Functions
find_slice_chunks (index) |
A generator to yield (start, stop, step) tuples |
Classes
FileType |
An abstract base class representing a file object. |
nbodykit.io.base.
FileType
[source]¶An abstract base class representing a file object.
Users should subclass this class and implement the read()
function, responsible for reading data from the specific file type.
Attributes
columns |
A list of the names of the columns in the file. |
dtype |
A numpy.dtype object holding the data types of each column in the file. |
ncol |
The number of data columns in the file. |
shape |
The shape of the file, which defaults to (size, ) |
size |
The size of the file, i.e., number of rows |
Methods
asarray () |
Return a view of the file, where the fields of the |
get_dask (column[, blocksize]) |
Return the specified column as a dask array, which |
keys () |
Aliased function to return columns |
read (columns, start, stop[, step]) |
Read the specified column(s) over the given range, |
__getitem__
(s)[source]¶This function provides numpy-like array indexing of the file object.
It supports:
keys()
Note
If a single column is being returned, a numpy array holding the data is returned, rather than a structured array with only a single field.
asarray
()[source]¶Return a view of the file, where the fields of the structured array are stacked in columns of a single numpy array
Examples
Start with a file object with three named columns,
ra
, dec
, and z
>>> ff.dtype
dtype([('ra', '<f4'), ('dec', '<f4'), ('z', '<f4')])
>>> ff.shape
(1000,)
>>> ff.columns
['ra', 'dec', 'z']
>>> ff[:3]
array([(235.63442993164062, 59.39099884033203, 0.6225500106811523),
(140.36181640625, -1.162310004234314, 0.5026500225067139),
(129.96627807617188, 45.970130920410156, 0.4990200102329254)],
dtype=(numpy.record, [('ra', '<f4'), ('dec', '<f4'), ('z', '<f4')]))
Select a subset of columns and switch the ordering and convert output to a single numpy array
>>> x = ff[['dec', 'ra']].asarray()
>>> x.dtype
dtype('float32')
>>> x.shape
(1000, 2)
>>> x.columns
['dec', 'ra']
>>> x[:3]
array([[ 59.39099884, 235.63442993],
[ -1.16231 , 140.36181641],
[ 45.97013092, 129.96627808]], dtype=float32)
Now, select only the first column (dec
)
>>> dec = x[:,0]
>>> dec[:3]
array([ 59.39099884, -1.16231 , 45.97013092], dtype=float32)
Returns: | a file object that will return a numpy array with the columns representing the fields |
---|---|
Return type: | FileType |
columns
¶A list of the names of the columns in the file.
This defaults to the named fields in the file’s dtype
attribute, but differ from this if a view of the file has been
returned with asarray()
dtype
¶A numpy.dtype
object holding the data types of each column in the file.
get_dask
(column, blocksize=None)[source]¶Return the specified column as a dask array, which
delays the explicit reading of the data until
dask.compute()
is called
The dask array is chunked into blocks of size blocksize
Parameters: | |
---|---|
Returns: | the dask array holding the column, which computes the necessary functions to read the data, but delays evaluating until the user specifies |
Return type: |
ncol
¶The number of data columns in the file.
read
(columns, start, stop, step=1)[source]¶Read the specified column(s) over the given range, returning a structured numpy array
Parameters: | |
---|---|
Returns: | data – a numpy structured array holding the requested data |
Return type: | array_like |
shape
¶The shape of the file, which defaults to (size, )
Multiple dimensions can be introduced into the shape if
a view of the file has been returned with asarray()
size
¶The size of the file, i.e., number of rows
nbodykit.io.base.
find_slice_chunks
(index)[source]¶A generator to yield (start, stop, step) tuples which will correspond to the input selection index
index
can be either a boolen index, or a list of integers
specifying the rows to include
Parameters: | index (array_like) – either a boolean array, indicating which rows to select, or integers specifying which rows to include |
---|---|
Yields: | (start, stop, step) (tuple of int) – the slice integers to read, corresponding to a valid spart of the selection index |