1. Clumps: First Data Inspection
Simulation Overview
using Mera
info = getinfo(400, "../../testing/simulations/manu_sim_sf_L14");[Mera]: 2020-02-12T20:41:16.814
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 clumps properties is printed:
- existence of clumps files
- the variable names from the header of the clump files
Load Clump Data
Read the Clumps data from all files of the full box with all existing variables. MERA checks the first line of a clump file to find the column names. The identified names give the number of existing columns.
clumps = getclumps(info);[Mera]: Get clump data: 2020-02-12T20:41:23.656
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]
Read 12 colums:
Symbol[:index, :lev, :parent, :ncell, :peak_x, :peak_y, :peak_z, Symbol("rho-"), Symbol("rho+"), :rho_av, :mass_cl, :relevance]
Memory used for data table :61.77734375 KB
-------------------------------------------------------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(clumps);Memory used: 331.672 KBThe assigned object is now of type: ClumpsDataType:
typeof(clumps)ClumpDataTypeIt is a sub-type of ContainMassDataSetType
supertype( ContainMassDataSetType )DataSetTypeContainMassDataSetType is a sub-type of to the super-type DataSetType
supertype( ClumpDataType )ContainMassDataSetTypeThe data is stored as a JuliaDB table and the selected clump variables and parameters are assigned to fields:
viewfields(clumps)data ==> JuliaDB table: (:index, :lev, :parent, :ncell, :peak_x, :peak_y, :peak_z, Symbol("rho-"), Symbol("rho+"), :rho_av, :mass_cl, :relevance)
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)
boxlen = 48.0
ranges = [0.0, 1.0, 0.0, 1.0, 0.0, 1.0]
selected_clumpvars = Symbol[:index, :lev, :parent, :ncell, :peak_x, :peak_y, :peak_z, Symbol("rho-"), Symbol("rho+"), :rho_av, :mass_cl, :relevance]
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 "clumps.info" and the scaling relations from code to cgs units in "clumps.scale". The box length, the selected ranges and number of the clump variables are also retained.
Print the fields of an object (composite type) in a simple list:
propertynames(clumps)(:data, :info, :boxlen, :ranges, :selected_clumpvars, :used_descriptors, :scale)Overview of Clump Data
Get some overview of the data associated with the object clumps. The calculated information can be accessed from the object data_overview (here) in code units for further calculations:
data_overview = dataoverview(clumps)Table with 2 rows, 13 columns:
Columns:
# colname type
───────────────────
1 extrema Any
2 index Any
3 lev Any
4 parent Any
5 ncell Any
6 peak_x Any
7 peak_y Any
8 peak_z Any
9 rho- Any
10 rho+ Any
11 rho_av Any
12 mass_cl Any
13 relevance 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 ":mass_cl" is called a quoted Symbol (see in Julia documentation):
using JuliaDBselect(data_overview, (:extrema, :index, :peak_x, :peak_y, :peak_z, :mass_cl) )Table with 2 rows, 6 columns:
extrema index peak_x peak_y peak_z mass_cl
──────────────────────────────────────────────────────
"min" 4.0 10.292 9.93604 22.1294 0.00031216
"max" 2147.0 38.1738 35.7056 25.4634 0.860755Get an array from the column ":masscl" in `dataoverviewand scale it to the unitsMsol`. The order of the calculated data is consistent with the table above:
select(data_overview, :mass_cl) * info.scale.Msol2-element Array{Float64,1}:
312073.3187055649
8.605166312657958e8Or simply convert the :mass_cl data in the table to Msol units by manipulating the column:
data_overview = transform(data_overview, :mass_cl => :mass_cl => value->value * info.scale.Msol);select(data_overview, (:extrema, :index, :peak_x, :peak_y, :peak_z, :mass_cl) )Table with 2 rows, 6 columns:
extrema index peak_x peak_y peak_z mass_cl
─────────────────────────────────────────────────────
"min" 4.0 10.292 9.93604 22.1294 3.12073e5
"max" 2147.0 38.1738 35.7056 25.4634 8.60517e8Data Inspection
The data is associated with the field clumps.data as a JuliaDB table (code units). Each row corresponds to a clump 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 positions peakx, peaky,peak_z are the positions and should not be modified.
clumps.dataTable with 644 rows, 12 columns:
Columns:
# colname type
──────────────────────
1 index Float64
2 lev Float64
3 parent Float64
4 ncell Float64
5 peak_x Float64
6 peak_y Float64
7 peak_z Float64
8 rho- Float64
9 rho+ Float64
10 rho_av Float64
11 mass_cl Float64
12 relevance Float64A more detailed view into the data:
select(clumps.data, (:index, :peak_x, :peak_y, :peak_z, :mass_cl) )Table with 644 rows, 5 columns:
index peak_x peak_y peak_z mass_cl
─────────────────────────────────────────────
4.0 20.1094 11.5005 23.9604 0.0213767
5.0 20.1592 11.5122 23.9253 0.0131504
9.0 21.7852 17.855 23.814 0.00358253
12.0 21.8232 17.8608 23.855 0.00509792
13.0 21.8906 17.2837 23.5415 0.0319414
18.0 21.7822 16.8823 23.7817 0.00848828
19.0 21.75 16.8589 23.7993 0.00587003
20.0 21.6006 17.5679 23.7935 0.0324672
25.0 21.5801 17.6177 23.9341 0.0245806
26.0 21.5859 17.5796 23.9165 0.0183601
29.0 21.5625 17.5854 23.8726 0.0303356
46.0 21.5215 17.6235 23.9458 0.343594
⋮
2115.0 27.7705 13.2788 23.8081 0.0340939
2116.0 27.7617 13.3081 23.8081 0.0145199
2117.0 27.7793 13.2993 23.6851 0.00855992
2120.0 27.7559 13.1792 23.8638 0.00508007
2125.0 27.7939 13.0298 23.9194 0.00128829
2128.0 27.791 13.0649 23.9019 0.00183979
2131.0 28.3037 12.8188 23.9487 0.00128627
2132.0 28.626 12.8188 23.8755 0.00434
2137.0 29.9736 15.0571 23.7202 0.00195464
2140.0 27.1436 15.6401 23.9048 0.0160477
2147.0 25.1953 9.93604 23.9897 0.0294943