https://github.com/benmaier/cnetworkdiff
For fast diffusion simulation (or random walks) on networks.
https://github.com/benmaier/cnetworkdiff
Last synced: 2 months ago
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For fast diffusion simulation (or random walks) on networks.
- Host: GitHub
- URL: https://github.com/benmaier/cnetworkdiff
- Owner: benmaier
- Created: 2016-12-04T12:50:32.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2019-01-25T15:23:44.000Z (over 6 years ago)
- Last Synced: 2024-10-11T11:08:05.603Z (8 months ago)
- Language: C++
- Size: 27.3 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# cNetworkDiff
For fast simulations of diffusion processes on networks.
## Install
For all systems, first clone this repository.
### Python
Install
$ pip install ./cNetworkDiff
Install development version (stored in this directory)
$ pip install -e ./cNetworkDiff --no-binary :all:
### Matlab (Mac OSX)
You need to have the current XCode version installed (free in AppStore). Open Matlab and change into the directory of the repository. At first, there's two files you need to change.
```matlab
>>> cd /path/to/repository
>>> edit ([matlabroot '/bin/maci64/mexopts/clang++_maci64.xml'])
>>> edit ([matlabroot '/bin/maci64/mexopts/clang_maci64.xml'])
```
In both files, copy lines matching occurences of `MacOSX10.x.sdk` and change `MacOSX10.x.sdk` to `MacOSX10.11.sdk`(or whichever current version of XCode you're using).
Now, run
```matlab
>>> setup
>>> cd sandbox
>>> matlab_test
```
## Examples
### Python
There's some examples in the folder sandbox, e.g. `sandbox/nwdiff_test.py`.
Here's an example to get a single saturation time.
```python
from cNetworkDiffusion import saturation_time
N = 2
E = [(0,1)]
source = 0
target = 1
N_walker = 10
N_saturation = 5
t = saturation_time(N,E,source,target,N_walker,N_saturation)
```
And example on how to get a distribution of saturation times
```python
from cNetworkDiffusion import saturation_time
print("Let's do a histogram on this graph")
print(" o")
print(" /|\\")
print(" S | T")
print(" \\|/")
print(" o")
print("where S is the source node and T is the target node")
print("simulating ...")
saturation_times = []
N_meas = 1000
N_walker = 1000
N_saturation = 950
E = [ (0, 1), (0, 2), (1,2), (1, 3), (2, 3) ]
N = max([ node for e in E for node in e ]) + 1
source = 0
target = 3
from collections import Counter
for meas in range(N_meas):
t = saturation_time(N,E,source,target,N_walker,N_saturation,seed=meas)
saturation_times.append(t)
max_t = max(saturation_times)
# get histogram
hist = Counter(saturation_times)
length = 30
max_str_len = str(len(str(max_t)))
fmt_str = '{:0'+max_str_len+'d}'
print("saturation times")
print("================")
print((" " * (int(max_str_len)-1)) + "t: probability")
print("-"*length)
for t in range(1,max_t+1):
this_length = round(hist[t] / float(N_meas) * length)
print( (fmt_str + ': ' + '#' * this_length).format(t))
```