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Correctly calculate y-axis range for multi-frequency upper limits #567

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merged 4 commits into from
Sep 11, 2024
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Merged

Correctly calculate y-axis range for multi-frequency upper limits #567

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6aadc8a
Recalculate upper_lims
ddobie Sep 11, 2024
a461978
Merge branch 'dev' into fix-lightcurve-lims-566
ddobie Sep 11, 2024
7cea460
PEP8
ddobie Sep 11, 2024
481342f
Updated changelog
ddobie Sep 11, 2024
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2 changes: 2 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -25,6 +25,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),

#### Fixed

- Correctly calculate plot_lightcurve y-axis range for multi-frequency upper limits [#567](https://github.com/askap-vast/vast-tools/pull/567)
- Fixed formatting of new epoch addition git example [#568](https://github.com/askap-vast/vast-tools/pull/568)
- Directly compare stmoc times, avoiding conversion to JD, and replace equality requirement with `isclose` [#334](https://github.com/askap-vast/vast-tools/pull/334)

Expand All @@ -34,6 +35,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),

#### List of PRs

- [#567](https://github.com/askap-vast/vast-tools/pull/567): fix: Correctly calculate plot_lightcurve y-axis range for multi-frequency upper limits
- [#568](https://github.com/askap-vast/vast-tools/pull/568): feat, docs: Add epochs 64 and 65, and fix new epoch addition docs page syntax
- [#334](https://github.com/askap-vast/vast-tools/pull/334): fix, docs, feat: Dependency refresh including python 3.10 support and corresponding minor updates
- [#563](https://github.com/askap-vast/vast-tools/pull/563): feat: Add access to epoch 63
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11 changes: 11 additions & 0 deletions vasttools/source.py
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Expand Up @@ -569,6 +569,17 @@ def plot_lightcurve(
detections = measurements_df[
~upper_lim_mask
]

if self.pipeline:
upper_lim_mask = measurements_df.forced
else:
upper_lim_mask = measurements_df.detection == False
if use_forced_for_all:
upper_lim_mask = np.array([False for i in upper_lim_mask])
upper_lims = measurements_df[
upper_lim_mask
]

if yaxis_start == "0":
max_det = detections.loc[:, [flux_col, err_value_col]].sum(axis=1)
if use_forced_for_limits or self.pipeline:
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