def saveSparseMatrix(file: str,
matrix: csr_matrix,
colnames: Union[List[str], None] = None) -> None:
""" Save sparse matrix to json file
Args:
ile: file name to store results, full or relative path
matrix (M,N): sparse matrix of size (M,N)
colnames, optional (1,N): column names
Returns:
None
"""
json_content = dict()
if colnames is not None:
json_content["features"] = colnames
json_content["size"] = matrix.shape
matrix = matrix.astype(float)
keys = matrix.todok().keys()
keys = [tuple(map(int, key)) for key in keys]
vals = matrix.todok().values()
vals = list(map(float, vals))
json_content["positions"] = keys
json_content["counts"] = vals
with open(file, "w") as f:
json.dump(json_content, f, indent=4)
