anriseth

anriseth

Script started on Tue 14 Mar 2017 16:49:45 GMT
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++

anriseth

mkdir /scratch/brosa
cd /scratch/brosa
git clone git://github.com/JuliaLang/julia.git
cd julia
git checkout release-0.5
make -j 2
mkdir $HOME/bin
ln -s julia $HOME/bin
# Run julia
$HOME/bin/julia

anriseth

# Ask admin to install the following packages:
# build-essential git libsecret-1-dev fakeroot rpm libx11-dev libxkbfile-dev libgnome-keyring-dev

# When that is done, you can install everything else locally
# Install Node.js
curl -o- https://raw.githubusercontent.com/creationix/nvm/v0.33.2/install.sh | bash
source $HOME/.bashrc
nvm install v6.10.3
nvm use v6.10.3 

anriseth

using Interpolations, Optim
using LaTeXStrings, Plots

function brownsim(T,γ,C,x,amin,amax,Varr,polarr)
    # Dynamics
    # dS_t = -Q(a) dt + σQ(a) dW_t, stopped at zero

    # Solve
    # max \int_0^T aQ(a) dt - CS_T
    #

anriseth

\documentclass{article}
\usepackage{amssymb,amsmath}
\usepackage{filecontents}
\usepackage{url}

\DeclareMathOperator*{\argmax}{arg\,max}
\author{Asbj{\o}rn Nilsen Riseth}
\date{\today}
\title{Optim example: Solve HJB equation}

anriseth

Hi, I'm trying to solve a nonlinear PDE that looks similar to a time-dependent eikonal equation. Can anyone provide me some advise for the best Julia-ecosystem approach to solving it, please?

I'm trying to find $$v:[0,1]\times \mathbb R_{\geq 0}^2$$, such that $$ v_t - \frac{\sigma^2}{2} g^2 v_{gg} - gq_2{\left(\frac{\frac{q_1}{q_2}-v_s}{2}\right)}^2 = 0 $$

With boundary conditions

• $$ v(t,s,g) = -Cs $$ on $${t=0}$$ or $${s=0}$$ or $${g=0}$$.
• $$v_g(t,s,\infty) = 0 $$
• $$v_s(t,\infty,g) = -C $$

anriseth

julia> include("test/runtests.jl")
./general/objective_types.jl
  2.170476 seconds (641.11 k allocations: 34.523 MiB, 0.86% gc time)
Test Summary: | Pass  Total
general       |   21     21
./multivariate/fdtime.jl
#####################
Solver: L-BFGS
Problem: Rosenbrock
f-calls: 77

anriseth

;-- README ---------------------------------------------------------------------
; This AHK file re-maps a Qwerty keyboard into a Dvorak keyboard. This is especially useful when 
; the local computer is limited by corporate security policies to disallow installation of custom 
; software. AHK can be run as a portable app, and this script then remaps the existing keyboard.
; 
; Original script by: ----------------------------------------------------------
; Torben Gundtofte-Bruun, torben@g-b.dk, http://torben.g-b.dk/+
; 
; Amended for UK keyboard by by: -----------------------------------------------
; Asbjørn Nilsen Riseth

anriseth

import pandas as pd
import matplotlib.pyplot as plt
plt.ion()

file_url = 'https://data.london.gov.uk/download/coronavirus--covid-19--deaths/516cc869-179d-4cc7-84a4-2cf2fa2d112f/nhse_daily_announced_deaths_by_region.csv'
df = pd.read_csv(file_url, index_col=[0, 1], parse_dates=[1])
df_grouped = df.groupby(['nhs_england_region', 'date_of_death']).sum()['new_deaths_total'].unstack(0)

df_grouped.ewm(alpha=1/3).mean().plot()