updated readme

README.md

@@ -1,4 +1,95 @@
 talk-like-a-congressman
 =======================
 
-n-gram models trained on congressional public speech data
+n-gram models trained on congressional public speech data.
+
+I'm working with this data as part of the
+[lazer lab](www.lazerlab.net) at Northeastern University, so I decided
+to have a little fun with it.
+
+## To Use:
+
+Right now, there's no 'main script'. You have to run some methods in a python interpreter.
+
+To do this, import the modules:
+
+```python
+import corpus
+import markov
+```
+
+read the vocabulary data and the data of the congressman you want to talk like:
+
+```python
+c = corpus.read_data('corpora/1032/corpus.txt', 'vocab.txt')
+```
+
+create the markov model:
+
+```python
+m = markov.Markov(c, 3)
+```
+
+generate some text:
+
+```python
+m.generate(100)
+```
+should output something like:
+
+```
+they now have better access to technology in the affordable care
+act is already paying dividends for millions of americans with more to
+come children can no longer have the records to defend themselves
+similarly at least some irs agents have taken the position that anyone
+who claimed edc benefits as a certainly as a participant in a recent
+report from the leaders and residents of the pre jobs act with respect
+to the united states and that met the program s criteria for creating
+jobs and economic opportunity for virgin islanders the increase of our
+nation i believe the path'
+```
+
+No punctuation, just words.
+
+
+## A little documentation
+
+Each congresspersons' collection of public statements is considered a
+separate corpus.
+
+Each corpus consists of some number of documents, and each document
+consists of some number of tokens, or words.
+
+A corpus is represented as a single file, where each line is a
+document. Each word is an integer, and words are separated by spaces.
+
+There is a single `vocab.txt` file for all the corpora that serves to
+map tokens to integer IDs.
+
+`vocab.txt` contains all the unique words recognized in the corpus on
+a single line, each separated by a space.
+
+In the corpus code and in the markov model, each word is represented
+by its' index in the vocabulary list. The first word in the line is
+the 0th index.
+
+### using the markov model
+
+initialize a corpus object by giving it two arguments - the first is
+the corpus file to use, and the second is the vocabulary file:
+
+```python
+c = corpus.read_data('corpus.txt', 'vocab.txt')
+```
+
+initialize a markov object with code that looks like this:
+
+```python
+m = Markov(corpus, 3)
+```
+
+where `corpus` is a corpus object, and `3` is the length of n-grams to use.
+
+to generate text, call `Markov.generate(l)`, where `l` is the length of the text you want to generate.
+
+