BioSANS2020.prepcodes.process¶

Functions¶

BioSANS2020.prepcodes.process.eval_dict(to_eval, loc_dict)¶

This function takes a string expression and return the evaluated expression using SBML_FUNCT_DICT and the locals() dictionary where eval_dict is called.

Args:

to_eval (str): the expression to evaluate loc_dict (dict): local dictionary from the calling function

Returns:

multitype: result of eval command

BioSANS2020.prepcodes.process.tofloat(val, loc_dict)¶

This function attempts to convert the input val into float

Args:

val (str): the expression to evaluate loc_dict (dict): local dictionary from the calling function

Returns:

float: float equivalent of val

BioSANS2020.prepcodes.process.is_number(xvar)¶

This function checks if a string xvar is float

Args:

xvar (str): input string expression or number

Returns:

bool: True if xvar cal be converted to float otherwise False

BioSANS2020.prepcodes.process.process(rfile='Reactions', miter=1, conc_unit='molecules', v_volms=1e-20, tend=1, del_coef=10, normalize=False, logx=False, logy=False, method='CLE', tlen=1000, mix_plot=True, save=True, out_fname='', plot_show=True, time_unit='time (sec)', vary='', vary2='', mult_proc=False, implicit=False, items=None, exp_data_file=None, c_input=None)¶

[summary]

Args:

rfile (str): file name of BioSANS topology file. miter (int, optional): Number of iteration or trajectory samples

for stochastic integration

conc_unit (bool, optional): “mole”,”molar”, or “molecules” - the

unit used in any amount in topology file. Defaults to “molecules”.

v_volms (float, optional): the volume of compartment used in the

simulation. Defaults to 1.0e-20.

tend (float): trajectory simulation end time. Defaults to 1. del_coef (float, optional): factor for modifying time steps used

in the integration/propagation of ODE. Defaults to 10.

normalize (bool, optional): True will be normalized the y axis

based on max value . Defaults to False.

logx (bool, optional): If True, the x-axis will be in log scale.

Defaults to False.

logy (bool, optional): if True, the y-axis will be in log scale.

Defaults to False.

method (str, optional): Defaults to “CLE”. Any of the option in

the list of available method keywords is listed below;

Stochastic (refer to section 10.2.4)

1. “CLE” - Molecules(micro), tau-adaptive

2. “CLE2” - Molecules(micro), cle-fixIntvl

3. “Gillespie_” - Molecules(micro), Direct method

4. “Tau-leaping” - Molecules(micro),

   Not swapping with Gillespie

5. “Tau-leaping2” - Molecules(micro),

   Swapping with Gillespie

6. “Sim-TauLeap” - Molecules(micro), Simplified,

   Swapping with Gillespie

Deterministic (refer to section 10.2.1)

7. “Euler-1” - Molecules(micro), tau-adaptive-1

8. “Euler-2” - Molar (macro), tau-adaptive-1

9. “Euler-3” - Mole (macro), tau-adaptive-1

10. “Euler2-1” - Molecules(micro), tau-adaptive-2

11. “Euler2-2” - Molar (macro), tau-adaptive-2

12. “Euler2-3” - Mole (macro), tau-adaptive-2

13. “ODE-1” - Molecules(micro),

    using ode_int from scipy

14. “ODE-2” - Molar(macro),

    using ode_int from scipy

15. “ODE-3” - Mole(macro), using ode_int from scipy

16. “rk4-1” - Molecules(micro), fix-interval

17. “rk4-2” - Molar(macro), fix-interval

18. “rk4-3” - Mole(macro), fix-interval

19. “rk4-1a” - Molecules(micro), tau-adaptive

20. “rk4-2a” - Molar(macro), tau-adaptive

21. “rk4-3a” - Mole(macro), tau-adaptive

Linear Noise Approximation (refer to 10.1.2 & 10.2.2)

22. “LNA” - Numeric, values

23. “LNA-vs” - Symbolic, values, Macroscopic

24. “LNA-ks” - Symbolic, f(ks), Macroscopic

25. “LNA-xo” - Symbolic, f(xo), Macroscopic

26. “LNA2” - Symbolic, f(xo,ks), Microscopic

27. “LNA3” - Symbolic, f(xo,ks), Macroscopic

28. “LNA(t)” - COV-time-dependent, Macroscopic

29. “LNA2(t)” - FF-time-dependent, Macroscopic

Network Localization (refer to 10.1.3)

30. “NetLoc1” - Symbolic, Macroscopic

31. “NetLoc2” - Numeric, Macroscopic

Parameter estimation (refer to 10.2.3)

32. “k_est1” - MCEM, Macroscopic

33. “k_est2” - MCEM, Microscopic

34. “k_est3” - NM-Diff. Evol., Macroscopic

35. “k_est4” - NM-Diff. Evol., Microscopic

36. “k_est5” - Parameter slider/scanner

37. “k_est6” - Nelder-Mead (NM), Macroscopic

38. “k_est7” - Nelder-Mead (NM), Microscopic

39. “k_est8” - Powell, Macroscopic

40. “k_est9” - Powell, Microscopic

41. “k_est10” - L-BFGS-B, Macroscopic

42. “k_est11” - L-BFGS-B, Microscopic

Symbolic/Analytical expression of species (refer to 10.1.1)

43. “Analyt” - Pure Symbolic :f(t,xo,k)

44. “Analyt-ftx” - Semi-Symbolic :f(t,xo)

45. “SAnalyt” - Semi-Symbolic :f(t)

46. “SAnalyt-ftk” - Semi-Symbolic :f(t,k)

47. “Analyt2” - Creates commands for wxmaxima

tlen (int, optional): number of integration steps reported in

the final result. Defaults to 1000.

mix_plot (bool, optional): If True, all species are plotted in

one plot/figure. Defaults to True.

save (bool, optional): If True, the resulting trajectory in the

simulation will be saved as a file. Defaults to True.

out_fname (str, optional): output filename. Defaults to “”. plot_show (bool, optional): If True, an image of the plots will

be created in the directory of the topology file.

time_unit (str, optional): Defaults to “time (sec)”. vary (str, optional): Varying initial concentration.

Defaults to “”.

vary2 (str, optional): [description]. Defaults to “”. mult_proc (bool, optional): If True, trajectories will be propa-

gated on parallel. Defaults to False.

implicit (bool, optional): True means report in time intervals

similar to the input time intervals even if actual step is more or less. Defaults to False.

items (tuple, optional): (canvas, scroll_x, scroll_y).

Defaults to None.

exp_data_file ([type], optional): Experimental data file contai-

ning True or accepted trajectories. Defaults to None.

c_input (dict, optional): [description]. Defaults to {}.

Returns:

list: list of simulated trajecotry.

data[j][0] - time for trajectory j data[j][1][:, i] - trajectories of each component i