Files
cellxgene/server/converters/to_sparse.py

81 lines
2.8 KiB
Python

"""
Script to create a sparse dataset in CXG format based on an input dataset in CXG format.
The input dataset is not modified.
"""
import argparse
import os
import shutil
import sys
import tiledb
from server.common.utils.cxg_generation_utils import convert_ndarray_to_cxg_dense_array, convert_matrix_to_cxg_array
from server.common.utils.matrix_utils import is_matrix_sparse, get_column_shift_encode_for_matrix
def main():
parser = argparse.ArgumentParser()
parser.add_argument("input", help="input cxg directory")
parser.add_argument("output", help="output cxg directory")
parser.add_argument("--overwrite", action="store_true", help="replace output cxg directory")
parser.add_argument("--verbose", "-v", action="count", default=0, help="verbose output")
parser.add_argument(
"--sparse-threshold",
"-s",
type=float,
default=5.0, # default is 5% non-zero values
help="The X array will be sparse if the percent of non-zeros falls below this value",
)
args = parser.parse_args()
if os.path.exists(args.output):
print("output dir exists:", args.output)
if args.overwrite:
print("output dir removed:", args.output)
shutil.rmtree(args.output)
else:
print("use the overwrite option to remove the output directory")
sys.exit(1)
if not os.path.isdir(args.input):
print("input is not a directory", args.input)
sys.exit(1)
shutil.copytree(args.input, args.output, ignore=shutil.ignore_patterns("X", "X_col_shift"))
ctx = tiledb.Ctx(
{
"sm.num_reader_threads": 32,
"sm.num_writer_threads": 32,
"sm.consolidation.buffer_size": 1 * 1024 * 1024 * 1024,
}
)
with tiledb.DenseArray(os.path.join(args.input, "X"), mode="r", ctx=ctx) as X_in:
x_matrix_data = X_in[:, :]
matrix_container = args.output
is_sparse = is_matrix_sparse(x_matrix_data, args.sparse_threshold)
if not is_sparse:
col_shift = get_column_shift_encode_for_matrix(x_matrix_data, args.sparse_threshold)
is_sparse = col_shift is not None
else:
col_shift = None
if col_shift is not None:
x_col_shift_name = f"{args.output}/X_col_shift"
convert_ndarray_to_cxg_dense_array(x_col_shift_name, col_shift, ctx)
tiledb.consolidate(matrix_container, ctx=ctx)
if is_sparse:
convert_matrix_to_cxg_array(matrix_container, x_matrix_data, is_sparse, ctx, col_shift)
tiledb.consolidate(matrix_container, ctx=ctx)
if not is_sparse:
print("The array is not sparse, cleaning up, abort.")
shutil.rmtree(args.output)
sys.exit(1)
if __name__ == "__main__":
main()