import sys
sys.path.append(os.path.join(os.path.dirname(__file__),"../"))
import pylarc
import argparse
from timeit import default_timer as timer
if __name__ == '__main__':
# Returns the count of a specified scalar in a json matrix file
parser = argparse.ArgumentParser(description="Count the number of entries in a LARCmatrix json file with a given scalar value.")
parser.add_argument("matrix_path", help="the path to the json file containing the LARC matrix")
parser.add_argument("-x", "--scalar", default="0", help="the scalar value to count (default 0)")
parser.add_argument("-v", "--verbose", action="store_true", help="set to verbose printing")
larc_starter = pylarc.LarcSettings()
larc_starter.addArgsToParser(parser)
args = parser.parse_args()
larc_starter.parseArgs(args)
# Exit gracefully if matrix is too big (i.e, has either dimension > 1024)
[mat_row_level, mat_col_level] = pylarc.get_levels_from_larcMatrix_file(args.matrix_path)
if (mat_row_level > 10) or (mat_col_level > 10):
print("Sorry, matrix is too big to process. Levels = [{0}, {1}]".format(mat_row_level, mat_col_level))
sys.exit(1)
larc_starter.getLevelFromFiles(args.matrix_path)
larc_starter.initLarc()
# if args.verbose:
# larc_starter.getLevelFromFiles(args.matrix_path)
parser.add_argument(
"matrix_path",
help="the path to write the json file containing the LARC matrix")
parser.add_argument("num_ones", help="the number of 1's in the matrix")
parser.add_argument("-r",
"--row_level",
type=int,
default=4,
help="row level for the matrix (default 4)")
parser.add_argument("-c",
"--col_level",
type=int,
default=4,
help="column level for the matrix (default 4)")
larc_initer = pylarc.LarcSettings()
larc_initer.addArgsToParser(parser)
args = parser.parse_args()
larc_initer.parseArgs(args)
larc_initer.max_mat_level = max(args.row_level, args.col_level)
# initialize larc
# with pylarc.stdout_redirected():
larc_initer.initLarc()
# generate matrix
matID = pylarc.random_bool_matrixID_from_count(args.row_level,
args.col_level,
args.num_ones)