BioSANS2020.propagation.symbolic.lna_approx2¶

Functions¶

BioSANS2020.propagation.symbolic.lna_approx2.subs2(zvar, cval)¶

This function helps in the substitution of value to sympy Symbols

Args:

zvar (Symbol): sympy expression cval (dict): dictionary of values

Returns:

(Symbol): substituted expression

BioSANS2020.propagation.symbolic.lna_approx2.lna_symbolic2(sp_comp, ks_dict, conc, r_dict, p_dict, stch_var, items=None, molar=False, mode=None)¶

This function facilitates in the symbolic LNA computation.

Args:

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 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

ks_dict (dict): dictionary of rate constant that appears 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 ([type]): [description] 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

}

stch_var (numpy.ndarray): stoichiometric matrix. For example

v_stoich = np.array([

[ -1, 0 ] # species A [ 1, -1 ] # species B [ 0, 1 ] # species C

#1st rxn 2nd rxn

])

items (list): list of [canvas, scroll_x, scroll_y] molar (bool, optional): If True, the units for any amount is in

molar. Propensity will be macroscopic. Defaults to False.

mode (str, optional): method keywords : Numeric, fofks, fofCo

Returns:

list: [0, 0] - not used