| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226 |
- # This file is part of h5py, a Python interface to the HDF5 library.
- #
- # 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.
- import numpy as np
- from .common import TestCase, is_main_thread, make_name
- from h5py import File
- import h5py
- class BaseDataset(TestCase):
- """
- data is a 3-dimensional dataset with dimensions [z, y, x]
- The z dimension is labeled. It does not have any attached scales.
- The y dimension is not labeled. It has one attached scale.
- The x dimension is labeled. It has two attached scales.
- data2 is a 3-dimensional dataset with no associated dimension scales.
- """
- def setUp(self):
- self.f = File(self.mktemp(), 'w')
- self.f['data'] = np.ones((4, 3, 2), 'f')
- self.f['data2'] = np.ones((4, 3, 2), 'f')
- self.f['x1'] = np.ones((2), 'f')
- h5py.h5ds.set_scale(self.f['x1'].id)
- h5py.h5ds.attach_scale(self.f['data'].id, self.f['x1'].id, 2)
- self.f['x2'] = np.ones((2), 'f')
- h5py.h5ds.set_scale(self.f['x2'].id, b'x2 name')
- h5py.h5ds.attach_scale(self.f['data'].id, self.f['x2'].id, 2)
- self.f['y1'] = np.ones((3), 'f')
- h5py.h5ds.set_scale(self.f['y1'].id, b'y1 name')
- h5py.h5ds.attach_scale(self.f['data'].id, self.f['y1'].id, 1)
- self.f['z1'] = np.ones((4), 'f')
- h5py.h5ds.set_label(self.f['data'].id, 0, b'z')
- h5py.h5ds.set_label(self.f['data'].id, 2, b'x')
- def tearDown(self):
- if self.f:
- self.f.close()
- class TestH5DSBindings(BaseDataset):
- """
- Feature: Datasets can be created from existing data
- """
- def test_create_dimensionscale(self):
- """ Create a dimension scale from existing dataset """
- self.assertTrue(h5py.h5ds.is_scale(self.f['x1'].id))
- self.assertEqual(h5py.h5ds.get_scale_name(self.f['x1'].id), b'')
- self.assertEqual(self.f['x1'].attrs['CLASS'], b"DIMENSION_SCALE")
- self.assertEqual(h5py.h5ds.get_scale_name(self.f['x2'].id), b'x2 name')
- def test_attach_dimensionscale(self):
- self.assertTrue(
- h5py.h5ds.is_attached(self.f['data'].id, self.f['x1'].id, 2)
- )
- self.assertFalse(
- h5py.h5ds.is_attached(self.f['data'].id, self.f['x1'].id, 1))
- self.assertEqual(h5py.h5ds.get_num_scales(self.f['data'].id, 0), 0)
- self.assertEqual(h5py.h5ds.get_num_scales(self.f['data'].id, 1), 1)
- self.assertEqual(h5py.h5ds.get_num_scales(self.f['data'].id, 2), 2)
- def test_detach_dimensionscale(self):
- name = make_name()
- self.f[name] = np.ones((4, 3, 2), 'f')
- ds = self.f[name]
- h5py.h5ds.attach_scale(ds.id, self.f['x1'].id, 2)
- h5py.h5ds.attach_scale(ds.id, self.f['x2'].id, 2)
- self.assertTrue(h5py.h5ds.is_attached(ds.id, self.f['x1'].id, 2))
- self.assertEqual(h5py.h5ds.get_num_scales(ds.id, 2), 2)
- h5py.h5ds.detach_scale(ds.id, self.f['x1'].id, 2)
- self.assertFalse(h5py.h5ds.is_attached(ds.id, self.f['x1'].id, 2))
- self.assertEqual(h5py.h5ds.get_num_scales(ds.id, 2), 1)
- def test_label_dimensionscale(self):
- self.assertEqual(h5py.h5ds.get_label(self.f['data'].id, 0), b'z')
- self.assertEqual(h5py.h5ds.get_label(self.f['data'].id, 1), b'')
- self.assertEqual(h5py.h5ds.get_label(self.f['data'].id, 2), b'x')
- def test_iter_dimensionscales(self):
- def func(dsid):
- res = h5py.h5ds.get_scale_name(dsid)
- if res == b'x2 name':
- return dsid
- res = h5py.h5ds.iterate(self.f['data'].id, 2, func, 0)
- self.assertEqual(h5py.h5ds.get_scale_name(res), b'x2 name')
- class TestDimensionManager(BaseDataset):
- def test_make_scale(self):
- # test recreating or renaming an existing scale:
- self.f['x1'].make_scale(b'foobar')
- self.assertEqual(self.f['data'].dims[2]['foobar'], self.f['x1'])
- # test creating entirely new scale:
- self.f['data2'].make_scale(b'foobaz')
- self.f['data'].dims[2].attach_scale(self.f['data2'])
- self.assertEqual(self.f['data'].dims[2]['foobaz'], self.f['data2'])
- def test_get_dimension(self):
- with self.assertRaises(IndexError):
- self.f['data'].dims[3]
- def test_len(self):
- self.assertEqual(len(self.f['data'].dims), 3)
- self.assertEqual(len(self.f['data2'].dims), 3)
- def test_iter(self):
- dims = self.f['data'].dims
- self.assertEqual(
- [d for d in dims],
- [dims[0], dims[1], dims[2]]
- )
- def test_repr(self):
- ds = self.f.create_dataset(make_name(), (2,3), "f4")
- self.assertIsInstance(repr(ds.dims), str)
- if is_main_thread():
- self.f.close()
- self.assertIsInstance(repr(ds.dims), str)
- class TestDimensionsHighLevel(BaseDataset):
- def test_len(self):
- self.assertEqual(len(self.f['data'].dims[0]), 0)
- self.assertEqual(len(self.f['data'].dims[1]), 1)
- self.assertEqual(len(self.f['data'].dims[2]), 2)
- self.assertEqual(len(self.f['data2'].dims[0]), 0)
- self.assertEqual(len(self.f['data2'].dims[1]), 0)
- self.assertEqual(len(self.f['data2'].dims[2]), 0)
- def test_get_label(self):
- self.assertEqual(self.f['data'].dims[2].label, 'x')
- self.assertEqual(self.f['data'].dims[1].label, '')
- self.assertEqual(self.f['data'].dims[0].label, 'z')
- self.assertEqual(self.f['data2'].dims[2].label, '')
- self.assertEqual(self.f['data2'].dims[1].label, '')
- self.assertEqual(self.f['data2'].dims[0].label, '')
- def test_set_label(self):
- self.f['data'].dims[0].label = 'foo'
- self.assertEqual(self.f['data'].dims[2].label, 'x')
- self.assertEqual(self.f['data'].dims[1].label, '')
- self.assertEqual(self.f['data'].dims[0].label, 'foo')
- def test_attach_detach_scale(self):
- name = make_name('data3')
- self.f[name] = self.f['data'][...]
- ds = self.f[name]
- ds.dims[2].attach_scale(self.f["x1"])
- ds.dims[2].attach_scale(self.f["x2"])
- self.assertEqual(len(ds.dims[2]), 2)
- self.assertEqual(ds.dims[2][0], self.f["x1"])
- self.assertEqual(ds.dims[2][1], self.f["x2"])
- ds.dims[2].detach_scale(self.f["x1"])
- self.assertEqual(len(ds.dims[2]), 1)
- self.assertEqual(ds.dims[2][0], self.f["x2"])
- ds.dims[2].detach_scale(self.f["x2"])
- self.assertEqual(len(ds.dims[2]), 0)
- def test_get_dimension_scale(self):
- self.assertEqual(self.f['data'].dims[2][0], self.f['x1'])
- with self.assertRaises(RuntimeError):
- self.f['data2'].dims[2][0], self.f['x2']
- self.assertEqual(self.f['data'].dims[2][''], self.f['x1'])
- self.assertEqual(self.f['data'].dims[2]['x2 name'], self.f['x2'])
- def test_get_items(self):
- self.assertEqual(
- self.f['data'].dims[2].items(),
- [('', self.f['x1']), ('x2 name', self.f['x2'])]
- )
- def test_get_keys(self):
- self.assertEqual(self.f['data'].dims[2].keys(), ['', 'x2 name'])
- def test_get_values(self):
- self.assertEqual(
- self.f['data'].dims[2].values(),
- [self.f['x1'], self.f['x2']]
- )
- def test_iter(self):
- self.assertEqual([i for i in self.f['data'].dims[2]], ['', 'x2 name'])
- def test_repr(self):
- ds = self.f["data"]
- self.assertEqual(repr(ds.dims[2])[1:16], '"x" dimension 2')
- if is_main_thread():
- self.f.close()
- self.assertIsInstance(repr(ds.dims), str)
- def test_attributes(self):
- self.f["data2"].attrs["DIMENSION_LIST"] = self.f["data"].attrs[
- "DIMENSION_LIST"]
- self.assertEqual(len(self.f['data2'].dims[0]), 0)
- self.assertEqual(len(self.f['data2'].dims[1]), 1)
- self.assertEqual(len(self.f['data2'].dims[2]), 2)
- def test_is_scale(self):
- """Test Dataset.is_scale property"""
- self.assertTrue(self.f['x1'].is_scale)
- self.assertTrue(self.f['x2'].is_scale)
- self.assertTrue(self.f['y1'].is_scale)
- self.assertFalse(self.f['z1'].is_scale)
- self.assertFalse(self.f['data'].is_scale)
- self.assertFalse(self.f['data2'].is_scale)
|