{"id":18290221,"url":"https://github.com/deshima-dev/kidanalysis-delft","last_synced_at":"2025-08-01T03:37:46.668Z","repository":{"id":241261706,"uuid":"800895316","full_name":"deshima-dev/kidanalysis-delft","owner":"deshima-dev","description":"KID analysis scripts made in Delft","archived":false,"fork":false,"pushed_at":"2024-09-03T13:35:21.000Z","size":279,"stargazers_count":1,"open_issues_count":2,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-15T01:42:35.754Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/deshima-dev.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-15T07:51:25.000Z","updated_at":"2024-09-03T13:35:25.000Z","dependencies_parsed_at":"2024-05-29T04:34:52.580Z","dependency_job_id":"3f1c49ed-78b5-42c6-a332-f63fff86628e","html_url":"https://github.com/deshima-dev/kidanalysis-delft","commit_stats":null,"previous_names":["deshima-dev/kidanalysis-delft"],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deshima-dev%2Fkidanalysis-delft","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deshima-dev%2Fkidanalysis-delft/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deshima-dev%2Fkidanalysis-delft/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deshima-dev%2Fkidanalysis-delft/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/deshima-dev","download_url":"https://codeload.github.com/deshima-dev/kidanalysis-delft/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247996785,"owners_count":21030523,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-05T14:09:54.597Z","updated_at":"2025-04-09T07:26:39.047Z","avatar_url":"https://github.com/deshima-dev.png","language":"Python","readme":"# @ scripts/terahertzsweep\nThese shell scripts are for Toptica THz sweep analysis and Readout power sweep analysis\n## run_sf.sh (for Toptica THz sweep analysis)\n\nex.)\n\n```\n$ ./run_sf.sh /home/deshima/data/LT263_FlightChip/run_20240421_004647/TerahertzScan_20240421_005117/ out_test\n```\n\n```shell\n#!/bin/sh\nNCPU=`python -c \"import multiprocessing as m; print(m.cpu_count() - 1);\"`\n\necho NCPU = $NCPU\n\nfile_dir=$1\nout_dir=$2\n\nlast_dir=$(basename \"$file_dir\")\nsecond_last_dir=$(basename \"$(dirname \"$file_dir\")\")\n\necho ====Configure.py====\necho -e \"${file_dir}\\n/home/deshima/data/analysis/${second_last_dir}/${last_dir}/${out_dir}\" | python Configure.py\n\necho ====FitSweep.py====\npython FitSweep.py\necho ====FitSweep.py --mode plot --ncpu $NCPU====\npython FitSweep.py --mode plot --ncpu $NCPU\n\n\necho ====SaveFits.py====\npython SaveFits.py\necho ====SaveFits.py --mode plot --ncpu $NCPU====\npython SaveFits.py --mode plot --ncpu $NCPU\n\n\necho ====THzFrequencyTOD.py --refvalue 5.0====\npython THzFrequencyTOD.py --refvalue 5.0\necho ====THzFrequencyTOD.py --mode plot --ncpu $NCPU====\npython THzFrequencyTOD.py --mode plot --ncpu $NCPU\n\n\necho ====python AnaSpectrum.py --mode 1 --ncpu $NCPU====\n###python AnaSpectrum.py --mode 1 --ncpu $NCPU\necho ====python AnaSpectrum.py --mode 2====\npython AnaSpectrum.py --mode 2\n\n\necho ====KIDCorresp.py====\npython KIDCorresp.py\n\njson_fullpath=/home/deshima/data/analysis/${second_last_dir}/${last_dir}/${out_dir}/kid_corresp.json\ntimestamp=$(date +\"%Y%m%d_%H%M%S\")\ndestination_base_json=\"/data/spacekids/data/ASTE2024/LT263_FlightChip/kidcorresp\"\nremote_machine=\"aste-d1c\"\nscp ${json_fullpath} ${remote_machine}:${destination_base_json}/${timestamp}_kid_corresp.json\nssh ${remote_machine} \u003c\u003cEOF\nln -sf ${destination_base_json}/${timestamp}_kid_corresp.json /data/spacekids/data/ASTE2024/LT263_FlightChip/kid_corresp.json\nEOF\n\necho ====Symbolic link created   ln -sf ${destination_base_json}/${timestamp}_kid_corresp.json /data/spacekids/data/ASTE2024/LT263_FlightChip/kid_corresp.json\n\nssh desql1 \u003c\u003cEOF\nmkdir -p /home/deshima/data/fujita_analysis/${second_last_dir}/${last_dir}/${out_dir}\nEOF\n\nscp /home/deshima/data/analysis/${second_last_dir}/${last_dir}/${out_dir}/{reference.dat,reference.png,kid_corresp.json} deshima@desql1:/home/deshima/data/fujita_analysis/${second_last_dir}/${last_dir}/${out_dir}/\nscp /home/deshima/data/analysis/${second_last_dir}/${last_dir}/${out_dir}/KIDCorresp/*png deshima@desql1:/home/deshima/data/fujita_analysis/${second_last_dir}/${last_dir}/${out_dir}/\n\n\necho ====FINISHED====\n```\n\nThis is a shell script that executes the following python scripts.\n\nComment out and run it as appropriate.\n\nThe default is to use a maximum of -1 CPU.\n\n* Configure.py\n  * Specify a new directory in which to place the analysis results. If the directory already exists, this will fail.\n* FitSweep.py\n  \\*\n* SaveFits.py\n  \\*\n* THzFrequencyTOD.py\n  * This generates reference.dat, which lists the KIDs that are performing worse than a certain threshold. The threshold value is specified with --refvalue. The higher the threshold value, the fewer KIDs will be listed in reference.dat.\n* AnaSpectrum.py\n  \\*\n* KIDCorresp.py\n  * At the top of the script, specify the appropriate kid_test.db path. Also, edit the \"detector_version =\" line appropriately.\n\nLater in the script, \"kid_corresp.json is transferred to aste-d1c and a symbolic link will be created.\n\n## run_powersweep.sh (for Readout power sweep analysis)\n\nex.)\n\n```\n$ ./run_powersweep.sh ~/data/LT263_FlightChip/widesweep_20240423_140629/run_20240423_140758/ out_test\n```\n\n```shell\n#!/bin/bash\n#NCPU=`python -c \"import multiprocessing as m; print(m.cpu_count() - 1);\"`\n\nfile_dir=$1\nout_dir=$2\n\nlast_dir=$(basename \"$file_dir\")\nsecond_last_dir=$(basename \"$(dirname \"$file_dir\")\")\n\n#for file in ${file_dir}/PreadScan_*; do\n#  echo -e \"${file}/${out_dir}\\ny\" | python Configure.py\n#  python FitSweep.py\n#  python SaveFits.py\n#done\n\nexport file_dir out_dir last_dir second_last_dir\n\ncp ${file_dir}/kids.list /home/deshima/data/analysis/${second_last_dir}/${last_dir}/\nparallel -j 12 --delay 5 '\n  Preaddir=$(basename \"{}\")\n  echo -e \"{}\\n/home/deshima/data/analysis/${second_last_dir}/${last_dir}/${Preaddir}/${out_dir}\" | python Configure.py\n  python FitSweep.py\n  #python SaveFits.py\n' ::: ${file_dir}/PreadScan_*\n\npython AnaPowersweep.py /home/deshima/data/analysis/${second_last_dir}/${last_dir} ${out_dir}\n\n#exit\n\nkids_fullpath=/home/deshima/data/analysis/${second_last_dir}/${last_dir}/kids.list\ntimestamp=$(date +\"%Y%m%d_%H%M%S\")\ndestination_base_kids=\"/data/spacekids/data/ASTE2024/LT263_FlightChip/kidlist\"\nremote_machine=\"aste-d1c\"\nscp ${kids_fullpath} ${remote_machine}:${destination_base_kids}/${timestamp}_kids.list\nssh ${remote_machine} \u003c\u003cEOF\nln -sf ${destination_base_kids}/${timestamp}_kids.list /data/spacekids/data/ASTE2024/LT263_FlightChip/kids.list\nEOF\n\necho ====Symbolic link created   ln -sf ${destination_base_kids}/${timestamp}_kids.list /data/spacekids/data/ASTE2024/LT263_FlightChip/kids.list\n\nssh desql1 \u003c\u003cEOF\nmkdir -p /home/deshima/data/fujita_analysis/${second_last_dir}/${last_dir}/\nEOF\n\nscp /home/deshima/data/analysis/${second_last_dir}/${last_dir}/{fr_list_list.npy,P_list.npy,Freq_center_list_list.npy,kids.list} deshima@desql1:/home/deshima/data/fujita_analysis/${second_last_dir}/${last_dir}/\n\nssh desql1 \u003c\u003cEOF\npython plot_Psweep.py ${second_last_dir}/${last_dir}\nEOF\n\n\n\n```\n\nThis script runs FitSweep.py on multiple data (PreadScan\\_\\*).\n\nIn this script, AnaPowersweep.py has been included.\n\nThis script finds the appropriate read power and writes them (-4 dBm) to \"kids.list\".\n\nThe original \"kids.list\" is renamed with a timestamp.\n\nLater in the script, \"kids.list\" is transferred to aste-d1c and a symbolic link will be created.\n\n\n# @ scripts/aste\nThis shell script is for both Noise analysis and COSMOS data analysis\n## run_sf.sh\n\nex.)\n\n```\n$ ./run_sf.sh /home/deshima/data/LT263_FlightChip/run_20240423_145620/ out_test\n```\n\n```shell\n#!/bin/sh\nNCPU=`python -c \"import multiprocessing as m; print(m.cpu_count() - 1);\"`\n\necho NCPU = $NCPU\n\nfile_dir=$1\nout_dir=$2\n\nlast_dir=$(basename \"$file_dir\")\n#second_last_dir=$(basename \"$(dirname \"$file_dir\")\")\n\necho ====Configure.py====\necho -e \"${file_dir}\\n/home/deshima/data/analysis/${last_dir}/${out_dir}\" | python Configure.py\n\n\necho ====FitSweep.py====\npython FitSweep.py\necho ====FitSweep.py --mode plot --ncpu $NCPU====\npython FitSweep.py --mode plot --ncpu $NCPU\n\n\necho ====SaveFits.py====\npython SaveFits.py\necho ====SaveFits.py --mode plot --ncpu $NCPU====\npython SaveFits.py --mode plot --ncpu $NCPU\n\n\necho ====FINISHED====\n```\n\nThis is a shell script that executes the following python scripts.\n\nComment out and run it as appropriate.\n\nThe default is to use a maximum of -1 CPU.\n\n* Configure.py\n  * Specify a new directory in which to place the analysis results. If the directory already exists, this will fail.\n* FitSweep.py\n  \\*\n* SaveFits.py\n  * Creates reduced fits file\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeshima-dev%2Fkidanalysis-delft","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdeshima-dev%2Fkidanalysis-delft","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeshima-dev%2Fkidanalysis-delft/lists"}