add single ch result plotting

read_res_decoding_single_ch.py

@@ -16,19 +16,55 @@
 
 df_all = pd.concat(l_)
 
-plt.figure()
-sns.boxplot(data=df_all, x="loc", y="ba", hue="mod", palette="viridis")
+plt.figure(figsize=(15, 12))
+diseases_ = df_all.dout.unique()
+locs_ = df_all["loc"].unique()
+
+for disease_idx, disease in enumerate(diseases_):
+    for loc_idx, loc_ in enumerate(locs_):
+        df_disease = df_all[df_all["dout"] == disease]
+        df_disease = df_disease[df_disease["loc"] == loc_]
+        plt.subplot(len(diseases_), len(locs_) , len(locs_)*disease_idx + 1 + loc_idx)
+        sns.boxplot(data=df_disease, x="mod", y="ba", palette="viridis")
+        plt.title(f"{loc_} {disease}")
+        #df_disease = df_all[df_all["dout"] == disease]
+        #plt.subplot(1, len(diseases_), disease_idx + 1)
+        #sns.boxplot(data=df_all, x="loc", y="ba", hue="mod", palette="viridis")
 plt.tight_layout()
 plt.show(block=True)
 
 df = pd.read_csv(os.path.join(PATH_, f"out_per_loc_mod_fft.csv"))
 # melt the dataframe that all columns with coef_ become a column
 df_melt = df.melt(id_vars=["ba", "loc", "sub", "dout"], value_vars=[c for c in df.columns if "coef_" in c])
 
-plt.figure()
+plt.figure(figsize=(15, 12))
 # melt the dataframe that coef_ becomes a column
 sns.boxplot(data=df_melt, x="variable", y="value", palette="viridis")
 plt.xticks(rotation=90)
 plt.ylabel("Coef")
 plt.tight_layout()
+plt.show(block=True)
+
+plt.figure(figsize=(15, 12))
+for disease_idx, disease in enumerate(diseases_):
+    for loc_idx, loc_ in enumerate(locs_):
+        df_disease = df_melt[df_melt["dout"] == disease]
+        df_disease = df_disease[df_disease["loc"] == loc_]
+        plt.subplot(len(diseases_), len(locs_) , len(locs_)*disease_idx + 1 + loc_idx)
+        sns.boxplot(data=df_disease, x="variable", y="value", palette="viridis")
+        plt.title(f"{loc_} {disease}")
+        #df_disease = df_all[df_all["dout"] == disease]
+        #plt.subplot(1, len(diseases_), disease_idx + 1)
+        #sns.boxplot(data=df_all, x="loc", y="ba", hue="mod", palette="viridis")
+plt.tight_layout()
+plt.show(block=True)
+
+
+#  .groupby(["sub"]).max()
+
+plt.figure(figsize=(4, 3), dpi=300)
+sns.boxplot(data=df.query("loc == 'STN'"), x="dout", y="ba")
+sns.swarmplot(data=df.query("loc == 'STN'"), x="dout", y="ba", color="gray", alpha=0.5)
+plt.tight_layout()
+plt.savefig("STN_per_comp_location.svg")
 plt.show(block=True)