prediction_generation/abed

import copy ############################################################################## # General Settings # ############################################################################## PROJECT_NAME = "cpdbench" TASK_FILE = "abed_tasks.txt" AUTO_FILE = "abed_auto.txt" RESULT_DIR = "./abed_results" STAGE_DIR = "./stagedir" PRUNE_DIR = "./pruned" MAX_FILES = 1000 ZIP_DIR = "./zips" LOG_DIR = "./logs" OUTPUT_DIR = "./output" AUTO_SLEEP = 120 HTML_PORT = 8000 COMPRESSION = "bzip2" RESULT_EXTENSION = ".json" ############################################################################## # Server parameters and settings # ############################################################################## REMOTE_USER = "username" REMOTE_HOST = "address.of.host" REMOTE_DIR = "/home/%s/projects/%s" % (REMOTE_USER, PROJECT_NAME) REMOTE_PORT = 22 REMOTE_SCRATCH = None REMOTE_SCRATCH_ENV = "TMPDIR" ############################################################################## # Settings for Master/Worker program # ############################################################################## MW_SENDATONCE = 1 # number of tasks (hashes!) to send at once MW_COPY_WORKER = False MW_COPY_SLEEP = 120 MW_NUM_WORKERS = None ############################################################################## # Experiment type # ############################################################################## # Uncomment the desired type # Model assessment # TYPE = "ASSESS" # Cross validation with train and test dataset # # TYPE = 'CV_TT' # CV_BASESEED = 123456 # YTRAIN_LABEL = 'y_train' # Commands defined in a text file # # TYPE = 'RAW' # RAW_CMD_FILE = '/path/to/file.txt' ############################################################################## # Build settings # ############################################################################## NEEDS_BUILD = False # If remote compilation is required BUILD_DIR = "build" # Relative directory where build takes place BUILD_CMD = "make all" # Build command ############################################################################## # Experiment parameters and settings # ############################################################################## DATADIR = "datasets" EXECDIR = "execs" DATASETS = DATASETPLACEHOLDER DATASET_NAMES = {k: k for k in DATASETS} ''' METHODS = [ "best_bocpd", # EN COURS (local macmini) "best_cpnp", # EN COURS (local macmini) "best_pelt", # EN COURS (local macmini) "best_amoc", # EN COURS (local macmini) "best_segneigh", "best_binseg", FINIS (remote macmini) "best_rfpop", # FINIS (remote macmini) "best_ecp", # EN COURS (local macmini) "best_kcpa", # FINIS (remote macmini) "best_wbs", # EN COURS (local macmini) "best_prophet", "best_zero", # EN COURS (local macmini) "best_mongodb", # FINIS (remote macmini) "default_bocpd", # EN COURS (local macmini) "default_cpnp", # EN COURS (local macmini) "default_pelt", # EN COURS (local macmini) "default_amoc", # EN COURS (local macmini) "default_segneigh", "default_binseg", FINIS (remote macmini) "default_rfpop", # FINIS (remote macmini) "default_ecp", # EN COURS (local macmini) "default_kcpa", # FINIS (remote macmini) "default_wbs", # EN COURS (local macmini) "default_prophet", "default_zero", # EN COURS (local macmini) "default_mongodb", # FINIS (remote macmini) ] ''' METHODS = [ "best_mozilla_rep", "default_mozilla_rep", ] # many of these combinations will be invalid for the changepoint package, but # it's easier to do it this way than to generate only the valid configurations. R_changepoint_params = { "function": ["mean", "var", "meanvar"], "penalty": [ "None", "SIC", "BIC", "MBIC", "AIC", "Hannan-Quinn", "Asymptotic", ], "statistic": ["Normal", "CUSUM", "CSS", "Gamma", "Exponential", "Poisson"], } R_changepoint_params_seg = copy.deepcopy(R_changepoint_params) R_changepoint_params_seg["Q"] = ["max", "default"] PARAMS = { "best_bocpd": { "intensity": [50, 100, 200], "prior_a": [0.01, 1.0, 100], "prior_b": [0.01, 1.0, 100], "prior_k": [0.01, 1.0, 100], }, "best_cpnp": { "penalty": [ "None", "SIC", "BIC", "MBIC", "AIC", "Hannan-Quinn", "Asymptotic", ], "quantiles": [10, 20, 30, 40], }, "best_pelt": R_changepoint_params, "best_amoc": R_changepoint_params, "best_segneigh": R_changepoint_params_seg, "best_binseg": R_changepoint_params_seg, "best_rfpop": {"loss": ["L1", "L2", "Huber", "Outlier"]}, "best_ecp": { "algorithm": ["e.agglo", "e.divisive"], "siglvl": [0.01, 0.05], "minsize": [2, 30], "alpha": [0.5, 1.0, 1.5], "runs": [100, 200, 500], }, "best_kcpa": { "maxcp": [2, 5, 10], "minsize": [2, 3, 5], "kernel": ["linear", "rbf"] }, "best_wbs": { "Kmax": ["max", "default"], "penalty": ["SSIC", "BIC", "MBIC"], "integrated": ["true", "false"], }, "best_prophet": {"Nmax": ["max", "default"], "ChangepointRange": [0.6, 0.8, 0.95], "ChangepointPriorScale": [0.001, 0.1, 0.5], "IntervalWidth": [0.6, 0.8, 0.95], "growth": ['linear', 'logistic'] }, "best_zero": {"no_param": [0]}, "best_mongodb": { "pvalue": [0.01, 0.05], "permutations": [10, 20, 50, 100, 150, 200], }, "best_mozilla_rep": {"no_param": [0]}, "default_bocpd": {"no_param": [0]}, "default_cpnp": {"no_param": [0]}, "default_pelt": {"no_param": [0]}, "default_amoc": {"no_param": [0]}, "default_segneigh": {"no_param": [0]}, "default_binseg": {"no_param": [0]}, "default_rfpop": {"no_param": [0]}, "default_ecp": {"no_param": [0]}, "default_kcpa": {"no_param": [0]}, "default_wbs": {"no_param": [0]}, "default_prophet": {"no_param": [0]}, "default_zero": {"no_param": [0]}, "default_mongodb": {"no_param": [0]}, "default_mozilla_rep": {"no_param": [0]} } ''' "best_prophet": {"Nmax": ["max", "default"]}, ''' COMMANDS = { "best_amoc": "Rscript --no-save --slave {execdir}/R/cpdbench_changepoint.R -i {datadir}/{dataset}.json -p {penalty} -f {function} -t {statistic} -m AMOC", "best_binseg": "Rscript --no-save --slave {execdir}/R/cpdbench_changepoint.R -i {datadir}/{dataset}.json -p {penalty} -f {function} -t {statistic} -m BinSeg -Q {Q}", "best_cpnp": "Rscript --no-save --slave {execdir}/R/cpdbench_changepointnp.R -i {datadir}/{dataset}.json -p {penalty} -q {quantiles}", "best_ecp": "Rscript {execdir}/R/cpdbench_ecp.R -i {datadir}/{dataset}.json --siglvl {siglvl} --minsize {minsize} --alpha {alpha} --algorithm {algorithm} --runs {runs}", "best_kcpa": "python3.9 {execdir}/python/cpdbench_kcpa.py -i {datadir}/{dataset}.json --maxcp {maxcp} --minsize {minsize} --kernel {kernel}", "best_pelt": "Rscript --no-save --slave {execdir}/R/cpdbench_changepoint.R -i {datadir}/{dataset}.json -p {penalty} -f {function} -t {statistic} -m PELT", "best_prophet": "source {execdir}/python/venv/bin/activate && python {execdir}/python/cpdbench_prophet.py -i {datadir}/{dataset}.json -N {Nmax} --WeeklySeasonality True --DailySeasonality False --ChangepointRange {ChangepointRange} --ChangepointPriorScale {ChangepointPriorScale} --IntervalWidth {IntervalWidth} --growth {growth} --cap 100", "best_rfpop": "Rscript --no-save --slave {execdir}/R/cpdbench_rfpop.R -i {datadir}/{dataset}.json -l {loss}", "best_segneigh": "Rscript --no-save --slave {execdir}/R/cpdbench_changepoint.R -i {datadir}/{dataset}.json -p {penalty} -f {function} -t {statistic} -m SegNeigh -Q {Q}", "best_wbs": "Rscript --no-save --slave {execdir}/R/cpdbench_wbs.R -i {datadir}/{dataset}.json -K {Kmax} --penalty {penalty} -g {integrated}", "best_bocpd": "Rscript --no-save --slave {execdir}/R/cpdbench_ocp.R -i {datadir}/{dataset}.json -l {intensity} --prior-a {prior_a} --prior-b {prior_b} --prior-k {prior_k}", "best_zero": "python3.9 {execdir}/python/cpdbench_zero.py -i {datadir}/{dataset}.json", "best_mongodb": "source {execdir}/python/venv/bin/activate && python {execdir}/python/cpdbench_mongodb.py -i {datadir}/{dataset}.json --pvalue {pvalue} --permutations {permutations}", "best_mozilla_rep": "python3.9 {execdir}/python/cpdbench_mozilla_rep.py -i {datadir}/{dataset}.json -a /TCPDBench/analysis/annotations/signatures_attributes.json", "default_amoc": "Rscript --no-save --slave {execdir}/R/cpdbench_changepoint.R -i {datadir}/{dataset}.json -p MBIC -f mean -t Normal -m AMOC", "default_binseg": "Rscript --no-save --slave {execdir}/R/cpdbench_changepoint.R -i {datadir}/{dataset}.json -p MBIC -f mean -t Normal -m BinSeg -Q default", "default_cpnp": "Rscript --no-save --slave {execdir}/R/cpdbench_changepointnp.R -i {datadir}/{dataset}.json -p MBIC -q 10", "default_pelt": "Rscript --no-save --slave {execdir}/R/cpdbench_changepoint.R -i {datadir}/{dataset}.json -p MBIC -f mean -t Normal -m PELT", "default_segneigh": "Rscript --no-save --slave {execdir}/R/cpdbench_changepoint.R -i {datadir}/{dataset}.json -p BIC -f mean -t Normal -m SegNeigh -Q default", "default_wbs": "Rscript --no-save --slave {execdir}/R/cpdbench_wbs.R -i {datadir}/{dataset}.json -K default -p SSIC -g true", "default_prophet": "source {execdir}/python/venv/bin/activate && python {execdir}/python/cpdbench_prophet.py -i {datadir}/{dataset}.json -N default --WeeklySeasonality True --DailySeasonality False --ChangepointRange 0.8 --ChangepointPriorScale 0.05 --IntervalWidth 0.8 --growth linear --cap 1000", "default_rfpop": "Rscript --no-save --slave {execdir}/R/cpdbench_rfpop.R -i {datadir}/{dataset}.json -l Outlier", "default_ecp": "Rscript {execdir}/R/cpdbench_ecp.R -i {datadir}/{dataset}.json --alpha 2.0 --minsize 5 --algorithm e.divisive --siglvl 0.05 --runs 199", "default_kcpa": "python3.9 {execdir}/python/cpdbench_kcpa.py -i {datadir}/{dataset}.json --maxcp 2 --minsize 3 --kernel linear", "default_bocpd": "Rscript --no-save --slave {execdir}/R/cpdbench_ocp.R -i {datadir}/{dataset}.json -l 100 --prior-a 1.0 --prior-b 1.0 --prior-k 1.0", "default_zero": "python3.9 {execdir}/python/cpdbench_zero.py -i {datadir}/{dataset}.json", "default_mongodb": "source {execdir}/python/venv/bin/activate && python {execdir}/python/cpdbench_mongodb.py -i {datadir}/{dataset}.json", "default_mozilla_rep": "python3.9 {execdir}/python/cpdbench_mozilla_rep.py -i {datadir}/{dataset}.json -a /TCPDBench/analysis/annotations/signatures_attributes.json", } METRICS = {} SCALARS = {"time": {"best": min}} RESULT_PRECISION = 15 DATA_DESCRIPTION_CSV = None REFERENCE_METHOD = None SIGNIFICANCE_LEVEL = 0.05 ############################################################################### # PBS Settings # ############################################################################### PBS_NODES = 1 PBS_WALLTIME = 360 # Walltime in minutes PBS_CPUTYPE = None PBS_CORETYPE = None PBS_PPN = None PBS_MODULES = ["mpicopy", "python/3.9.6"] PBS_EXPORTS = ["PATH=$PATH:/home/%s/.local/bin/abed" % REMOTE_USER] PBS_MPICOPY = ["datasets", "execs", TASK_FILE] PBS_TIME_REDUCE = 600 # Reduction of runtime in seconds PBS_LINES_BEFORE = [] PBS_LINES_AFTER = []

prediction_generation/abed_conf.py (200 lines of code) (raw):