MonteShaffer

# https://stackoverflow.com/questions/64476043/
# https://stackoverflow.com/questions/1189759/
convertDirectoryR.toWin = function(myDir = getwd())  # "R:/data/state-capitals/final/"
  {
  cat( normalizePath(myDir) );
    writeClipboard( normalizePath(myDir) ); # R:\data\state-capitals\final\
  }

openDirectoryR.inWin = function(myDir = getwd())  # "R:/data/state-capitals/final/"

MonteShaffer

#' Convert String Matrix to Numeric Matrix
#'
#' @param m string matrix
#'
#' @return numeric matrix
#' @export

numericMatrix = function(m)
{

MonteShaffer

# Blender v2.74 (sub 0) OBJ File: 'Hand.blend'
# www.blender.org
mtllib Hand.mtl
o ZBrushPolyMesh3D
v 0.614360 0.281365 -0.675872
v 0.684894 0.445729 -0.634615
v 1.294752 1.048795 -0.574309
v 0.552541 0.233567 -0.579448
v 0.631207 0.406862 -0.474761
v 1.311582 1.012985 -0.257089

MonteShaffer

# helper class to interface between R and python using rpy2
# © Monte J. Shaffer
# [email protected]
# MIT license
import numpy as np

import rpy2
import rpy2.robjects as robjects
import rpy2.robjects.packages as rpackages
from rpy2.robjects.packages import importr

MonteShaffer

# I wrote this in 2009 as part of my M.S. Stats - Statistical Computing Course
# Not all the bells and whistles, but should be understandable
# © Monte J. Shaffer
# [email protected]
# MIT license

myKmeans = function(data,clusters,maxIter=25)
	{
	data = as.matrix(data);
	n = nrow(data);

MonteShaffer

# https://datasciencelab.wordpress.com/2014/01/15/improved-seeding-for-clustering-with-k-means/

import numpy as np
import random
from numpy import zeros


import matplotlib
matplotlib.use("qt4agg")
from matplotlib import pyplot as plt