Merge pull request #60 from SystemsBioinformatics/dev

CBMPy 0.8.7 dev merge

Author: bgoli

.gitignore

@@ -1,4 +1,5 @@
 .svn
+build
 cbmpy.egg-info
 __pycache__
 wing-cbmpy.wpr 

CONTRIBUTORS.md

@@ -1,5 +1,8 @@
 # Contributors
 
+## Release 0.8.7
+Many thanks to Steven Wijnen for his debugging, testing and help with the QP, constraints and FBCV3 implementation. This release supports his dcFBA/endPointFBA https://github.com/SystemsBioinformatics/dynamic-community-fba package.
+
 ## Release 0.8.4
 Many thanks go to @willigot for their suggestions and code contributions.
 

README.md

@@ -1,6 +1,6 @@
 # CBMPy
-PySCeS Constraint Based Modelling (http://cbmpy.sourceforge.net)
-Copyright (C) 2010-2023 Brett G. Olivier, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
+PySCeS Constraint Based Modelling (https://systemsbioinformatics.github.io/cbmpy/)
+Copyright (C) 2010-2024 Brett G. Olivier, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
 
 This program is free software: you can redistribute it and/or modify
 it under the terms of the GNU General Public License as published by
@@ -18,38 +18,40 @@ along with this program.  If not, see <http://www.gnu.org/licenses/>
 Author: Brett G. Olivier (@bgoli)
 
 ## About
-PySCeS CBMPy (http://cbmpy.sourceforge.net) is a new platform for constraint
+CBMPy (https://systemsbioinformatics.github.io/cbmpy/) is a new platform for constraint
 based modelling and analysis. It has been designed using principles developed
 in the PySCeS simulation software project: usability, flexibility and accessibility.
 Its architecture is both extensible and flexible using data structures that are intuitive
 to  the biologist (metabolites, reactions, compartments) while transparently translating
 these into the underlying mathematical structures used in advanced analysis (LP's, MILP's).
 
-PySCeS CBMPy implements popular analyses such as FBA, FVA, element/charge
+CBMPy fully supports all the SBML Flux Balance Constraints (FBC) interoperability standards.
+
+CBMPy implements popular analyses such as FBA, FVA, element/charge
 balancing, network analysis and model editing as well as advanced methods
 developed specifically for the ecosystem modelling: minimal distance methods,
 flux minimization and input selection. To cater for a diverse range of modelling
-needs PySCeS CBMPy supports user interaction via:
+needs CBMPy supports user interaction via:
 
 - interactive console, scripting for advanced use or as a library for software development
 - GUI, for quick access to a visual representation of the model, analysis methods and annotation tools
 - SOAP based web services: using the Mariner framework much high level functionality is exposed for integration into web tools
 
-For more information on the development and use of CBMPy (https://github.com/SystemsBioinformatics/cbmpy)
+For more information on the development and use of CBMPy (https://systemsbioinformatics.github.io/cbmpy/)
 
-CBMPy has been tested on Windows 7 and 8.1, 10, Mac OSX and Ubuntu Linux 12.04, 14.04, 16.04, 20.04.
-CBMPy is currently developed on Python 3.7 and Python 3.6 or newer is highly recommended
+CBMPy has been tested on Windows 7 and 8.1, 10, 11, Mac OSX and Ubuntu Linux 12.04, 14.04, 16.04, 20.04, 22.04
+CBMPy is currently developed on Python 3.10 and Python 3.8 or newer is highly recommended
 
 ## Install
-The best way to get the basic CBMPy running is to install from **PyPI** or create an Anaconda environment. CBMPy is developed on GitHub (https://github.com/SystemsBioinformatics/cbmpy)
+The best way to get the basic CBMPy running is to install from **PyPI** or create an Anaconda environment. CBMPy is developed on GitHub (https://systemsbioinformatics.github.io/cbmpy/)
 
 ### Install with pip using requirements.txt
-From a terrminal or command prompt try:
+From a terrminal or command prompt try to install the required packages
 
 `pip install -r requirements.txt`
 
-### New experimental PyPI install method.
-`pip install cbmpy[sbml]`
+### Then install CBMPy
+`pip install cbmpy`
 
 ### Install by creating an Anaconda environment using environment.yml
 From a terminal or command prompt try:
@@ -75,4 +77,4 @@ Once you have installed CBMPy it can be easily upgraded.
 ### Anaconda update
 `conda update cbmpy`
 
-(c) Brett G. Olivier, Amsterdam, 2014-2023
+(c) Brett G. Olivier, Amsterdam, 2014-2024

RELEASES.md

@@ -1,16 +1,18 @@
 # Release history
 
-## Release 0.8.4 (2023)
-Primarily a Python 9.x compatability release
+## Release 0.8.7 (2023)
+Intermediatery release that includes bug fixes, code cleanup and new features to support endPoint FBA. Has alpha support for Flux Balance Constraints V3 features including quadratic objectives, non-storichiometric user constraints and KeyValue pairs. Try the latest format with cbmpy.writeSBML3FBCV3.
 
+## Release 0.8.4 (2022)
+Primarily a Python 3.x compatability release
 
 ## Release 0.8.2 (2021)
 ## Release 0.8.1 (2021-07-23)
-
 Primarily a bugfix release to fix the SymPy compatability issues as well as improved requirements handling.
 
 
 
 
 
-(c) Brett G. Olivier, Amsterdam, 2021
+(c) Brett G. Olivier, Amsterdam, 2023
+cbmpy.writeSBML3FBCV2(

cbmpy-anaconda-py10.yml

@@ -0,0 +1,200 @@
+name: cbmpy
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - aiofiles=22.1.0=py310haa95532_0
+  - aiosqlite=0.18.0=py310haa95532_0
+  - anyio=3.5.0=py310haa95532_0
+  - appdirs=1.4.4=pyhd3eb1b0_0
+  - argon2-cffi=21.3.0=pyhd3eb1b0_0
+  - argon2-cffi-bindings=21.2.0=py310h2bbff1b_0
+  - asttokens=2.0.5=pyhd3eb1b0_0
+  - attrs=22.1.0=py310haa95532_0
+  - babel=2.11.0=py310haa95532_0
+  - backcall=0.2.0=pyhd3eb1b0_0
+  - beautifulsoup4=4.12.2=py310haa95532_0
+  - biopython=1.78=py310h2bbff1b_0
+  - blas=1.0=mkl
+  - bleach=4.1.0=pyhd3eb1b0_0
+  - brotli=1.0.9=h2bbff1b_7
+  - brotli-bin=1.0.9=h2bbff1b_7
+  - brotlipy=0.7.0=py310h2bbff1b_1002
+  - bzip2=1.0.8=he774522_0
+  - ca-certificates=2023.05.30=haa95532_0
+  - certifi=2023.7.22=py310haa95532_0
+  - cffi=1.15.1=py310h2bbff1b_3
+  - charset-normalizer=2.0.4=pyhd3eb1b0_0
+  - colorama=0.4.6=py310haa95532_0
+  - comm=0.1.2=py310haa95532_0
+  - contourpy=1.0.5=py310h59b6b97_0
+  - cryptography=41.0.2=py310h31511bf_0
+  - cycler=0.11.0=pyhd3eb1b0_0
+  - debugpy=1.6.7=py310hd77b12b_0
+  - decorator=5.1.1=pyhd3eb1b0_0
+  - defusedxml=0.7.1=pyhd3eb1b0_0
+  - entrypoints=0.4=py310haa95532_0
+  - executing=0.8.3=pyhd3eb1b0_0
+  - fonttools=4.25.0=pyhd3eb1b0_0
+  - freetype=2.12.1=ha860e81_0
+  - giflib=5.2.1=h8cc25b3_3
+  - glib=2.69.1=h5dc1a3c_2
+  - gst-plugins-base=1.18.5=h9e645db_0
+  - gstreamer=1.18.5=hd78058f_0
+  - icc_rt=2022.1.0=h6049295_2
+  - icu=58.2=ha925a31_3
+  - idna=3.4=py310haa95532_0
+  - intel-openmp=2023.1.0=h59b6b97_46319
+  - ipykernel=6.25.0=py310h9909e9c_0
+  - ipython=8.12.0=py310haa95532_0
+  - ipython_genutils=0.2.0=pyhd3eb1b0_1
+  - ipywidgets=8.0.4=py310haa95532_0
+  - jedi=0.18.1=py310haa95532_1
+  - jinja2=3.1.2=py310haa95532_0
+  - jpeg=9e=h2bbff1b_1
+  - json5=0.9.6=pyhd3eb1b0_0
+  - jsonschema=4.17.3=py310haa95532_0
+  - jupyter=1.0.0=py310haa95532_8
+  - jupyter_client=7.4.9=py310haa95532_0
+  - jupyter_console=6.6.3=py310haa95532_0
+  - jupyter_core=5.3.0=py310haa95532_0
+  - jupyter_events=0.6.3=py310haa95532_0
+  - jupyter_server=1.23.4=py310haa95532_0
+  - jupyter_server_fileid=0.9.0=py310haa95532_0
+  - jupyter_server_ydoc=0.8.0=py310haa95532_1
+  - jupyter_ydoc=0.2.4=py310haa95532_0
+  - jupyterlab=3.6.3=py310haa95532_0
+  - jupyterlab_pygments=0.1.2=py_0
+  - jupyterlab_server=2.22.0=py310haa95532_0
+  - jupyterlab_widgets=3.0.5=py310haa95532_0
+  - kiwisolver=1.4.4=py310hd77b12b_0
+  - krb5=1.19.4=h5b6d351_0
+  - lerc=3.0=hd77b12b_0
+  - libbrotlicommon=1.0.9=h2bbff1b_7
+  - libbrotlidec=1.0.9=h2bbff1b_7
+  - libbrotlienc=1.0.9=h2bbff1b_7
+  - libclang=14.0.6=default_hb5a9fac_1
+  - libclang13=14.0.6=default_h8e68704_1
+  - libdeflate=1.17=h2bbff1b_0
+  - libffi=3.4.4=hd77b12b_0
+  - libiconv=1.16=h2bbff1b_2
+  - libogg=1.3.5=h2bbff1b_1
+  - libpng=1.6.39=h8cc25b3_0
+  - libsodium=1.0.18=h62dcd97_0
+  - libtiff=4.5.0=h6c2663c_2
+  - libvorbis=1.3.7=he774522_0
+  - libwebp=1.2.4=hbc33d0d_1
+  - libwebp-base=1.2.4=h2bbff1b_1
+  - libxml2=2.10.3=h0ad7f3c_0
+  - libxslt=1.1.37=h2bbff1b_0
+  - lxml=4.9.2=py310h2bbff1b_0
+  - lz4-c=1.9.4=h2bbff1b_0
+  - markupsafe=2.1.1=py310h2bbff1b_0
+  - matplotlib=3.7.1=py310haa95532_1
+  - matplotlib-base=3.7.1=py310h4ed8f06_1
+  - matplotlib-inline=0.1.6=py310haa95532_0
+  - mistune=0.8.4=py310h2bbff1b_1000
+  - mkl=2023.1.0=h8bd8f75_46356
+  - mkl-service=2.4.0=py310h2bbff1b_1
+  - mkl_fft=1.3.6=py310h4ed8f06_1
+  - mkl_random=1.2.2=py310h4ed8f06_1
+  - mpmath=1.3.0=py310haa95532_0
+  - munkres=1.1.4=py_0
+  - nbclassic=0.5.5=py310haa95532_0
+  - nbclient=0.5.13=py310haa95532_0
+  - nbconvert=6.5.4=py310haa95532_0
+  - nbformat=5.7.0=py310haa95532_0
+  - nest-asyncio=1.5.6=py310haa95532_0
+  - notebook=6.5.4=py310haa95532_1
+  - notebook-shim=0.2.2=py310haa95532_0
+  - numpy=1.25.0=py310h055cbcc_0
+  - numpy-base=1.25.0=py310h65a83cf_0
+  - openssl=1.1.1v=h2bbff1b_0
+  - packaging=23.0=py310haa95532_0
+  - pandocfilters=1.5.0=pyhd3eb1b0_0
+  - parso=0.8.3=pyhd3eb1b0_0
+  - pcre=8.45=hd77b12b_0
+  - pickleshare=0.7.5=pyhd3eb1b0_1003
+  - pillow=9.4.0=py310hd77b12b_0
+  - pip=23.2.1=py310haa95532_0
+  - platformdirs=2.5.2=py310haa95532_0
+  - ply=3.11=py310haa95532_0
+  - pooch=1.4.0=pyhd3eb1b0_0
+  - prometheus_client=0.14.1=py310haa95532_0
+  - prompt-toolkit=3.0.36=py310haa95532_0
+  - prompt_toolkit=3.0.36=hd3eb1b0_0
+  - psutil=5.9.0=py310h2bbff1b_0
+  - pure_eval=0.2.2=pyhd3eb1b0_0
+  - pycparser=2.21=pyhd3eb1b0_0
+  - pygments=2.15.1=py310haa95532_1
+  - pyopenssl=23.2.0=py310haa95532_0
+  - pyparsing=3.0.9=py310haa95532_0
+  - pyqt=5.15.7=py310hd77b12b_0
+  - pyqt5-sip=12.11.0=py310hd77b12b_0
+  - pyrsistent=0.18.0=py310h2bbff1b_0
+  - pysocks=1.7.1=py310haa95532_0
+  - python=3.10.12=h966fe2a_0
+  - python-dateutil=2.8.2=pyhd3eb1b0_0
+  - python-fastjsonschema=2.16.2=py310haa95532_0
+  - python-json-logger=2.0.7=py310haa95532_0
+  - python-libsbml=5.20.1=py310h00ffb61_0
+  - python_abi=3.10=2_cp310
+  - pytz=2022.7=py310haa95532_0
+  - pywin32=305=py310h2bbff1b_0
+  - pywinpty=2.0.10=py310h5da7b33_0
+  - pyyaml=6.0=py310h2bbff1b_1
+  - pyzmq=23.2.0=py310hd77b12b_0
+  - qt-main=5.15.2=he8e5bd7_8
+  - qt-webengine=5.15.9=hb9a9bb5_5
+  - qtconsole=5.4.2=py310haa95532_0
+  - qtpy=2.2.0=py310haa95532_0
+  - qtwebkit=5.212=h2bbfb41_5
+  - requests=2.31.0=py310haa95532_0
+  - rfc3339-validator=0.1.4=py310haa95532_0
+  - rfc3986-validator=0.1.1=py310haa95532_0
+  - scipy=1.10.1=py310h309d312_1
+  - send2trash=1.8.0=pyhd3eb1b0_1
+  - setuptools=68.0.0=py310haa95532_0
+  - sip=6.6.2=py310hd77b12b_0
+  - six=1.16.0=pyhd3eb1b0_1
+  - sniffio=1.2.0=py310haa95532_1
+  - soupsieve=2.4=py310haa95532_0
+  - sqlite=3.41.2=h2bbff1b_0
+  - stack_data=0.2.0=pyhd3eb1b0_0
+  - sympy=1.11.1=py310haa95532_0
+  - tbb=2021.8.0=h59b6b97_0
+  - terminado=0.17.1=py310haa95532_0
+  - tinycss2=1.2.1=py310haa95532_0
+  - tk=8.6.12=h2bbff1b_0
+  - toml=0.10.2=pyhd3eb1b0_0
+  - tomli=2.0.1=py310haa95532_0
+  - tornado=6.3.2=py310h2bbff1b_0
+  - traitlets=5.7.1=py310haa95532_0
+  - typing-extensions=4.7.1=py310haa95532_0
+  - typing_extensions=4.7.1=py310haa95532_0
+  - tzdata=2023c=h04d1e81_0
+  - ucrt=10.0.22621.0=h57928b3_0
+  - urllib3=1.26.16=py310haa95532_0
+  - vc=14.2=h21ff451_1
+  - vc14_runtime=14.36.32532=hfdfe4a8_17
+  - vs2015_runtime=14.36.32532=h05e6639_17
+  - wcwidth=0.2.5=pyhd3eb1b0_0
+  - webencodings=0.5.1=py310haa95532_1
+  - websocket-client=0.58.0=py310haa95532_4
+  - wheel=0.38.4=py310haa95532_0
+  - widgetsnbextension=4.0.5=py310haa95532_0
+  - win_inet_pton=1.1.0=py310haa95532_0
+  - winpty=0.4.3=4
+  - xlrd=2.0.1=pyhd3eb1b0_1
+  - xlsxwriter=3.1.1=py310haa95532_0
+  - xlwt=1.3.0=py310haa95532_0
+  - xz=5.4.2=h8cc25b3_0
+  - y-py=0.5.9=py310hb6bf4ef_0
+  - yaml=0.2.5=he774522_0
+  - ypy-websocket=0.8.2=py310haa95532_0
+  - zeromq=4.3.4=hd77b12b_0
+  - zlib=1.2.13=h8cc25b3_0
+  - zstd=1.5.5=hd43e919_0
+  - pip:
+      - nose-py3
+prefix: C:\Anaconda3\envs\cbmpy

cbmpy/CBCPLEX.py

@@ -2,7 +2,7 @@
 CBMPy: CBCPLEX module
 =====================
 PySCeS Constraint Based Modelling (http://cbmpy.sourceforge.net)
-Copyright (C) 2009-2022 Brett G. Olivier, VU University Amsterdam, Amsterdam, The Netherlands
+Copyright (C) 2009-2024 Brett G. Olivier, VU University Amsterdam, Amsterdam, The Netherlands
 
 This program is free software: you can redistribute it and/or modify
 it under the terms of the GNU General Public License as published by
@@ -17,8 +17,8 @@
 You should have received a copy of the GNU General Public License
 along with this program.  If not, see <http://www.gnu.org/licenses/>
 
-Author: Brett G. Olivier
-Contact email: [email protected]
+Author: Brett G. Olivier PhD
+Contact developers: https://github.com/SystemsBioinformatics/cbmpy/issues
 Last edit: $Author: bgoli $ ($Id: CBCPLEX.py 710 2020-04-27 14:22:34Z bgoli $)
 
 """
@@ -212,6 +212,7 @@ def cplx_constructLPfromFBA(fba, fname=None):
     # print(lp.parameters.simplex.get_changed())
     lp.set_problem_name('%s' % (fba.getId()))
     lp.variables.add(names=fba.N.col)
+
     try:
         # define objective
         osense = fba.getActiveObjective().operation.lower()
@@ -222,12 +223,42 @@ def cplx_constructLPfromFBA(fba, fname=None):
         else:
             raise RuntimeError('\n%s - is not a valid objective operation' % osense)
         lp.objective.set_name(fba.getActiveObjective().getId())
-        lp.objective.set_linear(
-            [
-                (fo.reaction, fo.coefficient)
-                for fo in fba.getActiveObjective().fluxObjectives
-            ]
-        )
+
+        if fba.__FBC_VERSION__ < 3:
+            lp.objective.set_linear(
+                [
+                    (fo.reaction, fo.coefficient)
+                    for fo in fba.getActiveObjective().flux_objectives
+                ]
+            )
+        else:
+            # TODO bgoli this needs to be cleaned up
+            if len(fba.getActiveObjective().getLinearFluxObjectives()) > 0:
+                print('Linear term(s) detected and added to objective function.')
+                # print(fba.getActiveObjective().getLinearFluxObjectives())
+                # print([
+                        # (fo.reaction, fo.coefficient)
+                        # for fo in fba.getActiveObjective().getLinearFluxObjectives()
+                    # ])
+                lp.objective.set_linear(
+                    [
+                        (fo.reaction, fo.coefficient)
+                        for fo in fba.getActiveObjective().getLinearFluxObjectives()
+                    ]
+                )
+            if len(fba.getActiveObjective().getQuadraticFluxObjectives()) > 0:
+                print('Quadratric terms detected and added to objective function.')
+                # print(fba.getActiveObjective().getQuadraticFluxObjectives())
+                # print([
+                    # (fo.reaction, fo.reaction2, float(fo.coefficient))
+                        # for fo in fba.getActiveObjective().getQuadraticFluxObjectives()
+                    # ])
+                lp.objective.set_quadratic_coefficients(
+                    [
+                        (fo.reaction, fo.reaction2, float(fo.coefficient))
+                        for fo in fba.getActiveObjective().getQuadraticFluxObjectives()
+                    ])
+
     except AttributeError:
         print('\nWARNING(CPLEX create LP): no objective function defined')
 
@@ -390,8 +421,10 @@ def cplx_analyzeModel(
     if build_n:
         f.buildStoichMatrix()
 
+    # I've moved the check gene activity function to the evaluation
     if f.__check_gene_activity__:
         f.updateNetwork(lower=0.0, upper=0.0)
+        f.__check_gene_activity__ = False
 
     fid = f.id