Mrg: Dev

doc/conf.py

@@ -95,7 +95,7 @@ def __getattr__(cls, name):
 version = '0.9'
 # The full version, including alpha/beta/rc tags.
 
-release = '0.9.0-b1'
+release = '0.9.0-b2'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

pytfa/analysis/manipulation.py

@@ -67,10 +67,10 @@ def apply_directionality(tmodel,solution, inplace = True):
         backward_use = _tmodel.backward_use_variable.get_by_id(this_reaction.id)
         forward_use = _tmodel.forward_use_variable.get_by_id(this_reaction.id)
 
-        backward_use.variable.lb = round(solution.x_dict[backward_use.name])
-        backward_use.variable.ub = round(solution.x_dict[backward_use.name])
+        backward_use.variable.lb = round(solution.raw[backward_use.name])
+        backward_use.variable.ub = round(solution.raw[backward_use.name])
 
-        forward_use.variable.lb  = round(solution.x_dict[forward_use.name])
-        forward_use.variable.ub  = round(solution.x_dict[forward_use.name])
+        forward_use.variable.lb  = round(solution.raw[forward_use.name])
+        forward_use.variable.ub  = round(solution.raw[forward_use.name])
 
     return _tmodel

pytfa/analysis/variability.py

@@ -75,21 +75,21 @@ def find_directionality_profiles(tmodel, bidirectional, max_iter = 1e4,
         except SolverError:
             break
 
-        profiles[iter_count] = solution.x_dict
+        profiles[iter_count] = solution.raw
         if iter_count > 0:
             sse = sum((profiles[iter_count-1] - profiles[iter_count])**2)
         else:
             sse =0
 
-        tmodel.logger.info(str(iter_count) + ' - ' + str(sse))
+        tmodel.logger.debug(str(iter_count) + ' - ' + str(sse))
 
         # active_use_variables = get_active_use_variables(this_tmodel,solution)
         active_use_variables = get_direction_use_variables(this_tmodel,solution)
         bidirectional_use_variables = [x for x in active_use_variables \
                                        if x.reaction in bidirectional_reactions]
         bool_id = ''.join('1' if isinstance(x,ForwardUseVariable) else '0' \
                 for x in bidirectional_use_variables)
-        Tracer()()
+
         # Make the expression to forbid this expression profile to happen again
         # FP_1101: FU_rxn1 + FU_rxn2 + BU_rxn3 + FU_rxn4 <= 4-1 = 3
         expr = sum(bidirectional_use_variables)
@@ -205,10 +205,10 @@ def calculate_dissipation(tmodel,solution=None):
         solution = tmodel.solution
 
     reaction_id  = [x.id for x in tmodel.reactions]
-    fluxes = solution.x_dict[reaction_id]
+    fluxes = solution.fluxes[reaction_id]
 
     deltag_var = tmodel.get_variables_of_type(DeltaG)
-    deltag = pd.Series({x.id:solution.x_dict[x.name]
+    deltag = pd.Series({x.id:solution.raw[x.name]
                                       for x in deltag_var})
     dissipation = fluxes*deltag
 

pytfa/core/model.py

@@ -28,10 +28,10 @@
 
 def timeit(method):
     """
-    Adapted from Andreas Jung's blog:
-    https://www.zopyx.com/andreas-jung/contents/a-python-decorator-for-measuring-the-execution-time-of-methods
+    Adapted from Andreas Jung's `blog
+    <https://www.zopyx.com/andreas-jung/contents/a-python-decorator-for-measuring-the-execution-time-of-methods>`_
 
-    :param method:
+    :param method: The method to time
     :return:
     """
 
@@ -121,6 +121,7 @@ def add_variable(self, kind, hook, queue=False, **kwargs):
                    **kwargs)
 
         self._var_dict[var.name] = var
+        self.logger.debug('Added variable: {}'.format(var.name))
         # self.add_cons_vars(var.variable)
 
         return var
@@ -150,6 +151,7 @@ def add_constraint(self, kind, hook, expr, queue=False,**kwargs):
                     queue=queue,
                     **kwargs)
         self._cons_dict[cons.name] = cons
+        self.logger.debug('Added constraint: {}'.format(cons.name))
         # self.add_cons_vars(cons.constraint)
 
         return cons
@@ -321,6 +323,21 @@ def get_solution(self):
         """
         Overrides the cobra.thermo.solution method, to also get the supplementary
         variables we added to the cobra_model
+
+        *   :code:`solution.fluxes` in `cobrapy` is a transformed version of the solver
+            output, as it actually calculates the _net_ flux of each reaction by
+            substracting the reverse variable value to the forward variable value.
+            This should be used anytime one needs the actual flux value
+
+        *   :code:`solution.raw` is a clear copy of the solver output. From there one
+            can access the value at solution for all the variables of the problem.
+            However, looking for a reaction ID in there will only give the
+            _forward_ flux. This should be used for any other variable than fluxes.
+
+        *   :code:`solution.values` yields variables multiplied by their scaling factor
+            (1 by default). Useful if you operated scaling on your equations for
+            numerical reasons. This does _not_ include fluxes
+
         :return:
         """
         objective_value = self.solver.objective.value

pytfa/io/dict.py

@@ -16,6 +16,7 @@
 
 from ..optim.variables import ReactionVariable, MetaboliteVariable, ModelVariable
 from ..optim.constraints import ReactionConstraint, MetaboliteConstraint, ModelConstraint
+from ..optim.utils import symbol_sum
 
 from optlang.util import expr_to_json, parse_expr
 
@@ -155,6 +156,10 @@ def get_solver_string(model):
     return SOLVER_DICT[model.solver.__class__.__module__]
 
 
+def obj_to_dict(model):
+    return {x.name: v
+            for x,v in model.objective.expression.as_coefficients_dict().items()}
+
 def model_to_dict(model):
     """
 
@@ -167,6 +172,7 @@ def model_to_dict(model):
     obj = cbd.model_to_dict(model)
 
     obj['solver'] = get_solver_string(model)
+    obj['objective'] = obj_to_dict(model)
 
     # Copy variables, constraints
     # obj['var_dict'] = archive_variables(model._var_kinds)
@@ -285,15 +291,17 @@ def model_from_dict(obj, solver=None, custom_hooks = None):
                                   id_=this_id,
                                   ub=ub,
                                   lb=lb,
-                                  queue=True)
+                                  queue=True,
+                                  scaling_factor=scaling_factor)
         elif classname in name2class:
             hook = name2hook[classname].get_by_id(this_id)
             this_class = name2class[classname]
             nv = new.add_variable(kind=this_class,
                                   hook=hook,
                                   ub = ub,
                                   lb = lb,
-                                  queue=True)
+                                  queue=True,
+                                  scaling_factor=scaling_factor)
         else:
             raise TypeError(
                 'Class {} serialization not handled yet' \
@@ -343,6 +351,11 @@ def model_from_dict(obj, solver=None, custom_hooks = None):
 
     new.repair()
 
+    try:
+        rebuild_obj_from_dict(new, obj['objective'])
+    except KeyError:
+        pass
+
     # Relaxation info
     try:
         new.relaxation = obj['relaxation']
@@ -351,6 +364,10 @@ def model_from_dict(obj, solver=None, custom_hooks = None):
 
     return new
 
+def rebuild_obj_from_dict(new, objective_dict):
+    obj_expr = symbol_sum([v*new.variables.get(x) for x,v in objective_dict.items()])
+    new.objective = obj_expr
+
 def add_custom_classes(model, custom_hooks):
     """
     Allows custom variable serialization

pytfa/io/plotting.py

@@ -71,7 +71,7 @@ def plot_thermo_displacement_histogram(tmodel,solution = None):
         thermo_displacements = tmodel.get_variables_of_type(ThermoDisplacement)
         varnames = [x.name for x in thermo_displacements]
 
-        values = solution.x_dict[varnames]
+        values = solution.raw[varnames]
 
     p1 = plot_histogram(values)
 

pytfa/optim/constraints.py

@@ -11,13 +11,14 @@
 """
 
 from ..utils.str import camel2underscores
+from .meta import ABCRequirePrefixMeta
 
 ###################################################
 ###                 CONSTRAINTS                 ###
 ###################################################
 
 
-class GenericConstraint:
+class GenericConstraint(metaclass=ABCRequirePrefixMeta):
     """
     Class to represent a generic constraint. The purpose is that the interface
      is instantiated on initialization, to follow the type of interface used
@@ -35,7 +36,7 @@ class GenericConstraint:
         :cobra_model: the cobra_model hook.
         :constraint: links directly to the cobra_model representation of tbe constraint
     """
-    prefix = ''
+    prefix = NotImplemented
 
 
     @property
@@ -159,6 +160,8 @@ def __init__(self, model, expr, id_, **kwargs):
                                    hook=model,
                                    **kwargs)
 
+    prefix = 'MODC_'
+
 
 class GeneConstraint(GenericConstraint):
     """
@@ -186,6 +189,8 @@ def id(self):
     def model(self):
         return self.gene.model
 
+    prefix = 'GC_'
+
 class ReactionConstraint(GenericConstraint):
     """
     Class to represent a variable attached to a reaction
@@ -213,6 +218,8 @@ def id(self):
     def model(self):
         return self.reaction.model
 
+    prefix = 'RC_'
+
 class MetaboliteConstraint(GenericConstraint):
     """
     Class to represent a variable attached to a enzyme
@@ -239,6 +246,8 @@ def id(self):
     def model(self):
         return self.metabolite.model
 
+    prefix = 'MC_'
+
 class NegativeDeltaG(ReactionConstraint):
     """
     Class to represent thermodynamics constraints.

pytfa/optim/meta.py

@@ -0,0 +1,28 @@
+# -*- coding: utf-8 -*-
+"""
+.. module:: pytfa
+   :platform: Unix, Windows
+   :synopsis: Thermodynamics-based Flux Analysis
+
+.. moduleauthor:: pyTFA team
+
+Metaclass declarations to force the definition of prefixes in GenericVariable
+and GeneriConstraint subclasses
+
+"""
+from abc import ABCMeta
+
+class RequirePrefixMeta(type):
+    """Metaclass that enforces child classes define prefix."""
+
+    def __init__(cls, name, bases, attrs):
+        # Skip the check if there are no parent classes,
+        # which allows base classes to not define prefix.
+        if not bases:
+            return
+        if attrs.get('prefix', NotImplemented) is NotImplemented:
+            # Choose your favorite exception.
+            raise NotImplementedError('You forgot to define a prefix for your class ;)')
+
+ABCRequirePrefixMeta = type('ABCRequirePrefixMeta',
+                            (ABCMeta, RequirePrefixMeta), {})

pytfa/optim/variables.py

@@ -9,10 +9,13 @@
 Variable declarations
 
 """
+from abc import ABCMeta
+
 from distutils.version import LooseVersion
 from optlang import __version__ as OPTLANG_VER
 
 from ..utils.str import camel2underscores
+from .meta import ABCRequirePrefixMeta
 
 from warnings import warn
 
@@ -28,8 +31,7 @@
 ###                  VARIABLES                  ###
 ###################################################
 
-
-class GenericVariable:
+class GenericVariable(metaclass=ABCRequirePrefixMeta):
     """
     Class to represent a generic variable. The purpose is that the interface
     is instantiated on initialization, to follow the type of interface used
@@ -46,7 +48,7 @@ class GenericVariable:
         :cobra_model: the cobra_model hook.
         :variable: links directly to the cobra_model representation of tbe variable
     """
-    prefix = ''
+    prefix = NotImplemented
 
     @property
     def __attrname__(self):
@@ -147,7 +149,7 @@ def unscaled(self):
     @property
     def value(self):
         try:
-            return self.model.solution.x_dict[self.name]
+            return self.model.solution.raw[self.name]
         except AttributeError:
             warn('Model need to be optimized to get a value for this variable')
 
@@ -345,6 +347,7 @@ def __init__(self, model, id_, **kwargs):
                                  model=model,
                                  hook=model,
                                  **kwargs)
+    prefix = 'MODV_'
 
 class GeneVariable(GenericVariable):
     """
@@ -422,6 +425,8 @@ def id(self):
     def model(self):
         return self.reaction.model
 
+    prefix = 'RV_'
+
 class MetaboliteVariable(GenericVariable):
     """
     Class to represent a variable attached to a enzyme
@@ -447,6 +452,8 @@ def id(self):
     def model(self):
         return self.metabolite.model
 
+    prefix = 'MV_'
+
 
 class ForwardUseVariable(ReactionVariable, BinaryVariable):
     """