File size: 3,498 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 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | # reading_sparse_layouts.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 see the TileDB documentation for more information:
# https://docs.tiledb.com/main/how-to/arrays/reading-arrays/basic-reading
#
# When run, this program will create a simple 2D sparse array, write some data
# to it, and read a slice of the data back in the layout of the user's choice
# (passed as an argument to the program: "row", "col", or "global").
#
import sys
import numpy as np
import tiledb
# Name of the array to create.
array_name = "reading_sparse_layouts"
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)
def write_array():
# Open the array and write to it.
with tiledb.SparseArray(array_name, mode="w") as A:
# To write, the coordinates must be split into two vectors, one per dimension
IJ = [1, 1, 2, 1, 2, 2], [1, 2, 2, 4, 3, 4]
data = np.array(([1, 2, 3, 4, 5, 6]))
A[IJ] = data
def read_array(order):
# Open the array and read from it.
with tiledb.SparseArray(array_name, mode="r") as A:
# Get non-empty domain
print("Non-empty domain: {}".format(A.nonempty_domain()))
# Slice only rows 1, 2 and cols 2, 3, 4.
# NOTE: The `query` syntax is required to specify an order
# other than the default row-major
data = A.query(attrs=["a"], order=order, coords=True)[1:3, 2:5]
a_vals = data["a"]
for i, coord in enumerate(zip(data["rows"], data["cols"])):
print("Cell {} has data {}".format(str(coord), str(a_vals[i])))
# Check if the array already exists.
if tiledb.object_type(array_name) != "array":
create_array()
write_array()
layout = ""
if len(sys.argv) > 1:
layout = sys.argv[1]
order = "C"
if layout == "col":
order = "F"
elif layout == "global":
order = "G"
else:
order = "C"
read_array(order)
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