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LoomLayer (class)
=================
A LoomLayer represents a layer of data and provides a numpy ndarray-like interface.
.. highlight:: python
.. code-block:: python
with loompy.connect("mydataset.loom") as ds:
# Names of all the layers ("" is the main matrix)
ds.layers.keys()
# Upper left corner of the main matrix
ds.layers[""][0,0]
# Shorthand to slice the main matrix
ds[0,0]
# Load the entire layer named "spliced"
ds.layers["spliced"][:, :]
# Shorthand access to the layer named "spliced"
ds["spliced"][:, :]
# Assign a row of data to the named layer
ds["spliced"][0, :] = new_data
# Create a new empty layer of `ìnt32`` elements
ds["empty_layer"] = "int32"
Layers can also be accessed using numpy fancy indexing, e.g. with a vector of bools or a list of element indices.
.. tip::
Note that
using fancy indexing to slice more than ~1% of the rows (or columns) is inefficient. If you want to extract a larger subset
of rows or columns, you're better of using :meth:`.LoomConnection.scan`.
.. autoclass:: loompy.LoomLayer
:members:
:undoc-members:
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