def set_bng_path(dir): """ Deprecated. Use pysb.pathfinder.set_path() instead. """ warn("Function %s() is deprecated; use pysb.pathfinder.set_path() " "instead" % set_bng_path.__name__, category=DeprecationWarning, stacklevel=2) pf.set_path('bng', dir)
def stochkit(model, start=0, finish=10, points=10, n_runs=20, path='/opt/conda/bin/'): set_path('stochkit_ssa', path) sims = StochKitSimulator(model, linspace(start, finish, points + 1)).run(n_runs=n_runs).dataframe sims = modes(sims, n_runs) return {'sims': sims['sims'], 'avrg': sims['avrg'], 'stdv': sims['stdv']}
def bngNF(model, start=0, finish=10, points=10, n_runs=20, path='/opt/conda/bin/'): set_path('bng', path) sims = BngSimulator(model, linspace(start, finish, points + 1)).run(method='nf', n_runs=n_runs).dataframe sims = modes(sims, n_runs) return {'sims': sims['sims'], 'avrg': sims['avrg'], 'stdv': sims['stdv']}
def set_kappa_path(path): """Set the path to the KaSim and KaSa executables. Deprecated. Use pysb.pathfinder.set_path() instead. Parameters ---------- path: string Directory containing KaSim and KaSa executables. """ warnings.warn("Function %s() is deprecated; use " "pysb.pathfinder.set_path() instead" % set_kappa_path.__name__, category=DeprecationWarning, stacklevel=2) pf.set_path('kasim', path) pf.set_path('kasa', path)
from pysb import * from pysb import pathfinder # this is your pythonanywhere.com username user_name = 'rah' bngl_path = '/home/' + str(user_name) + '/BioNetGen-2.3.1/' pathfinder.set_path('bng', bngl_path) pathfinder.get_path('bng') Model() # Physical and geometric constants Parameter('NA', 6.0e23) # Avogadro's num Parameter('f', 0.01) # scaling factor Expression('Vo', f * 1e-10) # L Expression('V', f * 3e-12) # L # Initial concentrations Parameter('EGF_conc', 2e-9) # nM Expression('EGF0', EGF_conc * NA * Vo) # nM Expression('EGFR0', f * 1.8e5) # copy per cell # Rate constants Expression('kp1', 9.0e7 / (NA * Vo)) # input /M/sec Parameter('km1', 0.06) # /sec Monomer('EGF', ['R']) Monomer('EGFR', ['L', 'CR1', 'Y1068'], {'Y1068': ['U', 'P']}) Initial(EGF(R=None), EGF0)
def cupsoda(model, start=0, finish=10, points=10, path='/opt/conda/bin/'): set_path('cupsoda', path) return CupSodaSimulator(model, linspace(start, finish, points + 1)).run().dataframe
def bngODE(model, start=0, finish=10, points=10, path='/opt/conda/bin/'): set_path('bng', path) return BngSimulator(model, linspace(start, finish, points + 1)).run(method='ode').dataframe
def test_get_set_path(): bng_path = get_path('bng') assert os.path.exists(bng_path) set_path('bng', bng_path)
from numpy import linspace from pysb.bng import generate_network, generate_equations from pysb.simulator import ScipyOdeSimulator, BngSimulator, KappaSimulator # modify accordingly from pysb.pathfinder import set_path set_path('bng', '/opt/git-repositories/bionetgen.RuleWorld/bng2/') set_path('kasim', '/opt/git-repositories/KaSim4.Kappa-Dev/') ## for network-based simulations: ## ScipyOdeSimulator and BngSimulator ode and ssa methods # generate_network(model) # generate_equations(model) ## set the number of stochastic simulations runs = 100 # data1 = ScipyOdeSimulator(model, linspace(0, 100, 200)).run().dataframe # data1 = BngSimulator(model, linspace(0, 200, 201)).run(method = 'ode').dataframe # data2 = BngSimulator(model, linspace(0, 200, 201)).run(method = 'ssa', n_runs = runs).dataframe # data2 = BngSimulator(model, linspace(0, 200, 201)).run(method = 'nf', n_runs = runs).dataframe data2 = KappaSimulator(model, linspace(0, 100, 101)).run(n_runs = runs).dataframe ## process simulations data = [] for i in range(0, runs): data.append(data2.xs(i)) avrg = 0 for i in range(0, runs): avrg += data[i] avrg = avrg / runs