Neural networks numerical labels












4















The code given below generates a MWE.



documentclass{standalone}



usepackage{lmodern}

usepackage{neuralnetwork}



newcommand{linklab}[4]{ifnum0=#2 $w_{0}$ else $w_{{#2}}$ fi}



begin{document}



begin{neuralnetwork} 



inputlayer[count=3, bias=true]

outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]



end{neuralnetwork}

end{document}


enter image description here



TO (generated by inkscape)



enter image description here



I would like to use numerical labels automatically. The code should give (for example) 1.5, 2.3, 1 and 5.1 instead of w_0, w_1, w_2 and w_3 when I write label = {1.5, 2.3, 1, 5.1} (or sth. similar).



I tried to use foreach with ifnum but could not get what I would like.






tikz-pgf foreach fill







share|improve this question

























  • I believe that the success of any approach with your linklab macro requires knowledge, how outputlayer treats the labels= argument.

    – Christian Hupfer
    Jan 5 at 16:02
















4















The code given below generates a MWE.



documentclass{standalone}



usepackage{lmodern}

usepackage{neuralnetwork}



newcommand{linklab}[4]{ifnum0=#2 $w_{0}$ else $w_{{#2}}$ fi}



begin{document}



begin{neuralnetwork} 



inputlayer[count=3, bias=true]

outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]



end{neuralnetwork}

end{document}


enter image description here



TO (generated by inkscape)



enter image description here



I would like to use numerical labels automatically. The code should give (for example) 1.5, 2.3, 1 and 5.1 instead of w_0, w_1, w_2 and w_3 when I write label = {1.5, 2.3, 1, 5.1} (or sth. similar).



I tried to use foreach with ifnum but could not get what I would like.






tikz-pgf foreach fill







share|improve this question

























  • I believe that the success of any approach with your linklab macro requires knowledge, how outputlayer treats the labels= argument.

    – Christian Hupfer
    Jan 5 at 16:02














4












4








4


0






The code given below generates a MWE.



documentclass{standalone}



usepackage{lmodern}

usepackage{neuralnetwork}



newcommand{linklab}[4]{ifnum0=#2 $w_{0}$ else $w_{{#2}}$ fi}



begin{document}



begin{neuralnetwork} 



inputlayer[count=3, bias=true]

outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]



end{neuralnetwork}

end{document}


enter image description here



TO (generated by inkscape)



enter image description here



I would like to use numerical labels automatically. The code should give (for example) 1.5, 2.3, 1 and 5.1 instead of w_0, w_1, w_2 and w_3 when I write label = {1.5, 2.3, 1, 5.1} (or sth. similar).



I tried to use foreach with ifnum but could not get what I would like.






tikz-pgf foreach fill







share|improve this question
















The code given below generates a MWE.



documentclass{standalone}



usepackage{lmodern}

usepackage{neuralnetwork}



newcommand{linklab}[4]{ifnum0=#2 $w_{0}$ else $w_{{#2}}$ fi}



begin{document}



begin{neuralnetwork} 



inputlayer[count=3, bias=true]

outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]



end{neuralnetwork}

end{document}


enter image description here



TO (generated by inkscape)



enter image description here



I would like to use numerical labels automatically. The code should give (for example) 1.5, 2.3, 1 and 5.1 instead of w_0, w_1, w_2 and w_3 when I write label = {1.5, 2.3, 1, 5.1} (or sth. similar).



I tried to use foreach with ifnum but could not get what I would like.






tikz-pgf foreach fill




tikz-pgf foreach fill






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Jan 5 at 16:05







mert

















asked Jan 5 at 15:14









mertmert

7241614




7241614













  • I believe that the success of any approach with your linklab macro requires knowledge, how outputlayer treats the labels= argument.

    – Christian Hupfer
    Jan 5 at 16:02



















  • I believe that the success of any approach with your linklab macro requires knowledge, how outputlayer treats the labels= argument.

    – Christian Hupfer
    Jan 5 at 16:02

















I believe that the success of any approach with your linklab macro requires knowledge, how outputlayer treats the labels= argument.

– Christian Hupfer
Jan 5 at 16:02





I believe that the success of any approach with your linklab macro requires knowledge, how outputlayer treats the labels= argument.

– Christian Hupfer
Jan 5 at 16:02










1 Answer
1






active

oldest

votes


















6














Something like this?



documentclass{standalone}



usepackage{lmodern}

usepackage{neuralnetwork}

newcommand{linklab}[4]{ifcase#2

0

or

1.5

or

2.3

or

1

or

5.1

fi}



begin{document}



begin{neuralnetwork} 



inputlayer[count=3, bias=true]

outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]



end{neuralnetwork}

end{document}


enter image description here






share|improve this answer























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    1 Answer
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    active

    oldest

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    active

    oldest

    votes






    active

    oldest

    votes









    6














    Something like this?



    documentclass{standalone}
    

    
usepackage{lmodern}
    
usepackage{neuralnetwork}
    
newcommand{linklab}[4]{ifcase#2
    
0
    
or
    
1.5
    
or
    
2.3
    
or
    
1
    
or
    
5.1
    
fi}
    

    
begin{document}
    

    
begin{neuralnetwork} 
    

    
inputlayer[count=3, bias=true]
    
outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]
    

    
end{neuralnetwork}
    
end{document}


    enter image description here






    share|improve this answer




























      6














      Something like this?



      documentclass{standalone}
      

      
usepackage{lmodern}
      
usepackage{neuralnetwork}
      
newcommand{linklab}[4]{ifcase#2
      
0
      
or
      
1.5
      
or
      
2.3
      
or
      
1
      
or
      
5.1
      
fi}
      

      
begin{document}
      

      
begin{neuralnetwork} 
      

      
inputlayer[count=3, bias=true]
      
outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]
      

      
end{neuralnetwork}
      
end{document}


      enter image description here






      share|improve this answer


























        6












        6








        6







        Something like this?



        documentclass{standalone}
        

        
usepackage{lmodern}
        
usepackage{neuralnetwork}
        
newcommand{linklab}[4]{ifcase#2
        
0
        
or
        
1.5
        
or
        
2.3
        
or
        
1
        
or
        
5.1
        
fi}
        

        
begin{document}
        

        
begin{neuralnetwork} 
        

        
inputlayer[count=3, bias=true]
        
outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]
        

        
end{neuralnetwork}
        
end{document}


        enter image description here






        share|improve this answer













        Something like this?



        documentclass{standalone}
        

        
usepackage{lmodern}
        
usepackage{neuralnetwork}
        
newcommand{linklab}[4]{ifcase#2
        
0
        
or
        
1.5
        
or
        
2.3
        
or
        
1
        
or
        
5.1
        
fi}
        

        
begin{document}
        

        
begin{neuralnetwork} 
        

        
inputlayer[count=3, bias=true]
        
outputlayer[count=1, bias=false]linklayers[style={above,sloped},labels=linklab]
        

        
end{neuralnetwork}
        
end{document}


        enter image description here







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Jan 5 at 17:19









        marmotmarmot

        93.3k4109204




        93.3k4109204






























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