tests.py

import brain
import brain_util as bu
import numpy as np
import random
import copy
import pickle
import matplotlib.pyplot as plt

from collections import OrderedDict

def fixed_assembly_test(n=100000,k=317,p=0.01,beta=0.01):
	b = brain.Brain(p)
	b.add_stimulus("stim",k)
	b.add_area("A",n,k,beta)
	b.project({"stim":["A"]},{})
	for i in xrange(3):
		b.project({"stim":["A"]},{"A":["A"]})
		print(b.areas["A"].w)
	b.areas["A"].fix_assembly()
	for i in xrange(5):
		b.project({"stim":["A"]},{"A":["A"]})
		print(b.areas["A"].w)
	b.areas["A"].unfix_assembly()
	for i in xrange(5):
		b.project({"stim":["A"]},{"A":["A"]})
		print(b.areas["A"].w)

def explicit_assembly_test():
	b = brain.Brain(0.5)
	b.add_stimulus("stim",3)
	b.add_explicit_area("A",10,3,beta=0.5)
	b.add_area("B",10,3,beta=0.5)

	print(b.stimuli_connectomes["stim"]["A"])
	print(b.connectomes["A"]["A"])
	print(b.connectomes["A"]["B"].shape)
	print(b.connectomes["B"]["A"].shape)

	# Now test projection stimulus -> explicit area
	print("Project stim->A")
	b.project({"stim":["A"]},{})
	print(b.areas["A"].winners)
	print(b.stimuli_connectomes["stim"]["A"])
	# Now test projection stimulus, area -> area
	b.project({"stim":["A"]},{"A":["A"]})
	print(b.areas["A"].winners)
	print(b.stimuli_connectomes["stim"]["A"])
	print(b.connectomes["A"]["A"])

	# project explicit A -> B
	print("Project explicit A -> normal B")
	b.project({},{"A":["B"]})
	print(b.areas["B"].winners)
	print(b.connectomes["A"]["B"])
	print(b.connectomes["B"]["A"])
	print(b.stimuli_connectomes["stim"]["B"])

def explicit_assembly_test2(rounds=20):
	b = brain.Brain(0.1)
	b.add_explicit_area("A",100,10,beta=0.5)
	b.add_area("B",10000,100,beta=0.5)

	b.areas["A"].winners = list(range(10,20))
	b.areas["A"].fix_assembly()
	b.project({}, {"A": ["B"]})

	# Test that if we fire back from B->A now, we don't recover the fixed assembly
	b.areas["A"].unfix_assembly()
	b.project({}, {"B": ["A"]})
	print(b.areas["A"].winners)

	b.areas["A"].winners = list(range(10,20))
	b.areas["A"].fix_assembly()
	b.project({}, {"A": ["B"]})
	for _ in range(rounds):
		b.project({}, {"A": ["B"], "B": ["A", "B"]})
		print(b.areas["B"].w)

	b.areas["A"].unfix_assembly()
	b.project({}, {"B": ["A"]})
	print("After 1 B->A, got A winners:")
	print(b.areas["A"].winners)

	for _ in range(4):
		b.project({}, {"B": ["A"], "A": ["A"]})
	print("After 5 B->A, got A winners:")
	print(b.areas["A"].winners)

def explicit_assembly_recurrent():
	b = brain.Brain(0.1)
	b.add_explicit_area("A",100,10,beta=0.5)

	b.areas["A"].winners = list(range(60,70))