def numpy2r(mat):
    num_rows = mat.shape[0]
    data = mat.T.flatten()
    data = ["%f"%each for each in data]
    data = "c(" + ",".join(data) + ")"
    return "matrix(%s,%d)"%(data,num_rows)
Enforce only one celery task at a time.
dataset/ETHPy150Open bolme/pyvision/src/pyvision/__init__.py/numpy2r--crossover with--dataset/ETHPy150Open globocom/database-as-a-service/dbaas/util/decorators.py/only_one