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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:

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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 $@

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/**
   BasicHTTPClient.ino

    Created on: 24.05.2015

*/

#include <Arduino.h>

#include <ESP8266WiFi.h>

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#!/usr/bin/env python

import numpy as np


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

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#!/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)))

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#!/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).

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#!/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

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#!/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)

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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 && \

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#!/usr/bin/env python
#  Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software