A machinaut

Foam Extension Development Quick Start Guide

For OSX, tested on my computer on a monday. YMMV. I started without any node/etc installed.

I never got NVM to work for node versioning, so I defaulted to just using brew node:

	brew install node

And then install yarn and lerna globally:

	#!/usr/bin/env python
	import random
	import time
	from itertools import product
	from ortools.sat.python import cp_model

	# use globals to emulate the server behavior
	current_layout = None
	queryCount = None

	CUDA_PATH ?= /usr/local/cuda

	.PHONY: clean

	vadd.so: vadd.o
	nvcc -shared $^ -o $@ -lcuda

	vadd.o: vadd.cu
	nvcc -I $(CUDA_PATH)/include -I$(CUDA_PATH)/samples/common/inc -arch=sm_70 --compiler-options '-fPIC' $^ -c $@

	#!/usr/bin/env python

	import numpy as np


	'''
	Notes:
	- Tensile strength of 7x19 1/4" galvanized steel wire rope ~ 7000 lbs
	'''

	#!/usr/bin/env python

	import numpy as np
	from collections import OrderedDict
	from scipy.optimize import LinearConstraint, minimize, BFGS


	def normlen(v):
	''' length of norm of a vector '''
	return np.sqrt(np.sum(np.square(v)))

	#!/usr/bin/env python

	import numpy as np
	import matplotlib.pyplot as plt
	from scipy.optimize import minimize

	'''
	Parameterize a solution space so all numbers are valid:
	Solver coordinates are given as arctanh(radius), theta
	Then minimize the inverse average distance (to maximize average distance).

	#!/usr/bin/env python

	from itertools import product

	PROB_MORNING_RAIN = .5
	PROB_EVENING_RAIN = .4


	# Enumerate all possible cases, and sum the probability of getting rained on
	total_probability = 0 # Total probability of getting rained on

	#!/usr/bin/env python

	import os
	import mujoco_py
	import numpy as np

	PATH_TO_HUMANOID_XML = os.path.expanduser('~/.mujoco/mjpro150/model/humanoid.xml')

	# Load the model and make a simulator
	model = mujoco_py.load_model_from_path(PATH_TO_HUMANOID_XML)

	FROM ubuntu:18.04

	# Install python and utils
	RUN apt-get update && apt-get install -y python3-pip curl unzip \
	libosmesa-dev libglew-dev patchelf libglfw3-dev

	# Download mujoco
	RUN curl https://www.roboti.us/download/mjpro150_linux.zip --output /tmp/mujoco.zip && \
	mkdir -p /root/.mujoco && \
	unzip /tmp/mujoco.zip -d /root/.mujoco && \