Update arXiv link; warn node2vec+ usage for unweighted graphs

Author: RemyLau

README.md

@@ -7,7 +7,7 @@ Learning low-dimensional representations (embeddings) of nodes in large graphs i
 
 The details of implementation and the optimizations, along with benchmarks, are described in the application note [_PecanPy: a fast, efficient and parallelized Python implementation of node2vec_](https://doi.org/10.1093/bioinformatics/btab202), which is published in _Bioinformatics_. The benchmarking results presented in the preprint can be reproduced using the test scripts provided in the companion [benchmarks repo](https://github.com/krishnanlab/PecanPy_benchmarks).
 
-**v2 update**: PecanPy is now equipped with _node2vec+_, which is a natural extension of _node2vec_, and handles weighted graph more effectively. For more information, see [*Accurately Modeling Biased Random Walks on Weighted Wraphs Using Node2vec+*](). The datasets and test scripts for reproducing the presented results are available in the [node2vec+ benchmarks repo](https://github.com/krishnanlab/node2vecplus_benchmarks).
+**v2 update**: PecanPy is now equipped with _node2vec+_, which is a natural extension of _node2vec_, and handles weighted graph more effectively. For more information, see [*Accurately Modeling Biased Random Walks on Weighted Wraphs Using Node2vec+*](https://arxiv.org/abs/2109.08031). The datasets and test scripts for reproducing the presented results are available in the [node2vec+ benchmarks repo](https://github.com/krishnanlab/node2vecplus_benchmarks).
 
 ## Installation
 
@@ -122,7 +122,7 @@ If you use this work, please cite:
 Liu R, Krishnan A (2021) **PecanPy: a fast, efficient, and parallelized Python implementation of node2vec.** _Bioinformatics_ https://doi.org/10.1093/bioinformatics/btab202
 
 If you find _node2vec+_ useful, please cite:
-Liu R, Hirn M, Krishnan A (2021) **Accurately Modeling Biased Random Walks on Weighted Wraphs Using Node2vec+.** _axXiv_ (TBA)
+Liu R, Hirn M, Krishnan A (2021) **Accurately Modeling Biased Random Walks on Weighted Wraphs Using Node2vec+.** _axXiv_ https://arxiv.org/abs/2109.08031
 
 ### Authors
 Renming Liu, Arjun Krishnan*

src/pecanpy/cli.py

@@ -179,6 +179,8 @@ def read_graph(args):
         raise ValueError(f"Unkown mode: {repr(mode)}")
 
     check_mode(g, mode)
+    if extend and not weighted:
+        print("WARNING: node2vec+ is equivalent to node2vec for unweighted graphs.")
 
     return g