synthesizer.load_data.load_eagle¶
A module for interfacing with the outputs of the EAGLE hydrodynamical simulations suite.
The EAGLE hdf5 data loading scripts have been taken from the eagle_io package (https://github.com/flaresimulations/eagle_IO/). This has been to make the call as self-contained as possible.
The functions here used in https://github.com/flaresimulations/synthesizer-pipeline
Functions
- synthesizer.load_data.load_eagle.apply_CGSUnits_conversion(filename, dataset, dat, verbose=True)[source]¶
- Parameters:
filename (str) – filename to read from
dataset (str) – dataset to read attribute
dat (array) – dataset array to apply conversion
- Return type:
ndarray
[Any
,dtype
[Any
]]- Returns:
Numpy array of the dataset converted to CGS units
- synthesizer.load_data.load_eagle.apply_PhotUnits(filename, dataset, dat, verbose=True)[source]¶
” :type filename:
str
:param filename: filename to read from :type filename: str :type dataset:str
:param dataset: dataset to read attribute :type dataset: str :type dat:ndarray
[Any
,dtype
[Any
]] :param dat: dataset array to apply conversion :type dat: array- Return type:
unyt_array
[unyt_quantity
]- Returns:
Unyt array of the dataset in the photometric units
- synthesizer.load_data.load_eagle.apply_hfreeUnits_conversion(filename, dataset, dat, verbose=True)[source]¶
- Parameters:
filename (str) – filename to read from
dataset (str) – dataset to read attribute
dat (array) – dataset array to apply conversion
- Return type:
ndarray
[Any
,dtype
[Any
]]- Returns:
Numpy array of the dataset converted to h free units
- synthesizer.load_data.load_eagle.apply_physicalUnits_conversion(filename, dataset, dat, verbose=True)[source]¶
- Parameters:
filename (str) – filename to read from
dataset (str) – dataset to read attribute
dat (array) – dataset array to apply conversion
- Return type:
ndarray
[Any
,dtype
[Any
]]- Returns:
Numpy array of the dataset converted to physical units
- synthesizer.load_data.load_eagle.assign_galaxy_prop(ii, zed, boxl, aperture, grpno, sgrpno, cop, s_grpno, s_sgrpno, s_imasses, s_masses, s_ages, s_Zsmooth, s_coords, s_hsml, s_oxygen, s_hydrogen, g_grpno, g_sgrpno, g_masses, g_Zsmooth, g_sfr, g_coords, g_hsml, verbose, s_kwargs={}, g_kwargs={})[source]¶
Load stellar and gas particle data into synthesizer galaxy object.
- Parameters:
ii (int) – galaxy number
zed (float) – redshift
boxl (float) – simulation box side length
aperture (float) – aperture to use from centre of potential
grpno (array) – Group numbers in this chunk
sgrpno (array) – Subgroup numbers in this chunk
cop (array) – centre of potential of subhalos in this chunk
s_grpno (array) – Stellar particle group numbers
s_sgrpno (array) – Stellar particle subgroup numbers
s_imasses (array) – Stellar particle initial masses in Msun
s_masses (array) – Stellar particle current masses in Msun
s_ages (array) – Stellar particle ages in Gyr
s_Zsmooth (array) – Stellar particle smoothed metallicity
s_coords (array) – Stellar particle coordinates in pMpc
s_hsml (array) – Stellar particle smoothing length in pMpc
s_oxygen (array) – Stellar particle abundance in oxygen
s_hydrogen (array) – Stellar particle abundance in hydrogen
g_grpno (array) – Gas particle group number
g_sgrpno (array) – Gas particle subgroup number
g_masses (array) – Gas particle masses in Msun
g_Zsmooth (array) – Gas particle smoothed metallicity
g_sfr (array) – Gas particle instantaneous SFR in Msun/yr
g_coords (
ndarray
[Any
,dtype
[float32
]]) – (array) Gas particle coordinates in pMpcg_hsml (array) – Gas particle smoothing length in pMpc
verbose (bool) – Are we talking?
s_kwargs (dictionary) – kwargs for stars
g_kwargs (dictionary) – kwargs for gas
- Return type:
- Returns:
- Galaxy
synthesizer galaxy object
- synthesizer.load_data.load_eagle.get_age(scale_factors, z, numThreads=4)[source]¶
Function to convert scale factor to z
- Parameters:
scale_factors (array) – scale factor of the star particle
z (float) – redshift
numThreads (int) – number of threads to use
- Return type:
ndarray
[Any
,dtype
[Any
]]- Returns:
array of ages of the star particles in years
- synthesizer.load_data.load_eagle.get_files(fileType, directory, tag)[source]¶
Fetch filename for the different eagle outputs for reading
- Parameters:
fileType (string) – type of file in the eagle outputs
directory (string) – eagle data file location
tag (string) – snapshot tag to load
- Return type:
List
[str
]- Returns:
array of files to read
- synthesizer.load_data.load_eagle.get_star_formation_time(scale_factor)[source]¶
Function to convert scale factor to z
- Parameters:
scale_factor (float) – scale factor of the star particle
- Return type:
float
- Returns:
age of the star particle in years
- synthesizer.load_data.load_eagle.load_EAGLE(fileloc, args, tot_chunks=1535, verbose=False)[source]¶
Load EAGLE required EAGLE galaxy properties for generating their SEDs Most useful for running on high-z snaps or individual chunks
- Parameters:
fileloc (string) – eagle data file location
args (namedtuple) – parser arguments passed on to this job
tot_chunks (int) – total number of files to process
verbose (bool) – Are we talking?
- Return type:
List
[Union
[Galaxy
,Never
]]- Returns:
a dictionary of Galaxy objects with stars and gas components
- synthesizer.load_data.load_eagle.load_EAGLE_shm(chunk, fileloc, tag, s_len, g_len, args, numThreads=1, dtype='float32', tot_chunks=1535, verbose=False)[source]¶
Load EAGLE required EAGLE galaxy properties for generating their SEDs using numpy memmap. Most useful for running on high-z snaps
- Parameters:
chunk (int) – file number to process
fileloc (string) – eagle data file location
tag (string) – snapshot tag to load
s_len (int) – total number of star particles
g_len (int) – total number of gas particles
args (namedtuple) – parser arguments passed on to this job
numThreads (int) – number of threads to use
dtype (numpy object) – data type of the array in memory
tot_chunks (int) – total number of files to process
verbose (bool) – Are we talking?
- Return type:
List
[Union
[Galaxy
,Never
]]- Returns:
a dictionary of Galaxy objects with stars and gas components
- synthesizer.load_data.load_eagle.np_shm_read(name, array_shape, dtype)[source]¶
Read the required numpy memmap array
- Parameters:
name (str) – location of the memmap
array_shape (tuple) – shape of the memmap array
dtype (str) – data type of the memmap array
- Return type:
ndarray
[Any
,dtype
[Any
]]- Returns:
Required eagle array from numpy memmap location
- synthesizer.load_data.load_eagle.read_array(ftype, directory, tag, dataset, numThreads=1, noH=False, physicalUnits=False, CGS=False, photUnits=False, verbose=True)[source]¶
- Parameters:
ftype (str) – eagle file type to read
directory (str) – location of the eagle simulation directory
tag (str) – snapshot tag to read
dataset (str) – name of the dataset to read
numThreads (int) – number threads to use
noH (bool) – remove any reduced Hubble factors
physicalUnits (bool) – return in physical units
CGS (bool) – return in CGS units
verbose (bool) – verbose condition
- Return type:
Union
[ndarray
[Any
,dtype
[Any
]],unyt_array
[unyt_quantity
]]- Returns:
Numpy/unyt array from eagle hdf5 filetype
- synthesizer.load_data.load_eagle.read_hdf5(filename, dataset)[source]¶
Read the required dataset from the eagle hdf5 file
- Parameters:
filename (str) – name of the hdf5 file
dataset (str) – name of the dataset to extract
- Return type:
ndarray
[Any
,dtype
[Any
]]- Returns:
Numpy array of the required hdf5 dataset
- synthesizer.load_data.load_eagle.read_header(ftype, directory, tag, dataset)[source]¶
- ftype (str)
eagle file type to read
- directory (str)
location of the eagle simulation directory
- tag (str)
snapshot tag to read
- dataset (str)
name of the dataset to read
- Return type:
ndarray
[Any
,dtype
[Any
]]- Returns:
Reads in required eagle hdf5 header data