Chane internal module referencing

README.md

@@ -24,7 +24,7 @@ An HTML documentation of the source code of AutoPACMEN's Python modules can be f
 This HTML documentation was automatically generated using [pdoc3](https://pdoc3.github.io/pdoc/) (link accessed on Oct 30, 2019).
 The HTML documentation's starting point is "index.html" in the "./html/autopacmen" subfolder.
 
-In addition, the exemplary usage of AutoPACMEN with iJO1366* is explained in AutoPACMEN's publication Supplementary File 1.
+All scripts starting with "ec_model_2019_06_25" show the exemplary usage of AutoPACMEN for the generation of iJO1366*. All these scripts are intended to be run from the "autopacmen" subfolder of this repository. AutoPACMEN's exemplary usage is explained in AutoPACMEN's publication Supplementary File 1.
 
 <b>Note:</b> As it has a huge file size, the downloaded complete BRENDA text file brenda_downloads.txt (as described in
 AutoPACMEN's manual) is not included here.

autopacmen/analysis_fva_comparison.py

@@ -25,19 +25,21 @@
 # External module for command-line interfaces
 import click
 # Internal module, contains the actual FBA comparison function
-from submodules.fva_comparison import fva_comparison_with_sbml
+from .submodules.fva_comparison import fva_comparison_with_sbml
 
 
 # Set-up command-line parameters using click decorators
 @click.command()
 @click.option("--sbml_original_path",
               required=True,
-              type=click.Path(exists=True, file_okay=True, dir_okay=True, readable=True),
+              type=click.Path(exists=True, file_okay=True,
+                              dir_okay=True, readable=True),
               prompt="Original SBML path",
               help="Full SBML path of original model without protein allocation constraints")
 @click.option("--sbml_protein_constrained_path",
               required=True,
-              type=click.Path(exists=True, file_okay=True, dir_okay=True, readable=True),
+              type=click.Path(exists=True, file_okay=True,
+                              dir_okay=True, readable=True),
               prompt="SBML path of sMOMENT-enhanced model",
               help="Full SBML path of sMOMENT-enhanced model.")
 @click.option("--objective",
@@ -55,7 +57,8 @@ def fba_comparison_cli(sbml_original_path: str, sbml_protein_constrained_path: s
     Example: Print a comparative FVA for the non-constrained model 'C:\\original.xml' and the sMOMENT-model 'C:\\pac.xml' and the objective 'ACALD':
     python analysis_fva_comparison.py --sbml_original_path C:\\original.xml --sbml_protein_constrained_path C:\\pac.xml --objective ACALD
     """
-    fva_comparison_with_sbml(sbml_original_path, sbml_protein_constrained_path, objective)
+    fva_comparison_with_sbml(
+        sbml_original_path, sbml_protein_constrained_path, objective)
 
 
 # Start-up routine if script is called

autopacmen/analysis_fva_prot_pool.py

@@ -24,7 +24,7 @@
 import click
 from typing import List
 # Internal modules
-from submodules.fva_prot_pool import fva_prot_pool_with_sbml
+from .submodules.fva_prot_pool import fva_prot_pool_with_sbml
 
 
 # Set-up command-line parameters using click decorators

autopacmen/data_create_combined_kcat_database.py

@@ -22,7 +22,7 @@
 # External modules
 import click
 # Internal modules
-from submodules.create_combined_kcat_database import create_combined_kcat_database
+from .submodules.create_combined_kcat_database import create_combined_kcat_database
 
 
 # Set-up command-line parameters using click decorators

autopacmen/data_parse_bigg_metabolites_file.py

@@ -23,7 +23,7 @@
 # External modules
 import click
 # Internal modules
-from submodules.parse_bigg_metabolites_file import parse_bigg_metabolites_file
+from .submodules.parse_bigg_metabolites_file import parse_bigg_metabolites_file
 
 
 # Set-up command-line parameters using click decorators

autopacmen/data_parse_brenda_json_for_model.py

@@ -23,19 +23,21 @@
 # External modules
 import click
 # Internal modules
-from submodules.parse_brenda_json_for_model import parse_brenda_json_for_model
+from .submodules.parse_brenda_json_for_model import parse_brenda_json_for_model
 
 
 # Set-up command-line parameters using click decorators
 @click.command()
 @click.option("--sbml_path",
               required=True,
-              type=click.Path(exists=True, file_okay=True, dir_okay=True, readable=True),
+              type=click.Path(exists=True, file_okay=True,
+                              dir_okay=True, readable=True),
               prompt="Path to SBML model",
               help="Full path to the SBML with the model of which the BRENDA JSON will be derived.")
 @click.option("--brenda_json_path",
               required=True,
-              type=click.Path(exists=True, file_okay=True, dir_okay=True, readable=True),
+              type=click.Path(exists=True, file_okay=True,
+                              dir_okay=True, readable=True),
               prompt="BRENDA JSON path",
               help="Full path to the BRENDA JSON created with data_parse_brenda_textfile.py")
 @click.option("--json_output_path",

autopacmen/data_parse_brenda_textfile.py

@@ -23,7 +23,7 @@
 # External modules
 import click
 # Internal modules
-from submodules.parse_brenda_textfile import parse_brenda_textfile
+from .submodules.parse_brenda_textfile import parse_brenda_textfile
 
 
 # Set-up command-line parameters using click decorators

autopacmen/data_parse_sabio_rk_for_model.py

@@ -24,7 +24,7 @@
 # External modules
 import click
 # Internal modules
-from submodules.parse_sabio_rk_for_model import parse_sabio_rk_for_model_with_sbml
+from .submodules.parse_sabio_rk_for_model import parse_sabio_rk_for_model_with_sbml
 
 # Set-up command-line parameters using click decorators
 @click.command()

autopacmen/ec_model_2019_06_25_CALIBRATOR_get_reaction_flux_control_and_differential_reactions.py

@@ -22,11 +22,11 @@
 # External modules
 import cobra
 # Internal modules
-from ec_model_data_scenarios_for_optimization import ec_model_scenarios_for_optimization
-from ec_model_data_set_up_model import set_up_ec_model_with_sbml
-from submodules.reaction_flux_control_by_scenario import reaction_flux_control_by_scenario
-from submodules.get_differential_reactions import get_differential_reactions
-from submodules.helper_general import json_write
+from .ec_model_2019_06_25_data_scenarios_for_optimization import ec_model_scenarios_for_optimization
+from .ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
+from .submodules.reaction_flux_control_by_scenario import reaction_flux_control_by_scenario
+from .submodules.get_differential_reactions import get_differential_reactions
+from .submodules.helper_general import json_write
 
 
 # Set-up of project

autopacmen/ec_model_2019_06_25_analysis_fva_prot_pool.py

@@ -18,8 +18,8 @@
 
 """
 
-from submodules.fva_prot_pool import fva_prot_pool
-from ec_model_data_set_up_model import set_up_ec_model_with_sbml
+from .submodules.fva_prot_pool import fva_prot_pool
+from .ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
 
 model = set_up_ec_model_with_sbml("ec_model_output/iJO1366_GECKO.xml", .225)
 model.reactions.EX_glc__D_e.lower_bound = -1000

autopacmen/compare_gecko_and_gecko_analogon.py → autopacmen/ec_model_2019_06_25_compare_gecko_and_gecko_analogon.py

@@ -16,22 +16,26 @@
 
 import cobra
 
-gecko = cobra.io.read_sbml_model("ec_model_2019_06_25_output/iJO1366_2019_06_25_GECKO.xml")
-analogon = cobra.io.read_sbml_model("ec_model_2019_06_25_output/iJO1366_sMOMENT_2019_06_25_GECKO_ANALOGON.xml")
+gecko = cobra.io.read_sbml_model(
+    "ec_model_2019_06_25_output/iJO1366_2019_06_25_GECKO.xml")
+analogon = cobra.io.read_sbml_model(
+    "ec_model_2019_06_25_output/iJO1366_sMOMENT_2019_06_25_GECKO_ANALOGON.xml")
 
 gecko_reactions_with_arm = []
 for reaction in gecko.reactions:
     if "for gene rule" in reaction.name:
         continue
-    metabolite_ids = [x.id for x in reaction.metabolites.keys() if x.id.startswith("im_")]
+    metabolite_ids = [x.id for x in reaction.metabolites.keys()
+                      if x.id.startswith("im_")]
     if len(metabolite_ids) == 1:
         gecko_reactions_with_arm.append(reaction.id.split("_TG_")[0])
 
 analogon_reactions_with_arm = []
 for reaction in analogon.reactions:
     if "Arm reaction" in reaction.name:
         continue
-    metabolite_ids = [x.id for x in reaction.metabolites.keys() if x.id.startswith("armm_")]
+    metabolite_ids = [x.id for x in reaction.metabolites.keys()
+                      if x.id.startswith("armm_")]
     if len(metabolite_ids) == 1:
         analogon_reactions_with_arm.append(reaction.id.split("_GPRSPLIT")[0])
 
@@ -40,7 +44,8 @@
 
 print("===STRUCTURAL COMPARISON OF ORIGINAL GECKO AND SMOMENT-BASED GECKO-ANALOGOUS MODEL===")
 print("Number of arm reactions - original GECKO:", len(gecko_reactions_with_arm))
-print("Number of arm reactions - sMOMENT GECKO analogon:", len(analogon_reactions_with_arm))
+print("Number of arm reactions - sMOMENT GECKO analogon:",
+      len(analogon_reactions_with_arm))
 difference = analogon_reactions_with_arm - gecko_reactions_with_arm
 print("---")
 print("Number of reactions - original GECKO: ", len(gecko.reactions))

autopacmen/ec_model_2019_06_25_data_read_supplementary_table_of_keff_paper.py

@@ -23,7 +23,7 @@
 import openpyxl
 from typing import Any, Dict, List
 
-from submodules.helper_general import json_write
+from .submodules.helper_general import json_write
 
 # Get kcats
 workbook = openpyxl.load_workbook("ec_model_2019_06_25_input_keff_paper/c3mb70119k-1.xlsx", read_only=True)

autopacmen/ec_model_2019_06_25_data_set_up_model.py

@@ -16,7 +16,7 @@
 """ec_model_data_set_up_model.py"""
 
 import cobra
-from ec_model_2019_06_25_data_standard_exchange_scenario import ec_model_shut_down_reactions
+from .ec_model_2019_06_25_data_standard_exchange_scenario import ec_model_shut_down_reactions
 
 
 def set_up_ec_model(model: cobra.Model, prot_pool: float):

autopacmen/ec_model_2019_06_25_figure_comparison_with_other_models_with_monk_et_al_values.py

@@ -24,9 +24,9 @@
 import matplotlib.pyplot as plt
 import numpy as np
 from scipy.stats import linregress, pearsonr, spearmanr
-from ec_model_2019_06_25_data_scenarios_for_moment_comparison import exchange_reactions_by_c_source
-from ec_model_2019_06_25_data_standard_exchange_scenario import ec_model_shut_down_reactions
-from ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
+from .ec_model_2019_06_25_data_scenarios_for_moment_comparison import exchange_reactions_by_c_source
+from .ec_model_2019_06_25_data_standard_exchange_scenario import ec_model_shut_down_reactions
+from .ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
 
 with open("ec_model_2019_06_25_input/c_sources_S3_Adadi_2012_with_monk_values.txt", "r") as f:
     lines = f.readlines()

autopacmen/ec_model_2019_06_25_figure_fva_variability_data.py

@@ -41,26 +41,32 @@ def _get_fva_statistics(model):
         # Minimum
         with model:
             if reaction.id.endswith("reverse"):
-                forward_reaction_name = reaction.id.replace("reverse", "forward")
+                forward_reaction_name = reaction.id.replace(
+                    "reverse", "forward")
                 model.reactions.get_by_id(forward_reaction_name).knock_out()
             if reaction.id.endswith("forward"):
-                reverse_reaction_name = reaction.id.replace("forward", "reverse")
+                reverse_reaction_name = reaction.id.replace(
+                    "forward", "reverse")
                 model.reactions.get_by_id(reverse_reaction_name).knock_out()
 
-            model.objective = model_original.problem.Objective(-1 * model.reactions.get_by_id(reaction.id).flux_expression)
+            model.objective = model_original.problem.Objective(
+                -1 * model.reactions.get_by_id(reaction.id).flux_expression)
             minimization_solution = model.optimize()
             minimum = minimization_solution.fluxes[reaction.id]
 
         # Maximum
         with model:
             if reaction.id.endswith("reverse"):
-                forward_reaction_name = reaction.id.replace("reverse", "forward")
+                forward_reaction_name = reaction.id.replace(
+                    "reverse", "forward")
                 model.reactions.get_by_id(forward_reaction_name).knock_out()
             if reaction.id.endswith("forward"):
-                reverse_reaction_name = reaction.id.replace("forward", "reverse")
+                reverse_reaction_name = reaction.id.replace(
+                    "forward", "reverse")
                 model.reactions.get_by_id(reverse_reaction_name).knock_out()
 
-            model.objective = model_original.problem.Objective(1 * model.reactions.get_by_id(reaction.id).flux_expression)
+            model.objective = model_original.problem.Objective(
+                1 * model.reactions.get_by_id(reaction.id).flux_expression)
 
             maximization_solution = model.optimize()
             maximum = maximization_solution.fluxes[reaction.id]
@@ -78,8 +84,10 @@ def _get_fva_statistics(model):
     mean_minimum = statistics.mean(minimums)
     mean_maximum = statistics.mean(maximums)
     num_zeroes = len([x for x in variabilities if x < 10e-10])
-    mean_variability = statistics.mean([x for x in variabilities if x > 10e-10])
-    median_variability = statistics.median([x for x in variabilities if x > 10e-10])
+    mean_variability = statistics.mean(
+        [x for x in variabilities if x > 10e-10])
+    median_variability = statistics.median(
+        [x for x in variabilities if x > 10e-10])
 
     fva_dict["MEAN"] = {}
     fva_dict["MEAN"]["minimum"] = mean_minimum
@@ -109,7 +117,8 @@ def split_all_reversibles(model: cobra.Model) -> cobra.Model:
         reverse_reaction.id += "_REV"
         reverse_reaction.upper_bound = -reaction.lower_bound
         reverse_reaction.lower_bound = 0
-        reverse_reaction_metabolites_copy = copy.deepcopy(reverse_reaction.metabolites)
+        reverse_reaction_metabolites_copy = copy.deepcopy(
+            reverse_reaction.metabolites)
         for key in list(reverse_reaction_metabolites_copy.keys()):
             reverse_reaction_metabolites_copy[key] *= -2
         reverse_reaction.add_metabolites(reverse_reaction_metabolites_copy)
@@ -143,8 +152,10 @@ def _add_worksheet(workbook, model_name, fva_dict):
 
 name_original = "iJO1366_shut_down_scenario"
 name_smoment = "sMOMENT_2019_06_25_sds_mc_fm_50"
-model_smoment = cobra.io.read_sbml_model("ec_model_2019_06_25_output_optimization/iJO1366_sMOMENT_2019_06_25_STANDARD_EXCHANGE_SCENARIO_MANUAL_CHANGES_FMINCON_CHANGE_FACTOR_50.xml")
-model_original = cobra.io.read_sbml_model("ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions_STANDARD_EXCHANGE_SCENARIO.xml")
+model_smoment = cobra.io.read_sbml_model(
+    "ec_model_2019_06_25_output_optimization/iJO1366_sMOMENT_2019_06_25_STANDARD_EXCHANGE_SCENARIO_MANUAL_CHANGES_FMINCON_CHANGE_FACTOR_50.xml")
+model_original = cobra.io.read_sbml_model(
+    "ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions_STANDARD_EXCHANGE_SCENARIO.xml")
 
 model_smoment.reactions.get_by_id("EX_glc__D_e").lower_bound = -9.53
 model_smoment.reactions.get_by_id("ER_pool_TG_").upper_bound = .095
@@ -187,7 +198,8 @@ def _add_worksheet(workbook, model_name, fva_dict):
 
 # Create XLSX
 print("Write XLSX \\o/")
-workbook = xlsxwriter.Workbook(f"ec_model_2019_06_25_test_fva/fva_comparison_2019_06_25_fitted_mc_fm_50_vs_original_iJO1366_both_with_standard_exchange_scenario.xlsx")
+workbook = xlsxwriter.Workbook(
+    f"ec_model_2019_06_25_test_fva/fva_comparison_2019_06_25_fitted_mc_fm_50_vs_original_iJO1366_both_with_standard_exchange_scenario.xlsx")
 workbook = _add_worksheet(workbook, name_original, fva_dict_original)
 workbook = _add_worksheet(workbook, name_smoment, fva_dict_smoment)
 

autopacmen/ec_model_2019_06_25_figure_secretion_behavior_on_different_maximal_glucose_uptake_rates.py

@@ -22,7 +22,7 @@
 
 import cobra
 import numpy as np
-from ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
+from .ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
 
 
 def fba_with_glucose_levels(model, glucose_levels, name):

autopacmen/ec_model_2019_06_25_fva_comparison.py

@@ -18,7 +18,7 @@
 
 """
 
-from submodules.fva_comparison import fva_comparison_with_sbml
+from .submodules.fva_comparison import fva_comparison_with_sbml
 
 SBML_ORIGINAL: str = "./ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions.xml"
 SBML_SMOMENT: str = "ec_model_2019_06_25_output/iJO1366_sMOMENT_2019_06_25.xml"

autopacmen/ec_model_2019_06_25_leucine_test.py

@@ -6,7 +6,8 @@
 min_yield = .2
 min_growth = .1
 
-model = cobra.io.read_sbml_model("ec_model_2019_06_25_output_optimization/iJO1366star.xml")
+model = cobra.io.read_sbml_model(
+    "ec_model_2019_06_25_output_optimization/iJO1366star.xml")
 
 biomass_reaction = model.reactions.get_by_id(biomass_reaction_id)
 substrate_reaction = model.reactions.get_by_id(substrate_reaction_id)
@@ -30,4 +31,5 @@
 print(model.summary())
 print(-solution.fluxes[substrate_reaction_id])
 print(solution.fluxes[product_reaction_id])
-print(solution.fluxes[product_reaction_id] / (-solution.fluxes[substrate_reaction_id]))
+print(solution.fluxes[product_reaction_id] /
+      (-solution.fluxes[substrate_reaction_id]))

autopacmen/ec_model_2019_06_25_modeling_create_gecko_model.py

@@ -19,7 +19,7 @@
 method was followed as described in Sánchez et al., 2017.
 """
 
-from submodules.create_gecko_model_reaction_wise import create_gecko_model_reaction_wise_with_sbml
+from .submodules.create_gecko_model_reaction_wise import create_gecko_model_reaction_wise_with_sbml
 
 INPUT_SBML: str = "./ec_model_2019_06_25_input/iJO1366.xml"
 OUTPUT_SBML: str = "iJO1366_2019_06_25_GECKO.xml"

autopacmen/ec_model_2019_06_25_optimization_apply_fmincon_optimized_kcats.py

@@ -1,7 +1,7 @@
-import ec_model_2019_06_25_data_set_up_model
+from .ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
 import cobra
 
-model = ec_model_2019_06_25_data_set_up_model.set_up_ec_model_with_sbml("ec_model_2019_06_25_output_optimization/iJO1366_sMOMENT_2019_06_25_STANDARD_EXCHANGE_SCENARIO_MANUAL_CHANGES.xml", .095)
+model = set_up_ec_model_with_sbml("ec_model_2019_06_25_output_optimization/iJO1366_sMOMENT_2019_06_25_STANDARD_EXCHANGE_SCENARIO_MANUAL_CHANGES.xml", .095)
 
 reactions_to_change = [
         # Acetate

autopacmen/ec_model_2019_06_25_optimization_apply_manual_changes.py

@@ -16,7 +16,7 @@
 """ec_model_2019_06_25_optimization_apply_manual_changes.py"""
 
 import cobra
-from submodules.apply_manual_changes import apply_manual_changes
+from .submodules.apply_manual_changes import apply_manual_changes
 
 
 KCAT_CHANGE_FACTORS = {

autopacmen/ec_model_2019_06_25_original_generate_comparable_model.py

@@ -16,11 +16,11 @@
 """ec_model_original_generate_comparable_model.py"""
 
 import cobra
-from ec_model_data_set_up_model import set_up_ec_model_with_sbml
-from submodules.helper_create_model import get_irreversible_model
+from .ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
+from .submodules.helper_create_model import get_irreversible_model
 
 model = set_up_ec_model_with_sbml("ec_model_2019_06_25_input/iJO1366.xml", .225)
-model = get_irreversible_model(model)
+model = get_irreversible_model(model, "_TG_")
 cobra.io.write_sbml_model(model, "ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions.xml")
 model = set_up_ec_model_with_sbml("ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions.xml", .225)
 cobra.io.write_sbml_model(model, "ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions_SHUT_DOWN_SCENARIO.xml")