ths_unq = _N.unique(ths)
interiorPts = _N.setdiff1d(_N.arange(len(x)), ths_unq)
#print("%(ths)d" % {"ths" : len(ths)})
return _ss.pearsonr(x[interiorPts], y[interiorPts])
# (12)
# (13)
# possible 2-patterns
#
oldnew = "new"
if oldnew == "old":
dates = _rt.date_range(start='7/13/2021', end='08/17/2021')
elif oldnew == "new":
dates = _rt.date_range(start='08/18/2021', end='10/30/2021')
partIDs, dats, cnstrs = _rt.filterRPSdats("TMB1", dates, visits=[1], domainQ=_rt._TRUE_ONLY_, demographic=_rt._TRUE_AND_FALSE_, mentalState=_rt._TRUE_AND_FALSE_, minIGI=300, maxIGI=30000, MinWinLossRat=0., has_useragent=True, has_start_and_end_times=True, has_constructor=True, blocks=4)
pid = 0
netwins = _N.empty((4, len(partIDs)))
win_aft_win = _N.empty((4, len(partIDs)))
win_aft_los = _N.empty((4, len(partIDs)))
win_aft_tie = _N.empty((4, len(partIDs)))
netwin_aft_win = _N.empty((4, len(partIDs)))
netwin_aft_los = _N.empty((4, len(partIDs)))
netwin_aft_tie = _N.empty((4, len(partIDs)))
tie_aft_win = _N.empty((4, len(partIDs)))
#partIDs7=["20201122_1108-25", "20201121_1959-30", "20201121_2131-38"]
#partIDs7 = ["20200410_2203-19", "20200410_2248-43", "20200415_2034-12", "20200418_2148-58"]
#partIDs7 = ["20200410_2248-43"]
if data == "EEG1":
partIDs = partIDs1 + partIDs2 + partIDs3 + partIDs4 + partIDs5 + partIDs6# + partIDs7
if data == "RAND":
USE = 43
_partIDs = os.listdir("/Users/arai/Sites/taisen/DATA/RAND/20210803")
partIDs = []
these = _N.random.choice(_N.arange(len(_partIDs)), USE)
for i in range(USE):
partIDs.append(_partIDs[these[i]])
if data == "TMB2":
dates = _rt.date_range(start='7/13/2021', end='08/30/2021')
#dates = _rt.date_range(start='7/13/2021', end='07/27/2021')
#dates = _rt.date_range(start='7/27/2021', end='08/20/2021')
#dates = _rt.date_range(start='07/27/2021', end='08/20/2021')
#dates = _rt.date_range(start='07/13/2021', end='07/27/2021')
#partIDs, dats, cnstrs = _rt.filterRPSdats(data, dates, visits=[1], domainQ=_rt._TRUE_AND_FALSE_, demographic=_rt._TRUE_AND_FALSE_, mentalState=_rt._TRUE_AND_FALSE_, minIGI=800, MinWinLossRat=0.7, has_useragent=True, has_start_and_end_times=True, has_constructor=True, blocks=1)
#partIDs, dats, cnstrs = _rt.filterRPSdats(data, dates, visits=[1], domainQ=_rt._TRUE_ONLY_, demographic=_rt._TRUE_AND_FALSE_, mentalState=_rt._TRUE_AND_FALSE_, minIGI=800, MinWinLossRat=0.7, has_useragent=True, has_start_and_end_times=True, has_constructor=True, blocks=1)
partIDs, dats, cnstrs = _rt.filterRPSdats(data, dates, visits=[1], domainQ=(_rt._TRUE_ONLY_ if look_at_AQ else _rt._TRUE_AND_FALSE_), demographic=_rt._TRUE_AND_FALSE_, mentalState=_rt._TRUE_AND_FALSE_, minIGI=650, maxIGI=30000, MinWinLossRat=0.3, has_useragent=True, has_start_and_end_times=True, has_constructor=True, blocks=1)
A1 = []
show_shuffled = False
process_keyval_args(globals(), sys.argv[1:])
#######################################################
MULT = 1. # kernel width
fxdGK = None
sys.exit()
if sys.argv[1] == "TMB2":
expt = sys.argv[1]
else:
expt = "TMB1"
old_TMB1 = False
if sys.argv[1] == "TMB1_o":
old_TMB1 = True
#######################################
####################################### where TMB1 and TMB2 directories are
zipped_dir = "/Users/arai/Sites/taisen/DATA/%s" % expt
#dates = ["20210723"]
dates = _rt.date_range(start='7/13/2021', end='12/30/2022')
if (expt == "TMB1"):
if old_TMB1:
dates = _rt.date_range(start='7/13/2021', end='8/17/2021')
else:
dates = _rt.date_range(start='8/18/2021', end='11/30/2021')
#dates = pd.date_range(start='7/1/2021', end='7/31/2021')
for date in dates:
# _date = "%(yr)d%(mn)2d%(dy)2d" % {"yr" : date_tmstmp.year, "mn" : date_tmstmp.month, "dy" : date_tmstmp.day}
# date = _date.replace(" ", "0")
hr = 0
mn = 0
_ME_WTL = 0
_ME_RPS = 1
_SHFL_KEEP_CONT = 0
_SHFL_NO_KEEP_CONT = 1
def depickle(s):
import pickle
with open(s, "rb") as f:
lm = pickle.load(f)
return lm
#dates = _rt.date_range(start='7/13/2021', end='8/17/2021')
dates = _rt.date_range(start='8/18/2021', end='11/30/2021')
nicknames = {
"FixedSequence(__moRSP__, " + "[1, 1, 2, 1, 3, 1, 1, 1, 1, 3, " + "1, 1, 2, 1, 1, 1, 1, 1, 1, 3, " + "1, 1, 2, 1, 1, 3, 1, 2, 1, 1, " + "2, 1, 1, 1, 3, 1, 1, 1, 1, 1]);":
"Biased_Random",
#
"FixedSequencen(__moRSP__, " + "[3, 1, 2, 3, 2, 1, 2, 3, 3, 1, " + "1, 1, 2, 1, 3, 3, 2, 1, 2, 3, " + "3, 1, 2, 1, 2, 1, 3, 2, 2, 3, " + "2, 1, 3, 3, 2, 2, 3, 1, 3, 1]);":
"Unbiased_Random",
#
"WTL(__moRSP__, " + "[0.05, 0.85, 0.1], [1/3, 1/3, 1/3], [1/3, 1/3, 1/3], false);":
"Exploitable_Win",
#
"Mimic(__moRSP__, 0, 0.2);":
"Mimic"
}
import AIiRPS.constants as _cnst
from AIiRPS.utils.dir_util import getResultFN
import GCoh.datconfig as datconf
def depickle(s):
import pickle
with open(s, "rb") as f:
lm = pickle.load(f)
return lm
data = "TMB2"
if data == "TMB1":
dates = _rt.date_range(start='7/13/2021', end='11/10/2021')
partIDs, dats, cnstrs = _rt.filterRPSdats(data,
dates,
visits=[1],
domainQ=_rt._TRUE_AND_FALSE_,
demographic=_rt._TRUE_ONLY_,
mentalState=_rt._TRUE_AND_FALSE_,
minIGI=400,
maxIGI=30000,
MinWinLossRat=0.1,
has_useragent=True,
has_start_and_end_times=True,
has_constructor=True,
blocks=4)
if data == "TMB2":
dates = _rt.date_range(start='7/13/2021', end='11/10/2021')
