Merge branch 'devel' into optknock

cameo/strain_design/heuristic/multiprocess/__init__.py

@@ -12,4 +12,31 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+
+"""
+Multiprocess heuristic optimization.
+
+It implements an islands model. Multiple processes run in parallel and each single process is an heuristic optimization.
+All of those processes are connected to a Queue and every iteration an individual from a process migrates through the
+Queue to another process enriching the results of the receiving by introducing variability.
+
+For information on how to run Gene Knockout or Reaction Knockout optimizations refer to
+~cameo.strain_design.heuristic.optimization
+
+The result is the same as in the single objective. The knockouts solutions resulting from all processes are merged.
+
+Examples
+--------
+>>> from cameo import models
+>>> from cameo.strain_design.heuristic.multiprocess import MultiprocessGeneKnockoutOptimization
+>>> from cameo.strain_design.heuristic.objective_functions import biomass_product_coupled_yield
+>>> import inspyred
+>>> model = models.bigg.iJO1366
+>>> objective_function = biomass_product_coupled_yield('Ec_biomass_iJO1366_core_53p95M', 'EX_succ_e', 'EX_glc__D_e')
+>>> opt = MultiprocessGeneKnockoutOptimization(model=model, objective_function=objective_function,
+>>>                                            heuristic_method=inspyred.ec.GA, max_migrants=1)
+>>> result = opt.run()
+
+
+"""
 from .optimization import MultiprocessGeneKnockoutOptimization, MultiprocessReactionKnockoutOptimization

cameo/strain_design/heuristic/multiprocess/migrators.py

@@ -14,6 +14,8 @@
 
 from __future__ import absolute_import, print_function
 
+__all__ = ['MultiprocessingMigrator']
+
 import six.moves.queue
 from cameo.parallel import RedisQueue
 from uuid import uuid4

cameo/strain_design/heuristic/multiprocess/observers.py

@@ -14,6 +14,8 @@
 
 from __future__ import absolute_import, print_function
 
+__all__ = ['CliMultiprocessProgressObserver', 'IPythonNotebookMultiprocessProgressObserver']
+
 import six
 from six.moves.queue import Empty
 from uuid import uuid4

cameo/strain_design/heuristic/multiprocess/optimization.py

@@ -39,6 +39,16 @@ class MultiprocessRunner(object):
     Runner for multiprocessing model. It generates the non-pickable
     objects on the beginning of the process.
 
+    Attributes
+    ----------
+    island_class: class
+        The class to be used when building the island process
+    init_kwargs: dict
+        The island_class constructor arguments.
+    migrator: Queue (supporting multiprocess)
+        The queue used to migrate individuals between islands
+    run_kwargs: dict
+        The arguments necessary to run the island
     """
 
     def __init__(self, island_class, init_kwargs, migrator, run_kwargs):
@@ -59,7 +69,7 @@ class MultiprocessHeuristicOptimization(StrainDesignMethod):
     Heuristic Optimization abstract implementation.
 
     Arguments
-    =========
+    ---------
 
     model: SolverBasedModel
         A model to simulate.
@@ -108,7 +118,7 @@ class MultiprocessKnockoutOptimization(MultiprocessHeuristicOptimization):
     Heuristic Knockout Optimization Abstract implementation.
 
     Arguments
-    =========
+    ---------
 
     model: SolverBasedModel
         A model to simulate.
@@ -166,15 +176,15 @@ def run(self, view=config.default_view, number_of_islands=None, **kwargs):
         for observer in self.observers:
             observer.finish()
 
-        return reduce(KnockoutOptimizationResult.merge, results)
+        return reduce(KnockoutOptimizationResult.__iadd__, results)
 
 
 class MultiprocessReactionKnockoutOptimization(MultiprocessKnockoutOptimization):
     """
     Heuristic Knockout Optimization Reaction implementation.
 
     Arguments
-    =========
+    ---------
 
     model: SolverBasedModel
         A model to simulate.
@@ -217,7 +227,7 @@ class MultiprocessGeneKnockoutOptimization(MultiprocessKnockoutOptimization):
     Heuristic Knockout Optimization Gene implementation.
 
     Arguments
-    =========
+    ---------
 
     model: SolverBasedModel
         A model to simulate.

cameo/strain_design/heuristic/multiprocess/plotters.py

@@ -14,6 +14,8 @@
 
 from __future__ import absolute_import, print_function
 
+__all__ = ['IPythonNotebookBokehMultiprocessPlotObserver']
+
 import six.moves.queue
 
 from uuid import uuid1

cameo/strain_design/heuristic/objective_functions.py

@@ -14,11 +14,13 @@
 # limitations under the License.
 
 from __future__ import absolute_import, print_function
+from functools import partial
+from cameo.util import TimeMachine
 
 __all__ = ['biomass_product_coupled_yield', 'product_yield', 'number_of_knockouts']
 
 from cobra import Reaction
-from cameo import config
+from cameo import config, flux_variability_analysis
 
 
 class ObjectiveFunction(object):
@@ -117,6 +119,71 @@ def reactions(self):
         return [self.biomass, self.product, self.substrate]
 
 
+class biomass_product_coupled_min_yield(ObjectiveFunction):
+    """
+    Biomass-Product Coupled Yield: (v[biomass] * min(v[product])) / v[substrate] [1]
+
+    Parameters
+    ----------
+    biomass: str or Reaction
+        biomass reaction identifier
+    product: str or Reaction
+        product reaction identifier
+    substrate: str or Reaction
+        substrate reaction identifier
+
+    Returns
+    -------
+    float
+        fitness value
+
+    """
+
+    def __init__(self, biomass, product, substrate, *args, **kwargs):
+        super(biomass_product_coupled_min_yield, self).__init__(*args, **kwargs)
+        if isinstance(biomass, Reaction):
+            biomass = biomass.id
+        self.biomass = biomass
+        if isinstance(product, Reaction):
+            product = product.id
+        self.product = product
+        if isinstance(substrate, Reaction):
+            substrate = substrate.id
+        self.substrate = substrate
+        self.__name__ = self.__class__.__name__
+
+    def __call__(self, model, solution, decoded_representation):
+        try:
+            biomass_flux = round(solution.fluxes[self.biomass], config.ndecimals)
+            with TimeMachine() as tm:
+                biomass_reaction = model.reactions.get_by_id(self.biomass)
+                tm(do=partial(setattr, biomass_reaction, 'lower_bound', biomass_flux),
+                   undo=partial(setattr, biomass_reaction, 'lower_bound', biomass_reaction.lower_bound))
+                for reaction_ko in decoded_representation[0]:
+                    reaction_ko.knock_out(tm)
+
+                fva_res = flux_variability_analysis(model, reactions=[self.product])
+
+            min_product_flux = fva_res["lower_bound"][self.product]
+            substrate_flux = round(abs(solution.fluxes[self.substrate]), config.ndecimals)
+            return round((biomass_flux * min_product_flux) / substrate_flux, config.ndecimals)
+
+        except ZeroDivisionError:
+            return 0.0
+
+    def _repr_latex_(self):
+        return "$$bpcy = \\frac{(%s * min(%s))}{%s}$$" % (
+            self.biomass.replace("_", "\\_"), self.product.replace("_", "\\_"), self.substrate.replace("_", "\\_"))
+
+    @property
+    def name(self):
+        return "bpcy = (%s * min(%s)) / %s" % (self.biomass, self.product, self.substrate)
+
+    @property
+    def reactions(self):
+        return [self.biomass, self.product, self.substrate]
+
+
 class product_yield(ObjectiveFunction):
     """
     Product Yield Objective function: v[product]/v[substrate]