/usr/lib/python2.7/dist-packages/h5py/tests/old/test_slicing.py is in python-h5py 2.7.1-2.
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#
# http://www.h5py.org
#
# Copyright 2008-2013 Andrew Collette and contributors
#
# License: Standard 3-clause BSD; see "license.txt" for full license terms
# and contributor agreement.
"""
Dataset slicing test module.
Tests all supported slicing operations, including read/write and
broadcasting operations. Does not test type conversion except for
corner cases overlapping with slicing; for example, when selecting
specific fields of a compound type.
"""
from __future__ import absolute_import
import six
import numpy as np
from ..common import ut, TestCase
import h5py
from h5py import h5s, h5t, h5d
from h5py.highlevel import File
class BaseSlicing(TestCase):
def setUp(self):
self.f = File(self.mktemp(), 'w')
def tearDown(self):
if self.f:
self.f.close()
class TestSingleElement(BaseSlicing):
"""
Feature: Retrieving a single element works with NumPy semantics
"""
def test_single_index(self):
""" Single-element selection with [index] yields array scalar """
dset = self.f.create_dataset('x', (1,), dtype='i1')
out = dset[0]
self.assertIsInstance(out, np.int8)
def test_single_null(self):
""" Single-element selection with [()] yields ndarray """
dset = self.f.create_dataset('x', (1,), dtype='i1')
out = dset[()]
self.assertIsInstance(out, np.ndarray)
self.assertEqual(out.shape, (1,))
def test_scalar_index(self):
""" Slicing with [...] yields scalar ndarray """
dset = self.f.create_dataset('x', shape=(), dtype='f')
out = dset[...]
self.assertIsInstance(out, np.ndarray)
self.assertEqual(out.shape, ())
def test_scalar_null(self):
""" Slicing with [()] yields array scalar """
dset = self.f.create_dataset('x', shape=(), dtype='i1')
out = dset[()]
self.assertIsInstance(out, np.int8)
def test_compound(self):
""" Compound scalar is numpy.void, not tuple (issue 135) """
dt = np.dtype([('a','i4'),('b','f8')])
v = np.ones((4,), dtype=dt)
dset = self.f.create_dataset('foo', (4,), data=v)
self.assertEqual(dset[0], v[0])
self.assertIsInstance(dset[0], np.void)
class TestObjectIndex(BaseSlicing):
"""
Feauture: numpy.object_ subtypes map to real Python objects
"""
def test_reference(self):
""" Indexing a reference dataset returns a h5py.Reference instance """
dset = self.f.create_dataset('x', (1,), dtype=h5py.special_dtype(ref=h5py.Reference))
dset[0] = self.f.ref
self.assertEqual(type(dset[0]), h5py.Reference)
def test_regref(self):
""" Indexing a region reference dataset returns a h5py.RegionReference
"""
dset1 = self.f.create_dataset('x', (10,10))
regref = dset1.regionref[...]
dset2 = self.f.create_dataset('y', (1,), dtype=h5py.special_dtype(ref=h5py.RegionReference))
dset2[0] = regref
self.assertEqual(type(dset2[0]), h5py.RegionReference)
def test_reference_field(self):
""" Compound types of which a reference is an element work right """
reftype = h5py.special_dtype(ref=h5py.Reference)
dt = np.dtype([('a', 'i'),('b',reftype)])
dset = self.f.create_dataset('x', (1,), dtype=dt)
dset[0] = (42, self.f['/'].ref)
out = dset[0]
self.assertEqual(type(out[1]), h5py.Reference) # isinstance does NOT work
def test_scalar(self):
""" Indexing returns a real Python object on scalar datasets """
dset = self.f.create_dataset('x', (), dtype=h5py.special_dtype(ref=h5py.Reference))
dset[()] = self.f.ref
self.assertEqual(type(dset[()]), h5py.Reference)
def test_bytestr(self):
""" Indexing a byte string dataset returns a real python byte string
"""
dset = self.f.create_dataset('x', (1,), dtype=h5py.special_dtype(vlen=bytes))
dset[0] = b"Hello there!"
self.assertEqual(type(dset[0]), bytes)
class TestSimpleSlicing(TestCase):
"""
Feature: Simple NumPy-style slices (start:stop:step) are supported.
"""
def setUp(self):
self.f = File(self.mktemp(), 'w')
self.arr = np.arange(10)
self.dset = self.f.create_dataset('x', data=self.arr)
def tearDown(self):
if self.f:
self.f.close()
def test_negative_stop(self):
""" Negative stop indexes work as they do in NumPy """
self.assertArrayEqual(self.dset[2:-2], self.arr[2:-2])
class TestArraySlicing(BaseSlicing):
"""
Feature: Array types are handled appropriately
"""
def test_read(self):
""" Read arrays tack array dimensions onto end of shape tuple """
dt = np.dtype('(3,)f8')
dset = self.f.create_dataset('x',(10,),dtype=dt)
self.assertEqual(dset.shape, (10,))
self.assertEqual(dset.dtype, dt)
# Full read
out = dset[...]
self.assertEqual(out.dtype, np.dtype('f8'))
self.assertEqual(out.shape, (10,3))
# Single element
out = dset[0]
self.assertEqual(out.dtype, np.dtype('f8'))
self.assertEqual(out.shape, (3,))
# Range
out = dset[2:8:2]
self.assertEqual(out.dtype, np.dtype('f8'))
self.assertEqual(out.shape, (3,3))
def test_write_broadcast(self):
""" Array fill from constant is not supported (issue 211).
"""
dt = np.dtype('(3,)i')
dset = self.f.create_dataset('x', (10,), dtype=dt)
with self.assertRaises(TypeError):
dset[...] = 42
def test_write_element(self):
""" Write a single element to the array
Issue 211.
"""
dt = np.dtype('(3,)f8')
dset = self.f.create_dataset('x', (10,), dtype=dt)
data = np.array([1,2,3.0])
dset[4] = data
out = dset[4]
self.assertTrue(np.all(out == data))
def test_write_slices(self):
""" Write slices to array type """
dt = np.dtype('(3,)i')
data1 = np.ones((2,), dtype=dt)
data2 = np.ones((4,5), dtype=dt)
dset = self.f.create_dataset('x', (10,9,11), dtype=dt)
dset[0,0,2:4] = data1
self.assertArrayEqual(dset[0,0,2:4], data1)
dset[3, 1:5, 6:11] = data2
self.assertArrayEqual(dset[3, 1:5, 6:11], data2)
def test_roundtrip(self):
""" Read the contents of an array and write them back
Issue 211.
"""
dt = np.dtype('(3,)f8')
dset = self.f.create_dataset('x', (10,), dtype=dt)
out = dset[...]
dset[...] = out
self.assertTrue(np.all(dset[...] == out))
class TestZeroLengthSlicing(BaseSlicing):
"""
Slices resulting in empty arrays
"""
def test_slice_zero_length_dimension(self):
""" Slice a dataset with a zero in its shape vector
along the zero-length dimension """
for i, shape in enumerate([(0,), (0, 3), (0, 2, 1)]):
dset = self.f.create_dataset('x%d'%i, shape, dtype=np.int, maxshape=(None,)*len(shape))
self.assertEqual(dset.shape, shape)
out = dset[...]
self.assertIsInstance(out, np.ndarray)
self.assertEqual(out.shape, shape)
out = dset[:]
self.assertIsInstance(out, np.ndarray)
self.assertEqual(out.shape, shape)
if len(shape) > 1:
out = dset[:, :1]
self.assertIsInstance(out, np.ndarray)
self.assertEqual(out.shape[:2], (0, 1))
def test_slice_other_dimension(self):
""" Slice a dataset with a zero in its shape vector
along a non-zero-length dimension """
for i, shape in enumerate([(3, 0), (1, 2, 0), (2, 0, 1)]):
dset = self.f.create_dataset('x%d'%i, shape, dtype=np.int, maxshape=(None,)*len(shape))
self.assertEqual(dset.shape, shape)
out = dset[:1]
self.assertIsInstance(out, np.ndarray)
self.assertEqual(out.shape, (1,)+shape[1:])
def test_slice_of_length_zero(self):
""" Get a slice of length zero from a non-empty dataset """
for i, shape in enumerate([(3,), (2, 2,), (2, 1, 5)]):
dset = self.f.create_dataset('x%d'%i, data=np.zeros(shape, np.int), maxshape=(None,)*len(shape))
self.assertEqual(dset.shape, shape)
out = dset[1:1]
self.assertIsInstance(out, np.ndarray)
self.assertEqual(out.shape, (0,)+shape[1:])
class TestFieldNames(BaseSlicing):
"""
Field names for read & write
"""
dt = np.dtype([('a', 'f'), ('b', 'i'), ('c', 'f4')])
data = np.ones((100,), dtype=dt)
def setUp(self):
BaseSlicing.setUp(self)
self.dset = self.f.create_dataset('x', (100,), dtype=self.dt)
self.dset[...] = self.data
def test_read(self):
""" Test read with field selections (bytes and unicode) """
if six.PY2:
# Byte strings are only allowed for field names on Py2
self.assertArrayEqual(self.dset[b'a'], self.data['a'])
self.assertArrayEqual(self.dset[u'a'], self.data['a'])
def test_unicode_names(self):
""" Unicode field names for for read and write """
self.assertArrayEqual(self.dset[u'a'], self.data['a'])
self.dset[u'a'] = 42
data = self.data.copy()
data['a'] = 42
self.assertArrayEqual(self.dset[u'a'], data['a'])
def test_write(self):
""" Test write with field selections """
data2 = self.data.copy()
data2['a'] *= 2
self.dset['a'] = data2
self.assertTrue(np.all(self.dset[...] == data2))
data2['b'] *= 4
self.dset['b'] = data2
self.assertTrue(np.all(self.dset[...] == data2))
data2['a'] *= 3
data2['c'] *= 3
self.dset['a','c'] = data2
self.assertTrue(np.all(self.dset[...] == data2))
def test_write_noncompound(self):
""" Test write with non-compound source (single-field) """
data2 = self.data.copy()
data2['b'] = 1.0
self.dset['b'] = 1.0
self.assertTrue(np.all(self.dset[...] == data2))
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