Fix PositionGroup.fetch_position_info() returning empty DataFrame when merge IDs are non-chronological

[Copilot]

PositionGroup.fetch_position_info() returns an empty DataFrame when position merge IDs are fetched in non-chronological order (e.g., alphabetically by UUID rather than by time). Pandas .loc[min:max] slicing on an unsorted index returns empty results.

Changes

• Core fix: Add .sort_index() before .loc[] slice in fetch_position_info() (line 232)
• Test coverage: Add test_position_group_non_chronological_order() to verify sorted output

Example

Without the fix, concatenating non-chronological position data fails:

# Sleep session (UUID: 141c4c08-..., time: 10-20s) fetched first
# Run session (UUID: a7585350-..., time: 0-5s) fetched second
# Concatenated index: [10, 15, 20, 0, 2.5, 5]

df.loc[0:20]  # Returns empty - index not sorted
df.sort_index().loc[0:20]  # Returns all data

The fix ensures correct behavior regardless of fetch order:

position_info = (
    pd.concat(position_info, axis=0).sort_index().loc[min_time:max_time]
)

Original prompt

---

This section details on the original issue you should resolve

<issue_title>PositionGroup.fetch_position_info() breaks if merge ids order does not match chronological order of the positions</issue_title> <issue_description>I'm running into an issue where PositionGroup.fetch_position_info() returns an empty dataframe and have narrowed it down to what I think is a bug at the end of the fetch_position() function.

The two pos_merge_ids that I'm trying to combine into a position group are as follows: run session 04_r2 (happens first): UUID('a7585350-6b4b-8f46-b4c9-e350ecffc1b6') sleep session 05_s3 (happens second): UUID('141c4c08-ec23-114f-ebbf-0168fc3b2b42')

Although I pass these keys into PositionGroup().create_group() via a list of dicts in the above order, they end up getting iterated through in alphabetically-sorted order in PositionGroup.fetch_position() which results in the position_info dataframe containing the sleep position info (chronologically later) first and the run position info (chronologically earlier) second. Because of this, once the dataframes are concatenated and indexed from [min_time: max_time] (see line 231 in spyglass.decoding.v1.core.py), this returns an empty dataframe.

Instead, I think the concatenated dataframe should be sorted by the time index prior to doing the min_time, max_time indexing.

I've replaced the original line 231 with position_info = pd.concat(position_info, axis=0).sort_index().loc[min_time:max_time] in my own code and that solved the issue for me!</issue_description>

<agent_instructions>Use TDD. </agent_instructions>

Comments on the Issue (you are @copilot in this section)

@edeno That makes sense. Thank for filing the issue!

• Fixes LorenFrankLab/spyglass#1471

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Codecov Report

:x: Patch coverage is 66.66667% with 1 line in your changes missing coverage. Please review. :white_check_mark: Project coverage is 71.11%. Comparing base (7d50c81) to head (d355ab2).

Files with missing lines	Patch %	Lines
src/spyglass/decoding/v1/sorted_spikes.py	0.00%	1 Missing :warning:

Additional details and impacted files

@@           Coverage Diff           @@
##           master    #1475   +/-   ##
=======================================
  Coverage   71.11%   71.11%           
=======================================
  Files         114      114           
  Lines       13307    13307           
=======================================
  Hits         9463     9463           
  Misses       3844     3844           

Flag	Coverage Δ
full-tests	71.11% <66.66%> (ø)

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