<jupyter_start><jupyter_text>RMSE vs Mean of adversary distribution<jupyter_code>vr = all_vars[-1]
means1 = means[means["Var"] == vr]
devs1 = stds[means["Var"] == vr]

t = "Variance" + " = " + str(round(vr, 2))
x = means1["Mean"]
y1 = means1["bayes_atdata"]
y2 = means1["nash_atdata"]
y3 = means1["raw_atdata"]
y1dev = devs1["bayes_atdata"]
y2dev = devs1["nash_atdata"]
y3dev = devs1["raw_atdata"]

f,ax2 = plt.subplots(1,1,sharex=True, facecolor='w')
sns.set_style("whitegrid")
# Plot distributions
ax2.errorbar(x, y1, yerr=y1dev ,ecolor='black', color = sns.xkcd_rgb["black"], fmt = 'o',linestyle='-',elinewidth=0.9,capsize=5,capthick=0.5)
ax2.errorbar(x, y2, yerr=y2dev ,ecolor='black', color = sns.xkcd_rgb["black"], fmt = 'o', linestyle='--',elinewidth=0.9,capsize=5,capthick=0.5)
ax2.errorbar(x, y3, yerr=y3dev ,ecolor='black', color = sns.xkcd_rgb["black"], fmt = 'o',linestyle=':',elinewidth=0.9,capsize=5,capthick=0.5)
# Create the legend box
box = ax2.get_position()
ax2.set_position([box.x0, box.y0, box.width * 0.8, box.height])
# Add legend and labels
ax2.legend(labels=["Bayes", "Nash", "Raw"],loc='upper right', bbox_to_anchor=(0,0.97,1,0.2), prop={'size': 14})
ax2.set(xlabel="Mean")
ax2.set_ylabel("RMSE")
# Set size of title and x,y labels
plt.gcf().autofmt_xdate()
ax2.tick_params(labelsize=14)
f.suptitle(t,x=0.5, y=0.93, fontsize=20)
ax2.xaxis.label.set_size(20)
ax2.yaxis.label.set_size(20)
plt.rcParams["figure.figsize"] = (12,9)

plt.savefig("fig/rmse_var_"+str(round(vr, 2))+".eps", format='eps', dpi=600)<jupyter_output><empty_output><jupyter_text>RMSE vs Variance of adversary distribution<jupyter_code>mn = all_means[-2]
means1 = means[means["Mean"] == mn]
devs1 = stds[means["Mean"] == mn]

t = "Mean" + " = " + str(round(mn, 2))
x = means1["Var"]
y1 = means1["bayes_atdata"]
y2 = means1["nash_atdata"]
y3 = means1["raw_atdata"]
y1dev = devs1["bayes_atdata"]
y2dev = devs1["nash_atdata"]
y3dev = devs1["raw_atdata"]

f,ax2 = plt.subplots(1,1,sharex=True, facecolor='w')
sns.set_style("whitegrid")
# Plot distributions
ax2.errorbar(x, y1, yerr=y1dev ,ecolor='black', color = sns.xkcd_rgb["black"], fmt = 'o',linestyle='-',elinewidth=0.9,capsize=5,capthick=0.5)
ax2.errorbar(x, y2, yerr=y2dev ,ecolor='black', color = sns.xkcd_rgb["black"], fmt = 'o', linestyle='--',elinewidth=0.9,capsize=5,capthick=0.5)
ax2.errorbar(x, y3, yerr=y3dev ,ecolor='black', color = sns.xkcd_rgb["black"], fmt = 'o',linestyle=':',elinewidth=0.9,capsize=5,capthick=0.5)
# Create the legend box
box = ax2.get_position()
ax2.set_position([box.x0, box.y0, box.width * 0.8, box.height])
# Add legend and labels
ax2.legend(labels=["Bayes", "Nash", "Raw"],loc='upper right', bbox_to_anchor=(0,0.97,1,0.2), prop={'size': 14})
ax2.set(xlabel="Variance")
ax2.set_ylabel("RMSE")
# Set size of title and x,y labels
plt.gcf().autofmt_xdate()
ax2.tick_params(labelsize=14)
f.suptitle(t,x=0.5, y=0.93, fontsize=20)
ax2.xaxis.label.set_size(20)
ax2.yaxis.label.set_size(20)
plt.rcParams["figure.figsize"] = (12,9)

plt.savefig("fig/rmse_mean_"+str(round(mn, 2))+".eps", format='eps', dpi=600)<jupyter_output><empty_output>
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