def testSingleImprovement(self):
P, T = loadsyn3(100)
test, validation = get_validation_set(P, T)
net1 = build_feedforward(2, 6, 1)
epochs = 100
P, T = test
Y = net1.sim(P)
[num_correct_first, num_correct_second, initial_test_performance, num_first, num_second, missed] = stat(Y, T) #@UnusedVariable
P, T = validation
Y = net1.sim(P)
[num_correct_first, num_correct_second, initial_val_performance, num_first, num_second, missed] = stat(Y, T) #@UnusedVariable
best1 = train_evolutionary(net1, test, validation, epochs, random_range = 5)
P, T = test
Y = best1.sim(P)
[num_correct_first, num_correct_second, genetic_test_performance, num_first, num_second, missed] = stat(Y, T) #@UnusedVariable
P, T = validation
Y = best1.sim(P)
[num_correct_first, num_correct_second, genetic_val_performance, num_first, num_second, missed] = stat(Y, T) #@UnusedVariable
#Test sets
print(initial_test_performance, genetic_test_performance)
assert(initial_test_performance < genetic_test_performance)
#Validation sets
#print(initial_val_performance, genetic_val_performance)
#assert(initial_val_performance < genetic_val_performance)
net2 = build_feedforward(2, 6, 1)
epochs = 100
P, T = test
Y = net2.sim(P)
[num_correct_first, num_correct_second, initial_test_performance, num_first, num_second, missed] = stat(Y, T) #@UnusedVariable
P, T = validation
Y = net2.sim(P)
[num_correct_first, num_correct_second, initial_val_performance, num_first, num_second, missed] = stat(Y, T) #@UnusedVariable
best2 = traingd(net2, test, validation, epochs, block_size = 10)
P, T = test
Y = best2.sim(P)
[num_correct_first, num_correct_second, gd_test_performance, num_first, num_second, missed] = stat(Y, T) #@UnusedVariable
P, T = validation
Y = best2.sim(P)
[num_correct_first, num_correct_second, gd_val_performance, num_first, num_second, missed] = stat(Y, T) #@UnusedVariable
#Assert that an improvement has occurred in each step
#Test sets
print(initial_test_performance, genetic_test_performance, gd_test_performance)
assert(initial_test_performance < gd_test_performance)
def testFilehandling(self):
print ("Testing network saving/loading")
net = build_feedforward()
results1 = net.update([1, 2])
print (results1)
filename = path.join(path.expanduser("~"), "test.ann")
print ("saving and reloading")
save_network(net, filename)
net = load_network(filename)
results2 = net.update([1, 2])
print (results2)
print (abs(results1[0] - results2[0]))
assert abs(results1[0] - results2[0]) < 0.0001 # float doesn't handle absolutes so well
print ("Good, now testing committee...")
com = build_feedforward_committee()
results1 = com.update([1, 2])
print (results1)
filename = path.join(path.expanduser("~"), "test.anncom")
print ("saving and reloading")
save_committee(com, filename)
com = load_committee(filename)
results2 = com.update([1, 2])
print (results2)
assert abs(results1[0] - results2[0]) < 0.0001 # float doesn't handle absolutes so well
print ("Results are good. Testing input parsing....")
filename = path.join(path.expanduser("~"), "ann_input_data_test_file.txt")
print ("First, split the file into a test set(80%) and validation set(20%)...")
inputs, targets = parse_file(filename, targetcols=5, ignorecols=[0, 1, 4], ignorerows=[])
test, validation = get_validation_set(inputs, targets, validation_size=0.5)
print (len(test[0]))
print (len(test[1]))
print (len(validation[0]))
print (len(validation[1]))
assert len(test) == 2
assert len(test[0]) > 0
assert len(test[1]) > 0
assert len(validation) == 2
assert len(validation[0]) > 0
assert len(validation[1]) > 0
print ("Went well, now expecting a zero size validation set...")
test, validation = get_validation_set(inputs, targets, validation_size=0)
print (len(test[0]))
print (len(test[1]))
print (len(validation[0]))
print (len(validation[1]))
assert len(test) == 2
assert len(test[0]) > 0
assert len(test[1]) > 0
assert len(validation) == 2
assert len(validation[0]) == 0
assert len(validation[1]) == 0
print ("As expected. Now a 100% validation set...")
test, validation = get_validation_set(inputs, targets, validation_size=1)
print (len(test[0]))
print (len(test[1]))
print (len(validation[0]))
print (len(validation[1]))
assert len(test) == 2
assert len(test[0]) == 0
assert len(test[1]) == 0
assert len(validation) == 2
assert len(validation[0]) > 0
assert len(validation[1]) > 0
print ("Now we test a stratified set...")
test, validation = get_validation_set(inputs, targets, validation_size=0.5, binary_column=0)
print (len(test[0]))
print (len(test[1]))
print (len(validation[0]))
print (len(validation[1]))
assert len(test) == 2
assert len(test[0]) > 0
assert len(test[1]) > 0
assert len(validation) == 2
assert len(validation[0]) > 0
assert len(validation[1]) > 0
print ("Test with no targets, the no inputs")
inputs, targets = parse_file(filename, ignorecols=[0, 1, 4], ignorerows=[])
assert (targets.size) == 0
assert (inputs.size) > 0
inputs, targets = parse_file(filename, targetcols=3, ignorecols=[0, 1, 2, 4, 5, 6, 7, 8, 9], ignorerows=[])
assert (targets.size) > 0
assert (inputs.size) == 0