ds=list(range(0, 50, 2)) + d_list,
xlabel="Dimension of matrix (D)",
ylabel="Index")
elif figure == "liarinfo":
plot_heatmap(datas,
fig,
map2liarinfo_heat,
"Error info (average)",
flat=args.flat,
grid=grid,
ns=d_list,
ds=list(range(0, 50, 2)) + d_list,
xlabel="Dimension of matrix (D)",
ylabel="Index")
elif dim_match := re.match("liarpos\(([0-9]+)\)", figure):
ax = plot_dim(datas, fig, map2liarpos, int(dim_match.group(1)),
"Error amount (average)")
ax.set_ylim((0, ax.get_ylim()[1]))
elif dim_match := re.match("liardepth\(([0-9]+)\)", figure):
ax = plot_dim(datas, fig, map2liardepth, int(dim_match.group(1)),
"Error depth (average)")
ax.set_ylim((0.8, ax.get_ylim()[1]))
elif dim_match := re.match("liarinfo\(([0-9]+)\)", figure):
ax = plot_dim(datas, fig, map2liarinfo, int(dim_match.group(1)),
"Error info (average)")
ax.set_ylim((0, ax.get_ylim()[1]))
else:
print("Unknown figure.")
exit(1)
# fig.tight_layout()
fig.subplots_adjust(top=0.949,
bottom=0.079,
grid=grid,
ns=d_list,
ds=list(range(0, 50, 2)) + d_list,
xlabel="run.D",
ylabel="D")
elif figure == "liarinfo":
plot_heatmap(datas,
fig,
map2liarinfo_heat,
"liar info",
flat=args.flat,
grid=grid,
ns=d_list,
ds=list(range(0, 50, 2)) + d_list,
xlabel="run.D",
ylabel="D")
elif dim_match := re.match("liarpos\(([0-9]+)\)", figure):
plot_dim(datas, fig, map2liarpos, int(dim_match.group(1)),
"liar amount")
elif dim_match := re.match("liardepth\(([0-9]+)\)", figure):
plot_dim(datas, fig, map2liardepth, int(dim_match.group(1)),
"liar depth (average)")
elif dim_match := re.match("liarinfo\(([0-9]+)\)", figure):
plot_dim(datas, fig, map2liarinfo, int(dim_match.group(1)),
"liar info")
else:
print("Unknown figure.")
exit(1)
fig.tight_layout()
plt.show()
ds=list(range(0, 50, 2)) + d_list,
xlabel="run.D",
ylabel="D")
elif figure == "liarinfo":
plot_heatmap(datas,
fig,
map2liarinfo_heat,
"liar info",
flat=args.flat,
grid=grid,
ns=d_list,
ds=list(range(0, 50, 2)) + d_list,
xlabel="run.D",
ylabel="D")
elif dim_match := re.match("liarpos\(([0-9]+)\)", figure):
plot_dim(datas, fig, map2liarpos, int(dim_match.group(1)),
"liar amount")
elif dim_match := re.match("liardepth\(([0-9]+)\)", figure):
plot_dim(datas, fig, map2liardepth, int(dim_match.group(1)),
"liar depth (average)")
elif dim_match := re.match("liarinfo\(([0-9]+)\)", figure):
plot_dim(datas, fig, map2liarinfo, int(dim_match.group(1)),
"Average error info (bits)")
elif figure == "flipamount":
plot_heatmap(datas,
fig,
map2flipamount,
"Flip amount",
flat=args.flat,
grid=grid)
elif figure == "flipindex":
plot_heatmap(datas,