Experimental features¶

Experimental features for modelbase2.

All APIs shown should be considered unstable and may change without notice.

In [1]:

from example_models import get_linear_chain_1v, get_linear_chain_2v
from modelbase2.experimental import (
    generate_model_code_py,
    generate_modelbase_code,
    model_diff,
    to_tex,
)

from example_models import get_linear_chain_1v, get_linear_chain_2v from modelbase2.experimental import ( generate_model_code_py, generate_modelbase_code, model_diff, to_tex, )

code generation¶

Currently, the limitation here is that functions used for reactions etc. cannot call other functions.

modelbase2 can generate own source code from a model.

In [2]:

print(generate_modelbase_code(get_linear_chain_1v()))

print(generate_modelbase_code(get_linear_chain_1v()))

from modelbase2 import Model

def constant(x: Float) -> Float:
    """Constant function."""
    return x

def mass_action_1s(s1: Float, k: Float) -> Float:
    """Irreversible mass action reaction with one substrate."""
    return k * s1

def create_model() -> Model:
    return (
        Model()
        .add_parameters({'k_in': 1.0, 'k_out': 1.0})
        .add_variables({'x': 1.0})
        .add_reaction(
                "v_in",
                fn=constant,
                args=['k_in'],
                stoichiometry={'x': 1},
            )
        .add_reaction(
                "v_out",
                fn=mass_action_1s,
                args=['k_out', 'x'],
                stoichiometry={'x': -1},
            )
    )

modelbase2 can also generate a generic python function from the source code.
The plan here is to generalise this to be able to export models into other programming languages as well.

In [3]:

print(generate_model_code_py(get_linear_chain_2v()))

print(generate_model_code_py(get_linear_chain_2v()))

from collections.abc import Iterable

from modelbase2.types import Float

def model(t: Float, y: Float) -> Iterable[Float]:
    x, y = y
    k1 = 1.0
    k2 = 2.0
    k3 = 1.0
    v1 = k1
    v2 = x * k2
    v3 = y * k3
    dxdt = v1 - v2
    dydt = v2 - v3
    return dxdt, dydt

Diffs¶

modelbase2 can generate diffs between two models to quickly analyse differences between all model elements.

In [4]:

print(
    model_diff(
        get_linear_chain_2v(),
        get_linear_chain_1v(),
    )
)

print( model_diff( get_linear_chain_2v(), get_linear_chain_1v(), ) )

Model Diff
----------
Missing Parameters: k1, k2, k3
Missing Variables: y
Missing Reactions: v2, v1, v3

In [5]:

print(
    model_diff(
        get_linear_chain_2v(),
        get_linear_chain_2v().scale_parameter("k3", 2.0),
    )
)

print( model_diff( get_linear_chain_2v(), get_linear_chain_2v().scale_parameter("k3", 2.0), ) )

Model Diff
----------
Different Parameters:
  k3: 1.0 != 2.0

LaTeX export¶

Currently, the limitation here is that functions used for reactions etc. cannot call other functions.

modelbase2 supports writing out your model as LaTeX.

In [6]:

print(to_tex(get_linear_chain_1v()))

print(to_tex(get_linear_chain_1v()))

\documentclass{article}
\usepackage[english]{babel}
\usepackage[a4paper,top=2cm,bottom=2cm,left=2cm,right=2cm,marginparwidth=1.75cm]{geometry}
\usepackage{amsmath, amssymb, array, booktabs,
            breqn, caption, longtable, mathtools, placeins,
            ragged2e, tabularx, titlesec, titling}
\newcommand{\sectionbreak}{\clearpage}
\setlength{\parindent}{0pt}

\title{Model construction}
\date{} % clear date
\author{modelbase}
\begin{document}
\maketitle
\FloatBarrier\subsubsection*{Variables}
\begin{longtable}{c|c}
    Model name & Initial concentration \\
    \hline
    \endhead
    x & 1.00e+00 \\
    \caption[Model variables]{Model variables}
    \label{table:model-vars}
\end{longtable}

\FloatBarrier\subsubsection*{Parameters}
\begin{longtable}{c|c}
    Parameter name & Parameter value \\
    \hline
    \endhead
    $\mathrm{k\_in}$ & 1.00e+00 \\
    $\mathrm{k\_out}$ & 1.00e+00 \\
    \caption[Model parameters]{Model parameters}
    \label{table:model-pars}
\end{longtable}

\FloatBarrier\subsubsection*{Reactions}
\begin{dmath*}
    v_in = \mathrm{k\_in}
\end{dmath*}

\begin{dmath*}
    v_out = x \cdot \mathrm{k\_out}
\end{dmath*}

\FloatBarrier\subsubsection*{Stoichiometries}
\begin{longtable}{c|c}
    Rate name & Stoichiometry \\
    \hline
    \endhead
    v\_in & $\mathrm{x}$ \\
    v\_out & $-\mathrm{x}$ \\
    \caption[Model stoichiometries.]{Model stoichiometries.}
    \label{table:model-stoichs}
\end{longtable}
\end{document}

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