# reading_dense_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 dense 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_dense_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 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) def write_array(): # Open the array and write to it. with tiledb.DenseArray(array_name, mode="w") as A: # NOTE: global writes are not currently supported in the Python API. # The following code will produce the same array as the corresponding # C++ example in the docs (which wrote in global order) data = np.array(([1, 2, 5, 6], [3, 4, 7, 8], [9, 10, 13, 14], [11, 12, 15, 16])) A[:] = data def read_array(order): # Open the array and read from it. with tiledb.DenseArray(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 get the coordinates for # dense arrays and 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"] coords = np.asarray(list(zip(data["rows"], data["cols"]))) if order != "G" and a_vals.flags["F_CONTIGUOUS"]: print("NOTE: The following result array has col-major layout internally") if order != "G": for i in range(coords.shape[0]): for j in range(coords.shape[1]): print( "Cell {} has data {}".format( str(coords[i, j]), str(a_vals[i, j]) ) ) else: # When reading in global order, TileDB always returns a vector (1D array) for i in range(coords.shape[0]): print("Cell {} has data {}".format(str(coords[i]), 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)