src/find_interaction_cluster/community_figures/fig_functions.py: Add a...

src/find_interaction_cluster/community_figures/fig_functions.py: Add a parameter sd_community to show or hide communities sd

src/find_interaction_cluster/community_figures/fig_functions.py

@@ -315,7 +315,8 @@ def expand_results_perm(df: pd.DataFrame, rdf: pd.DataFrame, target_col: str,
 
 
 def make_barplot(df_bar: pd.DataFrame, outfile: Path,
-                 target_col: str, feature: str, target_kind: str = "") -> None:
+                 target_col: str, feature: str, target_kind: str = "",
+                 sd_community: Optional[str] = "sd") -> None:
     """
     Create a barplot showing the frequency of `nt` for every community \
     of exons/gene in `df_bar`.
@@ -327,11 +328,13 @@ def make_barplot(df_bar: pd.DataFrame, outfile: Path,
     target_col.
     :param target_col: The name of the column containing the data of interest
     :param feature: The king of feature of interest
+    :param sd_community: sd to display community error bar, None to display \
+    nothing
     """
     sns.set(context="poster")
     g = sns.catplot(x="community", y=target_col, data=df_bar, kind="point",
-                    ci="sd", aspect=2.5, height=14, errwidth=0.5, capsize=.4,
-                    scale=0.5,
+                    ci=sd_community, aspect=2.5, height=14, errwidth=0.5,
+                    capsize=.4, scale=0.5,
                     palette=["red"] + ["darkgray"] * (df_bar.shape[0] - 1))
     g2 = sns.catplot(x="community", y=target_col, data=df_bar, kind="bar",
                      ci="sd", aspect=2.5, height=14, errwidth=0.5, capsize=.4,
@@ -347,7 +350,9 @@ def make_barplot(df_bar: pd.DataFrame, outfile: Path,
     for i, p in enumerate(g2.ax.patches):
         stats = "*" if df_bara.iloc[i, :]["p-adj"] < 0.05 else ""
         com = df_bara.iloc[i, :]["community"]
-        csd = np.std(df_bar.loc[df_bar["community"] == com, target_col])
+        csd = 0
+        if sd_community == "sd":
+            csd = np.std(df_bar.loc[df_bar["community"] == com, target_col])
         g.ax.annotate(stats,
                       (p.get_x() + p.get_width() / 2., p.get_height() + csd),
                       ha='center', va='center', xytext=(0, 10), fontsize=12,
@@ -357,7 +362,8 @@ def make_barplot(df_bar: pd.DataFrame, outfile: Path,
 
 def make_barplot_perm(df_bar: pd.DataFrame, outfile: Path,
                       target_col: str, feature: str,
-                      target_kind: str = "") -> None:
+                      target_kind: str = "",
+                      sd_community: Optional[str] = "sd") -> None:
     """
     Create a barplot showing the frequency of `nt` for every community \
     of exons/gene in `df_bar`.
@@ -369,6 +375,8 @@ def make_barplot_perm(df_bar: pd.DataFrame, outfile: Path,
     target_col.
     :param target_col: The name of the column containing the data of interest
     :param feature: The king of feature of interest
+    :param sd_community: sd to display community error bar, None to display \
+    nothing
     """
     sns.set(context="poster")
     df_ctrl = df_bar.loc[df_bar[f"id_{feature}"] == 'ctrl', :]
@@ -377,13 +385,17 @@ def make_barplot_perm(df_bar: pd.DataFrame, outfile: Path,
                      ci="sd", aspect=2.5, height=14, errwidth=0.5, capsize=.4,
                      palette=["darkgray"] * (df_bar.shape[0]))
     g = sns.catplot(x="community", y=target_col, data=df_bar, kind="point",
-                    ci="sd", aspect=2.5, height=14, errwidth=0.5, capsize=.4,
-                    scale=0.5, palette=["darkgray"] * (df_bar.shape[0]))
+                    ci=sd_community, aspect=2.5, height=14, errwidth=0.5,
+                    capsize=.4, scale=0.5,
+                    palette=["darkgray"] * (df_bar.shape[0]))
     xrange = g.ax.get_xlim()
+    yrange = g.ax.get_ylim()
     df_ctrl.plot(x="community", y=target_col, kind="scatter", ax=g.ax,
                  yerr="ctrl_std", legend=False, zorder=10,
                  color=(0.8, 0.2, 0.2, 0.4))
     g.ax.set_xlim(xrange)
+    if sd_community is None:
+        g.ax.set_ylim(yrange)
     g.fig.subplots_adjust(top=0.9)
     target_kind = f" ({target_kind})" if target_kind else ""
     g.fig.suptitle(f"Mean frequency of {target_col}{target_kind}"
@@ -395,7 +407,9 @@ def make_barplot_perm(df_bar: pd.DataFrame, outfile: Path,
     for i, p in enumerate(g2.ax.patches):
         stats = "*" if df_bara.iloc[i, :]["p-adj"] < 0.05 else ""
         com = df_bara.iloc[i, :]["community"]
-        csd = np.std(df_bar.loc[df_bar["community"] == com, target_col])
+        csd = 0
+        if sd_community == "sd":
+            csd = np.std(df_bar.loc[df_bar["community"] == com, target_col])
         g.ax.annotate(stats,
                       (p.get_x() + p.get_width() / 2., p.get_height() + csd),
                       ha='center', va='center', xytext=(0, 10), fontsize=12,
@@ -405,7 +419,7 @@ def make_barplot_perm(df_bar: pd.DataFrame, outfile: Path,
 
 def barplot_creation(df_bar: pd.DataFrame, outfig: Path,
                      cpnt: str, test_type: str, feature: str,
-                     target_kind) -> None:
+                     target_kind: str, sd_community: bool) -> None:
     """
     Reformat a dataframe with the enrichment of a nucleotide frequency \
     for every feature for every community and then create a \
@@ -421,11 +435,15 @@ def barplot_creation(df_bar: pd.DataFrame, outfig: Path,
     :param test_type: The type of test to make (permutation or lm)
     :param target_kind: An optional name that describe a bit further \
     target_col.
+    :param sd_community: True to display the errors bars for communities,
+    False else.
     """
+    sd_community = "sd" if sd_community else None
     if test_type == "lm":
         make_barplot(df_bar, outfig, cpnt, feature, target_kind)
     else:
-        make_barplot_perm(df_bar, outfig, cpnt, feature, target_kind)
+        make_barplot_perm(df_bar, outfig, cpnt, feature, target_kind,
+                          sd_community)
 
 
 def get_feature_by_community(df: pd.DataFrame, feature: str) -> Dict:
@@ -461,7 +479,8 @@ def create_community_fig(df: pd.DataFrame, feature: str,
                          outfile_ctrl: Path, test_type: str,
                          dic_com: Optional[Dict] = None,
                          target_kind: str = "",
-                         iteration: int = 10000) -> None:
+                         iteration: int = 10000,
+                         sd_community: bool = True) -> None:
     """
     Create a dataframe with a control community, save it as a table and \
     as a barplot figure.
@@ -480,6 +499,8 @@ def create_community_fig(df: pd.DataFrame, feature: str,
     :param target_kind: An optional name that describe a bit further \
     target_col.
     :param iteration: The number of sub samples to create
+    :param sd_community: True to display the errors bars for communities,
+    False else.
     """
     if dic_com is None:
         dic_com = {} if test_type == 'lm' \
@@ -495,4 +516,4 @@ def create_community_fig(df: pd.DataFrame, feature: str,
     bar_outfile = str(outfile_ctrl).replace(".pdf", "_bar.txt")
     df_bar.to_csv(bar_outfile, sep="\t", index=False)
     barplot_creation(df_bar, outfile_ctrl, target_col, test_type, feature,
-                     target_kind)
+                     target_kind, sd_community)