added support function to load_raw_protected_data(fname)

README.md

@@ -43,8 +43,52 @@ $ pip3 install  networkred@git+https://gitlab.cs.uni-duesseldorf.de/schubert/net
 ```python
 >>> import networkred
 
-
->>> .... (yet to be filled)
+import os
+import pandas as pd
+
+    data_dir = 'sample_data/data'
+    model_name = 'Deniz_model_fba'
+    protected_parts_file = 'Deniz_model_fba_nrp.xlsx'
+
+import networkred
+
+    original_sbml = 'sample_data/SBML_models/Deniz_model_fba.xml'
+    reduced_sbml = 'sample_data/SBML_models/Deniz_model_fba_red.xml'
+    
+    # import original SBML file
+    red_model = networkred.ReduceModel(original_sbml)
+
+    # set protected parts
+    
+    
+    protect_name = os.path.join(data_dir, protected_parts_file)
+    print('load reduction parameters from:', protect_name)
+    protect_rids = None
+    protect_mids = None
+    protect_funcs = None
+    with pd.ExcelFile(protect_name) as xlsx:
+        if 'reactions' in xlsx.sheet_names:
+            protect_rids = pd.read_excel(xlsx, sheet_name='reactions', index_col=0).index.tolist()
+        if 'metabolites' in xlsx.sheet_names:
+            protect_mids = pd.read_excel(xlsx, sheet_name='metabolites', index_col=0).index.tolist()
+        if 'functions' in xlsx.sheet_names:
+            protect_funcs = pd.read_excel(xlsx, sheet_name='functions', index_col=0)
+        if 'bounds' in xlsx.sheet_names:
+            temp_fbc_bounds = pd.read_excel(xlsx, sheet_name='bounds', index_col=0)
+    red_model.set_reduction_params(protect_rids=protect_rids,
+                                   protect_mids=protect_mids,
+                                   protect_funcs=protect_funcs,
+                                   temp_fbc_bounds=temp_fbc_bounds,
+                                   model_base='original')
+
+    # reduce the network
+    red_model.reduce()
+
+    # export reduced model to sbml
+    red_model.write_sbml(reduced_sbml)
+
+
+>>> 
 ```
 
 

networkred/__init__.py

-from networkred.reduce_model import ReduceModel
-
 from networkred._version import __version__
+from networkred.reduce_model import ReduceModel, load_raw_protected_data
 
-__author__ = 'Peter Schubert'
\ No newline at end of file
+__author__ = 'Peter Schubert'

networkred/reduce_model.py

@@ -33,10 +33,12 @@ reduction process. Essential reactions are identified earlier.
 ### References
 
 [1]: Kamp A, Thiele S, Haedicke O, Klamt S. (2017) Use of CellNetAnalyzer
-in biotechnology and metabolic engineering. Journal of Biotechnolgy 261: 221-228.
+in biotechnology and metabolic engineering. Journal of Biotechnolgy 261:
+221-228.
 
-[2]: Ebrahim, A., Lerman, J.A., Palsson, B.O. et al. COBRApy: COnstraints-Based Reconstruction
-and Analysis for Python. BMC Syst Biol 7, 74 (2013). https://doi.org/10.1186/1752-0509-7-74
+[2]: Ebrahim, A., Lerman, J.A., Palsson, B.O. et al. COBRApy:
+COnstraints-Based Reconstruction and Analysis for Python. BMC Syst Biol 7, 74
+(2013). https://doi.org/10.1186/1752-0509-7-74
 
 Peter Schubert, Computational Cell Biology, HHU Duesseldorf, November 2021
 """
@@ -55,6 +57,36 @@ from cobra.flux_analysis import flux_variability_analysis, find_blocked_reaction
 from cobra.util.array import create_stoichiometric_matrix
 
 
+def load_raw_protected_data(fname):
+    """Load raw protected parts from excel file.
+
+    Reaction/metabolite identifiers not modified.
+
+    :param fname: file name with protected parts
+    :type fname: str
+    :returns: dict with protected parts including:
+        list of pretected reactions or None,
+        list of protected metabolites or None,
+        DataFrame of protected functions or None,
+        DataFrame of temporary flux bounds or None
+    :rtype: dict
+    """
+    nrp = {'reactions': None, 'metabolites': None,
+           'functions': None, 'bounds': None}
+
+    if type(fname) == str:
+        if fname.endswith('.xlsx') and os.path.exists(fname):
+            print('loading protected parts from:', fname)
+            with pd.ExcelFile(fname) as xlsx:
+                for key in nrp.keys():
+                    if key in xlsx.sheet_names:
+                        nrp[key] = pd.read_excel(xlsx, sheet_name=key,
+                                                 index_col=0)
+                        if key in ['reactions', 'metabolites']:
+                            nrp[key] = nrp[key].index.tolist()
+    return nrp
+
+
 def get_items(items_str, delim=';'):
     """Generator to return individual records.
 
@@ -195,7 +227,8 @@ class ReduceModel:
             self._orig_fbc_bounds = {}
 
     def set_reduction_params(self, protect_rids=None, protect_mids=None,
-                             protect_funcs=None, temp_fbc_bounds=None, model_base='original'):
+                             protect_funcs=None, temp_fbc_bounds=None,
+                             model_base='original'):
         """Set protected parts of the model.
 
         reaction ids and metabolite ids get converted to cobra ids (i.e. stripping of 'R_' and 'M_').

sample_data/SBML_models/Deniz_model_fba_reduced.xml

 <?xml version="1.0" encoding="UTF-8"?>
-<!-- Created by sbmlxdf version 0.2.5 on 2021-11-05 11:24 with libSBML version 5.19.0. -->
+<!-- Created by sbmlxdf version 0.2.5 on 2021-11-05 12:13 with libSBML version 5.19.0. -->
 <sbml xmlns="http://www.sbml.org/sbml/level3/version2/core" xmlns:fbc="http://www.sbml.org/sbml/level3/version1/fbc/version2" level="3" version="2" fbc:required="false">
   <model metaid="Deniz_model_fba" id="Deniz_model_fba_reduced" name="Deniz_model_fba" substanceUnits="substance" timeUnits="time" extentUnits="substance" fbc:strict="true">
     <notes>

sample_reduce_model.py

@@ -4,10 +4,10 @@
 import sys
 import os
 import logging
-import pandas as pd
 
 import networkred
 
+
 def reduce_model():
 
     # activate logging
@@ -28,44 +28,27 @@ def reduce_model():
     print('working directory :', os.getcwd())
 
     # file names and directories
-    sbml_dir = 'sample_data/SBML_models'
-    data_dir = 'sample_data/data'
-    model_name = 'Deniz_model_fba'
-    protected_parts_file = 'Deniz_model_fba_nrp.xlsx'
+    original_sbml = 'sample_data/SBML_models/Deniz_model_fba.xml'
+    reduced_sbml = 'sample_data/SBML_models/Deniz_model_fba_reduced.xml'
+    protected_parts = 'sample_data/data/Deniz_model_fba_nrp.xlsx'
 
     # load the original model
-    sbml_file = os.path.join(sbml_dir, model_name) + '.xml'
-    red_model = networkred.ReduceModel(sbml_file)
-
-    # set protected parts
-    protect_name = os.path.join(data_dir, protected_parts_file)
-    print('load reduction parameters from:', protect_name)
-    protect_rids = None
-    protect_mids = None
-    protect_funcs = None
-    with pd.ExcelFile(protect_name) as xlsx:
-        if 'reactions' in xlsx.sheet_names:
-            protect_rids = pd.read_excel(xlsx, sheet_name='reactions', index_col=0).index.tolist()
-        if 'metabolites' in xlsx.sheet_names:
-            protect_mids = pd.read_excel(xlsx, sheet_name='metabolites', index_col=0).index.tolist()
-        if 'functions' in xlsx.sheet_names:
-            protect_funcs = pd.read_excel(xlsx, sheet_name='functions', index_col=0)
-        if 'bounds' in xlsx.sheet_names:
-            temp_fbc_bounds = pd.read_excel(xlsx, sheet_name='bounds', index_col=0)
-    red_model.set_reduction_params(protect_rids=protect_rids,
-                                   protect_mids=protect_mids,
-                                   protect_funcs=protect_funcs,
-                                   temp_fbc_bounds=temp_fbc_bounds,
+    red_model = networkred.ReduceModel(original_sbml)
+
+    # load protected parts for network reduction
+    nrp = networkred.load_raw_protected_data(protected_parts)
+    red_model.set_reduction_params(protect_rids=nrp['reactions'],
+                                   protect_mids=nrp['metabolites'],
+                                   protect_funcs=nrp['functions'],
+                                   temp_fbc_bounds=nrp['bounds'],
                                    model_base='original')
 
-    # prune network (for specific dof, rmin), create snapshots every two reduced reactions
-    print('---- network pruning -----')
+    print('---- network reduction -----')
     red_model.reduce()
 
     # write reduced model to sbml
-    reduced_name = os.path.join(sbml_dir, model_name) + '_reduced.xml'
-    red_model.write_sbml(reduced_name)
-    print('reduced model converted to SBML:', reduced_name)
+    red_model.write_sbml(reduced_sbml)
+    print('reduced model converted to SBML:', reduced_sbml)
 
     logging.info('Finished')