Skip to content

Instantly share code, notes, and snippets.

@kaizu

kaizu/Porting_SBML.ipynb

Created June 4, 2019 04:40
Show Gist options
  • Save kaizu/b477e452001b2ab2b36ce3c801399079 to your computer and use it in GitHub Desktop.
Save kaizu/b477e452001b2ab2b36ce3c801399079 to your computer and use it in GitHub Desktop.
Download ZIP
Display the source blob
Display the rendered blob
Raw
Porting_SBML.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from ecell4 import *"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"filename = 'test.xml'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"with reaction_rules():\n",
" A + B == C | (0.01, 0.3)\n",
"m1 = get_model()\n",
"y0 = {'C': 60}"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A+B>C|0.01\n",
"C>A+B|0.3\n"
]
}
],
"source": [
"show(m1)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"run_simulation(100, model=m1, y0=y0)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# from ecell4.util.ports import save_sbml\n",
"from ports import save_sbml\n",
"save_sbml(filename, m1, y0, volume=1.0)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\r\n",
"<sbml xmlns=\"http://www.sbml.org/sbml/level3/version1/core\" level=\"3\" version=\"1\">\r\n",
" <model>\r\n",
" <listOfCompartments>\r\n",
" <compartment id=\"world\" spatialDimensions=\"3\" size=\"1\" constant=\"true\"/>\r\n",
" </listOfCompartments>\r\n",
" <listOfSpecies>\r\n",
" <species id=\"s0\" name=\"A\" compartment=\"world\" initialAmount=\"0\" hasOnlySubstanceUnits=\"false\" boundaryCondition=\"false\" constant=\"false\"/>\r\n",
" <species id=\"s1\" name=\"B\" compartment=\"world\" initialAmount=\"0\" hasOnlySubstanceUnits=\"false\" boundaryCondition=\"false\" constant=\"false\"/>\r\n",
" <species id=\"s2\" name=\"C\" compartment=\"world\" initialAmount=\"60\" hasOnlySubstanceUnits=\"false\" boundaryCondition=\"false\" constant=\"false\"/>\r\n",
" </listOfSpecies>\r\n",
" <listOfParameters>\r\n",
" <parameter id=\"k0\" value=\"0.01\" constant=\"true\"/>\r\n",
" <parameter id=\"k1\" value=\"0.3\" constant=\"true\"/>\r\n",
" </listOfParameters>\r\n",
" <listOfReactions>\r\n",
" <reaction id=\"r0\" reversible=\"true\" fast=\"false\">\r\n",
" <listOfReactants>\r\n",
" <speciesReference species=\"s0\" stoichiometry=\"1\" constant=\"false\"/>\r\n",
" <speciesReference species=\"s1\" stoichiometry=\"1\" constant=\"false\"/>\r\n",
" </listOfReactants>\r\n",
" <listOfProducts>\r\n",
" <speciesReference species=\"s2\" stoichiometry=\"1\" constant=\"false\"/>\r\n",
" </listOfProducts>\r\n",
" <kineticLaw>\r\n",
" <math xmlns=\"http://www.w3.org/1998/Math/MathML\">\r\n",
" <apply>\r\n",
" <times/>\r\n",
" <ci> k0 </ci>\r\n",
" <ci> s0 </ci>\r\n",
" <ci> s1 </ci>\r\n",
" </apply>\r\n",
" </math>\r\n",
" </kineticLaw>\r\n",
" </reaction>\r\n",
" <reaction id=\"r1\" reversible=\"true\" fast=\"false\">\r\n",
" <listOfReactants>\r\n",
" <speciesReference species=\"s2\" stoichiometry=\"1\" constant=\"false\"/>\r\n",
" </listOfReactants>\r\n",
" <listOfProducts>\r\n",
" <speciesReference species=\"s0\" stoichiometry=\"1\" constant=\"false\"/>\r\n",
" <speciesReference species=\"s1\" stoichiometry=\"1\" constant=\"false\"/>\r\n",
" </listOfProducts>\r\n",
" <kineticLaw>\r\n",
" <math xmlns=\"http://www.w3.org/1998/Math/MathML\">\r\n",
" <apply>\r\n",
" <times/>\r\n",
" <ci> k1 </ci>\r\n",
" <ci> s2 </ci>\r\n",
" </apply>\r\n",
" </math>\r\n",
" </kineticLaw>\r\n",
" </reaction>\r\n",
" </listOfReactions>\r\n",
" </model>\r\n",
"</sbml>\r\n"
]
}
],
"source": [
"!cat $filename"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# from ecell4.util.ports import load_sbml\n",
"from ports import load_sbml\n",
"m2, y0, volume = load_sbml(filename)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"({'C': 60.0}, 1.0)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y0, volume"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A+B>C|0.01\n",
"C>A+B|0.3\n"
]
}
],
"source": [
"show(m2)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"run_simulation(100.0, model=m2, y0=y0, volume=volume, species_list=['A', 'B', 'C'])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment