I hereby claim:
- I am claymcleod on github.
- I am clmcleod (https://keybase.io/clmcleod) on keybase.
- I have a public key ASAq3m8EC04REjVlhiiWoN_TyW6Exl2ZpR3387VQewzG4go
To claim this, I am signing this object:
import sys,os | |
import curses | |
def draw_menu(stdscr): | |
k = 0 | |
cursor_x = 0 | |
cursor_y = 0 | |
# Clear and refresh the screen for a blank canvas | |
stdscr.clear() |
#! /usr/bin/env python | |
# -*- coding: utf-8 -*- | |
# | |
# This file presents an interface for interacting with the Playstation 4 Controller | |
# in Python. Simply plug your PS4 controller into your computer using USB and run this | |
# script! | |
# | |
# NOTE: I assume in this script that the only joystick plugged in is the PS4 controller. | |
# if this is not the case, you will need to change the class accordingly. | |
# |
# Title: Regular Expressions with Python | |
# Authors: Clay McLeod | |
# Description: Shows you how to find all instances of a regular expression | |
# in a string | |
# Section: Python | |
# Subsection: General | |
# | |
# Python docs on Regex: https://docs.python.org/2/howto/regex.html | |
# | |
# Notes: |
I hereby claim:
To claim this, I am signing this object:
# Title: Randomized Algorithm (Median) | |
# Authors: Clay McLeod | |
# Description: A randomized algorithm for finding the median of an array. | |
# Section: Python | |
# Subsection: Interesting Problems | |
import sys | |
import math | |
import random |
#!/usr/bin/python | |
# Title: Reddit Data Mining Script | |
# Authors: Clay McLeod | |
# Description: This script mines JSON data | |
# from the Reddit front page and stores it | |
# as a CSV file for analysis. | |
# Section: Python | |
# Subsection: Data Science | |
want=["domain", "subreddit", "subreddit_id" "id", "author", "score", "over_18", "downs", "created_utc", "ups", "num_comments"] |
# Title: Simple Ruby Datamining Example | |
# Authors: Clay McLeod | |
# Description: Mines data every minute concerning how many people are logged into a certain subreddit. | |
# Section: Ruby | |
# Subsection: Data Science | |
require 'csv' | |
require 'rubygems' | |
require 'nokogiri' | |
require 'rest-client' |
#!/bin/bash | |
useage() { | |
printf "\n\e[1;4mAscii Escape Code Helper Utility\e[m\n\n" | |
printf " \e[1mUseage:\e[m colors.sh [-|-b|-f|-bq|-fq|-?|?] [start] [end] [step]\n\n" | |
printf "The values for the first parameter may be one of the following:\n\n" | |
printf " \e[1m-\e[m Will result in the default output.\n" | |
printf " \e[1m-b\e[m This will display the 8 color version of this chart.\n" | |
printf " \e[1m-f\e[m This will display the 256 color version of this chart using foreground colors.\n" | |
printf " \e[1m-q\e[m This will display the 256 color version of this chart without the extra text.\n" |
# Setup | |
import os | |
import sys | |
from keras.models import Sequential | |
from keras.layers.core import Dense, Dropout, Activation, Flatten | |
from keras.layers.convolutional import Convolution2D, MaxPooling2D | |
from keras.preprocessing.image import ImageDataGenerator | |
from keras.layers.advanced_activations import Quorum | |
from keras.datasets import mnist |
# Get kernel source | |
apt-get source linux-image-$(uname -r) | |
# Download kernel build tools | |
sudo apt-get install libncurses5-dev kernel-package | |
sudo apt-get build-dep linux-image-$(uname -r) | |
# Change the directory to the Linux source directory | |
cd /usr/src/linux-..... |