edouardp

TODO

• Create a write-up on how this works

edouardp

class DbProviderHelper
{
    const string AssemblyQualifiedName = "AssemblyQualifiedName";
    const string Name = "Name";
    const string InvariantName = "InvariantName";
    const string Description = "Description";

    internal class FactoryInfo
    {
        public string InvariantName { get; set; }

edouardp

import inspect
def raise_on_none(f):
    arg_spec = inspect.getargspec(f)
    def new_f(*args, **kwargs):
        bound_args = inspect.getcallargs(f, *args, **kwargs)
        if(any([bound_args[a]==None for a in arg_spec.args])):
            raise RuntimeError('Named arg is None')
        if(arg_spec.keywords != None):
            if(any([a==None for a in bound_args[arg_spec.keywords].values()])):
                raise RuntimeError('Keyword arg is None')

edouardp

import inspect

def ignore_unused_args(f):
    arg_spec = inspect.getargspec(f)
    def new_f(*args, **kwargs):
        new_kwargs = {key:kwargs[key] for key in arg_spec.args if key in kwargs}
        return f(*args, **new_kwargs)
    new_f.spec = arg_spec
    return new_f

edouardp

# Assumes you have a np.array((height,width,3), dtype=float) as your HDR image

import numpy as np

f = open("xxx.hdr", "wb")
f.write("#?RADIANCE\n# Made with Python & Numpy\nFORMAT=32-bit_rle_rgbe\n\n")
f.write("-Y {0} +X {1}\n".format(image.shape[0], image.shape[1]))

brightest = np.maximum(np.maximum(image[...,0], image[...,1]), image[...,2])
mantissa = np.zeros_like(brightest)

edouardp

# -- Shapes -------------------------------------------------------------------

class Square:
    def __init__(self, side_length, color):
        self.name = 'square'
        self.side_length = side_length
        self.color = color

class Circle:

edouardp

class UniformGenerator:
    def __init__(self):
        self.uniform = random.uniform

    def next(self):
        return self.uniform(0,1)

def haltonterm(i, base=2):
    h = 0
    fac = 1.0/base