meggart

using Dagger


struct PartialShard
    chunks::Dict{Dagger.Processor,Tuple{Dagger.Chunk,Dagger.Chunk}}
end


function partialshard(@nospecialize(f); procs=nothing, workers=nothing, per_thread=false)
    if procs === nothing

meggart

import Interpolations
import Dierckx

function interpolate_data(tsteps_old, tsteps_new, y, options)
  # Apply interpolation according to the options
  y_interp = if options.interpolation_method == "Dierckx"

    if options.boundary_condition == "flat"
      s = Dierckx.Spline1D(tsteps_old,y,bc="nearest")
      s(tsteps_new)

meggart

module SphericalHarmonics
using FastTransforms
import Geodesy: LLA,distance


immutable PLM{T}
  coefs::Matrix{T}
end
function lm2ij(l,m)
  l<0 && throw(BoundsError("l must be positive"))

meggart

using DimensionalData
using GeoData

# Functions to be extended
"""
    gridcoordinates(::Gridtype,x)

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meggart

import Tokenize.Tokens: IDENTIFIER, LSQUARE, COMMA, RSQUARE, STRING, ENDMARKER
function parsetokens(t,ar)
if t[1].kind==Tokenize.Tokens.IDENTIFIER
    @assert t[2].kind==LSQUARE
    brackcount=1
    i=3
    while true
        t[i].kind==LSQUARE && (brackcount=brackcount+1)
        t[i].kind==RSQUARE && (brackcount=brackcount-1)
        brackcount==0 && break

meggart

FROM jupyter/datascience-notebook:eb149a8c333a

MAINTAINER [email protected]
LABEL version='0.6.1'

USER root
RUN sudo apt-get update && sudo apt-get upgrade -y
RUN sudo apt-get install -y git unzip apt-utils vim

ADD start.sh /usr/local/bin/start.sh

meggart

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import numpy.fft as fft\n",

meggart

meggart

"""
    broadcast_reduce(f,op,v0,A,Bs...)

Should behave like mapreduce, with the only difference that singleton dimension are expanded like in broadcast.
"""
function broadcast_reduce(f,op,v0,A,Bs...)
    shape = Base.Broadcast.broadcast_indices(A,Bs...)
    iter = CartesianRange(shape)
    keeps, Idefaults = Base.Broadcast.map_newindexer(shape, A, Bs)
    _broadcast_reduce(f,op,v0,keeps,Idefaults,A, Bs,Val{length(Bs)}(),iter)