[coalesce] Use mean of grouped edge weights rather than minimum #127
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Excellent observation - thank you!! This also helps in working towards addressing various risks associated with this issue: #126 |
yiyange
changed the title
kuanb
changed the title
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TODO:
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@kuanb i updated the logic and reran, the impact is much less unfortunately. but it is a start. |
peartree/toolkit.py
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| if not G.has_edge(rn1, rn2): | ||
| # Append new edge with attributes to list | ||
| length = avg_length | ||
| # Note: the mode is determined by the first edge |
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@kuanb what's your thought on this?
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I think coalesce is sort of a mess with transit... Let's figure it out for walk first... I think assume a comment like you did is good. Maybe add a todo. In future we should segment coalesce by mode
peartree/toolkit.py
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| # Second step; which uses results from edge_df grouping/parsing | ||
| edges_to_add = [] | ||
| # Go through each edge |
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Nit: Extraneous comment, would remove
peartree/toolkit.py
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| if not G.has_edge(rn1, rn2): | ||
| # Append new edge with attributes to list | ||
| length = avg_length | ||
| # Note: the mode is determined by the first edge |
There was a problem hiding this comment.
I think coalesce is sort of a mess with transit... Let's figure it out for walk first... I think assume a comment like you did is good. Maybe add a todo. In future we should segment coalesce by mode
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@yiyange Update on this PR: I just updated tests, tweaked logic. Should be passing the Travis tests shortly and will merge in after that - thanks again. |
Codecov Report
@@ Coverage Diff @@
## master #127 +/- ##
==========================================
+ Coverage 91.43% 91.68% +0.24%
==========================================
Files 13 13
Lines 1109 1106 -3
==========================================
Hits 1014 1014
+ Misses 95 92 -3
Continue to review full report at Codecov.
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Using minimum of grouped edge weights effectively reduce path costs, and increase accessibility significantly.
The following map shows shortest path lengths from one single source to all destinations in Berkeley.
It changes from using original full network to coalesced network using min grouped edge weights. Noticing the shortest path lengths reduce significantly (darker color to lighter color)
The following map shows the same change but using coalesced network using mean (different color bins though). The change is less significant.
Also some stats comparison:
Visuals made by UrbanFootprint :))