A visual representation of a simple neural network expanding on previous work done on https://github.com/samueleishion/neural-network-experiment

make network 

To clean the project:

make clean

Several nodes (neurons) will be displayed. The top ones are sensorial, the middle ones are transmitters, and the bottom ones are terminals. You can click on the sensorials to transmit signals.

On the right side of the graphic window, there is a graph/map-like visualization of the interactions between sensorial and terminal neurons. The sensorial neurons are displayed on the y-axis while the terminal neurons are displayed on the x-axis.

Several features can be changed to change the experiment on the settings.py file. The features include:

WINDOW_X = 1000 

• purpose: establishes width of graphic window
• type: int
• default value: 1000px

WINDOW_Y = 600

• purpose: establishes height of graphic window
• type: int
• default value: 600px

SENSORY_NEURONS = 10 

• purpose: establishes total number of sensorial neurons
• type: int
• default value: 10

TERMINAL_NEURONS = 10 

• purpose: establishes total number of terminal neurons
• type: int
• default value: 10

INTENSITY = 20 

• purpose: equivalent to duration/potence of sensation, this is a fixed number for all sensations in this experiment
• type: int
• default value: 20

AUTOMATIC = False 

• purpose: allows the sensations to be automatically distributed
• type: boolean
• default value: False
• detail: setting this feature to True facilitates the graph visualization and experimentation

GRAPH = True 

• purpose: displays the right panel with the graph/map-like visualization
• type: boolean
• default value: True
• detail: this graph maps the number of reached terminals after trigerring a given sensory neuron.

If the GRAPH feature is set to True, the y-axis represents the sensorial neurons. The x-axis represents the sensorial neurons. If a given sensory neuron (S) has sent a transmission and is received by a given terminal neuron (T), then the graph at coordinates (S,T) will be lit up with a shade of red (given that, for this particular graphics window the y-axis increases downwards).

For example, we have 3 sensory neurons and 4 terminal neurons. This would be a numeric representation of the graph:

After several interactions, say that:

• S1 has successfully transmitted
  • 3 sensations to T1
  • 2 sensations to T2
• S2 has successfully transmitted
  • 1 sensation to T2
  • 3 sensations to T3
  • 2 sensations to T4
• S3 has successfully transmitted
  • 2 sensations to T1
  • 4 sensations to T3
  • 1 sensation to T4

Our graph will now be:

On the actual visualization, these decimals are used to calculate the intensity of the color.