Code formatting checks

.github/pull_request_template.md

@@ -14,5 +14,6 @@
 - [ ] I am submitting my contribution to the develop branch.
 - [ ] I have updated the list of python modules in [required_packages.txt](../required_packages.txt) and [environment.yml](../environment.yml), if necessary.
 - [ ] I have properly commented my changes.
+- [ ] I used the pre-commit hook to prevent dirty commits and used `pre-commit run --all` to format old commits.
 - [ ] I have updated the [documentation](../Documentation/), if necessary.
 - [ ] I have added a test case that demonstrates my contribution, if necessary.

.github/workflows/linting.yml

@@ -0,0 +1,28 @@
+name: Linting
+
+on:
+  pull_request:
+    branches:
+      - 'develop'
+
+jobs:
+    Ruff:
+        name: Code linting with Ruff
+        runs-on: ubuntu-latest
+        steps:
+            - name: Checkout code
+              uses: actions/checkout@v4
+            - name: Set up Python
+              uses: actions/setup-python@v5
+              with:
+                python-version: '3.13'
+            - name: Install Ruff
+              run: pip install ruff 
+            - name: Trailing whitespaces
+              run: ruff check --select=W291
+            - name: Unused modules
+              run: ruff check --select=F401
+            - name: Unused variables
+              run: ruff check --select=F841
+            - name: Duplicate class members
+              run: ruff check --select=PIE794

.pre-commit-config.yaml

@@ -0,0 +1,18 @@
+repos:
+- repo: https://github.com/astral-sh/ruff-pre-commit
+  # Ruff version.
+  rev: v0.15.13
+  hooks:
+    # Run the linter.
+    - id: ruff-check
+      name: Trailing whitespaces
+      args: [ --fix, --select=W291]
+    - id: ruff-check
+      name: Unused modules
+      args: [ --fix, --select=F401]
+    - id: ruff-check
+      name: Unused variables
+      args: [--select=F841]
+    - id: ruff-check
+      name: Duplicate class members
+      args: [--select=PIE794]

Common/DataDrivenConfig.py

@@ -190,7 +190,6 @@ def SetFluid(self, fluid_name=DefaultSettings_NICFD.fluid_name):
             #     raise Exception("Only two fluids can be used for mixtures")
 
             self.__fluid_names = []
-            fluid_mixing = []
             for f in fluid_name:
                 if type(f) is not str:
                     raise Exception("Fluid name should be provided in string format.")
@@ -1263,7 +1262,7 @@ def SetNpMix(self, input:int=DefaultSettings_FGM.Np_eq):
         """
         Set number of divisions between lean and rich mixture status for flamelet generation.
 
-        :param input: Number of divisions between leanest and richest pre-mixed solution. 
+        :param input: Number of divisions between leanest and richest pre-mixed solution.
         :type input: int
         :raise: Exception: If the number of divisions is lower than one.
 
@@ -1509,7 +1508,7 @@ def GetProgressVariableWeights(self):
         return self.__pv_weights
 
     def SetDefaultProgressVariable(self):
-        """Set progress variable to be weighted sum of fuel and oxidizer species (minus N2) and major product at stochiometry. 
+        """Set progress variable to be weighted sum of fuel and oxidizer species (minus N2) and major product at stochiometry.
            Weights are set as the inverse of specie molecular weight: negative for reactants, positive for product.
         """
 
@@ -1684,8 +1683,6 @@ def GetSparkSources(self, val_phi:float, val_T:float, iGroup:int=0):
         flame = ct.FreeFlame(self.gas)
         flame.transport_model = self.__transport_model
         flame.solve(auto=True,refine_grid=True,loglevel=0)
-        dx = flame.grid[1:] - flame.grid[:-1]
-        t_res = np.sum(dx / flame.velocity[:-1])
         qdot = flame.heat_release_rate
         ix_max = np.argmax(qdot)
         ydot = flame.net_production_rates

Data_Generation/DataGenerator_Base.py

@@ -119,7 +119,7 @@ def SetTrainFraction(self, input:float=DefaultProperties.train_fraction):
         Define the fraction of fluid data used for training multi-layer perceptrons.
 
         :param input: fluid data train fraction.
-        :type input: float 
+        :type input: float
         :raise: Exception: if provided fraction is equal or higher than one.
         """
         if input >= 1 or input <=0:
@@ -146,7 +146,7 @@ def GetTrainFraction(self):
         Get fluid data fraction used for multi-layer perceptron training.
 
         :return: fluid data train fraction.
-        :rtype: float 
+        :rtype: float
         """
         return self.__train_fraction
 
@@ -155,7 +155,7 @@ def GetTestFraction(self):
         Get fluid data fraction used for determining accuracy after training.
 
         :return: fluid data test fraction.
-        :rtype: float 
+        :rtype: float
         """
         return self.__test_fraction
 

Data_Generation/DataGenerator_FGM.py

@@ -485,7 +485,7 @@ def ComputeBurnerFlames(self, mix_status:float, m_dot:np.ndarray[float], T_burne
                 pass
 
     def ComputeCounterFlowFlames(self, v_fuel:float, v_ox:float, T_ub:float):
-        """Generate counter-flow diffusion flamelet data for a given temperature, and reactant velocities. 
+        """Generate counter-flow diffusion flamelet data for a given temperature, and reactant velocities.
         Strain rate is gradually increased until extinction in order to distribute data over the progress variable spectrum.
 
         :param v_fuel: Fuel reactant velocity in meters per second.

Data_Generation/DataGenerator_NICFD.py

@@ -188,7 +188,7 @@ def UpdateConfig(self):
     def VisualizeDataGrid(self):
         """Visualize query points at which fluid data are evaluated.
         """
-        fig = plt.figure(figsize=[10,10])
+        plt.figure(figsize=[10,10])
         ax = plt.axes()
         ax.plot(self.__X_grid.flatten(), self.__Y_grid.flatten(), 'k.')
         if self. __use_PT:
@@ -830,7 +830,7 @@ def __get_saturated_transport_properties(self, p:float):
                 'k_l': k_l, 'k_g': k_g,
                 'rho_l': rho_l, 'rho_g': rho_g
             }
-        except Exception as ex:
+        except Exception:
             return None
 
     def __compute_void_fraction(self, quality:float, rho_l:float, rho_g:float):
@@ -949,18 +949,10 @@ def DiscretizationError(self, rho, e):
         self.UpdateFluid(rho, e)
         state_vector,_ = self.GetStateVector()
         self.UpdateFluid(rho, e)
-        dPde_rho_ref = self.fluid.first_partial_deriv(CP.iP, CP.iUmass, CP.iDmass)
-        dPdrho_e_ref = self.fluid.first_partial_deriv(CP.iP, CP.iDmass, CP.iUmass)
-        dTde_rho_ref = self.fluid.first_partial_deriv(CP.iT, CP.iUmass, CP.iDmass)
-        dTdrho_e_ref = self.fluid.first_partial_deriv(CP.iT, CP.iDmass, CP.iUmass)
         P_ref = self.fluid.p()
         T_ref = self.fluid.T()
         ref_data = np.array([P_ref, T_ref])
 
-        dPde_rho_test = state_vector[EntropicVars.dpde_rho.value]
-        dPdrho_e_test = state_vector[EntropicVars.dpdrho_e.value]
-        dTde_rho_test = state_vector[EntropicVars.dTde_rho.value]
-        dTdrho_e_test = state_vector[EntropicVars.dTdrho_e.value]
         P_test = state_vector[EntropicVars.p.value]
         T_test = state_vector[EntropicVars.T.value]
         test_data = np.array([P_test, T_test])

Data_Processing/DataPlotters.py

@@ -58,7 +58,7 @@ def __init__(self, Config_in:Config_FGM=None):
     def ManualSelection(self, input:bool=False):
         """Select flamelets to plot manually.
 
-        :param input: select flamelets manually(True) or all flamelets within 
+        :param input: select flamelets manually(True) or all flamelets within
         :type input: bool
         """
         self.__manual_select = input

Data_Processing/OptimizeProgressVariable.py

@@ -32,7 +32,7 @@
 import matplotlib.pyplot as plt
 from scipy.optimize import differential_evolution, Bounds, LinearConstraint, minimize
 from sklearn.decomposition import PCA
-from sklearn.preprocessing import StandardScaler, RobustScaler, MinMaxScaler
+from sklearn.preprocessing import MinMaxScaler
 
 from Common.Properties import FGMVars, DefaultSettings_FGM
 from Common.DataDrivenConfig import Config_FGM
@@ -290,7 +290,7 @@ def PlotConvergence(self):
 
 
     def penalty_function(self, x:np.array):
-        """Optimization penalty function computing the derivative of the 
+        """Optimization penalty function computing the derivative of the
         progress vector w.r.t. that of the progress variable increment.
 
         :param x: progress variable weights vector.
@@ -397,10 +397,10 @@ def SetCurveStepThreshold(self, val_tol:float=1e-4):
         self.__CurveStepTolerance = val_tol
 
     def SetSpeciesRangeTolerance(self, val_tol:float=1e-5):
-        """Specify the minimum change in species mass fraction for species to be 
+        """Specify the minimum change in species mass fraction for species to be
         considered in progress variable optimization.
 
-        :param val_tol: species mass fraction range threshold. 
+        :param val_tol: species mass fraction range threshold.
         :type val_tol: float
         :raises Exception: if threshold value is negative.
         """
@@ -897,7 +897,6 @@ def RunOptimizer(self):
         else:
             update_strategy = "immediate"
 
-        A_constr = np.hstack((-self._progress_vector, self._delta_Y_flamelets))
         #self._monotonicity_full = LinearConstraint(A_constr, lb=-1e-4,keep_feasible=True)
         # Initiate evolutionary algorithm.
         print("Generation,Penalty," + ",".join(s for s in self._pv_definition_optim))

Data_Processing/collectFlameletData.py

@@ -1058,7 +1058,7 @@ def __ComputeNumberofEvaluations(self, group_variables:list[list[str]]):
         return n_networks_eval
 
     def PostProcessGroups(self):
-        """Extract the combinations of variables with the highest affinity and fewest number of network evaluations. 
+        """Extract the combinations of variables with the highest affinity and fewest number of network evaluations.
         Groups with most potential are visualized in a figure.
         """
         min_group = min(self.__n_groups)

Documentation/source/Development.rst

@@ -27,6 +27,17 @@ Publish branch, push changes
 
 Open a pull request on the GitHub page, review PR checklist 
 
+Formatting
+----------
+
+Before commiting changes, run the command 
+
+.. code-block::
+
+    >>> pre-commit run --all
+
+in order to check the code for unused variables and modules and for trailing whitespaces.
+
 
 Regression Tests 
 ----------------

GUI/pipeline.py

@@ -377,7 +377,7 @@ def get_descendants(self, _id, descendants_list=[]):
             if self._nodes[k]['parent']==_id:
               #child_name = self._nodes[k]['name']
               descendants_list.append(k)
-              child = self.get_descendants(k,descendants_list)
+              self.get_descendants(k,descendants_list)
 
         #print("descendants=",descendants_list)
         #return descendants_list

GUI/trame_test.py

@@ -1,28 +1,22 @@
 from trame.app import get_server
-from trame.widgets import vuetify, paraview
+from trame.widgets import vuetify
 from trame.ui.vuetify import SinglePageLayout
 from trame.widgets import vuetify, vtk as vtk_widgets
 import vtk
 from vtkmodules.vtkCommonDataModel import vtkDataObject
 from vtkmodules.vtkCommonColor import vtkNamedColors
 from vtkmodules.vtkRenderingCore import (
-    vtkActor,
-    vtkDataSetMapper,
     vtkRenderer,
     vtkRenderWindow,
     vtkRenderWindowInteractor,
-    vtkColorTransferFunction,
 )
-from vtkmodules.vtkRenderingAnnotation import vtkCubeAxesActor, vtkScalarBarActor
-from vtkmodules.vtkInteractionWidgets import vtkOrientationMarkerWidget, vtkScalarBarWidget
+from vtkmodules.vtkRenderingAnnotation import vtkScalarBarActor
+from vtkmodules.vtkInteractionWidgets import vtkScalarBarWidget
 from Common.Properties import DefaultSettings_FGM
-from Common.DataDrivenConfig import Config_FGM
 
 #from .pipeline import PipelineManager
-from trame.assets.local import LocalFileManager
 
 import numpy as np
-import time
 
 server = get_server(client_type='vue2')
 renderer = vtkRenderer()
@@ -138,7 +132,6 @@
 
 DEFAULT_Z=0.5
 
-from vtk import vtkPlaneSource
 planeSource = vtk.vtkPlaneSource()
 planeSource.SetCenter(0.5,0.5,0.5)
 planeSource.SetNormal(0,0,1.0)

Manifold_Generation/LUT/FlameletTableGeneration.py

@@ -31,12 +31,10 @@
 from Common.DataDrivenConfig import Config_FGM, Config
 from Common.CommonMethods import GetReferenceData
 from Common.Properties import DefaultSettings_FGM
-import cantera as ct
 import gmsh
 import pickle
 from multiprocessing import Pool
 from Common.Interpolators import Invdisttree
-from random import sample
 
 class SU2TableGenerator_Base:
     _Config = None
@@ -176,7 +174,6 @@ def EvaluateManifoldInterpolator(self, CV_unscaled:np.ndarray):
         return data_interp
 
     def Compute2DTable(self, CV_1:str, CV_2:str):
-        Np_grid = 300
 
         return
 
@@ -460,7 +457,7 @@ def VisualizeTableLevel(self, val_mix_frac:float, var_to_plot:str=None):
 
     def GenerateTableNodes(self):
         """
-        Generate the table nodes and connectivity. 
+        Generate the table nodes and connectivity.
         """
 
         self.__PrepareTableLevels()
@@ -646,7 +643,7 @@ def ComputeTableLevelMesh(self, val_mix_frac:float):
         :type val_mix_frac: float
         :return Connectivity: Delaunay triangulation connectivity
         :rtype Connecivity: NDarray
-        :return MeshNodes: 
+        :return MeshNodes:
         """
         Coord_refinement, Coord_hull, hull_area,z_norm, CV_mesh, table_level_data  = self.__ComputeCurvature(val_mix_frac)
         MeshNodes_Norm, table_level_data = self.__Compute2DMesh(XY_hull=Coord_hull, XY_refinement=Coord_refinement,val_mixfrac_norm=z_norm, level_area=hull_area)
@@ -661,7 +658,7 @@ def __ComputeCurvature(self, val_mix_frac:float):
         Compute the curvature of the reaction rate surface at a constant mixture fraction level. Identify the locations of high curvature where table refinement is required.
 
         :param val_mix_frac: mixture fraction of current table level.
-        :type val_mix_frac: float 
+        :type val_mix_frac: float
         :return XY_refinement: normalized pv and enth coordinates where refinement should be applied.
         :rtype XY_refinement: array
         :return XY_hull: normalized pv and enth coordinates of the convex hull of the current table level.
@@ -820,7 +817,6 @@ def __Compute2DMesh(self, XY_hull:np.ndarray, XY_refinement:np.ndarray, val_mixf
         gmsh.model.mesh.field.setNumbers(7, "FieldsList", [2])
         gmsh.model.mesh.field.setAsBackgroundMesh(7)
 
-        lc = base_cell_size
         def meshSizeCallback(dim,tag,x,y,z,lc):
             return lc
 

Manifold_Generation/LUT/LUTGenerators.py

@@ -32,7 +32,6 @@
 import gmsh
 from concave_hull import concave_hull, concave_hull_indexes
 import meshio
-import matplotlib.pyplot as plt
 
 def shoelace(XY:np.ndarray[float]):
     """Shoelace algorithm for area computations

Manifold_Generation/MLP/Trainer_Base.py

@@ -378,7 +378,7 @@ def SaveWeights(self):
         return
 
     def SetDecaySteps(self):
-        """Set the number of steps in the exponential decay algorithm. The number of steps scale are proportioned based on the number of epochs, 
+        """Set the number of steps in the exponential decay algorithm. The number of steps scale are proportioned based on the number of epochs,
         and training data size and mini batch size.
         """
         self._decay_steps = int(1e-3 * self._n_epochs * self._Np_train / self._Np_batch)
@@ -429,7 +429,7 @@ def GetActivationFunction(self):
         return self._activation_function_name
 
     def PlotR2Data(self):
-        """Plot the MLP prediction in the form of R2-plots w.r.t. the reference data, and along each of the 
+        """Plot the MLP prediction in the form of R2-plots w.r.t. the reference data, and along each of the
         normalized controlling variables.
         """