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evaluate_with_trained_mvsc.py
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evaluate_with_trained_mvsc.py
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from laldetchar.idq import idq
import numpy as np
import ConfigParser
from laldetchar.idq import time_lock as tl
import plotROC as pR
def evaluate_all_combinations(patfile, trainedforestbase, trainedforesttend, config):
original_usertag = config.get("general", "usertag") ### remember what the tag started as
original_variables = config.get("mvsc", "z") ### remember the variables
print (original_variables)
for tstart in ["no_tstart", "yes_tstart"]: ### iterate over all possible combinations
for tend in ["no_tend", "yes_tend"]:
config.set("general", "usertag", "%s-%s-%s"%(original_usertag, tstart, tend) ) ### change the usertag as needed
if(tstart == "no_tstart" and tend == "no_tend"):
config.set("mvsc", "z", "%s,%s,%s"%(original_variables, "time_locked", "time_end"))
elif(tstart == "no_tstart"):
config.set("mvsc", "z", "%s,%s"%(original_variables, "time_locked"))
elif(tend == "no_tend"):
config.set("mvsc", "z", "%s,%s"%(original_variables, "time_end"))
else:
config.set("mvsc","z", original_variables)
trainedforest = trainedforestbase + "%s-%s/"%(tstart,tend) + trainedforestend
ranked_file = trainedforest[:-3] + "dat"
gps_start_time = -np.infty
gps_end_time = np.infty
dir = "."
classifiersD, mla, ovl = idq.config_to_classifiersD( config )
classD = classifiersD['mvsc']
miniconfig = classD['config']
print(ranked_file)
print(trainedforest)
print(config.get("mvsc", "z"))
idq.forest_evaluate(patfile, trainedforest, ranked_file, miniconfig, gps_start_time, gps_end_time, dir)
config.set("general", "usertag", original_usertag)
config.set("mvsc", "z", original_variables)
config = ConfigParser.SafeConfigParser()
patfile = "/home/jessica.hyde/test/dev-branch/now//train/1117329857_1118336935//L1_mla-1117329857-1007078-B.pat"
config.read("/home/jessica.hyde/lalsuites/src/laldetchar/python/laldetchar/idq/idq.ini")
trainedforestbase = "/home/jessica.hyde/test/dev-branch/now//train/1117329857_1118336935//mvsc/"
trainedforestend = "L1_mla-1117329857-1007078-A.spr"
#evaluate_all_combinations(patfile, trainedforestbase, trainedforestend, config)
#pR.plot_ROC_combinations("ER7_ROC_Curves-A.png", 1117329857, 1118336935)
gpsstart = 1117329857
gpsstop = 1118336935
### get start and end seg times formatted as list of lists
tl.get_segments(gpsstart, gpsstop)
scisegs = tl.parse_segments("segment_times.txt")
newsegs = []
for seg in scisegs:
if (seg[1]-seg[0] >= 3600):
newsegs.append(seg)
scisegs=newsegs
for seg in scisegs:
patf = idq.pat("/home/jessica.hyde/test/dev-branch/now/train/%s_%s/" % (gpsstart, gpsstop), "L1", "LowThresh", seg[0], seg[1]-seg[0])
patfile = patf
trainedforestbase = "/home/jessica.hyde/test/dev-branch/now/train/%s_%s/mvsc/" % (gpsstart, gpsstop)
trainedforestend = "L1_mla-%s-%s-A.spr" % (int(seg[0]), int(seg[1]-seg[0]))
evaluate_all_combinations(patfile, trainedforestbase, trainedforestend, config)
pR.plot_ROC_combinations("LowThreshROCSegment%s-%s-A.png" % (seg[0], seg[1]), gpsstart, gpsstop, seg[0], seg[1])
# trainedforestend = "L1_mla-%s-%s-B.spr" % (int(seg[0]), int(seg[1]-seg[0]))
# evaluate_all_combinations(patfile, trainedforestbase, trainedforestend, config)
# pR.plot_ROC_combinations("LowThreshROCSegment%s-%s-B.png" % (seg[0], seg[1]), gpsstart, gpsstop, seg[0], seg[1])
"""for seg in scisegs:
patf = idq.pat("/home/jessica.hyde/test/dev-branch/now/train/%s_%s/" % (gpsstart, gpsstop), "L1", "", seg[0], seg[1]-seg[0])
patfile = patf[:-4] + "-B.pat"
trainedforestbase = "/home/jessica.hyde/test/dev-branch/now/train/%s_%s/mvsc/" % (gpsstart, gpsstop)
trainedforestend = "L1_mla-%s-%s-A.spr" % (int(seg[0]), int(seg[1]-seg[0]))
evaluate_all_combinations(patfile, trainedforestbase, trainedforestend, config)
pR.plot_ROC_combinations("ROCSegment%s-%s.png" % (seg[0], seg[1]), gpsstart, gpsstop, seg[0], seg[1])"""