Python scan Examples, command.scan.scan.scan Python Examples

Example #1

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File: Scan_NTools_2.py Project: mlcenter/ScanCraft

ignore=[ 'Landau Pole'#27
        ,'relic density'#30
        ,'Relic density'
        ,'Excluded by LUX'
        ,'b->s gamma'#32
        ,'B_s->mu+mu-'#35
        ,'Muon magn'#37
        ,'No Higgs in the'#46
        ,'b -> c tau nu'#58 always keep alive
        ]
#r=readSLHA(discountKeys=ignore)

#print(read.readline.readline)
#print(mcmc.Scan)

free=scan()
free.AddScalar('tanB',  'MINPAR',3, 2., 60.)
free.AddScalar('M1',    'EXTPAR',1, 20.,800.)
free.AddScalar('M2',    'EXTPAR',2, 100.,   1200.)
free.AddScalar('Atop',  'EXTPAR',11,-5e3,   5e3)
free.AddFollower('Abottom', 'EXTPAR',12,'Atop')
free.AddScalar('Atau',      'EXTPAR',13,100.,1200.)
free.AddFollower('MtauL',   'EXTPAR',33,'Atau')
free.AddFollower('MtauR',   'EXTPAR',36,'Atau')
free.AddScalar('MQ3L',  'EXTPAR',43,100.,2.e3)
free.AddScalar('MtopR', 'EXTPAR',46,100.,2.e3)
free.AddFollower('MbottomR','EXTPAR',49,'MtopR')
free.AddScalar('Lambda',    'EXTPAR',61,1e-3,   .75,    prior_distribution='lognormal')
#free.AddScalar('Kappa',    'EXTPAR',62,-0.75,  -1e-3,  prior_distribution='lognormal')
free.AddScalar('minusK', 'auxiliary',62,1e-3,   .75,    prior_distribution='lognormal')
Minus=lambda x : -x

Example #2

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File: rand_NTools.py Project: vooum/ScanCommander

#!/usr/bin/env python3

import sys,pandas
sys.path.append('/home/heyangle/Desktop/ScanCraft/ScanCraft')
from command.scan.scan import scan
from command.NMSSMTools import NMSSMTools
from command.multi_thread.queue_operation import GenerateQueue#,FillQueue
from command.multi_thread.MT_NTools import MT_NTools
from command.data_transformer.InputListToPandas import InputListToPandas as I2P

mold=scan(method='random')
mold.AddScalar('tanB','MINPAR',3,1.,60.)
mold.AddScalar('M1','EXTPAR',1  ,20.    ,1000.)
mold.AddScalar('M2','EXTPAR'   ,2  ,100.    ,2000.)
mold.AddScalar('Atop','EXTPAR'   ,11  ,  -6e3    ,6e3)
mold.AddFollower('Abottom','EXTPAR'   ,12,'Atop')
mold.AddScalar('Atau','EXTPAR'   ,13  ,  100.      ,2000.)
mold.AddFollower('MtauL','EXTPAR'   ,33,'Atau')
mold.AddFollower('MtauR','EXTPAR'   ,36,'Atau')
mold.AddScalar('MQ3L','EXTPAR'   ,43,	100.,	2.e3)
mold.AddScalar('MtopR'	,'EXTPAR'   ,46,	100.,	2.e3)
mold.AddFollower('MbottomR','EXTPAR'  ,49,'MtopR')
mold.AddScalar('Lambda','EXTPAR'  ,61  ,1e-3    ,1. ,prior_distribution='exponential')
mold.AddScalar('Kappa','EXTPAR'   ,62 ,1.e-3    ,1. ,prior_distribution='exponential')
mold.AddScalar('A_Lambda','EXTPAR' ,63,-3.e3,3.e3)
mold.AddScalar('A_kappa','EXTPAR' ,64,-3.e3,3.e3)
mold.AddScalar('mu_eff','EXTPAR'  ,65,100.,1500.)

MTN=MT_NTools(threads=6)
ore_q=GenerateQueue(mold,lenth=10)
MTN.Run(ore_q)

Example #3

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File: Relic_FineTuning.py Project: vooum/ScanCommander

ism='h2'
target_number=3000
step_factor=.3 # sigma = n% of (maximum - minimum) of the free parameters
slop_factor=1. # difficulty of accepting a new point with higher chisq
ignore=[ 'Landau Pole'#27
        ,'relic density'#30
        ,'Relic density'
        ,'Excluded by LUX'
        ,'b->s gamma'#32
        ,'B_s->mu+mu-'#35
        ,'Muon magn'#37
        ,'No Higgs in the'#46
        ,'b -> c tau nu'#58 always keep alive
        ]

mold=scan()
mold.AddScalar('tanB',  'MINPAR',3, 2., 60.)
mold.AddScalar('M1',    'EXTPAR',1, 20.,800.)
mold.AddScalar('M2',    'EXTPAR',2, 100.,   1200.)
mold.AddScalar('Atop',  'EXTPAR',11,-5e3,   5e3)
mold.AddFollower('Abottom', 'EXTPAR',12,'Atop')
mold.AddScalar('Atau',      'EXTPAR',13,100.,1200.)
mold.AddFollower('MtauL',   'EXTPAR',33,'Atau')
mold.AddFollower('MtauR',   'EXTPAR',36,'Atau')
mold.AddScalar('MQ3L',  'EXTPAR',43,100.,2.e3)
mold.AddScalar('MtopR', 'EXTPAR',46,100.,2.e3)
mold.AddFollower('MbottomR','EXTPAR',49,'MtopR')
mold.AddScalar('Lambda',    'EXTPAR',61,1e-3,   .75)#,    prior_distribution='lognormal')
#mold.AddScalar('Kappa',    'EXTPAR',62,-0.75,  -1e-3,  prior_distribution='lognormal')
mold.AddScalar('minusK', 'auxiliary',62,1e-3,   .75)#,    prior_distribution='lognormal')
Minus=lambda x : -x

Example #4

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File: rand_NTools.py Project: mlcenter/ScanCraft

#!/usr/bin/env python3

import sys, pandas
sys.path.append('/home/heyangle/Desktop/ScanCraft/ScanCraft')
from command.scan.scan import scan
from command.NMSSMTools import NMSSMTools
from command.multi_thread.queue_operation import GenerateQueue  #,FillQueue
from command.multi_thread.MT_NTools import MT_NTools
from command.data_transformer.InputListToPandas import InputListToPandas as I2P

mold = scan(method='random')
mold.AddScalar('tanB', 'MINPAR', 3, 1., 60.)
mold.AddScalar('M1', 'EXTPAR', 1, 20., 1000.)
mold.AddScalar('M2', 'EXTPAR', 2, 100., 2000.)
mold.AddScalar('Atop', 'EXTPAR', 11, -6e3, 6e3)
mold.AddFollower('Abottom', 'EXTPAR', 12, 'Atop')
mold.AddScalar('Atau', 'EXTPAR', 13, 100., 2000.)
mold.AddFollower('MtauL', 'EXTPAR', 33, 'Atau')
mold.AddFollower('MtauR', 'EXTPAR', 36, 'Atau')
mold.AddScalar('MQ3L', 'EXTPAR', 43, 100., 2.e3)
mold.AddScalar('MtopR', 'EXTPAR', 46, 100., 2.e3)
mold.AddFollower('MbottomR', 'EXTPAR', 49, 'MtopR')
mold.AddScalar('Lambda',
               'EXTPAR',
               61,
               1e-3,
               1.,
               prior_distribution='exponential')
mold.AddScalar('Kappa',
               'EXTPAR',
               62,

Example #5

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Show file

File: Scan_NTools.py Project: vooum/ScanCommander

step_factor=.1 # sigma = n% of (maximum - minimum) of the free parameters
slop_factor=1. # difficulty of accepting a new point with higher chisq
ignore=[ 'Landau Pole'#27
        ,'relic density'#30
        ,'b->s gamma'#32
        ,'B_s->mu+mu-'#35
        ,'Muon magn'#37
        ,'No Higgs in the'#46
        ,'b -> c tau nu'#58 always keep alive
        ]
#r=readSLHA(discountKeys=ignore)

#print(read.readline.readline)
#print(mcmc.Scan)

free=scan()
free.AddScalar('tanB','MINPAR',3,1.,60.)


N=NMSSMTools(input_mold='./mcmc/inp.dat')
free.GetValue('./mcmc/inp.dat')
print('Start point is:')
newpoint=copy.deepcopy(free)
newpoint.Print()
Data=DataFile(Dir='mcmc')

record_number=-1
try_point=0
last_chisq=1e10
# scan ==================================================================
while record_number < target_number:

Example #6

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File: Relic_FineTuning.py Project: mlcenter/ScanCraft

    'relic density'  #30
    ,
    'Relic density',
    'Excluded by LUX',
    'b->s gamma'  #32
    ,
    'B_s->mu+mu-'  #35
    ,
    'Muon magn'  #37
    ,
    'No Higgs in the'  #46
    ,
    'b -> c tau nu'  #58 always keep alive
]

mold = scan()
mold.AddScalar('tanB', 'MINPAR', 3, 2., 60.)
mold.AddScalar('M1', 'EXTPAR', 1, 20., 800.)
mold.AddScalar('M2', 'EXTPAR', 2, 100., 1200.)
mold.AddScalar('Atop', 'EXTPAR', 11, -5e3, 5e3)
mold.AddFollower('Abottom', 'EXTPAR', 12, 'Atop')
mold.AddScalar('Atau', 'EXTPAR', 13, 100., 1200.)
mold.AddFollower('MtauL', 'EXTPAR', 33, 'Atau')
mold.AddFollower('MtauR', 'EXTPAR', 36, 'Atau')
mold.AddScalar('MQ3L', 'EXTPAR', 43, 100., 2.e3)
mold.AddScalar('MtopR', 'EXTPAR', 46, 100., 2.e3)
mold.AddFollower('MbottomR', 'EXTPAR', 49, 'MtopR')
mold.AddScalar('Lambda', 'EXTPAR', 61, 1e-3,
               .75)  #,    prior_distribution='lognormal')
#mold.AddScalar('Kappa',    'EXTPAR',62,-0.75,  -1e-3,  prior_distribution='lognormal')
mold.AddScalar('minusK', 'auxiliary', 62, 1e-3,