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SPHtoGrid

Package to map SPH particle data to a cartesian grid

https://github.com/ludwigboess/sphtogrid.jl

Science Score: 49.0%

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    Found 1 DOI reference(s) in README
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    Scientific vocabulary similarity
    Low similarity (9.2%) to scientific vocabulary
Last synced: 7 months ago · JSON representation

Repository

Package to map SPH particle data to a cartesian grid

Basic Info
  • Host: GitHub
  • Owner: LudwigBoess
  • License: gpl-3.0
  • Language: Julia
  • Default Branch: master
  • Homepage:
  • Size: 16.4 MB
Statistics
  • Stars: 6
  • Watchers: 2
  • Forks: 2
  • Open Issues: 1
  • Releases: 22
Created almost 6 years ago · Last pushed 10 months ago
Metadata Files
Readme License Zenodo

README.md

| Documentation | Build Status | Licence |Citation | |:-----------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------:| :-----------------------------------------------------------------------------------------------:| :-----------------------------------------------------------------------------------------------:| | Build Status codecov.io | License: GPL v3 | DOI |

SPHtoGrid.jl

This package maps SPH quantities to a cartesian grid or a healpix sphere. It is based on Smac by Klaus Dolag und Smac2 by Julius Donnert.

Please see the Documentation for details.

Quickstart

You can map SPH data to a grid using the function sphMapping:

```julia function sphMapping(Pos::Array{<:Real}, HSML::Array{<:Real}, M::Array{<:Real}, Rho::Array{<:Real}, BinQuant::Array{<:Real}, Weights::Array{<:Real}=Rho; param::mappingParameters, kernel::AbstractSPHKernel, showprogress::Bool=true, parallel::Bool=false, reduceimage::Bool=true, returnbothmaps::Bool=false, dimensions::Int=2, calcmean::Bool=false, sort_z::Bool=false)

[...]

end ```

Define parameters for mapping

To map the data you need to define the mapping parameters via the mappingParameters object. One way to set this up is by defining the limits of the map as

julia par = mappingParameters(xlim=[xmin, xmax], ylim=[ymin, ymax], zlim=[zmin, zmax], Npixels=200)

or give a center position and the size in each direction

julia par = mappingParameters(center=[x0, y0, z0], x_size=x_size, y_size=y_size, z_size=z_size, Npixels=200)

Instead of Npixels you can also give the keyword argument pixelSideLength if you prefer to define your image that way.

Select Kernel

You also need to choose the kernel you used in the simulation. For this you need to install the package SPHKernels.jl. You can currently use these kernels:

julia k = Cubic() k = Quintic() k = WendlandC4() k = WendlandC6() k = WendlandC8()

Please see the SPHKernels docs for more details.

Mapping

With the setup done you can now map (e.g.) density of your data using the function above as:

julia image = sphMapping(x, hsml, m, rho, rho, param=par, kernel=k)

Replacing the second rho with any other quantity would map that quantity of course. Please note: This function doesn't do any unit conversion for you, so you need to convert to the desired units beforehand. You can do this e.g. with GadgetUnits.jl.

Image now contains a 2D array with the binned data and can easily be plotted with imshow() from any plotting package of your choosing.

The keyword parallel = true causes the run to use multiple processors. For this you need to start julia with julia -p <N> where <N> is the number of processors in your machine, or define

```julia using Distributed addprocs(8)

now you can load SPHtoGrid

using SPHtoGrid ```

Conserved quantities

Particles are mapped to a grid while also conserving the particle volume, following the algorithm described in Dolag et. al. 2006.

Owner

  • Name: Ludwig
  • Login: LudwigBoess
  • Kind: user
  • Location: Munich

I'm a PhD student at the University Observatory Munich working on cosmological MHD simulations.

GitHub Events

Total
  • Create event: 4
  • Commit comment event: 2
  • Release event: 1
  • Delete event: 2
  • Issue comment event: 3
  • Push event: 7
  • Pull request event: 3
Last Year
  • Create event: 4
  • Commit comment event: 2
  • Release event: 1
  • Delete event: 2
  • Issue comment event: 3
  • Push event: 7
  • Pull request event: 3

Committers

Last synced: about 3 years ago

All Time
  • Total Commits: 304
  • Total Committers: 6
  • Avg Commits per committer: 50.667
  • Development Distribution Score (DDS): 0.405
Top Committers
Name Email Commits
LudwigBoess l****s@u****e 181
Ludwig Boess d****g@c****e 79
Ludwig 3****s@u****m 17
Ludwig Böss l****s@o****e 11
github-actions[bot] 4****]@u****m 11
Julia Package Butler 5
Committer Domains (Top 20 + Academic)
outlook.de: 1 c2paplogin.cos.lrz.de: 1 usm.lmu.de: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 10
  • Total pull requests: 122
  • Average time to close issues: 6 months
  • Average time to close pull requests: 14 days
  • Total issue authors: 2
  • Total pull request authors: 5
  • Average comments per issue: 4.1
  • Average comments per pull request: 0.51
  • Merged pull requests: 91
  • Bot issues: 0
  • Bot pull requests: 42
Past Year
  • Issues: 0
  • Pull requests: 7
  • Average time to close issues: N/A
  • Average time to close pull requests: 6 days
  • Issue authors: 0
  • Pull request authors: 3
  • Average comments per issue: 0
  • Average comments per pull request: 0.57
  • Merged pull requests: 7
  • Bot issues: 0
  • Bot pull requests: 2
View more stats
Top Authors
Issue Authors
  • LudwigBoess (9)
  • JuliaTagBot (1)
Pull Request Authors
  • LudwigBoess (81)
  • github-actions[bot] (39)
  • lucasvalenzuela (4)
  • dependabot[bot] (2)
  • stevengj (1)
Top Labels
Issue Labels
enhancement (6) bug (2) documentation (1) help wanted (1)
Pull Request Labels
dependencies (2) github_actions (2)

Packages

  • Total packages: 1
  • Total downloads:
    • julia 4 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 22
juliahub.com: SPHtoGrid

Package to map SPH particle data to a cartesian grid

  • Versions: 22
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 4 Total
Rankings
Dependent repos count: 9.9%
Average: 36.8%
Dependent packages count: 38.9%
Forks count: 40.4%
Stargazers count: 58.1%
Last synced: 8 months ago

Dependencies

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