Comparisons¶

mxlpy provides simple routines to numerically compare two models.
For this, we use the compare module.

In [1]:

import numpy as np

from example_models import get_sir, get_sird
from mxlpy import compare, make_protocol

import numpy as np from example_models import get_sir, get_sird from mxlpy import compare, make_protocol

Steady-states¶

You can compare the steady-states of two models using the compare_steady_states function.

In [2]:

ssc = compare.steady_states(get_sir(), get_sird())

ssc = compare.steady_states(get_sir(), get_sird())

This returns a SteadyStateComparison object, for which you can either access the direct comparisons

In [3]:

ssc.variables

ssc.variables

Out[3]:

	m1	m2	diff	rel_diff
d	NaN	7.121887e-02	NaN	NaN
i	6.676138e-12	3.794859e-12	-2.881278e-12	-0.431579
r	8.282883e-01	7.121887e-01	-1.160997e-01	-0.140168
s	1.717117e-01	2.165925e-01	4.488079e-02	0.261373

In [4]:

ssc.fluxes

ssc.fluxes

Out[4]:

	m1	m2	diff	rel_diff
death	NaN	3.794859e-14	NaN	NaN
infection	2.292742e-13	1.643876e-13	-6.488657e-14	-0.283009
recovery	6.676138e-13	3.794859e-13	-2.881278e-13	-0.431579

or plot the results

In [5]:

_ = ssc.plot_variables()
_ = ssc.plot_fluxes()
_ = ssc.plot_all()

_ = ssc.plot_variables() _ = ssc.plot_fluxes() _ = ssc.plot_all()

Time courses¶

For comparing time courses, you can use the compare_time_courses function.
This returns a TimeCourseComparison object, which you can directly use to plot for example the relative differences of variables or fluxes.

In [6]:

pc = compare.time_courses(
    get_sir(),
    get_sird(),
    time_points=np.linspace(0, 100, 101),
)

_ = pc.plot_variables_relative_difference()
_ = pc.plot_fluxes_relative_difference()

pc = compare.time_courses( get_sir(), get_sird(), time_points=np.linspace(0, 100, 101), ) _ = pc.plot_variables_relative_difference() _ = pc.plot_fluxes_relative_difference()

Protocol time courses¶

For comparing protocol time courses, you can use the protocol_time_courses function.
This returns a ProtocolComparison object, which you can directly use to plot for example the relative differences of variables or fluxes.

In [7]:

pc = compare.protocol_time_courses(
    get_sir(),
    get_sird(),
    protocol=make_protocol(
        [
            (10, {"beta": 0.2}),
            (10, {"beta": 1.0}),
            (80, {"beta": 0.2}),
        ]
    ),
)

_ = pc.plot_variables_relative_difference()

pc = compare.protocol_time_courses( get_sir(), get_sird(), protocol=make_protocol( [ (10, {"beta": 0.2}), (10, {"beta": 1.0}), (80, {"beta": 0.2}), ] ), ) _ = pc.plot_variables_relative_difference()

Optionally, if you want to indicate one of the protocol parameters on the plots, you can use the shade_protocol_variable argument

In [8]:

_ = pc.plot_variables_relative_difference(shade_protocol_variable="beta")
_ = pc.plot_fluxes_relative_difference(shade_protocol_variable="beta")

_ = pc.plot_variables_relative_difference(shade_protocol_variable="beta") _ = pc.plot_fluxes_relative_difference(shade_protocol_variable="beta")

In [ ]: