https://github.com/benmaier/biasedrandomwalks
Provides classes around biased random walks on networks.
Science Score: 13.0%
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Low similarity (4.6%) to scientific vocabulary
Keywords
Repository
Provides classes around biased random walks on networks.
Basic Info
- Host: GitHub
- Owner: benmaier
- Language: Python
- Default Branch: master
- Size: 31.3 KB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
BiasedRandomWalks
Provides classes around biased random walks on networks.
Install
$ git clone git@github.com:benmaier/BiasedRandomWalks.git
$ pip install ./BiasedRandomWalks
Examples
```python import numpy as np import matplotlib.pyplot as pl import networkx as nx
from BiasedRandomWalks import BiasedRandomWalk
Create a test Graph with weighted edges where weights are distances
G = nx.Graph() N = 4 G.addnodesfrom(range(N)) G.addedge(0,1,weight=1) G.addedge(0,2,weight=1) G.addedge(1,2,weight=1) G.addedge(1,3,weight=0.1) G.add_edge(2,3,weight=0.2)
define sink nodes
sink_nodes = [2,]
define bias
gamma = 1
initial distribution on transient
p0 = np.array([1,0,0])
initial distribution on all
p0_all = np.array([1,0,0,0])
initial base class (choose 'exponential' or 'scale free')
RW = BiasedRandomWalk(G, gamma, sinknodes, biaskind = 'exponential')
fig, ax = pl.subplots(2,2,figsize=(9,7))
integrate up to this time step
tmax = 10
========== prob density on sinks =========
t, rho = RW.getamountofwalkersarrivingatsink_nodes(p0,tmax)
for is, s in enumerate(sinknodes): ax[0,0].plot(t, rho[:,i_s], label='sink node '+ str(s))
ax[0,0].legend() ax[0,0].setxlabel('time') ax[0,0].setylabel('amount of walkers arriving')
========== cdf on sinks =========
t, rho = RW.getamountofwalkersarrivedatsink_nodes(p0,tmax)
for is, s in enumerate(sinknodes): ax[0,1].plot(t, rho[:,i_s], label='sink node '+ str(s))
ax[0,1].legend() ax[0,1].setxlabel('time') ax[0,1].setylabel('total amount of walkers arrived')
========== prob density on all =========
t, rho = RW.getamountofwalkersonnodes(p0all,tmax)
for s in G.nodes(): ax[1,0].plot(t, rho[:,s], label='node '+ str(s))
ax[1,0].legend() ax[1,0].setxlabel('time') ax[1,0].setylabel('amount of walkers on each node')
pl.show() ```
Owner
- Name: Benjamin F. Maier
- Login: benmaier
- Kind: user
- Location: Copenhagen
- Company: Technical University of Denmark
- Website: benmaier.org
- Twitter: benfmaier
- Repositories: 101
- Profile: https://github.com/benmaier
Postdoc @suneman 's, generative art, electronic music. DTU Compute & SODAS.
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Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Benjamin Maier | b****r@g****m | 15 |
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Last synced: 7 months ago
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Dependencies
- networkx >=2
- numpy >=1.14