Saran Ahluwalia ahlusar1989

## snr-periodic.py
"""
Plot white noise with added sinusoidal signal
"""
import numpy as np
import matplotlib.pyplot as plt
import sys
import h5py

fs = 4096           # sampling rate [Hz]
T = 4               # duration [s]

## YeoJohnson.py
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
import warnings
import numpy as np
import pandas as pd
import sys

__author__ = "Mohsen Mesgarpour"
__copyright__ = "Copyright 2016, https://github.com/mesgarpour"
__credits__ = ["Mohsen Mesgarpour"]

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

"""
GIBBS SAMPLING IMPLEMENTATION FOR LATENT DIRICHLET ALLOCATION (2003)
IMPLEMENTED BY CHANG-UK, PARK
DATA FORMAT: "DocID\t WordID\t FREQUENCY\n"
"""

import sys
import random

## jupyter-google-cloud.md

      
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                ahlusar1989
                / jupyter-google-cloud.md
            
            
              Last active
              January 4, 2018 15:13
                — forked from valentina-s/jupyter-google-cloud.md
            
              
                Jupyter Notebook on Google Cloud Compute Instance 
              
          
    On Instance:
pip install jupyter[notebook]

jupyter notebook --generate-config

# nano .jupyter/jupyter_notebook_config.py

echo "c = get_config()
c.NotebookApp.ip = '*'


## pytorch_keras_gcloud.txt
# This script is designed to work with ubuntu 16.04 LTS
# with keras 1.2.2 and the latest Pytorch with CUDA 8 support
##########################################################################
#This is used to install CUDA 8 driver for Tesla K80
##########################################################################

#!/bin/bash
echo "Checking for CUDA and installing."
# Check for CUDA and try to install.
if ! dpkg-query -W cuda-8-0; then

## middlewares.py
from random import choice
from scrapy import signals
from scrapy.exceptions import NotConfigured


class RotateUserAgentMiddleware(object):
    """Rotate user-agent for each request."""
    def __init__(self, user_agents):
        self.enabled = False
        self.user_agents = user_agents

## LRUCache.js
// LRUCache.js - super simple JavaScript Implementation
// LRU stands for "Least Recently Used"
// https://en.wikipedia.org/wiki/Cache_replacement_policies#LRU

// -----------------------------------------

function LRUNode(key) {
  this.key = key;
  this.next = this.prev = null;
}

## FormContainer.js
import { graphql } from 'react-apollo';
import { connect } from 'react-redux';
import { compose } from 'redux';

import {
  change,
  getFormSubmitErrors,
  getFormValues,
  reduxForm,
  stopAsyncValidation,

## int_additions.scala
object MindBlown extends App {
  trait Monoid[A] {
    def op(a1: A, a2: A): A
    def zero: A
  }

  val intAddition = new Monoid[Int] {
    override def op(a1: Int, a2: Int) = a1 + a2
    override def zero = 0
  }

## rds_to_docker.md

      
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                ahlusar1989
                / rds_to_docker.md
            
            
              Created
              September 4, 2016 14:21
                — forked from rtorino/rds_to_docker.md
            
              
                Moving a Postgres db from RDS to a Docker container
              
          
    Make a backup from RDS

pg_dump -h <rds host> -p 5432 -F c -O -U <rds user> <db name> > db.dump

Restore the backup into a Docker container

docker run --rm --interactive --link <postgres container id>:postgres --volume $PWD/:/tmp/ postgres:latest /bin/bash -c 'pg_restore --verbose --clean --no-acl --no-owner -h "$POSTGRES_PORT_5432_TCP_ADDR" -p "$POSTGRES_PORT_5432_TCP_PORT" -U postgres -d <db name> /tmp/db.dump'
	"""
	Plot white noise with added sinusoidal signal
	"""
	import numpy as np
	import matplotlib.pyplot as plt
	import sys
	import h5py

	fs = 4096 # sampling rate [Hz]
	T = 4 # duration [s]
	#!/usr/bin/env python
	# -- coding: UTF-8 --
	import warnings
	import numpy as np
	import pandas as pd
	import sys

	__author__ = "Mohsen Mesgarpour"
	__copyright__ = "Copyright 2016, https://github.com/mesgarpour"
	__credits__ = ["Mohsen Mesgarpour"]
	#-- coding: utf-8 --

	"""
	GIBBS SAMPLING IMPLEMENTATION FOR LATENT DIRICHLET ALLOCATION (2003)
	IMPLEMENTED BY CHANG-UK, PARK
	DATA FORMAT: "DocID\t WordID\t FREQUENCY\n"
	"""

	import sys
	import random
	# This script is designed to work with ubuntu 16.04 LTS
	# with keras 1.2.2 and the latest Pytorch with CUDA 8 support
	##########################################################################
	#This is used to install CUDA 8 driver for Tesla K80
	##########################################################################

	#!/bin/bash
	echo "Checking for CUDA and installing."
	# Check for CUDA and try to install.
	if ! dpkg-query -W cuda-8-0; then
	from random import choice
	from scrapy import signals
	from scrapy.exceptions import NotConfigured


	class RotateUserAgentMiddleware(object):
	"""Rotate user-agent for each request."""
	def __init__(self, user_agents):
	self.enabled = False
	self.user_agents = user_agents
	// LRUCache.js - super simple JavaScript Implementation
	// LRU stands for "Least Recently Used"
	// https://en.wikipedia.org/wiki/Cache_replacement_policies#LRU

	// -----------------------------------------

	function LRUNode(key) {
	this.key = key;
	this.next = this.prev = null;
	}
	import { graphql } from 'react-apollo';
	import { connect } from 'react-redux';
	import { compose } from 'redux';

	import {
	change,
	getFormSubmitErrors,
	getFormValues,
	reduxForm,
	stopAsyncValidation,
	object MindBlown extends App {
	trait Monoid[A] {
	def op(a1: A, a2: A): A
	def zero: A
	}

	val intAddition = new Monoid[Int] {
	override def op(a1: Int, a2: Int) = a1 + a2
	override def zero = 0
	}