Merge pull request #222 from biosustain/devel

Towards 0.11.7

.gitignore

@@ -54,6 +54,112 @@ docs/_build
 /.DS_Store
 .cache
 /coverage.xml
+### Python template
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
 
 cplex/
 cplex*.tar.gz

README.rst

@@ -4,7 +4,7 @@ Cameo—Computer Aided Metabolic Engineering and Optimization
 .. summary-start
 
 |Join the chat at https://gitter.im/biosustain/cameo| |PyPI| |License|
-|Build Status| |Coverage Status| |DOI|
+|Build Status| |Coverage Status| |DOI| |zenhub|
 
 What is cameo?
 ~~~~~~~~~~~~~~
@@ -139,3 +139,5 @@ Contributions
    :target: https://coveralls.io/r/biosustain/cameo?branch=devel
 .. |DOI| image:: https://zenodo.org/badge/5031/biosustain/cameo.svg
    :target: https://zenodo.org/badge/latestdoi/5031/biosustain/cameo
+.. |zenhub| image:: https://img.shields.io/badge/Shipping_faster_with-ZenHub-5e60ba.svg?style=flat-square
+   :target: https://zenhub.com

cameo/__init__.py

@@ -31,7 +31,7 @@
 
 # optimize the model and print the objective value
 solution = model.optimize()
-print 'Objective value:', solution.f
+print 'Objective value:', solution.objective_value
 
 # Determine a set of gene deletions that will optimize the production
 # of a desired compound

cameo/core/pathway.py

@@ -102,12 +102,14 @@ def to_file(self, file_path, sep="\t"):
         with open(file_path, "w") as output_file:
             for reaction in self.reactions:
                 equation = _build_equation(reaction.metabolites)
-                output_file.write(reaction.id + sep +
-                                  equation + sep +
-                                  reaction.lower_bound + sep +
-                                  reaction.upper_bound + sep +
-                                  reaction.name + sep +
-                                  reaction.notes.get("pathway_note", "") + "\n")
+                output_file.write(sep.join(map(str, [
+                    reaction.id,
+                    equation,
+                    reaction.lower_bound,
+                    reaction.upper_bound,
+                    reaction.name,
+                    reaction.notes.get("pathway_note", "")
+                ])) + "\n")
 
     def plug_model(self, model):
         """

cameo/core/target.py

@@ -342,8 +342,11 @@ def __gt__(self, other):
 
     def __eq__(self, other):
         if isinstance(other, GeneModulationTarget):
-            return (self.id == other.id and self._value == other._value and
-                    self._reference_value == other._reference_value)
+            return (
+                (self.id == other.id) and (
+                    self._value == other._value) and (
+                        self._reference_value == other._reference_value)
+            )
         else:
             return False
 
@@ -425,8 +428,11 @@ def __gt__(self, other):
 
     def __eq__(self, other):
         if isinstance(other, ReactionModulationTarget):
-            return (self.id == other.id and self._value == other._value and
-                    self._reference_value == other._reference_value)
+            return (
+                (self.id == other.id) and (
+                    self._value == other._value) and (
+                        self._reference_value == other._reference_value)
+            )
         else:
             return False
 

cameo/flux_analysis/analysis.py

@@ -172,9 +172,13 @@ def find_blocked_reactions(model):
         for exchange in model.exchanges:
             exchange.bounds = (-9999, 9999)
         fva_solution = flux_variability_analysis(model)
-    return frozenset(reaction for reaction in model.reactions
-                     if round(fva_solution.lower_bound(reaction.id), config.ndecimals) == 0 and
-                     round(fva_solution.upper_bound(reaction.id), config.ndecimals) == 0)
+    return frozenset(
+        reaction for reaction in model.reactions
+        if round(
+            fva_solution.lower_bound(reaction.id),
+            config.ndecimals) == 0 and round(
+            fva_solution.upper_bound(reaction.id), config.ndecimals) == 0
+    )
 
 
 def flux_variability_analysis(model, reactions=None, fraction_of_optimum=0., pfba_factor=None,
@@ -303,14 +307,16 @@ def phenotypic_phase_plane(model, variables, objective=None, source=None, points
 
     nice_variable_ids = [_nice_id(reaction) for reaction in variable_reactions]
     variable_reactions_ids = [reaction.id for reaction in variable_reactions]
-    phase_plane = pandas.DataFrame(envelope,
-                                   columns=(variable_reactions_ids +
-                                            ['objective_lower_bound',
-                                             'objective_upper_bound',
-                                             'c_yield_lower_bound',
-                                             'c_yield_upper_bound',
-                                             'mass_yield_lower_bound',
-                                             'mass_yield_upper_bound']))
+    phase_plane = pandas.DataFrame(
+        envelope, columns=(variable_reactions_ids + [
+            'objective_lower_bound',
+            'objective_upper_bound',
+            'c_yield_lower_bound',
+            'c_yield_upper_bound',
+            'mass_yield_lower_bound',
+            'mass_yield_upper_bound'
+        ])
+    )
 
     if objective is None:
         objective = model.objective
@@ -517,7 +523,7 @@ def _cycle_free_fva(model, reactions=None, sloppy=True, sloppy_bound=666):
         else:
             logger.debug('Determine if {} with bound {} is a cycle'.format(reaction.id, bound))
             solution = get_solution(model)
-            v0_fluxes = solution.x_dict
+            v0_fluxes = solution.fluxes
             v1_cycle_free_fluxes = remove_infeasible_cycles(model, v0_fluxes)
             if abs(v1_cycle_free_fluxes[reaction.id] - bound) < 10 ** -6:
                 fva_sol[reaction.id]['lower_bound'] = bound
@@ -556,7 +562,7 @@ def _cycle_free_fva(model, reactions=None, sloppy=True, sloppy_bound=666):
         else:
             logger.debug('Determine if {} with bound {} is a cycle'.format(reaction.id, bound))
             solution = get_solution(model)
-            v0_fluxes = solution.x_dict
+            v0_fluxes = solution.fluxes
             v1_cycle_free_fluxes = remove_infeasible_cycles(model, v0_fluxes)
             if abs(v1_cycle_free_fluxes[reaction.id] - bound) < 1e-6:
                 fva_sol[reaction.id]['upper_bound'] = v0_fluxes[reaction.id]

cameo/flux_analysis/simulation.py

@@ -178,7 +178,8 @@ def create_objective(model, variables):
         solution = model.optimize(raise_error=True)
 
         if reactions is not None:
-            result = FluxDistributionResult({r: solution.get_primal_by_id(r) for r in reactions}, solution.f)
+            result = FluxDistributionResult(
+                {r: solution.get_primal_by_id(r) for r in reactions}, solution.objective_value)
         else:
             result = FluxDistributionResult.from_solution(solution)
         return result
@@ -275,7 +276,8 @@ def create_objective(model, variables):
 
         solution = model.optimize(raise_error=True)
         if reactions is not None:
-            result = FluxDistributionResult({r: solution.get_primal_by_id(r) for r in reactions}, solution.f)
+            result = FluxDistributionResult(
+                {r: solution.get_primal_by_id(r) for r in reactions}, solution.objective_value)
         else:
             result = FluxDistributionResult.from_solution(solution)
         return result
@@ -369,7 +371,8 @@ def update_lower_constraint(model, constraint, reaction, variable, flux_value, e
 
         solution = model.optimize(raise_error=True)
         if reactions is not None:
-            result = FluxDistributionResult({r: solution.get_primal_by_id(r) for r in reactions}, solution.f)
+            result = FluxDistributionResult(
+                {r: solution.get_primal_by_id(r) for r in reactions}, solution.objective_value)
         else:
             result = FluxDistributionResult.from_solution(solution)
         return result
@@ -392,7 +395,7 @@ class FluxDistributionResult(Result):
 
     @classmethod
     def from_solution(cls, solution, *args, **kwargs):
-        return cls(solution.fluxes, solution.f, *args, **kwargs)
+        return cls(solution.fluxes, solution.objective_value, *args, **kwargs)
 
     def __init__(self, fluxes, objective_value, *args, **kwargs):
         super(FluxDistributionResult, self).__init__(*args, **kwargs)
@@ -538,13 +541,13 @@ def display_on_map(self, map_name=None, palette="YlGnBu"):
     # print("cobra fba")
     # tic = time.time()
     # cb_model.optimize(solver='cglpk')
-    # print("flux sum:", sum([abs(val) for val in list(cb_model.solution.x_dict.values())]))
+    # print("flux sum:", sum([abs(val) for val in list(cb_model.solution.fluxes.values())]))
     # print("cobra fba runtime:", time.time() - tic)
 
     # print("cobra pfba")
     # tic = time.time()
     # optimize_minimal_flux(cb_model, solver='cglpk')
-    # print("flux sum:", sum([abs(val) for val in list(cb_model.solution.x_dict.values())]))
+    # print("flux sum:", sum([abs(val) for val in list(cb_model.solution.fluxes.values())]))
     # print("cobra pfba runtime:", time.time() - tic)
 
     print("pfba")

cameo/flux_analysis/util.py

@@ -77,7 +77,7 @@ def remove_infeasible_cycles(model, fluxes, fix=()):
         except OptimizationError as e:
             logger.warning("Couldn't remove cycles from reference flux distribution.")
             raise e
-        result = solution.x_dict
+        result = solution.fluxes
         return result
 
 

cameo/strain_design/deterministic/flux_variability_based.py

@@ -77,7 +77,7 @@
 
 
 class DifferentialFVA(StrainDesignMethod):
-    """Differential flux variability analysis.
+    r"""Differential flux variability analysis.
 
     Compares flux ranges of a reference model to a set of models that
     have been parameterized to lie on a grid of evenly spaced points in the
@@ -354,22 +354,37 @@ def run(self, surface_only=True, improvements_only=True, progress=True, view=Non
             df['suddenly_essential'] = False
             df['free_flux'] = False
 
-            df.loc[(df.lower_bound == 0) & (df.upper_bound == 0) &
-                   (ref_upper_bound != 0) & (ref_lower_bound != 0), 'KO'] = True
-
-            df.loc[((ref_upper_bound < 0) & (df.lower_bound > 0) |
-                   ((ref_lower_bound > 0) & (df.upper_bound < 0))), 'flux_reversal'] = True
-
-            df.loc[((df.lower_bound <= 0) & (df.lower_bound > 0)) |
-                   ((ref_lower_bound >= 0) & (df.upper_bound <= 0)), 'suddenly_essential'] = True
+            df.loc[
+                (df.lower_bound == 0) & (
+                    df.upper_bound == 0) & (
+                        ref_upper_bound != 0) & (
+                            ref_lower_bound != 0),
+                'KO'
+            ] = True
+
+            df.loc[
+                ((ref_upper_bound < 0) & (df.lower_bound > 0) | (
+                    (ref_lower_bound > 0) & (df.upper_bound < 0))),
+                'flux_reversal'
+            ] = True
+
+            df.loc[
+                ((df.lower_bound <= 0) & (df.lower_bound > 0)) | (
+                    (ref_lower_bound >= 0) & (df.upper_bound <= 0)),
+                'suddenly_essential'
+            ] = True
 
             is_reversible = numpy.asarray([
-                self.design_space_model.reactions.get_by_id(i).reversibility for i in df.index], dtype=bool)
+                self.design_space_model.reactions.get_by_id(i).reversibility
+                for i in df.index], dtype=bool)
             not_reversible = numpy.logical_not(is_reversible)
 
-            df.loc[((df.lower_bound == -1000) & (df.upper_bound == 1000) & is_reversible) |
-                   ((df.lower_bound == 0) & (df.upper_bound == 1000) & not_reversible) |
-                   ((df.lower_bound == -1000) & (df.upper_bound == 0) & not_reversible), 'free_flux'] = True
+            df.loc[
+                ((df.lower_bound == -1000) & (df.upper_bound == 1000) & is_reversible) | (
+                    (df.lower_bound == 0) & (df.upper_bound == 1000) & not_reversible) | (
+                        (df.lower_bound == -1000) & (df.upper_bound == 0) & not_reversible),
+                'free_flux'
+            ] = True
 
             df['reaction'] = df.index
             df['excluded'] = df['reaction'].isin(self.exclude)
@@ -481,9 +496,9 @@ def _generate_designs(cls, solutions, reference_fva, reference_fluxes):
         for _, solution in solutions.groupby(('biomass', 'production')):
             targets = []
             relevant_targets = solution.loc[
-                (numpy.abs(solution['normalized_gaps']) > non_zero_flux_threshold) &
-                numpy.logical_not(solution['excluded']) &
-                numpy.logical_not(solution['free_flux'])
+                (numpy.abs(solution['normalized_gaps']) > non_zero_flux_threshold) & (
+                    numpy.logical_not(solution['excluded'])) & (
+                        numpy.logical_not(solution['free_flux']))
             ]
             for rid, relevant_row in relevant_targets.iterrows():
                 if relevant_row.KO:
@@ -648,8 +663,9 @@ def _display_on_map_static(self, index, map_name, palette="RdYlBu", **kwargs):
             data = self.nth_panel(index)
             # Find values above decimal precision and not NaN
             data = data.loc[
-                ~numpy.isnan(data['normalized_gaps']) &
-                (data['normalized_gaps'].abs() > non_zero_flux_threshold)]
+                ~numpy.isnan(data['normalized_gaps']) & (
+                    data['normalized_gaps'].abs() > non_zero_flux_threshold)
+            ]
             data.index = data['reaction']
 
             reaction_data = data['normalized_gaps'].copy()