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gap-packages / Thelma

GAP Package on threshold logic.
https://gap-packages.github.io/Thelma
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Report on variables defined by Thelma #5

Closed olexandr-konovalov closed 5 years ago

olexandr-konovalov commented 5 years ago

This output may be useful for package evaluation. I am pasting it as an issue for info - unless further testing will report any problems, it will likely be closed very soon.

===========================================
### Checking variables in "thelma", ver. 1.00
#E  component `ArchiveURL' must be bound to a string started with http://, htt\
ps:// or ftp://
#E  component `ArchiveURLSubset' must be bound to a list of strings denoting r\
elative paths to readable files or directories
#E Validation of package thelma from /circa/scratch/gap-jenkins/workspace/GAP-\
pkg-update-stable-quicktest-drop-in/GAPCOPTS/64build/GAPGMP/gmp/GAPTARGET/pack\
agesvars/label/kovacs/GAP-pkg-update-stable-snapshot/pkg/Thelma failed

new global functions:
  IsNeuralNetwork( A )
  IsThresholdElement( A )
  NeuralNetwork( InnerLayer, OuterLayer )
  OutputOfNeuralNetwork( NN )
  OutputOfThresholdElement( TE )
  RandomThresholdElement( N, lo, hi )
  ReducedKernelOfBooleanFunction( k )
  StructureOfThresholdElement( TE )
  ThresholdElement( Weights, Threshold )

new global variables:
  THELMA_INTERNAL_ActionOnVector( a, x )*
  THELMA_INTERNAL_BooleanFunctionByNeuralNetworkDASG( f )*
  THELMA_INTERNAL_BuildFMatU( j0, s0, wght, u )*
  THELMA_INTERNAL_BuildH( c )*
  THELMA_INTERNAL_BuildInverseToleranceMatrix( n )*
  THELMA_INTERNAL_BuildToleranceMatrix( n )*
  THELMA_INTERNAL_BuildUSet( j )*
  THELMA_INTERNAL_CharVectSet*
  THELMA_INTERNAL_CheckZeroMat( mat )*
  THELMA_INTERNAL_Conjunction( a, b )*
  THELMA_INTERNAL_ConvertDecToBin( dec, n )*
  THELMA_INTERNAL_Disjunction( a, b )*
  THELMA_INTERNAL_FindFunctionFromKernel( ker, onezero )*
  THELMA_INTERNAL_FindMaxSet( ker )*
  THELMA_INTERNAL_FindMaxSet2( ker, n )*
  THELMA_INTERNAL_FindPrecedingVectors( a )*
  THELMA_INTERNAL_FormNList( ker, rker )*
  THELMA_INTERNAL_FormNList2( ker, rker, onezero )*
  THELMA_INTERNAL_GetBMultBase( f )*
  THELMA_INTERNAL_InfluenceOfVariable( f, v )*
  THELMA_INTERNAL_IsLinIndependent( m )*
  THELMA_INTERNAL_IsRlzbl( f )*
  THELMA_INTERNAL_IsUnateAndInfluenceInVar( f, v )*
  THELMA_INTERNAL_IsUnateBFunc( f )*
  THELMA_INTERNAL_IsUnateInVar( f, v )*
  THELMA_INTERNAL_PIndex( mat )*
  THELMA_INTERNAL_PolToGF2( p, n )*
  THELMA_INTERNAL_PolToOneZero( p, n )*
  THELMA_INTERNAL_STESynthesis( g )*
  THELMA_INTERNAL_SelfDualExtensionOfBooleanFunction( f )*
  THELMA_INTERNAL_SignR( x )*
  THELMA_INTERNAL_SimplifyVector( l )*
  THELMA_INTERNAL_SolveZW( z1, z2, w )*
  THELMA_INTERNAL_SortCols( mat )*
  THELMA_INTERNAL_SortRows( mat )*
  THELMA_INTERNAL_SplitBooleanFunction( f, v, b )*
  THELMA_INTERNAL_ThrBatchTr( l, T, step, f, n )*
  THELMA_INTERNAL_ThrTr( l, T, step, f, n )*
  THELMA_INTERNAL_ThresholdOperator2( ker, rker, onezero, nlist )*
  THELMA_INTERNAL_ThresholdOperator3G( ker, rker, onezero, nlist )*
  THELMA_INTERNAL_ThresholdOperator4( ker, rker, onezero, nlist )*
  THELMA_INTERNAL_ThresholdOperator41( ker, rker, onezero, nlist )*
  THELMA_INTERNAL_VectorToFormula( f )*
  THELMA_INTERNAL_Winnow( f, step, niter )*
  THELMA_INTERNAL_Winnow2( f, step, niter )*

new operations:
  BooleanFunctionByNeuralNetwork( arg )
  BooleanFunctionByNeuralNetworkDASG( arg )
  BooleanFunctionBySTE( arg )
  CharacteristicVectorOfFunction( arg )
  InfluenceOfVariable( arg )
  IsCharacteristicVectorOfSTE( arg )
  IsInverseInKernel( arg )
  IsKernelContainingPrecedingVectors( arg )
  IsRKernelBiggerOfCombSum( arg )
  IsUnateBooleanFunction( arg )
  IsUnateInVariable( arg )
  KernelOfBooleanFunction( arg )
  PDBooleanFunctionBySTE( arg )
  STESynthesis( arg )
  SelfDualExtensionOfBooleanFunction( arg )
  SplitBooleanFunction( arg )
  ThresholdElementBatchTraining( arg )
  ThresholdElementTraining( arg )
  Winnow2Algorithm( arg )
  WinnowAlgorithm( arg )

new categories:
  IsNeuralNetworkObj( ... )*
  IsThresholdElementObj( ... )*

new representations:
  IsNeuralNetworkRep( ... )*
  IsThresholdElementRep( ... )*

new methods:
  <( x, y )*
    for two neural networks
  <( x, y )*
    for two threshold elements
  =( x, y )*
    for two neural networks
  =( x, y )*
    for two threshold elements
  BooleanFunctionByNeuralNetwork( f )
    f
  BooleanFunctionByNeuralNetworkDASG( f )
    function
  BooleanFunctionBySTE( f )
    f
  CharacteristicVectorOfFunction( f )
    f
  Display( A )
    displays a neural network
  Display( A )
    displays a threshold element
  InfluenceOfVariable( f, v )
    function, var
  IsCharacteristicVectorOfSTE( v )
    check if function is realizable for n<=6
  IsInverseInKernel( f )
    f
  IsKernelContainingPrecedingVectors( f )
    f
  IsRKernelBiggerOfCombSum( f )
    f
  IsUnateBooleanFunction( f )
    function
  IsUnateInVariable( f, v )
    function, integer
  KernelOfBooleanFunction( f )
    f
  PDBooleanFunctionBySTE( f )
    f
  PrintObj( A )
    displays a neural network
  PrintObj( A )
    displays a threshold element
  STESynthesis( f )
    function
  SelfDualExtensionOfBooleanFunction( f )
    function
  SplitBooleanFunction( f, v, b )
    function, var, bool
  ThresholdElementBatchTraining( te, step, f, maxit )
    threshold element, step, function, max_iter
  ThresholdElementTraining( te, step, f, maxit )
    threshold element, step, function, max_iter
  ViewObj( A )
    displays a neural network
  ViewObj( A )
    displays a threshold element
  Winnow2Algorithm( f, step, maxit )
    function, step, maxiter
  WinnowAlgorithm( f, step, maxit )
    function, step, maxiter

new other methods:
  BooleanFunctionByNeuralNetwork( f )
    f
  BooleanFunctionByNeuralNetwork( f )
    f
  BooleanFunctionByNeuralNetworkDASG( f )
    function
  BooleanFunctionByNeuralNetworkDASG( f )
    function
  BooleanFunctionBySTE( f )
    f
  BooleanFunctionBySTE( f )
    f
  BooleanFunctionBySTE( k, onezero )
    k, onezero
  CharacteristicVectorOfFunction( f )
    f
  CharacteristicVectorOfFunction( f )
    f
  InfluenceOfVariable( f, v )
    function, var
  InfluenceOfVariable( f, v )
    function, var
  IsInverseInKernel( f )
    f
  IsInverseInKernel( f )
    f
  IsInverseInKernel( ker )
    kernel
  IsKernelContainingPrecedingVectors( f )
    f
  IsKernelContainingPrecedingVectors( f )
    f
  IsKernelContainingPrecedingVectors( ker )
    ker
  IsRKernelBiggerOfCombSum( f )
    f
  IsRKernelBiggerOfCombSum( f )
    f
  IsRKernelBiggerOfCombSum( rker )
    reduced kernel
  IsUnateBooleanFunction( f )
    function
  IsUnateBooleanFunction( f )
    function
  IsUnateInVariable( f, v )
    function
  IsUnateInVariable( f, v )
    function
  KernelOfBooleanFunction( f )
    f
  KernelOfBooleanFunction( f )
    f
  PDBooleanFunctionBySTE( ker1, ker0 )
    ker1, ker0
  STESynthesis( f )
    function
  STESynthesis( f )
    function
  SelfDualExtensionOfBooleanFunction( f )
    function
  SelfDualExtensionOfBooleanFunction( f )
    function
  SplitBooleanFunction( f, v, b )
    function, var, bool
  SplitBooleanFunction( f, v, b )
    function, var, bool
  ThresholdElementBatchTraining( te, step, f1, maxit )
    threshold element, step, function, max_iter
  ThresholdElementBatchTraining( te, step, f1, maxit )
    threshold element, step, function, max_iter
  ThresholdElementTraining( te, step, f1, maxit )
    threshold element, step, function, max_iter
  ThresholdElementTraining( te, step, f1, maxit )
    threshold element, step, function, max_iter
  Winnow2Algorithm( f, step, maxit )
    function, step, max_iter
  Winnow2Algorithm( f, step, maxit )
    function, step, maxiter
  WinnowAlgorithm( f, step, maxit )
    function, step, maxiter
  WinnowAlgorithm( f, step, maxit )
    function, step, maxiter

other new globals (write protected):
  IsNeuralNetworkObjCollection( ... )*
  IsThresholdElementObjCollection( ... )*

### Variables checked for "thelma", ver. 1.00
===========================================
olexandr-konovalov commented 5 years ago

I will close this - #4 fixed, and the fix happened to be much simpler than I anticipated :)