brandonb927

#!/bin/sh

###
# SOME COMMANDS WILL NOT WORK ON macOS (Sierra or newer)
# For Sierra or newer, see https://github.com/mathiasbynens/dotfiles/blob/master/.macos
###

# Alot of these configs have been taken from the various places
# on the web, most from here
# https://github.com/mathiasbynens/dotfiles/blob/5b3c8418ed42d93af2e647dc9d122f25cc034871/.osx

ellisonbg

// Simple IPython Notebook test
// Requires PhantomJS and CasperJS.
// To run:
// 1) Start a notebook server in an empty directory.
// 2) casperjs test_basic.js

var casper = require('casper').create({
    // verbose: true,
    // logLevel: "debug"
});

kevin-keraudren

#!/usr/bin/python

import SimpleITK as sitk
import vtk
import numpy as np
import sys

from vtk.util.vtkConstants import *

filename = sys.argv[1]

shivaram

# Download Spark 1.4 from http://spark.apache.org/downloads.html
# 
# Download the nyc flights dataset as a CSV from https://s3-us-west-2.amazonaws.com/sparkr-data/nycflights13.csv

# Launch SparkR using 
# ./bin/sparkR --packages com.databricks:spark-csv_2.10:1.0.3

# The SparkSQL context should already be created for you as sqlContext
sqlContext
# Java ref type org.apache.spark.sql.SQLContext id 1

Larivact

Serving Flask under a subpath

Your Flask app object implements the __call__ method, which means it can be called like a regular function. When your WSGI container receives a HTTP request it calls your app with the environ dict and the start_response callable. WSGI is specified in PEP 0333. The two relevant environ variables are:

SCRIPT_NAME
The initial portion of the request URL's "path" that corresponds to the application object, so that the application knows its virtual "location". This may be an empty string, if the application corresponds to the "root" of the server.

EderSantana

Code for Keras plays catch blog post

Train

python qlearn.py

Test

1. Generate figures

mrocklin

jfeala

"""
AWS Batch wrapper for Luigi

From the AWS website:

    AWS Batch enables you to run batch computing workloads on the AWS Cloud. 

    Batch computing is a common way for developers, scientists, and engineers 
    to access large amounts of compute resources, and AWS Batch removes the 
    undifferentiated heavy lifting of configuring and managing the required 

oarriaga

from keras.layers.core import Layer
import keras.backend as K

if K.backend() == 'tensorflow':
    import tensorflow as tf
    def K_arange(start, stop=None, step=1, dtype='int32'):
        result = tf.range(start, limit=stop, delta=step, name='arange')
        if dtype != 'int32':
            result = K.cast(result, dtype)
        return result

yocontra

AOE2HD - For Mac OSX

Estimated time: 10 minutes

Purchase

• Sign in and purchase the game for $19.99

Installing PortingKit