From fb15ea69662810c1871379a8bf1eb75f6a09cc28 Mon Sep 17 00:00:00 2001
From: Peter Schubert <Peter.Schubert@hhu.de>
Date: Thu, 20 Oct 2022 17:22:04 +0200
Subject: [PATCH] ProtectedParts exposed. Create FBA Objective based on first
protected function
---
modelpruner/__init__.py | 1 +
modelpruner/core/__init__.py | 3 ++-
modelpruner/core/protected_parts.py | 32 ++++++++++++++---------------
modelpruner/models/fba_model.py | 21 ++++++++++++-------
4 files changed, 33 insertions(+), 24 deletions(-)
diff --git a/modelpruner/__init__.py b/modelpruner/__init__.py
index e422a21..4a33acb 100644
--- a/modelpruner/__init__.py
+++ b/modelpruner/__init__.py
@@ -1,5 +1,6 @@
from modelpruner._version import __version__
from modelpruner.core.model_pruner import ModelPruner
+from modelpruner.core.protected_parts import ProtectedParts
from . import core, models, problems
diff --git a/modelpruner/core/__init__.py b/modelpruner/core/__init__.py
index ca981c2..42fe4ff 100644
--- a/modelpruner/core/__init__.py
+++ b/modelpruner/core/__init__.py
@@ -1,5 +1,6 @@
from .model_pruner import ModelPruner
+from .model_pruner import ProtectedParts
-__all__ = ['ModelPruner']
+__all__ = ['ModelPruner', 'ProtectedParts']
diff --git a/modelpruner/core/protected_parts.py b/modelpruner/core/protected_parts.py
index 4f2180d..d77aeae 100644
--- a/modelpruner/core/protected_parts.py
+++ b/modelpruner/core/protected_parts.py
@@ -13,7 +13,7 @@ class ProtectedParts:
if type(protected_parts) == str:
if os.path.exists(protected_parts):
- nrp = self.load_raw_protected_data(protected_parts)
+ pp_dict = self.load_raw_protected_data(protected_parts)
print(f'Protected data loaded from {protected_parts} '
f'(last modified: {time.ctime(os.path.getmtime(protected_parts))})')
else:
@@ -21,29 +21,29 @@ class ProtectedParts:
raise FileNotFoundError
else:
assert type(protected_parts) == dict, 'expected filename or a dict'
- nrp = protected_parts
+ pp_dict = protected_parts
- self.protected_rids = set(nrp.get('reactions', []))
- self.protected_sids = set(nrp.get('metabolites', []))
- if 'bounds' in nrp:
+ self.protected_rids = set(pp_dict.get('reactions', []))
+ self.protected_sids = set(pp_dict.get('metabolites', []))
+ if 'bounds' in pp_dict:
num_cols = ['fbcLb', 'fbcUb']
- nrp['bounds'][num_cols] = nrp['bounds'][num_cols].applymap(
+ pp_dict['bounds'][num_cols] = pp_dict['bounds'][num_cols].applymap(
lambda x: np.nan if type(x) == str else x)
self.overwrite_bounds = {rid: [row['fbcLb'], row['fbcUb']]
- for rid, row in nrp['bounds'].iterrows()}
+ for rid, row in pp_dict['bounds'].iterrows()}
else:
self.overwrite_bounds = {}
self.protected_functions = {}
- if 'functions' in nrp:
+ if 'functions' in pp_dict:
num_cols = ['fbcLb', 'fbcUb', 'fraction']
- nrp['functions'][num_cols] = nrp['functions'][num_cols].applymap(
+ pp_dict['functions'][num_cols] = pp_dict['functions'][num_cols].applymap(
lambda x: np.nan if type(x) == str else x)
str_cols = ['fluxObjectives', 'reaction']
- nrp['functions'][str_cols] = nrp['functions'][str_cols].applymap(
+ pp_dict['functions'][str_cols] = pp_dict['functions'][str_cols].applymap(
lambda x: '' if type(x) != str else x)
- for func_id in list(nrp['functions'].index.unique()):
- df_pf = nrp['functions'].loc[func_id]
+ for func_id in list(pp_dict['functions'].index.unique()):
+ df_pf = pp_dict['functions'].loc[func_id]
self.protected_functions[func_id] = ProtectedFunction(df_pf)
@staticmethod
@@ -57,15 +57,15 @@ class ProtectedParts:
:returns: protected parts including:
:rtype: dict
"""
- nrp = {}
+ pp_dict = {}
with pd.ExcelFile(fname) as xlsx:
for key in ['reactions', 'metabolites']:
if key in xlsx.sheet_names:
- nrp[key] = pd.read_excel(xlsx, sheet_name=key).iloc[:, 0].to_list()
+ pp_dict[key] = pd.read_excel(xlsx, sheet_name=key).iloc[:, 0].to_list()
for key in ['functions', 'bounds']:
if key in xlsx.sheet_names:
- nrp[key] = pd.read_excel(xlsx, sheet_name=key, index_col=0)
- return nrp
+ pp_dict[key] = pd.read_excel(xlsx, sheet_name=key, index_col=0)
+ return pp_dict
class ProtectedFunction:
diff --git a/modelpruner/models/fba_model.py b/modelpruner/models/fba_model.py
index 68b2437..9021ab5 100644
--- a/modelpruner/models/fba_model.py
+++ b/modelpruner/models/fba_model.py
@@ -50,6 +50,7 @@ class FbaModel:
# lp problem will only be created once required.
# this gives chances to update e.g. flux bounds and to support pickling (multiprocessing)
self.lp = None
+ self.scaling = 'AUTO' # check also '2N'
def update_reversible_rids(self):
self.rids_rev = self.rids[self.reversible]
@@ -95,7 +96,10 @@ class FbaModel:
fwd_rev_rids = np.hstack((self.rids, self.rids_rev))
# identify groups of parallel reactions
- sorted_idx = np.lexsort(fwd_rev_s_mat_coo.todense())[0]
+ # first we sort the columns of the S-matrix (sorted_idx: index into sorted S-matrix)
+ # parallel reactions would be next to each other in sorted_idx
+ # second we check if parallel columns are identical (delta_coo) i.e. difference is zero vector
+ sorted_idx = np.lexsort(fwd_rev_s_mat_coo.toarray())
groups = []
consumed_idxs = set()
for pos in range(len(sorted_idx)):
@@ -104,8 +108,8 @@ class FbaModel:
group = [idx]
for adjacent_pos in range(pos + 1, len(sorted_idx)):
candiate_idx = sorted_idx[adjacent_pos]
- if (fwd_rev_s_mat_coo.getcol(idx) != fwd_rev_s_mat_coo.getcol(candiate_idx))\
- .getnnz() == 0:
+ delta_coo = fwd_rev_s_mat_coo.getcol(idx) - fwd_rev_s_mat_coo.getcol(candiate_idx)
+ if delta_coo.getnnz() == 0:
consumed_idxs.add(candiate_idx)
group.append(candiate_idx)
else:
@@ -142,7 +146,7 @@ class FbaModel:
status.update(self.full_model_shape)
return status
- def export_pruned_model(self, pruned_sbml):
+ def export_pruned_model(self, pruned_sbml, df_fba_objectives):
"""Export the pruned network (or snapshot) to SBML.
Component information of initial network will be carried over,
@@ -153,10 +157,13 @@ class FbaModel:
:param pruned_sbml: pathname of pruned network, ending with '.xml'
:type pruned_sbml: str
+ :param df_fba_objectives: new fba objective to overwrite existing model objetive
+ :type df_fba_objectives: pandas DataFrame
"""
sbml_model = sbmlxdf.Model(self.sbml_fname)
model_dict = sbml_model.to_df()
pruned_mdict = model_dict.copy()
+ pruned_mdict['fbcObjectives'] = df_fba_objectives.copy()
pruned_mdict['reactions'] = model_dict['reactions'].loc[self.rids]
pruned_mdict['species'] = model_dict['species'].loc[self.sids]
@@ -372,7 +379,7 @@ class FbaModel:
self.set_lp_objective(pf.objective, pf.obj_dir)
self.update_lp_flux_bounds(overwrite_bounds)
- res = self.lp.solve()
+ res = self.lp.solve(scaling=self.scaling)
# print(res['success'], res['fun'])
self.reset_lp_flux_bounds(overwrite_bounds.keys())
self.remove_lp_objective(pf.objective)
@@ -428,10 +435,10 @@ class FbaModel:
flux_max = np.zeros(len(rids))
for idx, rid in enumerate(rids):
self.set_lp_objective({rid: 1}, 'minimize')
- res = self.lp.solve()
+ res = self.lp.solve(scaling=self.scaling)
flux_min[idx] = res['fun'] if res['success'] else np.nan
self.lp.set_obj_dir('maximize')
- res = self.lp.solve()
+ res = self.lp.solve(scaling=self.scaling)
flux_max[idx] = res['fun'] if res['success'] else np.nan
self.remove_lp_objective({rid: 1})
--
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