def test_overlap():
""" Test hopfield_network.pattern_tools overlap"""
import neurodynex.hopfield_network.pattern_tools as tools
pattern_size = 10
factory = tools.PatternFactory(pattern_size)
p1 = factory.create_checkerboard()
p2 = factory.create_all_on()
overlap = tools.compute_overlap(p1, p2)
assert overlap == 0.0 # works for checkerboards with even valued size
def plot_pattern(pattern, reference=None, color_map="brg", diff_code=0):
"""
Plots the pattern. If a (optional) reference pattern is provided, the pattern is plotted
with differences highlighted
Args:
pattern (numpy.ndarray): N by N pattern to plot
reference (numpy.ndarray): optional. If set, differences between pattern and reference are highlighted
"""
plt.figure()
if reference is None:
p = pattern
overlap = 1
else:
p = pattern_tools.get_pattern_diff(pattern, reference, diff_code)
overlap = pattern_tools.compute_overlap(pattern, reference)
plt.imshow(p, interpolation="nearest", cmap=color_map)
if reference is not None:
plt.title("m = {:0.2f}".format(round(overlap, 2)))
plt.axis("off")
plt.show()
