[Tex/LaTex] Bottom up neural network with TikZ

graphicstikz-pgftikz-shape

I need to create a diagram of a neural network. I found this example online: http://www.texample.net/tikz/examples/neural-network/

However this examples shows how to create a graph from left to right. My goal is to create the graph from bottom up. So I want to show the visible layer on the bottom, then up the hidden layer. How can I achieve that?

Edit:

I'm trying to replicate this exact figure:

what-I-want

Best Answer

Update: The OP asked a second question. This solution modifies the first solution and removed some redundancy, hoping this time it compiles.

enter image description here

Code

\documentclass{article}

\usepackage{tikz}
\usetikzlibrary{calc}

\begin{document}
\pagestyle{empty}

\def\layersep{2.5cm}

\tikzset{neuron/.style={circle,thick,fill=black!25,minimum size=17pt,inner sep=0pt},
    input neuron/.style={neuron, draw,thick, fill=gray!30},
    hidden neuron/.style={neuron,fill=white,draw},
    hoz/.style={rotate=-90}}   %<--- for labels

\begin{tikzpicture}[-,draw=black, node distance=\layersep,transform shape,rotate=90]  %<-- rotate the NN

% Draw the input layer nodes
\foreach \name / \y in {1/1,2/2,3/3,5/m}
\node[input neuron, hoz] (I-\name) at (0,-\name) {\color{red}$b_\y$};

\node[hoz] (I-4) at (0,-4) {$\dots$};

\foreach \name / \y in {1/1,2/2,3/3,5/m}
\path[hoz] (I-\name) node[below=0.5cm](0,-\name) {$v_\y$};

% Draw the hidden layer nodes
\foreach \name / \y in {1/1,2/2,3/3,6/n}
\path[yshift=0.5cm] node [hidden neuron, hoz] (H-\name) at (\layersep,-\name cm) {\color{red}$c_\y$};

\path[yshift=0.5cm]
   node[hoz] () at (\layersep,-4 cm) {$\dots$};
\path[yshift=0.5cm]
   node[hoz] () at (\layersep,-5 cm) {$\dots$};

\foreach \name / \y in {1/1,2/2,3/3,6/n}
\path[hoz] (H-\name) node[above=0.5cm]  {$h_\y$};  

\path node[hoz,right] at ($(I-5)!0.5!(H-6)$) {\color{red}$w_{nm}$};       

% Connect every node in the input layer with every node in the  hidden layer.
    \foreach \source in {1,2,3,5}
        \foreach \dest in {1,2,3,6}
            \path (I-\source.north) edge (H-\dest.south);
\end{tikzpicture}
% End of code
\end{document}

-------------------------- first edition

This is one possibility, draw as usual, then rotate the tikzpicture with tansform shape option and label respectively after completed, as shown below,

enter image description here

Code

\documentclass{article}

\usepackage{tikz}
\begin{document}
\pagestyle{empty}

\def\layersep{2.5cm}

\begin{tikzpicture}[shorten >=1pt,->,draw=black!50, node distance=\layersep,transform shape,rotate=90]  %<-- rotate the NN
    \tikzstyle{every pin edge}=[<-,shorten <=1pt]
    \tikzstyle{neuron}=[circle,fill=black!25,minimum size=17pt,inner sep=0pt]
    \tikzstyle{input neuron}=[neuron, fill=green!50];
    \tikzstyle{output neuron}=[neuron, fill=red!50];
    \tikzstyle{hidden neuron}=[neuron, fill=blue!50];
    \tikzstyle{annot} = [text width=4em, text centered]
    \tikzset{hoz/.style={rotate=-90}}   %<--- for labels
    % Draw the input layer nodes
    \foreach \name / \y in {1,...,4}
    % This is the same as writing \foreach \name / \y in {1/1,2/2,3/3,4/4}
        \node[input neuron, pin=left:\rotatebox{-90}{\parbox[t][][r]{8mm}{\centering Input \\\#\y}}] (I-\name) at (0,-\y) {};

    % Draw the hidden layer nodes
    \foreach \name / \y in {1,...,5}
        \path[yshift=0.5cm]
            node[hidden neuron] (H-\name) at (\layersep,-\y cm) {};

    % Draw the output layer node
    \node[output neuron,pin={[pin edge={->}]right:\rotatebox{-90}{Output}}, right of=H-3] (O) {};

    % Connect every node in the input layer with every node in the
    % hidden layer.
    \foreach \source in {1,...,4}
        \foreach \dest in {1,...,5}
            \path (I-\source) edge (H-\dest);

    % Connect every node in the hidden layer with the output layer
    \foreach \source in {1,...,5}
        \path (H-\source) edge (O);

    % Annotate the layers
    \node[annot,above of=H-1, node distance=1cm,hoz] (hl) {Hidden layer};
    \node[annot,left of=hl,hoz] {Input layer};
    \node[annot,right of=hl,hoz] {Output layer};
\end{tikzpicture}
% End of code
\end{document}

Related Solutions

[Tex/LaTex] Drawing neural network with tikz

Here, we a have a festival of \foreach:

\documentclass[border=0.125cm]{standalone}
\usepackage{tikz}
\usetikzlibrary{positioning}
\begin{document}

\tikzset{%
  every neuron/.style={
    circle,
    draw,
    minimum size=1cm
  },
  neuron missing/.style={
    draw=none, 
    scale=4,
    text height=0.333cm,
    execute at begin node=\color{black}$\vdots$
  },
}

\begin{tikzpicture}[x=1.5cm, y=1.5cm, >=stealth]

\foreach \m/\l [count=\y] in {1,2,3,missing,4}
  \node [every neuron/.try, neuron \m/.try] (input-\m) at (0,2.5-\y) {};

\foreach \m [count=\y] in {1,missing,2}
  \node [every neuron/.try, neuron \m/.try ] (hidden-\m) at (2,2-\y*1.25) {};

\foreach \m [count=\y] in {1,missing,2}
  \node [every neuron/.try, neuron \m/.try ] (output-\m) at (4,1.5-\y) {};

\foreach \l [count=\i] in {1,2,3,n}
  \draw [<-] (input-\i) -- ++(-1,0)
    node [above, midway] {$I_\l$};

\foreach \l [count=\i] in {1,n}
  \node [above] at (hidden-\i.north) {$H_\l$};

\foreach \l [count=\i] in {1,n}
  \draw [->] (output-\i) -- ++(1,0)
    node [above, midway] {$O_\l$};

\foreach \i in {1,...,4}
  \foreach \j in {1,...,2}
    \draw [->] (input-\i) -- (hidden-\j);

\foreach \i in {1,...,2}
  \foreach \j in {1,...,2}
    \draw [->] (hidden-\i) -- (output-\j);

\foreach \l [count=\x from 0] in {Input, Hidden, Ouput}
  \node [align=center, above] at (\x*2,2) {\l \\ layer};

\end{tikzpicture}

\end{document}

Although it seems unwise to have n denote the number of nodes in each layer when they could be different and the arrangement of the diagram suggests they are not.

enter image description here

[Tex/LaTex] Multiple hidden layers in neural network diagram

Here is a modification of that code where you set the number of hidden layers in a macro, and the rest is done automatically.

\documentclass{article}

\usepackage{tikz}
\begin{document}
\pagestyle{empty}

\def\layersep{1.5cm}

\begin{tikzpicture}[
   shorten >=1pt,->,
   draw=black!50,
    node distance=\layersep,
    every pin edge/.style={<-,shorten <=1pt},
    neuron/.style={circle,fill=black!25,minimum size=17pt,inner sep=0pt},
    input neuron/.style={neuron, fill=green!50},
    output neuron/.style={neuron, fill=red!50},
    hidden neuron/.style={neuron, fill=blue!50},
    annot/.style={text width=4em, text centered}
]

    % Draw the input layer nodes
    \foreach \name / \y in {1,...,4}
    % This is the same as writing \foreach \name / \y in {1/1,2/2,3/3,4/4}
        \node[input neuron, pin=left:Input \#\y] (I-\name) at (0,-\y) {};

    % set number of hidden layers
    \newcommand\Nhidden{3}

    % Draw the hidden layer nodes
    \foreach \N in {1,...,\Nhidden} {
       \foreach \y in {1,...,5} {
          \path[yshift=0.5cm]
              node[hidden neuron] (H\N-\y) at (\N*\layersep,-\y cm) {};
           }
    \node[annot,above of=H\N-1, node distance=1cm] (hl\N) {Hidden layer \N};
    }

    % Draw the output layer node
    \node[output neuron,pin={[pin edge={->}]right:Output}, right of=H\Nhidden-3] (O) {};

    % Connect every node in the input layer with every node in the
    % hidden layer.
    \foreach \source in {1,...,4}
        \foreach \dest in {1,...,5}
            \path (I-\source) edge (H1-\dest);

    % connect all hidden stuff
    \foreach [remember=\N as \lastN (initially 1)] \N in {2,...,\Nhidden}
       \foreach \source in {1,...,5}
           \foreach \dest in {1,...,5}
               \path (H\lastN-\source) edge (H\N-\dest);

    % Connect every node in the hidden layer with the output layer
    \foreach \source in {1,...,5}
        \path (H\Nhidden-\source) edge (O);

    % Annotate the layers

    \node[annot,left of=hl1] {Input layer};
    \node[annot,right of=hl\Nhidden] {Output layer};
\end{tikzpicture}
% End of code
\end{document}

With \newcommand\Nhidden{3}:

With \newcommand\Nhidden{6}:

Best Answer

Related Solutions

[Tex/LaTex] Drawing neural network with tikz

[Tex/LaTex] Multiple hidden layers in neural network diagram

Related Question