disa-mhembere

#!/usr/bin/Rscript

frobenius.norm <- function(V, W, H) {
  sqrt(sum((V - (W%*%H))^2)/prod(dim(V)))
}

nmf <- function (V, r, H=abs(replicate(dim(V)[2], rnorm(r))),
                    W=abs(replicate(r, rnorm(dim(V)[1]))), max.iters=1000) {
  set.seed(12345)
  converged <- FALSE

disa-mhembere

#!/usr/bin/python
# Disa Mhembere

# Make me a new file with a nice comment block and optinal
# things like a main, and argparser
# This is free software and comes with not guarantee of correct
# functionality. Use at your own peril

import argparse
import os

disa-mhembere

import mrcap.utils.igraph_io as igraph_io
import igraph
from glob import glob
import cPickle as pickle
import os

def get_dist(directory):
  deg_map = {}
  for fn in glob(os.path.join(directory, "*.zip")):
    g = igraph_io.read_arbitrary(fn, informat="graphml")

disa-mhembere

#include <igraph.h>
#include <stdio.h>

void custom_warning_handler (const char *reason, const char *file,
               int line, int igraph_errno) {
    printf("Warning: %s\n", reason);
}

int main(int argc, char* argv[])
{

disa-mhembere

import subprocess
import os

for _file_ in os.listdir("."):
  if not _file_.startswith(".") and not _file_.endswith("py"):
    subprocess.call(["zip", "-v", _file_+".zip", _file_])
    print "Deleting,", _file_
    os.remove(_file_)

disa-mhembere

import os
import sys

value = sys.argv[1]

for _file_ in os.listdir("."):
  if not _file_.startswith(".") and not _file_.endswith("py"):
    print "Attempting to read and split %s ..." % _file_
    f = open(_file_, "r")
    print "Renaming uncompressed"

disa-mhembere

require(igraph)

g <- read.graph("./web-Google.txt") # Change fn
cl <- clusters(g, "strong") # "weak"
unique.clusters <-  unique(cl$csize)
for (i in 1: length(unique.clusters) ) { 
  cat(unique.clusters[i], length(which(cl$csize == unique.clusters[i])),"\n")
}

disa-mhembere

require(igraph)
dat <- read.table("./fly.csv", header=TRUE, sep=",")
dat <- dat[c("presynaptic",  "postsynaptic" , "pre.x", "post.x", "pre.y", "post.y", "pre.z", "post.z","proofreading.details")]
g <- graph.data.frame(dat, directed=TRUE)
g <- set.graph.attribute(g, "source", value="http://www.nature.com/nature/journal/v500/n7461/full/nature12450.html")
g <- set.graph.attribute(g, "info", value="source=presynaptic, targe=postsynaptic")
write.graph(g, "drosophila_retina.graphml", format="graphml")

disa-mhembere

require(Matrix)
require(igraph)
require(argparse)

parser <- ArgumentParser(description="Process some integers")
parser$add_argument("gfn", help="The graph file name")
parser$add_argument("nev", type="integer", help="Number of eigenvectors to compute")
parser$add_argument("ncv", type="integer",help="Number of Lanczos vectors to compute")
parser$add_argument("maxiter", type="integer",help="Max number of iterations to compute eigenvectors")

disa-mhembere

import networkx as nx
import numpy as np

p = 0.3 # Alter as necessary
n = 1000 # Alter as necessary
fn = "graph%d"%n # Alter as necessary

g = nx.erdos_renyi_graph(n, p,False)
gsp = nx.to_scipy_sparse_matrix(g)