testbed/TileDB-Inc__TileDB-Py/tiledb/tests/test_domain_index.py

# %%

import numpy as np

import tiledb

from .common import DiskTestCase, assert_array_equal, assert_equal


class DomainIndexingSparseTest(DiskTestCase):
    def test_int_domain_indexing(self):
        path = self.path("int_domain_indexing")

        dom = tiledb.Domain(
            tiledb.Dim(name="x", domain=(-10, 10), tile=1, dtype=np.int64)
        )
        schema = tiledb.ArraySchema(
            domain=dom, sparse=True, attrs=[tiledb.Attr(name="a", dtype=np.float64)]
        )

        tiledb.SparseArray.create(path, schema)

        X = np.arange(-10, 11, step=1)
        val = np.random.rand(len(X))

        with tiledb.SparseArray(path, mode="w") as A:
            A[X] = val

        with tiledb.SparseArray(path) as A:
            assert_array_equal(A.domain_index[X[0]]["a"], val[0])
            assert_array_equal(A.domain_index[X[-1]]["a"], val[-1])
            assert_array_equal(A.domain_index[X[0] : X[-1]]["a"], val[:])
            # sanity check
            assert_array_equal(A.domain_index[X[0] : X[-1]]["x"], X[:])

    def test_fp_domain_indexing(self):
        array_path = self.path("test_domain_idx")

        # test case from https://github.com/TileDB-Inc/TileDB-Py/issues/201
        tile = 1
        dom = tiledb.Domain(
            tiledb.Dim(name="x", domain=(-89.75, 89.75), tile=tile, dtype=np.float64),
            tiledb.Dim(name="y", domain=(-179.75, 179.75), tile=tile, dtype=np.float64),
            tiledb.Dim(name="z", domain=(157498, 157863), tile=tile, dtype=np.float64),
        )
        schema = tiledb.ArraySchema(
            domain=dom, sparse=True, attrs=[tiledb.Attr(name="data", dtype=np.float64)]
        )

        tiledb.SparseArray.create(array_path, schema)

        # fake data
        X = np.linspace(-89.75, 89.75, 359)
        Y = np.linspace(-179.75, 179.75, 359)
        Z = np.linspace(157498, 157857, 359)

        # data = np.random.rand(*map(lambda x: x[0], (X.shape, Y.shape, Z.shape)))
        data = np.random.rand(X.shape[0])

        with tiledb.SparseArray(array_path, mode="w") as A:
            A[X, Y, Z] = data

        with tiledb.SparseArray(array_path) as A:
            # check direct slicing
            assert_array_equal(A.domain_index[X[0], Y[0], Z[0]]["data"], data[0])

            # check small slice ranges
            tmp = A.domain_index[
                X[0] : np.nextafter(X[0], 0),
                Y[0] : np.nextafter(Y[0], 0),
                Z[0] : np.nextafter(Z[0], Z[0] + 1),
            ]
            assert_array_equal(tmp["data"], data[0])

            # check slicing last element
            tmp = A.domain_index[X[-1], Y[-1], Z[-1]]
            assert_array_equal(tmp["data"], data[-1])

            # check slice range multiple components
            tmp = A.domain_index[X[1] : X[2], Y[1] : Y[2], Z[1] : Z[2]]
            assert_array_equal(tmp["data"], data[1:3])

            # check an interior point
            coords = X[145], Y[145], Z[145]
            tmp = A.domain_index[coords]
            assert_array_equal(tmp["x"], X[145])
            assert_array_equal(tmp["data"], data[145])

            # check entire domain
            tmp = A.domain_index[X[0] : X[-1], Y[0] : Y[-1], Z[0] : Z[-1]]
            assert_array_equal(tmp["data"], data[:])

            # check entire domain
            # TODO uncomment if vectorized indexing is available
            # coords = np.array([X,Y,Z]).transpose().flatten()
            # tmp = A.domain_index[X,Y,Z]
            # assert_array_equal(
            #    tmp['data'],
            #    data[:]
            # )

    def test_fp_domain_count(self):
        array_path = self.path("test_domain_count")
        tile = 1

        dom = tiledb.Domain(
            tiledb.Dim(name="x", domain=(0.0, 2.0), tile=tile, dtype=np.float64),
            tiledb.Dim(name="y", domain=(0.0, 2.0), tile=tile, dtype=np.float64),
        )
        schema = tiledb.ArraySchema(
            domain=dom, sparse=True, attrs=[tiledb.Attr(name="data", dtype=np.float64)]
        )

        tiledb.SparseArray.create(array_path, schema)

        # fake data
        X = [1.0]
        Y = [1.0]
        data = [1.0]

        with tiledb.SparseArray(array_path, mode="w") as A:
            A[X, Y] = data

        with tiledb.SparseArray(array_path) as A:
            # check direct slicing
            assert_array_equal(A.domain_index[X[0], Y[0]]["data"], data[0])

            # check counting by slice
            assert_equal(A.domain_index[0:2.0, 0:1.0]["x"].shape[0], 1)
            assert_equal(A.domain_index[0:2.0, 0:1.0]["y"].shape[0], 1)
            assert_equal(A.domain_index[0:2.0, np.nextafter(1.0, 2.0)]["x"].shape[0], 0)
            assert_equal(A.domain_index[0:2.0, np.nextafter(1.0, 2.0)]["y"].shape[0], 0)


class DomainIndexingDenseTest(DiskTestCase):
    def test_int_domain_indexing(self):
        path = self.path("dense_int_domain_indexing")

        dom = tiledb.Domain(
            tiledb.Dim(name="x", domain=(0, 10), tile=1, dtype=np.int64)
        )
        schema = tiledb.ArraySchema(
            domain=dom, sparse=False, attrs=[tiledb.Attr(name="a", dtype=np.float64)]
        )

        tiledb.DenseArray.create(path, schema)

        X = np.arange(0, 11, step=1)
        val = np.random.rand(len(X))

        with tiledb.DenseArray(path, mode="w") as A:
            A[:] = val

        with tiledb.DenseArray(path) as A:
            assert_array_equal(A.domain_index[X[0]]["a"], val[0])
            assert_array_equal(A.domain_index[X[-1]]["a"], val[-1])
            assert_array_equal(A.domain_index[X[0] : X[-1]]["a"], val[:])
            # sanity check
            assert_array_equal(A.domain_index[X[0] : X[-1]]["x"], X[:])