def _plot_list(axes_list,
state_sequence,
reference=None,
title_pattern="S({0})",
color_map="brg"):
"""
For internal use.
Plots all states S(t) or patterns P in state_sequence.
If a (optional) reference pattern is provided, the patters are plotted with differences highlighted
Args:
state_sequence: (list(numpy.ndarray))
reference: (numpy.ndarray)
title_pattern (str) pattern injecting index i
"""
for i in range(len(state_sequence)):
if reference is None:
p = state_sequence[i]
else:
p = pattern_tools.get_pattern_diff(state_sequence[i],
reference,
diff_code=-0.2)
axes_list[i].imshow(p, interpolation="nearest", cmap=color_map)
axes_list[i].set_title(title_pattern.format(i))
axes_list[i].axis("off")
def _plot_list(axes_list, state_sequence, reference=None, title_pattern="S({0})", color_map="brg"):
"""
For internal use.
Plots all states S(t) or patterns P in state_sequence.
If a (optional) reference pattern is provided, the patters are plotted with differences highlighted
Args:
state_sequence: (list(numpy.ndarray))
reference: (numpy.ndarray)
title_pattern (str) pattern injecting index i
"""
for i in range(len(state_sequence)):
if reference is None:
p = state_sequence[i]
else:
p = pattern_tools.get_pattern_diff(state_sequence[i], reference, diff_code=-0.2)
axes_list[i].imshow(p, interpolation="nearest", cmap=color_map)
axes_list[i].set_title(title_pattern.format(i))
axes_list[i].axis("off")
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()
