Parcels v2.1.0: a Lagrangian Ocean Analysis tool for the petascale age
Parcels v2.1.0 builds on previous versions v2.0.0. The major changes of v2.1.0 are:
- Parcels has a parallel MPI version! While working on multiple processors, the particles are spread over the processors for an efficient integration. (#625). See https://oceanparcels.org#parallel_install for instructions on how to install.
- For an efficient loading of the
Fieldset, theFieldobjects are now loaded by chunks, controlled by the parameterfield_chunksize(#632). This results in lower memory usage and faster simulation. It is also a fundamental part of the parallel implementation, since for low number of particles per processor, the computation time is dominated by the loading of the data. A more efficient parallel version will be dynamically balancing the particles between the processors such to minimise the number of chunks loaded per processor. See this document for further background on the implementation. - An efficient writing of the particleset. For a quicker export of the data, particles are now dumped into npy files during simulation. The pickles are gathered into one single file at the end of the simulation. (#614)
- A proper management of
particle.dtmodified by the kernel. If the kernel modifiesparticle.dt, the kernel will automatically be restarted with the updateddt. If you want to simply updates thedtfor next kernel call, useparticle.update_next_dt(new_dt). (#657) - New particles can now be added to the
ParticleSetonly via a temporaryParticleSetobject. This enables a proper control of theparticle.idin parallel (#629) Field.gradient()function is not available anymore. This functionality was providing spurious results on curvilinear grids and was conflicting with the use of chunked fields. Users can still obtain easily an accurate field gradient (see example proposed in #633)- Using the
time_periodicflag inFieldSetcreation now requires the length of the period (#659) - Numerous bug fixes
Note that Parcels v2.1.0 is the last version to officially support Python 2.7. While all functionalities currently work with both Python 2 and 3, new development and code dependencies will progressively lead to incompatibility with Python 2. We strongly advice the users to switch to Python 3.