Shivam Rana TrigonaMinima

## .gitignore
# Compiled source #
###################
*.com
*.class
*.dll
*.exe
*.o
*.so
*.out
*.pyc

## receiver.py
# chat server using multicast
# python fork of the original ruby implementation
# http://tx.pignata.com/2012/11/multicast-in-ruby-building-a-peer-to-peer-chat-system.html
# receiver.py
# usage : $ python receiver.py  # wait for messages to come in

import socket
import struct

multicast_addr = '224.0.0.1'

## base_r_plotting_tutorial_koontz_d-rug.r
### Title: Back to basics: High quality plots using base R graphics
###	An interactive tutorial for the Davis R Users Group meeting on April 24, 2015
###
### Date created: 20150418
### Last updated: 20150423
###
### Author: Michael Koontz
### Email: mikoontz@gmail.com
###	Twitter: @michaeljkoontz
###

## min-char-rnn.py
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
	# Compiled source #
	###################
	*.com
	*.class
	*.dll
	*.exe
	*.o
	*.so
	*.out
	*.pyc
	# chat server using multicast
	# python fork of the original ruby implementation
	# http://tx.pignata.com/2012/11/multicast-in-ruby-building-a-peer-to-peer-chat-system.html
	# receiver.py
	# usage : $ python receiver.py # wait for messages to come in

	import socket
	import struct

	multicast_addr = '224.0.0.1'
	### Title: Back to basics: High quality plots using base R graphics
	### An interactive tutorial for the Davis R Users Group meeting on April 24, 2015
	###
	### Date created: 20150418
	### Last updated: 20150423
	###
	### Author: Michael Koontz
	### Email: mikoontz@gmail.com
	### Twitter: @michaeljkoontz
	###
	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)