Closed hcars closed 2 years ago
Hello,
Thank you for contributing!
We appreciate the functionalities you've added and would like you to make a few adjustments and corrections before we can merge your branch:
radius
, add a parameter n_sources
similar to that present in the diameter
function. That will make it possible to have an approximation even on large graphs.radius
, rather than using the eccentricity
function and map
, compute all distances between from all sources at once to enable faster computations (as the parallelism will be more efficient). Then take the max of each line and finally the min of those maxima.docs/
folder (have a glance at the Wiki for indications)I've also made some corrections for the function names we were in the process of making.
Beware of PEP8 styling. In particular, no line in the code should be more than 120 characters long.
I addressed the first 3 of your bullets. I added the methods to the path.rst file, but I'm not sure if that's sufficient.
Merging #522 (5455670) into develop (bd842b4) will increase coverage by
0.01%
. The diff coverage is100.00%
.
@@ Coverage Diff @@
## develop #522 +/- ##
===========================================
+ Coverage 98.55% 98.57% +0.01%
===========================================
Files 170 173 +3
Lines 7216 7295 +79
===========================================
+ Hits 7112 7191 +79
Misses 104 104
Impacted Files | Coverage Δ | |
---|---|---|
sknetwork/path/__init__.py | 100.00% <100.00%> (ø) |
|
sknetwork/path/metrics.py | 100.00% <100.00%> (ø) |
|
sknetwork/path/shortest_path.py | 100.00% <100.00%> (ø) |
|
sknetwork/path/tests/test_metrics.py | 100.00% <100.00%> (ø) |
|
sknetwork/path/tests/test_shortest_path.py | 100.00% <100.00%> (ø) |
|
sknetwork/data/load.py | 94.44% <0.00%> (ø) |
|
sknetwork/data/models.py | 100.00% <0.00%> (ø) |
|
sknetwork/ranking/__init__.py | 100.00% <0.00%> (ø) |
|
sknetwork/ranking/diffusion.py | ||
sknetwork/ranking/tests/test_diffusion.py | ||
... and 5 more |
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Thank you for your corrections. The last few steps before merging are the following:
get_distances
function (in both the n_jobs == 1
and n_jobs > 1
cases).You're welcome! I just added checks for those.
Modifications:
(new algorithms, added tests or documentation)
Impacted submodules:
(e.g.
sknetwork.topology
)This pull request:
(your PR must match these criteria before review)
develop
branchAny doubts about some technicalities? Do not hesitate to look at the dedicated Wiki.