Mingli Yuan mountain

## bind-events-with-bean-qwery-bonzo-but-without-ender.coffee
###
  csmain.coffee

  link for this section:
  http://playground.wahlque.org/tutorials/coffeescript/004-webworkers/
###
define [
  'underscore',
  'domReady',
  'qwery',

## antinode
#!/bin/bash
#
# A wrapper for runner
#
CUR="${BASH_SOURCE[0]}";
if([ -h "${CUR}" ]) then
  while([ -h "${CUR}" ]) do CUR=`readlink -m "${CUR}"`; done
fi
pushd . > /dev/null
cd `dirname ${CUR}` > /dev/null

## corpus_utilities.clj
(use 'clojure.java.io)
(use 'com.guokr.nlp.seg)

(def corpus-root "/path/to/directory")

(def corpus-dir (clojure.java.io/file corpus-root))
(def corpus-files (file-seq corpus-dir))
(def corpus-writer (writer (str corpus-root "/corpus.txt")))

(defn line-by-line [wrtr lhdl] (fn [file] (with-open [rdr (reader file)] (doseq [line (line-seq rdr)] (.write wrtr (str (lhdl line) "\n"))))))

## ldaschema.clj
(def lda (second (get-model "model")))

(spit "2014.sch" (clojure.string/join "\n" (map #(clojure.string/join ";" %) (map vec (vec (.getTopWords lda 12))))))

## NGramIterator.java
package ngram;

import java.util.Iterator;

public class NGramIterator implements Iterator<StringBuilder> {

	private char[] ring;
	private int n;
	private int cur;

## latency.markdown

      
              2 files
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                mountain
                / latency.markdown
            
            
              Created
              August 11, 2014 08:41
                — forked from hellerbarde/latency.markdown
            
          
    Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

  
## keybase.md

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                mountain
                / keybase.md
            
            
              Created
              December 25, 2015 15:01
            
          
    Keybase proof

I hereby claim:

I am mountain on github.
I am mingliyuan (https://keybase.io/mingliyuan) on keybase.
I have a public key whose fingerprint is ED86 CD82 A682 45D7 5CC5  2C3E 6EFF 88CB 304F 50A2

To claim this, I am signing this object:

  
## keybase.md

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                mountain
                / keybase.md
            
            
              Created
              December 25, 2015 15:01
            
          
    Keybase proof

I hereby claim:

I am mountain on github.
I am mingliyuan (https://keybase.io/mingliyuan) on keybase.
I have a public key whose fingerprint is ED86 CD82 A682 45D7 5CC5  2C3E 6EFF 88CB 304F 50A2

To claim this, I am signing this object:

  
## test_nn_width_depth_for_logic_gate.py
# -*- coding: utf-8 -*-

import numpy as np
import sys
import keras

from keras.layers import Input, Dense
from keras.models import Model


## search_crossword_chinese_poetries.py
# -*- coding: utf-8 -*-

'''
This simple program is used to search for crossword sentences in selected Chinese poetries

The selected Chinese poetries here is stored in a text file - tang_poetry_5char.txt.
You can change to your version of candidates

You should install networkx by pip
	###
	csmain.coffee

	link for this section:
	http://playground.wahlque.org/tutorials/coffeescript/004-webworkers/
	###
	define [
	'underscore',
	'domReady',
	'qwery',
	#!/bin/bash
	#
	# A wrapper for runner
	#
	CUR="${BASH_SOURCE[0]}";
	if([ -h "${CUR}" ]) then
	while([ -h "${CUR}" ]) do CUR=`readlink -m "${CUR}"`; done
	fi
	pushd . > /dev/null
	cd `dirname ${CUR}` > /dev/null
	(use 'clojure.java.io)
	(use 'com.guokr.nlp.seg)

	(def corpus-root "/path/to/directory")

	(def corpus-dir (clojure.java.io/file corpus-root))
	(def corpus-files (file-seq corpus-dir))
	(def corpus-writer (writer (str corpus-root "/corpus.txt")))

	(defn line-by-line [wrtr lhdl] (fn [file] (with-open [rdr (reader file)] (doseq [line (line-seq rdr)] (.write wrtr (str (lhdl line) "\n"))))))
	(def lda (second (get-model "model")))

	(spit "2014.sch" (clojure.string/join "\n" (map #(clojure.string/join ";" %) (map vec (vec (.getTopWords lda 12))))))
	package ngram;

	import java.util.Iterator;

	public class NGramIterator implements Iterator<StringBuilder> {

	private char[] ring;
	private int n;
	private int cur;
	# -- coding: utf-8 --

	import numpy as np
	import sys
	import keras

	from keras.layers import Input, Dense
	from keras.models import Model
	# -- coding: utf-8 --

	'''
	This simple program is used to search for crossword sentences in selected Chinese poetries

	The selected Chinese poetries here is stored in a text file - tang_poetry_5char.txt.
	You can change to your version of candidates

	You should install networkx by pip