Hydro Data: Load Selected Variables and Spatial Ranges

This notebook provides a comprehensive guide to selective data loading and spatial filtering in Mera.jl. You'll learn advanced techniques for efficiently loading only the data you need from large hydrodynamic simulations.

Learning Objectives

Master selective variable loading for memory optimization
Apply spatial filtering and region selection techniques
Work with different coordinates and units
Understand center-relative coordinate systems
Optimize data loading for large simulations

Quick Reference: Data Selection Functions

This section provides a comprehensive reference of Mera.jl functions for selective data loading and spatial filtering.

Variable Selection

# Load all variables (default behavior)
gas = gethydro(info)

# Select specific variables by name
gas = gethydro(info, vars=[:rho, :p, :vx])            # Density, pressure, x-velocity
gas = gethydro(info, vars=[:var1, :var5, :var2])      # Using variable numbers

# Select variables without keyword (order matters: info, variables)
gas = gethydro(info, [:rho, :p])                      # Multiple variables
gas = gethydro(info, :vx)                             # Single variable

# Common variable names and numbers
# :varn1 or :cpu  → CPU number (= -1)
# :var1 or :rho   → Density
# :var2 or :vx    → X-velocity
# :var3 or :vy    → Y-velocity
# :var4 or :vz    → Z-velocity
# :var5 or :p     → Pressure

Spatial Range Selection

# RAMSES standard notation (domain: [0:1]³)
gas = gethydro(info, xrange=[0.2, 0.8],              # X-range filter
                     yrange=[0.2, 0.8],              # Y-range filter
                     zrange=[0.4, 0.6])              # Z-range filter

# Center-relative coordinates (RAMSES units)
gas = gethydro(info, xrange=[-0.3, 0.3],             # Relative to center
                     yrange=[-0.3, 0.3],
                     zrange=[-0.1, 0.1],
                     center=[0.5, 0.5, 0.5])

# Physical units (e.g., kpc)
gas = gethydro(info, xrange=[2., 22.],                # Physical coordinates
                     yrange=[2., 22.],
                     zrange=[22., 26.],
                     range_unit=:kpc)

# Center-relative with physical units
gas = gethydro(info, xrange=[-16., 16.],              # Relative to center in kpc
                     yrange=[-16., 16.],
                     zrange=[-2., 2.],
                     center=[24., 24., 24.],
                     range_unit=:kpc)

# Box center shortcuts
gas = gethydro(info, center=[:boxcenter])            # All dimensions centered
gas = gethydro(info, center=[:bc])                   # Short form
gas = gethydro(info, center=[:bc, 24., :bc])         # Mixed: center x,z; fixed y

Performance Optimization

# Limit refinement levels for faster loading
gas = gethydro(info, lmax=8)                         # Maximum level 8 (existing higher levels are scaled down)

# Combined optimizations
gas = gethydro(info, [:rho, :p],                     # Select variables
                     lmax=10,                        # Limit levels
                     xrange=[-10., 10.],             # Spatial range
                     yrange=[-10., 10.],
                     zrange=[-2., 2.],
                     center=[:bc],                   # Box center
                     range_unit=:kpc)                # Physical units

Available Physical Units

# Check available units in simulation
viewfields(info.scale)

# Common length units
:m, :km, :cm, :mm, :μm, :Mpc, :kpc, :pc, :ly, :au, :Rsun

Getting Started: Simulation Setup

Before exploring data selection techniques, let's load our simulation and examine its properties. This establishes the foundation for all subsequent data loading operations.

using Mera
info = getinfo(300, "/Volumes/FASTStorage/Simulations/Mera-Tests/mw_L10");

[Mera]: 2025-08-14T14:26:46.643

Code: RAMSES
output [300] summary:
mtime: 2023-04-09T05:34:09
ctime: 2025-06-21T18:31:24.020
=======================================================
simulation time: 445.89 [Myr]
boxlen: 48.0 [kpc]
ncpu: 640
ndim: 3
-------------------------------------------------------
amr:           true
level(s): 6 - 10 --> cellsize(s): 750.0 [pc] - 46.88 [pc]
-------------------------------------------------------
hydro:         true
hydro-variables:  7  --> (:rho, :vx, :vy, :vz, :p, :var6, :var7)
hydro-descriptor: (:density, :velocity_x, :velocity_y, :velocity_z, :pressure, :scalar_00, :scalar_01)
γ: 1.6667
-------------------------------------------------------
gravity:       true
gravity-variables: (:epot, :ax, :ay, :az)
-------------------------------------------------------
particles:     true
- Nstars:   5.445150e+05
particle-variables: 7  --> (:vx, :vy, :vz, :mass, :family, :tag, :birth)
particle-descriptor: (:position_x, :position_y, :position_z, :velocity_x, :velocity_y, :velocity_z, :mass, :identity, :levelp, :family, :tag, :birth_time)
-------------------------------------------------------
rt:            false
clumps:           false
-------------------------------------------------------
namelist-file: ("&COOLING_PARAMS", "&SF_PARAMS", "&AMR_PARAMS", "&BOUNDARY_PARAMS", "&OUTPUT_PARAMS", "&POISSON_PARAMS", "&RUN_PARAMS", "&FEEDBACK_PARAMS", "&HYDRO_PARAMS", "&INIT_PARAMS", "&REFINE_PARAMS")
-------------------------------------------------------
timer-file:       true
compilation-file: false
makefile:         true
patchfile:        true
=======================================================

Variable Selection Techniques

Understanding how to selectively load variables is crucial for efficient memory usage and faster analysis. Mera provides flexible approaches to variable selection, from loading everything to precise variable targeting.

Understanding Variable References

Mera provides flexible ways to reference hydrodynamic variables. Understanding these reference methods enables precise control over data loading.

Core Variable References:

Variable	Symbol Format	Number Format	Description
CPU Number	`:cpu`	`:varn1`	Processor identification (= -1)
Density	`:rho`	`:var1`	Mass density
X-Velocity	`:vx`	`:var2`	Velocity component in x-direction
Y-Velocity	`:vy`	`:var3`	Velocity component in y-direction
Z-Velocity	`:vz`	`:var4`	Velocity component in z-direction
Pressure	`:p`	`:var5`	Gas pressure
Additional	-	`:var6`, `:var7`, ...	Extended variables

Key Features:

Variable order is flexible in function calls
Both symbolic (:rho) and numeric (:var1) formats supported
Future updates will support descriptor file variable names
Consistent naming across all Mera hydro functions

Loading All Variables (Default Behavior)

The simplest approach is to load all available variables. This is the default behavior when no specific variables are requested.

gas = gethydro(info);

[Mera]: Get hydro data: 2025-08-14T14:26:49.727

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 2, 3, 4, 5, 6, 7) = (:rho, :vx, :vy, :vz, :p, :var6, :var7)

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]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:25 (40.16 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 28320979 cells, 7 variables
Creating Table from 28320979 cells with max 8 threads...
  Threading: 8 threads for 11 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 8 threads
  Creating IndexedTable with 11 columns...
 28.692257 seconds (623.39 M allocations: 26.965 GiB, 5.05% gc time, 3.59% compilation time)
✓ Table created in 28.875 seconds
Memory used for data table :2.321086215786636 GB
-------------------------------------------------------

gas.data

Table with 28320979 rows, 11 columns:
Columns:
#   colname  type
────────────────────
1   level    Int64
2   cx       Int64
3   cy       Int64
4   cz       Int64
5   rho      Float64
6   vx       Float64
7   vy       Float64
8   vz       Float64
9   p        Float64
10  var6     Float64
11  var7     Float64

Selecting Multiple Variables

Mera provides multiple ways to select specific variables. You can use keyword arguments or positional arguments with flexible syntax.

gas_a = gethydro(info, vars=[:rho, :p]);

[Mera]: Get hydro data: 2025-08-14T14:27:49.310

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 5) = (:rho, :p)

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]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:28 (44.95 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 28320979 cells, 2 variables
Creating Table from 28320979 cells with max 8 threads...
  Threading: 6 threads for 6 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 6 threads
  Creating IndexedTable with 6 columns...
  2.227194 seconds (2.11 M allocations: 3.179 GiB, 1.11% gc time, 18.30% compilation time)
✓ Table created in 2.402 seconds
Memory used for data table :1.2660471182316542 GB
-------------------------------------------------------

Alternative: Use variable numbers instead of symbolic names. This approach provides identical functionality:

gas_a = gethydro(info, vars=[:var1, :var5]);

[Mera]: Get hydro data: 2025-08-14T14:28:20.836

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 5) = (:rho, :p)

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]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:28 (44.22 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 28320979 cells, 2 variables
Creating Table from 28320979 cells with max 8 threads...
  Threading: 6 threads for 6 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 6 threads
  Creating IndexedTable with 6 columns...
  2.332279 seconds (701.42 k allocations: 3.049 GiB, 0.33% gc time)
✓ Table created in 2.51 seconds
Memory used for data table :1.2660471182316542 GB
-------------------------------------------------------

Keyword-free syntax: When following the specific order (InfoType object, then variables), keyword arguments are optional:

gas_a = gethydro(info, [:rho, :p]);

[Mera]: Get hydro data: 2025-08-14T14:28:51.993

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 5) = (:rho, :p)

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]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:28 (44.70 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 28320979 cells, 2 variables
Creating Table from 28320979 cells with max 8 threads...
  Threading: 6 threads for 6 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 6 threads
  Creating IndexedTable with 6 columns...
  2.211744 seconds (701.42 k allocations: 3.071 GiB, 0.39% gc time)
✓ Table created in 2.386 seconds
Memory used for data table :1.2660471182316542 GB
-------------------------------------------------------

gas_a.data

Table with 28320979 rows, 6 columns:
level  cx   cy   cz   rho          p
─────────────────────────────────────────────
6      1    1    1    3.18647e-9   1.06027e-9
6      1    1    2    3.58591e-9   1.33677e-9
6      1    1    3    3.906e-9     1.58181e-9
6      1    1    4    4.27441e-9   1.93168e-9
6      1    1    5    4.61042e-9   2.37842e-9
6      1    1    6    4.83977e-9   2.8197e-9
6      1    1    7    4.974e-9     3.20883e-9
6      1    1    8    5.08112e-9   3.56075e-9
6      1    1    9    5.20596e-9   3.89183e-9
6      1    1    10   5.38372e-9   4.20451e-9
6      1    1    11   5.67209e-9   4.50256e-9
6      1    1    12   6.14423e-9   4.78595e-9
⋮
10     814  493  514  0.000321702  2.18179e-6
10     814  494  509  1.42963e-6   3.35949e-6
10     814  494  510  1.4351e-6    3.38092e-6
10     814  494  511  0.00029515   2.55696e-6
10     814  494  512  0.000395273  2.5309e-6
10     814  494  513  0.000321133  2.16472e-6
10     814  494  514  0.000319678  2.17348e-6
10     814  495  511  0.00024646   2.19846e-6
10     814  495  512  0.000269009  2.20717e-6
10     814  496  511  0.000235329  2.10577e-6
10     814  496  512  0.000242422  2.09634e-6

Selecting Single Variables

For single variable selection, arrays and keywords are unnecessary. Maintain the order: InfoType object, then variable symbol:

gas_c = gethydro(info, :vx );

[Mera]: Get hydro data: 2025-08-14T14:29:23.580

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(2,) = (:vx,)

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]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:28 (44.69 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 28320979 cells, 1 variables
Creating Table from 28320979 cells with max 8 threads...
  Threading: 5 threads for 5 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 5 threads
  Creating IndexedTable with 5 columns...
  2.032942 seconds (1.86 M allocations: 2.671 GiB, 0.99% gc time, 12.28% compilation time)
✓ Table created in 2.211 seconds
Memory used for data table :1.0550392987206578 GB
-------------------------------------------------------

gas_c.data

Table with 28320979 rows, 5 columns:
level  cx   cy   cz   vx
────────────────────────────────
6      1    1    1    -1.25532
6      1    1    2    -1.23262
6      1    1    3    -1.2075
6      1    1    4    -1.16462
6      1    1    5    -1.10493
6      1    1    6    -1.02686
6      1    1    7    -0.948004
6      1    1    8    -0.879731
6      1    1    9    -0.824484
6      1    1    10   -0.782768
6      1    1    11   -0.754141
6      1    1    12   -0.737723
⋮
10     814  493  514  0.268398
10     814  494  509  0.00398492
10     814  494  510  0.00496945
10     814  494  511  0.303842
10     814  494  512  0.305647
10     814  494  513  0.266079
10     814  494  514  0.26508
10     814  495  511  0.289612
10     814  495  512  0.290753
10     814  496  511  0.285209
10     814  496  512  0.285463

Spatial Range Selection Techniques

Spatial filtering is essential for focusing analysis on specific regions of interest. Mera offers multiple coordinate systems and reference methods to accommodate different analysis needs.

Available Coordinate Systems:

RAMSES Standard: Normalized domain [0:1]³
Center-Relative: Coordinates relative to specified points
Physical Units: Real astronomical units (kpc, pc, etc.)
Box-Centered: Convenient shortcuts for simulation center

This flexibility allows precise region selection for targeted analysis while optimizing memory usage and computational efficiency.

RAMSES Standard Coordinate System

The RAMSES standard provides a normalized coordinate system that simplifies numerical calculations and ensures consistency across different simulation scales.

Coordinate System Properties:

Domain Range: [0:1]³ in all dimensions
Origin: Located at [0., 0., 0.]
Benefits: Scale-independent, numerically stable
Usage: Ideal for relative positioning and grid calculations

Performance Optimization: Use lmax to limit maximum refinement levels for faster loading and preview analysis. This example demonstrates level 8 restriction:

gas = gethydro(info, lmax=8,
                xrange=[0.2,0.8],
                yrange=[0.2,0.8],
                zrange=[0.4,0.6]);

[Mera]: Get hydro data: 2025-08-14T14:29:55.127

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 2, 3, 4, 5, 6, 7) = (:rho, :vx, :vy, :vz, :p, :var6, :var7)

domain:
xmin::xmax: 0.2 :: 0.8  	==> 9.6 [kpc] :: 38.4 [kpc]
ymin::ymax: 0.2 :: 0.8  	==> 9.6 [kpc] :: 38.4 [kpc]
zmin::zmax: 0.4 :: 0.6  	==> 19.2 [kpc] :: 28.8 [kpc]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:17 (27.61 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 1233232 cells, 7 variables
Creating Table from 1233232 cells with max 8 threads...
  Threading: 8 threads for 11 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 8 threads
  Creating IndexedTable with 11 columns...
  1.162434 seconds (25.95 M allocations: 1.151 GiB)
✓ Table created in 1.34 seconds
Memory used for data table :103.4980878829956 MB
-------------------------------------------------------

Range Verification: The loaded data ranges are stored in the ranges field using RAMSES standard notation (domain: [0:1]³):

gas.ranges

6-element Vector{Float64}:
 0.2
 0.8
 0.2
 0.8
 0.4
 0.6

Center-Relative Coordinate Selection

Define spatial ranges relative to a specified center point. This approach is particularly useful for analyzing regions around specific features or objects:

gas = gethydro(info, lmax=8,
                xrange=[-0.3, 0.3],
                yrange=[-0.3, 0.3],
                zrange=[-0.1, 0.1],
                center=[0.5, 0.5, 0.5]);

[Mera]: Get hydro data: 2025-08-14T14:30:15.127

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 2, 3, 4, 5, 6, 7) = (:rho, :vx, :vy, :vz, :p, :var6, :var7)

center: [0.5, 0.5, 0.5] ==> [24.0 [kpc] :: 24.0 [kpc] :: 24.0 [kpc]]

domain:
xmin::xmax: 0.2 :: 0.8  	==> 9.6 [kpc] :: 38.4 [kpc]
ymin::ymax: 0.2 :: 0.8  	==> 9.6 [kpc] :: 38.4 [kpc]
zmin::zmax: 0.4 :: 0.6  	==> 19.2 [kpc] :: 28.8 [kpc]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:16 (25.32 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 1233232 cells, 7 variables
Creating Table from 1233232 cells with max 8 threads...
  Threading: 8 threads for 11 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 8 threads
  Creating IndexedTable with 11 columns...
  1.161734 seconds (25.95 M allocations: 1.160 GiB)
✓ Table created in 1.339 seconds
Memory used for data table :103.4980878829956 MB
-------------------------------------------------------

Physical Unit Coordinate System

Working with physical units provides intuitive scale references for astronomical analysis. This system automatically handles unit conversions and maintains physical meaning.

Key Advantages:

Intuitive Scaling: Use familiar astronomical units (kpc, pc, Mpc)
Automatic Conversion: Mera handles unit transformations internally
Reference Point: Coordinates measured from box corner [0., 0., 0.]
Flexibility: Mix different units as needed for analysis

The following example demonstrates kiloparsec (kpc) coordinate selection:

gas = gethydro(info, lmax=8,
                xrange=[2.,22.],
                yrange=[2.,22.],
                zrange=[22.,26.],
                range_unit=:kpc);

[Mera]: Get hydro data: 2025-08-14T14:30:32.839

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 2, 3, 4, 5, 6, 7) = (:rho, :vx, :vy, :vz, :p, :var6, :var7)

domain:
xmin::xmax: 0.0416667 :: 0.4583333  	==> 2.0 [kpc] :: 22.0 [kpc]
ymin::ymax: 0.0416667 :: 0.4583333  	==> 2.0 [kpc] :: 22.0 [kpc]
zmin::zmax: 0.4583333 :: 0.5416667  	==> 22.0 [kpc] :: 26.0 [kpc]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:11 (18.75 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 229992 cells, 7 variables
Creating Table from 229992 cells with max 8 threads...
  Threading: 8 threads for 11 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 8 threads
  Creating IndexedTable with 11 columns...
  0.209679 seconds (4.85 M allocations: 220.809 MiB)
✓ Table created in 0.388 seconds
Memory used for data table :19.302836418151855 MB
-------------------------------------------------------

Available Physical Units: The range_unit keyword accepts various length units defined in the simulation's scale field:

viewfields(info.scale)  # or e.g.: gas.info.scale


[Mera]: Fields to scale from user/code units to selected units
=======================================================================
Mpc	= 0.0010000000000006482
kpc	= 1.0000000000006481
pc	= 1000.0000000006482
mpc	= 1.0000000000006482e6
ly	= 3261.5637769461323
Au	= 2.0626480623310105e23
km	= 3.0856775812820004e16
m	= 3.085677581282e19
cm	= 3.085677581282e21
mm	= 3.085677581282e22
μm	= 3.085677581282e25
Mpc3	= 1.0000000000019446e-9
kpc3	= 1.0000000000019444
pc3	= 1.0000000000019448e9
mpc3	= 1.0000000000019446e18
ly3	= 3.469585750743794e10
Au3	= 8.775571306099254e69
km3	= 2.9379989454983075e49
m3	= 2.9379989454983063e58
cm3	= 2.9379989454983065e64
mm3	= 2.937998945498306e67
μm3	= 2.937998945498306e76
Msol_pc3	= 0.9997234790001649
Msun_pc3	= 0.9997234790001649
g_cm3	= 6.76838218451376e-23
Msol_pc2	= 999.7234790008131
Msun_pc2	= 999.7234790008131
g_cm2	= 0.20885045168302602
Gyr	= 0.014910986463557083
Myr	= 14.910986463557084
yr	= 1.4910986463557083e7
s	= 4.70554946422349e14
ms	= 4.70554946422349e17
Msol	= 9.99723479002109e8
Msun	= 9.99723479002109e8
Mearth	= 3.329677459032007e14
Mjupiter	= 1.0476363431814971e12
g	= 1.9885499720830952e42
km_s	= 65.57528732282063
m_s	= 65575.28732282063
cm_s	= 6.557528732282063e6
nH	= 30.987773856809987
erg	= 8.551000140274429e55
g_cms2	= 2.9104844143584656e-9
T_mu	= 517017.45993377
K_mu	= 517017.45993377
T	= 680286.1314918026
K	= 680286.1314918026
Ba	= 2.910484414358466e-9
g_cm_s2	= 2.910484414358466e-9
p_kB	= 2.1080552800592083e7
K_cm3	= 2.1080552800592083e7
erg_g_K	= 3.114563011649217e29
keV_cm2	= 1.252773885965637e65
erg_K	= 6.193464189866091e71
J_K	= 6.193464189866091e64
erg_cm3_K	= 2.1080552800592083e7
J_m3_K	= 2.1080552800592083e8
kB_per_particle	= 1.380649e-16
J_s	= 4.023715412864333e70
g_cm2_s	= 4.023715412864333e70
kg_m2_s	= 4.023715412864333e71
Gauss	= 0.00019124389093025845
muG	= 191.24389093025846
microG	= 191.24389093025846
Tesla	= 1.9124389093025845e-8
eV	= 5.3371144971238105e67
keV	= 5.33711449712381e64
MeV	= 5.33711449712381e61
erg_s	= 1.8172160775884043e41
Lsol	= 4.747168436751317e7
Lsun	= 4.747168436751317e7
cm_3	= 3.4036771916893676e-65
pc_3	= 1.158501842524895e-120
n_e	= 30.987773856809987
erg_g_s	= 0.09138397843151959
erg_cm3_s	= 6.185216915658869e-24
erg_cm2_s	= 6.185216915658869e-24
Jy	= 0.6185216915658869
mJy	= 618.5216915658868
microJy	= 618521.6915658868
atoms_cm2	= 1.2581352511025663e23
NH_cm2	= 1.2581352511025663e23
cm_s2	= 1.3935734353956443e-8
m_s2	= 1.3935734353956443e-10
km_s2	= 1.3935734353956443e-13
pc_Myr2	= 3.09843657823729e-9
erg_g	= 4.30011830747048e13
J_kg	= 4.30011830747048e6
km2_s2	= 4300.1183074704795
u_grav	= 2.910484414358466e-9
erg_cell	= 8.55100014027443e55
dyne	= 9.432237612943517e-31
s_2	= 4.516263928056473e-30
lambda_J	= 3.085677581282e21
M_J	= 1.9885499720830952e42
t_ff	= 4.70554946422349e14
alpha_vir	= 1.0
delta_rho	= 2.68258472e-314
a_mag	= 2.727176105e-314
v_esc	= 2.68258472e-314
ax	= 2.727176105e-314
ay	= 2.68258472e-314
az	= 2.727176105e-314
epot	= 2.68258472e-314
a_magnitude	= 2.727176105e-314
escape_speed	= 2.68258472e-314
gravitational_redshift	= 2.727176105e-314
gravitational_energy_density	= 2.68258472e-314
gravitational_binding_energy	= 2.727176105e-314
total_binding_energy	= 2.68258472e-314
specific_gravitational_energy	= 4.30011830747048e13
gravitational_work	= 2.68258472e-314
jeans_length_gravity	= 3.085677581282e21
jeans_mass_gravity	= 1.9885499720830952e42
jeansmass	= 1.9885499720830952e42
freefall_time_gravity	= 4.70554946422349e14
ekin	= 8.551000140274429e55
etherm	= 8.551000140274429e55
virial_parameter_local	= 1.0
Fg	= 2.68258472e-314
poisson_source	= 2.727176105e-314
ar_cylinder	= 1.3935734353956443e-8
aϕ_cylinder	= 1.3935734353956443e-8
ar_sphere	= 1.3935734353956443e-8
aθ_sphere	= 1.3935734353956443e-8
aϕ_sphere	= 1.3935734353956443e-8
r_cylinder	= 3.085677581282e21
r_sphere	= 3.085677581282e21
ϕ	= 1.0
dimensionless	= 1.0
rad	= 1.0
deg	= 57.29577951308232

Center-Relative with Physical Units: Combine center-relative positioning with physical unit specifications for precise regional analysis:

gas = gethydro(info, lmax=8,
                xrange=[-16.,16.],
                yrange=[-16.,16.],
                zrange=[-2.,2.],
                center=[24.,24.,24.],
                range_unit=:kpc);

[Mera]: Get hydro data: 2025-08-14T14:30:45.391

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 2, 3, 4, 5, 6, 7) = (:rho, :vx, :vy, :vz, :p, :var6, :var7)

center: [0.5, 0.5, 0.5] ==> [24.0 [kpc] :: 24.0 [kpc] :: 24.0 [kpc]]

domain:
xmin::xmax: 0.1666667 :: 0.8333333  	==> 8.0 [kpc] :: 40.0 [kpc]
ymin::ymax: 0.1666667 :: 0.8333333  	==> 8.0 [kpc] :: 40.0 [kpc]
zmin::zmax: 0.4583333 :: 0.5416667  	==> 22.0 [kpc] :: 26.0 [kpc]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:10 (16.15 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 650848 cells, 7 variables
Creating Table from 650848 cells with max 8 threads...
  Threading: 8 threads for 11 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 8 threads
  Creating IndexedTable with 11 columns...
  0.599757 seconds (13.73 M allocations: 622.916 MiB)
✓ Table created in 0.778 seconds
Memory used for data table :54.622477531433105 MB
-------------------------------------------------------

Box Center Coordinate Shortcuts

Mera provides convenient shortcuts for box-centered coordinate systems, simplifying analysis focused on the simulation center.

Available Shortcuts:

:bc or :boxcenter - Center coordinate for all dimensions
Can be applied to individual dimensions selectively
Combines seamlessly with physical units and range specifications
Ideal for symmetric analysis around simulation center

Benefits:

Eliminates manual center calculation
Ensures precise geometric centering
Simplifies symmetric region definitions
Reduces coordinate specification errors

gas = gethydro(info, lmax=8,
                xrange=[-16., 16.],
                yrange=[-16., 16.],
                zrange=[-2., 2.],
                center=[:boxcenter],
                range_unit=:kpc);

[Mera]: Get hydro data: 2025-08-14T14:30:56.645

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 2, 3, 4, 5, 6, 7) = (:rho, :vx, :vy, :vz, :p, :var6, :var7)

center: [0.5, 0.5, 0.5] ==> [24.0 [kpc] :: 24.0 [kpc] :: 24.0 [kpc]]

domain:
xmin::xmax: 0.1666667 :: 0.8333333  	==> 8.0 [kpc] :: 40.0 [kpc]
ymin::ymax: 0.1666667 :: 0.8333333  	==> 8.0 [kpc] :: 40.0 [kpc]
zmin::zmax: 0.4583333 :: 0.5416667  	==> 22.0 [kpc] :: 26.0 [kpc]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:01 ( 2.79 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 650848 cells, 7 variables
Creating Table from 650848 cells with max 8 threads...
  Threading: 8 threads for 11 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 8 threads
  Creating IndexedTable with 11 columns...
  0.607037 seconds (13.73 M allocations: 622.916 MiB)
✓ Table created in 0.782 seconds
Memory used for data table :54.622477531433105 MB
-------------------------------------------------------

gas = gethydro(info, lmax=8,
                xrange=[-16., 16.],
                yrange=[-16., 16.],
                zrange=[-2., 2.],
                center=[:bc],
                range_unit=:kpc);

[Mera]: Get hydro data: 2025-08-14T14:30:59.404

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 2, 3, 4, 5, 6, 7) = (:rho, :vx, :vy, :vz, :p, :var6, :var7)

center: [0.5, 0.5, 0.5] ==> [24.0 [kpc] :: 24.0 [kpc] :: 24.0 [kpc]]

domain:
xmin::xmax: 0.1666667 :: 0.8333333  	==> 8.0 [kpc] :: 40.0 [kpc]
ymin::ymax: 0.1666667 :: 0.8333333  	==> 8.0 [kpc] :: 40.0 [kpc]
zmin::zmax: 0.4583333 :: 0.5416667  	==> 22.0 [kpc] :: 26.0 [kpc]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:01 ( 2.73 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 650848 cells, 7 variables
Creating Table from 650848 cells with max 8 threads...
  Threading: 8 threads for 11 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 8 threads
  Creating IndexedTable with 11 columns...
  0.615515 seconds (13.73 M allocations: 622.916 MiB)
✓ Table created in 0.79 seconds
Memory used for data table :54.622477531433105 MB
-------------------------------------------------------

Selective Dimension Centering: Apply box center notation to specific dimensions while maintaining explicit coordinates for others. This example centers x and z dimensions while fixing y at 24 kpc:

gas = gethydro(info, lmax=8,
                xrange=[-16., 16.],
                yrange=[-16., 16.],
                zrange=[-2., 2.],
                center=[:bc, 24., :bc],
                range_unit=:kpc);

[Mera]: Get hydro data: 2025-08-14T14:31:02.085

Key vars=(:level, :cx, :cy, :cz)
Using var(s)=(1, 2, 3, 4, 5, 6, 7) = (:rho, :vx, :vy, :vz, :p, :var6, :var7)

center: [0.5, 0.5, 0.5] ==> [24.0 [kpc] :: 24.0 [kpc] :: 24.0 [kpc]]

domain:
xmin::xmax: 0.1666667 :: 0.8333333  	==> 8.0 [kpc] :: 40.0 [kpc]
ymin::ymax: 0.1666667 :: 0.8333333  	==> 8.0 [kpc] :: 40.0 [kpc]
zmin::zmax: 0.4583333 :: 0.5416667  	==> 22.0 [kpc] :: 26.0 [kpc]

📊 Processing Configuration:
   Total CPU files available: 640
   Files to be processed: 640
   Compute threads: 8
   GC threads: 4

Processing files: 100%|██████████████████████████████████████████████████| Time: 0:00:01 ( 2.73 ms/it)


✓ File processing complete! Combining results...
✓ Data combination complete!
Final data size: 650848 cells, 7 variables
Creating Table from 650848 cells with max 8 threads...
  Threading: 8 threads for 11 columns
  Max threads requested: 8
  Available threads: 8
  Using parallel processing with 8 threads
  Creating IndexedTable with 11 columns...
  0.616928 seconds (13.73 M allocations: 622.924 MiB)
✓ Table created in 0.794 seconds
Memory used for data table :54.622477531433105 MB
-------------------------------------------------------

Summary

This notebook demonstrated comprehensive data selection techniques in Mera.jl, covering both variable selection and spatial filtering strategies. Key concepts covered include:

Variable Selection Mastery

Flexible Reference Systems: Using both symbolic (:rho) and numeric (:var1) variable references
Selective Loading: Choosing specific variables to optimize memory usage
Syntax Variations: Keyword and positional argument approaches for different coding styles
Single vs. Multiple Variables: Appropriate syntax for different selection scenarios

Spatial Filtering Expertise

Coordinate Systems: RAMSES standard, physical units, center-relative, and box-centered approaches
Performance Optimization: Using lmax restrictions and tight spatial bounds
Unit Flexibility: Working with various astronomical length scales
Center Definitions: Absolute positioning and relative coordinate systems

Advanced Techniques

Combined Selection: Integrating variable selection with spatial filtering
Memory Management: Balancing analysis needs with computational resources
Coordinate Shortcuts: Using box center notation for simplified positioning
Quality Assurance: Verifying loaded data ranges and dimensions