rischanlab

__author__ = 'rischan - <[email protected]>'
__date__ = '3/4/16'

import os
import sys
import glob
from cmath import log
from datetime import datetime
from xml.dom.minidom import parse
import traceback

rischanlab

#!/usr/bin/env python
# encoding: utf-8

import tweepy #https://github.com/tweepy/tweepy
import csv

#Twitter API credentials
consumer_key = ""
consumer_secret = ""
access_key = ""

rischanlab

# -*- coding: utf-8 -*-
"""
This script is forked originally from Dave Jeffery. The original implementation
was very slow and deleted around 2 tweets per second. Making it multithreaded I 
am able to delete 30-50 tweets per second. 
@author: vik-y

----------------------------------------------------------------------------

This script will delete all of the tweets in the specified account.

rischanlab

__author__ = 'rischan'

from django.core.exceptions import ObjectDoesNotExist
from django.core.management.base import BaseCommand
from agri_mapper.utilities.script import CallWMS, CallWFS, UpdateModel


import logging
logger = logging.getLogger(__name__)

rischanlab

### Author Information #####
### Coded by Rischan Mafrur ###
### 01/01/2015 ###
### For Thesis Purpose ###
### Language : R ###
### Dataset : Private Data ###

#Function for loading data
f_load_data <- function(path){
  library(shiny)

rischanlab

### Author Information #####
### Coded by Rischan Mafrur ###
### 01/01/2015 ###
### For Thesis Purpose ###
### Language : R ###
### Dataset : Private Data ###

#Function for loading data
f_load_data <- function(path){
  library(shiny)

rischanlab

#to make the final table, I changed manually the n size every trial by: 1e3, 1e4, 1e5, 1e6, 1e7. Then I also chnaged the benchmark object 'res'
n <- 1e7
set.seed(51)
process <- data.frame(id=sample(100, n, rep=T), x=rnorm(n), y=runif(n), z=rpois(n, 1) pexp(2, rate=1/3) )

all <- multicore:::detectCores(all.tests=TRUE)

if(!require(rbenchmark)){
install.packages("rbenchmark")
} else{

rischanlab

install.packages("randomForest",dependencies=TRUE)

library(randomForest)
fit <- randomForest(data$user ~ data$academic+data$email
                    +data$socnet+data$porn+data$comic+data$music
                    +data$shop+data$blog+data$video+data$search
                    +data$news, data=data)
print(fit)
importance(fit)

rischanlab

\begin{figure*}%
\centering
\begin{subfigure}{.95\columnwidth}
\includegraphics[width=\columnwidth]{tolakpartaipoligami_pie3D.png}%
\caption{\#TolakPartaiPoligami hashtag}
\label{fig:sub1}
\end{subfigure}\hfill%
\begin{subfigure}{.95\columnwidth}
\includegraphics[width=\columnwidth]{sayapilihpks_pie3D.png}%
\caption{\#SayaPilihPKS hashtag}

rischanlab

#author		: Rischan Mafrur
#email		: [email protected]
#website	: rischanlab.github.io, ourmasjid.me 
#May 15, 2014

#install requirement packages
install.packages("klaR")
install.packages("caret")
install.packages("plotrix")