Closed yiyange closed 5 years ago
Excellent observation - thank you!!
This also helps in working towards addressing various risks associated with this issue: https://github.com/kuanb/peartree/issues/126
TODO:
@kuanb i updated the logic and reran, the impact is much less unfortunately. but it is a start.
@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.
Merging #127 into master will increase coverage by
0.24%
. The diff coverage is100%
.
@@ 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
Impacted Files | Coverage Δ | |
---|---|---|
peartree/toolkit.py | 93.5% <100%> (+1.19%) |
:arrow_up: |
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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)![use_min](https://user-images.githubusercontent.com/14876272/52310060-ef495e80-2956-11e9-88db-fe4aebd2e11a.gif)
The following map shows the same change but using coalesced network using mean (different color bins though). The change is less significant.![use_mean](https://user-images.githubusercontent.com/14876272/52319668-da34f580-297f-11e9-9a7c-44dc5cea2bb0.gif)
Also some stats comparison:
Visuals made by UrbanFootprint :))