Will Ware wware

OpenSCAD on the Linux box is faster than on the Macbook, I think, but it won't do recursion. Recursion must be done in Python. So the Sierpinski code must be rewritten as a Python script or an exercise in SolidPython that generates OpenSCAD.

The Linux version of OpenSCAD has a few other differences. Cylinders (and possibly spheres) don't support diameter arguments, only radius arguments. Anyway, I'm adding a Python script to perform the recursion and produce a flat *.scad file.

Or instead of all this nonsense resulting from the fact that the OpenSCAD in the Ubuntu repository is old and broken, you could just go to the download page and get a version that works correctly.

Git Merge Lore

I'm working at a place where people prefer merges over rebases. In the past I've been influenced by the pro-rebase school of thought, but if there are relatively few pull requests being merged, you can use --no-ff to maintain pretty good clarity, and merge points become the decision point where a pull request has been included or excluded. With that in mind, I want to look at a few relevant use cases.

	from functools import wraps

	# A decorator without an argument.

	def add_four(f):
	@wraps(f)
	def wrapped(x):
	y = f(x)
	return y + 4
	return wrapped

	class LinearRegression:
	"""
	>>> lr = LinearRegression()
	>>> lst = [(0., 0.)]
	>>> lr.add(lst[0][0], lst[0][1])
	>>> lr.get()
	>>> lr.error()
	>>> for nxt in [(1., 1.), (2., 2.), (4., 3.), (-1., -0.5)]:
	... lst.append(nxt)
	... lr.add(nxt[0], nxt[1])

	#!/usr/bin/env python

	"""
	Example usage:
	find . -type f \| head -3000 \| ./suffixes.py
	Use this to build a swish.conf file for swish-e, e.g:
	IndexDir .
	IndexOnly .h .qml .cpp .png .pro .qmlproject .svg .jpg .qdoc .qrc .json .js .sci .xml .pri .desktop .txt
	IndexContents TXT* .h .qml .cpp .png .pro .qmlproject .svg .jpg .qdoc .qrc .json .js .sci .xml .pri .desktop .txt
	"""

	#!/usr/bin/python

	import serial
	import sys
	import select
	import os

	ser=serial.Serial('/dev/ttyUSB0',115200)

	BUF=4096

	import pprint
	import logging


	def about(thang):
	def shorty(x):
	if len(x) > 200:
	x = x[:200] + "..."
	return x
	if isinstance(thang, dict):

	import doctest
	import numpy
	import sys


	def is_vector(x):
	return isinstance(x, numpy.ndarray) and x.shape == (3,)


	def normalize(vec):

	import aifc
	import math
	import sys

	filename = sys.argv[1]

	F_SAMPLE = 40000
	DT = 1. / F_SAMPLE

	class Aiff: