def to_numpy(self):
"""Collects the block matrix into a `NumPy ndarray
<https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html>`__.
Examples
--------
>>> from hail.linalg import BlockMatrix
>>> bm = BlockMatrix.random(10, 20)
>>> a = bm.to_numpy()
Notes
-----
The number of entries must be less than :math:`2^{31}`.
The resulting ndarray will have the same shape as the block matrix.
Returns
-------
:class:`numpy.ndarray`
"""
path = new_local_temp_file()
uri = local_path_uri(path)
self.tofile(uri)
return np.fromfile(path).reshape((self.n_rows, self.n_cols))
def _jarray_from_ndarray(nd):
if nd.size >= (1 << 31):
raise ValueError(f'size of ndarray must be less than 2^31, found {nd.size}')
nd = _ndarray_as_float64(nd)
path = new_local_temp_file()
uri = local_path_uri(path)
nd.tofile(path)
return Env.hail().utils.richUtils.RichArray.importFromDoubles(Env.hc()._jhc, uri, nd.size)
def from_numpy(cls, ndarray, block_size=None):
"""Distributes a `NumPy ndarray
<https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html>`__
as a block matrix.
Examples
--------
>>> import numpy as np
>>> a = np.random.rand(10, 20)
>>> bm = BlockMatrix.from_numpy(a)
Notes
-----
The ndarray must have two dimensions, each of non-zero size.
The number of entries must be less than :math:`2^{31}`.
Parameters
----------
ndarray: :class:`numpy.ndarray`
ndarray with two dimensions, each of non-zero size.
block_size: :obj:`int`, optional
Block size. Default given by :meth:`default_block_size`.
Returns
-------
:class:`.BlockMatrix`
"""
if not block_size:
block_size = BlockMatrix.default_block_size()
if any(i == 0 for i in ndarray.shape):
raise ValueError(
f'from_numpy: ndarray dimensions must be non-zero, found shape {ndarray.shape}'
)
nd = _ndarray_as_2d(ndarray)
nd = _ndarray_as_float64(nd)
n_rows, n_cols = nd.shape
path = new_local_temp_file()
uri = local_path_uri(path)
nd.tofile(path)
return cls.fromfile(uri, n_rows, n_cols, block_size)
def _ndarray_from_jarray(ja):
path = new_local_temp_file()
uri = local_path_uri(path)
Env.hail().utils.richUtils.RichArray.exportToDoubles(Env.hc()._jhc, uri, ja)
return np.fromfile(path)
