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# Derived from https://github.com/docker-library/julia which is distributed
# under the terms of the MIT Expat license and is
# Copyright (c) 2014-2015 Docker, Inc.
FROM ubuntu:trusty-20171117
# FROM ubuntu:xenial-20171114
# FROM ubuntu:zesty-20171114
# FROM ubuntu:artful-20171116
# FROM debian:jessie
# FROM ubuntu:trusty-20171117
# FROM ubuntu:xenial-20171114
# FROM ubuntu:zesty-20171114
FROM ubuntu:artful-20171116
# FROM debian:jessie
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
ca-certificates \
curl

Install IRIS at the inner-ellipsoid branch:

  git clone https://github.com/rdeits/iris-distro
  cd iris-distro
  git checkout inner-ellipsoid
  mkdir build
  cd build
  cmake .. -DPYTHON_EXECUTABLE=/path/to/python
 make
WARNING: An error occurred during inference. Type inference is now partially disabled.
Base.MethodError(f=typeof(Core.Inference.convert)(), args=(Base.AssertionError, "invalid age range update"), world=0x0000000000000ac2)
rec_backtrace at /Users/osx/buildbot/slave/package_osx10_9-x64/build/src/stackwalk.c:84
record_backtrace at /Users/osx/buildbot/slave/package_osx10_9-x64/build/src/task.c:245 [inlined]
jl_throw at /Users/osx/buildbot/slave/package_osx10_9-x64/build/src/task.c:564
jl_method_error_bare at /Users/osx/buildbot/slave/package_osx10_9-x64/build/src/gf.c:1478
jl_method_error at /Users/osx/buildbot/slave/package_osx10_9-x64/build/src/gf.c:1496
jl_lookup_generic_ at /Users/osx/buildbot/slave/package_osx10_9-x64/build/src/gf.c:1910
jl_apply_generic at /Users/osx/buildbot/slave/package_osx10_9-x64/build/src/gf.c:1930
Type at ./coreimg.jl:14
@rdeits
rdeits / director_python_vis.md
Created June 17, 2017 03:07
3D Visualizations from Python using Director

(for the Julia version of this code, check out the demo.ipynb notebook in https://github.com/rdeits/DrakeVisualizer.jl)

Installation

Easy: Pre-built binaries

Pre-built binary versions of Director are available from http://people.csail.mit.edu/patmarion/software/director/releases/. All of the features described here are known to work with version 0.1.0-35-g26aa674 but newer versions should work too. Just download the appropriate file for your operating system and extract the files.

Harder: Build from source

using JuMP
using SCS
using Gurobi
# Objective is min. 1/2 x'Qx + q'x
Q = [1 0.1; 0.1 1]
q = [-3., 4]
## Solve with SCS
m = Model(solver=SCSSolver())
"""
@wrappedallocs(expr)
Given an expression, this macro wraps that expression inside a new function
which will evaluate that expression and measure the amount of memory allocated
by the expression. Wrapping the expression in a new function allows for more
accurate memory allocation detection when using global variables (e.g. when
at the REPL).
For example, `@wrappedallocs(x + y)` produces:
import forcespro as fp
import numpy as np
NUM_FRICTION_CONE_BASIS_VECTORS = 4
stages = fp.MultistageProblem(1)
stages.dims[0]['n'] = NUM_FRICTION_CONE_BASIS_VECTORS # dimension of decision variables
stages.dims[0]['r'] = 0 # number of eq constraints
stages.dims[0]['l'] = NUM_FRICTION_CONE_BASIS_VECTORS # number of lower bounds
stages.dims[0]['u'] = 0 # number of upper bounds