mimgrating from another repo

lib/ann/examples/xor/test.lua

@@ -0,0 +1,41 @@
+#! /usr/bin/env lua
+
+-- load the library
+require("lfann")
+
+-- load the network from the exported file
+local net = fann.Net.create_from_file("xor.net")
+
+local n_input, n_output = 2, 1
+local input, output = {}
+local write, sf = io.write, string.format
+
+-- test using the stdio (enter q to quit)
+while true do
+    local cont = true
+    
+    -- input
+    for i = 1, n_input do
+        local aux = io.read("*n")
+        
+        if not aux then
+            cont = false
+            break
+        end
+        
+        input[i] = aux
+    end
+    
+    if not cont then break end
+    
+    -- run the network
+    output = net:run(input)
+    
+    -- output
+    for i = 1, n_output do
+        if i >  1 then write(" ") end
+        write( sf("%.6f", output[i]) )
+    end
+    
+    write("\n")
+end

lib/ann/examples/xor/train.data

@@ -0,0 +1,9 @@
+4 2 1
+1 1
+-1
+1 -1
+1
+-1 1
+1
+-1 -1
+-1

lib/ann/examples/xor/train.lua

@@ -0,0 +1,17 @@
+#! /usr/bin/env lua
+
+require("lfann")
+
+-- Create a Neural Network with tree layers, with 2, 3 and 1 neurons, plus one
+-- bias neuron per layer
+local net = fann.Net.create_standard{2, 3, 1}
+
+-- Configure the activation function
+net:set_activation_function_hidden(fann.GAUSSIAN_SYMMETRIC)
+net:set_activation_function_output(fann.GAUSSIAN_SYMMETRIC)
+
+-- Train the net from a file
+net:train_on_file("train.data", 1000, 10, 0.0001)
+
+-- Save the net to a file for a latter execution 
+net:save("xor.net");