gizmaa

Plotting

Last Update: May 13, 2019
Offline Version

Contents

• Translating
• Important Note
Basic Plot

aminnj

Execute the commands chunk by chunk because I haven't tested this as a whole

# setup environment
cd /cvmfs/cms.cern.ch/slc7_amd64_gcc630/cms/cmssw/CMSSW_10_2_0_pre6/ ; cmsenv ; cd -

# make containment folder somewhere and get vi
mkdir vim8
cd vim8
git clone https://github.com/vim/vim

aminnj

aminnj

import time
import numpy as np
import pandas as pd
import uproot
from yahist import Hist1D, Hist2D
from pandas.core.base import PandasObject
from cachetools import cached, LRUCache
from cachetools.keys import hashkey

def myhasher(*args, **kwargs):

bencbartlett

# Electromagnetic simulation at varying timescales - simulation code to make this animation:
# https://twitter.com/bencbartlett/status/1369396941730312193
#
# Animation idea was inspired by u/cenit997's (Twitter: @__cenit) Reddit post:
# https://www.reddit.com/r/Python/comments/hxmhai/a_simulation_of_how_an_incoherent_light_source/


#---
using LinearAlgebra, Base.Threads, BenchmarkTools, LoopVectorization, CSV, DataFrames, Printf, Plots

ChrisRackauckas

DiffEqFlux.jl (Julia) vs Jax on an Epidemic Model

The Jax developers optimized a differential equation benchmark in this issue which used DiffEqFlux.jl as a performance baseline. The Julia code from there was updated to include some standard performance tricks and is the benchmark code here. Thus both codes have been optimized by the library developers.

Results

Forward Pass

aminnj

Since writing out ROOT files is currently not possible with UnROOT, one can write out Arrow files directly from an UnROOT.LazyTree object which can be read back in julia. With some consideration of the chunking, this won't use much memory.

using UnROOT
using Arrow
using Tables

treename = "Events"
filename = "18BCCE71-15B8-194B-8738-EC993C8DD3BD.root"

Azzaare

# Add this file to ~/.julia/config/ (mkdir config if necessary)

try
    using Revise
catch e
    @warn "Error initializing Revise: trying install" exception=(e, catch_backtrace())
    using Pkg
    Pkg.add("Revise")
end

jkrumbiegel

@recipe(Barplot3D) do scene
    Attributes(
        color = theme(scene, :markercolor),
        colormap = theme(scene, :colormap),
    )
end

Makie.conversion_trait(::Type{<:Barplot3D}) = Makie.DiscreteSurface()

function Makie.plot!(p::Barplot3D)

oxinabox

#Helpers:
"Given some IR generates a MethodInstance suitable for passing to infer_ir!, if you don't already have one with the right argument types"
function get_toplevel_mi_from_ir(ir, _module::Module)
    mi = ccall(:jl_new_method_instance_uninit, Ref{Core.MethodInstance}, ());
    mi.specTypes = Tuple{ir.argtypes...}
    mi.def = _module
    return mi
end

"run type inference and constant propagation on the ir"