From 497d0838346ea0f0382e549b214ba6f99d9832be Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Wed, 5 Aug 2026 15:08:02 +0200
Subject: [PATCH 01/15] Fix stale results on UI with empty cusums

---
 oonipipeline/src/oonipipeline/events_panel/panel.py | 12 ++++++++++--
 1 file changed, 10 insertions(+), 2 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index cfe28988..5b30e73d 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -52,6 +52,10 @@ def detector_panel():
     # Only recompute on submit; store in session_state so results survive
     # reruns triggered by the selectboxes below.
     if submitted:
+        # Drop any cusum-related state left over from a previous submission
+        for key in ("changepoints", "cusum_steps", "block_type_select", "asn_select"):
+            st.session_state.pop(key, None)
+
         changepoints, _, cusum_steps = run_detector_cached(
             clickhouse_url,
             to_datetime(start_time),
@@ -86,11 +90,15 @@ def detector_panel():
     c2.write(f"Cusum steps: **{len(cusum_steps)}**")
 
     c1, c2 = st.columns(2)
-    block_type = c1.selectbox("Block type", [c[0] for c in ANALYSIS_COLS])
+    block_type = c1.selectbox(
+        "Block type", [c[0] for c in ANALYSIS_COLS], key="block_type_select"
+    )
 
     asn_list = list(asns.keys())
     asn_list.sort(key=lambda k: asns[k], reverse=True)
-    selected_asn = c2.selectbox("ASN", asn_list, format_func=lambda k: f"{k} ({asns[k]})")
+    selected_asn = c2.selectbox(
+        "ASN", asn_list, format_func=lambda k: f"{k} ({asns[k]})", key="asn_select"
+    )
 
     chart_steps = [s for s in cusum_steps if s["probe_asn"] == selected_asn]
 

From bbd736f2c7053c784b731b366f55b8b74e37e5db Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Thu, 6 Aug 2026 14:01:45 +0200
Subject: [PATCH 02/15] Add debug panel with png version of chart

---
 oonipipeline/pyproject.toml                         |  1 +
 oonipipeline/src/oonipipeline/events_panel/panel.py | 13 ++++++++++++-
 2 files changed, 13 insertions(+), 1 deletion(-)

diff --git a/oonipipeline/pyproject.toml b/oonipipeline/pyproject.toml
index 4feef080..2e66f9c1 100644
--- a/oonipipeline/pyproject.toml
+++ b/oonipipeline/pyproject.toml
@@ -42,6 +42,7 @@ analysis = [
   "bokeh ~= 3.5.2",
   "streamlit",
   "pyarrow < 19", # fixes segfault with streamlit
+  "vl-convert-python>=1.9.0.post1",
 ]
 
 [tool.hatch.build.targets.sdist]
diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index 5b30e73d..07cec37b 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -4,6 +4,7 @@
 from datetime import datetime, timezone, timedelta, date
 import logging
 import pandas as pd
+import vl_convert as vlc
 
 log = logging.getLogger(__name__)
 
@@ -106,7 +107,8 @@ def detector_panel():
         st.warning(f"No cusum steps found for ASN {selected_asn}")
         return
 
-    st.altair_chart(make_cusums_chart(chart_steps, block_type))
+    chart = make_cusums_chart(chart_steps, block_type)
+    st.altair_chart(chart)
 
     if asns:
         df = pd.DataFrame({"ASN": list(asns.keys()), "total": list(asns.values())})
@@ -114,5 +116,14 @@ def detector_panel():
         df["ASN"] = df["ASN"].astype(str)
         st.dataframe(df, hide_index=True)
 
+    with st.expander("🔧 Debug"):
+        if st.checkbox("Render chart as PNG", key="debug_render_png"):
+            spec = chart.to_dict()
+            png_bytes = vlc.vegalite_to_png(spec, scale=2)
+            st.image(png_bytes, caption="Chart rendered to PNG via vl-convert")
+
+        if st.checkbox("Show Vega-Lite spec", key="debug_show_spec"):
+            st.json(chart.to_dict())
+
 
 detector_panel()

From 03a397bfacacc12a49ca9038b29ece2fd04d54ce Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Thu, 6 Aug 2026 14:22:39 +0200
Subject: [PATCH 03/15] Add hour to chart

---
 .../src/oonipipeline/analysis/detector.py     | 31 ++++++++++++++-----
 .../src/oonipipeline/events_panel/panel.py    | 13 +++-----
 2 files changed, 29 insertions(+), 15 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index 52746761..f90d5589 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -585,6 +585,8 @@ def make_cusums_chart(steps: List[CusumStep], block_type: str):
     import pandas as pd
 
     STATE_COLORS = {"ok": "#d4edda", "blk": "#f8d7da", "unk": "#fff3cd"}
+    x_axis = alt.Axis(format="%b %d, %H:%M")
+    ts_tooltip_fmt = "%b %d, %H:%M"
 
     df_steps = pd.DataFrame([s for s in steps if s["block_type"] == block_type])
     df_last = df_steps.loc[[df_steps["ts"].idxmax()]]
@@ -608,7 +610,7 @@ def make_cusums_chart(steps: List[CusumStep], block_type: str):
         alt.Chart(df_bands)
         .mark_rect(opacity=0.25)
         .encode(
-            x=alt.X("state_start:T"),
+            x=alt.X("state_start:T", axis=x_axis),
             x2=alt.X2("state_end:T"),
             color=alt.Color(
                 "current_state:N",
@@ -622,11 +624,15 @@ def make_cusums_chart(steps: List[CusumStep], block_type: str):
                 ),
                 legend=alt.Legend(title="State"),
             ),
-            tooltip=["current_state:N", "state_start:T", "state_end:T"],
+            tooltip=[
+                "current_state:N",
+                alt.Tooltip("state_start:T", format=ts_tooltip_fmt),
+                alt.Tooltip("state_end:T", format=ts_tooltip_fmt),
+            ],
         )
     )
 
-    base = alt.Chart(df_steps).encode(x="ts:T")
+    base = alt.Chart(df_steps).encode(x=alt.X("ts:T", axis=x_axis))
 
     def make_label(df, field, label, color):
         return (
@@ -641,15 +647,20 @@ def make_label(df, field, label, color):
 
     obs_line = base.mark_line(color="steelblue", opacity=0.5).encode(
         y=alt.Y("obs_value:Q", title="value"),
-        tooltip=["ts:T", "obs_value:Q", "weight:Q", "current_state:N"],
+        tooltip=[
+            alt.Tooltip("ts:T", format=ts_tooltip_fmt),
+            "obs_value:Q",
+            "weight:Q",
+            "current_state:N",
+        ],
     )
     s_pos_line = base.mark_line(color="red").encode(
         y=alt.Y("s_pos:Q"),
-        tooltip=["ts:T", "s_pos:Q"],
+        tooltip=[alt.Tooltip("ts:T", format=ts_tooltip_fmt), "s_pos:Q"],
     )
     s_neg_line = base.mark_line(color="orange").encode(
         y=alt.Y("s_neg:Q"),
-        tooltip=["ts:T", "s_neg:Q"],
+        tooltip=[alt.Tooltip("ts:T", format=ts_tooltip_fmt), "s_neg:Q"],
     )
     threshold = (
         alt.Chart(df_steps).mark_rule(color="green", strokeDash=[4, 4]).encode(y="h:Q")
@@ -660,7 +671,13 @@ def make_label(df, field, label, color):
         .encode(
             x="ts:T",
             y=alt.Y("obs_value:Q"),
-            tooltip=["ts:T", "obs_value:Q", "s_pos:Q", "s_neg:Q", "current_state:N"],
+            tooltip=[
+                alt.Tooltip("ts:T", format=ts_tooltip_fmt),
+                "obs_value:Q",
+                "s_pos:Q",
+                "s_neg:Q",
+                "current_state:N",
+            ],
         )
     )
 
diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index 07cec37b..712b838d 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -1,16 +1,13 @@
 from collections import defaultdict
 import streamlit as st
 from oonipipeline.analysis.detector import make_cusums_chart, run_detector_for, ANALYSIS_COLS
-from datetime import datetime, timezone, timedelta, date
+from datetime import datetime, timezone, timedelta
 import logging
 import pandas as pd
 import vl_convert as vlc
 
 log = logging.getLogger(__name__)
 
-def to_datetime(d: date):
-    return datetime(year=d.year, month=d.month, day=d.day, hour=0, tzinfo=timezone.utc)
-
 
 @st.cache_data(ttl=300)
 def run_detector_cached(*args, **kwargs):
@@ -38,12 +35,12 @@ def detector_panel():
         c1, c2 = st.columns(2)
 
         # column 1
-        start_time = c1.date_input("**Start time**", now - timedelta(days=30))
+        start_time = c1.datetime_input("**Start date**", now - timedelta(days=30))
         probe_cc = c1.text_input("**Country code (two chars)**", "VE")
         edd = c1.number_input("**Estimated Detection Delay (EDD)**", value=10)
 
         # column2
-        end_time = c2.date_input("**End time**", now)
+        end_time = c2.datetime_input("**End date**", now)
         domain = c2.text_input("**domain**", "x.com")
         gap_halflife = c2.number_input("**Gap half life**", value=48.0)
 
@@ -59,8 +56,8 @@ def detector_panel():
 
         changepoints, _, cusum_steps = run_detector_cached(
             clickhouse_url,
-            to_datetime(start_time),
-            to_datetime(end_time),
+            start_time,
+            end_time,
             probe_cc,
             [domain],
             edd,

From bead93d312a23173c6a88e0a7d58d76abd64bcd6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Thu, 6 Aug 2026 14:52:20 +0200
Subject: [PATCH 04/15] make hover label show you the value of the closest
 chart

---
 .../src/oonipipeline/analysis/detector.py     | 115 +++++++++++++-----
 1 file changed, 86 insertions(+), 29 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index f90d5589..ea0de202 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -645,25 +645,69 @@ def make_label(df, field, label, color):
             )
         )
 
+    def make_nearest_hover(df, value_vars, colors, labels, y_title):
+        """
+        Builds an invisible hit-target layer plus a visible highlight dot per
+        series, using a melted long-form copy so the "nearest" selection
+        matches in true 2D (ts, value) space — hovering picks whichever
+        series is visually closest to the cursor rather than just the
+        closest timestamp.
+        """
+        df_melt = df.melt(
+            id_vars=["ts"],
+            value_vars=value_vars,
+            var_name="series",
+            value_name="value",
+        )
+        df_melt["series_label"] = df_melt["series"].map(labels)
+
+        nearest = alt.selection_single(
+            nearest=True,
+            on="mouseover",
+            fields=["ts", "series"],
+            empty="none",
+            name=f"nearest_{'_'.join(value_vars)}",
+        )
+        melt_base = alt.Chart(df_melt).encode(
+            x=alt.X("ts:T", axis=x_axis),
+            y=alt.Y("value:Q", title=y_title),
+            color=alt.Color(
+                "series:N",
+                scale=alt.Scale(
+                    domain=list(colors.keys()), range=list(colors.values())
+                ),
+                legend=None,
+            ),
+        )
+        selectors = (
+            melt_base.mark_point()
+            .encode(
+                opacity=alt.value(0),
+                tooltip=[
+                    alt.Tooltip("ts:T", format=ts_tooltip_fmt),
+                    alt.Tooltip("series_label:N", title="series"),
+                    alt.Tooltip("value:Q"),
+                ],
+            )
+            .add_selection(nearest)
+        )
+        hover_rule = base.mark_rule(color="gray").encode(
+            opacity=alt.condition(nearest, alt.value(0.3), alt.value(0))
+        )
+        highlight_points = melt_base.mark_point(filled=True, size=80).encode(
+            opacity=alt.condition(nearest, alt.value(1), alt.value(0))
+        )
+        return hover_rule + highlight_points + selectors
+
     obs_line = base.mark_line(color="steelblue", opacity=0.5).encode(
         y=alt.Y("obs_value:Q", title="value"),
-        tooltip=[
-            alt.Tooltip("ts:T", format=ts_tooltip_fmt),
-            "obs_value:Q",
-            "weight:Q",
-            "current_state:N",
-        ],
     )
-    s_pos_line = base.mark_line(color="red").encode(
-        y=alt.Y("s_pos:Q"),
-        tooltip=[alt.Tooltip("ts:T", format=ts_tooltip_fmt), "s_pos:Q"],
-    )
-    s_neg_line = base.mark_line(color="orange").encode(
-        y=alt.Y("s_neg:Q"),
-        tooltip=[alt.Tooltip("ts:T", format=ts_tooltip_fmt), "s_neg:Q"],
-    )
-    threshold = (
-        alt.Chart(df_steps).mark_rule(color="green", strokeDash=[4, 4]).encode(y="h:Q")
+    obs_hover = make_nearest_hover(
+        df_steps,
+        ["obs_value"],
+        {"obs_value": "steelblue"},
+        {"obs_value": "observed"},
+        y_title="value",
     )
     cp_points = (
         alt.Chart(df_steps[df_steps["is_changepoint"]])
@@ -680,8 +724,21 @@ def make_label(df, field, label, color):
             ],
         )
     )
-
     obs_label = make_label(df_last, "obs_value", "observed", "steelblue")
+    value_group = alt.layer(obs_line, obs_hover, cp_points, obs_label)
+
+    s_pos_line = base.mark_line(color="red").encode(y=alt.Y("s_pos:Q"))
+    s_neg_line = base.mark_line(color="orange").encode(y=alt.Y("s_neg:Q"))
+    cusum_hover = make_nearest_hover(
+        df_steps,
+        ["s_pos", "s_neg"],
+        {"s_pos": "red", "s_neg": "orange"},
+        {"s_pos": "S+", "s_neg": "S−"},
+        y_title="CUSUM statistic",
+    )
+    threshold = (
+        alt.Chart(df_steps).mark_rule(color="green", strokeDash=[4, 4]).encode(y="h:Q")
+    )
     s_pos_label = make_label(df_last, "s_pos", "S+", "red")
     s_neg_label = make_label(df_last, "s_neg", "S−", "orange")
     df_h = df_last[["ts", "h"]].copy()
@@ -690,20 +747,20 @@ def make_label(df, field, label, color):
         .mark_text(align="left", dx=5, fontSize=11, color="green")
         .encode(x="ts:T", y="h:Q", text=alt.value("threshold (h)"))
     )
+    cusum_group = alt.layer(
+        s_pos_line,
+        s_neg_line,
+        cusum_hover,
+        threshold,
+        s_pos_label,
+        s_neg_label,
+        threshold_label,
+    )
 
     chart = (
-        (
-            state_bands
-            + obs_line
-            + obs_label
-            + s_pos_line
-            + s_pos_label
-            + s_neg_line
-            + s_neg_label
-            + threshold
-            + threshold_label
-            + cp_points
-        )
+        alt.layer(state_bands, value_group, cusum_group)
+        .resolve_scale(y="independent", color="independent")
+        .resolve_legend(color="independent")
         .properties(
             width=900,
             height=400,

From 661304f52ada476a7b4d7963ed9df487b4930c75 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Thu, 6 Aug 2026 15:07:26 +0200
Subject: [PATCH 05/15] Add legend with lines colors

---
 .../src/oonipipeline/analysis/detector.py     | 20 +++++++++++--------
 1 file changed, 12 insertions(+), 8 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index ea0de202..a09c562c 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -645,13 +645,14 @@ def make_label(df, field, label, color):
             )
         )
 
-    def make_nearest_hover(df, value_vars, colors, labels, y_title):
+    def make_nearest_hover(df, value_vars, colors, labels, y_title, legend_title):
         """
         Builds an invisible hit-target layer plus a visible highlight dot per
         series, using a melted long-form copy so the "nearest" selection
         matches in true 2D (ts, value) space — hovering picks whichever
         series is visually closest to the cursor rather than just the
-        closest timestamp.
+        closest timestamp. The same color scale drives a legend labeling
+        each line.
         """
         df_melt = df.melt(
             id_vars=["ts"],
@@ -672,11 +673,12 @@ def make_nearest_hover(df, value_vars, colors, labels, y_title):
             x=alt.X("ts:T", axis=x_axis),
             y=alt.Y("value:Q", title=y_title),
             color=alt.Color(
-                "series:N",
+                "series_label:N",
                 scale=alt.Scale(
-                    domain=list(colors.keys()), range=list(colors.values())
+                    domain=[labels[v] for v in value_vars],
+                    range=[colors[v] for v in value_vars],
                 ),
-                legend=None,
+                legend=alt.Legend(title=legend_title),
             ),
         )
         selectors = (
@@ -708,6 +710,7 @@ def make_nearest_hover(df, value_vars, colors, labels, y_title):
         {"obs_value": "steelblue"},
         {"obs_value": "observed"},
         y_title="value",
+        legend_title="Value",
     )
     cp_points = (
         alt.Chart(df_steps[df_steps["is_changepoint"]])
@@ -731,10 +734,11 @@ def make_nearest_hover(df, value_vars, colors, labels, y_title):
     s_neg_line = base.mark_line(color="orange").encode(y=alt.Y("s_neg:Q"))
     cusum_hover = make_nearest_hover(
         df_steps,
-        ["s_pos", "s_neg"],
-        {"s_pos": "red", "s_neg": "orange"},
-        {"s_pos": "S+", "s_neg": "S−"},
+        ["s_pos", "s_neg", "h"],
+        {"s_pos": "red", "s_neg": "orange", "h": "green"},
+        {"s_pos": "S+", "s_neg": "S−", "h": "threshold (h)"},
         y_title="CUSUM statistic",
+        legend_title="CUSUM",
     )
     threshold = (
         alt.Chart(df_steps).mark_rule(color="green", strokeDash=[4, 4]).encode(y="h:Q")

From 6f60c9eeededbe5dc625604799b107cbc600b323 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Thu, 6 Aug 2026 15:22:27 +0200
Subject: [PATCH 06/15] Show label with both S+ and S-

---
 .../src/oonipipeline/analysis/detector.py     | 122 +++++++++++-------
 1 file changed, 74 insertions(+), 48 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index a09c562c..f3504730 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -645,50 +645,27 @@ def make_label(df, field, label, color):
             )
         )
 
-    def make_nearest_hover(df, value_vars, colors, labels, y_title, legend_title):
+    def make_nearest_hover(df, field, label, color, y_title, legend_title):
         """
-        Builds an invisible hit-target layer plus a visible highlight dot per
-        series, using a melted long-form copy so the "nearest" selection
-        matches in true 2D (ts, value) space — hovering picks whichever
-        series is visually closest to the cursor rather than just the
-        closest timestamp. The same color scale drives a legend labeling
-        each line.
+        Builds an invisible hit-target layer plus a visible highlight dot
+        for a single series. Uses a plain x-only "nearest" selection (cheap:
+        a sorted bisect) rather than a 2D Voronoi nearest selection, which
+        is what made panning/zooming sluggish.
         """
-        df_melt = df.melt(
-            id_vars=["ts"],
-            value_vars=value_vars,
-            var_name="series",
-            value_name="value",
-        )
-        df_melt["series_label"] = df_melt["series"].map(labels)
-
         nearest = alt.selection_single(
-            nearest=True,
-            on="mouseover",
-            fields=["ts", "series"],
-            empty="none",
-            name=f"nearest_{'_'.join(value_vars)}",
+            nearest=True, on="mouseover", fields=["ts"], empty="none", name=f"nearest_{field}"
         )
-        melt_base = alt.Chart(df_melt).encode(
+        hover_base = alt.Chart(df).encode(
             x=alt.X("ts:T", axis=x_axis),
-            y=alt.Y("value:Q", title=y_title),
-            color=alt.Color(
-                "series_label:N",
-                scale=alt.Scale(
-                    domain=[labels[v] for v in value_vars],
-                    range=[colors[v] for v in value_vars],
-                ),
-                legend=alt.Legend(title=legend_title),
-            ),
+            y=alt.Y(f"{field}:Q", title=y_title),
         )
         selectors = (
-            melt_base.mark_point()
+            hover_base.mark_point()
             .encode(
                 opacity=alt.value(0),
                 tooltip=[
                     alt.Tooltip("ts:T", format=ts_tooltip_fmt),
-                    alt.Tooltip("series_label:N", title="series"),
-                    alt.Tooltip("value:Q"),
+                    alt.Tooltip(f"{field}:Q", title=label),
                 ],
             )
             .add_selection(nearest)
@@ -696,19 +673,35 @@ def make_nearest_hover(df, value_vars, colors, labels, y_title, legend_title):
         hover_rule = base.mark_rule(color="gray").encode(
             opacity=alt.condition(nearest, alt.value(0.3), alt.value(0))
         )
-        highlight_points = melt_base.mark_point(filled=True, size=80).encode(
-            opacity=alt.condition(nearest, alt.value(1), alt.value(0))
+        highlight_point = hover_base.mark_point(
+            color=color, filled=True, size=80
+        ).encode(opacity=alt.condition(nearest, alt.value(1), alt.value(0)))
+        return hover_rule + highlight_point + selectors
+
+    def make_legend_swatch(labels, colors, title):
+        """A zero-opacity mark whose sole purpose is to render a fixed-domain
+        color legend, since the actual lines it labels use static (not
+        data-driven) mark colors and so don't produce one on their own."""
+        return (
+            alt.Chart(pd.DataFrame({"label": labels}))
+            .mark_point(filled=True, opacity=0)
+            .encode(
+                color=alt.Color(
+                    "label:N",
+                    scale=alt.Scale(domain=labels, range=colors),
+                    legend=alt.Legend(title=title),
+                )
+            )
         )
-        return hover_rule + highlight_points + selectors
 
     obs_line = base.mark_line(color="steelblue", opacity=0.5).encode(
         y=alt.Y("obs_value:Q", title="value"),
     )
     obs_hover = make_nearest_hover(
         df_steps,
-        ["obs_value"],
-        {"obs_value": "steelblue"},
-        {"obs_value": "observed"},
+        "obs_value",
+        "observed",
+        "steelblue",
         y_title="value",
         legend_title="Value",
     )
@@ -728,18 +721,47 @@ def make_nearest_hover(df, value_vars, colors, labels, y_title, legend_title):
         )
     )
     obs_label = make_label(df_last, "obs_value", "observed", "steelblue")
-    value_group = alt.layer(obs_line, obs_hover, cp_points, obs_label)
+    obs_legend = make_legend_swatch(["observed"], ["steelblue"], "Value")
+    value_group = alt.layer(obs_line, obs_hover, cp_points, obs_label, obs_legend)
 
-    s_pos_line = base.mark_line(color="red").encode(y=alt.Y("s_pos:Q"))
+    s_pos_line = base.mark_line(color="red").encode(
+        y=alt.Y("s_pos:Q", title="CUSUM statistic")
+    )
     s_neg_line = base.mark_line(color="orange").encode(y=alt.Y("s_neg:Q"))
-    cusum_hover = make_nearest_hover(
-        df_steps,
-        ["s_pos", "s_neg", "h"],
-        {"s_pos": "red", "s_neg": "orange", "h": "green"},
-        {"s_pos": "S+", "s_neg": "S−", "h": "threshold (h)"},
-        y_title="CUSUM statistic",
-        legend_title="CUSUM",
+
+    # Unconditionally show both S+ and S- in one tooltip (rather than trying
+    # to guess which line the cursor is closer to), using a plain x-only
+    # "nearest" selection — cheap, unlike a 2D Voronoi nearest selection.
+    cusum_nearest = alt.selection_single(
+        nearest=True, on="mouseover", fields=["ts"], empty="none", name="nearest_cusum"
     )
+    cusum_selectors = (
+        base.mark_point()
+        .encode(
+            opacity=alt.value(0),
+            tooltip=[
+                alt.Tooltip("ts:T", format=ts_tooltip_fmt),
+                alt.Tooltip("s_pos:Q", title="🔴 S+"),
+                alt.Tooltip("s_neg:Q", title="🟠 S−"),
+            ],
+        )
+        .add_selection(cusum_nearest)
+    )
+    cusum_hover_rule = base.mark_rule(color="gray").encode(
+        opacity=alt.condition(cusum_nearest, alt.value(0.3), alt.value(0))
+    )
+    s_pos_highlight = base.mark_point(color="red", filled=True, size=80).encode(
+        y=alt.Y("s_pos:Q"),
+        opacity=alt.condition(cusum_nearest, alt.value(1), alt.value(0)),
+    )
+    s_neg_highlight = base.mark_point(color="orange", filled=True, size=80).encode(
+        y=alt.Y("s_neg:Q"),
+        opacity=alt.condition(cusum_nearest, alt.value(1), alt.value(0)),
+    )
+    cusum_hover = (
+        cusum_hover_rule + s_pos_highlight + s_neg_highlight + cusum_selectors
+    )
+
     threshold = (
         alt.Chart(df_steps).mark_rule(color="green", strokeDash=[4, 4]).encode(y="h:Q")
     )
@@ -751,6 +773,9 @@ def make_nearest_hover(df, value_vars, colors, labels, y_title, legend_title):
         .mark_text(align="left", dx=5, fontSize=11, color="green")
         .encode(x="ts:T", y="h:Q", text=alt.value("threshold (h)"))
     )
+    cusum_legend = make_legend_swatch(
+        ["S+", "S−", "threshold (h)"], ["red", "orange", "green"], "CUSUM"
+    )
     cusum_group = alt.layer(
         s_pos_line,
         s_neg_line,
@@ -759,6 +784,7 @@ def make_nearest_hover(df, value_vars, colors, labels, y_title, legend_title):
         s_pos_label,
         s_neg_label,
         threshold_label,
+        cusum_legend,
     )
 
     chart = (

From 3514a5b73b9b8581e87437dd51b581c4c9f62558 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Fri, 7 Aug 2026 11:37:59 +0200
Subject: [PATCH 07/15] Add debugging dataframe mode; simplify chart code

---
 .../src/oonipipeline/analysis/detector.py     | 86 ++++++-------------
 .../src/oonipipeline/events_panel/panel.py    | 12 +++
 2 files changed, 40 insertions(+), 58 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index f3504730..eef63bc0 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -637,7 +637,7 @@ def make_cusums_chart(steps: List[CusumStep], block_type: str):
     def make_label(df, field, label, color):
         return (
             alt.Chart(df)
-            .mark_text(align="left", dx=5, fontSize=11, color=color)
+            .mark_text(align="right", dx=-5, fontSize=11, color=color)
             .encode(
                 x="ts:T",
                 y=alt.Y(f"{field}:Q"),
@@ -645,39 +645,6 @@ def make_label(df, field, label, color):
             )
         )
 
-    def make_nearest_hover(df, field, label, color, y_title, legend_title):
-        """
-        Builds an invisible hit-target layer plus a visible highlight dot
-        for a single series. Uses a plain x-only "nearest" selection (cheap:
-        a sorted bisect) rather than a 2D Voronoi nearest selection, which
-        is what made panning/zooming sluggish.
-        """
-        nearest = alt.selection_single(
-            nearest=True, on="mouseover", fields=["ts"], empty="none", name=f"nearest_{field}"
-        )
-        hover_base = alt.Chart(df).encode(
-            x=alt.X("ts:T", axis=x_axis),
-            y=alt.Y(f"{field}:Q", title=y_title),
-        )
-        selectors = (
-            hover_base.mark_point()
-            .encode(
-                opacity=alt.value(0),
-                tooltip=[
-                    alt.Tooltip("ts:T", format=ts_tooltip_fmt),
-                    alt.Tooltip(f"{field}:Q", title=label),
-                ],
-            )
-            .add_selection(nearest)
-        )
-        hover_rule = base.mark_rule(color="gray").encode(
-            opacity=alt.condition(nearest, alt.value(0.3), alt.value(0))
-        )
-        highlight_point = hover_base.mark_point(
-            color=color, filled=True, size=80
-        ).encode(opacity=alt.condition(nearest, alt.value(1), alt.value(0)))
-        return hover_rule + highlight_point + selectors
-
     def make_legend_swatch(labels, colors, title):
         """A zero-opacity mark whose sole purpose is to render a fixed-domain
         color legend, since the actual lines it labels use static (not
@@ -697,14 +664,6 @@ def make_legend_swatch(labels, colors, title):
     obs_line = base.mark_line(color="steelblue", opacity=0.5).encode(
         y=alt.Y("obs_value:Q", title="value"),
     )
-    obs_hover = make_nearest_hover(
-        df_steps,
-        "obs_value",
-        "observed",
-        "steelblue",
-        y_title="value",
-        legend_title="Value",
-    )
     cp_points = (
         alt.Chart(df_steps[df_steps["is_changepoint"]])
         .mark_point(color="black", size=100, shape="diamond")
@@ -720,46 +679,56 @@ def make_legend_swatch(labels, colors, title):
             ],
         )
     )
-    obs_label = make_label(df_last, "obs_value", "observed", "steelblue")
+    obs_last_value = df_last["obs_value"].iloc[0]
+    obs_label_text = (
+        f"observed: {obs_last_value:.2f}" if pd.notna(obs_last_value) else "observed: n/a"
+    )
+    obs_label = make_label(df_last, "obs_value", obs_label_text, "steelblue")
     obs_legend = make_legend_swatch(["observed"], ["steelblue"], "Value")
-    value_group = alt.layer(obs_line, obs_hover, cp_points, obs_label, obs_legend)
 
     s_pos_line = base.mark_line(color="red").encode(
         y=alt.Y("s_pos:Q", title="CUSUM statistic")
     )
     s_neg_line = base.mark_line(color="orange").encode(y=alt.Y("s_neg:Q"))
 
-    # Unconditionally show both S+ and S- in one tooltip (rather than trying
-    # to guess which line the cursor is closer to), using a plain x-only
+    # One tooltip covering all three series at once (rather than trying to
+    # guess which line the cursor is closer to), using a plain x-only
     # "nearest" selection — cheap, unlike a 2D Voronoi nearest selection.
-    cusum_nearest = alt.selection_single(
-        nearest=True, on="mouseover", fields=["ts"], empty="none", name="nearest_cusum"
+    nearest = alt.selection_single(
+        nearest=True, on="mouseover", fields=["ts"], empty="none", name="nearest"
     )
-    cusum_selectors = (
+    selectors = (
         base.mark_point()
         .encode(
             opacity=alt.value(0),
             tooltip=[
                 alt.Tooltip("ts:T", format=ts_tooltip_fmt),
+                alt.Tooltip("obs_value:Q", title="🔵 observed"),
                 alt.Tooltip("s_pos:Q", title="🔴 S+"),
                 alt.Tooltip("s_neg:Q", title="🟠 S−"),
             ],
         )
-        .add_selection(cusum_nearest)
+        .add_selection(nearest)
+    )
+    hover_rule = base.mark_rule(color="gray").encode(
+        opacity=alt.condition(nearest, alt.value(0.3), alt.value(0))
     )
-    cusum_hover_rule = base.mark_rule(color="gray").encode(
-        opacity=alt.condition(cusum_nearest, alt.value(0.3), alt.value(0))
+    obs_highlight = base.mark_point(color="steelblue", filled=True, size=80).encode(
+        y=alt.Y("obs_value:Q"),
+        opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
     )
     s_pos_highlight = base.mark_point(color="red", filled=True, size=80).encode(
         y=alt.Y("s_pos:Q"),
-        opacity=alt.condition(cusum_nearest, alt.value(1), alt.value(0)),
+        opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
     )
     s_neg_highlight = base.mark_point(color="orange", filled=True, size=80).encode(
         y=alt.Y("s_neg:Q"),
-        opacity=alt.condition(cusum_nearest, alt.value(1), alt.value(0)),
+        opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
     )
-    cusum_hover = (
-        cusum_hover_rule + s_pos_highlight + s_neg_highlight + cusum_selectors
+    hover = hover_rule + selectors
+
+    value_group = alt.layer(
+        obs_line, obs_highlight, cp_points, obs_label, obs_legend
     )
 
     threshold = (
@@ -779,7 +748,8 @@ def make_legend_swatch(labels, colors, title):
     cusum_group = alt.layer(
         s_pos_line,
         s_neg_line,
-        cusum_hover,
+        s_pos_highlight,
+        s_neg_highlight,
         threshold,
         s_pos_label,
         s_neg_label,
@@ -788,7 +758,7 @@ def make_legend_swatch(labels, colors, title):
     )
 
     chart = (
-        alt.layer(state_bands, value_group, cusum_group)
+        alt.layer(state_bands, value_group, cusum_group, hover)
         .resolve_scale(y="independent", color="independent")
         .resolve_legend(color="independent")
         .properties(
diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index 712b838d..52c2da39 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -104,6 +104,15 @@ def detector_panel():
         st.warning(f"No cusum steps found for ASN {selected_asn}")
         return
 
+    block_steps = [s for s in chart_steps if s["block_type"] == block_type]
+    if all(s["obs_value"] is None or s["obs_value"] != s["obs_value"] for s in block_steps):
+        st.info(
+            f"No **{block_type}** measurements were observed for this ASN in the "
+            "selected window (the underlying weight/count was zero every hour), so "
+            "the observed-value line has nothing to plot. The CUSUM statistics "
+            "below still reflect the detector's last known state."
+        )
+
     chart = make_cusums_chart(chart_steps, block_type)
     st.altair_chart(chart)
 
@@ -122,5 +131,8 @@ def detector_panel():
         if st.checkbox("Show Vega-Lite spec", key="debug_show_spec"):
             st.json(chart.to_dict())
 
+        if st.checkbox("Show cusum data as dataframe", key="debug_show_cusum_df"):
+            st.dataframe(pd.DataFrame(block_steps))
+
 
 detector_panel()

From 04cc7058f3ed710634bb1c23dce02b07c79c7e37 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Fri, 7 Aug 2026 13:58:01 +0200
Subject: [PATCH 08/15] Add all block_type charts into the same altair chart

---
 .../src/oonipipeline/analysis/detector.py     | 108 +++++++++++++++---
 .../src/oonipipeline/events_panel/panel.py    |  76 ++++++++----
 2 files changed, 144 insertions(+), 40 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index eef63bc0..d06b6759 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -580,12 +580,37 @@ def run_detector_for(
 def plot(steps: List[CusumStep], block_type: str):
     make_cusums_chart(steps, block_type).show()
 
-def make_cusums_chart(steps: List[CusumStep], block_type: str):
+def make_cusums_chart(
+    steps: List[CusumStep],
+    block_type: str,
+    zoom=None,
+    show_legend: bool = True,
+    show_x_axis: bool = True,
+):
+    """
+    zoom: an optional shared alt.selection_interval(bind="scales") to reuse
+    across multiple calls (see make_cusums_chart_grid) so pan/zoom on one
+    chart's time axis applies to all of them. When omitted, a private one is
+    created so this function still works as a standalone chart.
+
+    show_legend: when False, suppresses this chart's own State/Value/CUSUM
+    legends — used when stacking several of these charts so only one copy
+    of each (identically-scaled) legend is shown for the whole stack.
+
+    show_x_axis: when False, hides the time-axis tick labels/ticks (grid
+    lines stay) — used when stacking several of these charts so only the
+    bottom-most one shows the shared time axis.
+    """
     import altair as alt
     import pandas as pd
 
     STATE_COLORS = {"ok": "#d4edda", "blk": "#f8d7da", "unk": "#fff3cd"}
-    x_axis = alt.Axis(format="%b %d, %H:%M")
+    x_axis = alt.Axis(
+        format="%b %d, %H:%M",
+        title=None,
+        labels=show_x_axis,
+        ticks=show_x_axis,
+    )
     ts_tooltip_fmt = "%b %d, %H:%M"
 
     df_steps = pd.DataFrame([s for s in steps if s["block_type"] == block_type])
@@ -622,7 +647,7 @@ def make_cusums_chart(steps: List[CusumStep], block_type: str):
                         STATE_COLORS["unk"],
                     ],
                 ),
-                legend=alt.Legend(title="State"),
+                legend=alt.Legend(title="State") if show_legend else None,
             ),
             tooltip=[
                 "current_state:N",
@@ -727,9 +752,10 @@ def make_legend_swatch(labels, colors, title):
     )
     hover = hover_rule + selectors
 
-    value_group = alt.layer(
-        obs_line, obs_highlight, cp_points, obs_label, obs_legend
-    )
+    value_group_layers = [obs_line, obs_highlight, cp_points, obs_label]
+    if show_legend:
+        value_group_layers.append(obs_legend)
+    value_group = alt.layer(*value_group_layers)
 
     threshold = (
         alt.Chart(df_steps).mark_rule(color="green", strokeDash=[4, 4]).encode(y="h:Q")
@@ -742,10 +768,7 @@ def make_legend_swatch(labels, colors, title):
         .mark_text(align="left", dx=5, fontSize=11, color="green")
         .encode(x="ts:T", y="h:Q", text=alt.value("threshold (h)"))
     )
-    cusum_legend = make_legend_swatch(
-        ["S+", "S−", "threshold (h)"], ["red", "orange", "green"], "CUSUM"
-    )
-    cusum_group = alt.layer(
+    cusum_group_layers = [
         s_pos_line,
         s_neg_line,
         s_pos_highlight,
@@ -754,8 +777,17 @@ def make_legend_swatch(labels, colors, title):
         s_pos_label,
         s_neg_label,
         threshold_label,
-        cusum_legend,
-    )
+    ]
+    if show_legend:
+        cusum_group_layers.append(
+            make_legend_swatch(
+                ["S+", "S−", "threshold (h)"], ["red", "orange", "green"], "CUSUM"
+            )
+        )
+    cusum_group = alt.layer(*cusum_group_layers)
+
+    if zoom is None:
+        zoom = alt.selection_interval(bind="scales", encodings=["x"])
 
     chart = (
         alt.layer(state_bands, value_group, cusum_group, hover)
@@ -763,13 +795,59 @@ def make_legend_swatch(labels, colors, title):
         .resolve_legend(color="independent")
         .properties(
             width=900,
-            height=400,
-            title=f"CUSUM Detector: {block_type}",
+            height=100,
+            title=alt.TitleParams(
+                text=block_type,
+                fontSize=11,
+                fontWeight="normal",
+                color="gray",
+                anchor="start",
+                dy=-4,
+                offset=2,
+            ),
         )
-        .interactive()
+        .add_selection(zoom)
     )
     return chart
 
+
+def make_cusums_chart_grid(steps: List[CusumStep], block_types: List[str]):
+    """
+    One row per block type, stacked vertically in a single chart, so all of
+    an ASN's CUSUM series can be compared at a glance. The State/Value/CUSUM
+    legends (identical across rows) are only shown once, on the last row,
+    and every row shares one time-axis pan/zoom selection.
+    """
+    import altair as alt
+
+    present_block_types = [
+        block_type
+        for block_type in block_types
+        if any(s["block_type"] == block_type for s in steps)
+    ]
+    if not present_block_types:
+        return None
+
+    zoom = alt.selection_interval(bind="scales", encodings=["x"])
+    last_idx = len(present_block_types) - 1
+    charts = [
+        make_cusums_chart(
+            steps,
+            block_type,
+            zoom=zoom,
+            show_legend=(i == last_idx),
+            show_x_axis=(i == last_idx),
+        )
+        for i, block_type in enumerate(present_block_types)
+    ]
+    return (
+        alt.vconcat(*charts, spacing=0)
+        .resolve_scale(x="shared")
+        .properties(title="CUSUM Detector", padding=0)
+        .configure_view(strokeWidth=0)
+    )
+
+
 def notify_slack(
     changepoints: list[Changepoint],
     slack_webhook: str,
diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index 52c2da39..6a31ecd4 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -1,6 +1,10 @@
 from collections import defaultdict
 import streamlit as st
-from oonipipeline.analysis.detector import make_cusums_chart, run_detector_for, ANALYSIS_COLS
+from oonipipeline.analysis.detector import (
+    make_cusums_chart_grid,
+    run_detector_for,
+    ANALYSIS_COLS,
+)
 from datetime import datetime, timezone, timedelta
 import logging
 import pandas as pd
@@ -44,7 +48,11 @@ def detector_panel():
         domain = c2.text_input("**domain**", "x.com")
         gap_halflife = c2.number_input("**Gap half life**", value=48.0)
 
-        warmup = st.checkbox("**Warmup**", True)
+        warmup = st.checkbox(
+            "**Warmup**",
+            False,
+            help="When enabled, no changepoints will be returned.",
+        )
         submitted = st.form_submit_button("Run detector")
 
     # Only recompute on submit; store in session_state so results survive
@@ -83,19 +91,30 @@ def detector_panel():
     for step in cusum_steps:
         asns[step["probe_asn"]] += 1
 
+    asns_with_changepoints = {cp["probe_asn"] for cp in changepoints}
+
     c1, c2 = st.columns(2)
     c1.write(f"Changepoints: **{len(changepoints)}**")
     c2.write(f"Cusum steps: **{len(cusum_steps)}**")
 
-    c1, c2 = st.columns(2)
-    block_type = c1.selectbox(
-        "Block type", [c[0] for c in ANALYSIS_COLS], key="block_type_select"
-    )
+    if changepoints:
+        st.write("**Changepoints**")
+        cp_df = pd.DataFrame(changepoints)
+        cp_df = cp_df.sort_values("ts", ascending=False).reset_index(drop=True)
+        display_cols = [
+            c
+            for c in ["ts", "probe_asn", "domain", "block_type", "change_dir", "s_pos", "s_neg", "h"]
+            if c in cp_df.columns
+        ]
+        st.dataframe(cp_df[display_cols], hide_index=True)
 
     asn_list = list(asns.keys())
     asn_list.sort(key=lambda k: asns[k], reverse=True)
-    selected_asn = c2.selectbox(
-        "ASN", asn_list, format_func=lambda k: f"{k} ({asns[k]})", key="asn_select"
+    selected_asn = st.selectbox(
+        "ASN",
+        asn_list,
+        format_func=lambda k: f"{'❗️' if k in asns_with_changepoints else ''}{k} ({asns[k]})",
+        key="asn_select",
     )
 
     chart_steps = [s for s in cusum_steps if s["probe_asn"] == selected_asn]
@@ -104,24 +123,25 @@ def detector_panel():
         st.warning(f"No cusum steps found for ASN {selected_asn}")
         return
 
-    block_steps = [s for s in chart_steps if s["block_type"] == block_type]
-    if all(s["obs_value"] is None or s["obs_value"] != s["obs_value"] for s in block_steps):
-        st.info(
-            f"No **{block_type}** measurements were observed for this ASN in the "
-            "selected window (the underlying weight/count was zero every hour), so "
-            "the observed-value line has nothing to plot. The CUSUM statistics "
-            "below still reflect the detector's last known state."
-        )
-
-    chart = make_cusums_chart(chart_steps, block_type)
+    block_types = [c[0] for c in ANALYSIS_COLS]
+    for block_type in block_types:
+        block_steps = [s for s in chart_steps if s["block_type"] == block_type]
+        if block_steps and all(
+            s["obs_value"] is None or s["obs_value"] != s["obs_value"] for s in block_steps
+        ):
+            st.info(
+                f"No **{block_type}** measurements were observed for this ASN in the "
+                "selected window (the underlying weight/count was zero every hour), so "
+                "the observed-value line has nothing to plot for that row. The CUSUM "
+                "statistics still reflect the detector's last known state."
+            )
+
+    chart = make_cusums_chart_grid(chart_steps, block_types)
+    if chart is None:
+        st.warning(f"No cusum steps found for ASN {selected_asn}")
+        return
     st.altair_chart(chart)
 
-    if asns:
-        df = pd.DataFrame({"ASN": list(asns.keys()), "total": list(asns.values())})
-        df = df.sort_values("total", ascending=False).reset_index(drop=True)
-        df["ASN"] = df["ASN"].astype(str)
-        st.dataframe(df, hide_index=True)
-
     with st.expander("🔧 Debug"):
         if st.checkbox("Render chart as PNG", key="debug_render_png"):
             spec = chart.to_dict()
@@ -132,7 +152,13 @@ def detector_panel():
             st.json(chart.to_dict())
 
         if st.checkbox("Show cusum data as dataframe", key="debug_show_cusum_df"):
-            st.dataframe(pd.DataFrame(block_steps))
+            st.dataframe(pd.DataFrame(chart_steps))
+
+    if asns:
+        df = pd.DataFrame({"ASN": list(asns.keys()), "total": list(asns.values())})
+        df = df.sort_values("total", ascending=False).reset_index(drop=True)
+        df["ASN"] = df["ASN"].astype(str)
+        st.dataframe(df, hide_index=True)
 
 
 detector_panel()

From 24c63f8567a27e4bfd2ae000b8dc1f5b58041172 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Fri, 7 Aug 2026 15:42:13 +0200
Subject: [PATCH 09/15] Run detector panel with query arguments; add link to
 detector panel in slack messages

---
 .../src/oonipipeline/analysis/detector.py     | 21 ++++-
 .../src/oonipipeline/events_panel/panel.py    | 77 ++++++++++++++++---
 2 files changed, 86 insertions(+), 12 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index d06b6759..71da4ae2 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -511,6 +511,7 @@ def run_detector(
     trace: bool = False,
     slack_webhook: str | None = None,
     explorer_base_url: str = "https://explorer.ooni.org/",
+    detector_panel_base_url: str = "https://detector-panel.prod.ooni.io/",
 ) -> Tuple[List[Changepoint], List[LastCusum], List[CusumStep]]:
     db = ClickhouseClient.from_url(clickhouse_url)
     domains = get_domain_list(db)
@@ -536,7 +537,15 @@ def run_detector(
     update_tables(db, updated_cusums, changepoints)
 
     if slack_webhook is not None:
-        notify_slack(changepoints, slack_webhook, explorer_base_url)
+        notify_slack(
+            changepoints,
+            slack_webhook,
+            explorer_base_url,
+            detector_panel_base_url,
+            edd=edd,
+            gap_halflife=gap_halflife,
+            warmup=warmup,
+        )
 
     return changepoints, updated_cusums, steps
 
@@ -810,7 +819,6 @@ def make_legend_swatch(labels, colors, title):
     )
     return chart
 
-
 def make_cusums_chart_grid(steps: List[CusumStep], block_types: List[str]):
     """
     One row per block type, stacked vertically in a single chart, so all of
@@ -852,6 +860,10 @@ def notify_slack(
     changepoints: list[Changepoint],
     slack_webhook: str,
     explorer_base_url: str = "https://explorer.ooni.org/",
+    detector_panel_base_url: str = "https://detector-panel.prod.ooni.io/",
+    edd: int = 10,
+    gap_halflife: float = 48.0,
+    warmup: bool = False,
 ):
     """
     Sends a message to slack with a list of all changepoints that were detected
@@ -877,10 +889,13 @@ def dir_to_str(dir: int) -> str:
         explorer = get_explorer_url(cp, explorer_base_url)
         # Alerts panel not yet deployed to prod, we use the test one for now
         alerts = get_alert_page_url(cp, "https://explorer.test.ooni.org/")
+        panel = get_detector_panel_url(
+            cp, detector_panel_base_url, edd=edd, gap_halflife=gap_halflife, warmup=warmup
+        )
         message += (
             f"• :flag-{cp['probe_cc'].lower()}: [{cp['probe_cc']}/AS{cp['probe_asn']}] "
             f"*{cp['domain']}* {dir_to_str(cp['change_dir'])} - `{cp['block_type']}` "
-            f"| <{explorer}|explorer> | <{alerts}|alerts>\n"
+            f"| <{explorer}|explorer> | <{alerts}|alerts> | <{panel}|detector panel>\n"
         )
 
         # Send messages in 10 entries batches to avoid max message size limit
diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index 6a31ecd4..232b59e6 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -19,6 +19,36 @@ def run_detector_cached(*args, **kwargs):
 
 st.set_page_config(layout="wide")
 
+# Query params that can prefill the form, e.g.
+# ?probe_cc=VE&domain=x.com&start_time=2024-01-01T00:00:00&end_time=2024-01-15T00:00:00&edd=10&gap_halflife=48&warmup=false
+# When every one of these is present (and parses cleanly), the form auto-runs
+# on first load instead of waiting for a manual "Run detector" click.
+QUERY_FIELD_TO_WIDGET_KEY = {
+    "probe_cc": "probe_cc_input",
+    "domain": "domain_input",
+    "start_time": "start_time_input",
+    "end_time": "end_time_input",
+    "edd": "edd_input",
+    "gap_halflife": "gap_halflife_input",
+    "warmup": "warmup_input",
+}
+
+
+def _parse_query_value(field: str, raw: str):
+    if field in ("start_time", "end_time"):
+        dt = datetime.fromisoformat(raw)
+        if dt.tzinfo is None:
+            dt = dt.replace(tzinfo=timezone.utc)
+        return dt
+    if field == "edd":
+        return int(raw)
+    if field == "gap_halflife":
+        return float(raw)
+    if field == "warmup":
+        return raw.strip().lower() in ("1", "true", "yes")
+    return raw
+
+
 def detector_panel():
     st.write(
         """
@@ -31,6 +61,23 @@ def detector_panel():
 
     now = datetime.now(timezone.utc)
 
+    # Prefill the form from URL query params on first load, and remember
+    # whether every field was present so we can auto-run below.
+    if "query_params_applied" not in st.session_state:
+        st.session_state["query_params_applied"] = True
+        parsed_ok = set()
+        for field, widget_key in QUERY_FIELD_TO_WIDGET_KEY.items():
+            raw = st.query_params.get(field)
+            if raw is not None:
+                try:
+                    st.session_state[widget_key] = _parse_query_value(field, raw)
+                    parsed_ok.add(field)
+                except (ValueError, TypeError):
+                    pass
+        st.session_state["auto_submit_pending"] = parsed_ok == set(
+            QUERY_FIELD_TO_WIDGET_KEY
+        )
+
     clickhouse_url = st.sidebar.text_input(
         "**Clickhouse url**", "clickhouse://localhost:9000/ooni"
     )
@@ -39,25 +86,37 @@ def detector_panel():
         c1, c2 = st.columns(2)
 
         # column 1
-        start_time = c1.datetime_input("**Start date**", now - timedelta(days=30))
-        probe_cc = c1.text_input("**Country code (two chars)**", "VE")
-        edd = c1.number_input("**Estimated Detection Delay (EDD)**", value=10)
+        start_time = c1.datetime_input(
+            "**Start date**", now - timedelta(days=30), key="start_time_input"
+        )
+        probe_cc = c1.text_input(
+            "**Country code (two chars)**", "VE", key="probe_cc_input"
+        )
+        edd = c1.number_input(
+            "**Estimated Detection Delay (EDD)**", value=10, key="edd_input"
+        )
 
         # column2
-        end_time = c2.datetime_input("**End date**", now)
-        domain = c2.text_input("**domain**", "x.com")
-        gap_halflife = c2.number_input("**Gap half life**", value=48.0)
+        end_time = c2.datetime_input("**End date**", now, key="end_time_input")
+        domain = c2.text_input("**domain**", "x.com", key="domain_input")
+        gap_halflife = c2.number_input(
+            "**Gap half life**", value=48.0, key="gap_halflife_input"
+        )
 
         warmup = st.checkbox(
             "**Warmup**",
             False,
             help="When enabled, no changepoints will be returned.",
+            key="warmup_input",
         )
         submitted = st.form_submit_button("Run detector")
 
-    # Only recompute on submit; store in session_state so results survive
-    # reruns triggered by the selectboxes below.
-    if submitted:
+    auto_submit = st.session_state.pop("auto_submit_pending", False)
+
+    # Only recompute on submit (or on a fully-specified first load via query
+    # params); store in session_state so results survive reruns triggered by
+    # the selectboxes below.
+    if submitted or auto_submit:
         # Drop any cusum-related state left over from a previous submission
         for key in ("changepoints", "cusum_steps", "block_type_select", "asn_select"):
             st.session_state.pop(key, None)

From 5cb97c4b1db323b210201a65af418faa361e78f8 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Fri, 7 Aug 2026 16:05:47 +0200
Subject: [PATCH 10/15] Add url parameters to event detector panel

---
 .../src/oonipipeline/analysis/detector.py     | 34 +++++++++++++++++++
 .../src/oonipipeline/events_panel/panel.py    | 25 ++++++++++++--
 2 files changed, 57 insertions(+), 2 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index 71da4ae2..652dd558 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -953,3 +953,37 @@ def to_s(dt: datetime):
     }
     url = f"{base_url}/chart/alerts?{urlencode(params)}"
     return url
+
+
+def get_detector_panel_url(
+    changepoint: Changepoint,
+    base_url: str = "https://detector-panel.prod.ooni.io/",
+    edd: int = 10,
+    gap_halflife: float = 48.0,
+    warmup: bool = False,
+) -> str:
+    """
+    Builds a link to the events-panel Streamlit app (see
+    oonipipeline.events_panel.panel), prefilled via query params so the app
+    auto-runs the detector for this changepoint's country/domain and a
+    +-13/2 day window around it on first load — same window convention as
+    get_explorer_url/get_alert_page_url above.
+    """
+    start_time = changepoint["ts"] - timedelta(days=13)
+    end_time = changepoint["ts"] + timedelta(days=2)
+
+    def to_iso(dt: datetime) -> str:
+        return dt.strftime("%Y-%m-%dT%H:%M:%S")
+
+    params = {
+        "probe_cc": changepoint["probe_cc"],
+        "domain": changepoint["domain"],
+        "probe_asn": changepoint["probe_asn"],
+        "start_time": to_iso(start_time),
+        "end_time": to_iso(end_time),
+        "edd": edd,
+        "gap_halflife": gap_halflife,
+        "warmup": str(warmup).lower(),
+    }
+    url = f"{base_url}?{urlencode(params)}"
+    return url
diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index 232b59e6..2010f35f 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -20,9 +20,12 @@ def run_detector_cached(*args, **kwargs):
 st.set_page_config(layout="wide")
 
 # Query params that can prefill the form, e.g.
-# ?probe_cc=VE&domain=x.com&start_time=2024-01-01T00:00:00&end_time=2024-01-15T00:00:00&edd=10&gap_halflife=48&warmup=false
+# ?probe_cc=VE&domain=x.com&start_time=2024-01-01T00:00:00&end_time=2024-01-15T00:00:00&edd=10&gap_halflife=48&warmup=false&probe_asn=1234
 # When every one of these is present (and parses cleanly), the form auto-runs
 # on first load instead of waiting for a manual "Run detector" click.
+# probe_asn isn't a form field — it's applied afterwards to preselect the ASN
+# selectbox once results are in, since it's only known to be a valid choice
+# after the detector has actually run.
 QUERY_FIELD_TO_WIDGET_KEY = {
     "probe_cc": "probe_cc_input",
     "domain": "domain_input",
@@ -40,7 +43,7 @@ def _parse_query_value(field: str, raw: str):
         if dt.tzinfo is None:
             dt = dt.replace(tzinfo=timezone.utc)
         return dt
-    if field == "edd":
+    if field in ("edd", "probe_asn"):
         return int(raw)
     if field == "gap_halflife":
         return float(raw)
@@ -78,6 +81,15 @@ def detector_panel():
             QUERY_FIELD_TO_WIDGET_KEY
         )
 
+        raw_probe_asn = st.query_params.get("probe_asn")
+        if raw_probe_asn is not None:
+            try:
+                st.session_state["query_probe_asn"] = _parse_query_value(
+                    "probe_asn", raw_probe_asn
+                )
+            except (ValueError, TypeError):
+                pass
+
     clickhouse_url = st.sidebar.text_input(
         "**Clickhouse url**", "clickhouse://localhost:9000/ooni"
     )
@@ -169,6 +181,15 @@ def detector_panel():
 
     asn_list = list(asns.keys())
     asn_list.sort(key=lambda k: asns[k], reverse=True)
+
+    query_probe_asn = st.session_state.get("query_probe_asn")
+    if (
+        query_probe_asn is not None
+        and "asn_select" not in st.session_state
+        and query_probe_asn in asn_list
+    ):
+        st.session_state["asn_select"] = query_probe_asn
+
     selected_asn = st.selectbox(
         "ASN",
         asn_list,

From 6ab652b7cbf744676ee156fe099146e48b5d0707 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Fri, 7 Aug 2026 16:07:10 +0200
Subject: [PATCH 11/15] Summarize comment

---
 oonipipeline/src/oonipipeline/analysis/detector.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index 652dd558..4ac19130 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -963,11 +963,9 @@ def get_detector_panel_url(
     warmup: bool = False,
 ) -> str:
     """
-    Builds a link to the events-panel Streamlit app (see
+    Builds a link to the events-panel app (see
     oonipipeline.events_panel.panel), prefilled via query params so the app
-    auto-runs the detector for this changepoint's country/domain and a
-    +-13/2 day window around it on first load — same window convention as
-    get_explorer_url/get_alert_page_url above.
+    auto-runs the detector for this changepoint's metadata
     """
     start_time = changepoint["ts"] - timedelta(days=13)
     end_time = changepoint["ts"] + timedelta(days=2)

From d0fcf2be27427c3b93d110a03737bfcb1d3cd05d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Fri, 7 Aug 2026 16:26:40 +0200
Subject: [PATCH 12/15] Refactor make phighlights; simplify nan check

---
 .../src/oonipipeline/analysis/detector.py     | 21 ++++++++-----------
 .../src/oonipipeline/events_panel/panel.py    |  4 +---
 2 files changed, 10 insertions(+), 15 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index 4ac19130..d8933831 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -679,6 +679,12 @@ def make_label(df, field, label, color):
             )
         )
 
+    def make_highlight(field, color):
+        return base.mark_point(color=color, filled=True, size=80).encode(
+            y=alt.Y(f"{field}:Q"),
+            opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
+        )
+
     def make_legend_swatch(labels, colors, title):
         """A zero-opacity mark whose sole purpose is to render a fixed-domain
         color legend, since the actual lines it labels use static (not
@@ -747,18 +753,9 @@ def make_legend_swatch(labels, colors, title):
     hover_rule = base.mark_rule(color="gray").encode(
         opacity=alt.condition(nearest, alt.value(0.3), alt.value(0))
     )
-    obs_highlight = base.mark_point(color="steelblue", filled=True, size=80).encode(
-        y=alt.Y("obs_value:Q"),
-        opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
-    )
-    s_pos_highlight = base.mark_point(color="red", filled=True, size=80).encode(
-        y=alt.Y("s_pos:Q"),
-        opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
-    )
-    s_neg_highlight = base.mark_point(color="orange", filled=True, size=80).encode(
-        y=alt.Y("s_neg:Q"),
-        opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
-    )
+    obs_highlight = make_highlight("obs_value", "steelblue")
+    s_pos_highlight = make_highlight("s_pos", "red")
+    s_neg_highlight = make_highlight("s_neg", "orange")
     hover = hover_rule + selectors
 
     value_group_layers = [obs_line, obs_highlight, cp_points, obs_label]
diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index 2010f35f..b24d291b 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -206,9 +206,7 @@ def detector_panel():
     block_types = [c[0] for c in ANALYSIS_COLS]
     for block_type in block_types:
         block_steps = [s for s in chart_steps if s["block_type"] == block_type]
-        if block_steps and all(
-            s["obs_value"] is None or s["obs_value"] != s["obs_value"] for s in block_steps
-        ):
+        if block_steps and all(pd.isna(s["obs_value"]) for s in block_steps):
             st.info(
                 f"No **{block_type}** measurements were observed for this ASN in the "
                 "selected window (the underlying weight/count was zero every hour), so "

From 4304a3fe04ed5ea50be984a132ffe313d529d58e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Fri, 7 Aug 2026 16:51:26 +0200
Subject: [PATCH 13/15] optimize chart

---
 .../src/oonipipeline/analysis/detector.py     | 39 +++++++++++++------
 1 file changed, 28 insertions(+), 11 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index d8933831..5ff6662b 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -593,6 +593,7 @@ def make_cusums_chart(
     steps: List[CusumStep],
     block_type: str,
     zoom=None,
+    nearest=None,
     show_legend: bool = True,
     show_x_axis: bool = True,
 ):
@@ -602,6 +603,12 @@ def make_cusums_chart(
     chart's time axis applies to all of them. When omitted, a private one is
     created so this function still works as a standalone chart.
 
+    nearest: an optional shared alt.selection_single(nearest=True, ...) to
+    reuse across multiple calls (see make_cusums_chart_grid), so a single
+    mouseover listener drives the hover crosshair/highlights on every row
+    instead of one independent listener per row. When omitted, a private one
+    is created so this function still works as a standalone chart.
+
     show_legend: when False, suppresses this chart's own State/Value/CUSUM
     legends — used when stacking several of these charts so only one copy
     of each (identically-scaled) legend is shown for the whole stack.
@@ -668,6 +675,14 @@ def make_cusums_chart(
 
     base = alt.Chart(df_steps).encode(x=alt.X("ts:T", axis=x_axis))
 
+    # One tooltip covering all three series at once (rather than trying to
+    # guess which line the cursor is closer to), using a plain x-only
+    # "nearest" selection — cheap, unlike a 2D Voronoi nearest selection.
+    if nearest is None:
+        nearest = alt.selection_single(
+            nearest=True, on="mouseover", fields=["ts"], empty="none", name="nearest"
+        )
+
     def make_label(df, field, label, color):
         return (
             alt.Chart(df)
@@ -680,9 +695,13 @@ def make_label(df, field, label, color):
         )
 
     def make_highlight(field, color):
-        return base.mark_point(color=color, filled=True, size=80).encode(
-            y=alt.Y(f"{field}:Q"),
-            opacity=alt.condition(nearest, alt.value(1), alt.value(0)),
+        # transform_filter (rather than an opacity condition over the full
+        # dataset) means only the single matched point is ever rendered, so
+        # this stays O(1) instead of O(n) marks per row.
+        return (
+            base.transform_filter(nearest)
+            .mark_point(color=color, filled=True, size=80)
+            .encode(y=alt.Y(f"{field}:Q"))
         )
 
     def make_legend_swatch(labels, colors, title):
@@ -731,12 +750,6 @@ def make_legend_swatch(labels, colors, title):
     )
     s_neg_line = base.mark_line(color="orange").encode(y=alt.Y("s_neg:Q"))
 
-    # One tooltip covering all three series at once (rather than trying to
-    # guess which line the cursor is closer to), using a plain x-only
-    # "nearest" selection — cheap, unlike a 2D Voronoi nearest selection.
-    nearest = alt.selection_single(
-        nearest=True, on="mouseover", fields=["ts"], empty="none", name="nearest"
-    )
     selectors = (
         base.mark_point()
         .encode(
@@ -750,8 +763,8 @@ def make_legend_swatch(labels, colors, title):
         )
         .add_selection(nearest)
     )
-    hover_rule = base.mark_rule(color="gray").encode(
-        opacity=alt.condition(nearest, alt.value(0.3), alt.value(0))
+    hover_rule = (
+        base.transform_filter(nearest).mark_rule(color="gray", opacity=0.3)
     )
     obs_highlight = make_highlight("obs_value", "steelblue")
     s_pos_highlight = make_highlight("s_pos", "red")
@@ -834,12 +847,16 @@ def make_cusums_chart_grid(steps: List[CusumStep], block_types: List[str]):
         return None
 
     zoom = alt.selection_interval(bind="scales", encodings=["x"])
+    nearest = alt.selection_single(
+        nearest=True, on="mouseover", fields=["ts"], empty="none", name="nearest"
+    )
     last_idx = len(present_block_types) - 1
     charts = [
         make_cusums_chart(
             steps,
             block_type,
             zoom=zoom,
+            nearest=nearest,
             show_legend=(i == last_idx),
             show_x_axis=(i == last_idx),
         )

From 3864267b7dabe857f942716efc2a18e93e67b08e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Mon, 10 Aug 2026 11:01:07 +0200
Subject: [PATCH 14/15] Summarize docs

---
 .../src/oonipipeline/analysis/detector.py       | 11 +++++------
 .../src/oonipipeline/events_panel/panel.py      | 17 +++++------------
 2 files changed, 10 insertions(+), 18 deletions(-)

diff --git a/oonipipeline/src/oonipipeline/analysis/detector.py b/oonipipeline/src/oonipipeline/analysis/detector.py
index 5ff6662b..81389905 100644
--- a/oonipipeline/src/oonipipeline/analysis/detector.py
+++ b/oonipipeline/src/oonipipeline/analysis/detector.py
@@ -605,16 +605,15 @@ def make_cusums_chart(
 
     nearest: an optional shared alt.selection_single(nearest=True, ...) to
     reuse across multiple calls (see make_cusums_chart_grid), so a single
-    mouseover listener drives the hover crosshair/highlights on every row
-    instead of one independent listener per row. When omitted, a private one
-    is created so this function still works as a standalone chart.
+    mouseover listener drives the hover crosshair/highlights on every row.
+    When omitted, a private one is created
 
     show_legend: when False, suppresses this chart's own State/Value/CUSUM
-    legends — used when stacking several of these charts so only one copy
-    of each (identically-scaled) legend is shown for the whole stack.
+    legends. Used when stacking several of these charts so only one copy
+    of each legend is shown for the whole stack.
 
     show_x_axis: when False, hides the time-axis tick labels/ticks (grid
-    lines stay) — used when stacking several of these charts so only the
+    lines stay). Used when stacking several of these charts so only the
     bottom-most one shows the shared time axis.
     """
     import altair as alt
diff --git a/oonipipeline/src/oonipipeline/events_panel/panel.py b/oonipipeline/src/oonipipeline/events_panel/panel.py
index b24d291b..83c7f6f1 100644
--- a/oonipipeline/src/oonipipeline/events_panel/panel.py
+++ b/oonipipeline/src/oonipipeline/events_panel/panel.py
@@ -19,13 +19,8 @@ def run_detector_cached(*args, **kwargs):
 
 st.set_page_config(layout="wide")
 
-# Query params that can prefill the form, e.g.
-# ?probe_cc=VE&domain=x.com&start_time=2024-01-01T00:00:00&end_time=2024-01-15T00:00:00&edd=10&gap_halflife=48&warmup=false&probe_asn=1234
-# When every one of these is present (and parses cleanly), the form auto-runs
-# on first load instead of waiting for a manual "Run detector" click.
-# probe_asn isn't a form field — it's applied afterwards to preselect the ASN
-# selectbox once results are in, since it's only known to be a valid choice
-# after the detector has actually run.
+# When every one of these is present the form auto-runs
+# on first load
 QUERY_FIELD_TO_WIDGET_KEY = {
     "probe_cc": "probe_cc_input",
     "domain": "domain_input",
@@ -64,8 +59,7 @@ def detector_panel():
 
     now = datetime.now(timezone.utc)
 
-    # Prefill the form from URL query params on first load, and remember
-    # whether every field was present so we can auto-run below.
+    # Prefill the form from URL query params on first load
     if "query_params_applied" not in st.session_state:
         st.session_state["query_params_applied"] = True
         parsed_ok = set()
@@ -125,11 +119,10 @@ def detector_panel():
 
     auto_submit = st.session_state.pop("auto_submit_pending", False)
 
-    # Only recompute on submit (or on a fully-specified first load via query
-    # params); store in session_state so results survive reruns triggered by
+    # store in session_state so results survive reruns triggered by
     # the selectboxes below.
     if submitted or auto_submit:
-        # Drop any cusum-related state left over from a previous submission
+        # Drop any cusum-related state left over
         for key in ("changepoints", "cusum_steps", "block_type_select", "asn_select"):
             st.session_state.pop(key, None)
 

From 79917551144c8a965c8ae9e3d573dd80502ea549 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20D=C3=ADaz?= <ldiazn98@gmail.com>
Date: Mon, 10 Aug 2026 11:08:15 +0200
Subject: [PATCH 15/15] omit panel from code coverage; not useful to cover

---
 oonipipeline/pyproject.toml | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/oonipipeline/pyproject.toml b/oonipipeline/pyproject.toml
index 2e66f9c1..8fde5e99 100644
--- a/oonipipeline/pyproject.toml
+++ b/oonipipeline/pyproject.toml
@@ -82,6 +82,11 @@ test-cov = "pytest --cov=./ --cov-report=xml --cov-report=html --cov-report=term
 cov-report = ["coverage report"]
 cov = ["test-cov", "cov-report"]
 
+[tool.coverage.run]
+omit = [
+  "src/oonipipeline/events_panel/panel.py",
+]
+
 [tool.hatch.envs.analysis]
 template = "default"
 features = ["analysis"]