[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -1,12 +1,12 @@
 repos:
   - repo: https://github.com/pycqa/isort
-    rev: 6.0.1
+    rev: 9.0.0a3
     hooks:
       - id: isort
         additional_dependencies: [toml]
 
-  - repo: https://github.com/psf/black
-    rev: 25.1.0
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 26.5.1
     hooks:
       - id: black
         additional_dependencies: [toml]

biomass/construction/julia_template.py

@@ -7,9 +7,7 @@
 
 from typing import Final
 
-PARAMETERS: Final[
-    str
-] = """\
+PARAMETERS: Final[str] = """\
 module C
 
 const NAMES = []
@@ -24,9 +22,7 @@
 """
 
 
-SPECIES: Final[
-    str
-] = """\
+SPECIES: Final[str] = """\
 module V
 
 const NAMES = []
@@ -41,9 +37,7 @@
 """
 
 
-ODE: Final[
-    str
-] = """\
+ODE: Final[str] = """\
 function diffeq!(du, u, p, t)
     v = Dict{Int64,Float64}()
 
@@ -69,9 +63,7 @@
 """
 
 
-OBSERVABLE: Final[
-    str
-] = """\
+OBSERVABLE: Final[str] = """\
 const observables = []
 
 function observables_index(observable_name::String)::Int
@@ -83,9 +75,7 @@
 """
 
 
-SIMULATION: Final[
-    str
-] = """\
+SIMULATION: Final[str] = """\
 module Sim
 include("./name2idx/parameters.jl")
 include("./name2idx/species.jl")
@@ -187,9 +177,7 @@
 """
 
 
-EXPERIMENTAL_DATA: Final[
-    str
-] = """\
+EXPERIMENTAL_DATA: Final[str] = """\
 module Exp
 include("./observable.jl")
 
@@ -204,9 +192,7 @@
 """
 
 
-SEARCH_PARAM: Final[
-    str
-] = """\
+SEARCH_PARAM: Final[str] = """\
 # Specify model parameters and/or initial values to optimize
 function get_search_index()::Tuple{Array{Int64,1},Array{Int64,1}}
     # parameters
@@ -437,9 +423,7 @@
 end
 """
 
-PROBLEM: Final[
-    str
-] = """\
+PROBLEM: Final[str] = """\
 # Residual Sum of Squares
 function compute_objval_rss(
     sim_data::Vector{Float64},

biomass/construction/template/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized."""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/model_object.py

@@ -109,7 +109,7 @@ def load_param(self, paramset: int) -> OptimizedValues:
             Optimized parameter/initial values.
         """
         best_individual = self.get_individual(paramset)
-        (x, y0) = self.problem.update(best_individual)
+        x, y0 = self.problem.update(best_individual)
         optimized_values = OptimizedValues(x, y0)
         return optimized_values
 

biomass/models/Nakakuki_Cell_2010/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/circadian_clock/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/g1s_transition/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/insulin_signaling/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/jak_stat_pathway/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized."""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/mapk_cascade/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/nfkb_pathway/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/pan_rtk/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/prolif_quies/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")
 

biomass/models/tgfb_smad/problem.py

@@ -44,11 +44,11 @@ def _diff_sim_and_exp(sim_matrix, exp_dict, exp_timepoint, conditions, sim_norm_
     def objective(self, indiv, *args):
         """Define an objective function to be minimized"""
         if len(args) == 0:
-            (x, y0) = self.update(indiv)
+            x, y0 = self.update(indiv)
         elif len(args) == 1:
             raise ValueError("not enough values to unpack (expected 2, got 1)")
         elif len(args) == 2:
-            (x, y0) = args
+            x, y0 = args
         else:
             raise ValueError("too many values to unpack (expected 2)")