def run_b(config=None, force=False):
"모델의 베이신크기를 계산."
outputfile = config['output']['b']
if exists(outputfile) and force == False:
return
data = tab_s7.load_a()
model = "\n".join(data['equation'].values.tolist())
samples = config['parameters']['samples']
steps = config['parameters']['steps']
on_states = config['parameters']['on_states']
off_states = config['parameters']['off_states']
attr_cy.build(model, on_states=on_states, off_states=off_states)
result_data = attr_cy.run(samples=samples, steps=steps, debug=True)
# on_states=[], off_states=[]
json.dump(result_data, open(outputfile, 'w'), indent=4)
def test_this_1():
modeltext = '''
A= Random
B= Random
C= Random
A*= A or C
B*= A and C
C*= not A or B
'''
# if not exists('engine.pyx'):
attr_cy.build(modeltext)
import pyximport
pyximport.install()
res = attr_cy.run(samples=1000000, steps=50, debug=False, on_states=['A'], \
progress=True)
json.dump(res, open('test_attr_cy.json', 'w'), indent=4)
def test_hello(with_small, force):
if not exists('fumia_engine.pyx'):
attr_cy.build(preproc_model_file(datast_fumia),
pyx='fumia_engine.pyx',
weighted_sum=False)
import pyximport
pyximport.install()
import fumia_engine
res = attr_cy.parallel(fumia_engine,
steps=80,
samples=100,
ncpus=100,
repeats=1000,
on_states=[],
off_states=[])
with open(output_attr, 'w') as f:
json.dump(res, f, indent=4)
'b2-simul-result-table-summary.csv')
with open(file_a2, 'r') as fobj:
lines = fobj.readlines()
lines2 = []
for lin in lines:
lin = lin.strip()
if lin[0] == '#':
continue
right = lin.split('=')[1].strip()
if right == 'input':
lines2.append( lin.split('=')[0].strip() + '=' + 'False')
else:
lines2.append(lin)
modeltext = "\n".join(lines2)
attr_cy.build(modeltext, pyx='engine.pyx', weighted_sum=True)
import pyximport; pyximport.install()
template = {
'State_Mutagen' : False,
'State_GFs': False,
'State_Nutrients': False,
'State_TNFalpha': False,
'State_Hypoxia': False,
'State_Gli': False,
}
# with open(file_a2, 'r') as fobj:
# lines = fobj.readlines()
# lines2 = []
# for lin in lines:
# lin = lin.strip()
# if lin[0] == '#':
# continue
# right = lin.split('=')[1].strip()
# if right == 'input':
# lines2.append( lin.split('=')[0].strip() + '=' + 'False')
# else:
# lines2.append(lin)
# modeltext = "\n".join(lines2)
from sbie_optdrug2.results import fumia
attr_cy.build(fumia.modeltext(), pyx='engine.pyx', weighted_sum=False)
import pyximport
pyximport.install()
inplabels = [
'State_Mutagen', 'State_GFs', 'State_Nutrients', 'State_TNFalpha',
'State_Hypoxia'
]
mutlabels = ['State_APC', 'State_Ras', 'State_Smad', 'State_PTEN', 'State_p53']
chk_fumia_simul = 'chk-fumia-simul.json'
dataset_ccle_dose_resp = join(basedir,
'../table_s2/download/CCLE_NP24.2009_Drug_data_2015.02.24.csv')
# CRC subset of CCLE
dataset_ccle_crc_info = join(basedir,
'../table_s3/dataset-ccle_crc_info.csv')
chk_drug_model_target_dict = join(basedir,
'../table_s3/chk-drug-modeltarget.json')
msigdb = dataset_msigdb.load_msigdb()
if not exists('fumia_engine.pyx'):
attr_cy.build(model_fumia2013.modeltext(),
pyx='fumia_engine.pyx',
weighted_sum=True
)
import pyximport; pyximport.install()
max_num_drugs = 2;
samples = 10
with open('dataset-goterms-in-apq.json', 'r') as f:
goterms_in_apq = json.load(f)
def genesymdict():
# from termutil import progressbar
from os import system
from os.path import dirname, join, exists
from boolean3_addon import attr_cy
import numpy as np
from sbie_optdrug.result import tab_s3
from sbie_optdrug.result import tab_s7
from boolean3 import Model
from boolean3_addon import attractor
import pandas as pd
if not exists('engine.pyx'):
data = tab_s7.load_a()
model = "\n".join(data['equation'].values.tolist())
attr_cy.build(model)
import pyximport
pyximport.install()
import engine
def getconfig():
"return config object"
return tab_s7.config
def run_a(config=None, force=False):
"푸미아네트워크 이큐에이션을 준비한다."
if exists(config['output']['a']) and force == False:
return
PPP2CA*= p38
Proliferation*= p70 and MYC and not p21
PTEN*= p53
RAF*= (RAS or PKC) and not (ERK or AKT)
RAS*= SOS or PLCG
RSK*= ERK
SMAD*= TGFBR
SOS*= GRB2 and not RSK
SPRY*= ERK
TAK1*= TGFBR
TAOK*= ATM
TGFBR*= TGFBR_stimulus
TGFBR_stimulus*= TGFBR_stimulus
'''
attr_cy.build(modeltext)
import pyximport
pyximport.install()
res = attr_cy.run(samples=100000,
steps=100,
debug=False,
progress=True,
on_states=[
'DNA_damage', 'TGFBR_stimulus', 'p53', 'p38', 'PKC',
'GRB2', 'GAB1'
],
off_states=['EGFR_stimulus', 'ERK', 'FGFR3_stimulus'])
# on_states=['A01', 'A51'], off_states=['A38', 'A40']
# debug needs to be changed to 'True' to check trajectory
S_E2F_CyclinE *= S_CycE and S_E2F
S_cdh1_UbcH10 *= S_UbcH10 and S_cdh1
S_TAK1 *= S_TNFalpha
S_GSH *= S_Myc_Max or S_NF_kB or S_p21
S_TCF *= S_beta_cat and not S_TAK1
S_Miz_1 *= not S_Myc_Max
S_p70 *= S_PDK1 or S_mTOR
S_ATM_ATR *= S_DnaDamage
S_CHK1_2 *= S_ATM_ATR
S_DNARepair *= S_ATM_ATR
S_eEF2K *= S_p70 or S_p90
S_eEF2 *= not S_eEF2K
S_p53_PTEN *= S_PTEN and S_p53
S_LDHA *= S_HIF1 and S_Myc_Max
S_AcidLactic *= S_LDHA
S_Snail *= S_NF_kB and S_Smad and not S_GSK_3 and not S_p53
'''
# if not exists('engine.pyx'):
attr_cy.build(text)
import pyximport
pyximport.install()
import engine
def test_this_2():
result = engine.main(samples=1000000, steps=50, debug=False, \
progress=True, on_states=[], off_states=[])
json.dump(result, open('test_attr_cy_long.json', 'w'), indent=4)
