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)
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
json.dump(res, open('FVS_application_to_r10.json', 'w'), indent=4)
multilineString = modeltext.splitlines()
nodeRaw = []
node = []
combination = {}
for line in multilineString:
if not (line == "" or line.count("*=") >= 1):
nodeRaw.append(line)
for line in nodeRaw:
line.find("=")
node.append(line[0:line.find("=")])
combinationNumber = 2
for subset1 in itertools.combinations(node, combinationNumber):
for k in range(0, combinationNumber + 1):
for subset2 in itertools.combinations(subset1, k):
nodeOnList = [i for i in subset2]
nodeOffList = list(subset1)
for j in nodeOnList:
nodeOffList.remove(j)
res = attr_cy.run(samples=100000,
steps=200,
debug=False,
progress=True,
on_states=nodeOnList,
off_states=nodeOffList)
combination["On" + str(nodeOnList) + "Off" +
str(nodeOffList)] = res
json.dump(combination, open('CK_application_to_r9.json', 'w'), indent=4)
PKC*= PLCG
PLCG*= EGFR or FGFR3
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=['EGFR'],
off_states=['p14'])
# on_states=['A01', 'A51'], off_states=['A38', 'A40']
# debug needs to be changed to 'True' to check trajectory
json.dump(res, open('EGFR_p14.json', 'w'), indent=4)
p38*= (TAOK and MAP3K1_3) or (MAP3K1_3 and MTK1) or (TAOK and MTK1) or (TAK1 and MTK1) or (TAK1 and MAP3K1_3) or (TAK1 and TAOK) or ((TAOK or MTK1 or MAP3K1_3 or TAK1) and not DUSP1)
p53*= (ATM and p38) or ((ATM or p38) and not MDM2)
p70*= PDK1 and ERK
PDK1*= PI3K
PI3K*= GAB1 or (RAS and SOS)
PKC*= PLCG
PLCG*= EGFR or FGFR3
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=['A01', 'A51'], off_states=['A38', 'A40']
# debug needs to be changed to 'True' to check trajectory
json.dump(res, open('normal.json', 'w'), indent=4)