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slurm-batch-all.sh
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slurm-batch-all.sh
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#!/bin/zsh
datasets=(
# tranche 1
"IOPS/KPI-a8c06b47-cc41-3738-9110-12df0ee4c721"
"IOPS/KPI-c69a50cf-ee03-3bd7-831e-407d36c7ee91"
"IOPS/KPI-05f10d3a-239c-3bef-9bdc-a2feeb0037aa"
"IOPS/KPI-f0932edd-6400-3e63-9559-0a9860a1baa9"
"IOPS/KPI-57051487-3a40-3828-9084-a12f7f23ee38"
"IOPS/KPI-847e8ecc-f8d2-3a93-9107-f367a0aab37d"
"IOPS/KPI-431a8542-c468-3988-a508-3afd06a218da"
"IOPS/KPI-1c6d7a26-1f1a-3321-bb4d-7a9d969ec8f0"
"IOPS/KPI-ffb82d38-5f00-37db-abc0-5d2e4e4cb6aa"
"IOPS/KPI-54350a12-7a9d-3ca8-b81f-f886b9d156fd"
"KDD-TSAD/152_UCR_Anomaly_PowerDemand1"
"KDD-TSAD/114_UCR_Anomaly_CIMIS44AirTemperature2"
"KDD-TSAD/163_UCR_Anomaly_apneaecg2"
"KDD-TSAD/030_UCR_Anomaly_DISTORTEDInternalBleeding19"
"KDD-TSAD/070_UCR_Anomaly_DISTORTEDltstdbs30791AI"
"KDD-TSAD/102_UCR_Anomaly_NOISEMesoplodonDensirostris"
"KDD-TSAD/022_UCR_Anomaly_DISTORTEDGP711MarkerLFM5z4"
"KDD-TSAD/174_UCR_Anomaly_insectEPG2"
"KDD-TSAD/202_UCR_Anomaly_CHARISfive"
"KDD-TSAD/208_UCR_Anomaly_CHARISten"
"MGAB/2"
"MGAB/3"
"MGAB/4"
"MGAB/6"
"NAB/art_increase_spike_density"
"NAB/ec2_network_in_257a54"
"NAB/Twitter_volume_AMZN"
"NAB/rds_cpu_utilization_e47b3b"
"NAB/ec2_cpu_utilization_24ae8d"
"NAB/art_load_balancer_spikes"
"NAB/ec2_cpu_utilization_5f5533"
"NAB/Twitter_volume_CVS"
"NAB/rds_cpu_utilization_cc0c53"
"NAB/art_daily_jumpsdown"
"NASA-MSL/P-15"
"NASA-MSL/T-12"
"NASA-MSL/C-2"
"NASA-MSL/T-5"
"NASA-MSL/M-7"
"NASA-MSL/P-14"
"NASA-MSL/F-5"
"NASA-MSL/D-14"
"NASA-MSL/T-8"
"NASA-MSL/M-6"
"NASA-SMAP/P-4"
"NASA-SMAP/E-5"
"NASA-SMAP/G-3"
"NASA-SMAP/E-7"
"NASA-SMAP/D-13"
"NASA-SMAP/D-5"
"NASA-SMAP/S-1"
"NASA-SMAP/G-4"
"NASA-SMAP/E-1"
"NASA-SMAP/A-1"
"NormA/Discords_annsgun"
"NormA/Discords_dutch_power_demand"
"NormA/Discords_marotta_valve_tek_14"
"NormA/Discords_marotta_valve_tek_17"
"NormA/SinusRW_Length_106000_AnomalyL_100_AnomalyN_60_NoisePerc_0"
"NormA/SinusRW_Length_104000_AnomalyL_200_AnomalyN_20_NoisePerc_0"
"NormA/SinusRW_Length_108000_AnomalyL_200_AnomalyN_40_NoisePerc_0"
"TSB-UAD-artificial/-37_2_0.02_25"
"TSB-UAD-artificial/-69_2_0.02_15"
"TSB-UAD-artificial/-69_2_0.02_25"
"TSB-UAD-artificial/-104_2_0.02_35"
"TSB-UAD-synthetic/YAHOO_flat_region_0.02-Yahoo_A2synthetic_41_data"
"TSB-UAD-synthetic/YAHOO_add_random_walk_trend_0.2-YahooA4Benchmark-TS28_data"
"TSB-UAD-synthetic/YAHOO_change_segment_resampling_0.08-Yahoo_A2synthetic_93_data"
"TSB-UAD-synthetic/YAHOO_change_segment_resampling_0.04-Yahoo_A2synthetic_32_data"
"TSB-UAD-synthetic/YAHOO_change_segment_resampling_0.02-YahooA3Benchmark-TS84_data"
"TSB-UAD-synthetic/YAHOO_flat_region_0.02-Yahoo_A1real_14_data"
"TSB-UAD-synthetic/KDD21_change_segment_resampling_0.02-006_UCR_Anomaly_DISTORTEDCIMIS44AirTemperature2_4000_5703_5727"
"TSB-UAD-synthetic/YAHOO_flip_segment_0.08-YahooA4Benchmark-TS55_data"
"TSB-UAD-synthetic/YAHOO_change_segment_resampling_0.04-YahooA3Benchmark-TS85_data"
"TSB-UAD-synthetic/YAHOO_flat_region_0.04-YahooA3Benchmark-TS51_data"
"WebscopeS5/A4Benchmark-63"
"WebscopeS5/A2Benchmark-22"
"WebscopeS5/A1Benchmark-2"
"WebscopeS5/A4Benchmark-13"
"WebscopeS5/A1Benchmark-25"
"WebscopeS5/A4Benchmark-34"
"WebscopeS5/A1Benchmark-34"
"WebscopeS5/A4Benchmark-2"
"WebscopeS5/A3Benchmark-54"
"WebscopeS5/A3Benchmark-18"
# tranche 2
"IOPS/KPI-6a757df4-95e5-3357-8406-165e2bd49360"
"IOPS/KPI-7103fa0f-cac4-314f-addc-866190247439"
"IOPS/KPI-4d2af31a-9916-3d9f-8a8e-8a268a48c095"
"IOPS/KPI-c02607e8-7399-3dde-9d28-8a8da5e5d251"
"KDD-TSAD/011_UCR_Anomaly_DISTORTEDECG1"
"KDD-TSAD/031_UCR_Anomaly_DISTORTEDInternalBleeding20"
"KDD-TSAD/058_UCR_Anomaly_DISTORTEDapneaecg"
"KDD-TSAD/074_UCR_Anomaly_DISTORTEDqtdbSel1005V"
"KDD-TSAD/095_UCR_Anomaly_NOISECIMIS44AirTemperature4"
"KDD-TSAD/098_UCR_Anomaly_NOISEInternalBleeding16"
"KDD-TSAD/131_UCR_Anomaly_GP711MarkerLFM5z5"
"KDD-TSAD/147_UCR_Anomaly_Lab2Cmac011215EPG3"
"KDD-TSAD/154_UCR_Anomaly_PowerDemand3"
"KDD-TSAD/232_UCR_Anomaly_mit14134longtermecg"
"NAB/Twitter_volume_FB"
"NAB/Twitter_volume_GOOG"
"NAB/art_daily_flatmiddle"
"NAB/cpu_utilization_asg_misconfiguration"
"NAB/ec2_cpu_utilization_ac20cd"
"NAB/ec2_request_latency_system_failure"
"NAB/exchange-3_cpm_results"
"NAB/machine_temperature_system_failure"
"NAB/occupancy_t4013"
"NAB/speed_6005"
"NASA-MSL/F-7"
"NASA-MSL/P-10"
"NASA-MSL/P-11"
"NASA-MSL/S-2"
"NASA-MSL/T-4"
"NASA-SMAP/A-2"
"NASA-SMAP/A-3"
"NASA-SMAP/A-5"
"NASA-SMAP/B-1"
"NASA-SMAP/D-8"
"NASA-SMAP/E-6"
"NASA-SMAP/G-1"
"NASA-SMAP/G-2"
"NASA-SMAP/G-6"
"NASA-SMAP/G-7"
"TSB-UAD-synthetic/KDD21_change_segment_resampling_0.02-033_UCR_Anomaly_DISTORTEDInternalBleeding5_4000_6200_6370"
"TSB-UAD-synthetic/KDD21_change_segment_resampling_0.02-074_UCR_Anomaly_DISTORTEDqtdbSel1005V_4000_12400_12800"
"TSB-UAD-synthetic/KDD21_flat_region_0.02-104_UCR_Anomaly_NOISEapneaecg4_6000_16000_16100"
"TSB-UAD-synthetic/KDD21_flip_segment_0.02-210_UCR_Anomaly_Italianpowerdemand_36123_74900_74996"
"TSB-UAD-synthetic/YAHOO_add_random_walk_trend_0.2-YahooA3Benchmark-TS75_data"
"TSB-UAD-synthetic/YAHOO_add_random_walk_trend_0.2-Yahoo_A1real_32_data"
"TSB-UAD-synthetic/YAHOO_change_segment_add_scale_0.02-YahooA3Benchmark-TS22_data"
"TSB-UAD-synthetic/YAHOO_change_segment_add_scale_0.02-YahooA4Benchmark-TS28_data"
"TSB-UAD-synthetic/YAHOO_flat_region_0.08-YahooA4Benchmark-TS33_data"
"TSB-UAD-synthetic/YAHOO_flat_region_0.08-Yahoo_A2synthetic_1_data"
"WebscopeS5/A1Benchmark-27"
"WebscopeS5/A2Benchmark-41"
"WebscopeS5/A2Benchmark-67"
"WebscopeS5/A2Benchmark-83"
"WebscopeS5/A3Benchmark-44"
"WebscopeS5/A3Benchmark-61"
"WebscopeS5/A3Benchmark-83"
"WebscopeS5/A4Benchmark-67"
"WebscopeS5/A4Benchmark-88"
"WebscopeS5/A4Benchmark-92"
)
gutentag_datasets=(
# tranche 1
"poly-diff-count-5"
"rw-combined-diff-2"
"ecg-same-count-1"
"ecg-type-pattern-shift"
"sinus-position-middle"
"rw-length-100"
"sinus-type-mean"
"poly-length-500"
"ecg-type-mean"
"ecg-diff-count-1"
# tranche 2
"cbf-position-middle"
"ecg-diff-count-8"
"ecg-same-count-2"
"ecg-type-trend"
"poly-diff-count-2"
"poly-length-10"
"poly-trend-linear"
"rw-combined-diff-1"
"sinus-diff-count-2"
"sinus-length-50"
)
sand_datasets=(
"803"
"806"
"SED"
"803_806"
"803_820"
"803_SED"
"806_SED"
"803_805_820"
"805_806_820"
"803_805_806_820"
"803_806_820_SED"
)
synthetic_datasets=(
"gt-0"
# "gt-1"
"gt-2"
"gt-3"
"gt-4"
# "gt-5"
# "gt-6"
# "gt-7"
# "gt-8"
# "gt-9"
)
n_jobs=1
# without data cleaning
export AUTOTSAD__DATA_GEN__DISABLE_CLEANING="no"
# for default ensemble baseline:
export AUTOTSAD__OPTIMIZATION__DISABLED="yes"
# for single-threaded runtime
export AUTOTSAD__GENERAL__N_JOBS="${n_jobs}"
for d in "${datasets[@]}"; do
echo "Submitting Job >AutoTSAD ${d} p=${n_jobs}<"
sbatch -J "AutoTSAD ${d//\// } p=${n_jobs}" slurm-run.sh "${HOME}/data/benchmark-data/univariate/${d}.test.csv"
sleep 0.5
done
for d in "${gutentag_datasets[@]}"; do
echo "Submitting Job >AutoTSAD ${d} p=${n_jobs}<"
sbatch -J "AutoTSAD GutenTAG ${d//\// } p=${n_jobs}" slurm-run.sh "${HOME}/data/univariate-anomaly-test-cases/${d}/test.csv"
sleep 0.5
done
for d in "${sand_datasets[@]}"; do
echo "Submitting Job >AutoTSAD ${d} p=${n_jobs}<"
sbatch -J "AutoTSAD SAND ${d//\// } p=${n_jobs}" slurm-run.sh "${HOME}/data/sand-data/${d}.csv"
sleep 0.5
done
# for d in "${synthetic_datasets[@]}"; do
# echo "Submitting Job >AutoTSAD ${d}<"
# sbatch -J "AutoTSAD synthetic ${d//\// }" slurm-run.sh "${HOME}/data/autotsad-data/synthetic/${d}.csv"
# sleep 0.5
# done
# scaling experiments
#datasets=(
# "KDD-TSAD/022_UCR_Anomaly_DISTORTEDGP711MarkerLFM5z4"
# "TSB-UAD-artificial/-69_2_0.02_15"
#)
#n_jobs=(
# 1
# 5
# 10
# 40
# 80
#)
#cpus = (
# 2
# 10
# 15
# 60
# 120
#)
#for d in "${datasets[@]}"; do
# for (( i=1; i<=${#n_jobs[@]}; ++i)); do
# p="${n_jobs[$i]}"
# c="${cpus[$i]}"
# m="$((c*2))G"
# echo "Submitting Job >AutoTSAD p=${p} ${d}< (cpus=${c}, mem=${m})"
# export AUTOTSAD__GENERAL__N_JOBS="${p}"
# sbatch -J "AutoTSAD ${p} ${d//\// }" --cpus-per-task="${c}" --mem="${m}" slurm-run.sh "${HOME}/data/benchmark-data/univariate/${d}.test.csv"
# sleep 0.5
# done
#done
# Optimization experiments
#dataset="TSB-UAD-synthetic/KDD21_change_segment_resampling_0.02-006_UCR_Anomaly_DISTORTEDCIMIS44AirTemperature2_4000_5703_5727"
#seeds=(
## 1
## 2
# 3
## 4
## 5
## 6
# 7
# 8
## 9
## 10
#)
#max_trialss=(
# 200
# 400
# 800
# 1600
#)
#for max_trials in "${max_trialss[@]}"; do
# for seed in "${seeds[@]}"; do
# echo "Submitting Job >AutoTSAD n=${max_trials} seed=${seed}<"
# export AUTOTSAD__GENERAL__SEED="${seed}"
# export AUTOTSAD__OPTIMIZATION__MAX_TRAILS_PER_STUDY="${max_trials}"
# export AUTOTSAD__OPTIMIZATION__N_TRIALS_STEP="$(( max_trials / 10 ))"
# sbatch -J "AutoTSAD ${max_trials} ${seed}" slurm-run.sh "${HOME}/data/benchmark-data/univariate/${dataset}.test.csv"
# sleep 0.5
# done
#done