bmschmidt

library(ggplot2)
library(wordVectors)

slopegraph = function(
set1 = "RMP"
,
set2 = "genderless_RMP"
,
word = "she"
,

bmschmidt

import re
import gzip
import sys

def stripBadText(string):
    if string==None:
        return ""
    # No html tags
    string = re.sub("<[^>]+>","",string)
    # People don't talk in [brackets] or (inside parentheses), so I strip them.

bmschmidt

An idea that I proved unable to express in the number of characters on Twitter:

Train two word2vec models on the same corpus with 100 dimensions apiece; one with window size 5, and one with window size 15 (say).

Now you have 2 100-dimensional vector spaces with the same words in each.

That's the same as 1 200-dimensional vector space: you just append each of the vectors to each other.

That vector space has all the information from each of the original models in it: you can just use linear algebra to flatten it out along either of the original 100 degree vectors.

bmschmidt

#' Performs lazy load on a directory
#'
#' @param path a filepath containing the necessary files for lazy loading
#' @return NULL
#'
#' @details This function will go into a directory, search for all the files
#' that seem like they can be lazily loaded and attempt to load them.
#'
lazierLoad <- function(path){
  files <- dir(path)

bmschmidt

all:
	find ~ | parallel -n 1 -P 4 python dummy.py

bmschmidt

mkdir GUI
make linechartGUI webDirectory=GUI
git clone http://github.com/Bookworm-Project/BookwormAPI GUI/cgi-bin
git clone http://github.com/bmschmidt/BookwormD3 GUI/BookwormD3
cd GUI; python -m CGIHTTPServer 8000

bmschmidt

This is just a dummy file to get started

bmschmidt

layers = $(subst .shp,.topojson,$(subst shapefiles/,topojson/,$(wildcard shapefiles/*.shp)))


all: $(layers)

topojson/%.json: shapefiles/%.shp
	ogr2ogr -f GeoJSON $@ $<
	
topojson/%.topojson: topojson/%.json
	topojson -s .000001 -p -o $@ $<

bmschmidt

bmschmidt

MariaDB [DEGREES]> SELECT cip,cipTitle,SUM(count) FROM degrees NATURAL JOIN cip WHERE year=2010 AND school=186131 and variable="TOTAL" AND level=5 GROUP BY cip;
+---------+----------------------------------------------------------------------+------------+
| cip     | cipTitle                                                             | SUM(count) |
+---------+----------------------------------------------------------------------+------------+
|  4.0201 | Architecture.                                                        |         15 |
|  5.0104 | East Asian Studies.                                                  |         10 |
|  5.0108 | Near and Middle Eastern Studies.                                     |         13 |
| 14.0701 | Chemical Engineering.                                                |         36 |
| 14.0801 | Civil Engineering, General.                                          |         18 |
| 14.0901 | Computer Engineering, General.                                       |         44 |