1. Particles: First Data Inspection
Simulation Overview
using Mera
#info = getinfo(1, "../../testing/simulations/manu_stable_2019");
info = getinfo(400, "../../testing/simulations/manu_sim_sf_L14"); [Mera]: 2020-02-12T20:40:36.118
Code: RAMSES
output [400] summary:
mtime: 2018-09-05T09:51:55.041
ctime: 2019-11-01T17:35:21.051
=======================================================
simulation time: 594.98 [Myr]
boxlen: 48.0 [kpc]
ncpu: 2048
ndim: 3
-------------------------------------------------------
amr: true
level(s): 6 - 14 --> cellsize(s): 750.0 [pc] - 2.93 [pc]
-------------------------------------------------------
hydro: true
hydro-variables: 7 --> (:rho, :vx, :vy, :vz, :p, :var6, :var7)
hydro-descriptor: (:density, :velocity_x, :velocity_y, :velocity_z, :thermal_pressure, :passive_scalar_1, :passive_scalar_2)
γ: 1.6667
-------------------------------------------------------
gravity: true
gravity-variables: (:epot, :ax, :ay, :az)
-------------------------------------------------------
particles: true
- Npart: 5.091500e+05
- Nstars: 5.066030e+05
- Ndm: 2.547000e+03
particle variables: (:vx, :vy, :vz, :mass, :birth)
-------------------------------------------------------
clumps: true
clump-variables: (:index, :lev, :parent, :ncell, :peak_x, :peak_y, :peak_z, Symbol("rho-"), Symbol("rho+"), :rho_av, :mass_cl, :relevance)
-------------------------------------------------------
namelist-file: false
timer-file: false
compilation-file: true
makefile: true
patchfile: true
=======================================================A short overview of the loaded particle properties is printed:
- existence of particle files
- the predefined variables
- the number of particles for each id/family (if exist)
- the variable names from the descriptor file (if exist)
The functions in Mera "know" the predefined particle variable names:
- From >= ramses-version-2018: :vx, :vy, :vz, :mass, :family, :tag, :birth, :metals :var9,....
- For =< ramses-version-2017: :vx, :vy, :vz, :mass, :birth, :var6, :var7,....
- Currently, the following variables are loaded by default (if exist): :level, :x, :y, :z, :id, :family, :tag.
- The cpu number associated with the particles can be loaded with the variable names: :cpu or :varn1
- In a future version the variable names from the particle descriptor can be used by setting the field info.descriptor.useparticles = true .
Get an overview of the loaded particle properties:
viewfields(info.part_info) [Mera]: Particle overview
===============================
eta_sn = 0.0
age_sn = 0.6706464407596582
f_w = 0.0
Npart = 509150
Ndm = 2547
Nstars = 506603
Nsinks = 0
Ncloud = 0
Ndebris = 0
Nother = 0
Nundefined = 0
other_tracer1 = 0
debris_tracer = 0
cloud_tracer = 0
star_tracer = 0
other_tracer2 = 0
gas_tracer = 0Load AMR/Particle Data
Read the AMR and the Particle data from all files of the full box with all existing variables and particle positions:
particles = getparticles(info); [Mera]: Get particle data: 2020-02-12T20:40:36.139
Key vars=(:level, :x, :y, :z, :id)
Using var(s)=(1, 2, 3, 4, 5) = (:vx, :vy, :vz, :mass, :birth)
domain:
xmin::xmax: 0.0 :: 1.0 ==> 0.0 [kpc] :: 48.0 [kpc]
ymin::ymax: 0.0 :: 1.0 ==> 0.0 [kpc] :: 48.0 [kpc]
zmin::zmax: 0.0 :: 1.0 ==> 0.0 [kpc] :: 48.0 [kpc]
Reading data...100%|████████████████████████████████████| Time: 0:00:03
Found 5.089390e+05 particles
Memory used for data table :34.947275161743164 MB
-------------------------------------------------------The memory consumption of the data table is printed at the end. We provide a function which gives the possibility to print the used memory of any object:
usedmemory(particles);Memory used: 35.211 MBThe assigned object is now of type PartDataType:
typeof(particles)PartDataTypeIt is a sub-type of ContainMassDataSetType
supertype( ContainMassDataSetType )DataSetTypeContainMassDataSetType is a sub-type of to the super-type DataSetType
supertype( PartDataType )HydroPartTypeThe data is stored in a JuliaDB table and the user selected particle variables and parameters are assigned to fields:
viewfields(particles) data ==> JuliaDB table: (:level, :x, :y, :z, :id, :vx, :vy, :vz, :mass, :birth)
info ==> subfields: (:output, :path, :fnames, :simcode, :mtime, :ctime, :ncpu, :ndim, :levelmin, :levelmax, :boxlen, :time, :aexp, :H0, :omega_m, :omega_l, :omega_k, :omega_b, :unit_l, :unit_d, :unit_m, :unit_v, :unit_t, :gamma, :hydro, :nvarh, :nvarp, :variable_list, :gravity_variable_list, :particles_variable_list, :clumps_variable_list, :sinks_variable_list, :descriptor, :amr, :gravity, :particles, :clumps, :sinks, :rt, :namelist, :namelist_content, :headerfile, :makefile, :files_content, :timerfile, :compilationfile, :patchfile, :Narraysize, :scale, :grid_info, :part_info, :compilation, :constants)
lmin = 6
lmax = 14
boxlen = 48.0
ranges = [0.0, 1.0, 0.0, 1.0, 0.0, 1.0]
selected_partvars = Symbol[:level, :x, :y, :z, :id, :vx, :vy, :vz, :mass, :birth]
scale ==> subfields: (:Mpc, :kpc, :pc, :mpc, :ly, :Au, :km, :m, :cm, :mm, :μm, :Msol_pc3, :g_cm3, :Msol_pc2, :g_cm2, :Gyr, :Myr, :yr, :s, :ms, :Msol, :Mearth, :Mjupiter, :g, :km_s, :m_s, :cm_s, :nH, :erg, :g_cms2, :T_mu, :Ba)For convenience, all the fields from the info-object above (InfoType) are now also accessible from the object with "particles.info" and the scaling relations from code to cgs units in "particles.scale".
Print the fields of an object (composite type) in a simple list:
propertynames(particles)(:data, :info, :lmin, :lmax, :boxlen, :ranges, :selected_partvars, :used_descriptors, :scale)Overview of AMR/Particles
Get an overview of the AMR structure associated with the object particles (PartDataType). The printed information is stored into the object overview_amr as a JuliaDB table (code units) and can be used for further calculations:
amr_overview = amroverview(particles)Counting...
Table with 9 rows, 2 columns:
level particles
────────────────
6 2867
7 11573
8 56209
9 118156
10 115506
11 77303
12 49300
13 31859
14 46166Get some overview of the data that is associated with the object particles. The calculated information can be accessed from the object data_overview (here) in code units for further calculations:
data_overview = dataoverview(particles)Table with 9 rows, 19 columns:
Columns:
# colname type
───────────────────
1 level Any
2 x_min Any
3 x_max Any
4 y_min Any
5 y_max Any
6 z_min Any
7 z_max Any
8 id_min Any
9 id_max Any
10 vx_min Any
11 vx_max Any
12 vy_min Any
13 vy_max Any
14 vz_min Any
15 vz_max Any
16 mass_min Any
17 mass_max Any
18 birth_min Any
19 birth_max AnyIf the number of columns is relatively long, the table is typically represented by an overview. To access certain columns, use the select function. The representation ":birth_max" is called a quoted Symbol (see in Julia documentation):
using JuliaDBselect(data_overview, (:level,:mass_min, :mass_max, :birth_min, :birth_max ) )Table with 9 rows, 5 columns:
level mass_min mass_max birth_min birth_max
───────────────────────────────────────────────────
6 1.13606e-5 1.13606e-5 4.54194 38.2611
7 1.13606e-5 1.13606e-5 4.35262 38.6822
8 1.13606e-5 2.27212e-5 4.30782 39.2733
9 1.13606e-5 2.27212e-5 4.39811 39.397
10 1.13606e-5 2.27212e-5 4.29246 39.6783
11 1.13606e-5 2.27212e-5 4.36385 39.744
12 1.13606e-5 2.27212e-5 4.51187 39.8358
13 4.99231e-6 2.27212e-5 4.47027 39.883
14 4.91416e-6 2.27212e-5 5.2582 39.902Get an array from the column ":birth" in data_overview and scale it to the units Myr. The order of the calculated data is consistent with the table above:
column(data_overview, :birth_min) * info.scale.Myr9-element Array{Float64,1}:
67.72475450854526
64.901905404619
64.23377578948651
65.58011000778922
64.00484282690913
65.06931266062217
67.27645257301232
66.6561171130916
78.40495776518468Or simply convert the birth_max data in the table to Myr units by manipulating the column:
data_overview = transform(data_overview, :birth_max => :birth_max => value->value * info.scale.Myr);select(data_overview, (:level,:mass_min, :mass_max, :birth_min, :birth_max ) )Table with 9 rows, 5 columns:
level mass_min mass_max birth_min birth_max
───────────────────────────────────────────────────
6 1.13606e-5 1.13606e-5 4.54194 570.511
7 1.13606e-5 1.13606e-5 4.35262 576.79
8 1.13606e-5 2.27212e-5 4.30782 585.604
9 1.13606e-5 2.27212e-5 4.39811 587.448
10 1.13606e-5 2.27212e-5 4.29246 591.643
11 1.13606e-5 2.27212e-5 4.36385 592.623
12 1.13606e-5 2.27212e-5 4.51187 593.991
13 4.99231e-6 2.27212e-5 4.47027 594.694
14 4.91416e-6 2.27212e-5 5.2582 594.977Data inspection
The data is associated with the field particles.data as a JuliaDB table (code units). Each row corresponds to a particle and each column to a property which makes it easy to find, filter, map, aggregate, group the data, etc. More information can be found in the Mera tutorials or in: JuliaDB API Reference
Table View
The particle positions x,y,z are given in code units and used in many functions of MERA and should not be modified.
particles.dataTable with 508939 rows, 10 columns:
Columns:
# colname type
────────────────────
1 level Int32
2 x Float64
3 y Float64
4 z Float64
5 id Int32
6 vx Float64
7 vy Float64
8 vz Float64
9 mass Float64
10 birth Float64A more detailed view into the data:
select(particles.data, (:level,:x, :y, :z, :birth) )Table with 508939 rows, 5 columns:
level x y z birth
────────────────────────────────────────────
6 0.00462947 22.3885 24.571 32.0735
6 0.109066 22.3782 21.5844 19.8963
6 0.238211 28.7537 24.8191 24.9471
6 0.271366 22.7512 31.5681 20.9888
6 0.312574 16.2385 23.7591 23.0935
6 0.314957 28.2084 30.966 31.6911
6 0.328337 4.59858 23.5001 30.3666
6 0.420712 27.6688 26.5735 18.9512
6 0.509144 33.1737 23.9789 24.3613
6 0.565516 25.9409 26.0579 32.7551
6 0.587289 9.60231 23.8477 29.6981
6 0.592878 25.5519 21.3079 15.9204
⋮
14 37.6271 25.857 23.8833 36.7754
14 37.6299 25.8403 23.9383 36.0289
14 37.6301 25.8502 23.9361 38.7225
14 37.6326 25.8544 23.9383 36.3547
14 37.6528 25.8898 23.9928 38.2109
14 37.6643 25.9061 23.9945 39.49
14 37.6813 25.8743 23.9789 36.6981
14 37.7207 25.8623 23.8775 38.6107
14 38.173 25.8862 23.7978 33.0212
14 38.1738 25.8914 23.7979 35.2712
14 38.1739 25.8905 23.7992 34.4097