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)