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figures_exp.jl
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function figure_drug(batch_ID, study, sessions, session_labels, cue_labels)
fig_sz_inch = (6.4, 8)
font_sz = 11
dir = string("./exp/", batch_ID, "/", study,"/")
df = read_JBT(dir)
df_cb = CSV.File(string(dir,"counterbalance/", study, "_counterbalance.csv")) |> DataFrame
filter!(row -> row.session == "probe", df)
df.session = map(row -> df_cb[df_cb.ID.==row.ID, row.date][1], eachrow(df))
cues = [2, 5, 8]
f = Figure(resolution = 72 .* fig_sz_inch, fontsize=font_sz)
ga = f[1, 1] = GridLayout()
gb = f[2, 1] = GridLayout()
gc = f[2, 2] = GridLayout()
gd = f[3, 1] = GridLayout()
ge = f[3, 2] = GridLayout()
ax = [
Axis(ga[1,1],
xticks=(1:length(sessions[sessions.!="vehicle"]), session_labels[sessions.!="vehicle"]),
yticks=[-1.0,-0.5,0.0,0.5,1.0],
ylabel="Difference in CBI"),
Axis(gb[1,1],
yticks=0.0:25.0:100.0,
xlabel="Cue",
xticks=(1:length(cues), cue_labels),
ylabel="HA responses [%]"),
Axis(gc[1,1],
xlabel="Cue",
xticks=(1:length(cues), cue_labels),
ylabel="Response time [sec]"),
Axis(gd[1,1],
xlabel="Cue",
xticks=(1:length(cues), cue_labels),
ylabel="Omissions [%]"),
Axis(ge[1,1],
xticks=(1:length(sessions), session_labels),
ylabel="Premature responses [%]")
]
plot_diff_CBI!(ax[1], df, sessions, session_labels)
plot_responses!(ax[2], df, 2, cues, sessions, session_labels)
plot_RT!(ax[3], df, cues, sessions, session_labels)
plot_omissions!(ax[4], df, cues, sessions, session_labels)
plot_prematures!(ax[5], df, sessions, session_labels)
xlims!(ax[1], [0.5, length(sessions[sessions.!="vehicle"])+0.5])
xlims!(ax[5], 0.5, length(sessions)+0.5)
ylims!(ax[1], -1.6, 1.6)
colgap!(f.layout, Relative(0.04))
rowgap!(f.layout, Relative(0.005))
f[1, 2] = Legend(f, ax[2], framevisible=false, unique=true, tellwidth=false, tellheight=false)
for (label, layout) in zip(["A", "B", "C", "D", "E"], [ga, gb, gc, gd, ge])
Label(layout[1, 1, TopLeft()], label,
textsize = 18,
halign = :right)
end
save(string("./figures/exp/", batch_ID, "_", study, ".eps"), f, pt_per_unit = 1)
end
function figure_probe(batch_ID, study, sessions, session_labels, cue_labels;
ID_excluded=[], S_excluded=[], reversed=false)
fig_sz_inch = (6.4, 8)
font_sz = 11
dir = string("./exp/", batch_ID, "/", study,"/")
df = read_JBT(dir; reversed=reversed)
filter!(row -> row.session == "probe", df)
df_cb = CSV.File(string(dir,"counterbalance/", study, "_counterbalance.csv")) |> DataFrame
df.session = map(row -> df_cb[df_cb.ID.==row.ID, row.date][1], eachrow(df))
filter!(row -> !in(row.ID, ID_excluded) && !in(row.session, S_excluded), df)
cues = [2, 5, 8]
f = Figure(resolution = 72 .* fig_sz_inch, fontsize=font_sz)
ga = f[1, 1] = GridLayout()
gb = f[2, 1] = GridLayout()
gc = f[2, 2] = GridLayout()
gd = f[3, 1] = GridLayout()
ge = f[3, 2] = GridLayout()
ax = [
Axis(ga[1,1],
xticks=(1:length(sessions), session_labels),
ylabel="CBI"),
Axis(gb[1,1],
yticks=0.0:25.0:100.0,
xlabel="Cue",
xticks=(1:length(cues), cue_labels),
ylabel="HA responses [%]"),
Axis(gc[1,1],
xlabel="Cue",
xticks=(1:length(cues), cue_labels),
ylabel="Response time [sec]"),
Axis(gd[1,1],
xlabel="Cue",
xticks=(1:length(cues), cue_labels),
ylabel="Omissions [%]"),
Axis(ge[1,1],
xticks=(1:length(sessions), session_labels),
ylabel="Premature responses [%]")
]
plot_CBI!(ax[1], df, sessions, session_labels)
plot_responses!(ax[2], df, 2, cues, sessions, session_labels)
plot_RT!(ax[3], df, cues, sessions, session_labels)
plot_omissions!(ax[4], df, cues, sessions, session_labels)
plot_prematures!(ax[5], df, sessions, session_labels)
xlims!(ax[1], 0.5, length(sessions)+0.5)
xlims!(ax[5], 0.5, length(sessions)+0.5)
ylims!(ax[1], -1.4, 1.4)
colgap!(f.layout, Relative(0.04))
rowgap!(f.layout, Relative(0.005))
f[1, 2] = Legend(f, ax[2], framevisible=false, unique=true, tellwidth=false, tellheight=false)
for (label, layout) in zip(["A", "B", "C", "D", "E"], [ga, gb, gc, gd, ge])
Label(layout[1, 1, TopLeft()], label,
textsize = 18,
halign = :right)
end
save(string("./figures/exp/", batch_ID, "_", study, ".eps"), f, pt_per_unit = 1)
end
figure_probe("HO2",
"1vs1",
["1vs1_2"],
["Session 2"],
["2 kHz", "5 kHz", "8 kHz"];
ID_excluded=["HO2_4", "HO2_11"],
S_excluded=["1vs1_1"]
)
figure_probe("HO2",
"4vs1",
["4vs1_1", "4vs1_2"],
["Session 1", "Session 2"],
["HC", "AC", "LC"]
)
figure_drug("HO2",
"24hket",
["vehicle", "ketamine_24h"],
["Vehicle", "Ketamine (24h)"],
["HC", "AC", "LC"]
)
figure_drug("HO2",
"amph",
["vehicle", "amphetamine"],
["Vehicle", "Amphetamine"],
["HC", "AC", "LC"]
)
figure_drug("HO2",
"ket",
["vehicle", "ketamine"],
["Vehicle", "Ketamine"],
["HC", "AC", "LC"]
)
figure_drug("HO2",
"ket_ds",
["vehicle", "ketamine_03", "ketamine_1", "ketamine_3"],
["V", "K 0.3", "K 1.0", "K 3.0"],
["HC", "AC", "LC"]
)
figure_probe("HO3",
"1vs1",
["1vs1_1", "1vs1_2"],
["Session 1", "Session 2"],
["2 kHz\n+ LL", "LL", "8 kHz\n+ LL"]
)
figure_drug("HO3",
"ket_1vs1",
["vehicle", "ketamine"],
["Vehicle", "Ketamine"],
["2 kHz\n+ LL", "LL", "8 kHz\n+ LL"]
)
figure_probe("HO3",
"1vs1_reversed",
["1vs1_reversed_1", "1vs1_reversed_2"],
["Session 1", "Session 2"],
["2 kHz\n+ LL", "LL", "8 kHz\n+ LL"];
reversed=true
)