Commit 30413e7b authored by Andreas Tille's avatar Andreas Tille
Browse files

New upstream version 0.13.3

parent e3e44933

.github/ISSUE_TEMPLATE.md

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@@ -8,8 +8,7 @@ Please explain: 


#### Code Sample



Create a [minimal, complete, verifiable example

](https://stackoverflow.com/help/mcve).

Create a [minimal, complete, verifiable example](https://stackoverflow.com/help/mcve).



```python

# Paste your code here.
@@ -20,9 +19,13 @@ Create a [minimal, complete, verifiable example 


#### Expected Output



#### Output of `cobra.show_versions()`

#### Dependency Information



Please paste the output of `python -c "from cobra import show_versions;

show_versions()"` in the details block below.



<details>

# Paste the output of `import cobra;cobra.show_versions()` here.



[Paste output here.]



</details>

.travis.yml

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Original line number Diff line number Diff line
@@ -2,8 +2,7 @@ language: python 
python: 3.5

sudo: false

cache:

  directories:

    - $HOME/.cache/pip

  pip: true

git:

  depth: 2
@@ -15,8 +14,6 @@ branches: 


env:

  global:

    - secure: "hkKBaGLvoDVgktSKR3BmX+mYlGzHw9EO11MRHtiH8D9BbdygOR9p9aSV/OxkaRWhnkSP5/0SXqVgBrvU1g5OsR6cc85UQSpJ5H5jVnLoWelIbTxMCikjxDSkZlseD7ZEWrKZjRo/ZN2qym0HRWpsir3qLpl8W25xHRv/sK7Z6g8="

    - secure: "DflyBz+QiyhlhBxn4wN00xu248EJUMjKTxUZQN6wq22qV55xO3ToGJTy9i4D6OBfZGAlSXxjjKCJ2+0sAjsghBSDEK56ud3EEg/08TIo7/T8ex/C58FsGoGFz3yDBATmquClEWN8vAMrLdxwniHmQVCBZCP/phdt5dct0AUuDc8="

    - GITHUB_REPO=opencobra/cobrapy



matrix:
@@ -80,7 +77,7 @@ deploy: 
      repo: $GITHUB_REPO

      python: '3.6'

      condition: $TRAVIS_OS_NAME == "linux"

    user: $PYPI_USERNAME

    user: cobrapy

    password: $PYPI_PASSWORD

  - provider: script

    skip_cleanup: true

appveyor.yml

+2 −6
Original line number Diff line number Diff line
@@ -8,23 +8,18 @@ environment: 


  global:

    PIP_CACHE_DIR: "pip_cache"

    PIP_DISABLE_PIP_VERSION_CHECK: "yes"



  matrix:

    - PYTHON: "C:\\Miniconda-x64"

      CONDA: true



    - PYTHON: "C:\\Miniconda35-x64"

      CONDA: true



    - PYTHON: "C:\\Miniconda36-x64"

      CONDA: true



    - PYTHON: "C:\\Python27-x64"

      TOXENV: py27



    - PYTHON: "C:\\Python35-x64"

      TOXENV: py35



    - PYTHON: "C:\\Python36-x64"

      TOXENV: py36
@@ -46,6 +41,7 @@ install: 
  - ps: |

      if ($env:CONDA -eq "true") {

        conda config --set always_yes yes --set changeps1 no;

        conda config --add channels conda-forge

        conda install -q pip setuptools wheel numpy scipy;

        pip install -r develop-requirements.txt;

        pip install .

benchmarks/geometric_fba.ipynb

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%% Cell type:code id: tags:



``` python

import logging

```



%% Cell type:code id: tags:



``` python

logging.basicConfig(level="DEBUG")

```



%% Cell type:code id: tags:



``` python

from cobra.test import create_test_model

```



%% Output



    DEBUG:optlang.util:Gurobi python bindings found at /home/moritz/.virtualenvs/cobra/lib/python3.5/site-packages/gurobipy

    DEBUG:optlang.util:GLPK python bindings found at /home/moritz/.virtualenvs/cobra/lib/python3.5/site-packages/swiglpk

    DEBUG:optlang.util:Mosek python bindings not available.

    DEBUG:optlang.util:CPLEX python bindings found at /home/moritz/.virtualenvs/cobra/lib/python3.5/site-packages/cplex

    DEBUG:optlang.util:Scipy solver not available

    DEBUG:pip._internal.utils.misc:lzma module is not available

    DEBUG:pip._internal.vcs:Registered VCS backend: git

    DEBUG:pip._internal.vcs:Registered VCS backend: hg

    DEBUG:pip._internal.vcs:Registered VCS backend: svn

    DEBUG:pip._internal.vcs:Registered VCS backend: bzr



%% Cell type:code id: tags:



``` python

from cobra.flux_analysis import geometric_fba

```



%% Cell type:code id: tags:



``` python

model = create_test_model("textbook")

```



%% Cell type:code id: tags:



``` python

model.solver = "cplex"

```



%% Cell type:code id: tags:



``` python

logging.getLogger().setLevel(logging.DEBUG)

```



%% Cell type:code id: tags:



``` python

%time geometric_fba(model)

```



%% Output



    DEBUG:cobra.flux_analysis.geometric:Iteration: 1; delta: 4e-13; status: optimal.



    CPU times: user 481 ms, sys: 0 ns, total: 481 ms

    Wall time: 480 ms



    <Solution 0.000 at 0x7f0c62d3f6a0>



%% Cell type:code id: tags:



``` python

model.solver = "gurobi"

```



%% Cell type:code id: tags:



``` python

%time geometric_fba(model)

```



%% Output



    DEBUG:cobra.flux_analysis.geometric:Iteration: 1; delta: 6.47e-12; status: optimal.



    CPU times: user 504 ms, sys: 2.91 ms, total: 507 ms

    Wall time: 505 ms



    <Solution 0.000 at 0x7f0c6288be10>



%% Cell type:code id: tags:



``` python

model.solver = "glpk"

```



%% Cell type:code id: tags:



``` python

%time geometric_fba(model)

```



%% Output



    DEBUG:optlang.glpk_interface:Status undefined. GLPK status code returned by glp_simplex was 1

    DEBUG:cobra.flux_analysis.geometric:Iteration: 1; delta: 2.96e-13; status: optimal.



    CPU times: user 263 ms, sys: 3.46 ms, total: 267 ms

    Wall time: 263 ms



    <Solution -0.000 at 0x7f0c6283d9b0>

benchmarks/objective_benchmark.ipynb

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%% Cell type:code id: tags:



``` python

from cobra.io import read_sbml_model

```



%% Cell type:code id: tags:



``` python

from optlang.symbolics import Zero, One, add, mul, Add, Mul, Real

```



%% Cell type:code id: tags:



``` python

one = Real(1.0)

```



%% Cell type:code id: tags:



``` python

model = read_sbml_model("/home/moritz/Projects/memote/Models/iJO1366.xml.gz")

```



%% Cell type:code id: tags:



``` python

import cobra.util.solver as sutil

```



%% Cell type:code id: tags:



``` python

from itertools import chain

```



%% Cell type:code id: tags:



``` python

model.solver = "glpk"

```



%% Cell type:code id: tags:



``` python

reaction_variables = ((rxn.forward_variable, rxn.reverse_variable)

                      for rxn in model.reactions)

variables = list(chain(*reaction_variables))

```



%% Cell type:code id: tags:



``` python

%%timeit

with model:

    model.objective = model.problem.Objective(

        Zero, direction='min', sloppy=True,

        name="_pfba_objective")

    model.objective.set_linear_coefficients({v: 1.0 for v in variables})

```



%% Output



    146 ms ± 3.94 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)



%% Cell type:code id: tags:



``` python

%%timeit

with model:

    model.objective = model.problem.Objective(

        add([mul(one, v) for v in variables]),

        direction='min', sloppy=True, name="_pfba_objective")

```



%% Output



    149 ms ± 2.13 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)



%% Cell type:code id: tags:



``` python

model.solver = "gurobi"

```



%% Cell type:code id: tags:



``` python

reaction_variables = ((rxn.forward_variable, rxn.reverse_variable)

                      for rxn in model.reactions)

variables = list(chain(*reaction_variables))

```



%% Cell type:code id: tags:



``` python

%%timeit

with model:

    model.objective = model.problem.Objective(

        Zero, direction='min', sloppy=True,

        name="_pfba_objective")

    model.objective.set_linear_coefficients({v: 1.0 for v in variables})

```



%% Output



    13.7 ms ± 269 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)



%% Cell type:code id: tags:



``` python

%%timeit

with model:

    model.objective = model.problem.Objective(

        add([mul(one, v) for v in variables]),

        direction='min', sloppy=True, name="_pfba_objective")

```



%% Output



    218 ms ± 2.55 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)



%% Cell type:code id: tags:



``` python

model.solver = "cplex"

```



%% Cell type:code id: tags:



``` python

reaction_variables = ((rxn.forward_variable, rxn.reverse_variable)

                      for rxn in model.reactions)

variables = list(chain(*reaction_variables))

```



%% Cell type:code id: tags:



``` python

%%timeit

with model:

    model.objective = model.problem.Objective(

        Zero, direction='min', sloppy=True,

        name="_pfba_objective")

    model.objective.set_linear_coefficients({v: 1.0 for v in variables})

```



%% Output



    2.04 s ± 32.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)



%% Cell type:code id: tags:



``` python

%%timeit

with model:

    model.objective = model.problem.Objective(

        add([mul(one, v) for v in variables]),

        direction='min', sloppy=True, name="_pfba_objective")

```



%% Output



    183 ms ± 5.28 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)