def make_cutDict(cut, inputDict=None):
global c
c = klt.pyPlot(REPLAYPATH, readDict)
x = c.w_dict(cut)
# print("%s" % cut)
# print("x ", x)
if inputDict == None:
inputDict = {}
for key, val in readDict.items():
if key == cut:
inputDict.update({key: {}})
for i, val in enumerate(x):
tmp = x[i]
if tmp == "":
continue
else:
inputDict[cut].update(eval(tmp))
return inputDict
T_coin_pTRIG1_ROC1_tdcTime = tree.array("T.coin.pTRIG1_ROC1_tdcTime")
T_coin_pTRIG3_ROC1_tdcTime = tree.array("T.coin.pTRIG3_ROC1_tdcTime")
T_coin_pTRIG5_ROC1_tdcTime = tree.array("T.coin.pTRIG5_ROC1_tdcTime")
T_coin_pTRIG1_ROC2_tdcTime = tree.array("T.coin.pTRIG1_ROC2_tdcTime")
T_coin_pTRIG3_ROC2_tdcTime = tree.array("T.coin.pTRIG3_ROC2_tdcTime")
T_coin_pTRIG5_ROC2_tdcTime = tree.array("T.coin.pTRIG5_ROC2_tdcTime")
T_coin_pEDTM_tdcTime = tree.array("T.coin.pEDTM_tdcTime")
EvtType = tree.array("fEvtHdr.fEvtType")
fout = REPLAYPATH + '/UTIL_KAONLT/DB/CUTS/run_type/lumi.cuts'
# read in cuts file and make dictionary
c = klt.pyPlot(REPLAYPATH)
# apply RF cuts to timing cuts file
c.cut_RF(runNum, MaxEvent)
readDict = c.read_dict(fout, runNum)
# This method calls several methods in kaonlt package. It is required to create properly formated
# dictionaries. The evaluation must be in the analysis script because the analysis variables (i.e. the
# leaves of interest) are not defined in the kaonlt package. This makes the system more flexible
# overall, but a bit more cumbersome in the analysis script. Perhaps one day a better solution will be
# implimented.
def make_cutDict(cut, inputDict=None):
global c
c = klt.pyPlot(REPLAYPATH, readDict)
H_gtr_beta = e_tree.array("H.gtr.beta")
H_gtr_xp = e_tree.array("H.gtr.th") # xpfp -> Theta
H_gtr_yp = e_tree.array("H.gtr.ph") # ypfp -> Phi
H_gtr_dp = e_tree.array("H.gtr.dp")
# SHMS info
P_gtr_beta = e_tree.array("P.gtr.beta")
P_gtr_xp = e_tree.array("P.gtr.th") # xpfp -> Theta
P_gtr_yp = e_tree.array("P.gtr.ph") # ypfp -> Phi
P_gtr_p = e_tree.array("P.gtr.p")
P_gtr_dp = e_tree.array("P.gtr.dp")
r = klt.pyRoot()
# Specify the file which contains the cuts we want to use
fout = '%s/UTIL_KAONLT/DB/CUTS/run_type/demo.cuts' % REPLAYPATH
# read in cuts file and make dictionary
c = klt.pyPlot(REPLAYPATH,
DEBUG=False) # Switch False to True to enable DEBUG mode
readDict = c.read_dict(fout, runNum)
# This method calls several methods in kaonlt package. It is required to create properly formated
# dictionaries. The evaluation must be in the analysis script because the analysis variables (i.e. the
# leaves of interest) are not defined in the kaonlt package. This makes the system more flexible
# overall, but a bit more cumbersome in the analysis script. Perhaps one day a better solution will be
# implimented.
def make_cutDict(cut, inputDict=None):
global c
c = klt.pyPlot(REPLAYPATH, readDict)
x = c.w_dict(cut)
print("%s" % cut)
missmass = np.array(np.sqrt(abs(emiss * emiss - pmiss * pmiss)))
#
# Mp = 0.93828
# MPi = 0.13957018
# MK = 0.493677
# MMpi = np.array([math.sqrt(abs((em + math.sqrt(abs((MK*MK) + (gtrp*gtrp))) - math.sqrt(abs((MPi*MPi) + (gtrp*gtrp) - (pm*pm))) ))**2) for (em, pm, gtrp) in zip(emiss, pmiss, P_gtr_p)])
# MMK = np.array([math.sqrt(abs((em*em)-(pm*pm))) for (em, pm) in zip(emiss, pmiss)])
# MMp = np.array([math.sqrt(abs((em + math.sqrt(abs((MK*MK) + (gtrp*gtrp))) - math.sqrt(abs((Mp*Mp) + (gtrp*gtrp) - (pm*pm))) ))**2) for (em, pm, gtrp) in zip(emiss, pmiss, P_gtr_p)])
r = klt.pyRoot()
fout = REPLAYPATH + '/UTIL_PION/DB/CUTS/run_type/pid_eff.cuts'
# read in cuts file and make dictionary
c = klt.pyPlot(None)
readDict = c.read_dict(fout, runNum)
# This method calls several methods in kaonlt package. It is required to create properly formated
# dictionaries. The evaluation must be in the analysis script because the analysis variables (i.e. the
# leaves of interest) are not defined in the kaonlt package. This makes the system more flexible
# overall, but a bit more cumbersome in the analysis script. Perhaps one day a better solution will be
# implimented.
def make_cutDict(cut, inputDict=None):
global c
c = klt.pyPlot(readDict)
x = c.w_dict(cut)
print("%s" % cut)
# Author: Richard L. Trotta III <*****@*****.**>
#
# Copyright (c) trottar
#
import numpy as np
import pandas as pd
from csv import DictReader
import matplotlib.pyplot as plt
import scipy.optimize as opt
import sys
sys.path.insert(0, '../../../../bin/python/')
import kaonlt as klt
c = klt.pyPlot(None)
# inp_f = "../covid-19-data/public/data/ecdc/full_data.csv"
inp_case = "../covid-19-data/public/data/ecdc/total_cases.csv"
inp_death = "../covid-19-data/public/data/ecdc/total_deaths.csv"
inp_test = "../covid-19-data/public/data/testing/covid-testing-latest-data-source-details.csv"
try:
case_data = dict(pd.read_csv(inp_case))
death_data = dict(pd.read_csv(inp_death))
test_data = dict(pd.read_csv(inp_test))
except IOError:
print("Error: %s or %s [plz]does not appear to exist." %
(inp_death, case_data))
# Testing
