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from .tags.core import ndarray
class Stream(ndarray.NDArrayType):
"""
Used to put a streamed array into the tree.
Examples
--------
Save a double-precision array with 1024 columns, one row at a
time::
>>> from asdf import AsdfFile, Stream
>>> import numpy as np
>>> ff = AsdfFile()
>>> ff.tree['streamed'] = Stream([1024], np.float64)
>>> with open('test.asdf', 'wb') as fd:
... ff.write_to(fd)
... for i in range(200):
... nbytes = fd.write(
... np.array([i] * 1024, np.float64).tobytes())
"""
name = None
types = []
def __init__(self, shape, dtype, strides=None):
self._shape = shape
self._datatype, self._byteorder = ndarray.numpy_dtype_to_asdf_datatype(dtype)
self._strides = strides
self._array = None
def _make_array(self):
self._array = None
@classmethod
def reserve_blocks(cls, data, ctx):
if isinstance(data, Stream):
yield ctx.blocks.get_streamed_block()
@classmethod
def from_tree(cls, data, ctx):
return ndarray.NDArrayType.from_tree(data, ctx)
@classmethod
def to_tree(cls, data, ctx):
ctx.blocks.get_streamed_block()
result = {}
result["source"] = -1
result["shape"] = ["*"] + data._shape
result["datatype"] = data._datatype
result["byteorder"] = data._byteorder
if data._strides is not None:
result["strides"] = data._strides
return result
def __repr__(self):
return f"Stream({self._shape}, {self._datatype}, strides={self._strides})"
def __str__(self):
return str(self.__repr__())
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