def plot_similarity(self):
avg_inhib = map(lambda x : x[0]["avg"],self._part_result)
var_inhib = map(lambda x : x[0]["var"],self._part_result)
avg_no_inhib = map(lambda x : x[1]["avg"],self._part_result)
var_no_inhib = map(lambda x : x[1]["var"],self._part_result)
math_tools.histogram([[average(avg_no_inhib),average(avg_inhib)]],confidence_list=[[average(var_no_inhib),average(var_inhib)]],title="Average simalirity over 10 trials",ylim=(0,1),ylabel="Similarity, s",stick_labels=("Inhib Free Network", "Inhib Network"))
math_tools.histogram([[average(var_no_inhib),average(var_inhib)]],title="Average simalirity variance over 10 trials",ylim=(0,0.04),ylabel="Similarity Variance",stick_labels=("Inhib Free Network", "Inhib Network"))
smart_plot([avg_inhib,avg_no_inhib],xlabel="Trial number",ylabel="Similarity, s",names="Average similarity for both inhibs/inhibs_free networks",ylim=(0,1),legend=["With Inhibs Network","Inhibs free Network"],legend_position=2)
smart_plot([var_no_inhib,var_inhib],xlabel="Trial number",ylabel="Similarity variance",names="Similarity variance for both inhibs/inhibs_free networks",ylim=(0,0.06),legend=["Inhibs Free Network","With Inhibs Network"],legend_position=1)
def deep_plot(self, lim=10000):
classic_data = map(lambda x: x[0], self._part_result)
inhib_free_data = map(lambda x: x[1], self._part_result)
math_tools.histogram(
[[average(inhib_free_data),
average(classic_data)]],
confidence_list=[[var(inhib_free_data),
var(classic_data)]],
title="Average Relearning time",
ylim=(0, lim),
ylabel="Time, ms",
stick_labels=("Inhib Free Network", "Inhib Network"))
def deep_plot(self,lim=10000):
classic_data = map(lambda x : x[0], self._part_result)
inhib_free_data = map(lambda x : x[1], self._part_result)
math_tools.histogram(
[[average(inhib_free_data),average(classic_data)]],
confidence_list=[[var(inhib_free_data),var(classic_data)]],
title="Average Relearning time",
ylim=(0,lim),
ylabel="Time, ms",
stick_labels=("Inhib Free Network", "Inhib Network")
)
def plot_similarity(self):
avg_inhib = map(lambda x: x[0]["avg"], self._part_result)
var_inhib = map(lambda x: x[0]["var"], self._part_result)
avg_no_inhib = map(lambda x: x[1]["avg"], self._part_result)
var_no_inhib = map(lambda x: x[1]["var"], self._part_result)
math_tools.histogram(
[[average(avg_no_inhib), average(avg_inhib)]],
confidence_list=[[average(var_no_inhib),
average(var_inhib)]],
title="Average simalirity over 10 trials",
ylim=(0, 1),
ylabel="Similarity, s",
stick_labels=("Inhib Free Network", "Inhib Network"))
math_tools.histogram(
[[average(var_no_inhib), average(var_inhib)]],
title="Average simalirity variance over 10 trials",
ylim=(0, 0.04),
ylabel="Similarity Variance",
stick_labels=("Inhib Free Network", "Inhib Network"))
smart_plot(
[avg_inhib, avg_no_inhib],
xlabel="Trial number",
ylabel="Similarity, s",
names="Average similarity for both inhibs/inhibs_free networks",
ylim=(0, 1),
legend=["With Inhibs Network", "Inhibs free Network"],
legend_position=2)
smart_plot(
[var_no_inhib, var_inhib],
xlabel="Trial number",
ylabel="Similarity variance",
names="Similarity variance for both inhibs/inhibs_free networks",
ylim=(0, 0.06),
legend=["Inhibs Free Network", "With Inhibs Network"],
legend_position=1)
