/usr/lib/python2.7/dist-packages/asdf/stream.py is in python-asdf 1.2.1-2.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, unicode_literals, print_function
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).tostring())
"""
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
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