:py:mod:`BioSANS2020.prepcodes.processes_hub` ============================================= .. py:module:: BioSANS2020.prepcodes.processes_hub .. autoapi-nested-parse:: This module is the processes_hub module The purpose of this module is to direct the information from the process module into other modules. This module expects some to get some response or data from thos emodule where its directs the information. The respon- ses will be saved or plotted depending on the options provided to this module. The following are the list of function in this module. 1. process_hub Module Contents --------------- Functions ~~~~~~~~~ .. autoapisummary:: BioSANS2020.prepcodes.processes_hub.process_hub .. py:function:: process_hub(time_var, sp_comp, ksn_dict, concn, r_dict, p_dict, stoch_var, v_volms=1, miter=1, logx=False, logy=False, del_coef=10, normalize=False, method='CLE', mix_plot=True, save=True, out_fname='', plot_show=True, time_unit='time (sec)', vary='', mult_proc=False, items=None, vary2='', implicit=False, rfile='', exp_data_file=None) This function redirect all information from the process to other modules and expect the return from those module for plotting or for saving into a file. Args: time_var (list): list of time points in the simulation sp_comp (dict): dictionary of appearance or position of species or component in the reaction tag of BioSANS topology file. For example; #REACTIONS A => B, -kf1 # negative means to be estimated B => C, kf2 The value of sp_comp is sp_comp = {'A': {0}, 'B': {0, 1}, 'C': {1}} A appears in first reaction with index 0 B appears in first and second reaction with index 0, 1 C appears in second reaction with index 1 ksn_dict (dict): dictionary of rate constant that appear in each reactions. For example; #REACTIONS A => B , 0.3 # first reaction B <=> C, 0.1, 0.2 # second reaction The value of ks_dict is ks_dict = { 0 : [0.3], # first reaction 1 : [0.1, 0.2] # second reaction } conc (dict): dictionary of initial concentration. For example; {'A': 100.0, 'B': -1.0, 'C': 0.0} negative means unknown or for estimation r_dict (dict): dictionary of reactant stoichiometry. For example r_dict = { 0: {'A': 1}, # first reaction, coefficient of A is 1 1: {'B': 1} # second reaction, coefficient of B is 1 } p_dict (dict): dictionary of product stoichiometry. For example p_dict = { 0: {'B': 1}, # first reaction, coefficient of B is 1 1: {'C': 1} # second reaction, coefficient of C is 1 } stoch_var (numpy.ndarray): stoichiometric matrix. For example stoch_var = np.array([ [ -1, 0 ] # species A [ 1, -1 ] # species B [ 0, 1 ] # species C #1st rxn 2nd rxn ]) v_volms (float, optional): volume of compartment. Defaults to 1. miter (int, optional): Number of iteration or trajectory samples for stochastic integration 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. 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. 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 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 "". mult_proc (bool, optional): If True, trajectories will be propa- gated on parallel. Defaults to False. items (tuple, optional): (canvas, scroll_x, scroll_y). Defaults to None. vary2 (str, optional): [description]. Defaults to "". 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. rfile (str): file name of BioSANS topology file. exp_data_file ([type], optional): Experimental data file contai- ning True or accepted trajectories. Defaults to None.