nbodykit.source.catalog.halos¶
Classes
|
A CatalogSource of objects that represent halos, which can be populated using analytic models from |
|
A CatalogSource to represent a set of objects populated into a |
- class nbodykit.source.catalog.halos.HaloCatalog(source, cosmo, redshift, mdef='vir', mass='Mass', position='Position', velocity='Velocity')[source]¶
A CatalogSource of objects that represent halos, which can be populated using analytic models from
halotools
.- Parameters
source (CatalogSource) – the source holding the particles to be interpreted as halos
cosmo (
Cosmology
) – the cosmology instance;redshift (float) – the redshift of the halo catalog
mdef (str, optional) – string specifying mass definition, used for computing default halo radii and concentration; should be ‘vir’ or ‘XXXc’ or ‘XXXm’ where ‘XXX’ is an int specifying the overdensity
mass (str, optional) – the column name specifying the mass of each halo
position (str, optional) – the column name specifying the position of each halo
velocity (str, optional) – the column name specifying the velocity of each halo
- Attributes
Index
The attribute giving the global index rank of each particle in the list.
attrs
A dictionary storing relevant meta-data about the CatalogSource.
columns
All columns in the CatalogSource, including those hard-coded into the class’s defintion and override columns provided by the user.
csize
The total, collective size of the CatalogSource, i.e., summed across all ranks.
hardcolumns
A list of the hard-coded columns in the CatalogSource.
size
The number of objects in the CatalogSource on the local rank.
Methods
The halo concentration, computed using
nbodykit.transform.HaloConcentration()
.Mass
()The halo mass column, assumed to be in units of \(M_\odot/h\).
Position
()The halo position column, assumed to be in units of \(\mathrm{Mpc}/h\).
Radius
()The halo radius, computed using
nbodykit.transform.HaloRadius()
.A boolean column that selects a subset slice of the CatalogSource.
Value
()When interpolating a CatalogSource on to a mesh, the value of this array is used as the Value that each particle contributes to a given mesh cell.
Velocity
()The halo velocity column, assumed to be in units of km/s.
The redshift-space distance offset due to the velocity in units of distance.
Weight
()The column giving the weight to use for each particle on the mesh.
compute
(*args, **kwargs)Our version of
dask.compute()
that computes multiple delayed dask collections at once.copy
()Return a shallow copy of the object, where each column is a reference of the corresponding column in
self
.get_hardcolumn
(col)Construct and return a hard-coded column.
gslice
(start, stop[, end, redistribute])Execute a global slice of a CatalogSource.
make_column
(array)Utility function to convert an array-like object to a
dask.array.Array
.persist
([columns])Return a CatalogSource, where the selected columns are computed and persist in memory.
populate
(model[, BoxSize, seed])Populate the HaloCatalog using a
halotools
model.read
(columns)Return the requested columns as dask arrays.
save
(output[, columns, dataset, datasets, ...])Save the CatalogSource to a
bigfile.BigFile
.sort
(keys[, reverse, usecols])Return a CatalogSource, sorted globally across all MPI ranks in ascending order by the input keys.
to_halotools
([BoxSize])Return the HaloCatalog as a
halotools.sim_manager.UserSuppliedHaloCatalog
.to_mesh
([Nmesh, BoxSize, dtype, interlaced, ...])Convert the CatalogSource to a MeshSource, using the specified parameters.
to_subvolumes
([domain, position, columns])Domain Decompose a catalog, sending items to the ranks according to the supplied domain object.
view
([type])Return a "view" of the CatalogSource object, with the returned type set by
type
.create_instance
- Concentration()[source]¶
The halo concentration, computed using
nbodykit.transform.HaloConcentration()
.This uses the analytic formulas for concentration from Dutton and Maccio 2014.
Users can override this column to implement custom mass-concentration relations.
- property Index¶
The attribute giving the global index rank of each particle in the list. It is an integer from 0 to
self.csize
.Note that slicing changes this index value.
- Radius()[source]¶
The halo radius, computed using
nbodykit.transform.HaloRadius()
.Assumed units of \(\mathrm{Mpc}/h\).
- Selection()¶
A boolean column that selects a subset slice of the CatalogSource.
By default, this column is set to
True
for all particles, and all CatalogSource objects will contain this column.
- Value()¶
When interpolating a CatalogSource on to a mesh, the value of this array is used as the Value that each particle contributes to a given mesh cell.
The mesh field is a weighted average of
Value
, with the weights given byWeight
.By default, this array is set to unity for all particles, and all CatalogSource objects will contain this column.
- VelocityOffset()[source]¶
The redshift-space distance offset due to the velocity in units of distance. The assumed units are \(\mathrm{Mpc}/h\).
This multiplies
Velocity
by \(1 / (a 100 E(z)) = 1 / (a H(z)/h)\).
- Weight()¶
The column giving the weight to use for each particle on the mesh.
The mesh field is a weighted average of
Value
, with the weights given byWeight
.By default, this array is set to unity for all particles, and all CatalogSource objects will contain this column.
- __delitem__(col)¶
Delete a column; cannot delete a “hard-coded” column.
Note
If the
base
attribute is set, columns will be deleted frombase
instead of fromself
.
- __finalize__(other)¶
Finalize the creation of a CatalogSource object by copying over any additional attributes from a second CatalogSource.
The idea here is to only copy over attributes that are similar to meta-data, so we do not copy some of the core attributes of the
CatalogSource
object.- Parameters
other – the second object to copy over attributes from; it needs to be a subclass of CatalogSourcBase for attributes to be copied
- Returns
return
self
, with the added attributes- Return type
- __getitem__(sel)¶
The following types of indexing are supported:
strings specifying a column in the CatalogSource; returns a dask array holding the column data
boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
slice object specifying which particles to select
list of strings specifying column names; returns a CatalogSource holding only the selected columns
Notes
Slicing is a collective operation
If the
base
attribute is set, columns will be returned frombase
instead of fromself
.
- __len__()¶
The local size of the CatalogSource on a given rank.
- __setitem__(col, value)¶
Add columns to the CatalogSource, overriding any existing columns with the name
col
.
- property attrs¶
A dictionary storing relevant meta-data about the CatalogSource.
- property columns¶
All columns in the CatalogSource, including those hard-coded into the class’s defintion and override columns provided by the user.
Note
If the
base
attribute is set, the value ofbase.columns
will be returned.
- compute(*args, **kwargs)¶
Our version of
dask.compute()
that computes multiple delayed dask collections at once.This should be called on the return value of
read()
to converts any dask arrays to numpy arrays.- . note::
If the
base
attribute is set,compute()
will called usingbase
instead ofself
.
- Parameters
args (object) – Any number of objects. If the object is a dask collection, it’s computed and the result is returned. Otherwise it’s passed through unchanged.
- copy()¶
Return a shallow copy of the object, where each column is a reference of the corresponding column in
self
.Note
No copy of data is made.
Note
This is different from view in that the attributes dictionary of the copy no longer related to
self
.- Returns
a new CatalogSource that holds all of the data columns of
self
- Return type
- property csize¶
The total, collective size of the CatalogSource, i.e., summed across all ranks.
It is the sum of
size
across all available ranks.If the
base
attribute is set, thebase.csize
attribute will be returned.
- get_hardcolumn(col)¶
Construct and return a hard-coded column.
These are usually produced by calling member functions marked by the
@column
decorator.Subclasses may override this method and the hardcolumns attribute to bypass the decorator logic.
Note
If the
base
attribute is set,get_hardcolumn()
will called usingbase
instead ofself
.
- gslice(start, stop, end=1, redistribute=True)¶
Execute a global slice of a CatalogSource.
Note
After the global slice is performed, the data is scattered evenly across all ranks.
Note
The current algorithm generates an index on the root rank and does not scale well.
- Parameters
start (int) – the start index of the global slice
stop (int) – the stop index of the global slice
step (int, optional) – the default step size of the global size
redistribute (bool, optional) – if
True
, evenly re-distribute the sliced data across all ranks, otherwise just return any local data part of the global slice
- property hardcolumns¶
A list of the hard-coded columns in the CatalogSource.
These columns are usually member functions marked by
@column
decorator. Subclasses may override this method and useget_hardcolumn()
to bypass the decorator logic.Note
If the
base
attribute is set, the value ofbase.hardcolumns
will be returned.
- static make_column(array)¶
Utility function to convert an array-like object to a
dask.array.Array
.Note
The dask array chunk size is controlled via the
dask_chunk_size
global option. Seeset_options
.- Parameters
array (array_like) – an array-like object; can be a dask array, numpy array, ColumnAccessor, or other non-scalar array-like object
- Returns
a dask array initialized from
array
- Return type
- persist(columns=None)¶
Return a CatalogSource, where the selected columns are computed and persist in memory.
- populate(model, BoxSize=None, seed=None, **params)[source]¶
Populate the HaloCatalog using a
halotools
model.The model can be a built-in model from
nbodykit.hod
(which will be converted to a Halotools model) or directly a Halotools model instance.This assumes that this is the first time this catalog has been populated with the input model. To re-populate using the same model (but different parameters), call the
repopulate()
function of the returnedPopulatedHaloCatalog
.- Parameters
model (
nbodykit.hod.HODModel
or halotools model object) – the model instance to use to populate; model types fromnbodykit.hod
will automatically be convertedBoxSize (float, 3-vector, optional) – the box size of the catalog; this must be supplied if ‘BoxSize’ is not in
attrs
seed (int, optional) – the random seed to use when populating the mock
**params – key/value pairs specifying the model parameters to use
- Returns
cat – the catalog object storing information about the populated objects
- Return type
Examples
Initialize a demo halo catalog:
>>> from nbodykit.tutorials import DemoHaloCatalog >>> cat = DemoHaloCatalog('bolshoi', 'rockstar', 0.5)
Populate with the built-in Zheng07 model:
>>> from nbodykit.hod import Zheng07Model >>> galcat = cat.populate(Zheng07Model, seed=42)
And then re-populate galaxy catalog with new parameters:
>>> galcat.repopulate(alpha=0.9, logMmin=13.5, seed=42)
- read(columns)¶
Return the requested columns as dask arrays.
- Parameters
columns (list of str) – the names of the requested columns
- Returns
the list of column data, in the form of dask arrays
- Return type
list of
dask.array.Array
- save(output, columns=None, dataset=None, datasets=None, header='Header', compute=True)¶
Save the CatalogSource to a
bigfile.BigFile
.Only the selected columns are saved and
attrs
are saved inheader
. The attrs of columns are stored in the datasets.- Parameters
output (str) – the name of the file to write to
columns (list of str) – the names of the columns to save in the file, or None to use all columns
dataset (str, optional) – dataset to store the columns under.
datasets (list of str, optional) – names for the data set where each column is stored; defaults to the name of the column (deprecated)
header (str, optional, or None) – the name of the data set holding the header information, where
attrs
is stored if header is None, do not save the header.compute (boolean, default True) – if True, wait till the store operations finish if False, return a dictionary with column name and a future object for the store. use dask.compute() to wait for the store operations on the result.
- property size¶
The number of objects in the CatalogSource on the local rank.
If the
base
attribute is set, thebase.size
attribute will be returned.Important
This property must be defined for all subclasses.
- sort(keys, reverse=False, usecols=None)¶
Return a CatalogSource, sorted globally across all MPI ranks in ascending order by the input keys.
Sort columns must be floating or integer type.
Note
After the sort operation, the data is scattered evenly across all ranks.
- Parameters
keys (list, tuple) – the names of columns to sort by. If multiple columns are provided, the data is sorted consecutively in the order provided
reverse (bool, optional) – if
True
, perform descending sort operationsusecols (list, optional) – the name of the columns to include in the returned CatalogSource
- to_halotools(BoxSize=None)[source]¶
Return the HaloCatalog as a
halotools.sim_manager.UserSuppliedHaloCatalog
.The Halotools catalog only holds the local data, although halos are labeled via the
halo_id
column using the global index.
- to_mesh(Nmesh=None, BoxSize=None, dtype='f4', interlaced=False, compensated=False, resampler='cic', weight='Weight', value='Value', selection='Selection', position='Position', window=None)¶
Convert the CatalogSource to a MeshSource, using the specified parameters.
- Parameters
Nmesh (int, optional) – the number of cells per side on the mesh; must be provided if not stored in
attrs
BoxSize (scalar, 3-vector, optional) – the size of the box; must be provided if not stored in
attrs
dtype (string, optional) – the data type of the mesh array
interlaced (bool, optional) – use the interlacing technique of Sefusatti et al. 2015 to reduce the effects of aliasing on Fourier space quantities computed from the mesh
compensated (bool, optional) – whether to correct for the resampler window introduced by the grid interpolation scheme
resampler (str, optional) – the string specifying which resampler interpolation scheme to use; see pmesh.resampler.methods
weight (str, optional) – the name of the column specifying the weight for each particle
value (str, optional) – the name of the column specifying the field value for each particle
selection (str, optional) – the name of the column that specifies which (if any) slice of the CatalogSource to take
position (str, optional) – the name of the column that specifies the position data of the objects in the catalog
window (str, deprecated) – use resampler instead.
- Returns
mesh – a mesh object that provides an interface for gridding particle data onto a specified mesh
- Return type
- to_subvolumes(domain=None, position='Position', columns=None)¶
Domain Decompose a catalog, sending items to the ranks according to the supplied domain object. Using the position column as the Position.
This will read in the full position array and all of the requested columns.
- Parameters
domain (
pmesh.domain.GridND
object, or None) – The domain to distribute the catalog. If None, try to evenly divide spatially. An easiest way to find a domain object is to use pm.domain, where pm is apmesh.pm.ParticleMesh
object.position (string_like) – column to use to compute the position.
columns (list of string_like) – columns to include in the new catalog, if not supplied, all catalogs will be exchanged.
- Returns
A decomposed catalog source, where each rank only contains objects belongs to the rank as claimed by the domain object.
self.attrs are carried over as a shallow copy to the returned object.
- Return type
- view(type=None)¶
Return a “view” of the CatalogSource object, with the returned type set by
type
.This initializes a new empty class of type
type
and attaches attributes to it via the__finalize__()
mechanism.- Parameters
type (Python type) – the desired class type of the returned object.
- class nbodykit.source.catalog.halos.PopulatedHaloCatalog(data, model, cosmo, comm=None)[source]¶
A CatalogSource to represent a set of objects populated into a
HaloCatalog
.Note
Users should not access this class directly, but rather, call
HaloCatalog.populate()
to generate aPopulatedHaloCatalog
.- Parameters
data (structured numpy.ndarray) – the data of the populated objects
model – the Halotools model instance
cosmo (
nbodykit.cosmology.cosmology.Cosmology
) – the cosmology instance
- Attributes
Index
The attribute giving the global index rank of each particle in the list.
attrs
A dictionary storing relevant meta-data about the CatalogSource.
columns
All columns in the CatalogSource, including those hard-coded into the class’s defintion and override columns provided by the user.
csize
The total, collective size of the CatalogSource, i.e., summed across all ranks.
hardcolumns
The union of the columns in the file and any transformed columns.
size
The number of objects in the CatalogSource on the local rank.
Methods
A boolean column that selects a subset slice of the CatalogSource.
Value
()When interpolating a CatalogSource on to a mesh, the value of this array is used as the Value that each particle contributes to a given mesh cell.
Weight
()The column giving the weight to use for each particle on the mesh.
compute
(*args, **kwargs)Our version of
dask.compute()
that computes multiple delayed dask collections at once.copy
()Return a shallow copy of the object, where each column is a reference of the corresponding column in
self
.get_hardcolumn
(col)Return a column from the underlying data array/dict.
gslice
(start, stop[, end, redistribute])Execute a global slice of a CatalogSource.
make_column
(array)Utility function to convert an array-like object to a
dask.array.Array
.persist
([columns])Return a CatalogSource, where the selected columns are computed and persist in memory.
read
(columns)Return the requested columns as dask arrays.
repopulate
([seed])Re-populate the catalog in-place, using the specified
seed
or model parameters.save
(output[, columns, dataset, datasets, ...])Save the CatalogSource to a
bigfile.BigFile
.sort
(keys[, reverse, usecols])Return a CatalogSource, sorted globally across all MPI ranks in ascending order by the input keys.
to_mesh
([Nmesh, BoxSize, dtype, interlaced, ...])Convert the CatalogSource to a MeshSource, using the specified parameters.
to_subvolumes
([domain, position, columns])Domain Decompose a catalog, sending items to the ranks according to the supplied domain object.
view
([type])Return a "view" of the CatalogSource object, with the returned type set by
type
.create_instance
- property Index¶
The attribute giving the global index rank of each particle in the list. It is an integer from 0 to
self.csize
.Note that slicing changes this index value.
- Selection()¶
A boolean column that selects a subset slice of the CatalogSource.
By default, this column is set to
True
for all particles, and all CatalogSource objects will contain this column.
- Value()¶
When interpolating a CatalogSource on to a mesh, the value of this array is used as the Value that each particle contributes to a given mesh cell.
The mesh field is a weighted average of
Value
, with the weights given byWeight
.By default, this array is set to unity for all particles, and all CatalogSource objects will contain this column.
- Weight()¶
The column giving the weight to use for each particle on the mesh.
The mesh field is a weighted average of
Value
, with the weights given byWeight
.By default, this array is set to unity for all particles, and all CatalogSource objects will contain this column.
- __delitem__(col)¶
Delete a column; cannot delete a “hard-coded” column.
Note
If the
base
attribute is set, columns will be deleted frombase
instead of fromself
.
- __finalize__(other)¶
Finalize the creation of a CatalogSource object by copying over any additional attributes from a second CatalogSource.
The idea here is to only copy over attributes that are similar to meta-data, so we do not copy some of the core attributes of the
CatalogSource
object.- Parameters
other – the second object to copy over attributes from; it needs to be a subclass of CatalogSourcBase for attributes to be copied
- Returns
return
self
, with the added attributes- Return type
- __getitem__(sel)¶
The following types of indexing are supported:
strings specifying a column in the CatalogSource; returns a dask array holding the column data
boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
slice object specifying which particles to select
list of strings specifying column names; returns a CatalogSource holding only the selected columns
Notes
Slicing is a collective operation
If the
base
attribute is set, columns will be returned frombase
instead of fromself
.
- __len__()¶
The local size of the CatalogSource on a given rank.
- __setitem__(col, value)¶
Add columns to the CatalogSource, overriding any existing columns with the name
col
.
- property attrs¶
A dictionary storing relevant meta-data about the CatalogSource.
- property columns¶
All columns in the CatalogSource, including those hard-coded into the class’s defintion and override columns provided by the user.
Note
If the
base
attribute is set, the value ofbase.columns
will be returned.
- compute(*args, **kwargs)¶
Our version of
dask.compute()
that computes multiple delayed dask collections at once.This should be called on the return value of
read()
to converts any dask arrays to numpy arrays.- . note::
If the
base
attribute is set,compute()
will called usingbase
instead ofself
.
- Parameters
args (object) – Any number of objects. If the object is a dask collection, it’s computed and the result is returned. Otherwise it’s passed through unchanged.
- copy()¶
Return a shallow copy of the object, where each column is a reference of the corresponding column in
self
.Note
No copy of data is made.
Note
This is different from view in that the attributes dictionary of the copy no longer related to
self
.- Returns
a new CatalogSource that holds all of the data columns of
self
- Return type
- property csize¶
The total, collective size of the CatalogSource, i.e., summed across all ranks.
It is the sum of
size
across all available ranks.If the
base
attribute is set, thebase.csize
attribute will be returned.
- get_hardcolumn(col)¶
Return a column from the underlying data array/dict.
Columns are returned as dask arrays.
- gslice(start, stop, end=1, redistribute=True)¶
Execute a global slice of a CatalogSource.
Note
After the global slice is performed, the data is scattered evenly across all ranks.
Note
The current algorithm generates an index on the root rank and does not scale well.
- Parameters
start (int) – the start index of the global slice
stop (int) – the stop index of the global slice
step (int, optional) – the default step size of the global size
redistribute (bool, optional) – if
True
, evenly re-distribute the sliced data across all ranks, otherwise just return any local data part of the global slice
- property hardcolumns¶
The union of the columns in the file and any transformed columns.
- static make_column(array)¶
Utility function to convert an array-like object to a
dask.array.Array
.Note
The dask array chunk size is controlled via the
dask_chunk_size
global option. Seeset_options
.- Parameters
array (array_like) – an array-like object; can be a dask array, numpy array, ColumnAccessor, or other non-scalar array-like object
- Returns
a dask array initialized from
array
- Return type
- persist(columns=None)¶
Return a CatalogSource, where the selected columns are computed and persist in memory.
- read(columns)¶
Return the requested columns as dask arrays.
- Parameters
columns (list of str) – the names of the requested columns
- Returns
the list of column data, in the form of dask arrays
- Return type
list of
dask.array.Array
- repopulate(seed=None, **params)[source]¶
Re-populate the catalog in-place, using the specified
seed
or model parameters.This re-uses the model that was last used to create this catalog. It is faster than
HaloCatalog.populate()
as it avoids initialization steps. It is intended to be used when looping over different parameter sets, e.g., when performing parameter optimization.Note
This operation is performed in-place.
- Parameters
seed (int, optional) – the random seed to use when populating the mock
**params – key/value pairs specifying the model parameters to use
- save(output, columns=None, dataset=None, datasets=None, header='Header', compute=True)¶
Save the CatalogSource to a
bigfile.BigFile
.Only the selected columns are saved and
attrs
are saved inheader
. The attrs of columns are stored in the datasets.- Parameters
output (str) – the name of the file to write to
columns (list of str) – the names of the columns to save in the file, or None to use all columns
dataset (str, optional) – dataset to store the columns under.
datasets (list of str, optional) – names for the data set where each column is stored; defaults to the name of the column (deprecated)
header (str, optional, or None) – the name of the data set holding the header information, where
attrs
is stored if header is None, do not save the header.compute (boolean, default True) – if True, wait till the store operations finish if False, return a dictionary with column name and a future object for the store. use dask.compute() to wait for the store operations on the result.
- property size¶
The number of objects in the CatalogSource on the local rank.
If the
base
attribute is set, thebase.size
attribute will be returned.Important
This property must be defined for all subclasses.
- sort(keys, reverse=False, usecols=None)¶
Return a CatalogSource, sorted globally across all MPI ranks in ascending order by the input keys.
Sort columns must be floating or integer type.
Note
After the sort operation, the data is scattered evenly across all ranks.
- Parameters
keys (list, tuple) – the names of columns to sort by. If multiple columns are provided, the data is sorted consecutively in the order provided
reverse (bool, optional) – if
True
, perform descending sort operationsusecols (list, optional) – the name of the columns to include in the returned CatalogSource
- to_mesh(Nmesh=None, BoxSize=None, dtype='f4', interlaced=False, compensated=False, resampler='cic', weight='Weight', value='Value', selection='Selection', position='Position', window=None)¶
Convert the CatalogSource to a MeshSource, using the specified parameters.
- Parameters
Nmesh (int, optional) – the number of cells per side on the mesh; must be provided if not stored in
attrs
BoxSize (scalar, 3-vector, optional) – the size of the box; must be provided if not stored in
attrs
dtype (string, optional) – the data type of the mesh array
interlaced (bool, optional) – use the interlacing technique of Sefusatti et al. 2015 to reduce the effects of aliasing on Fourier space quantities computed from the mesh
compensated (bool, optional) – whether to correct for the resampler window introduced by the grid interpolation scheme
resampler (str, optional) – the string specifying which resampler interpolation scheme to use; see pmesh.resampler.methods
weight (str, optional) – the name of the column specifying the weight for each particle
value (str, optional) – the name of the column specifying the field value for each particle
selection (str, optional) – the name of the column that specifies which (if any) slice of the CatalogSource to take
position (str, optional) – the name of the column that specifies the position data of the objects in the catalog
window (str, deprecated) – use resampler instead.
- Returns
mesh – a mesh object that provides an interface for gridding particle data onto a specified mesh
- Return type
- to_subvolumes(domain=None, position='Position', columns=None)¶
Domain Decompose a catalog, sending items to the ranks according to the supplied domain object. Using the position column as the Position.
This will read in the full position array and all of the requested columns.
- Parameters
domain (
pmesh.domain.GridND
object, or None) – The domain to distribute the catalog. If None, try to evenly divide spatially. An easiest way to find a domain object is to use pm.domain, where pm is apmesh.pm.ParticleMesh
object.position (string_like) – column to use to compute the position.
columns (list of string_like) – columns to include in the new catalog, if not supplied, all catalogs will be exchanged.
- Returns
A decomposed catalog source, where each rank only contains objects belongs to the rank as claimed by the domain object.
self.attrs are carried over as a shallow copy to the returned object.
- Return type
- view(type=None)¶
Return a “view” of the CatalogSource object, with the returned type set by
type
.This initializes a new empty class of type
type
and attaches attributes to it via the__finalize__()
mechanism.- Parameters
type (Python type) – the desired class type of the returned object.