update timespoken for multi

utils.py

@@ -333,7 +333,7 @@ def build_fig_pie1(df3, catTypeColors):
     """Voice category pie chart."""
     fig = go.Figure()
     fig.update_layout(
-        title_text="Percentage of each voice category",
+        title_text="Percentage of each Voice Category",
         colorway=catTypeColors,
         **TRANSPARENT_BG,
     )
@@ -348,7 +348,7 @@ def build_fig_pie2(df4, speakerNames, speaker_color_map, catColors, get_display_
     colors = [speaker_color_map.get(n, _SPEAKER_PALETTE[i % len(_SPEAKER_PALETTE)])
               for i, n in enumerate(df4["names"])]
     fig = go.Figure()
-    fig.update_layout(title_text="Percentage of speakers per role", **TRANSPARENT_BG)
+    fig.update_layout(title_text="Percentage of Speakers per Role", **TRANSPARENT_BG)
     fig.add_trace(go.Pie(values=df4["values"], labels=df4["names"],
                          marker_colors=colors, sort=False))
     return fig
@@ -392,7 +392,7 @@ def build_fig_sunburst(df5, catTypeColors, speaker_color_map, get_display_name_f
         values="percentiles",
         custom_data=["labels", "valueStrings", "percentiles", "parentNames", "parentPercentiles"],
         color="labels",
-        title="Percentage of each voice category with speakers (Combination)",
+        title="Percentage of each Voice Category with Speakers",
         color_discrete_map=color_map,
     )
     fig.update_traces(hovertemplate="<br>".join([
@@ -406,84 +406,6 @@ def build_fig_sunburst(df5, catTypeColors, speaker_color_map, get_display_name_f
     return fig
 
 
-def build_fig_sunburst_single(df5, speaker_color_map, get_display_name_fn, currFile):
-    """Sunburst showing only Single Voice speakers."""
-    df5 = df5.copy()
-    df5["labels"]      = df5["labels"].apply(lambda s: get_display_name_fn(s, currFile))
-    df5["parentNames"] = df5["parentNames"].apply(lambda s: get_display_name_fn(s, currFile))
-
-    # Keep only the Single Voice parent row and its children
-    keep_ids = {"OV"} | {row["ids"] for _, row in df5.iterrows()
-                         if row["parents"] == "OV"}
-    df5 = df5[df5["ids"].isin(keep_ids)].copy()
-    # Re-root: Single Voice becomes the top-level (parent = "")
-    df5.loc[df5["ids"] == "OV", "parents"] = ""
-
-    color_map = {lbl: speaker_color_map.get(lbl, _SPEAKER_PALETTE[i % len(_SPEAKER_PALETTE)])
-                 for i, lbl in enumerate(df5["labels"])}
-    color_map["Single Voice"] = _PALETTE[0]
-
-    fig = px.sunburst(
-        df5,
-        branchvalues="total",
-        names="labels", ids="ids", parents="parents",
-        values="percentiles",
-        custom_data=["labels", "valueStrings", "percentiles", "parentNames", "parentPercentiles"],
-        color="labels",
-        title="Percentage of each voice category with speakers (Single Voice)",
-        color_discrete_map=color_map,
-    )
-    fig.update_traces(hovertemplate="<br>".join([
-        "<b>%{customdata[0]}</b>",
-        "Duration: %{customdata[1]}s",
-        "Percentage of Total: %{customdata[2]:.2f}%",
-        "Parent: %{customdata[3]}",
-        "Percentage of Parent: %{customdata[4]:.2f}%",
-    ]))
-    fig.update_layout(**TRANSPARENT_BG, font_color="#323236")
-    return fig
-
-
-def build_fig_sunburst_multi(df5, speaker_color_map, get_display_name_fn, currFile):
-    """Sunburst showing only Multi Voice speakers."""
-    df5 = df5.copy()
-    df5["labels"]      = df5["labels"].apply(lambda s: get_display_name_fn(s, currFile))
-    df5["parentNames"] = df5["parentNames"].apply(lambda s: get_display_name_fn(s, currFile))
-
-    # Keep only the Multi Voice parent row and its children
-    keep_ids = {"MV"} | {row["ids"] for _, row in df5.iterrows()
-                         if row["parents"] == "MV"}
-    df5 = df5[df5["ids"].isin(keep_ids)].copy()
-    if df5.empty:
-        return None
-    # Re-root: Multi Voice becomes the top-level (parent = "")
-    df5.loc[df5["ids"] == "MV", "parents"] = ""
-
-    color_map = {lbl: speaker_color_map.get(lbl, _SPEAKER_PALETTE[i % len(_SPEAKER_PALETTE)])
-                 for i, lbl in enumerate(df5["labels"])}
-    color_map["Multi Voice"] = _PALETTE[9]
-
-    fig = px.sunburst(
-        df5,
-        branchvalues="total",
-        names="labels", ids="ids", parents="parents",
-        values="percentiles",
-        custom_data=["labels", "valueStrings", "percentiles", "parentNames", "parentPercentiles"],
-        color="labels",
-        title="Percentage of each voice category with speakers (Multiple Voices)",
-        color_discrete_map=color_map,
-    )
-    fig.update_traces(hovertemplate="<br>".join([
-        "<b>%{customdata[0]}</b>",
-        "Duration: %{customdata[1]}s",
-        "Percentage of Total: %{customdata[2]:.2f}%",
-        "Parent: %{customdata[3]}",
-        "Percentage of Parent: %{customdata[4]:.2f}%",
-    ]))
-    fig.update_layout(**TRANSPARENT_BG, font_color="#323236")
-    return fig
-
-
 def build_fig_treemap(df5, catTypeColors, speaker_color_map, get_display_name_fn, currFile):
     """Treemap voice-category chart."""
     df5 = df5.copy()
@@ -499,7 +421,7 @@ def build_fig_treemap(df5, catTypeColors, speaker_color_map, get_display_name_fn
         values="percentiles",
         custom_data=["labels", "valueStrings", "percentiles", "parentNames", "parentPercentiles"],
         color="labels",
-        title="Division of speakers in each voice category",
+        title="Division of Speakers in each Voice Category",
         color_discrete_map=color_map,
     )
     fig.update_traces(hovertemplate="<br>".join([
@@ -533,7 +455,7 @@ def build_fig_timeline(speakers_dataFrame, currTotalTime, speaker_color_map, get
 
     fig = px.timeline(
         df, x_start="Start", x_end="Finish", y="Resource", color="Resource",
-        title="Timeline of audio with speakers",
+        title="Timeline of Audio with Speakers",
         color_discrete_map=speaker_color_map,
     )
     fig.update_yaxes(autorange="reversed")
@@ -571,36 +493,88 @@ def _seconds_to_hhmmss(seconds):
     return f"{h:02d}:{m:02d}:{s:05.2f}"
 
 
-def build_fig_bar(df2, speakerNames, catColors, speaker_color_map, get_display_name_fn, currFile):
+def _darken_hex(hex_color, factor=0.55):
+    """Return a darker version of a hex color by reducing brightness."""
+    import colorsys
+    h = hex_color.lstrip('#')
+    r, g, b = int(h[0:2],16)/255, int(h[2:4],16)/255, int(h[4:6],16)/255
+    hue, sat, val = colorsys.rgb_to_hsv(r, g, b)
+    val = max(val * factor, 0.0)
+    r2, g2, b2 = colorsys.hsv_to_rgb(hue, sat, val)
+    return f"#{int(r2*255):02X}{int(g2*255):02X}{int(b2*255):02X}"
+
+
+def build_fig_bar(df2, speakerNames, catColors, speaker_color_map, get_display_name_fn, currFile, mv_per_speaker=None):
     """Horizontal bar chart — time spoken per speaker (hh:mm:ss.ss).
     Only individual speakers are shown; role/category rows are excluded.
     """
+    mv_per_speaker = mv_per_speaker or {}
     df2 = df2.copy()
-    # Keep only rows whose raw name is an actual speaker (not a category label)
     df2 = df2[df2["names"].isin(speakerNames)]
-    df2["names"]      = df2["names"].apply(lambda s: get_display_name_fn(s, currFile))
-    df2["time_label"] = df2["values"].apply(_seconds_to_hhmmss)
-    fig = px.bar(
-        df2, x="values", y="names", color="names", orientation="h",
-        custom_data=["names", "time_label"],
-        title="Time spoken by each speaker",
-        color_discrete_map=speaker_color_map,
-    )
-    # Hide x-axis tick labels — values are crowded with many speakers.
-    # The exact time is still visible on hover via the hovertemplate.
-    fig.update_xaxes(showticklabels=False)
-    fig.update_yaxes(autorange="reversed")
+
+    # Map raw speaker names to display names
+    raw_to_display = {sp: get_display_name_fn(sp, currFile) for sp in df2["names"]}
+    df2["display"] = df2["names"].map(raw_to_display)
+    df2["mv_secs"] = df2["names"].map(lambda sp: mv_per_speaker.get(sp, 0.0))
+    df2["sv_secs"] = (df2["values"] - df2["mv_secs"]).clip(lower=0)
+    df2["time_label"]    = df2["values"].apply(_seconds_to_hhmmss)
+    df2["mv_time_label"] = df2["mv_secs"].apply(_seconds_to_hhmmss)
+
+    # Build display-keyed color maps
+    disp_color_map = {raw_to_display[sp]: speaker_color_map.get(raw_to_display[sp], "#aaaaaa")
+                      for sp in df2["names"]}
+    disp_dark_map  = {disp: _darken_hex(col) for disp, col in disp_color_map.items()}
+
+    fig = go.Figure()
+
+    # Trace 1: single-voice portion (base color)
+    for _, row in df2.iterrows():
+        col = disp_color_map.get(row["display"], "#aaaaaa")
+        fig.add_trace(go.Bar(
+            x=[row["sv_secs"]],
+            y=[row["display"]],
+            orientation="h",
+            marker_color=col,
+            showlegend=False,
+            customdata=[[row["display"], row["time_label"], row["mv_time_label"]]],
+            hovertemplate=(
+                "<b>%{customdata[0]}</b><br>"
+                "Total: %{customdata[1]}<br>"
+                "Multi Voice: %{customdata[2]}"
+                "<extra></extra>"
+            ),
+        ))
+
+    # Trace 2: multi-voice portion (darker shade stacked on top)
+    for _, row in df2.iterrows():
+        if row["mv_secs"] <= 0:
+            continue
+        dark = disp_dark_map.get(row["display"], "#555555")
+        fig.add_trace(go.Bar(
+            x=[row["mv_secs"]],
+            y=[row["display"]],
+            orientation="h",
+            marker_color=dark,
+            showlegend=False,
+            customdata=[[row["display"], row["time_label"], row["mv_time_label"]]],
+            hovertemplate=(
+                "<b>%{customdata[0]}</b><br>"
+                "Total: %{customdata[1]}<br>"
+                "Multi Voice: %{customdata[2]}"
+                "<extra></extra>"
+            ),
+        ))
+
     fig.update_layout(
+        barmode="stack",
+        title="Time spoken by each speaker",
         xaxis_title="Time Spoken",
         yaxis_title=None,
         showlegend=False,
-        yaxis={"showticklabels": True},
+        yaxis={"showticklabels": True, "autorange": "reversed"},
+        xaxis={"showticklabels": False},
         **TRANSPARENT_BG,
     )
-    fig.update_traces(hovertemplate="<br>".join([
-        "<b>%{customdata[0]}</b>",
-        "Time Spoken: %{customdata[1]}",
-    ]))
     return fig