How to use the tiledb.Attr function in tiledb

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github TileDB-Inc / TileDB-Py / examples / libtiledb / tiledb_dense_create.py View on Github external
def main():
    ctx = tiledb.Ctx()

    # Create dimensions
    d1 = tiledb.Dim(ctx, "d1", domain=(1, 4), tile=2, dtype="uint64")
    d2 = tiledb.Dim(ctx, "d2", domain=(1, 4), tile=2, dtype="uint64")

    # Create domain
    domain = tiledb.Domain(ctx, d1, d2)

    # Create attributes
    a1 = tiledb.Attr(ctx, "a1", compressor=('blosc-lz', -1), dtype="int32")
    a2 = tiledb.Attr(ctx, "a2", compressor=("gzip", -1), dtype="S4")
    a3 = tiledb.Attr(ctx, "a3", compressor=('zstd', -1), dtype='float32,float32')

    # Create dense array
    tiledb.DenseArray(ctx, "my_dense_array",
                      domain=domain,
                      attrs=(a1, a2, a3),
                      cell_order='row-major',
                      tile_order='row-major')
github TileDB-Inc / TileDB-Py / examples / writing_dense_multiple.py View on Github external
def create_array():
    # The array will be 4x4 with dimensions "rows" and "cols", with domain [1,4].
    dom = tiledb.Domain(tiledb.Dim(name="rows", domain=(1, 4), tile=2, dtype=np.int32),
                        tiledb.Dim(name="cols", domain=(1, 4), tile=2, dtype=np.int32))

    # The array will be dense with a single attribute "a" so each (i,j) cell can store an integer.
    schema = tiledb.ArraySchema(domain=dom, sparse=False,
                                attrs=[tiledb.Attr(name="a", dtype=np.int32)])

    # Create the (empty) array on disk.
    tiledb.DenseArray.create(array_name, schema)
github TileDB-Inc / TileDB-Py / examples / libtiledb / tiledb_dense_create.py View on Github external
def main():
    ctx = tiledb.Ctx()

    # Create dimensions
    d1 = tiledb.Dim(ctx, "d1", domain=(1, 4), tile=2, dtype="uint64")
    d2 = tiledb.Dim(ctx, "d2", domain=(1, 4), tile=2, dtype="uint64")

    # Create domain
    domain = tiledb.Domain(ctx, d1, d2)

    # Create attributes
    a1 = tiledb.Attr(ctx, "a1", compressor=('blosc-lz', -1), dtype="int32")
    a2 = tiledb.Attr(ctx, "a2", compressor=("gzip", -1), dtype="S4")
    a3 = tiledb.Attr(ctx, "a3", compressor=('zstd', -1), dtype='float32,float32')

    # Create dense array
    tiledb.DenseArray(ctx, "my_dense_array",
                      domain=domain,
                      attrs=(a1, a2, a3),
                      cell_order='row-major',
                      tile_order='row-major')
github TileDB-Inc / TileDB-Py / examples / fragments_consolidation.py View on Github external
def create_array():
    # The array will be 4x4 with dimensions "rows" and "cols", with domain [1,4] and space tiles 2x2.
    dom = tiledb.Domain(tiledb.Dim(name="rows", domain=(1, 4), tile=2, dtype=np.int32),
                        tiledb.Dim(name="cols", domain=(1, 4), tile=2, dtype=np.int32))

    # The array will be dense with a single attribute "a" so each (i,j) cell can store an integer.
    schema = tiledb.ArraySchema(domain=dom, sparse=False,
                                attrs=[tiledb.Attr(name="a", dtype=np.int32)])

    # Create the (empty) array on disk.
    tiledb.DenseArray.create(array_name, schema)
github TileDB-Inc / TileDB-Py / examples / libtiledb / tiledb_kv.py View on Github external
def main():
    # Create TileDB context
    ctx = tiledb.Ctx()

    # KV objects are limited to storing string keys/values for the time being
    a1 = tiledb.Attr(ctx, "value", compressor=("gzip", -1), dtype=bytes)
    kv = tiledb.KV(ctx, "my_kv", attrs=(a1,))

    # Dump the KV schema
    kv.dump()

    # Update the KV with some key-value pairs
    vals = {"key1": "a", "key2": "bb", "key3": "dddd"}
    print("Updating KV with values: {!r}\n".format(vals))
    kv.update(vals)

    # Get kv item
    print("KV value for 'key3': {}\n".format(kv['key3']))

    try:
        kv["don't exist"]
    except KeyError:
github TileDB-Inc / TileDB-Py / examples / reading_sparse_layouts.py View on Github external
def create_array():
    # The array will be 4x4 with dimensions "rows" and "cols", with domain [1,4].
    dom = tiledb.Domain(tiledb.Dim(name="rows", domain=(1, 4), tile=2, dtype=np.int32),
                        tiledb.Dim(name="cols", domain=(1, 4), tile=2, dtype=np.int32))

    # The array will be sparse with a single attribute "a" so each (i,j) cell can store an integer.
    schema = tiledb.ArraySchema(domain=dom, sparse=True,
                                attrs=[tiledb.Attr(name="a", dtype=np.int32)])

    # Create the (empty) array on disk.
    tiledb.SparseArray.create(array_name, schema)
github TileDB-Inc / TileDB-Py / examples / quickstart_kv.py View on Github external
def create_array():
    # The KV array will have a single attribute "a" storing a string.
    schema = tiledb.KVSchema(attrs=[tiledb.Attr(name="a", dtype=bytes)])

    # Create the (empty) array on disk.
    tiledb.KV.create(kv_name, schema)
github TileDB-Inc / TileDB-Py / examples / variable_length.py View on Github external
def create_array():
    ctx = tiledb.Ctx()

    dom = tiledb.Domain(tiledb.Dim(name="rows", domain=(1, 4), tile=4, dtype=np.int64),
                        tiledb.Dim(name="cols", domain=(1, 4), tile=4, dtype=np.int64),
                        ctx=ctx)

    attrs = [
        tiledb.Attr(name="a1", var=True, dtype='U', ctx=ctx),
        tiledb.Attr(name="a2", var=True, dtype=np.int64, ctx=ctx)
        ]

    schema = tiledb.ArraySchema(domain=dom, sparse=False,
                                attrs=attrs,
                                ctx=ctx)

    tiledb.Array.create(array_name, schema, ctx=ctx)

    return schema