Merge pull request #7 from pcarruscag/develop

update master

Author: pcarruscag

.github/workflows/codeql.yml

@@ -13,10 +13,10 @@ name: "CodeQL"
 
 on:
   push:
-    branches: [ "master" ]
+    branches: [ "master", "develop" ]
   pull_request:
     # The branches below must be a subset of the branches above
-    branches: [ "master" ]
+    branches: [ "master", "develop" ]
   schedule:
     - cron: '41 14 * * 5'
 
@@ -52,7 +52,7 @@ jobs:
         # Prefix the list here with "+" to use these queries and those in the config file.
 
         # Details on CodeQL's query packs refer to : https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
-        # queries: security-extended,security-and-quality
+        queries: security-and-quality
 
 
     # Autobuild attempts to build any compiled languages  (C/C++, C#, Go, or Java).

README.md

@@ -1,8 +1,6 @@
 # FADO
 Framework for Aerostructural Design Optimization
 
-[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/pcarruscag/FADO.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/pcarruscag/FADO/context:python)
-
 ## Motivation
 Q: "What is my purpose?"
 

__init__.py

@@ -12,6 +12,7 @@
 from tools import GradientScale
 from drivers import ExteriorPenaltyDriver
 from drivers import ScipyDriver
+# Import IpOpt driver if possible.
 try: from drivers import IpoptDriver
 except: pass
 from optimizers import goldenSection

documentation.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #

drivers/__init__.py

@@ -1,4 +1,5 @@
 from drivers.exterior_penalty import *
 from drivers.scipy_driver import *
+# Import IpOpt driver if possible.
 try: from drivers.ipopt_driver import *
 except: pass

drivers/base_driver.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #
@@ -46,6 +46,11 @@ def __init__(self,function,scale,bound=-1E20):
             self.function = function
     #end
 
+    class _Monitor:
+        def __init__(self,function):
+            self.function = function
+    #end
+
     def __init__(self):
         self._variables = []
         self._varScales = None
@@ -61,11 +66,13 @@ def __init__(self):
         self._objectives = []
         self._constraintsEQ = []
         self._constraintsGT = []
+        self._monitors = []
 
         # function values
         self._ofval = None
         self._eqval = None
         self._gtval = None
+        self._monval = None
 
         # map the start index of each variable in the design vector
         self._variableStartMask = None
@@ -123,6 +130,10 @@ def addUpLowBound(self,function,lower=-1.0,upper=1.0):
         self._constraintsGT.append(self._Constraint(function,scale,lower))
         self._constraintsGT.append(self._Constraint(function,-1*scale,upper))
 
+    def addMonitor(self,function):
+        """Add a function to monitor its value, does not participate in the optimization."""
+        self._monitors.append(self._Monitor(function))
+
     def setWorkingDirectory(self,dir):
         """Set the name of the working directory where each iteration runs, it should not exist."""
         self._workDir = dir
@@ -201,6 +212,7 @@ def _preprocessVariables(self):
         self._getVarsAndParsFromFun(self._objectives)
         self._getVarsAndParsFromFun(self._constraintsEQ)
         self._getVarsAndParsFromFun(self._constraintsGT)
+        self._getVarsAndParsFromFun(self._monitors)
 
         # map the start index of each variable in the design vector
         idx = [0]
@@ -262,6 +274,8 @@ def _resetAllValueEvaluations(self):
             obj.function.resetValueEvalChain()
         for obj in self._constraintsGT:
             obj.function.resetValueEvalChain()
+        for obj in self._monitors:
+            obj.function.resetValueEvalChain()
     #end
 
     def _resetAllGradientEvaluations(self):
@@ -271,6 +285,8 @@ def _resetAllGradientEvaluations(self):
             obj.function.resetGradientEvalChain()
         for obj in self._constraintsGT:
             obj.function.resetGradientEvalChain()
+        for obj in self._monitors:
+            obj.function.resetGradientEvalChain()
     #end
 
     # Writes a line to the history file.
@@ -283,6 +299,8 @@ def _writeHisLine(self):
             hisLine += str(val)+self._hisDelim
         for val in self._gtval:
             hisLine += str(val)+self._hisDelim
+        for val in self._monval:
+            hisLine += str(val)+self._hisDelim
         hisLine = hisLine.strip(self._hisDelim)+"\n"
         self._hisObj.write(hisLine)
     #end

drivers/constrained_optim_driver.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #
@@ -73,6 +73,7 @@ def preprocess(self):
         self._ofval = np.zeros((len(self._objectives),))
         self._eqval = np.zeros((len(self._constraintsEQ),))
         self._gtval = np.zeros((len(self._constraintsGT),))
+        self._monval = np.zeros((len(self._monitors),))
 
         # write the header for the history file
         if self._hisObj is not None:
@@ -83,6 +84,8 @@ def preprocess(self):
                 header += obj.function.getName()+self._hisDelim
             for obj in self._constraintsGT:
                 header += obj.function.getName()+self._hisDelim
+            for obj in self._monitors:
+                header += obj.function.getName()+self._hisDelim
             header = header.strip(self._hisDelim)+"\n"
             self._hisObj.write(header)
         #end

drivers/exterior_penalty.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #
@@ -39,7 +39,7 @@ class ExteriorPenaltyDriver(ParallelEvalDriver):
     """
     def __init__(self, tol, freq=40, rini=8, rmax=1024, factorUp=4, factorDown=0.5):
         ParallelEvalDriver.__init__(self, True)
-        
+
         # parameters of the method
         self._tol = tol
         self._freq = freq
@@ -57,8 +57,6 @@ def __init__(self, tol, freq=40, rini=8, rmax=1024, factorUp=4, factorDown=0.5):
         self._old_grad = None
 
         # timers, counters, flags
-        self._funEval = 0
-        self._jacEval = 0
         self._isInit = False
         self._isFeasible = False
         self._logRowFormat = ""
@@ -79,6 +77,7 @@ def _initialize(self):
         self._ofval = np.zeros((len(self._objectives),))
         self._eqval = np.zeros((len(self._constraintsEQ),))
         self._gtval = np.zeros((len(self._constraintsGT),))
+        self._monval = np.zeros((len(self._monitors),))
 
         self._eqpen = np.ones((len(self._constraintsEQ),))*self._rini
         self._gtpen = np.ones((len(self._constraintsGT),))*self._rini
@@ -102,6 +101,9 @@ def _initialize(self):
                 headerData.append(obj.function.getName(w-1))
                 headerData.append("PEN COEFF")
                 self._logRowFormat += "{:>W.Pg}"*2
+            for obj in self._monitors:
+                headerData.append(obj.function.getName(w-1))
+                self._logRowFormat += "{:>W.Pg}"
             # right-align, set width in format and a precision that fits it
             self._logRowFormat = self._logRowFormat.replace("W",str(w))+"\n"
             self._logRowFormat = self._logRowFormat.replace("P",str(min(8,w-7)))
@@ -120,6 +122,8 @@ def _initialize(self):
                 header += obj.function.getName()+self._hisDelim
             for obj in self._constraintsGT:
                 header += obj.function.getName()+self._hisDelim
+            for obj in self._monitors:
+                header += obj.function.getName()+self._hisDelim
             header = header.strip(self._hisDelim)+"\n"
             self._hisObj.write(header)
         #end
@@ -139,8 +143,10 @@ def _writeLogLine(self):
         for (g,r) in zip(self._gtval,self._gtpen):
             data.append(g)
             data.append(r)
+        for f in self._monval:
+            data.append(f)
         self._logObj.write(self._logRowFormat.format(*data))
-    #end        
+    #end
 
     def fun(self,x):
         """Evaluate the penalized function at "x"."""
@@ -199,7 +205,7 @@ def _evaluateGradients(self,x):
 
         # update penalties and params (evaluating the gradient concludes an outer iteration)
         if self._freq > 0:
-            if self._jacEval % self._freq is 0: self.update()
+            if self._jacEval % self._freq == 0: self.update()
 
         # make copy to use as fallback
         self._old_grad[()] = self._grad

drivers/ipopt_driver.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #

drivers/parallel_eval_driver.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #
@@ -72,6 +72,7 @@ def _addEvals(flist,vlist,jlist):
         _addEvals(self._objectives   ,valEvals,jacEvals)
         _addEvals(self._constraintsEQ,valEvals,jacEvals)
         _addEvals(self._constraintsGT,valEvals,jacEvals)
+        _addEvals(self._monitors     ,valEvals,jacEvals)
 
         # for each unique evaluation list its direct dependencies
         self._funEvalGraph = dict(zip(valEvals,[set() for i in range(len(valEvals))]))
@@ -91,6 +92,7 @@ def _addDependencies(flist,funGraph,jacGraph):
         _addDependencies(self._objectives   ,self._funEvalGraph,self._jacEvalGraph)
         _addDependencies(self._constraintsEQ,self._funEvalGraph,self._jacEvalGraph)
         _addDependencies(self._constraintsGT,self._funEvalGraph,self._jacEvalGraph)
+        _addDependencies(self._monitors     ,self._funEvalGraph,self._jacEvalGraph)
     #end
 
     # run the active evaluations of a dependency graph
@@ -171,6 +173,8 @@ def _evalJacInParallel(self):
                 for evl in obj.function.getGradientEvalChain():
                     active[evl] = True
 
+        # gradients are not needed for monitor functions
+
         self._evalInParallel(self._jacEvalGraph, active)
 
         self._jacTime += time.time()
@@ -225,6 +229,7 @@ def fetchValues(dst, src):
         fetchValues(self._ofval, self._objectives)
         fetchValues(self._eqval, self._constraintsEQ)
         fetchValues(self._gtval, self._constraintsGT)
+        fetchValues(self._monval, self._monitors)
 
         self._funTime += time.time()
 
@@ -253,7 +258,7 @@ def fetchValues(dst, src):
     # when the results are read in "function.getGradient".
     def _evaluateGradients(self, x):
         # we assume that evaluating the gradients requires the functions
-        self._evaluateFunctions(x)        
+        self._evaluateFunctions(x)
 
         # lazy evaluation
         if self._jacReady: return False

drivers/scipy_driver.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #
@@ -27,10 +27,6 @@ class ScipyDriver(ConstrainedOptimizationDriver):
     """
     def __init__(self):
         ConstrainedOptimizationDriver.__init__(self)
-
-        # list of constraints and variable bounds
-        self._constraints = []
-        self._bounds = []
     #end
 
     def preprocess(self):
@@ -86,7 +82,7 @@ def fun(self, x):
     def grad(self, x):
         """Method passed to SciPy to get the objective function gradient."""
         # Evaluates gradients and functions if necessary, otherwise it
-        # simply combines and scales the results.    
+        # simply combines and scales the results.
         self._jacTime -= time.time()
         try:
             self._evaluateGradients(x)

evaluation.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #

function.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #
@@ -187,6 +187,7 @@ def getGradient(self,mask=None):
         for var,file,parser in zip(self._variables,self._gradFiles,self._gradParse):
             grad = parser.read(file)
             if var.getSize() == 1:
+                # Convert the value to a scalar if it is not yet.
                 try: grad = sum(grad)
                 except: pass
             #end
@@ -200,7 +201,7 @@ def getGradient(self,mask=None):
                 idx += 1
             #end
         #end
-        
+
         return gradient
     #end
 
@@ -211,7 +212,7 @@ def _sequentialEval(self,evals):
         #end
     #end
 
-    def resetValueEvalChain(self): 
+    def resetValueEvalChain(self):
         self._resetEvals(self._funEval)
 
     def resetGradientEvalChain(self):

optimizers/fletcher_reeves.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #

optimizers/line_searches.py

@@ -1,4 +1,4 @@
-#  Copyright 2019-2020, FADO Contributors (cf. AUTHORS.md)
+#  Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
 #
 #  This file is part of FADO.
 #
@@ -43,7 +43,7 @@ def goldenSection(fun,maxiter,f0=None,lbd0=1,tol=1e-3):
     x = [0.0, L2, x[2]-L2, x[2]]
     y = [fun(x[1]), fun(x[2])]
     feval += 2
-    
+
     # iterate
     while feval < maxiter:
         if y[0] < y[1]: # keep left interval
@@ -120,7 +120,7 @@ def quadraticInterp(fun,maxiter,f0=None,lbd0=1,tol=1e-3):
 
     # iterate
     y_ref = max(max(y),-min(y),tol)
-    
+
     while True:
         # compute x_opt'
         det = (x[0]-x[1])*(x[1]-x[2])*(x[2]-x[0])