File size: 2,942 Bytes
2c3c408
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
# quickstart_sparse.py
#
# LICENSE
#
# The MIT License
#
# Copyright (c) 2020 TileDB, Inc.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# DESCRIPTION
#
# Please refer to the TileDB and TileDB-Py documentation for more information:
#   https://docs.tiledb.com/main/how-to
#   https://tiledb-inc-tiledb.readthedocs-hosted.com/projects/tiledb-py/en/stable/python-api.html
#
# When run, this program will create a simple 2D sparse array, write some data
# to it, and read a slice of the data back.
#


import numpy as np

import tiledb

# Name of the array to create.
array_name = "quickstart_sparse"


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=4, dtype=np.int32),
        tiledb.Dim(name="cols", domain=(1, 4), tile=4, 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)


def write_array():
    # Open the array and write to it.
    with tiledb.SparseArray(array_name, mode="w") as A:
        # Write some simple data to cells (1, 1), (2, 4) and (2, 3).
        IJ = [1, 2, 2], [1, 4, 3]
        data = np.array(([1, 2, 3]))
        A[IJ] = data


def read_array():
    # Open the array and read from it.
    with tiledb.SparseArray(array_name, mode="r") as A:
        # Slice only rows 1, 2 and cols 2, 3, 4.
        data = A[1:3, 2:5]
        a_vals = data["a"]
        for i, coord in enumerate(zip(data["rows"], data["cols"])):
            print("Cell (%d, %d) has data %d" % (coord[0], coord[1], a_vals[i]))


if tiledb.object_type(array_name) != "array":
    create_array()
    write_array()

read_array()