def test_manifest_func():
x = Array([1, 2, 3])
y = Array([1, 2, 3])
val = add(x, y)
assert val[0] == 2
assert val[1] == 4
assert val[2] == 6
def test_all_construct():
# Assert that the pretty pritner works for all of the
# toplevel structures
expected_ds = dshape('3, int')
a = NDArray([1,2,3])
str(a)
repr(a)
a.datashape._equal(expected_ds)
a = Array([1,2,3])
str(a)
repr(a)
a.datashape._equal(expected_ds)
a = NDTable([(1, 1)])
str(a)
repr(a)
#a.datashape._equal(expected_ds)
a = Table([(1, 1)])
str(a)
repr(a)
def test_getitem_nd():
# create
nd = ndarr()
barray = Array(nd)
# read
data = barray[:]
assert np.all(data == nd)
def test_simple_persistence():
import tempfile, shutil, os.path
import numpy as np
from blaze import Array, dshape, params
ds = dshape('2, 2, float64')
data = np.zeros(4).reshape(2,2)
td = tempfile.mkdtemp()
tmppath = os.path.join(td, 'a')
a = Array([1,2,3,4], ds, params=params(storage=tmppath))
# Remove everything under the temporary dir
shutil.rmtree(td)
def dd_as_py(dd):
"""
Converts the data in a data descriptor into Python
types. This uses the data_descriptor iteration methods,
so is not expected to be fast. Its main initial purpose
is to assist with writing unit tests.
"""
# TODO: This function should probably be removed.
if not isinstance(dd, IDataDescriptor):
raise TypeError('expected DataDescriptor, got %r' % type(dd))
if isinstance(dd, BLZDataDescriptor):
return [dd_as_py(child_dd) for child_dd in dd]
if dd.capabilities.deferred:
from blaze import Array, eval
dd = eval(Array(dd))._data
return nd.as_py(dd.dynd_arr())
def test_getitem_nd_persistent():
import tempfile, shutil, os.path
td = tempfile.mkdtemp()
path = os.path.join(td, 'test.blz')
# write
bparams = params(storage=path, clevel=6)
nd = ndarr()
barray = Array(nd, params=bparams)
# read
arr = open(path)
data = arr[:]
assert np.all(data == nd)
shutil.rmtree(td)
def arr():
return Array([1, 2, 3], '3, int32')
def test_simple_session():
from blaze import Array, dshape
ds = dshape('2, 2, int')
a = Array([1,2,3,4], ds)