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Disable log scale when value is within 0.1 of zero for Histograms #13496

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Disable log scale when value is within 0.1 of zero for Histograms #13496

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5 changes: 4 additions & 1 deletion src/ert/gui/tools/plot/plot_window.py
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Original file line number Diff line number Diff line change
Expand Up @@ -419,7 +419,10 @@ def fetch_data(
if key_def.parameter is not None and key_def.parameter.type == "gen_kw":
for data in ensemble_to_data_map.values():
numeric = data.select_dtypes(include=["number"])
if not numeric.empty and numeric.le(0).any().any():
# Use 0.11 instead of 0 because the histogram
# expands the range by ±0.1 when min == max,
# which would make a value of 0.1 become a negative bin edge.
if not numeric.empty and numeric.lt(0.11).any().any():
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@jonathan-eq jonathan-eq May 8, 2026

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I dont think we should do this to compensate for a magic number we set somewhere else. I think the solution should be to dynamically calculate the width of the bars so they wont be <=0 on the plotter side instead of hardcoded 0.5+0.5.

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@eilskra eilskra May 8, 2026

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Revert this to <= 0 and do the bin calculation in the plot such that a bin edge can never be <= 0 instead?

negative_values_in_data = True
break

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3 changes: 0 additions & 3 deletions src/ert/gui/tools/plot/plottery/plots/histogram.py
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Expand Up @@ -188,9 +188,6 @@ def _plotHistogram(
if minimum is not None and maximum is not None:
# Ensure we have at least 2 bin edges to create 1 bin
effective_bin_count = max(bin_count + 1, 2)
if minimum == maximum:
minimum -= 0.5
maximum += 0.5
Comment on lines -191 to -193
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@jonathan-eq jonathan-eq May 8, 2026

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Why do we remove this?

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@eilskra eilskra May 8, 2026 •
edited
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Since plotHistogram() calls _plotHistogram() and prior to _plotHistogram() being called the min/max transformation is checked/applied:

if minimum is not None and maximum is not None and minimum == maximum:
                    minimum -= 0.1
                    maximum += 0.1

so I don't think min can be equal to max in _plotHistogram

if use_log_scale:
bins = _histogramLogBins(effective_bin_count, minimum, maximum) # type: ignore
axes.set_xscale("log")
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4 changes: 2 additions & 2 deletions tests/ert/unit_tests/gui/tools/plot/test_plot_window.py
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Expand Up @@ -124,7 +124,7 @@ def test_that_plotting_gen_kw_parameter_with_negative_values_hides_log_scale_che

def mock_data_for_parameter(ensemble_id: str, parameter_key: str) -> pd.DataFrame:
if parameter_key == "gen_kw_a":
return pd.DataFrame({0: [0.1, 0.5, 0.9]})
return pd.DataFrame({0: [0.11, 0.5, 0.9]})
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@andreas-el andreas-el May 7, 2026

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Can we extract this as a constant, like @eqbech proposed?
You could import this from plot_window.

return pd.DataFrame({0: [-0.1, -0.5, -0.9]})

mock_plot_api.data_for_parameter.side_effect = mock_data_for_parameter
Expand Down Expand Up @@ -313,7 +313,7 @@ def test_that_plot_widget_hides_log_scale_checkbox_for_const_distribution(qtbot:
)
plot_widget.updatePlot(
ctx,
{ensemble: pd.DataFrame({0: [0.1, 0.2, 0.3]})},
{ensemble: pd.DataFrame({0: [0.11, 0.2, 0.3]})},
pd.DataFrame(),
{},
None,
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