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Redo constraint violation indicators and legend on inample and predicted plots #2955

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Redo constraint violation indicators and legend on inample and predicted plots #2955

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89 changes: 86 additions & 3 deletions ax/analysis/plotly/arm_effects/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -65,9 +65,60 @@ def prepare_arm_effects_plot(
color="source",
# TODO: can we format this by callable or string template?
hover_data=_get_parameter_columns(df),
size="size_column",
size_max=10,
# avoid red because it will match the constraint violation indicator
color_discrete_sequence=px.colors.qualitative.Vivid,
)
dot_size = 8
# set all dots to size 8 in plots
fig.update_traces(marker={"line": {"width": 2}, "size": dot_size})

# Manually create each constraint violation indicator
# as a red outline around the dot, with alpha based on the
# probability of constraint violation.
for trace in fig.data:
# there is a trace per source, so get the rows of df
# pertaining to this trace
indices = df["source"] == trace.name
trace.marker.line.color = [
# raising the alpha to a power < 1 makes the colors more
# visible when there is a lower chance of constraint violation
f"rgba(255, 0, 0, {(alpha) ** .75})"
for alpha in df.loc[indices, "overall_probability_constraints_violated"]
]
# Create a separate trace for the legend, otherwise the legend
# will have the constraint violation indicator of the first arm
# in the source group
legend_trace = go.Scatter(
# (None, None) is a hack to get a legend item without
# appearing on the plot
x=[None],
y=[None],
mode="markers",
marker={
"size": dot_size,
"color": trace.marker.color,
},
name=trace.name,
)
fig.add_trace(legend_trace)
trace.showlegend = False

# Add an item to the legend for the constraint violation indicator
legend_trace = go.Scatter(
# (None, None) is a hack to get a legend item without
# appearing on the plot
x=[None],
y=[None],
mode="markers",
marker={
"size": dot_size,
"color": "white",
"line": {"width": 2, "color": "red"},
},
name="Constraint Violation",
)
fig.add_trace(legend_trace)

_add_style_to_effects_by_arm_plot(
fig=fig, df=df, metric_name=metric_name, outcome_constraints=outcome_constraints
)
Expand Down Expand Up @@ -100,6 +151,20 @@ def _add_style_to_effects_by_arm_plot(
y=df[df["arm_name"] == "status_quo"]["mean"].iloc[0],
line_width=1,
line_color="red",
showlegend=True,
name="Status Quo Mean",
)
# Add the status quo mean to the legend
fig.add_trace(
go.Scatter(
# (None, None) is a hack to get a legend item without
# appearing on the plot
x=[None],
y=[None],
mode="lines",
line={"color": "red", "width": 1},
name="Status Quo Mean",
)
)
for constraint in outcome_constraints:
if constraint.metric.name == metric_name:
Expand All @@ -110,10 +175,25 @@ def _add_style_to_effects_by_arm_plot(
line_color="red",
line_dash="dash",
)
# Add the constraint bound to the legend
fig.add_trace(
go.Scatter(
# (None, None) is a hack to get a legend item without
# appearing on the plot
x=[None],
y=[None],
mode="lines",
line={"color": "red", "width": 1, "dash": "dash"},
name="Constraint Bound",
)
)
fig.update_layout(
xaxis={
"tickangle": 45,
},
legend={
"title": None,
},
)


Expand Down Expand Up @@ -206,7 +286,10 @@ def get_predictions_by_arm(
"constraints_violated": format_constraint_violated_probabilities(
constraints_violated[i]
),
"size_column": 100 - probabilities_not_feasible[i] * 100,
# used for constraint violation indicator
"overall_probability_constraints_violated": round(
probabilities_not_feasible[i], ndigits=2
),
"parameters": format_parameters_for_effects_by_arm_plot(
parameters=features[i].parameters
),
Expand Down
4 changes: 3 additions & 1 deletion ax/analysis/plotly/tests/test_insample_effects.py
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Original file line number Diff line number Diff line change
Expand Up @@ -405,7 +405,9 @@ def test_constraints(self) -> None:
str(non_sq_df["constraints_violated"][0]),
)
# AND THEN it marks that constraints are not violated for the SQ
self.assertEqual(sq_row["size_column"].iloc[0], 100)
self.assertEqual(
sq_row["overall_probability_constraints_violated"].iloc[0], 0
)
self.assertEqual(
sq_row["constraints_violated"].iloc[0], "No constraints violated"
)
Expand Down
6 changes: 4 additions & 2 deletions ax/analysis/plotly/tests/test_predicted_effects.py
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Original file line number Diff line number Diff line change
Expand Up @@ -180,7 +180,7 @@ def test_compute(self) -> None:
"sem",
"error_margin",
"constraints_violated",
"size_column",
"overall_probability_constraints_violated",
},
)
self.assertIsNotNone(card.blob)
Expand Down Expand Up @@ -380,7 +380,9 @@ def test_constraints(self) -> None:
str(non_sq_df["constraints_violated"][0]),
)
# AND THEN it marks that constraints are not violated for the SQ
self.assertEqual(sq_row["size_column"].iloc[0], 100)
self.assertEqual(
sq_row["overall_probability_constraints_violated"].iloc[0], 0
)
self.assertEqual(
sq_row["constraints_violated"].iloc[0], "No constraints violated"
)
Expand Down