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<style> | |
.node { | |
stroke: #fff; | |
stroke-width: 1.5px; | |
} | |
.link { | |
stroke: #999; | |
stroke-opacity: .6; |
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# Brian Abelson @brianabelson | |
# Harmony Institute | |
# December 5, 2012 | |
# lda is a wrapper for lda.collapsed.gibbs.sampler in the "lda" package | |
# it fits topic models using latent dirichlet allocation | |
# it provides arguments for cleaning the input text and tuning the parameters of the model | |
# it also returns alot of useful information about the topics/documents in a format that you can easily join back to your original data | |
# this allows you to easily model outcomes based on the distribution of topics within a collection of texts |
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doInstall <- TRUE | |
toInstall <- c("twitteR", "dismo", "maps", "ggplot2") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
searchTerm <- "#rstats" | |
searchResults <- searchTwitter(searchTerm, n = 1000) # Gather Tweets | |
tweetFrame <- twListToDF(searchResults) # Convert to a nice dF | |
userInfo <- lookupUsers(tweetFrame$screenName) # Batch lookup of user info |
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<script src="http://d3js.org/d3.v3.js"></script> | |
<script type="text/javascript"> | |
(function(){ | |
// Probably not idiomatic javascript. | |
this.countValue=0; | |
updateView = function(message) { | |
var svg = d3.select(".d3io").select("svg") |
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doInstall <- TRUE | |
toInstall <- c("twitteR", "dismo", "maps", "ggplot2") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
searchTerm <- "#rstats" | |
searchResults <- searchTwitter(searchTerm, n = 1000) # Gather Tweets | |
tweetFrame <- twListToDF(searchResults) # Convert to a nice dF | |
userInfo <- lookupUsers(tweetFrame$screenName) # Batch lookup of user info |
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# Requirements | |
#sudo apt-get install libcurl4-gnutls-dev # for RCurl on linux | |
#install.packages('RCurl') | |
#install.packages('RJSONIO') | |
library('RCurl') | |
library('RJSONIO') | |
query <- function(querystring) { | |
h = basicTextGatherer() |
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# User facing function | |
# | |
# to_math(x_1 + 1^{2 + 4} + 5 + sqrt(y) / 5 %/% 10) | |
# to_math(paste(x^2, y - 1, z_i)) | |
# to_math(hat(tilde(ring(x)))) | |
to_math <- function(x) { | |
to_math_q(substitute(x)) | |
} | |
to_math_q <- function(x) { |
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## See http://gettinggeneticsdone.blogspot.com/2013/06/customize-rprofile.html | |
## Load packages | |
library(BiocInstaller) | |
## Don't show those silly significanct stars | |
options(show.signif.stars=FALSE) | |
## Do you want to automatically convert strings to factor variables in a data.frame? | |
## WARNING!!! This makes your code less portable/reproducible. |
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require(rCharts) | |
require(rjson) | |
#get source from original example | |
#this is a JSON, so will need to translate | |
#this is complicated and unnecessary but feel I need to replicate | |
#for completeness | |
#expect most data to come straight from R | |
#in form of source, target, value |
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""" | |
Simply display the contents of the webcam with optional mirroring using OpenCV | |
via the new Pythonic cv2 interface. Press <esc> to quit. | |
""" | |
import cv2 | |
def show_webcam(mirror=False): | |
cam = cv2.VideoCapture(0) |