nbodykit.source.catalog

class nbodykit.source.catalog.CSVCatalog(*args, **kwargs)

A CatalogSource that uses CSVFile to read data from disk.

Multiple files can be read at once by supplying a list of file names or a glob asterisk pattern as the path argument. See Reading Multiple Data Files at Once for examples.

Parameters:
  • path (str) – the name of the file to load
  • names (list of str) – the names of the columns of the csv file; this should give names of all the columns in the file – pass usecols to select a subset of columns
  • blocksize (int, optional) – the file will be partitioned into blocks of bytes roughly of this size
  • dtype (dict, str, optional) – if specified as a string, assume all columns have this dtype, otherwise; each column can have a dtype entry in the dict; if not specified, the data types will be inferred from the file
  • usecols (list, optional) – a pandas.read_csv; a subset of names to store, ignoring all other columns
  • delim_whitespace (bool, optional) – a pandas.read_csv keyword; if the CSV file is space-separated, set this to True
  • **config – additional keyword arguments that will be passed to pandas.read_csv(); see the documentation of that function for a full list of possible options
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator
  • attrs (dict, optional) – dictionary of meta-data to store in attrs

Examples

Please see the documentation for examples.

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

Selection() 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 file source.
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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)

Return a column from the underlying file source.

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
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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.BinaryCatalog(*args, **kwargs)

A CatalogSource that uses BinaryFile to read data from disk.

Multiple files can be read at once by supplying a list of file names or a glob asterisk pattern as the path argument. See Reading Multiple Data Files at Once for examples.

Parameters:
  • path (str) – the name of the binary file to load
  • dtype (numpy.dtype or list of tuples) – the dtypes of the columns to load; this should be either a numpy.dtype or be able to be converted to one via a numpy.dtype() call
  • offsets (dict, optional) – a dictionay specifying the byte offsets of each column in the binary file; if not supplied, the offsets are inferred from the dtype size of each column, assuming a fixed header size, and contiguous storage
  • header_size (int, optional) – the size of the header in bytes
  • size (int, optional) – the number of objects in the binary file; if not provided, the value is inferred from the dtype and the total size of the file in bytes
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator
  • attrs (dict, optional) – dictionary of meta-data to store in attrs

Examples

Please see the documentation for examples.

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

Selection() 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 file source.
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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)

Return a column from the underlying file source.

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
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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.BigFileCatalog(*args, **kwargs)

A CatalogSource that uses BigFile to read data from disk.

Multiple files can be read at once by supplying a list of file names or a glob asterisk pattern as the path argument. See Reading Multiple Data Files at Once for examples.

Parameters:
  • path (str) – the name of the directory holding the bigfile data
  • exclude (list of str, optional) – the data sets to exlude from loading within bigfile; default is the header. If any list is given, the name of the header column must be given too if it is not part of the data set. The names are shell glob patterns.
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator
  • attrs (dict, optional) – dictionary of meta-data to store in attrs

Examples

Please see the documentation for examples.

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

Selection() 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 file source.
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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)

Return a column from the underlying file source.

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
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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.HDFCatalog(*args, **kwargs)

A CatalogSource that uses HDFFile to read data from disk.

Multiple files can be read at once by supplying a list of file names or a glob asterisk pattern as the path argument. See Reading Multiple Data Files at Once for examples.

Parameters:
  • path (str) – the file path to load
  • root (str, optional) – the start path in the HDF file, loading all data below this path
  • exclude (list of str, optional) – list of path names to exclude; these can be absolute paths, or paths relative to root
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator
  • attrs (dict, optional) – dictionary of meta-data to store in attrs

Examples

Please see the documentation for examples.

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

Selection() 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 file source.
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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)

Return a column from the underlying file source.

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
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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.TPMBinaryCatalog(*args, **kwargs)

A CatalogSource that uses TPMBinaryFile to read data from disk.

Multiple files can be read at once by supplying a list of file names or a glob asterisk pattern as the path argument. See Reading Multiple Data Files at Once for examples.

Parameters:
  • path (str) – the path to the binary file to load
  • precision ({'f4', 'f8'}, optional) – the string dtype specifying the precision
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator
  • attrs (dict, optional) – dictionary of meta-data to store in attrs
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

Selection() 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 file source.
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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)

Return a column from the underlying file source.

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
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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.FITSCatalog(*args, **kwargs)

A CatalogSource that uses FITSFile to read data from disk.

Multiple files can be read at once by supplying a list of file names or a glob asterisk pattern as the path argument. See Reading Multiple Data Files at Once for examples.

Parameters:
  • path (str) – the file path to load
  • ext (number or string, optional) – The extension. Either the numerical extension from zero or a string extension name. If not sent, data is read from the first HDU that has data.
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator
  • attrs (dict, optional) – dictionary of meta-data to store in attrs

Examples

Please see the documentation for examples.

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

Selection() 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 file source.
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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)

Return a column from the underlying file source.

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
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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.Gadget1Catalog(*args, **kwargs)

A CatalogSource that uses Gadget1File to read data from disk.

Multiple files can be read at once by supplying a list of file names or a glob asterisk pattern as the path argument. See Reading Multiple Data Files at Once for examples.

Parameters:
  • path (str) – the path to the binary file to load
  • columndefs (list) – a list of triplets (columnname, element_dtype, particle_types)
  • ptype (int) – type of particle of interest.
  • hdtype (list, dtype) – dtype of the header; must define Massarr and Npart
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator
  • attrs (dict, optional) – dictionary of meta-data to store in attrs
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

Selection() 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 file source.
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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)

Return a column from the underlying file source.

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
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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.ArrayCatalog(data, comm=None, **kwargs)[source]

A CatalogSource initialized from an in-memory dict, structured numpy.ndarray, or astropy.table.Table.

Parameters:
  • data (obj:dict, numpy.ndarray, astropy.table.Table) – a dictionary, structured ndarray, or astropy Table; items are interpreted as the columns of the catalog; the length of any item is used as the size of the catalog.
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator
  • **kwargs – additional keywords to store as meta-data in attrs
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

Selection() 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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)[source]

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
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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.LogNormalCatalog(Plin, nbar, BoxSize, Nmesh, bias=2.0, seed=None, cosmo=None, redshift=None, unitary_amplitude=False, inverted_phase=False, comm=None)[source]

A CatalogSource containing biased particles that have been Poisson-sampled from a log-normal density field.

Parameters:
  • Plin (callable) – callable specifying the linear power spectrum at the desired redshift.
  • nbar (float) – the number density of the particles in the box, assumed constant across the box; this is used when Poisson sampling the density field
  • BoxSize (float, 3-vector of floats) – the size of the box to generate the grid on
  • Nmesh (int) – the mesh size to use when generating the density and displacement fields, which are Poisson-sampled to particles
  • bias (float, optional) – the desired bias of the particles; applied while applying a log-normal transformation to the density field
  • seed (int, optional) – the global random seed; if set to None, the seed will be set randomly
  • cosmo (nbodykit.cosmology.core.Cosmology, optional) – this must be supplied if Plin does not carry cosmo attribute
  • redshift (float, optional) – this must be supplied if Plin does not carry a redshift attribute
  • comm (MPI Communicator, optional) – the MPI communicator instance; default (None) sets to the current communicator

References

Cole and Jones, 1991 Agrawal et al. 2017

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

Position() Position assumed to be in Mpc/h
Selection() 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() Velocity in km/s
VelocityOffset() The corresponding RSD offset, in Mpc/h
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.
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_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  
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.

Position()[source]

Position assumed to be in 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 by Weight.

By default, this array is set to unity for all particles, and all CatalogSource objects will contain this column.

Velocity()[source]

Velocity in km/s

VelocityOffset()[source]

The corresponding RSD offset, in Mpc/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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.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 using base instead of self.

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
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 use get_hardcolumn() to bypass the decorator logic.

Note

If the base attribute is set, the value of base.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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.UniformCatalog(nbar, BoxSize, seed=None, dtype='f8', comm=None)[source]

A CatalogSource that has uniformly-distributed Position and Velocity columns.

The random numbers generated do not depend on the number of available ranks.

Parameters:
  • nbar (float) – the desired number density of particles in the box
  • BoxSize (float, 3-vector) – the size of the box
  • seed (int, optional) – the random seed
  • comm – the MPI communicator
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.

rng

A MPIRandomState that behaves as numpy.random.RandomState but generates random numbers in a manner independent of the number of ranks.

size

The number of objects in the CatalogSource on the local rank.

Methods

Position() The position of particles, uniformly distributed in BoxSize
Selection() 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 velocity of particles, uniformly distributed in 0.01 x BoxSize
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.
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_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  
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.

Position()[source]

The position of particles, uniformly distributed in BoxSize

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 by Weight.

By default, this array is set to unity for all particles, and all CatalogSource objects will contain this column.

Velocity()[source]

The velocity of particles, uniformly distributed in 0.01 x BoxSize

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.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 using base instead of self.

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
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 use get_hardcolumn() to bypass the decorator logic.

Note

If the base attribute is set, the value of base.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. See set_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:dask.array.Array
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
rng

A MPIRandomState that behaves as numpy.random.RandomState but generates random numbers in a manner independent of the number of ranks.

save(output, columns, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.RandomCatalog(csize, seed=None, comm=None)[source]

A CatalogSource that can have columns added via a collective random number generator.

The random number generator stored as rng behaves as numpy.random.RandomState but generates random numbers only on the local rank in a manner independent of the number of ranks.

Parameters:
  • csize (int) – the desired collective size of the Source
  • seed (int, optional) – the global seed for the random number generator
  • comm (MPI communicator) – the MPI communicator; set automatically if None
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.

rng

A MPIRandomState that behaves as numpy.random.RandomState but generates random numbers in a manner independent of the number of ranks.

size

The number of objects in the CatalogSource on the local rank.

Methods

Selection() 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) 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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.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 using base instead of self.

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
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 use get_hardcolumn() to bypass the decorator logic.

Note

If the base attribute is set, the value of base.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. See set_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:dask.array.Array
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
rng

A MPIRandomState that behaves as numpy.random.RandomState but generates random numbers in a manner independent of the number of ranks.

save(output, columns, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.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

Concentration() 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().
Selection() 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.
VelocityOffset() 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.
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.

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.

Mass()[source]

The halo mass column, assumed to be in units of \(M_\odot/h\).

Position()[source]

The halo position column, assumed to be in units of \(\mathrm{Mpc}/h\).

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 by Weight.

By default, this array is set to unity for all particles, and all CatalogSource objects will contain this column.

Velocity()[source]

The halo velocity column, assumed to be in units of km/s.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.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 using base instead of self.

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
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 use get_hardcolumn() to bypass the decorator logic.

Note

If the base attribute is set, the value of base.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. See set_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:dask.array.Array
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 returned PopulatedHaloCatalog.

Parameters:
  • model (nbodykit.hod.HODModel or halotools model object) – the model instance to use to populate; model types from nbodykit.hod will automatically be converted
  • BoxSize (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:

PopulatedHaloCatalog

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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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.

Parameters:BoxSize (float, array_like, optional) – the size of the box; must be supplied if ‘BoxSize’ is not in the attrs dict
Returns:cat – the Halotools halo catalog, storing the local halo data
Return type:halotools.sim_manager.UserSuppliedHaloCatalog
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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.SubVolumesCatalog(source, domain=None, position='Position', columns=None)[source]

A catalog that distributes the particles spatially into subvolumes per MPI rank.

domain

The domain objects for decomposition. If None, generate a domain to decompose the catalog into a 3d grid.

Type::pyclass:`pmesh.domain.GridND`;
layout
Type:A large object that holds which particle belongs to which rank.
source
Type:the original source object
Parameters:

columns (list) – a list of columns to already exchange

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

Selection() 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) 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.
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_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  
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 by Weight.

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 by Weight.

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 from base instead of from self.

__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:CatalogSource
__getitem__(sel)

The following types of indexing are supported:

  1. strings specifying a column in the CatalogSource; returns a dask array holding the column data
  2. boolean arrays specifying a slice of the CatalogSource; returns a CatalogSource holding only the revelant slice
  3. slice object specifying which particles to select
  4. 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 from base instead of from self.
__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.

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.

Note

If the base attribute is set, the value of base.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 using base instead of self.
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:CatalogSource
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, the base.csize attribute will be returned.

get_hardcolumn(col)[source]

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 using base instead of self.

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
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 use get_hardcolumn() to bypass the decorator logic.

Note

If the base attribute is set, the value of base.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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
size

The number of objects in the CatalogSource on the local rank.

If the base attribute is set, the base.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 operations
  • usecols (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:

CatalogMesh

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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.MultipleSpeciesCatalog(names, *species, **kwargs)[source]

A CatalogSource interface for handling multiples species of particles.

This CatalogSource stores a copy of the original CatalogSource objects for each species, providing access to the columns via the format species/ where “species” is one of the species names provided.

Parameters:
  • names (list of str) – list of strings specifying the names of the various species; data columns are prefixed with “species/” where “species” is in names
  • *species (two or more CatalogSource objects) – catalogs to be combined into a single catalog, which give the data for different species of particles; as many catalogs as names must be provided

Examples

Initialization:

>>> data = UniformCatalog(nbar=3e-5, BoxSize=512., seed=42)
>>> randoms = UniformCatalog(nbar=3e-5, BoxSize=512., seed=84)
>>> cat = MultipleSpeciesCatalog(['data', 'randoms'], data, randoms)

Accessing the Catalogs for individual species:

>>> data = cat["data"] # a copy of the original "data" object

Accessing individual columns:

>>> data_pos = cat["data/Position"]

Setting new columns:

>>> cat["data"]["new_column"] = 1.0
>>> assert "data/new_column" in cat
Attributes:
attrs

A dictionary storing relevant meta-data about the CatalogSource.

columns

Columns for individual species can be accessed using a species/ prefix and the column name, i.e., data/Position.

hardcolumns

Hardcolumn of the form species/name

species

List of species names

Methods

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.
make_column(array) Utility function to convert an array-like object to a dask.array.Array.
read(columns) Return the requested columns as dask arrays.
save(output, columns[, dataset, datasets, …]) Save the CatalogSource to a bigfile.BigFile.
to_mesh([Nmesh, BoxSize, dtype, interlaced, …]) Convert the catalog to a mesh, which knows how to “paint” the the combined density field, summed over all particle species.
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  
__delitem__(col)[source]

Delete a column of the form species/column

__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:CatalogSource
__getitem__(key)[source]

This provides access to the underlying data in two ways:

  • The CatalogSource object for a species can be accessed if key is a species name.
  • Individual columns for a species can be accessed using the format: species/column.
__setitem__(col, value)[source]

Add columns to any of the species catalogs.

Note

New column names should be prefixed by ‘species/’ where ‘species’ is a name in the species attribute.

attrs

A dictionary storing relevant meta-data about the CatalogSource.

columns

Columns for individual species can be accessed using a species/ prefix and the column name, i.e., data/Position.

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 using base instead of self.
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:CatalogSource
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 using base instead of self.

hardcolumns

Hardcolumn of the form species/name

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. See set_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:dask.array.Array
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, dataset=None, datasets=None, header='Header')

Save the CatalogSource to a bigfile.BigFile.

Only the selected columns are saved and attrs are saved in header. 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
  • 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.
species

List of species names

to_mesh(Nmesh=None, BoxSize=None, dtype='f4', interlaced=False, compensated=False, resampler='cic', weight='Weight', value='Value', selection='Selection', position='Position', window=None)[source]

Convert the catalog to a mesh, which knows how to “paint” the the combined density field, summed over all particle species.

Parameters:
  • Nmesh (int, 3-vector, optional) – the number of cells per box side; can be inferred from attrs if the value is the same for all species
  • BoxSize (float, 3-vector, optional) – the size of the box; can be inferred from attrs if the value is the same for all species
  • dtype (str, dtype, optional) – the data type of the mesh when painting
  • interlaced (bool, optional) – whether to use interlacing to reduce aliasing when painting the particles on the mesh
  • compensated (bool, optional) – whether to apply a Fourier-space transfer function to account for the effects of the gridding + aliasing
  • resampler (str, optional) – the string name of the resampler to use when interpolating the
  • weight (str, optional) – the name of the column specifying the weight for each particle
  • selection (str, optional) – the name of the column that specifies which (if any) slice of the CatalogSource to take
  • value (str, optional) – the name of the column specifying the field value for each particle
  • position (str, optional) – the name of the column that specifies the position data of the objects in the catalog
  • window (str, optional) – the string name of the window to use when interpolating (deprecated, use resampler)
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 (:pyclass:`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 a :pyclass:`pmesh.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:

CatalogSource

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.