# 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.

"""
    Tests the h5py.Dataset.__getitem__ method.

    This module does not specifically test type conversion.  The "type" axis
    therefore only tests objects which interact with the slicing system in
    unreliable ways; for example, compound and array types.

    See test_dataset_getitem_types for type-conversion tests.

    Tests are organized into TestCases by dataset shape and type.  Test
    methods vary by slicing arg type.

    1. Dataset shape:
        Empty
        Scalar
        1D
        3D

    2. Type:
        Float
        Compound
        Array

    3. Slicing arg types:
        Ellipsis
        Empty tuple
        Regular slice
        MultiBlockSlice
        Indexing
        Index list
        Boolean mask
        Field names
"""

import sys

import numpy as np
import h5py

from .common import ut, TestCase


class TestEmpty(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        sid = h5py.h5s.create(h5py.h5s.NULL)
        tid = h5py.h5t.C_S1.copy()
        tid.set_size(10)
        dsid = h5py.h5d.create(self.f.id, b'x', tid, sid)
        self.dset = h5py.Dataset(dsid)
        self.empty_obj = h5py.Empty(np.dtype("S10"))

    def test_ndim(self):
        """ Verify number of dimensions """
        self.assertEqual(self.dset.ndim, 0)

    def test_shape(self):
        """ Verify shape """
        self.assertEqual(self.dset.shape, None)

    def test_size(self):
        """ Verify shape """
        self.assertEqual(self.dset.size, None)

    def test_nbytes(self):
        """ Verify nbytes """
        self.assertEqual(self.dset.nbytes, 0)

    def test_ellipsis(self):
        self.assertEqual(self.dset[...], self.empty_obj)

    def test_tuple(self):
        self.assertEqual(self.dset[()], self.empty_obj)

    def test_slice(self):
        """ slice -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[0:4]

    def test_multi_block_slice(self):
        """ MultiBlockSlice -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[h5py.MultiBlockSlice()]

    def test_index(self):
        """ index -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[0]

    def test_indexlist(self):
        """ index list -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[[1,2,5]]

    def test_mask(self):
        """ mask -> ValueError """
        mask = np.array(True, dtype='bool')
        with self.assertRaises(ValueError):
            self.dset[mask]

    def test_fieldnames(self):
        """ field name -> ValueError """
        with self.assertRaises(ValueError):
            self.dset['field']


class TestScalarFloat(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        self.data = np.array(42.5, dtype=np.double)
        self.dset = self.f.create_dataset('x', data=self.data)

    def test_ndim(self):
        """ Verify number of dimensions """
        self.assertEqual(self.dset.ndim, 0)

    def test_size(self):
        """ Verify size """
        self.assertEqual(self.dset.size, 1)

    def test_nbytes(self):
        """ Verify nbytes """
        self.assertEqual(self.dset.nbytes, self.data.dtype.itemsize)  # not sure if 'f' is always alias for 'f4'

    def test_shape(self):
        """ Verify shape """
        self.assertEqual(self.dset.shape, tuple())

    def test_ellipsis(self):
        """ Ellipsis -> scalar ndarray """
        out = self.dset[...]
        self.assertArrayEqual(out, self.data)

    def test_tuple(self):
        """ () -> bare item """
        out = self.dset[()]
        self.assertArrayEqual(out, self.data.item())

    def test_slice(self):
        """ slice -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[0:4]

    def test_multi_block_slice(self):
        """ MultiBlockSlice -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[h5py.MultiBlockSlice()]

    def test_index(self):
        """ index -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[0]

    # FIXME: NumPy has IndexError instead
    def test_indexlist(self):
        """ index list -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[[1,2,5]]

    # FIXME: NumPy permits this
    def test_mask(self):
        """ mask -> ValueError """
        mask = np.array(True, dtype='bool')
        with self.assertRaises(ValueError):
            self.dset[mask]

    def test_fieldnames(self):
        """ field name -> ValueError (no fields) """
        with self.assertRaises(ValueError):
            self.dset['field']


class TestScalarCompound(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        self.data = np.array((42.5, -118, "Hello"), dtype=[('a', 'f'), ('b', 'i'), ('c', '|S10')])
        self.dset = self.f.create_dataset('x', data=self.data)

    def test_ndim(self):
        """ Verify number of dimensions """
        self.assertEqual(self.dset.ndim, 0)

    def test_shape(self):
        """ Verify shape """
        self.assertEqual(self.dset.shape, tuple())

    def test_size(self):
        """ Verify size """
        self.assertEqual(self.dset.size, 1)

    def test_nbytes(self):
        """ Verify nbytes """
        self.assertEqual(self.dset.nbytes, self.data.dtype.itemsize)

    def test_ellipsis(self):
        """ Ellipsis -> scalar ndarray """
        out = self.dset[...]
        # assertArrayEqual doesn't work with compounds; do manually
        self.assertIsInstance(out, np.ndarray)
        self.assertEqual(out.shape, self.data.shape)
        self.assertEqual(out.dtype, self.data.dtype)

    def test_tuple(self):
        """ () -> np.void instance """
        out = self.dset[()]
        self.assertIsInstance(out, np.void)
        self.assertEqual(out.dtype, self.data.dtype)

    def test_slice(self):
        """ slice -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[0:4]

    def test_multi_block_slice(self):
        """ MultiBlockSlice -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[h5py.MultiBlockSlice()]

    def test_index(self):
        """ index -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[0]

    # FIXME: NumPy has IndexError instead
    def test_indexlist(self):
        """ index list -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[[1,2,5]]

    # FIXME: NumPy permits this
    def test_mask(self):
        """ mask -> ValueError  """
        mask = np.array(True, dtype='bool')
        with self.assertRaises(ValueError):
            self.dset[mask]

    # FIXME: NumPy returns a scalar ndarray
    def test_fieldnames(self):
        """ field name -> bare value """
        out = self.dset['a']
        self.assertIsInstance(out, np.float32)
        self.assertEqual(out, self.dset['a'])


class TestScalarArray(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        self.dt = np.dtype('(3,2)f')
        self.data = np.array([(3.2, -119), (42, 99.8), (3.14, 0)], dtype='f')
        self.dset = self.f.create_dataset('x', (), dtype=self.dt)
        self.dset[...] = self.data

    def test_ndim(self):
        """ Verify number of dimensions """
        self.assertEqual(self.data.ndim, 2)
        self.assertEqual(self.dset.ndim, 0)

    def test_size(self):
        """ Verify size """
        self.assertEqual(self.dset.size, 1)

    def test_nbytes(self):
        """ Verify nbytes """
        self.assertEqual(self.dset.nbytes, self.dset.dtype.itemsize)  # not sure if 'f' is always alias for 'f4'

    def test_shape(self):
        """ Verify shape """
        self.assertEqual(self.data.shape, (3, 2))
        self.assertEqual(self.dset.shape, tuple())

    def test_ellipsis(self):
        """ Ellipsis -> ndarray promoted to underlying shape """
        out = self.dset[...]
        self.assertArrayEqual(out, self.data)

    def test_tuple(self):
        """ () -> same as ellipsis """
        out = self.dset[...]
        self.assertArrayEqual(out, self.data)

    def test_slice(self):
        """ slice -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[0:4]

    def test_multi_block_slice(self):
        """ MultiBlockSlice -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[h5py.MultiBlockSlice()]

    def test_index(self):
        """ index -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[0]

    def test_indexlist(self):
        """ index list -> ValueError """
        with self.assertRaises(ValueError):
            self.dset[[]]

    def test_mask(self):
        """ mask -> ValueError """
        mask = np.array(True, dtype='bool')
        with self.assertRaises(ValueError):
            self.dset[mask]

    def test_fieldnames(self):
        """ field name -> ValueError (no fields) """
        with self.assertRaises(ValueError):
            self.dset['field']


class Test1DZeroFloat(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        self.data = np.ones((0,), dtype='f')
        self.dset = self.f.create_dataset('x', data=self.data)

    def test_ndim(self):
        """ Verify number of dimensions """
        self.assertEqual(self.dset.ndim, 1)

    def test_shape(self):
        """ Verify shape """
        self.assertEqual(self.dset.shape, (0,))

    def test_ellipsis(self):
        """ Ellipsis -> ndarray of matching shape """
        self.assertNumpyBehavior(self.dset, self.data, np.s_[...])

    def test_tuple(self):
        """ () -> same as ellipsis """
        self.assertNumpyBehavior(self.dset, self.data, np.s_[()])

    def test_slice(self):
        """ slice -> ndarray of shape (0,) """
        self.assertNumpyBehavior(self.dset, self.data, np.s_[0:4])

    def test_slice_stop_less_than_start(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[7:5])

    def test_index(self):
        """ index -> out of range """
        with self.assertRaises(IndexError):
            self.dset[0]

    def test_indexlist(self):
        """ index list """
        self.assertNumpyBehavior(self.dset, self.data, np.s_[[]])

    def test_mask(self):
        """ mask -> ndarray of matching shape """
        mask = np.ones((0,), dtype='bool')
        self.assertNumpyBehavior(
            self.dset,
            self.data,
            np.s_[mask],
            # Fast reader doesn't work with boolean masks
            skip_fast_reader=True,
        )

    def test_fieldnames(self):
        """ field name -> ValueError (no fields) """
        with self.assertRaises(ValueError):
            self.dset['field']


class Test1DFloat(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        self.data = np.arange(13).astype('f')
        self.dset = self.f.create_dataset('x', data=self.data)

    def test_ndim(self):
        """ Verify number of dimensions """
        self.assertEqual(self.dset.ndim, 1)

    def test_shape(self):
        """ Verify shape """
        self.assertEqual(self.dset.shape, (13,))

    def test_ellipsis(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[...])

    def test_tuple(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[()])

    def test_slice_simple(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[0:4])

    def test_slice_zerosize(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[4:4])

    def test_slice_strides(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[1:7:3])

    def test_slice_negindexes(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[-8:-2:3])

    def test_slice_stop_less_than_start(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[7:5])

    def test_slice_outofrange(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[100:400:3])

    def test_slice_backwards(self):
        """ we disallow negative steps """
        with self.assertRaises(ValueError):
            self.dset[::-1]

    def test_slice_zerostride(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[::0])

    def test_index_simple(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[3])

    def test_index_neg(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[-4])

    # FIXME: NumPy permits this... it adds a new axis in front
    def test_index_none(self):
        with self.assertRaises(TypeError):
            self.dset[None]

    def test_index_illegal(self):
        """ Illegal slicing argument """
        with self.assertRaises(TypeError):
            self.dset[{}]

    def test_index_outofrange(self):
        with self.assertRaises(IndexError):
            self.dset[100]

    def test_indexlist_simple(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[[1,2,5]])

    def test_indexlist_numpyarray(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[np.array([1, 2, 5])])

    def test_indexlist_single_index_ellipsis(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[[0], ...])

    def test_indexlist_numpyarray_single_index_ellipsis(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[np.array([0]), ...])

    def test_indexlist_numpyarray_ellipsis(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[np.array([1, 2, 5]), ...])

    def test_indexlist_empty(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[[]])

    def test_indexlist_outofrange(self):
        with self.assertRaises(IndexError):
            self.dset[[100]]

    def test_indexlist_nonmonotonic(self):
        """ we require index list values to be strictly increasing """
        with self.assertRaises(TypeError):
            self.dset[[1,3,2]]

    def test_indexlist_monotonic_negative(self):
        # This should work: indices are logically increasing
        self.assertNumpyBehavior(self.dset, self.data,  np.s_[[0, 2, -2]])

        with self.assertRaises(TypeError):
            self.dset[[-2, -3]]

    def test_indexlist_repeated(self):
        """ we forbid repeated index values """
        with self.assertRaises(TypeError):
            self.dset[[1,1,2]]

    def test_mask_true(self):
        self.assertNumpyBehavior(
            self.dset,
            self.data,
            np.s_[self.data > -100],
            # Fast reader doesn't work with boolean masks
            skip_fast_reader=True,
        )

    def test_mask_false(self):
        self.assertNumpyBehavior(
            self.dset,
            self.data,
            np.s_[self.data > 100],
            # Fast reader doesn't work with boolean masks
            skip_fast_reader=True,
        )

    def test_mask_partial(self):
        self.assertNumpyBehavior(
            self.dset,
            self.data,
            np.s_[self.data > 5],
            # Fast reader doesn't work with boolean masks
            skip_fast_reader=True,
        )

    def test_mask_wrongsize(self):
        """ we require the boolean mask shape to match exactly """
        with self.assertRaises(TypeError):
            self.dset[np.ones((2,), dtype='bool')]

    def test_fieldnames(self):
        """ field name -> ValueError (no fields) """
        with self.assertRaises(ValueError):
            self.dset['field']


class Test2DZeroFloat(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        self.data = np.ones((0,3), dtype='f')
        self.dset = self.f.create_dataset('x', data=self.data)

    def test_ndim(self):
        """ Verify number of dimensions """
        self.assertEqual(self.dset.ndim, 2)

    def test_shape(self):
        """ Verify shape """
        self.assertEqual(self.dset.shape, (0, 3))

    def test_indexlist(self):
        """ see issue #473 """
        self.assertNumpyBehavior(self.dset, self.data, np.s_[:,[0,1,2]])


class Test2DFloat(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        self.data = np.ones((5,3), dtype='f')
        self.dset = self.f.create_dataset('x', data=self.data)

    def test_ndim(self):
        """ Verify number of dimensions """
        self.assertEqual(self.dset.ndim, 2)

    def test_size(self):
        """ Verify size """
        self.assertEqual(self.dset.size, 15)

    def test_nbytes(self):
        """ Verify nbytes """
        self.assertEqual(self.dset.nbytes, 15*self.data.dtype.itemsize)  # not sure if 'f' is always alias for 'f4'

    def test_shape(self):
        """ Verify shape """
        self.assertEqual(self.dset.shape, (5, 3))

    def test_indexlist(self):
        """ see issue #473 """
        self.assertNumpyBehavior(self.dset, self.data, np.s_[:,[0,1,2]])

    def test_index_emptylist(self):
        self.assertNumpyBehavior(self.dset, self.data, np.s_[:, []])
        self.assertNumpyBehavior(self.dset, self.data, np.s_[[]])


class TestVeryLargeArray(TestCase):

    def setUp(self):
        TestCase.setUp(self)
        self.dset = self.f.create_dataset('x', shape=(2**15, 2**16))

    @ut.skipIf(sys.maxsize < 2**31, 'Maximum integer size >= 2**31 required')
    def test_size(self):
        self.assertEqual(self.dset.size, 2**31)


def test_read_no_fill_value(writable_file):
    # With FILL_TIME_NEVER, HDF5 doesn't write zeros in the output array for
    # unallocated chunks. If we read into uninitialized memory, it can appear
    # to read random values. https://github.com/h5py/h5py/issues/2069
    dcpl = h5py.h5p.create(h5py.h5p.DATASET_CREATE)
    dcpl.set_chunk((1,))
    dcpl.set_fill_time(h5py.h5d.FILL_TIME_NEVER)
    ds = h5py.Dataset(h5py.h5d.create(
        writable_file.id, b'a', h5py.h5t.IEEE_F64LE, h5py.h5s.create_simple((5,)), dcpl
    ))
    np.testing.assert_array_equal(ds[:3], np.zeros(3, np.float64))


class TestBoolIndex(TestCase):
    """
    Tests for indexing with Boolean arrays
    """
    def setUp(self):
        super().setUp()
        self.arr = np.arange(9).reshape(3,-1)
        self.dset = self.f.create_dataset('x', data=self.arr)

    def test_select_first_axis(self):
        sel = np.s_[[False, True, False],:]
        self.assertNumpyBehavior(self.dset, self.arr, sel)

    def test_wrong_size(self):
        sel = np.s_[[False, True, False, False],:]
        with self.assertRaises(TypeError):
            self.dset[sel]
