crnt4sbml.LowDeficiencyApproach

class crnt4sbml.LowDeficiencyApproach(cgraph)[source]

Class for testing the Deficiency Zero and One Theorems.

__init__(cgraph)[source]

Initialization of LowDeficiency Approach class.

Methods

__init__(cgraph) Initialization of LowDeficiency Approach class.
does_satisfy_deficiency_zero_theorem() Function to see if the network satisfies the Deficiency Zero Theorem.
does_satisfy_deficiency_one_theorem() Function to see if the network satisfies the Deficiency One Theorem.
does_satisfy_any_low_deficiency_theorem() Function to see if the network satisfies the Deficiency Zero or One Theorem.
report_deficiency_zero_theorem() Prints out the applicability of the Deficiency Zero Theorem for the provided network.
report_deficiency_one_theorem() Prints out the applicability of the Deficiency One Theorem for the provided network.
does_satisfy_any_low_deficiency_theorem()[source]

Function to see if the network satisfies the Deficiency Zero or One Theorem. Returns True if the network satisfies the Deficiency Zero or One Theorem, False otherwise. Fig1Ci.xml for the provided example.

Example

>>> import crnt4sbml
>>> network = crnt4sbml.CRNT("path/to/Fig1Ci.xml")
>>> approach = network.get_low_deficiency_approach()
>>> print(approach.does_satisfy_any_low_deficiency_theorem())
    False
does_satisfy_deficiency_one_theorem()[source]

Function to see if the network satisfies the Deficiency One Theorem. Returns True if the network satisfies the Deficiency One Theorem, False otherwise. Fig1Ci.xml for the provided example.

Example

>>> import crnt4sbml
>>> network = crnt4sbml.CRNT("path/to/Fig1Ci.xml")
>>> approach = network.get_low_deficiency_approach()
>>> print(approach.does_satisfy_deficiency_one_theorem())
    False
does_satisfy_deficiency_zero_theorem()[source]

Function to see if the network satisfies the Deficiency Zero Theorem. Returns True if the network satisfies the Deficiency Zero Theorem, False otherwise. Fig1Ci.xml for the provided example.

Example

>>> import crnt4sbml
>>> network = crnt4sbml.CRNT("path/to/Fig1Ci.xml")
>>> approach = network.get_low_deficiency_approach()
>>> print(approach.does_satisfy_deficiency_zero_theorem())
    False
report_deficiency_one_theorem()[source]

Prints out the applicability of the Deficiency One Theorem for the provided network. Possible output:

“By the Deficiency One Theorem, the differential equations admit precisely one equilibrium in each positive stoichiometric compatibility class. Thus, multiple equilibria cannot exist for the network.”

or

“The network satisfies relaxed Deficiency One Theorem. That is it is not weakly reversable, but each linkage class contains no more than one terminal linkage class. There can exist within a positive stoichiometric compatibility class at most one equilibrium. Thus, multiple equilibria cannot exist for the network.”

or

“The network does not satisfy the Deficiency One Theorem, multistability cannot be excluded.”

Fig1Ci.xml for the provided example.

Example

>>> import crnt4sbml
>>> network = crnt4sbml.CRNT("path/to/Fig1Ci.xml")
>>> approach = network.get_low_deficiency_approach()
>>> print(approach.report_deficiency_zero_theorem())
    The network does not satisfy the Deficiency One Theorem, multistability cannot be excluded.
report_deficiency_zero_theorem()[source]

Prints out the applicability of the Deficiency Zero Theorem for the provided network. Possible output:

“By the Deficiency Zero Theorem, the differential equations cannot admit a positive equilibrium or a cyclic composition trajectory containing a positive composition. Thus, multiple equilibria cannot exist for the network.”

or

“By the Deficiency Zero Theorem, there exists within each positive stoichiometric compatibility class precisely one equilibrium. Thus, multiple equilibria cannot exist for the network.”

or

“The network does not satisfy the Deficiency Zero Theorem, multistability cannot be excluded.”

Fig1Ci.xml for the provided example.

Example

>>> import crnt4sbml
>>> network = crnt4sbml.CRNT("path/to/Fig1Ci.xml")
>>> approach = network.get_low_deficiency_approach()
>>> print(approach.report_deficiency_zero_theorem())
    The network does not satisfy the Deficiency Zero Theorem, multistability cannot be excluded.