 215s + #' marked Poisson models 215s + fit <- ppm(Y) 215s + Ysim <- rmh(fit) 215s + 215s + fit <- ppm(Y~marks) 215s + Ysim <- rmh(fit) 215s + 215s + fit <- ppm(Y~x) 215s + Ysim <- rmh(fit) 215s + 215s + fit <- ppm(Y~marks+x) 215s + Ysim <- rmh(fit) 215s + } 215s + 215s + if(ALWAYS) { 215s + #' multitype Strauss 215s + typ <- levels(Y$marks) 215s + MS <- MultiStrauss(types = typ, 215s + radii=matrix(0.07, ncol=2, nrow=2)) 215s + 215s + fit <- ppm(Y~marks*x, MS) 215s + Ysim <- rmh(fit) 215s + 215s + #' multitype Hardcore 215s + h0 <- minnndist(unmark(Y)) * 0.95 215s + MH <- MultiHard(types = typ, 215s + hradii=matrix(h0, ncol=2, nrow=2)) 215s + fit <- ppm(Y ~ marks+x, MH) 215s + Ysim <- rmh(fit) 215s + #' other code blocks 215s + Ysim <- rmh(fit, control=list(periodic=TRUE, expand=1)) 215s + Ysim <- rmh(fit, control=list(periodic=FALSE, expand=1)) 215s + #' multihard core with invalid initial state 215s + Ydouble <- superimpose(Y, rjitter(Y, h0/10)) 215s + Ysim <- rmh(fit, start=list(x.start=Ydouble)) 215s + 215s + #' Lennard-Jones 215s + fut <- ppm(unmark(longleaf) ~ 1, LennardJones(), rbord=1) 215s + Ysim <- rmh(fut) 215s + Ysim <- rmh(fut, control=list(periodic=TRUE, expand=1)) 215s + } 215s + 215s + spatstat.options(op) 215s + }) 215s Extracting model information...Evaluating trend...done. 215s Checking arguments..determining simulation windows...Starting simulation. 215s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 215s Extracting model information...Evaluating trend...done. 215s Checking arguments..determining simulation windows...Starting simulation. 215s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 215s Extracting model information...Evaluating trend...done. 215s Checking arguments..determining simulation windows...Starting simulation. 215s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 218s Extracting model information...Evaluating trend...done. 218s Checking arguments..determining simulation windows...Starting simulation. 218s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 218s Extracting model information...Evaluating trend...done. 218s Checking arguments..determining simulation windows...Starting simulation. 218s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 218s Model is invalid - projecting it 219s Extracting model information...Evaluating trend...done. 219s Checking arguments..determining simulation windows...Starting simulation. 219s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 219s Extracting model information...Evaluating trend...done. 219s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 219s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 219s Extracting model information...Evaluating trend...done. 219s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 219s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 219s Extracting model information...Evaluating trend...done. 219s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 219s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 219s Extracting model information...Evaluating trend...done. 219s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 219s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 220s Extracting model information...Evaluating trend...done. 220s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 220s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 220s Extracting model information...Evaluating trend...done. 220s Checking arguments..determining simulation windows...Starting simulation. 220s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 220s Extracting model information...Evaluating trend...done. 220s Checking arguments..determining simulation windows...Starting simulation. 220s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 220s > 220s > 220s > reset.spatstat.options() 220s > #' 220s > #' tests/rmhsnoopy.R 220s > #' 220s > #' Test the rmh interactive debugger 220s > #' 220s > #' $Revision: 1.11 $ $Date: 2022/10/23 01:19:00 $ 220s > 220s > if(ALWAYS) { # may depend on platform 220s + local({ 220s + R <- 0.1 220s + ## fit a model and prepare to simulate 220s + model <- ppm(amacrine ~ marks + x, Strauss(R)) 220s + siminfo <- rmh(model, preponly=TRUE) 220s + Wsim <- siminfo$control$internal$w.sim 220s + Wclip <- siminfo$control$internal$w.clip 220s + if(is.null(Wclip)) Wclip <- Window(cells) 220s + 220s + ## determine debugger interface panel geometry 220s + Xinit <- runifpoint(ex=amacrine)[1:40] 220s + P <- rmhsnoop(Wsim=Wsim, Wclip=Wclip, R=R, 220s + xcoords=Xinit$x, 220s + ycoords=Xinit$y, 220s + mlevels=levels(marks(Xinit)), 220s + mcodes=as.integer(marks(Xinit)) - 1L, 220s + irep=3L, itype=1L, 220s + proptype=1, proplocn=c(0.5, 0.5), propmark=0, propindx=0, 220s + numerator=42, denominator=24, 220s + panel.only=TRUE) 220s + boxes <- P$boxes 220s + clicknames <- names(P$clicks) 220s + boxcentres <- do.call(concatxy, lapply(boxes, centroid.owin)) 220s + 220s + ## design a sequence of clicks 220s + actionsequence <- c("Up", "Down", "Left", "Right", 220s + "At Proposal", "Zoom Out", "Zoom In", "Reset", 220s + "Accept", "Reject", "Print Info", 220s + "Next Iteration", "Next Shift", "Next Death", 220s + "Skip 10", "Skip 100", "Skip 1000", "Skip 10,000", 220s + "Skip 100,000", "Exit Debugger") 220s + actionsequence <- match(actionsequence, clicknames) 220s + actionsequence <- actionsequence[!is.na(actionsequence)] 220s + xy <- lapply(boxcentres, "[", actionsequence) 220s + 220s + ## queue the click sequence 220s + spatstat.utils::queueSpatstatLocator(xy$x,xy$y) 220s + 220s + ## go 220s + rmh(model, snoop=TRUE) 220s + }) 220s + } 220s Extracting model information...Evaluating trend...done. 220s Checking arguments..determining simulation windows...Evaluating trend integral...Extracting model information...Evaluating trend...done. 220s Checking arguments..determining simulation windows...Evaluating trend integral...Starting simulation. 220s Initial state... 220s Creating debugger environment..Done. 220s Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 221s 221s 221s ------------------- 221s Iteration 0 221s Simulation window: 221s window: rectangle = [0, 1.6012085] x [0, 1] units (one unit = 662 microns) 221s Clipping window: 221s window: rectangle = [0, 1.6012085] x [0, 1] units (one unit = 662 microns) 221s Current state: 221s Marked planar point pattern: 72 points 221s Multitype, with levels = off, on 221s window: rectangle = [0, 1.6012085] x [0, 1] units (one unit = 662 microns) 221s Proposal type: Shift 221s Shift data point 18 from current location (0.290108, 0.0160037, “off”) to 221s new location (0.620599, 0.378428, “off”) 221s Hastings ratio = 6831.92992943093 / 14545.6615344216 = 0.469688498750194 221s Fate of proposal: Rejected 223s Marked planar point pattern: 350 points 223s Multitype, with levels = off, on 223s window: rectangle = [0, 1.6012085] x [0, 1] units (one unit = 662 microns) 223s Pattern was generated by Metropolis-Hastings simulation. 223s > 223s BEGIN TEST testsS.R 223s 223s R version 4.4.3 (2025-02-28) -- "Trophy Case" 223s Copyright (C) 2025 The R Foundation for Statistical Computing 223s Platform: aarch64-unknown-linux-gnu 223s 223s R is free software and comes with ABSOLUTELY NO WARRANTY. 223s You are welcome to redistribute it under certain conditions. 223s Type 'license()' or 'licence()' for distribution details. 223s 223s R is a collaborative project with many contributors. 223s Type 'contributors()' for more information and 223s 'citation()' on how to cite R or R packages in publications. 223s 223s Type 'demo()' for some demos, 'help()' for on-line help, or 223s 'help.start()' for an HTML browser interface to help. 223s Type 'q()' to quit R. 223s 223s > #' 223s > #' Header for all (concatenated) test files 223s > #' 223s > #' Require spatstat.model 223s > #' Obtain environment variable controlling tests. 223s > #' 223s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 223s > 223s > require(spatstat.model) 223s Loading required package: spatstat.model 223s Loading required package: spatstat.data 224s Loading required package: spatstat.univar 224s spatstat.univar 3.1-2 224s Loading required package: spatstat.geom 224s spatstat.geom 3.3-6 224s Loading required package: spatstat.random 224s spatstat.random 3.3-3 224s Loading required package: spatstat.explore 224s Loading required package: nlme 224s spatstat.explore 3.3-4 224s Loading required package: rpart 224s spatstat.model 3.3-4 224s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 224s > ALWAYS <- TRUE 224s > cat(paste("--------- Executing", 224s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 224s + "test code -----------\n")) 224s --------- Executing **RESTRICTED** subset of test code ----------- 224s > # 224s > # tests/slrm.R 224s > # 224s > # $Revision: 1.3 $ $Date: 2020/05/01 09:59:59 $ 224s > # 224s > # Test slrm fitting and prediction when there are NA's 224s > # 224s > 224s > if(ALWAYS) { 224s + local({ 224s + X <- copper$SouthPoints 224s + W <- owin(poly=list(x=c(0,35,35,1),y=c(1,1,150,150))) 224s + Y <- X[W] 224s + fit <- slrm(Y ~ x+y) 224s + pred <- predict(fit) 224s + extractAIC(fit) 224s + fitx <- update(fit, . ~ x) 224s + simulate(fitx, seed=42) 224s + if(FULLTEST) { 224s + unitname(fitx) 224s + unitname(fitx) <- "km" 224s + 224s + mur <- solapply(murchison,rescale, 1000, "km") 224s + mur$dfault <- distfun(mur$faults) 224s + fut <- slrm(gold ~ dfault, data=mur, splitby="greenstone") 224s + A <- model.images(fut) 224s + } 224s + }) 224s + } 224s > 224s > 224s > # 224s > # tests/step.R 224s > # 224s > # $Revision: 1.5 $ $Date: 2020/05/01 09:59:59 $ 224s > # 224s > # test for step() operation 224s > # 224s > if(FULLTEST) { 224s + local({ 224s + Z <- as.im(function(x,y){ x^3 - y^2 }, nztrees$window) 224s + fitP <- ppm(nztrees ~x+y+Z, covariates=list(Z=Z)) 224s + step(fitP) 224s + fitS <- update(fitP, Strauss(7)) 224s + step(fitS) 224s + fitM <- ppm(amacrine ~ marks*(x+y), 224s + MultiStrauss(types=levels(marks(amacrine)), radii=matrix(0.04, 2, 2))) 224s + step(fitM) 224s + }) 224s + } 224s > 224s > 224s > 224s > 224s BEGIN TEST testsT.R 224s 224s R version 4.4.3 (2025-02-28) -- "Trophy Case" 224s Copyright (C) 2025 The R Foundation for Statistical Computing 224s Platform: aarch64-unknown-linux-gnu 224s 224s R is free software and comes with ABSOLUTELY NO WARRANTY. 224s You are welcome to redistribute it under certain conditions. 224s Type 'license()' or 'licence()' for distribution details. 224s 224s R is a collaborative project with many contributors. 224s Type 'contributors()' for more information and 224s 'citation()' on how to cite R or R packages in publications. 224s 224s Type 'demo()' for some demos, 'help()' for on-line help, or 224s 'help.start()' for an HTML browser interface to help. 224s Type 'q()' to quit R. 224s 224s > #' 224s > #' Header for all (concatenated) test files 224s > #' 224s > #' Require spatstat.model 224s > #' Obtain environment variable controlling tests. 224s > #' 224s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 224s > 224s > require(spatstat.model) 224s Loading required package: spatstat.model 224s Loading required package: spatstat.data 225s Loading required package: spatstat.univar 225s spatstat.univar 3.1-2 225s Loading required package: spatstat.geom 225s spatstat.geom 3.3-6 225s Loading required package: spatstat.random 225s spatstat.random 3.3-3 225s Loading required package: spatstat.explore 225s Loading required package: nlme 225s spatstat.explore 3.3-4 225s Loading required package: rpart 226s spatstat.model 3.3-4 226s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 226s > ALWAYS <- TRUE 226s > cat(paste("--------- Executing", 226s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 226s + "test code -----------\n")) 226s --------- Executing **RESTRICTED** subset of test code ----------- 226s > # 226s > # tests/testaddvar.R 226s > # 226s > # test addvar options 226s > # 226s > # $Revision: 1.3 $ $Date: 2020/05/02 01:32:58 $ 226s > 226s > if(FULLTEST) { 226s + local({ 226s + X <- rpoispp(function(x,y){exp(3+3*x)}) 226s + model <- ppm(X ~y) 226s + addvar(model, "x", crosscheck=TRUE) 226s + addvar(model, "x", bw.input="quad") 226s + w <- square(0.5) 226s + addvar(model, "x", subregion=w) 226s + addvar(model, "x", subregion=w, bw.input="points") 226s + Z <- as.im(function(x,y) { x }, Window(X)) 226s + addvar(model, Z) 226s + }) 226s + } 226s > # 226s > # tests/testparres.R 226s > # 226s > # additional test of parres 226s > # 226s > # $Revision: 1.8 $ $Date: 2022/05/20 06:59:59 $ 226s > # 226s > 226s > if(FULLTEST) { 226s + local({ 226s + X <- rpoispp(function(x,y){exp(3+x+2*x^2)}) 226s + model <- ppm(X ~x+y) 226s + 226s + # options in parres (and code blocks in print.parres) 226s + parres(model, "x") 226s + parres(model, "x", smooth.effect=TRUE) 226s + parres(model, "x", bw.input="quad") 226s + w <- square(0.5) 226s + parres(model, "x", subregion=w) 226s + parres(model, "x", subregion=w, bw.input="quad") 226s + f <- function(x,y) { x + y } 226s + parres(model, f) 226s + 226s + # check whether 'update.ppm' has messed up internals 226s + mod2 <- update(model, ~x) 226s + parres(mod2, "x") 226s + 226s + #' other kinds of covariates 226s + mod3 <- ppm(X ~ x + offset(y)) 226s + parres(mod3, "offset(y)") 226s + Z <- distmap(runifpoint(3)) 226s + parres(mod3, Z) 226s + mod4 <- ppm(X ~ sin(x), data=solist(B=Z)) 226s + parres(mod4, "sin(x)") 226s + parres(mod4, "B") 226s + 226s + #' models with interaction 226s + mod5 <- ppm(cells ~ x, AreaInter(0.06)) 226s + parres(mod5, "x") 226s + dlin <- distfun(copper$SouthLines) 226s + copfit <- ppm(copper$SouthPoints ~ dlin, Geyer(1,1)) 226s + parres(copfit, "dlin") 226s + 226s + #' covariate need not be specified if there is only one. 226s + parres(mod5) 226s + parres(copfit) 226s + 226s + #' infrastructure 226s + ltuae <- evaluateCovariate(42, cells) 226s + LTUAE <- evaluateCovariate(ltuae, cells) 226s + 226s + fit <- ppm(amacrine ~ x * marks, nd=16) 226s + dmat <- model.depends(fit) 226s + check.separable(dmat, "x", c(x=FALSE, marks=FALSE), FALSE) 226s + check.separable(dmat, "x", c(FALSE, FALSE), FALSE) 226s + check.separable(dmat, "x", c(x=FALSE, marks=TRUE), FALSE) 226s + }) 226s + } 226s > #' 226s > #' tests/threedee.R 226s > #' 226s > #' Tests of 3D code 226s > #' 226s > #' $Revision: 1.8 $ $Date: 2020/05/02 01:32:58 $ 226s > #' 226s > 226s > local({ 226s + X <- runifpoint3(30) 226s + Y <- runifpoint3(20) 226s + if(FULLTEST) { 226s + A <- runifpoint3(10, nsim=2) 226s + Z <- ppsubset(X, 2:4) 226s + } 226s + ## 226s + if(ALWAYS) { # includes C code 226s + d <- pairdist(X, periodic=TRUE, squared=TRUE) 226s + d <- crossdist(X, Y, squared=TRUE) 226s + d <- crossdist(X, Y, squared=TRUE, periodic=TRUE) 226s + #' 226s + h <- has.close(X, 0.2) 226s + h <- has.close(X, 0.2, periodic=TRUE) 226s + h <- has.close(X, 0.2, Y=Y) 226s + h <- has.close(X, 0.2, Y=Y, periodic=TRUE) 226s + #' code blocks not otherwise reached 226s + rmax <- 0.6 * max(nndist(X)) 226s + g <- G3est(X, rmax=rmax, correction="rs") 226s + g <- G3est(X, rmax=rmax, correction="km") 226s + g <- G3est(X, rmax=rmax, correction="Hanisch") 226s + g <- G3est(X, rmax=rmax, sphere="ideal") 226s + g <- G3est(X, rmax=rmax, sphere="digital") 226s + v <- sphere.volume() 226s + v <- digital.volume() 226s + #' older code 226s + co <- coords(X) 226s + xx <- co$x 226s + yy <- co$y 226s + zz <- co$z 226s + gg1 <- g3engine(xx, yy, zz, correction="Hanisch G3") 226s + gg2 <- g3engine(xx, yy, zz, correction="minus sampling") 226s + ff1 <- f3engine(xx, yy, zz, correction="no") 226s + ff2 <- f3engine(xx, yy, zz, correction="minus sampling") 226s + } 226s + ## 226s + if(ALWAYS) { 226s + #'class support 226s + X <- runifpoint3(10) 226s + print(X) 226s + print(X %mark% runif(10)) 226s + print(X %mark% factor(letters[c(1:5,5:1)])) 226s + print(X %mark% data.frame(a=1:10, b=runif(10))) 226s + da <- as.Date(paste0("2020-01-0", c(1:5,5:1))) 226s + print(X %mark% da) 226s + print(X %mark% data.frame(a=1:10, b=da)) 226s + } 226s + }) 226s Three-dimensional point pattern: 10 points 226s Box: [0, 1] x [0, 1] x [0, 1] units 226s Marked three-dimensional point pattern: 10 points 226s marks are numeric, of storage type ‘double’ 226s Box: [0, 1] x [0, 1] x [0, 1] units 226s Marked three-dimensional point pattern: 10 points 226s Multitype, with levels = a, b, c, d, e 226s Box: [0, 1] x [0, 1] x [0, 1] units 226s Marked three-dimensional point pattern: 10 points 226s Mark variables: a, b 226s Box: [0, 1] x [0, 1] x [0, 1] units 226s Marked three-dimensional point pattern: 10 points 226s marks are dates, of class ‘Date’ 226s Box: [0, 1] x [0, 1] x [0, 1] units 226s Marked three-dimensional point pattern: 10 points 226s Mark variables: a, b 226s Box: [0, 1] x [0, 1] x [0, 1] units 226s > # 226s > # tests/triplets.R 226s > # 226s > # test code for triplet interaction 226s > # 226s > # $Revision: 1.9 $ $Date: 2022/05/22 08:45:38 $ 226s > # 226s > if(ALWAYS) { # C code, platform dependence 226s + local({ 226s + #' valid model 226s + fit <- ppm(cells ~1, Triplets(0.1)) 226s + fit 226s + suffstat(fit) 226s + #' invalid model 226s + fitR <- ppm(redwood ~1, Triplets(0.1)) 226s + fitR 226s + suffstat(fitR) 226s + #' hard core (zero triangles, coefficient is NA) 226s + fit0 <- ppm(cells ~1, Triplets(0.05)) 226s + fit0 226s + suffstat(fit0) 226s + #' bug case (1 triangle in data) 226s + fit1 <- ppm(cells ~1, Triplets(0.15)) 226s + fit1 226s + suffstat(fit1) 226s + #' simulation 226s + X <- simulate(fit) 226s + mod <- list(cif="triplets",par=list(beta=50,gamma=0.2,r=0.07), w=square(1)) 226s + Xm <- rmh(model=mod,start=list(n.start=5), control=list(nrep=1e5)) 226s + #' hard core 226s + mod$par$gamma <- 0 226s + XmHard <- rmh(model=mod,start=list(n.start=5), control=list(nrep=1e5)) 226s + }) 226s + } 226s Warning messages: 226s 1: In G3est: unrecognised argument ‘sphere’ was ignored 226s 2: In G3est: unrecognised argument ‘sphere’ was ignored 227s Checking arguments..determining simulation windows...Starting simulation. 227s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 227s Checking arguments..determining simulation windows...Starting simulation. 227s Initial state...Ready to simulate. Generating proposal points...Running Metropolis-Hastings. 227s > 227s BEGIN TEST testsUtoZ.R 227s 227s R version 4.4.3 (2025-02-28) -- "Trophy Case" 227s Copyright (C) 2025 The R Foundation for Statistical Computing 227s Platform: aarch64-unknown-linux-gnu 227s 227s R is free software and comes with ABSOLUTELY NO WARRANTY. 227s You are welcome to redistribute it under certain conditions. 227s Type 'license()' or 'licence()' for distribution details. 227s 227s R is a collaborative project with many contributors. 227s Type 'contributors()' for more information and 227s 'citation()' on how to cite R or R packages in publications. 227s 227s Type 'demo()' for some demos, 'help()' for on-line help, or 227s 'help.start()' for an HTML browser interface to help. 227s Type 'q()' to quit R. 227s 228s > #' 228s > #' Header for all (concatenated) test files 228s > #' 228s > #' Require spatstat.model 228s > #' Obtain environment variable controlling tests. 228s > #' 228s > #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ 228s > 228s > require(spatstat.model) 228s Loading required package: spatstat.model 228s Loading required package: spatstat.data 229s Loading required package: spatstat.univar 229s spatstat.univar 3.1-2 229s Loading required package: spatstat.geom 229s spatstat.geom 3.3-6 229s Loading required package: spatstat.random 229s spatstat.random 3.3-3 229s Loading required package: spatstat.explore 229s Loading required package: nlme 229s spatstat.explore 3.3-4 229s Loading required package: rpart 229s > FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) 229s > ALWAYS <- TRUE 229s > cat(paste("--------- Executing", 229s + if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", 229s + "test code -----------\n")) 229s --------- Executing **RESTRICTED** subset of test code ----------- 229s > # 229s > # tests/undoc.R 229s > # 229s > # $Revision: 1.16 $ $Date: 2020/11/02 07:06:49 $ 229s > # 229s > # Test undocumented hacks, experimental code, etc 229s > 229s > 229s > local({ 229s + if(FULLTEST) { 229s + ## cases of 'pickoption' 229s + aliases <- c(Lenin="Ulyanov", Stalin="Djugashvili", Trotsky="Bronstein") 229s + surname <- "Trot" 229s + pickoption("leader", surname, aliases) 229s + pickoption("leader", surname, aliases, exact=TRUE, die=FALSE) 229s + } 229s + if(ALWAYS) { 229s + ## pixellate.ppp accepts a data frame of weights 229s + pixellate(cells, weights=data.frame(a=1:42, b=42:1)) 229s + ## test parts of 'rmhsnoop' that don't require interaction with user 229s + rmhSnoopEnv(cells, Window(cells), 0.1) 229s + } 229s + if(FULLTEST) { 229s + ## Berman-Turner frame 229s + A <- bt.frame(quadscheme(cells), ~x, Strauss(0.07), rbord=0.07) 229s + print(A) 229s + ## digestCovariates 229s + D <- distfun(cells) 229s + Z <- distmap(cells) 229s + U <- dirichlet(cells) 229s + stopifnot(is.scov(D)) 229s + stopifnot(is.scov(Z)) 229s + stopifnot(is.scov(U)) 229s + stopifnot(is.scov("x")) 229s + dg <- digestCovariates(D=D,Z=Z,U=U,"x",list(A="x", B=D)) 229s + ## 229s + a <- getfields(dg, c("A", "D", "niets"), fatal=FALSE) 229s + ## util.R 229s + gg <- pointgrid(owin(), 7) 229s + checkbigmatrix(1000000L, 1000000L, FALSE, TRUE) 229s + spatstatDiagnostic("whatever") 229s + M <- list(list(a=2, b=FALSE), 229s + list(a=2, b=TRUE)) 229s spatstat.model 3.3-4 229s + stopifnot(!allElementsIdentical(M)) 229s + stopifnot(allElementsIdentical(M, "a")) 229s + ## 229s + A <- Strauss(0.1) 229s + A <- reincarnate.interact(A) 229s + ## 229s + ## special lists 229s + B <- solist(a=cells, b=redwood, c=japanesepines) 229s + BB <- as.ppplist(B) 229s + BL <- as.layered(B) 229s + DB <- as.imlist(lapply(B, density)) 229s + is.solist(B) 229s + is.ppplist(B) 229s + is.imlist(DB) 229s + ## case of density.ppplist 229s + DEB <- density(BB, se=TRUE) 229s + } 229s + 229s + if(ALWAYS) { 229s + ## fft 229s + z <- matrix(1:16, 4, 4) 229s + a <- fft2D(z, west=FALSE) 229s + if(fftwAvailable()) 229s + b <- fft2D(z, west=TRUE) 229s + } 229s + 229s + if(ALWAYS) { 229s + ## experimental interactions 229s + pot <- function(d, par) { d <= 0.1 } 229s + A <- Saturated(pot) 229s + print(A) 229s + A <- update(A, name="something") 229s + ppm(amacrine ~ x, A, rbord=0.1) 229s + } 229s + 229s + if(ALWAYS) { # platform dependent 229s + #' version-checking 229s + now <- Sys.Date() 229s + versioncurrency.spatstat(now + 80, FALSE) 229s + versioncurrency.spatstat(now + 140, FALSE) 229s + versioncurrency.spatstat(now + 400, FALSE) 229s + versioncurrency.spatstat(now + 1000) 229s + } 229s + 229s + if(FULLTEST) { 229s + #' general Ord interaction 229s + gradual <- function(d, pars) { 229s + y <- pmax(0, 0.005 - d)/0.005 229s + if(is.matrix(d)) y <- matrix(y, nrow(d), ncol(d)) 229s + return(y) 229s + } 229s + B <- Ord(gradual, "gradual Ord process") 229s + } 229s + }) 229s Saturated pairwise interaction family 229s Interaction:Saturated process with user-defined potential 229s Potential function: 229s function (d, par) 229s { 229s d <= 0.1 229s } 229s 229s > 229s > 229s > ## 229s > ## tests/updateppm.R 229s > ## 229s > ## Check validity of update.ppm 229s > ## 229s > ## $Revision: 1.8 $ $Date: 2022/10/23 01:19:19 $ 229s > 229s > local({ 229s + if(ALWAYS) { 229s + require(spatstat.utils) 229s + h <- function(m1, m2) { 229s + mc <- short.deparse(sys.call()) 229s + cat(paste(mc, "\t... ")) 229s + m1name <- short.deparse(substitute(m1)) 229s + m2name <- short.deparse(substitute(m2)) 229s + if(!identical(names(coef(m1)), names(coef(m2)))) 229s + stop(paste("Differing results for", m1name, "and", m2name, 229s + "in updateppm.R"), 229s + call.=FALSE) 229s + cat("OK\n") 229s + } 229s + 229s + X <- redwood[c(TRUE,FALSE)] 229s + Y <- redwood[c(FALSE,TRUE)] 229s + Loading required package: spatstat.utils 229s fit0f <- ppm(X ~ 1, nd=8) 229s + fit0p <- ppm(X, ~1, nd=8) 229s + fitxf <- ppm(X ~ x, nd=8) 229s + fitxp <- ppm(X, ~x, nd=8) 229s + 229s + cat("Basic consistency ...\n") 229s + h(fit0f, fit0p) 229s + h(fitxf, fitxp) 229s + 229s + cat("\nTest correct handling of model formulas ...\n") 229s + h(update(fitxf, Y), fitxf) 229s + h(update(fitxf, Q=Y), fitxf) 229s + h(update(fitxf, Y~x), fitxf) 229s + h(update(fitxf, Q=Y~x), fitxf) 229s + h(update(fitxf, ~x), fitxf) 229s + } 229s + 229s + if(FULLTEST) { 229s + h(update(fitxf, Y~1), fit0f) 229s + h(update(fitxf, ~1), fit0f) 229s + h(update(fit0f, Y~x), fitxf) 229s + h(update(fit0f, ~x), fitxf) 229s + 229s + h(update(fitxp, Y), fitxp) 229s + h(update(fitxp, Q=Y), fitxp) 229s + h(update(fitxp, Y~x), fitxp) 229s + h(update(fitxp, Q=Y~x), fitxp) 229s + h(update(fitxp, ~x), fitxp) 229s + 229s + h(update(fitxp, Y~1), fit0p) 229s + h(update(fitxp, ~1), fit0p) 229s + h(update(fit0p, Y~x), fitxp) 229s + h(update(fit0p, ~x), fitxp) 229s + } 229s + 229s + if(ALWAYS) { 229s + cat("\nTest scope handling for left hand side ...\n") 229s + X <- Y 229s + h(update(fitxf), fitxf) 229s + } 229s + 229s + if(ALWAYS) { 229s + cat("\nTest scope handling for right hand side ...\n") 229s + Z <- distmap(X) 229s + fitZf <- ppm(X ~ Z) 229s + fitZp <- ppm(X, ~ Z) 229s + h(update(fitxf, X ~ Z), fitZf) 229s + } 229s + if(FULLTEST) { 229s + h(update(fitxp, X ~ Z), fitZp) 229s + h(update(fitxf, . ~ Z), fitZf) 229s + h(update(fitZf, . ~ x), fitxf) 229s + h(update(fitZf, . ~ . - Z), fit0f) 229s + h(update(fitxp, . ~ Z), fitZp) 229s + h(update(fitZp, . ~ . - Z), fit0p) 229s + h(update(fit0p, . ~ . + Z), fitZp) 229s + h(update(fitZf, . ~ . ), fitZf) 229s + h(update(fitZp, . ~ . ), fitZp) 229s + } 229s + if(ALWAYS) { 229s + cat("\nTest use of internal data ...\n") 229s + h(update(fitZf, ~ x, use.internal=TRUE), fitxf) 229s + fitsin <- update(fitZf, X~sin(Z)) 229s + h(update(fitZf, ~ sin(Z), use.internal=TRUE), fitsin) 229s + } 229s + if(FULLTEST) { 229s + cat("\nTest step() ... ") 229s + fut <- ppm(X ~ Z + x + y, nd=8) 229s + fut0 <- step(fut, trace=0) 229s + cat("OK\n") 229s + } 229s + 229s + }) 229s Basic consistency ... 229s h(fit0f, fit0p) ... OK 229s h(fitxf, fitxp) ... OK 229s 229s Test correct handling of model formulas ... 229s h(update(fitxf, Y), fitxf) ... OK 229s h(update(fitxf, Q = Y), fitxf) ... OK 229s h(update(fitxf, Y ~ x), fitxf) ... OK 229s h(update(fitxf, Q = Y ~ x), fitxf) ... OK 229s h(update(fitxf, ~x), fitxf) ... OK 229s 229s Test scope handling for left hand side ... 229s h(update(fitxf), fitxf) ... OK 229s 229s Test scope handling for right hand side ... 229s h(update(fitxf, X ~ Z), fitZf) ... OK 229s 229s Test use of internal data ... 229s h(update(fitZf, ~x, use.internal = TRUE), fitxf) ... OK 229s h(update(fitZf, ~sin(Z), use.internal = TRUE), fitsin) ... OK 229s > # 229s > # tests/vcovppm.R 229s > # 229s > # Check validity of vcov.ppm algorithms 229s > # 229s > # Thanks to Ege Rubak 229s > # 229s > # $Revision: 1.12 $ $Date: 2020/05/02 01:32:58 $ 229s > # 229s > 229s > local({ 229s + 229s + set.seed(42) 229s + X <- rStrauss(200, .5, .05) 229s + model <- ppm(X, inter = Strauss(.05)) 229s + 229s + if(ALWAYS) { 229s + b <- vcov(model, generic = TRUE, algorithm = "basic") 229s + v <- vcov(model, generic = TRUE, algorithm = "vector") 229s + vc <- vcov(model, generic = TRUE, algorithm = "vectorclip") 229s + vn <- vcov(model, generic = FALSE) 229s + 229s + disagree <- function(x, y, tol=1e-7) { max(abs(x-y)) > tol } 229s + asymmetric <- function(x) { disagree(x, t(x)) } 229s + 229s + if(asymmetric(b)) 229s + stop("Non-symmetric matrix produced by vcov.ppm 'basic' algorithm") 229s + if(asymmetric(v)) 229s + stop("Non-symmetric matrix produced by vcov.ppm 'vector' algorithm") 229s + if(asymmetric(vc)) 229s + stop("Non-symmetric matrix produced by vcov.ppm 'vectorclip' algorithm") 229s + if(asymmetric(vn)) 229s + stop("Non-symmetric matrix produced by vcov.ppm Strauss algorithm") 229s + 229s + if(disagree(v, b)) 229s + stop("Disagreement between vcov.ppm algorithms 'vector' and 'basic' ") 229s + if(disagree(v, vc)) 229s + stop("Disagreement between vcov.ppm algorithms 'vector' and 'vectorclip' ") 229s + if(disagree(vn, vc)) 229s + stop("Disagreement between vcov.ppm generic and Strauss algorithms") 229s + } 229s + 229s + if(ALWAYS) { # C code 229s + ## Geyer code 229s + xx <- c(0.7375956, 0.6851697, 0.6399788, 0.6188382) 229s + yy <- c(0.5816040, 0.6456319, 0.5150633, 0.6191592) 229s + Y <- ppp(xx, yy, window=square(1)) 229s + modelY <- ppm(Y ~1, Geyer(0.1, 1)) 229s + 229s + b <- vcov(modelY, generic = TRUE, algorithm = "basic") 229s + v <- vcov(modelY, generic = TRUE, algorithm = "vector") 229s + vc <- vcov(modelY, generic = TRUE, algorithm = "vectorclip") 229s + 229s + if(asymmetric(b)) 229s + stop("Non-symmetric matrix produced by vcov.ppm 'basic' algorithm for Geyer model") 229s + if(asymmetric(v)) 229s + stop("Non-symmetric matrix produced by vcov.ppm 'vector' algorithm for Geyer model") 229s + if(asymmetric(vc)) 229s + stop("Non-symmetric matrix produced by vcov.ppm 'vectorclip' algorithm for Geyer model") 229s + 229s + if(disagree(v, b)) 229s + stop("Disagreement between vcov.ppm algorithms 'vector' and 'basic' for Geyer model") 229s + if(disagree(v, vc)) 229s + stop("Disagreement between vcov.ppm algorithms 'vector' and 'vectorclip' for Geyer model") 229s + } 229s + 229s + if(ALWAYS) { # C code 229s + ## tests of 'deltasuffstat' code 229s + ## Handling of offset terms 229s + modelH <- ppm(cells ~x, Hardcore(0.05)) 229s + a <- vcov(modelH, generic=TRUE) ## may fall over 229s + b <- vcov(modelH, generic=FALSE) 229s + if(disagree(a, b)) 229s + stop("Disagreement between vcov.ppm algorithms for Hardcore model") 229s + 229s + ## Correctness of pairwise.family$delta2 229s + modelZ <- ppm(amacrine ~1, MultiStrauss(radii=matrix(0.1, 2, 2))) 229s + b <- vcov(modelZ, generic=FALSE) 229s + g <- vcov(modelZ, generic=TRUE) 229s + if(disagree(b, g)) 229s + stop("Disagreement between vcov.ppm algorithms for MultiStrauss model") 229s + 229s + ## Test that 'deltasuffstat' works for Hybrids 229s + modelHyb <- ppm(japanesepines ~ 1, Hybrid(Strauss(0.05), Strauss(0.1))) 229s + vHyb <- vcov(modelHyb) 229s + } 229s + 229s + if(FULLTEST) { 229s + ## Code blocks for other choices of 'what' 229s + model <- ppm(X ~ 1, Strauss(.05)) 229s + cG <- vcov(model, what="corr") 229s + cP <- vcov(update(model, Poisson()), what="corr") 229s + ## outdated usage 229s + cX <- vcov(model, A1dummy=TRUE) 229s + 229s + ## Model with zero-length coefficient vector 229s + lam <- intensity(X) 229s + f <- function(x,y) { rep(lam, length(x)) } 229s + model0 <- ppm(X ~ offset(log(f)) - 1) 229s + dd <- vcov(model0) 229s + cc <- vcov(model0, what="corr") 229s + 229s + ## Model with NA coefficients 229s + fit <- ppm(X ~ log(f)) 229s + vcov(fit) 229s + fitE <- emend(fit, trace=TRUE) 229s + 229s + ## Other weird stuff 229s + su <- suffloc(ppm(X ~ x)) 229s + } 229s + }) 231s > 232s autopkgtest [10:52:55]: test run-unit-test: -----------------------] 233s autopkgtest [10:52:56]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 233s run-unit-test PASS 233s autopkgtest [10:52:56]: test pkg-r-autopkgtest: preparing testbed 394s autopkgtest [10:55:37]: testbed dpkg architecture: arm64 394s autopkgtest [10:55:37]: testbed apt version: 3.0.0 395s autopkgtest [10:55:38]: @@@@@@@@@@@@@@@@@@@@ test bed setup 395s autopkgtest [10:55:38]: testbed release detected to be: questing 396s autopkgtest [10:55:39]: updating testbed package index (apt update) 396s Get:1 http://ftpmaster.internal/ubuntu questing-proposed InRelease [110 kB] 396s Hit:2 http://ftpmaster.internal/ubuntu questing InRelease 396s Hit:3 http://ftpmaster.internal/ubuntu questing-updates InRelease 396s Hit:4 http://ftpmaster.internal/ubuntu questing-security InRelease 397s Get:5 http://ftpmaster.internal/ubuntu questing-proposed/multiverse Sources [44.4 kB] 397s Get:6 http://ftpmaster.internal/ubuntu questing-proposed/main Sources [175 kB] 397s Get:7 http://ftpmaster.internal/ubuntu questing-proposed/universe Sources [2076 kB] 397s Get:8 http://ftpmaster.internal/ubuntu questing-proposed/main arm64 Packages [219 kB] 397s Get:9 http://ftpmaster.internal/ubuntu questing-proposed/universe arm64 Packages [1509 kB] 397s Get:10 http://ftpmaster.internal/ubuntu questing-proposed/multiverse arm64 Packages [15.4 kB] 398s Fetched 4149 kB in 2s (2696 kB/s) 398s Reading package lists... 399s autopkgtest [10:55:42]: upgrading testbed (apt dist-upgrade and autopurge) 399s Reading package lists... 399s Building dependency tree... 399s Reading state information... 400s Calculating upgrade...Starting pkgProblemResolver with broken count: 0 400s Starting 2 pkgProblemResolver with broken count: 0 400s Done 401s Entering ResolveByKeep 401s 401s Calculating upgrade... 402s The following packages will be upgraded: 402s htop mtd-utils nano 402s 3 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 402s Need to get 936 kB of archives. 402s After this operation, 727 kB of additional disk space will be used. 402s Get:1 http://ftpmaster.internal/ubuntu questing/main arm64 nano arm64 8.4-1 [290 kB] 402s Get:2 http://ftpmaster.internal/ubuntu questing/main arm64 htop arm64 3.4.1-4 [177 kB] 402s Get:3 http://ftpmaster.internal/ubuntu questing/main arm64 mtd-utils arm64 1:2.3.0-1ubuntu1 [469 kB] 403s Fetched 936 kB in 1s (1528 kB/s) 403s (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 ... 117820 files and directories currently installed.) 403s Preparing to unpack .../archives/nano_8.4-1_arm64.deb ... 403s Unpacking nano (8.4-1) over (8.3-1) ... 403s Preparing to unpack .../htop_3.4.1-4_arm64.deb ... 403s Unpacking htop (3.4.1-4) over (3.4.0-2) ... 404s Preparing to unpack .../mtd-utils_1%3a2.3.0-1ubuntu1_arm64.deb ... 404s Unpacking mtd-utils (1:2.3.0-1ubuntu1) over (1:2.2.0-2ubuntu2) ... 404s Setting up htop (3.4.1-4) ... 404s Setting up mtd-utils (1:2.3.0-1ubuntu1) ... 404s Setting up nano (8.4-1) ... 404s Installing new version of config file /etc/nanorc ... 404s Processing triggers for man-db (2.13.0-1) ... 405s Processing triggers for install-info (7.1.1-1) ... 405s Reading package lists... 406s Building dependency tree... 406s Reading state information... 406s Starting pkgProblemResolver with broken count: 0 406s Starting 2 pkgProblemResolver with broken count: 0 406s Done 406s Solving dependencies... 407s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 410s Reading package lists... 410s Building dependency tree... 410s Reading state information... 410s Starting pkgProblemResolver with broken count: 0 411s Starting 2 pkgProblemResolver with broken count: 0 411s Done 411s The following NEW packages will be installed: 411s build-essential cpp cpp-14 cpp-14-aarch64-linux-gnu cpp-aarch64-linux-gnu 411s dctrl-tools fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono 411s fonts-mathjax g++ g++-14 g++-14-aarch64-linux-gnu g++-aarch64-linux-gnu gcc 411s gcc-14 gcc-14-aarch64-linux-gnu gcc-aarch64-linux-gnu gfortran gfortran-14 411s gfortran-14-aarch64-linux-gnu gfortran-aarch64-linux-gnu icu-devtools 411s libasan8 libblas-dev libblas3 libbz2-dev libcairo2 libcc1-0 libdatrie1 411s libdeflate-dev libdeflate0 libfontconfig1 libgcc-14-dev libgfortran-14-dev 411s libgfortran5 libgomp1 libgraphite2-3 libgsl28 libgslcblas0 libharfbuzz0b 411s libhwasan0 libice6 libicu-dev libisl23 libitm1 libjbig0 libjpeg-dev 412s libjpeg-turbo8 libjpeg-turbo8-dev libjpeg8 libjpeg8-dev libjs-mathjax 412s liblapack-dev liblapack3 liblerc4 liblsan0 liblzma-dev libmpc3 412s libncurses-dev libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 412s libpaper-utils libpaper2 libpcre2-16-0 libpcre2-32-0 libpcre2-dev 412s libpcre2-posix3 libpixman-1-0 libpkgconf3 libpng-dev libreadline-dev 412s libsharpyuv0 libsm6 libstdc++-14-dev libtcl8.6 libthai-data libthai0 412s libtiff6 libtirpc-dev libtk8.6 libtsan2 libubsan1 libwebp7 libxcb-render0 412s libxcb-shm0 libxft2 libxrender1 libxss1 libxt6t64 littler pkg-r-autopkgtest 412s pkgconf pkgconf-bin r-base-core r-base-dev r-cran-abind r-cran-codetools 412s r-cran-deldir r-cran-foreach r-cran-glmnet r-cran-goftest r-cran-gsl 412s r-cran-iterators r-cran-lattice r-cran-littler r-cran-matrix r-cran-mgcv 412s r-cran-nleqslv r-cran-nlme r-cran-pkgkitten r-cran-polyclip r-cran-rcpp 412s r-cran-rcppeigen r-cran-rpart r-cran-shape r-cran-sm r-cran-spatial 412s r-cran-spatstat r-cran-spatstat.data r-cran-spatstat.explore 412s r-cran-spatstat.geom r-cran-spatstat.linnet r-cran-spatstat.model 412s r-cran-spatstat.random r-cran-spatstat.sparse r-cran-spatstat.univar 412s r-cran-spatstat.utils r-cran-survival r-cran-tensor unzip x11-common 412s xdg-utils zip zlib1g-dev 412s 0 upgraded, 137 newly installed, 0 to remove and 0 not upgraded. 412s Need to get 191 MB of archives. 412s After this operation, 544 MB of additional disk space will be used. 412s Get:1 http://ftpmaster.internal/ubuntu questing/main arm64 libisl23 arm64 0.27-1 [676 kB] 412s Get:2 http://ftpmaster.internal/ubuntu questing/main arm64 libmpc3 arm64 1.3.1-1build2 [56.8 kB] 412s Get:3 http://ftpmaster.internal/ubuntu questing/main arm64 cpp-14-aarch64-linux-gnu arm64 14.2.0-19ubuntu2 [10.6 MB] 413s Get:4 http://ftpmaster.internal/ubuntu questing/main arm64 cpp-14 arm64 14.2.0-19ubuntu2 [1026 B] 413s Get:5 http://ftpmaster.internal/ubuntu questing/main arm64 cpp-aarch64-linux-gnu arm64 4:14.2.0-1ubuntu1 [5558 B] 413s Get:6 http://ftpmaster.internal/ubuntu questing/main arm64 cpp arm64 4:14.2.0-1ubuntu1 [22.4 kB] 413s Get:7 http://ftpmaster.internal/ubuntu questing/main arm64 libcc1-0 arm64 15-20250404-0ubuntu1 [49.1 kB] 413s Get:8 http://ftpmaster.internal/ubuntu questing/main arm64 libgomp1 arm64 15-20250404-0ubuntu1 [147 kB] 413s Get:9 http://ftpmaster.internal/ubuntu questing/main arm64 libitm1 arm64 15-20250404-0ubuntu1 [27.8 kB] 413s Get:10 http://ftpmaster.internal/ubuntu questing/main arm64 libasan8 arm64 15-20250404-0ubuntu1 [2922 kB] 414s Get:11 http://ftpmaster.internal/ubuntu questing/main arm64 liblsan0 arm64 15-20250404-0ubuntu1 [1318 kB] 414s Get:12 http://ftpmaster.internal/ubuntu questing/main arm64 libtsan2 arm64 15-20250404-0ubuntu1 [2692 kB] 414s Get:13 http://ftpmaster.internal/ubuntu questing/main arm64 libubsan1 arm64 15-20250404-0ubuntu1 [1177 kB] 414s Get:14 http://ftpmaster.internal/ubuntu questing/main arm64 libhwasan0 arm64 15-20250404-0ubuntu1 [1640 kB] 414s Get:15 http://ftpmaster.internal/ubuntu questing/main arm64 libgcc-14-dev arm64 14.2.0-19ubuntu2 [2593 kB] 414s Get:16 http://ftpmaster.internal/ubuntu questing/main arm64 gcc-14-aarch64-linux-gnu arm64 14.2.0-19ubuntu2 [20.9 MB] 415s Get:17 http://ftpmaster.internal/ubuntu questing/main arm64 gcc-14 arm64 14.2.0-19ubuntu2 [529 kB] 415s Get:18 http://ftpmaster.internal/ubuntu questing/main arm64 gcc-aarch64-linux-gnu arm64 4:14.2.0-1ubuntu1 [1200 B] 415s Get:19 http://ftpmaster.internal/ubuntu questing/main arm64 gcc arm64 4:14.2.0-1ubuntu1 [4998 B] 415s Get:20 http://ftpmaster.internal/ubuntu questing/main arm64 libstdc++-14-dev arm64 14.2.0-19ubuntu2 [2501 kB] 415s Get:21 http://ftpmaster.internal/ubuntu questing/main arm64 g++-14-aarch64-linux-gnu arm64 14.2.0-19ubuntu2 [12.1 MB] 415s Get:22 http://ftpmaster.internal/ubuntu questing/main arm64 g++-14 arm64 14.2.0-19ubuntu2 [23.0 kB] 415s Get:23 http://ftpmaster.internal/ubuntu questing/main arm64 g++-aarch64-linux-gnu arm64 4:14.2.0-1ubuntu1 [956 B] 415s Get:24 http://ftpmaster.internal/ubuntu questing/main arm64 g++ arm64 4:14.2.0-1ubuntu1 [1080 B] 415s Get:25 http://ftpmaster.internal/ubuntu questing/main arm64 build-essential arm64 12.12ubuntu1 [5082 B] 415s Get:26 http://ftpmaster.internal/ubuntu questing/main arm64 dctrl-tools arm64 2.24-3build3 [103 kB] 415s Get:27 http://ftpmaster.internal/ubuntu questing/main arm64 fonts-dejavu-mono all 2.37-8 [502 kB] 415s Get:28 http://ftpmaster.internal/ubuntu questing/main arm64 fonts-dejavu-core all 2.37-8 [835 kB] 415s Get:29 http://ftpmaster.internal/ubuntu questing/main arm64 fontconfig-config arm64 2.15.0-2.2ubuntu1 [37.9 kB] 415s Get:30 http://ftpmaster.internal/ubuntu questing/main arm64 libfontconfig1 arm64 2.15.0-2.2ubuntu1 [144 kB] 415s Get:31 http://ftpmaster.internal/ubuntu questing/main arm64 fontconfig arm64 2.15.0-2.2ubuntu1 [191 kB] 415s Get:32 http://ftpmaster.internal/ubuntu questing/main arm64 fonts-mathjax all 2.7.9+dfsg-1 [2208 kB] 415s Get:33 http://ftpmaster.internal/ubuntu questing/main arm64 libgfortran5 arm64 15-20250404-0ubuntu1 [444 kB] 415s Get:34 http://ftpmaster.internal/ubuntu questing/main arm64 libgfortran-14-dev arm64 14.2.0-19ubuntu2 [498 kB] 415s Get:35 http://ftpmaster.internal/ubuntu questing/main arm64 gfortran-14-aarch64-linux-gnu arm64 14.2.0-19ubuntu2 [11.4 MB] 416s Get:36 http://ftpmaster.internal/ubuntu questing/main arm64 gfortran-14 arm64 14.2.0-19ubuntu2 [14.2 kB] 416s Get:37 http://ftpmaster.internal/ubuntu questing/main arm64 gfortran-aarch64-linux-gnu arm64 4:14.2.0-1ubuntu1 [1022 B] 416s Get:38 http://ftpmaster.internal/ubuntu questing/main arm64 gfortran arm64 4:14.2.0-1ubuntu1 [1166 B] 416s Get:39 http://ftpmaster.internal/ubuntu questing/main arm64 icu-devtools arm64 76.1-1ubuntu2 [213 kB] 416s Get:40 http://ftpmaster.internal/ubuntu questing/main arm64 libblas3 arm64 3.12.1-2 [161 kB] 416s Get:41 http://ftpmaster.internal/ubuntu questing/main arm64 libblas-dev arm64 3.12.1-2 [126 kB] 416s Get:42 http://ftpmaster.internal/ubuntu questing/main arm64 libbz2-dev arm64 1.0.8-6 [36.1 kB] 416s Get:43 http://ftpmaster.internal/ubuntu questing/main arm64 libpixman-1-0 arm64 0.44.0-3 [197 kB] 416s Get:44 http://ftpmaster.internal/ubuntu questing/main arm64 libxcb-render0 arm64 1.17.0-2 [16.6 kB] 416s Get:45 http://ftpmaster.internal/ubuntu questing/main arm64 libxcb-shm0 arm64 1.17.0-2 [5884 B] 416s Get:46 http://ftpmaster.internal/ubuntu questing/main arm64 libxrender1 arm64 1:0.9.10-1.1build1 [18.8 kB] 416s Get:47 http://ftpmaster.internal/ubuntu questing/main arm64 libcairo2 arm64 1.18.4-1 [560 kB] 416s Get:48 http://ftpmaster.internal/ubuntu questing/main arm64 libdatrie1 arm64 0.2.13-3build1 [19.2 kB] 416s Get:49 http://ftpmaster.internal/ubuntu questing/main arm64 libdeflate0 arm64 1.23-1 [46.2 kB] 416s Get:50 http://ftpmaster.internal/ubuntu questing/main arm64 libdeflate-dev arm64 1.23-1 [53.7 kB] 416s Get:51 http://ftpmaster.internal/ubuntu questing/main arm64 libgraphite2-3 arm64 1.3.14-2ubuntu1 [70.6 kB] 416s Get:52 http://ftpmaster.internal/ubuntu questing/universe arm64 libgslcblas0 arm64 2.8+dfsg-5ubuntu1 [87.4 kB] 416s Get:53 http://ftpmaster.internal/ubuntu questing/universe arm64 libgsl28 arm64 2.8+dfsg-5ubuntu1 [982 kB] 416s Get:54 http://ftpmaster.internal/ubuntu questing/main arm64 libharfbuzz0b arm64 10.2.0-1 [490 kB] 416s Get:55 http://ftpmaster.internal/ubuntu questing/main arm64 x11-common all 1:7.7+23ubuntu4 [21.8 kB] 416s Get:56 http://ftpmaster.internal/ubuntu questing/main arm64 libice6 arm64 2:1.1.1-1 [42.3 kB] 416s Get:57 http://ftpmaster.internal/ubuntu questing/main arm64 libicu-dev arm64 76.1-1ubuntu2 [12.2 MB] 416s Get:58 http://ftpmaster.internal/ubuntu questing/main arm64 libjpeg-turbo8 arm64 2.1.5-3ubuntu2 [165 kB] 416s Get:59 http://ftpmaster.internal/ubuntu questing/main arm64 libjpeg-turbo8-dev arm64 2.1.5-3ubuntu2 [306 kB] 416s Get:60 http://ftpmaster.internal/ubuntu questing/main arm64 libjpeg8 arm64 8c-2ubuntu11 [2148 B] 416s Get:61 http://ftpmaster.internal/ubuntu questing/main arm64 libjpeg8-dev arm64 8c-2ubuntu11 [1484 B] 416s Get:62 http://ftpmaster.internal/ubuntu questing/main arm64 libjpeg-dev arm64 8c-2ubuntu11 [1482 B] 416s Get:63 http://ftpmaster.internal/ubuntu questing/main arm64 liblapack3 arm64 3.12.1-2 [2307 kB] 416s Get:64 http://ftpmaster.internal/ubuntu questing/main arm64 liblapack-dev arm64 3.12.1-2 [4439 kB] 416s Get:65 http://ftpmaster.internal/ubuntu questing/main arm64 liblerc4 arm64 4.0.0+ds-5ubuntu1 [167 kB] 416s Get:66 http://ftpmaster.internal/ubuntu questing/main arm64 libncurses-dev arm64 6.5+20250216-2 [389 kB] 416s Get:67 http://ftpmaster.internal/ubuntu questing/main arm64 libthai-data all 0.1.29-2build1 [158 kB] 416s Get:68 http://ftpmaster.internal/ubuntu questing/main arm64 libthai0 arm64 0.1.29-2build1 [18.2 kB] 416s Get:69 http://ftpmaster.internal/ubuntu questing/main arm64 libpango-1.0-0 arm64 1.56.3-1 [238 kB] 416s Get:70 http://ftpmaster.internal/ubuntu questing/main arm64 libpangoft2-1.0-0 arm64 1.56.3-1 [49.8 kB] 416s Get:71 http://ftpmaster.internal/ubuntu questing/main arm64 libpangocairo-1.0-0 arm64 1.56.3-1 [27.6 kB] 416s Get:72 http://ftpmaster.internal/ubuntu questing/main arm64 libpaper2 arm64 2.2.5-0.3 [17.3 kB] 416s Get:73 http://ftpmaster.internal/ubuntu questing/main arm64 libpaper-utils arm64 2.2.5-0.3 [15.4 kB] 416s Get:74 http://ftpmaster.internal/ubuntu questing/main arm64 libpcre2-16-0 arm64 10.45-1 [222 kB] 416s Get:75 http://ftpmaster.internal/ubuntu questing/main arm64 libpcre2-32-0 arm64 10.45-1 [210 kB] 416s Get:76 http://ftpmaster.internal/ubuntu questing/main arm64 libpcre2-posix3 arm64 10.45-1 [7084 B] 416s Get:77 http://ftpmaster.internal/ubuntu questing/main arm64 libpcre2-dev arm64 10.45-1 [768 kB] 416s Get:78 http://ftpmaster.internal/ubuntu questing/main arm64 libpkgconf3 arm64 1.8.1-4 [31.4 kB] 416s Get:79 http://ftpmaster.internal/ubuntu questing/main arm64 zlib1g-dev arm64 1:1.3.dfsg+really1.3.1-1ubuntu1 [894 kB] 416s Get:80 http://ftpmaster.internal/ubuntu questing/main arm64 libpng-dev arm64 1.6.47-1.1 [269 kB] 416s Get:81 http://ftpmaster.internal/ubuntu questing/main arm64 libreadline-dev arm64 8.2-6 [179 kB] 416s Get:82 http://ftpmaster.internal/ubuntu questing/main arm64 libsharpyuv0 arm64 1.5.0-0.1 [16.9 kB] 417s Get:83 http://ftpmaster.internal/ubuntu questing/main arm64 libsm6 arm64 2:1.2.4-1 [16.4 kB] 417s Get:84 http://ftpmaster.internal/ubuntu questing/main arm64 libtcl8.6 arm64 8.6.16+dfsg-1 [987 kB] 417s Get:85 http://ftpmaster.internal/ubuntu questing/main arm64 libjbig0 arm64 2.1-6.1ubuntu2 [29.3 kB] 417s Get:86 http://ftpmaster.internal/ubuntu questing/main arm64 libwebp7 arm64 1.5.0-0.1 [194 kB] 417s Get:87 http://ftpmaster.internal/ubuntu questing/main arm64 libtiff6 arm64 4.5.1+git230720-4ubuntu4 [193 kB] 417s Get:88 http://ftpmaster.internal/ubuntu questing/main arm64 libxft2 arm64 2.3.6-1build1 [44.1 kB] 417s Get:89 http://ftpmaster.internal/ubuntu questing/main arm64 libxss1 arm64 1:1.2.3-1build3 [7244 B] 417s Get:90 http://ftpmaster.internal/ubuntu questing/main arm64 libtk8.6 arm64 8.6.16-1 [776 kB] 417s Get:91 http://ftpmaster.internal/ubuntu questing/main arm64 libxt6t64 arm64 1:1.2.1-1.2build1 [168 kB] 417s Get:92 http://ftpmaster.internal/ubuntu questing/main arm64 zip arm64 3.0-14ubuntu2 [173 kB] 417s Get:93 http://ftpmaster.internal/ubuntu questing/main arm64 unzip arm64 6.0-28ubuntu6 [178 kB] 417s Get:94 http://ftpmaster.internal/ubuntu questing/main arm64 xdg-utils all 1.2.1-2ubuntu1 [66.0 kB] 417s Get:95 http://ftpmaster.internal/ubuntu questing/universe arm64 r-base-core arm64 4.4.3-1 [28.4 MB] 418s Get:96 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-littler arm64 0.3.20-2 [96.1 kB] 418s Get:97 http://ftpmaster.internal/ubuntu questing/universe arm64 littler all 0.3.20-2 [2554 B] 418s Get:98 http://ftpmaster.internal/ubuntu questing/main arm64 liblzma-dev arm64 5.6.4-1ubuntu1 [180 kB] 418s Get:99 http://ftpmaster.internal/ubuntu questing/main arm64 pkgconf-bin arm64 1.8.1-4 [20.9 kB] 418s Get:100 http://ftpmaster.internal/ubuntu questing/main arm64 pkgconf arm64 1.8.1-4 [16.7 kB] 418s Get:101 http://ftpmaster.internal/ubuntu questing/main arm64 libtirpc-dev arm64 1.3.4+ds-1.3 [201 kB] 418s Get:102 http://ftpmaster.internal/ubuntu questing/universe arm64 r-base-dev all 4.4.3-1 [4176 B] 418s Get:103 http://ftpmaster.internal/ubuntu questing/universe arm64 pkg-r-autopkgtest all 20231212ubuntu1 [6448 B] 418s Get:104 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-abind all 1.4-8-1 [66.9 kB] 418s Get:105 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-codetools all 0.2-20-1 [90.5 kB] 418s Get:106 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-deldir arm64 2.0-4-1build1 [270 kB] 418s Get:107 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-iterators all 1.0.14-1 [336 kB] 418s Get:108 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-foreach all 1.5.2-1 [124 kB] 418s Get:109 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-lattice arm64 0.22-6-1 [1363 kB] 419s Get:110 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-matrix arm64 1.7-3-1 [4045 kB] 419s Get:111 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-shape all 1.4.6.1-1 [749 kB] 419s Get:112 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-survival arm64 3.8-3-1 [8213 kB] 420s Get:113 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-pkgkitten all 0.2.4-1 [27.2 kB] 420s Get:114 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-rcpp arm64 1.0.14-1 [1978 kB] 420s Get:115 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-rcppeigen arm64 0.3.4.0.2-1 [1422 kB] 420s Get:116 http://ftpmaster.internal/ubuntu questing/main arm64 libjs-mathjax all 2.7.9+dfsg-1 [5665 kB] 421s Get:117 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-glmnet arm64 4.1-8-1 [1898 kB] 421s Get:118 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-goftest arm64 1.2-3-1 [60.2 kB] 421s Get:119 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-gsl arm64 2.1-8-1build1 [485 kB] 421s Get:120 http://ftpmaster.internal/ubuntu questing-proposed/universe arm64 r-cran-nlme arm64 3.1.168-1 [2310 kB] 421s Get:121 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-mgcv arm64 1.9-1-1 [3248 kB] 421s Get:122 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-nleqslv arm64 3.3.5-1 [101 kB] 421s Get:123 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-polyclip arm64 1.10-7-1 [113 kB] 421s Get:124 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-rpart arm64 4.1.24-1 [665 kB] 421s Get:125 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-sm arm64 2.2-6.0-1 [787 kB] 421s Get:126 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatial arm64 7.3-18-1 [133 kB] 421s Get:127 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.utils arm64 3.1-3-1 [386 kB] 421s Get:128 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.data all 3.1-6-1 [4153 kB] 421s Get:129 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.univar arm64 3.1-2-1 [314 kB] 421s Get:130 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.geom arm64 3.3-6-1 [3941 kB] 422s Get:131 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.random arm64 3.3-3-1 [1163 kB] 422s Get:132 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-tensor all 1.5-4 [15.7 kB] 422s Get:133 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.sparse arm64 3.1-0-1 [218 kB] 422s Get:134 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.explore arm64 3.3-4-1 [3272 kB] 422s Get:135 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.model arm64 3.3-4-1 [3398 kB] 422s Get:136 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat.linnet arm64 3.2-5-1 [1507 kB] 422s Get:137 http://ftpmaster.internal/ubuntu questing/universe arm64 r-cran-spatstat arm64 3.3-1-1 [4120 kB] 423s Preconfiguring packages ... 423s Fetched 191 MB in 11s (17.4 MB/s) 423s Selecting previously unselected package libisl23:arm64. 423s (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 ... 117821 files and directories currently installed.) 423s Preparing to unpack .../000-libisl23_0.27-1_arm64.deb ... 423s Unpacking libisl23:arm64 (0.27-1) ... 423s Selecting previously unselected package libmpc3:arm64. 423s Preparing to unpack .../001-libmpc3_1.3.1-1build2_arm64.deb ... 423s Unpacking libmpc3:arm64 (1.3.1-1build2) ... 423s Selecting previously unselected package cpp-14-aarch64-linux-gnu. 423s Preparing to unpack .../002-cpp-14-aarch64-linux-gnu_14.2.0-19ubuntu2_arm64.deb ... 423s Unpacking cpp-14-aarch64-linux-gnu (14.2.0-19ubuntu2) ... 423s Selecting previously unselected package cpp-14. 423s Preparing to unpack .../003-cpp-14_14.2.0-19ubuntu2_arm64.deb ... 423s Unpacking cpp-14 (14.2.0-19ubuntu2) ... 423s Selecting previously unselected package cpp-aarch64-linux-gnu. 423s Preparing to unpack .../004-cpp-aarch64-linux-gnu_4%3a14.2.0-1ubuntu1_arm64.deb ... 423s Unpacking cpp-aarch64-linux-gnu (4:14.2.0-1ubuntu1) ... 423s Selecting previously unselected package cpp. 423s Preparing to unpack .../005-cpp_4%3a14.2.0-1ubuntu1_arm64.deb ... 423s Unpacking cpp (4:14.2.0-1ubuntu1) ... 423s Selecting previously unselected package libcc1-0:arm64. 423s Preparing to unpack .../006-libcc1-0_15-20250404-0ubuntu1_arm64.deb ... 423s Unpacking libcc1-0:arm64 (15-20250404-0ubuntu1) ... 423s Selecting previously unselected package libgomp1:arm64. 423s Preparing to unpack .../007-libgomp1_15-20250404-0ubuntu1_arm64.deb ... 423s Unpacking libgomp1:arm64 (15-20250404-0ubuntu1) ... 423s Selecting previously unselected package libitm1:arm64. 423s Preparing to unpack .../008-libitm1_15-20250404-0ubuntu1_arm64.deb ... 423s Unpacking libitm1:arm64 (15-20250404-0ubuntu1) ... 423s Selecting previously unselected package libasan8:arm64. 424s Preparing to unpack .../009-libasan8_15-20250404-0ubuntu1_arm64.deb ... 424s Unpacking libasan8:arm64 (15-20250404-0ubuntu1) ... 424s Selecting previously unselected package liblsan0:arm64. 424s Preparing to unpack .../010-liblsan0_15-20250404-0ubuntu1_arm64.deb ... 424s Unpacking liblsan0:arm64 (15-20250404-0ubuntu1) ... 424s Selecting previously unselected package libtsan2:arm64. 424s Preparing to unpack .../011-libtsan2_15-20250404-0ubuntu1_arm64.deb ... 424s Unpacking libtsan2:arm64 (15-20250404-0ubuntu1) ... 424s Selecting previously unselected package libubsan1:arm64. 424s Preparing to unpack .../012-libubsan1_15-20250404-0ubuntu1_arm64.deb ... 424s Unpacking libubsan1:arm64 (15-20250404-0ubuntu1) ... 424s Selecting previously unselected package libhwasan0:arm64. 424s Preparing to unpack .../013-libhwasan0_15-20250404-0ubuntu1_arm64.deb ... 424s Unpacking libhwasan0:arm64 (15-20250404-0ubuntu1) ... 424s Selecting previously unselected package libgcc-14-dev:arm64. 424s Preparing to unpack .../014-libgcc-14-dev_14.2.0-19ubuntu2_arm64.deb ... 424s Unpacking libgcc-14-dev:arm64 (14.2.0-19ubuntu2) ... 424s Selecting previously unselected package gcc-14-aarch64-linux-gnu. 424s Preparing to unpack .../015-gcc-14-aarch64-linux-gnu_14.2.0-19ubuntu2_arm64.deb ... 424s Unpacking gcc-14-aarch64-linux-gnu (14.2.0-19ubuntu2) ... 424s Selecting previously unselected package gcc-14. 424s Preparing to unpack .../016-gcc-14_14.2.0-19ubuntu2_arm64.deb ... 424s Unpacking gcc-14 (14.2.0-19ubuntu2) ... 425s Selecting previously unselected package gcc-aarch64-linux-gnu. 425s Preparing to unpack .../017-gcc-aarch64-linux-gnu_4%3a14.2.0-1ubuntu1_arm64.deb ... 425s Unpacking gcc-aarch64-linux-gnu (4:14.2.0-1ubuntu1) ... 425s Selecting previously unselected package gcc. 425s Preparing to unpack .../018-gcc_4%3a14.2.0-1ubuntu1_arm64.deb ... 425s Unpacking gcc (4:14.2.0-1ubuntu1) ... 425s Selecting previously unselected package libstdc++-14-dev:arm64. 425s Preparing to unpack .../019-libstdc++-14-dev_14.2.0-19ubuntu2_arm64.deb ... 425s Unpacking libstdc++-14-dev:arm64 (14.2.0-19ubuntu2) ... 425s Selecting previously unselected package g++-14-aarch64-linux-gnu. 425s Preparing to unpack .../020-g++-14-aarch64-linux-gnu_14.2.0-19ubuntu2_arm64.deb ... 425s Unpacking g++-14-aarch64-linux-gnu (14.2.0-19ubuntu2) ... 425s Selecting previously unselected package g++-14. 425s Preparing to unpack .../021-g++-14_14.2.0-19ubuntu2_arm64.deb ... 425s Unpacking g++-14 (14.2.0-19ubuntu2) ... 425s Selecting previously unselected package g++-aarch64-linux-gnu. 425s Preparing to unpack .../022-g++-aarch64-linux-gnu_4%3a14.2.0-1ubuntu1_arm64.deb ... 425s Unpacking g++-aarch64-linux-gnu (4:14.2.0-1ubuntu1) ... 425s Selecting previously unselected package g++. 425s Preparing to unpack .../023-g++_4%3a14.2.0-1ubuntu1_arm64.deb ... 425s Unpacking g++ (4:14.2.0-1ubuntu1) ... 425s Selecting previously unselected package build-essential. 425s Preparing to unpack .../024-build-essential_12.12ubuntu1_arm64.deb ... 425s Unpacking build-essential (12.12ubuntu1) ... 425s Selecting previously unselected package dctrl-tools. 425s Preparing to unpack .../025-dctrl-tools_2.24-3build3_arm64.deb ... 425s Unpacking dctrl-tools (2.24-3build3) ... 425s Selecting previously unselected package fonts-dejavu-mono. 425s Preparing to unpack .../026-fonts-dejavu-mono_2.37-8_all.deb ... 425s Unpacking fonts-dejavu-mono (2.37-8) ... 425s Selecting previously unselected package fonts-dejavu-core. 425s Preparing to unpack .../027-fonts-dejavu-core_2.37-8_all.deb ... 425s Unpacking fonts-dejavu-core (2.37-8) ... 425s Selecting previously unselected package fontconfig-config. 425s Preparing to unpack .../028-fontconfig-config_2.15.0-2.2ubuntu1_arm64.deb ... 426s Unpacking fontconfig-config (2.15.0-2.2ubuntu1) ... 426s Selecting previously unselected package libfontconfig1:arm64. 426s Preparing to unpack .../029-libfontconfig1_2.15.0-2.2ubuntu1_arm64.deb ... 426s Unpacking libfontconfig1:arm64 (2.15.0-2.2ubuntu1) ... 426s Selecting previously unselected package fontconfig. 426s Preparing to unpack .../030-fontconfig_2.15.0-2.2ubuntu1_arm64.deb ... 426s Unpacking fontconfig (2.15.0-2.2ubuntu1) ... 426s Selecting previously unselected package fonts-mathjax. 426s Preparing to unpack .../031-fonts-mathjax_2.7.9+dfsg-1_all.deb ... 426s Unpacking fonts-mathjax (2.7.9+dfsg-1) ... 426s Selecting previously unselected package libgfortran5:arm64. 426s Preparing to unpack .../032-libgfortran5_15-20250404-0ubuntu1_arm64.deb ... 426s Unpacking libgfortran5:arm64 (15-20250404-0ubuntu1) ... 426s Selecting previously unselected package libgfortran-14-dev:arm64. 426s Preparing to unpack .../033-libgfortran-14-dev_14.2.0-19ubuntu2_arm64.deb ... 426s Unpacking libgfortran-14-dev:arm64 (14.2.0-19ubuntu2) ... 426s Selecting previously unselected package gfortran-14-aarch64-linux-gnu. 426s Preparing to unpack .../034-gfortran-14-aarch64-linux-gnu_14.2.0-19ubuntu2_arm64.deb ... 426s Unpacking gfortran-14-aarch64-linux-gnu (14.2.0-19ubuntu2) ... 426s Selecting previously unselected package gfortran-14. 427s Preparing to unpack .../035-gfortran-14_14.2.0-19ubuntu2_arm64.deb ... 427s Unpacking gfortran-14 (14.2.0-19ubuntu2) ... 427s Selecting previously unselected package gfortran-aarch64-linux-gnu. 427s Preparing to unpack .../036-gfortran-aarch64-linux-gnu_4%3a14.2.0-1ubuntu1_arm64.deb ... 427s Unpacking gfortran-aarch64-linux-gnu (4:14.2.0-1ubuntu1) ... 427s Selecting previously unselected package gfortran. 427s Preparing to unpack .../037-gfortran_4%3a14.2.0-1ubuntu1_arm64.deb ... 427s Unpacking gfortran (4:14.2.0-1ubuntu1) ... 427s Selecting previously unselected package icu-devtools. 427s Preparing to unpack .../038-icu-devtools_76.1-1ubuntu2_arm64.deb ... 427s Unpacking icu-devtools (76.1-1ubuntu2) ... 427s Selecting previously unselected package libblas3:arm64. 427s Preparing to unpack .../039-libblas3_3.12.1-2_arm64.deb ... 427s Unpacking libblas3:arm64 (3.12.1-2) ... 427s Selecting previously unselected package libblas-dev:arm64. 427s Preparing to unpack .../040-libblas-dev_3.12.1-2_arm64.deb ... 427s Unpacking libblas-dev:arm64 (3.12.1-2) ... 427s Selecting previously unselected package libbz2-dev:arm64. 427s Preparing to unpack .../041-libbz2-dev_1.0.8-6_arm64.deb ... 427s Unpacking libbz2-dev:arm64 (1.0.8-6) ... 427s Selecting previously unselected package libpixman-1-0:arm64. 427s Preparing to unpack .../042-libpixman-1-0_0.44.0-3_arm64.deb ... 427s Unpacking libpixman-1-0:arm64 (0.44.0-3) ... 427s Selecting previously unselected package libxcb-render0:arm64. 427s Preparing to unpack .../043-libxcb-render0_1.17.0-2_arm64.deb ... 427s Unpacking libxcb-render0:arm64 (1.17.0-2) ... 427s Selecting previously unselected package libxcb-shm0:arm64. 427s Preparing to unpack .../044-libxcb-shm0_1.17.0-2_arm64.deb ... 427s Unpacking libxcb-shm0:arm64 (1.17.0-2) ... 427s Selecting previously unselected package libxrender1:arm64. 427s Preparing to unpack .../045-libxrender1_1%3a0.9.10-1.1build1_arm64.deb ... 427s Unpacking libxrender1:arm64 (1:0.9.10-1.1build1) ... 427s Selecting previously unselected package libcairo2:arm64. 427s Preparing to unpack .../046-libcairo2_1.18.4-1_arm64.deb ... 427s Unpacking libcairo2:arm64 (1.18.4-1) ... 427s Selecting previously unselected package libdatrie1:arm64. 427s Preparing to unpack .../047-libdatrie1_0.2.13-3build1_arm64.deb ... 427s Unpacking libdatrie1:arm64 (0.2.13-3build1) ... 427s Selecting previously unselected package libdeflate0:arm64. 427s Preparing to unpack .../048-libdeflate0_1.23-1_arm64.deb ... 427s Unpacking libdeflate0:arm64 (1.23-1) ... 427s Selecting previously unselected package libdeflate-dev:arm64. 427s Preparing to unpack .../049-libdeflate-dev_1.23-1_arm64.deb ... 427s Unpacking libdeflate-dev:arm64 (1.23-1) ... 427s Selecting previously unselected package libgraphite2-3:arm64. 427s Preparing to unpack .../050-libgraphite2-3_1.3.14-2ubuntu1_arm64.deb ... 427s Unpacking libgraphite2-3:arm64 (1.3.14-2ubuntu1) ... 427s Selecting previously unselected package libgslcblas0:arm64. 427s Preparing to unpack .../051-libgslcblas0_2.8+dfsg-5ubuntu1_arm64.deb ... 427s Unpacking libgslcblas0:arm64 (2.8+dfsg-5ubuntu1) ... 427s Selecting previously unselected package libgsl28:arm64. 427s Preparing to unpack .../052-libgsl28_2.8+dfsg-5ubuntu1_arm64.deb ... 427s Unpacking libgsl28:arm64 (2.8+dfsg-5ubuntu1) ... 427s Selecting previously unselected package libharfbuzz0b:arm64. 427s Preparing to unpack .../053-libharfbuzz0b_10.2.0-1_arm64.deb ... 427s Unpacking libharfbuzz0b:arm64 (10.2.0-1) ... 427s Selecting previously unselected package x11-common. 427s Preparing to unpack .../054-x11-common_1%3a7.7+23ubuntu4_all.deb ... 427s Unpacking x11-common (1:7.7+23ubuntu4) ... 427s Selecting previously unselected package libice6:arm64. 427s Preparing to unpack .../055-libice6_2%3a1.1.1-1_arm64.deb ... 427s Unpacking libice6:arm64 (2:1.1.1-1) ... 427s Selecting previously unselected package libicu-dev:arm64. 427s Preparing to unpack .../056-libicu-dev_76.1-1ubuntu2_arm64.deb ... 427s Unpacking libicu-dev:arm64 (76.1-1ubuntu2) ... 428s Selecting previously unselected package libjpeg-turbo8:arm64. 428s Preparing to unpack .../057-libjpeg-turbo8_2.1.5-3ubuntu2_arm64.deb ... 428s Unpacking libjpeg-turbo8:arm64 (2.1.5-3ubuntu2) ... 428s Selecting previously unselected package libjpeg-turbo8-dev:arm64. 428s Preparing to unpack .../058-libjpeg-turbo8-dev_2.1.5-3ubuntu2_arm64.deb ... 428s Unpacking libjpeg-turbo8-dev:arm64 (2.1.5-3ubuntu2) 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to unpack .../064-liblerc4_4.0.0+ds-5ubuntu1_arm64.deb ... 428s Unpacking liblerc4:arm64 (4.0.0+ds-5ubuntu1) ... 428s Selecting previously unselected package libncurses-dev:arm64. 428s Preparing to unpack .../065-libncurses-dev_6.5+20250216-2_arm64.deb ... 428s Unpacking libncurses-dev:arm64 (6.5+20250216-2) ... 428s Selecting previously unselected package libthai-data. 428s Preparing to unpack .../066-libthai-data_0.1.29-2build1_all.deb ... 428s Unpacking libthai-data (0.1.29-2build1) ... 428s Selecting previously unselected package libthai0:arm64. 428s Preparing to unpack .../067-libthai0_0.1.29-2build1_arm64.deb ... 428s Unpacking libthai0:arm64 (0.1.29-2build1) ... 428s Selecting previously unselected package libpango-1.0-0:arm64. 428s Preparing to unpack .../068-libpango-1.0-0_1.56.3-1_arm64.deb ... 428s Unpacking libpango-1.0-0:arm64 (1.56.3-1) ... 428s Selecting previously unselected package libpangoft2-1.0-0:arm64. 428s Preparing to unpack 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libpcre2-32-0:arm64 (10.45-1) ... 429s Selecting previously unselected package libpcre2-posix3:arm64. 429s Preparing to unpack .../075-libpcre2-posix3_10.45-1_arm64.deb ... 429s Unpacking libpcre2-posix3:arm64 (10.45-1) ... 429s Selecting previously unselected package libpcre2-dev:arm64. 429s Preparing to unpack .../076-libpcre2-dev_10.45-1_arm64.deb ... 429s Unpacking libpcre2-dev:arm64 (10.45-1) ... 429s Selecting previously unselected package libpkgconf3:arm64. 429s Preparing to unpack .../077-libpkgconf3_1.8.1-4_arm64.deb ... 429s Unpacking libpkgconf3:arm64 (1.8.1-4) ... 429s Selecting previously unselected package zlib1g-dev:arm64. 429s Preparing to unpack .../078-zlib1g-dev_1%3a1.3.dfsg+really1.3.1-1ubuntu1_arm64.deb ... 429s Unpacking zlib1g-dev:arm64 (1:1.3.dfsg+really1.3.1-1ubuntu1) ... 429s Selecting previously unselected package libpng-dev:arm64. 429s Preparing to unpack .../079-libpng-dev_1.6.47-1.1_arm64.deb ... 429s Unpacking libpng-dev:arm64 (1.6.47-1.1) ... 429s Selecting previously unselected package libreadline-dev:arm64. 429s Preparing to unpack .../080-libreadline-dev_8.2-6_arm64.deb ... 429s Unpacking libreadline-dev:arm64 (8.2-6) ... 429s Selecting previously unselected package libsharpyuv0:arm64. 429s Preparing to unpack .../081-libsharpyuv0_1.5.0-0.1_arm64.deb ... 429s Unpacking libsharpyuv0:arm64 (1.5.0-0.1) ... 429s Selecting previously unselected package libsm6:arm64. 429s Preparing to unpack .../082-libsm6_2%3a1.2.4-1_arm64.deb ... 429s Unpacking libsm6:arm64 (2:1.2.4-1) ... 429s Selecting previously unselected package libtcl8.6:arm64. 429s Preparing to unpack .../083-libtcl8.6_8.6.16+dfsg-1_arm64.deb ... 429s Unpacking libtcl8.6:arm64 (8.6.16+dfsg-1) ... 429s Selecting previously unselected package libjbig0:arm64. 429s Preparing to unpack .../084-libjbig0_2.1-6.1ubuntu2_arm64.deb ... 429s Unpacking libjbig0:arm64 (2.1-6.1ubuntu2) ... 429s Selecting previously unselected package libwebp7:arm64. 429s Preparing to unpack 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(1:1.2.1-1.2build1) ... 429s Selecting previously unselected package zip. 429s Preparing to unpack .../091-zip_3.0-14ubuntu2_arm64.deb ... 429s Unpacking zip (3.0-14ubuntu2) ... 429s Selecting previously unselected package unzip. 429s Preparing to unpack .../092-unzip_6.0-28ubuntu6_arm64.deb ... 429s Unpacking unzip (6.0-28ubuntu6) ... 430s Selecting previously unselected package xdg-utils. 430s Preparing to unpack .../093-xdg-utils_1.2.1-2ubuntu1_all.deb ... 430s Unpacking xdg-utils (1.2.1-2ubuntu1) ... 430s Selecting previously unselected package r-base-core. 430s Preparing to unpack .../094-r-base-core_4.4.3-1_arm64.deb ... 430s Unpacking r-base-core (4.4.3-1) ... 430s Selecting previously unselected package r-cran-littler. 430s Preparing to unpack .../095-r-cran-littler_0.3.20-2_arm64.deb ... 430s Unpacking r-cran-littler (0.3.20-2) ... 430s Selecting previously unselected package littler. 430s Preparing to unpack .../096-littler_0.3.20-2_all.deb ... 430s Unpacking littler (0.3.20-2) ... 430s Selecting previously unselected package liblzma-dev:arm64. 430s Preparing to unpack .../097-liblzma-dev_5.6.4-1ubuntu1_arm64.deb ... 430s Unpacking liblzma-dev:arm64 (5.6.4-1ubuntu1) ... 430s Selecting previously unselected package pkgconf-bin. 430s Preparing to unpack .../098-pkgconf-bin_1.8.1-4_arm64.deb ... 430s Unpacking pkgconf-bin (1.8.1-4) ... 430s Selecting previously unselected package pkgconf:arm64. 430s Preparing to unpack .../099-pkgconf_1.8.1-4_arm64.deb ... 430s Unpacking pkgconf:arm64 (1.8.1-4) ... 430s Selecting previously unselected package libtirpc-dev:arm64. 430s Preparing to unpack .../100-libtirpc-dev_1.3.4+ds-1.3_arm64.deb ... 430s Unpacking libtirpc-dev:arm64 (1.3.4+ds-1.3) ... 430s Selecting previously unselected package r-base-dev. 430s Preparing to unpack .../101-r-base-dev_4.4.3-1_all.deb ... 430s Unpacking r-base-dev (4.4.3-1) ... 430s Selecting previously unselected package pkg-r-autopkgtest. 430s Preparing to unpack .../102-pkg-r-autopkgtest_20231212ubuntu1_all.deb ... 430s Unpacking pkg-r-autopkgtest (20231212ubuntu1) ... 430s Selecting previously unselected package r-cran-abind. 430s Preparing to unpack .../103-r-cran-abind_1.4-8-1_all.deb ... 430s Unpacking r-cran-abind (1.4-8-1) ... 430s Selecting previously unselected package r-cran-codetools. 430s Preparing to unpack .../104-r-cran-codetools_0.2-20-1_all.deb ... 430s Unpacking r-cran-codetools (0.2-20-1) ... 430s Selecting previously unselected package r-cran-deldir. 430s Preparing to unpack .../105-r-cran-deldir_2.0-4-1build1_arm64.deb ... 430s Unpacking r-cran-deldir (2.0-4-1build1) ... 430s Selecting previously unselected package r-cran-iterators. 430s Preparing to unpack .../106-r-cran-iterators_1.0.14-1_all.deb ... 430s Unpacking r-cran-iterators (1.0.14-1) ... 430s Selecting previously unselected package r-cran-foreach. 430s Preparing to unpack .../107-r-cran-foreach_1.5.2-1_all.deb ... 430s Unpacking r-cran-foreach (1.5.2-1) ... 430s 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431s Unpacking r-cran-rcpp (1.0.14-1) ... 431s Selecting previously unselected package r-cran-rcppeigen. 431s Preparing to unpack .../114-r-cran-rcppeigen_0.3.4.0.2-1_arm64.deb ... 431s Unpacking r-cran-rcppeigen (0.3.4.0.2-1) ... 431s Selecting previously unselected package libjs-mathjax. 431s Preparing to unpack .../115-libjs-mathjax_2.7.9+dfsg-1_all.deb ... 431s Unpacking libjs-mathjax (2.7.9+dfsg-1) ... 432s Selecting previously unselected package r-cran-glmnet. 432s Preparing to unpack .../116-r-cran-glmnet_4.1-8-1_arm64.deb ... 432s Unpacking r-cran-glmnet (4.1-8-1) ... 432s Selecting previously unselected package r-cran-goftest. 432s Preparing to unpack .../117-r-cran-goftest_1.2-3-1_arm64.deb ... 432s Unpacking r-cran-goftest (1.2-3-1) ... 432s Selecting previously unselected package r-cran-gsl. 432s Preparing to unpack .../118-r-cran-gsl_2.1-8-1build1_arm64.deb ... 432s Unpacking r-cran-gsl (2.1-8-1build1) ... 432s Selecting previously unselected package r-cran-nlme. 432s 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libdeflate0:arm64 (1.23-1) ... 433s Setting up libxcb-shm0:arm64 (1.17.0-2) ... 433s Setting up libreadline-dev:arm64 (8.2-6) ... 433s Setting up libgomp1:arm64 (15-20250404-0ubuntu1) ... 433s Setting up libjbig0:arm64 (2.1-6.1ubuntu2) ... 433s Setting up libpcre2-16-0:arm64 (10.45-1) ... 433s Setting up zip (3.0-14ubuntu2) ... 433s Setting up libpcre2-32-0:arm64 (10.45-1) ... 433s Setting up libblas3:arm64 (3.12.1-2) ... 433s update-alternatives: using /usr/lib/aarch64-linux-gnu/blas/libblas.so.3 to provide /usr/lib/aarch64-linux-gnu/libblas.so.3 (libblas.so.3-aarch64-linux-gnu) in auto mode 433s Setting up libtirpc-dev:arm64 (1.3.4+ds-1.3) ... 433s Setting up libpkgconf3:arm64 (1.8.1-4) ... 433s Setting up fonts-dejavu-mono (2.37-8) ... 433s Setting up libmpc3:arm64 (1.3.1-1build2) ... 433s Setting up libtcl8.6:arm64 (8.6.16+dfsg-1) ... 433s Setting up icu-devtools (76.1-1ubuntu2) ... 433s Setting up fonts-dejavu-core (2.37-8) ... 433s Setting up pkgconf-bin (1.8.1-4) ... 433s Setting up libjpeg-turbo8:arm64 (2.1.5-3ubuntu2) ... 433s Setting up libgfortran5:arm64 (15-20250404-0ubuntu1) ... 433s Setting up libwebp7:arm64 (1.5.0-0.1) ... 433s Setting up liblzma-dev:arm64 (5.6.4-1ubuntu1) ... 433s Setting up libubsan1:arm64 (15-20250404-0ubuntu1) ... 433s Setting up zlib1g-dev:arm64 (1:1.3.dfsg+really1.3.1-1ubuntu1) ... 433s Setting up libpcre2-posix3:arm64 (10.45-1) ... 433s Setting up libhwasan0:arm64 (15-20250404-0ubuntu1) ... 433s Setting up libasan8:arm64 (15-20250404-0ubuntu1) ... 433s Setting up libharfbuzz0b:arm64 (10.2.0-1) ... 433s Setting up libthai-data (0.1.29-2build1) ... 433s Setting up libxss1:arm64 (1:1.2.3-1build3) ... 433s Setting up libpaper2:arm64 (2.2.5-0.3) ... 433s Setting up libtsan2:arm64 (15-20250404-0ubuntu1) ... 433s Setting up libisl23:arm64 (0.27-1) ... 433s Setting up libgsl28:arm64 (2.8+dfsg-5ubuntu1) ... 433s Setting up libdeflate-dev:arm64 (1.23-1) ... 433s Setting up libicu-dev:arm64 (76.1-1ubuntu2) ... 433s Setting up xdg-utils (1.2.1-2ubuntu1) ... 433s update-alternatives: using /usr/bin/xdg-open to provide /usr/bin/open (open) in auto mode 433s Setting up libcc1-0:arm64 (15-20250404-0ubuntu1) ... 433s Setting up liblsan0:arm64 (15-20250404-0ubuntu1) ... 433s Setting up libblas-dev:arm64 (3.12.1-2) ... 433s update-alternatives: using /usr/lib/aarch64-linux-gnu/blas/libblas.so to provide /usr/lib/aarch64-linux-gnu/libblas.so (libblas.so-aarch64-linux-gnu) in auto mode 433s Setting up dctrl-tools (2.24-3build3) ... 433s Setting up libitm1:arm64 (15-20250404-0ubuntu1) ... 433s Setting up libbz2-dev:arm64 (1.0.8-6) ... 433s Setting up libjpeg8:arm64 (8c-2ubuntu11) ... 433s Setting up libice6:arm64 (2:1.1.1-1) ... 433s Setting up libjpeg-turbo8-dev:arm64 (2.1.5-3ubuntu2) ... 433s Setting up liblapack3:arm64 (3.12.1-2) ... 433s update-alternatives: using /usr/lib/aarch64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/aarch64-linux-gnu/liblapack.so.3 (liblapack.so.3-aarch64-linux-gnu) in auto mode 433s Setting up libpcre2-dev:arm64 (10.45-1) ... 433s Setting up fontconfig-config (2.15.0-2.2ubuntu1) ... 434s Setting up libpng-dev:arm64 (1.6.47-1.1) ... 434s Setting up libpaper-utils (2.2.5-0.3) ... 434s Setting up pkgconf:arm64 (1.8.1-4) ... 434s Setting up libthai0:arm64 (0.1.29-2build1) ... 434s Setting up liblapack-dev:arm64 (3.12.1-2) ... 434s update-alternatives: using /usr/lib/aarch64-linux-gnu/lapack/liblapack.so to provide /usr/lib/aarch64-linux-gnu/liblapack.so (liblapack.so-aarch64-linux-gnu) in auto mode 434s Setting up cpp-14-aarch64-linux-gnu (14.2.0-19ubuntu2) ... 434s Setting up libtiff6:arm64 (4.5.1+git230720-4ubuntu4) ... 434s Setting up libfontconfig1:arm64 (2.15.0-2.2ubuntu1) ... 434s Setting up libgcc-14-dev:arm64 (14.2.0-19ubuntu2) ... 434s Setting up libjpeg8-dev:arm64 (8c-2ubuntu11) ... 434s Setting up libstdc++-14-dev:arm64 (14.2.0-19ubuntu2) ... 434s Setting up libsm6:arm64 (2:1.2.4-1) ... 434s Setting up libgfortran-14-dev:arm64 (14.2.0-19ubuntu2) ... 434s Setting up fontconfig (2.15.0-2.2ubuntu1) ... 436s Regenerating fonts cache... done. 436s Setting up libxft2:arm64 (2.3.6-1build1) ... 436s Setting up libtk8.6:arm64 (8.6.16-1) ... 436s Setting up libpango-1.0-0:arm64 (1.56.3-1) ... 436s Setting up libjpeg-dev:arm64 (8c-2ubuntu11) ... 436s Setting up libcairo2:arm64 (1.18.4-1) ... 436s Setting up cpp-aarch64-linux-gnu (4:14.2.0-1ubuntu1) ... 436s Setting up libxt6t64:arm64 (1:1.2.1-1.2build1) ... 436s Setting up cpp-14 (14.2.0-19ubuntu2) ... 436s Setting up cpp (4:14.2.0-1ubuntu1) ... 436s Setting up gcc-14-aarch64-linux-gnu (14.2.0-19ubuntu2) ... 436s Setting up libpangoft2-1.0-0:arm64 (1.56.3-1) ... 436s Setting up libpangocairo-1.0-0:arm64 (1.56.3-1) ... 436s Setting up gcc-aarch64-linux-gnu (4:14.2.0-1ubuntu1) ... 436s Setting up g++-14-aarch64-linux-gnu (14.2.0-19ubuntu2) ... 436s Setting up gcc-14 (14.2.0-19ubuntu2) ... 436s Setting up r-base-core (4.4.3-1) ... 436s Creating config file /etc/R/Renviron with new version 436s Setting up r-cran-lattice (0.22-6-1) ... 436s Setting up r-cran-nlme (3.1.168-1) ... 436s Setting up r-cran-spatstat.utils (3.1-3-1) ... 436s Setting up gfortran-14-aarch64-linux-gnu (14.2.0-19ubuntu2) ... 436s Setting up g++-aarch64-linux-gnu (4:14.2.0-1ubuntu1) ... 436s Setting up gfortran-aarch64-linux-gnu (4:14.2.0-1ubuntu1) ... 436s Setting up r-cran-tensor (1.5-4) ... 436s Setting up g++-14 (14.2.0-19ubuntu2) ... 436s Setting up r-cran-pkgkitten (0.2.4-1) ... 436s Setting up gfortran-14 (14.2.0-19ubuntu2) ... 436s Setting up r-cran-spatstat.univar (3.1-2-1) ... 436s Setting up r-cran-littler (0.3.20-2) ... 436s Setting up r-cran-nleqslv (3.3.5-1) ... 436s Setting up r-cran-rcpp (1.0.14-1) ... 436s Setting up r-cran-codetools (0.2-20-1) ... 436s Setting up littler (0.3.20-2) ... 436s Setting up r-cran-gsl (2.1-8-1build1) ... 436s Setting up r-cran-iterators (1.0.14-1) ... 436s Setting up r-cran-spatial (7.3-18-1) ... 436s Setting up r-cran-abind (1.4-8-1) ... 436s Setting up r-cran-foreach (1.5.2-1) ... 436s Setting up r-cran-sm (2.2-6.0-1) ... 436s Setting up r-cran-polyclip (1.10-7-1) ... 436s Setting up gcc (4:14.2.0-1ubuntu1) ... 436s Setting up r-cran-deldir (2.0-4-1build1) ... 436s Setting up r-cran-goftest (1.2-3-1) ... 436s Setting up r-cran-shape (1.4.6.1-1) ... 436s Setting up r-cran-matrix (1.7-3-1) ... 436s Setting up r-cran-spatstat.sparse (3.1-0-1) ... 436s Setting up r-cran-mgcv (1.9-1-1) ... 436s Setting up g++ (4:14.2.0-1ubuntu1) ... 436s update-alternatives: using /usr/bin/g++ to provide /usr/bin/c++ (c++) in auto mode 436s Setting up build-essential (12.12ubuntu1) ... 436s Setting up r-cran-rcppeigen (0.3.4.0.2-1) ... 436s Setting up r-cran-survival (3.8-3-1) ... 436s Setting up gfortran (4:14.2.0-1ubuntu1) ... 436s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f95 (f95) in auto mode 436s 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 436s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f77 (f77) in auto mode 436s 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 436s Setting up r-cran-spatstat.data (3.1-6-1) ... 436s Setting up r-cran-spatstat.geom (3.3-6-1) ... 436s Setting up r-cran-glmnet (4.1-8-1) ... 436s Setting up r-base-dev (4.4.3-1) ... 436s Setting up r-cran-rpart (4.1.24-1) ... 436s Setting up r-cran-spatstat.random (3.3-3-1) ... 436s Setting up r-cran-spatstat.explore (3.3-4-1) ... 436s Setting up pkg-r-autopkgtest (20231212ubuntu1) ... 436s Setting up r-cran-spatstat.model (3.3-4-1) ... 436s Setting up r-cran-spatstat.linnet (3.2-5-1) ... 436s Setting up r-cran-spatstat (3.3-1-1) ... 436s Processing triggers for install-info (7.1.1-1) ... 436s Processing triggers for libc-bin (2.41-6ubuntu1) ... 436s Processing triggers for man-db (2.13.0-1) ... 440s autopkgtest [10:56:23]: test pkg-r-autopkgtest: /usr/share/dh-r/pkg-r-autopkgtest 440s autopkgtest [10:56:23]: test pkg-r-autopkgtest: [----------------------- 440s Test: Try to load the R library spatstat.model 440s 440s R version 4.4.3 (2025-02-28) -- "Trophy Case" 440s Copyright (C) 2025 The R Foundation for Statistical Computing 440s Platform: aarch64-unknown-linux-gnu 440s 440s R is free software and comes with ABSOLUTELY NO WARRANTY. 440s You are welcome to redistribute it under certain conditions. 440s Type 'license()' or 'licence()' for distribution details. 440s 440s R is a collaborative project with many contributors. 440s Type 'contributors()' for more information and 440s 'citation()' on how to cite R or R packages in publications. 440s 440s Type 'demo()' for some demos, 'help()' for on-line help, or 440s 'help.start()' for an HTML browser interface to help. 440s Type 'q()' to quit R. 440s 440s > library('spatstat.model') 440s Loading required package: spatstat.data 441s Loading required package: spatstat.univar 441s spatstat.univar 3.1-2 441s Loading required package: spatstat.geom 441s spatstat.geom 3.3-6 441s Loading required package: spatstat.random 441s spatstat.random 3.3-3 441s Loading required package: spatstat.explore 441s Loading required package: nlme 441s spatstat.explore 3.3-4 441s Loading required package: rpart 441s spatstat.model 3.3-4 441s > 441s > 441s Other tests are currently unsupported! 441s They will be progressively added. 442s autopkgtest [10:56:25]: test pkg-r-autopkgtest: -----------------------] 442s pkg-r-autopkgtest PASS 442s autopkgtest [10:56:25]: test pkg-r-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 443s autopkgtest [10:56:26]: @@@@@@@@@@@@@@@@@@@@ summary 443s run-unit-test PASS 443s pkg-r-autopkgtest PASS 460s nova [W] Using flock in prodstack6-arm64 460s Creating nova instance adt-questing-arm64-r-cran-spatstat.model-20250502-104903-juju-7f2275-prod-proposed-migration-environment-15-c6c746e0-499e-4499-b7d0-dcf388ff46f9 from image adt/ubuntu-questing-arm64-server-20250502.img (UUID a0b7b7fd-ad05-4ea9-97eb-0f52dbbe98e1)... 460s nova [W] Timed out waiting for 6f68f018-48d6-4d28-8947-d8494aaadfd6 to get deleted. 460s nova [W] Using flock in prodstack6-arm64 460s Creating nova instance adt-questing-arm64-r-cran-spatstat.model-20250502-104903-juju-7f2275-prod-proposed-migration-environment-15-c6c746e0-499e-4499-b7d0-dcf388ff46f9 from image adt/ubuntu-questing-arm64-server-20250502.img (UUID a0b7b7fd-ad05-4ea9-97eb-0f52dbbe98e1)... 460s nova [W] Timed out waiting for 4295b5cc-01cd-4a77-a8b4-ba443b819a50 to get deleted.