oshea00

# Saturday #
===
    >If you knew you could not fail, what would you do?

oshea00

//Just a quick code snippet. I was interested in executing javascript from C#. So far, the two clear winners for a framework to do this are JInt and Jurrasic.  Needless to say, the V8 Javascript.Net project is dead and doesn't even try to pretend otherwise...
//JScript .Net has been dead a long time - let's not even go there.

//Jurassic takes a bit more effort to integrate existing .Net objects into scripts as parameters, but makes perhaps is faster.

//JInt is the easiest to use and integrate (takes objects directly as parameters) - and for quick DSL-like scripting using Javascript - wins my vote.

using Jint;
using Jurassic;
using Newtonsoft.Json;

oshea00

// Add this to LinqPad "C# Program"
//  Example use:
//  Insead of this: (create a List<CS_POSITION>)
//  CS_POSITIONs.InsertOnSubmit(position);  
//  This:
//  positions.Add(position);
//  
//  Then instead of this:
//  SubmitChanges()
//  This:

oshea00

void Main()
{
	var g = new Grid();
	var w = new Window { Width = 420, Height = 440, Title = "Graph", Content = g};
	var c = new Canvas { Background = Brushes.BlanchedAlmond };

	DrawLine(200,10,200,390,c);
	DrawLine(10,200,390,200,c);
	
	double x1 = 150;

oshea00

// flips.cpp : Defines the entry point for the console application.
//
#include "time.h"
#include "stdio.h"
#include "stdlib.h"

double f(int, int *i, int *hist);

int main(int argc, char* argv[] )
{

oshea00

// flipfunc.c : Flips a coin

#include "time.h"
#include "stdio.h"
#include "stdlib.h"

double f(int, int *i, int *hist);

// Input: flips - how many times to flip the coin.
// Output:

oshea00

import math

def isprime(n):
    if n == 2:
        return True
    if n == 3:
        return True
    if n % 2 == 0:
        return False
    if n % 3 == 0:

oshea00

months = [0, 6, 2, 2, 5, 0, 3, 5, 1, 4, 6, 2, 4]

def centuryOffset(c):
    if c / 100 == 21:
        return -2
    if c / 100 == 20:
        return 0
    if c / 100 == 19:
        return 1

oshea00

import numpy as np
from math import sqrt

scaling = False

# Implements Kabsch algorithm - best fit.
# Supports scaling (umeyama)
# Compares well to SA results for the same data.
# Input:
#     Nominal  A Nx3 matrix of points

oshea00

import io

f = open('somefile.txt','w')
freq = 2

rows = []
rows.append('row a')
rows.append('row b')
rows.append('row c')
rows.append('row d')