Parcels documentation¶
Welcome to the documentation of parcels. This page provides detailed documentation for each method, class and function. The documentation corresponds to the latest conda release, for newer documentation see the docstrings in the code.
See http://www.oceanparcels.org for general information on the Parcels project, including how to install and use.
parcels.particleset module¶
parcels.fieldset module¶
- class parcels.fieldset.FieldSet(U, V, fields=None)[source]¶
Bases:
object
FieldSet class that holds hydrodynamic data needed to execute particles
- Parameters
U –
parcels.field.Field
object for zonal velocity componentV –
parcels.field.Field
object for meridional velocity componentfields – Dictionary of additional
parcels.field.Field
objects
- add_constant(name, value)[source]¶
Add a constant to the FieldSet. Note that all constants are stored as 32-bit floats. While constants can be updated during execution in SciPy mode, they can not be updated in JIT mode.
Tutorials using fieldset.add_constant: Analytical advection Diffusion Periodic boundaries
- Parameters
name – Name of the constant
value – Value of the constant (stored as 32-bit float)
- add_constant_field(name, value, mesh='flat')[source]¶
- Wrapper function to add a Field that is constant in space,
useful e.g. when using constant horizontal diffusivity
- Parameters
name – Name of the
parcels.field.Field
object to be addedvalue – Value of the constant field (stored as 32-bit float)
units – Optional UnitConverter object, to convert units (e.g. for Horizontal diffusivity from m2/s to degree2/s)
- add_field(field, name=None)[source]¶
Add a
parcels.field.Field
object to the FieldSet- Parameters
field –
parcels.field.Field
object to be addedname – Name of the
parcels.field.Field
object to be added
For usage examples see the following tutorials:
- add_periodic_halo(zonal=False, meridional=False, halosize=5)[source]¶
Add a ‘halo’ to all
parcels.field.Field
objects in a FieldSet, through extending the Field (and lon/lat) by copying a small portion of the field on one side of the domain to the other.- Parameters
zonal – Create a halo in zonal direction (boolean)
meridional – Create a halo in meridional direction (boolean)
halosize – size of the halo (in grid points). Default is 5 grid points
- add_vector_field(vfield)[source]¶
Add a
parcels.field.VectorField
object to the FieldSet- Parameters
vfield –
parcels.field.VectorField
object to be added
- advancetime(fieldset_new)[source]¶
Replace oldest time on FieldSet with new FieldSet
- Parameters
fieldset_new – FieldSet snapshot with which the oldest time has to be replaced
- computeTimeChunk(time, dt)[source]¶
Load a chunk of three data time steps into the FieldSet. This is used when FieldSet uses data imported from netcdf, with default option deferred_load. The loaded time steps are at or immediatly before time and the two time steps immediately following time if dt is positive (and inversely for negative dt)
- Parameters
time – Time around which the FieldSet chunks are to be loaded. Time is provided as a double, relatively to Fieldset.time_origin
dt – time step of the integration scheme
- classmethod from_b_grid_dataset(filenames, variables, dimensions, indices=None, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, tracer_interp_method='bgrid_tracer', chunksize=None, **kwargs)[source]¶
Initialises FieldSet object from NetCDF files of Bgrid fields.
- Parameters
filenames – Dictionary mapping variables to file(s). The filepath may contain wildcards to indicate multiple files, or be a list of file. filenames can be a list [files], a dictionary {var:[files]}, a dictionary {dim:[files]} (if lon, lat, depth and/or data not stored in same files as data), or a dictionary of dictionaries {var:{dim:[files]}} time values are in filenames[data]
variables – Dictionary mapping variables to variable names in the netCDF file(s).
dimensions –
Dictionary mapping data dimensions (lon, lat, depth, time, data) to dimensions in the netCF file(s). Note that dimensions can also be a dictionary of dictionaries if dimension names are different for each variable. U and V velocity nodes are not located as W velocity and T tracer nodes (see http://www.cesm.ucar.edu/models/cesm1.0/pop2/doc/sci/POPRefManual.pdf ).
U[k,j+1,i],V[k,j+1,i]
U[k,j+1,i+1],V[k,j+1,i+1]
W[k:k+2,j+1,i+1],T[k,j+1,i+1]
U[k,j,i],V[k,j,i]
U[k,j,i+1],V[k,j,i+1]
- In 2D: U and V nodes are on the cell vertices and interpolated bilinearly as a A-grid.
T node is at the cell centre and interpolated constant per cell as a C-grid.
- In 3D: U and V nodes are at the midlle of the cell vertical edges,
They are interpolated bilinearly (independently of z) in the cell. W nodes are at the centre of the horizontal interfaces. They are interpolated linearly (as a function of z) in the cell. T node is at the cell centre, and constant per cell.
indices – Optional dictionary of indices for each dimension to read from file(s), to allow for reading of subset of data. Default is to read the full extent of each dimension. Note that negative indices are not allowed.
fieldtype – Optional dictionary mapping fields to fieldtypes to be used for UnitConverter. (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
tracer_interp_method – Method for interpolation of tracer fields. It is recommended to use ‘bgrid_tracer’ (default) Note that in the case of from_pop() and from_bgrid(), the velocity fields are default to ‘bgrid_velocity’
chunksize – size of the chunks in dask loading
- classmethod from_c_grid_dataset(filenames, variables, dimensions, indices=None, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, tracer_interp_method='cgrid_tracer', gridindexingtype='nemo', chunksize=None, **kwargs)[source]¶
Initialises FieldSet object from NetCDF files of Curvilinear NEMO fields.
See here for a more detailed explanation of the different methods that can be used for c-grid datasets.
- Parameters
filenames – Dictionary mapping variables to file(s). The filepath may contain wildcards to indicate multiple files, or be a list of file. filenames can be a list [files], a dictionary {var:[files]}, a dictionary {dim:[files]} (if lon, lat, depth and/or data not stored in same files as data), or a dictionary of dictionaries {var:{dim:[files]}} time values are in filenames[data]
variables – Dictionary mapping variables to variable names in the netCDF file(s).
dimensions –
Dictionary mapping data dimensions (lon, lat, depth, time, data) to dimensions in the netCF file(s). Note that dimensions can also be a dictionary of dictionaries if dimension names are different for each variable. Watch out: NEMO is discretised on a C-grid: U and V velocities are not located on the same nodes (see https://www.nemo-ocean.eu/doc/node19.html ).
V[k,j+1,i+1]
U[k,j+1,i]
W[k:k+2,j+1,i+1],T[k,j+1,i+1]
U[k,j+1,i+1]
V[k,j,i+1]
To interpolate U, V velocities on the C-grid, Parcels needs to read the f-nodes, which are located on the corners of the cells. (for indexing details: https://www.nemo-ocean.eu/doc/img360.png ) In 3D, the depth is the one corresponding to W nodes.
indices – Optional dictionary of indices for each dimension to read from file(s), to allow for reading of subset of data. Default is to read the full extent of each dimension. Note that negative indices are not allowed.
fieldtype – Optional dictionary mapping fields to fieldtypes to be used for UnitConverter. (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
tracer_interp_method – Method for interpolation of tracer fields. It is recommended to use ‘cgrid_tracer’ (default) Note that in the case of from_nemo() and from_cgrid(), the velocity fields are default to ‘cgrid_velocity’
gridindexingtype – The type of gridindexing. Set to ‘nemo’ in FieldSet.from_nemo() See also the Grid indexing documentation on oceanparcels.org
chunksize – size of the chunks in dask loading
- classmethod from_data(data, dimensions, transpose=False, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, **kwargs)[source]¶
Initialise FieldSet object from raw data
- Parameters
data –
Dictionary mapping field names to numpy arrays. Note that at least a ‘U’ and ‘V’ numpy array need to be given, and that the built-in Advection kernels assume that U and V are in m/s
If data shape is [xdim, ydim], [xdim, ydim, zdim], [xdim, ydim, tdim] or [xdim, ydim, zdim, tdim], whichever is relevant for the dataset, use the flag transpose=True
If data shape is [ydim, xdim], [zdim, ydim, xdim], [tdim, ydim, xdim] or [tdim, zdim, ydim, xdim], use the flag transpose=False (default value)
If data has any other shape, you first need to reorder it
dimensions – Dictionary mapping field dimensions (lon, lat, depth, time) to numpy arrays. Note that dimensions can also be a dictionary of dictionaries if dimension names are different for each variable (e.g. dimensions[‘U’], dimensions[‘V’], etc).
transpose – Boolean whether to transpose data on read-in
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation, see also this tutorial:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
- classmethod from_mitgcm(filenames, variables, dimensions, indices=None, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, tracer_interp_method='cgrid_tracer', chunksize=None, **kwargs)[source]¶
Initialises FieldSet object from NetCDF files of MITgcm fields. All parameters and keywords are exactly the same as for FieldSet.from_nemo(), except that gridindexing is set to ‘mitgcm’ for grids that have the shape
_________________V[k,j+1,i]__________________
U[k,j,i] W[k-1:k,j,i], T[k,j,i] U[k,j,i+1] | | | | |_________________V[k,j,i]____________________|
For indexing details: https://mitgcm.readthedocs.io/en/latest/algorithm/algorithm.html#spatial-discretization-of-the-dynamical-equations Note that vertical velocity (W) is assumed postive in the positive z direction (which is upward in MITgcm)
- classmethod from_mom5(filenames, variables, dimensions, indices=None, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, tracer_interp_method='bgrid_tracer', chunksize=None, **kwargs)[source]¶
Initialises FieldSet object from NetCDF files of MOM5 fields.
- Parameters
filenames – Dictionary mapping variables to file(s). The filepath may contain wildcards to indicate multiple files, or be a list of file. filenames can be a list [files], a dictionary {var:[files]}, a dictionary {dim:[files]} (if lon, lat, depth and/or data not stored in same files as data), or a dictionary of dictionaries {var:{dim:[files]}} time values are in filenames[data]
variables – Dictionary mapping variables to variable names in the netCDF file(s). Note that the built-in Advection kernels assume that U and V are in m/s
dimensions –
Dictionary mapping data dimensions (lon, lat, depth, time, data) to dimensions in the netCF file(s). Note that dimensions can also be a dictionary of dictionaries if dimension names are different for each variable. U[k,j+1,i],V[k,j+1,i] ____________________U[k,j+1,i+1],V[k,j+1,i+1] | | | W[k-1:k+1,j+1,i+1],T[k,j+1,i+1] | | | U[k,j,i],V[k,j,i] ________________________U[k,j,i+1],V[k,j,i+1] In 2D: U and V nodes are on the cell vertices and interpolated bilinearly as a A-grid.
T node is at the cell centre and interpolated constant per cell as a C-grid.
- In 3D: U and V nodes are at the midlle of the cell vertical edges,
They are interpolated bilinearly (independently of z) in the cell. W nodes are at the centre of the horizontal interfaces, but below the U and V. They are interpolated linearly (as a function of z) in the cell. Note that W is normally directed upward in MOM5, but Parcels requires W in the positive z-direction (downward) so W is multiplied by -1. T node is at the cell centre, and constant per cell.
indices – Optional dictionary of indices for each dimension to read from file(s), to allow for reading of subset of data. Default is to read the full extent of each dimension. Note that negative indices are not allowed.
fieldtype – Optional dictionary mapping fields to fieldtypes to be used for UnitConverter. (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation, see also https://nbviewer.jupyter.org/github/OceanParcels/parcels/blob/master/parcels/examples/tutorial_unitconverters.ipynb:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
tracer_interp_method – Method for interpolation of tracer fields. It is recommended to use ‘bgrid_tracer’ (default) Note that in the case of from_mom5() and from_bgrid(), the velocity fields are default to ‘bgrid_velocity’
chunksize – size of the chunks in dask loading
- classmethod from_nemo(filenames, variables, dimensions, indices=None, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, tracer_interp_method='cgrid_tracer', chunksize=None, **kwargs)[source]¶
Initialises FieldSet object from NetCDF files of Curvilinear NEMO fields.
See here for a detailed tutorial on the setup for 2D NEMO fields and here for the tutorial on the setup for 3D NEMO fields.
See here for a more detailed explanation of the different methods that can be used for c-grid datasets.
- Parameters
filenames – Dictionary mapping variables to file(s). The filepath may contain wildcards to indicate multiple files, or be a list of file. filenames can be a list [files], a dictionary {var:[files]}, a dictionary {dim:[files]} (if lon, lat, depth and/or data not stored in same files as data), or a dictionary of dictionaries {var:{dim:[files]}} time values are in filenames[data]
variables – Dictionary mapping variables to variable names in the netCDF file(s). Note that the built-in Advection kernels assume that U and V are in m/s
dimensions –
Dictionary mapping data dimensions (lon, lat, depth, time, data) to dimensions in the netCF file(s). Note that dimensions can also be a dictionary of dictionaries if dimension names are different for each variable. Watch out: NEMO is discretised on a C-grid: U and V velocities are not located on the same nodes (see https://www.nemo-ocean.eu/doc/node19.html ).
V[k,j+1,i+1]
U[k,j+1,i]
W[k:k+2,j+1,i+1],T[k,j+1,i+1]
U[k,j+1,i+1]
V[k,j,i+1]
To interpolate U, V velocities on the C-grid, Parcels needs to read the f-nodes, which are located on the corners of the cells. (for indexing details: https://www.nemo-ocean.eu/doc/img360.png ) In 3D, the depth is the one corresponding to W nodes The gridindexingtype is set to ‘nemo’. See also the Grid indexing documentation on oceanparcels.org
indices – Optional dictionary of indices for each dimension to read from file(s), to allow for reading of subset of data. Default is to read the full extent of each dimension. Note that negative indices are not allowed.
fieldtype – Optional dictionary mapping fields to fieldtypes to be used for UnitConverter. (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation, see also this tutorial:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
tracer_interp_method – Method for interpolation of tracer fields. It is recommended to use ‘cgrid_tracer’ (default) Note that in the case of from_nemo() and from_cgrid(), the velocity fields are default to ‘cgrid_velocity’
chunksize – size of the chunks in dask loading. Default is None (no chunking)
- classmethod from_netcdf(filenames, variables, dimensions, indices=None, fieldtype=None, mesh='spherical', timestamps=None, allow_time_extrapolation=None, time_periodic=False, deferred_load=True, chunksize=None, **kwargs)[source]¶
Initialises FieldSet object from NetCDF files
- Parameters
filenames – Dictionary mapping variables to file(s). The filepath may contain wildcards to indicate multiple files or be a list of file. filenames can be a list [files], a dictionary {var:[files]}, a dictionary {dim:[files]} (if lon, lat, depth and/or data not stored in same files as data), or a dictionary of dictionaries {var:{dim:[files]}}. time values are in filenames[data]
variables – Dictionary mapping variables to variable names in the netCDF file(s). Note that the built-in Advection kernels assume that U and V are in m/s
dimensions – Dictionary mapping data dimensions (lon, lat, depth, time, data) to dimensions in the netCF file(s). Note that dimensions can also be a dictionary of dictionaries if dimension names are different for each variable (e.g. dimensions[‘U’], dimensions[‘V’], etc).
indices – Optional dictionary of indices for each dimension to read from file(s), to allow for reading of subset of data. Default is to read the full extent of each dimension. Note that negative indices are not allowed.
fieldtype – Optional dictionary mapping fields to fieldtypes to be used for UnitConverter. (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation, see also this tuturial:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
timestamps – list of lists or array of arrays containing the timestamps for each of the files in filenames. Outer list/array corresponds to files, inner array corresponds to indices within files. Default is None if dimensions includes time.
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
deferred_load – boolean whether to only pre-load data (in deferred mode) or fully load them (default: True). It is advised to deferred load the data, since in that case Parcels deals with a better memory management during particle set execution. deferred_load=False is however sometimes necessary for plotting the fields.
interp_method – Method for interpolation. Options are ‘linear’ (default), ‘nearest’, ‘linear_invdist_land_tracer’, ‘cgrid_velocity’, ‘cgrid_tracer’ and ‘bgrid_velocity’
gridindexingtype – The type of gridindexing. Either ‘nemo’ (default) or ‘mitgcm’ are supported. See also the Grid indexing documentation on oceanparcels.org
chunksize – size of the chunks in dask loading. Default is None (no chunking). Can be None or False (no chunking), ‘auto’ (chunking is done in the background, but results in one grid per field individually), or a dict in the format ‘{parcels_varname: {netcdf_dimname : (parcels_dimname, chunksize_as_int)}, …}’, where ‘parcels_dimname’ is one of (‘time’, ‘depth’, ‘lat’, ‘lon’)
netcdf_engine – engine to use for netcdf reading in xarray. Default is ‘netcdf’, but in cases where this doesn’t work, setting netcdf_engine=’scipy’ could help
For usage examples see the following tutorials:
- classmethod from_parcels(basename, uvar='vozocrtx', vvar='vomecrty', indices=None, extra_fields=None, allow_time_extrapolation=None, time_periodic=False, deferred_load=True, chunksize=None, **kwargs)[source]¶
Initialises FieldSet data from NetCDF files using the Parcels FieldSet.write() conventions.
- Parameters
basename – Base name of the file(s); may contain wildcards to indicate multiple files.
indices – Optional dictionary of indices for each dimension to read from file(s), to allow for reading of subset of data. Default is to read the full extent of each dimension. Note that negative indices are not allowed.
fieldtype – Optional dictionary mapping fields to fieldtypes to be used for UnitConverter. (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
extra_fields – Extra fields to read beyond U and V
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
deferred_load – boolean whether to only pre-load data (in deferred mode) or fully load them (default: True). It is advised to deferred load the data, since in that case Parcels deals with a better memory management during particle set execution. deferred_load=False is however sometimes necessary for plotting the fields.
chunksize – size of the chunks in dask loading
- classmethod from_pop(filenames, variables, dimensions, indices=None, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, tracer_interp_method='bgrid_tracer', chunksize=None, depth_units='m', **kwargs)[source]¶
- Initialises FieldSet object from NetCDF files of POP fields.
It is assumed that the velocities in the POP fields is in cm/s.
- Parameters
filenames – Dictionary mapping variables to file(s). The filepath may contain wildcards to indicate multiple files, or be a list of file. filenames can be a list [files], a dictionary {var:[files]}, a dictionary {dim:[files]} (if lon, lat, depth and/or data not stored in same files as data), or a dictionary of dictionaries {var:{dim:[files]}} time values are in filenames[data]
variables – Dictionary mapping variables to variable names in the netCDF file(s). Note that the built-in Advection kernels assume that U and V are in m/s
dimensions –
Dictionary mapping data dimensions (lon, lat, depth, time, data) to dimensions in the netCF file(s). Note that dimensions can also be a dictionary of dictionaries if dimension names are different for each variable. Watch out: POP is discretised on a B-grid: U and V velocity nodes are not located as W velocity and T tracer nodes (see http://www.cesm.ucar.edu/models/cesm1.0/pop2/doc/sci/POPRefManual.pdf ).
U[k,j+1,i],V[k,j+1,i]
U[k,j+1,i+1],V[k,j+1,i+1]
W[k:k+2,j+1,i+1],T[k,j+1,i+1]
U[k,j,i],V[k,j,i]
U[k,j,i+1],V[k,j,i+1]
- In 2D: U and V nodes are on the cell vertices and interpolated bilinearly as a A-grid.
T node is at the cell centre and interpolated constant per cell as a C-grid.
- In 3D: U and V nodes are at the middle of the cell vertical edges,
They are interpolated bilinearly (independently of z) in the cell. W nodes are at the centre of the horizontal interfaces. They are interpolated linearly (as a function of z) in the cell. T node is at the cell centre, and constant per cell. Note that Parcels assumes that the length of the depth dimension (at the W-points) is one larger than the size of the velocity and tracer fields in the depth dimension.
indices – Optional dictionary of indices for each dimension to read from file(s), to allow for reading of subset of data. Default is to read the full extent of each dimension. Note that negative indices are not allowed.
fieldtype – Optional dictionary mapping fields to fieldtypes to be used for UnitConverter. (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation, see also this tutorial:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
tracer_interp_method – Method for interpolation of tracer fields. It is recommended to use ‘bgrid_tracer’ (default) Note that in the case of from_pop() and from_bgrid(), the velocity fields are default to ‘bgrid_velocity’
chunksize – size of the chunks in dask loading
depth_units – The units of the vertical dimension. Default in Parcels is ‘m’, but many POP outputs are in ‘cm’
- classmethod from_xarray_dataset(ds, variables, dimensions, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, **kwargs)[source]¶
Initialises FieldSet data from xarray Datasets.
- Parameters
ds – xarray Dataset. Note that the built-in Advection kernels assume that U and V are in m/s
variables – Dictionary mapping parcels variable names to data variables in the xarray Dataset.
dimensions – Dictionary mapping data dimensions (lon, lat, depth, time, data) to dimensions in the xarray Dataset. Note that dimensions can also be a dictionary of dictionaries if dimension names are different for each variable (e.g. dimensions[‘U’], dimensions[‘V’], etc).
fieldtype – Optional dictionary mapping fields to fieldtypes to be used for UnitConverter. (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation, see also this tutorial:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
allow_time_extrapolation – boolean whether to allow for extrapolation (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). (Default: False) This flag overrides the allow_time_interpolation and sets it to False
- get_fields()[source]¶
Returns a list of all the
parcels.field.Field
andparcels.field.VectorField
objects associated with this FieldSet
parcels.field module¶
- class parcels.field.Field(name, data, lon=None, lat=None, depth=None, time=None, grid=None, mesh='flat', timestamps=None, fieldtype=None, transpose=False, vmin=None, vmax=None, time_origin=None, interp_method='linear', allow_time_extrapolation=None, time_periodic=False, gridindexingtype='nemo', **kwargs)[source]¶
Bases:
object
Class that encapsulates access to field data.
- Parameters
name – Name of the field
data –
2D, 3D or 4D numpy array of field data.
If data shape is [xdim, ydim], [xdim, ydim, zdim], [xdim, ydim, tdim] or [xdim, ydim, zdim, tdim], whichever is relevant for the dataset, use the flag transpose=True
If data shape is [ydim, xdim], [zdim, ydim, xdim], [tdim, ydim, xdim] or [tdim, zdim, ydim, xdim], use the flag transpose=False
If data has any other shape, you first need to reorder it
lon – Longitude coordinates (numpy vector or array) of the field (only if grid is None)
lat – Latitude coordinates (numpy vector or array) of the field (only if grid is None)
depth – Depth coordinates (numpy vector or array) of the field (only if grid is None)
time – Time coordinates (numpy vector) of the field (only if grid is None)
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation: (only if grid is None)
spherical: Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat (default): No conversion, lat/lon are assumed to be in m.
timestamps – A numpy array containing the timestamps for each of the files in filenames, for loading from netCDF files only. Default is None if the netCDF dimensions dictionary includes time.
grid –
parcels.grid.Grid
object containing all the lon, lat depth, time mesh and time_origin information. Can be constructed from any of the Grid objectsfieldtype – Type of Field to be used for UnitConverter when using SummedFields (either ‘U’, ‘V’, ‘Kh_zonal’, ‘Kh_meridional’ or None)
transpose – Transpose data to required (lon, lat) layout
vmin – Minimum allowed value on the field. Data below this value are set to zero
vmax – Maximum allowed value on the field. Data above this value are set to zero
time_origin – Time origin (TimeConverter object) of the time axis (only if grid is None)
interp_method – Method for interpolation. Options are ‘linear’ (default), ‘nearest’, ‘linear_invdist_land_tracer’, ‘cgrid_velocity’, ‘cgrid_tracer’ and ‘bgrid_velocity’
allow_time_extrapolation – boolean whether to allow for extrapolation in time (i.e. beyond the last available time snapshot)
time_periodic – To loop periodically over the time component of the Field. It is set to either False or the length of the period (either float in seconds or datetime.timedelta object). The last value of the time series can be provided (which is the same as the initial one) or not (Default: False) This flag overrides the allow_time_interpolation and sets it to False
(opt.) (chunkdims_name_map) – gives a name map to the FieldFileBuffer that declared a mapping between chunksize name, NetCDF dimension and Parcels dimension; required only if currently incompatible OCM field is loaded and chunking is used by ‘chunksize’ (which is the default)
For usage examples see the following tutorials:
- add_periodic_halo(zonal, meridional, halosize=5, data=None)[source]¶
Add a ‘halo’ to all Fields in a FieldSet, through extending the Field (and lon/lat) by copying a small portion of the field on one side of the domain to the other. Before adding a periodic halo to the Field, it has to be added to the Grid on which the Field depends
See this tutorial for a detailed explanation on how to set up periodic boundaries
- Parameters
zonal – Create a halo in zonal direction (boolean)
meridional – Create a halo in meridional direction (boolean)
halosize – size of the halo (in grid points). Default is 5 grid points
data – if data is not None, the periodic halo will be achieved on data instead of self.data and data will be returned
- calc_cell_edge_sizes()[source]¶
Method to calculate cell sizes based on numpy.gradient method Currently only works for Rectilinear Grids
- cell_areas()[source]¶
Method to calculate cell sizes based on cell_edge_sizes Currently only works for Rectilinear Grids
- property ctypes_struct¶
Returns a ctypes struct object containing all relevant pointers and sizes for this field.
- eval(time, z, y, x, particle=None, applyConversion=True)[source]¶
Interpolate field values in space and time.
We interpolate linearly in time and apply implicit unit conversion to the result. Note that we defer to scipy.interpolate to perform spatial interpolation.
- classmethod from_netcdf(filenames, variable, dimensions, indices=None, grid=None, mesh='spherical', timestamps=None, allow_time_extrapolation=None, time_periodic=False, deferred_load=True, **kwargs)[source]¶
Create field from netCDF file
- Parameters
filenames – list of filenames to read for the field. filenames can be a list [files] or a dictionary {dim:[files]} (if lon, lat, depth and/or data not stored in same files as data) In the latetr case, time values are in filenames[data]
variable – Tuple mapping field name to variable name in the NetCDF file.
dimensions – Dictionary mapping variable names for the relevant dimensions in the NetCDF file
indices – dictionary mapping indices for each dimension to read from file. This can be used for reading in only a subregion of the NetCDF file. Note that negative indices are not allowed.
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
timestamps – A numpy array of datetime64 objects containing the timestamps for each of the files in filenames. Default is None if dimensions includes time.
allow_time_extrapolation – boolean whether to allow for extrapolation in time (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – boolean whether to loop periodically over the time component of the FieldSet This flag overrides the allow_time_interpolation and sets it to False
deferred_load – boolean whether to only pre-load data (in deferred mode) or fully load them (default: True). It is advised to deferred load the data, since in that case Parcels deals with a better memory management during particle set execution. deferred_load=False is however sometimes necessary for plotting the fields.
gridindexingtype – The type of gridindexing. Either ‘nemo’ (default) or ‘mitgcm’ are supported. See also the Grid indexing documentation on oceanparcels.org
chunksize – size of the chunks in dask loading
For usage examples see the following tutorial:
- classmethod from_xarray(da, name, dimensions, mesh='spherical', allow_time_extrapolation=None, time_periodic=False, **kwargs)[source]¶
Create field from xarray Variable
- Parameters
da – Xarray DataArray
name – Name of the Field
dimensions – Dictionary mapping variable names for the relevant dimensions in the DataArray
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
allow_time_extrapolation – boolean whether to allow for extrapolation in time (i.e. beyond the last available time snapshot) Default is False if dimensions includes time, else True
time_periodic – boolean whether to loop periodically over the time component of the FieldSet This flag overrides the allow_time_interpolation and sets it to False
- set_depth_from_field(field)[source]¶
Define the depth dimensions from another (time-varying) field
See this tutorial for a detailed explanation on how to set up time-evolving depth dimensions
- set_scaling_factor(factor)[source]¶
Scales the field data by some constant factor.
- Parameters
factor – scaling factor
For usage examples see the following tutorial:
- show(animation=False, show_time=None, domain=None, depth_level=0, projection=None, land=True, vmin=None, vmax=None, savefile=None, **kwargs)[source]¶
Method to ‘show’ a Parcels Field
- Parameters
animation – Boolean whether result is a single plot, or an animation
show_time – Time at which to show the Field (only in single-plot mode)
domain – dictionary (with keys ‘N’, ‘S’, ‘E’, ‘W’) defining domain to show
depth_level – depth level to be plotted (default 0)
projection – type of cartopy projection to use (default PlateCarree)
land – Boolean whether to show land. This is ignored for flat meshes
vmin – minimum colour scale (only in single-plot mode)
vmax – maximum colour scale (only in single-plot mode)
savefile – Name of a file to save the plot to
- spatial_interpolation(ti, z, y, x, time, particle=None)[source]¶
Interpolate horizontal field values using a SciPy interpolator
- temporal_interpolate_fullfield(ti, time)[source]¶
Calculate the data of a field between two snapshots, using linear interpolation
- Parameters
ti – Index in time array associated with time (via
time_index()
)time – Time to interpolate to
- Return type
Linearly interpolated field
- class parcels.field.NestedField(name, F, V=None, W=None)[source]¶
Bases:
list
Class NestedField is a list of Fields from which the first one to be not declared out-of-boundaries at particle position is interpolated. This induces that the order of the fields in the list matters. Each one it its turn, a field is interpolated: if the interpolation succeeds or if an error other than ErrorOutOfBounds is thrown, the function is stopped. Otherwise, next field is interpolated. NestedField returns an ErrorOutOfBounds only if last field is as well out of boundaries. NestedField is composed of either Fields or VectorFields.
See here for a detailed tutorial
- Parameters
name – Name of the NestedField
F – List of fields (order matters). F can be a scalar Field, a VectorField, or the zonal component (U) of the VectorField
V – List of fields defining the meridional component of a VectorField, if F is the zonal component. (default: None)
W – List of fields defining the vertical component of a VectorField, if F and V are the zonal and meridional components (default: None)
- class parcels.field.SummedField(name, F, V=None, W=None)[source]¶
Bases:
list
Class SummedField is a list of Fields over which Field interpolation is summed. This can e.g. be used when combining multiple flow fields, where the total flow is the sum of all the individual flows. Note that the individual Fields can be on different Grids. Also note that, since SummedFields are lists, the individual Fields can still be queried through their list index (e.g. SummedField[1]). SummedField is composed of either Fields or VectorFields.
See here for a detailed tutorial
- Parameters
name – Name of the SummedField
F – List of fields. F can be a scalar Field, a VectorField, or the zonal component (U) of the VectorField
V – List of fields defining the meridional component of a VectorField, if F is the zonal component. (default: None)
W – List of fields defining the vertical component of a VectorField, if F and V are the zonal and meridional components (default: None)
- class parcels.field.VectorField(name, U, V, W=None)[source]¶
Bases:
object
Class VectorField stores 2 or 3 fields which defines together a vector field. This enables to interpolate them as one single vector field in the kernels.
- Parameters
name – Name of the vector field
U – field defining the zonal component
V – field defining the meridional component
W – field defining the vertical component (default: None)
- spatial_c_grid_interpolation3D(ti, z, y, x, time, particle=None)[source]¶
V1
U0
U1
V0
The interpolation is done in the following by interpolating linearly U depending on the longitude coordinate and interpolating linearly V depending on the latitude coordinate. Curvilinear grids are treated properly, since the element is projected to a rectilinear parent element.
parcels.gridset module¶
parcels.grid module¶
- class parcels.grid.CurvilinearSGrid(lon, lat, depth, time=None, time_origin=None, mesh='flat')[source]¶
Bases:
parcels.grid.CurvilinearGrid
Curvilinear S Grid.
- Parameters
lon – 2D array containing the longitude coordinates of the grid
lat – 2D array containing the latitude coordinates of the grid
depth – 4D (time-evolving) or 3D (time-independent) array containing the vertical coordinates of the grid, which are s-coordinates. s-coordinates can be terrain-following (sigma) or iso-density (rho) layers, or any generalised vertical discretisation. The depth of each node depends then on the horizontal position (lon, lat), the number of the layer and the time is depth is a 4D array. depth array is either a 4D array[xdim][ydim][zdim][tdim] or a 3D array[xdim][ydim[zdim].
time – Vector containing the time coordinates of the grid
time_origin – Time origin (TimeConverter object) of the time axis
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
- class parcels.grid.CurvilinearZGrid(lon, lat, depth=None, time=None, time_origin=None, mesh='flat')[source]¶
Bases:
parcels.grid.CurvilinearGrid
Curvilinear Z Grid.
- Parameters
lon – 2D array containing the longitude coordinates of the grid
lat – 2D array containing the latitude coordinates of the grid
depth – Vector containing the vertical coordinates of the grid, which are z-coordinates. The depth of the different layers is thus constant.
time – Vector containing the time coordinates of the grid
time_origin – Time origin (TimeConverter object) of the time axis
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
- class parcels.grid.Grid(lon, lat, time, time_origin, mesh)[source]¶
Bases:
object
Grid class that defines a (spatial and temporal) grid on which Fields are defined
- property child_ctypes_struct¶
Returns a ctypes struct object containing all relevant pointers and sizes for this grid.
- class parcels.grid.RectilinearSGrid(lon, lat, depth, time=None, time_origin=None, mesh='flat')[source]¶
Bases:
parcels.grid.RectilinearGrid
- Rectilinear S Grid. Same horizontal discretisation as a rectilinear z grid,
but with s vertical coordinates
- Parameters
lon – Vector containing the longitude coordinates of the grid
lat – Vector containing the latitude coordinates of the grid
depth – 4D (time-evolving) or 3D (time-independent) array containing the vertical coordinates of the grid, which are s-coordinates. s-coordinates can be terrain-following (sigma) or iso-density (rho) layers, or any generalised vertical discretisation. The depth of each node depends then on the horizontal position (lon, lat), the number of the layer and the time is depth is a 4D array. depth array is either a 4D array[xdim][ydim][zdim][tdim] or a 3D array[xdim][ydim[zdim].
time – Vector containing the time coordinates of the grid
time_origin – Time origin (TimeConverter object) of the time axis
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
- class parcels.grid.RectilinearZGrid(lon, lat, depth=None, time=None, time_origin=None, mesh='flat')[source]¶
Bases:
parcels.grid.RectilinearGrid
Rectilinear Z Grid
- Parameters
lon – Vector containing the longitude coordinates of the grid
lat – Vector containing the latitude coordinates of the grid
depth – Vector containing the vertical coordinates of the grid, which are z-coordinates. The depth of the different layers is thus constant.
time – Vector containing the time coordinates of the grid
time_origin – Time origin (TimeConverter object) of the time axis
mesh –
String indicating the type of mesh coordinates and units used during velocity interpolation:
spherical (default): Lat and lon in degree, with a correction for zonal velocity U near the poles.
flat: No conversion, lat/lon are assumed to be in m.
parcels.particle module¶
- class parcels.particle.JITParticle(*args, **kwargs)[source]¶
Bases:
parcels.particle.ScipyParticle
Particle class for JIT-based (Just-In-Time) Particle objects
- Parameters
lon – Initial longitude of particle
lat – Initial latitude of particle
fieldset –
parcels.fieldset.FieldSet
object to track this particle ondt – Execution timestep for this particle
time – Current time of the particle
Additional Variables can be added via the :Class Variable: objects
Users should use JITParticles for faster advection computation.
- class parcels.particle.ScipyParticle(lon, lat, pid, fieldset, depth=0.0, time=0.0, cptr=None)[source]¶
Bases:
parcels.particle._Particle
Class encapsulating the basic attributes of a particle, to be executed in SciPy mode
- Parameters
lon – Initial longitude of particle
lat – Initial latitude of particle
depth – Initial depth of particle
fieldset –
parcels.fieldset.FieldSet
object to track this particle ontime – Current time of the particle
Additional Variables can be added via the :Class Variable: objects
- class parcels.particle.Variable(name, dtype=<class 'numpy.float32'>, initial=0, to_write=True)[source]¶
Bases:
object
Descriptor class that delegates data access to particle data
- Parameters
name – Variable name as used within kernels
dtype – Data type (numpy.dtype) of the variable
initial – Initial value of the variable. Note that this can also be a Field object, which will then be sampled at the location of the particle
to_write ((bool, 'once', optional)) – Boolean or ‘once’. Controls whether Variable is written to NetCDF file. If to_write = ‘once’, the variable will be written as a time-independent 1D array
parcels.application_kernels.advection module¶
parcels.application_kernels.advectiondiffusion module¶
parcels.application_kernels.EOSseawaterproperties module¶
parcels.application_kernels.TEOSseawaterdensity module¶
parcels.compilation module¶
parcels.kernel module¶
- class parcels.kernel.Kernel(fieldset, ptype, pyfunc=None, funcname=None, funccode=None, py_ast=None, funcvars=None, c_include='', delete_cfiles=True)[source]¶
Kernel object that encapsulates auto-generated code.
- Parameters
fieldset – FieldSet object providing the field information
ptype – PType object for the kernel particle
delete_cfiles – Boolean whether to delete the C-files after compilation in JIT mode (default is True)
Note: A Kernel is either created from a compiled <function …> object or the necessary information (funcname, funccode, funcvars) is provided. The py_ast argument may be derived from the code string, but for concatenation, the merged AST plus the new header definition is required.
- execute(pset, endtime, dt, recovery=None, output_file=None, execute_once=False)[source]¶
Execute this Kernel over a ParticleSet for several timesteps
- remove_deleted(pset, output_file, endtime)[source]¶
Utility to remove all particles that signalled deletion.
This version is generally applicable to all structures and collections
parcels.particlefile module¶
Module controlling the writing of ParticleSets to NetCDF file
- class parcels.particlefile.ParticleFile(name, particleset, outputdt=inf, write_ondelete=False, convert_at_end=True, tempwritedir=None, pset_info=None)[source]¶
Bases:
object
Initialise trajectory output.
- Parameters
name – Basename of the output file
particleset – ParticleSet to output
outputdt – Interval which dictates the update frequency of file output while ParticleFile is given as an argument of ParticleSet.execute() It is either a timedelta object or a positive double.
write_ondelete – Boolean to write particle data only when they are deleted. Default is False
convert_at_end – Boolean to convert npy files to netcdf at end of run. Default is True
tempwritedir – directories to write temporary files to during executing. Default is out-XXXXXX where Xs are random capitals. Files for individual processors are written to subdirectories 0, 1, 2 etc under tempwritedir
pset_info – dictionary of info on the ParticleSet, stored in tempwritedir/XX/pset_info.npy, used to create NetCDF file from npy-files.
- add_metadata(name, message)[source]¶
Add metadata to
parcels.particleset.ParticleSet
- Parameters
name – Name of the metadata variabale
message – message to be written
- close(delete_tempfiles=True)[source]¶
Close the ParticleFile object by exporting and then deleting the temporary npy files
- delete_tempwritedir(tempwritedir=None)[source]¶
Deleted all temporary npy files
:param tempwritedir Optional path of the directory to delete
- dump_dict_to_npy(data_dict, data_dict_once)[source]¶
Buffer data to set of temporary numpy files, using np.save
- open_netcdf_file(data_shape)[source]¶
Initialise NetCDF4.Dataset for trajectory output. The output follows the format outlined in the Discrete Sampling Geometries section of the CF-conventions: http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#discrete-sampling-geometries The current implementation is based on the NCEI template: http://www.nodc.noaa.gov/data/formats/netcdf/v2.0/trajectoryIncomplete.cdl
- Parameters
data_shape – shape of the variables in the NetCDF4 file
- read_from_npy(file_list, time_steps, var)[source]¶
Read NPY-files for one variable using a loop over all files.
- Parameters
file_list – List that contains all file names in the output directory
time_steps – Number of time steps that were written in out directory
var – name of the variable to read
- write(pset, time, deleted_only=False)[source]¶
Write all data from one time step to a temporary npy-file using a python dictionary. The data is saved in the folder ‘out’.
- Parameters
pset – ParticleSet object to write
time – Time at which to write ParticleSet
deleted_only – Flag to write only the deleted Particles
parcels.rng module¶
- parcels.rng.expovariate(lamb)[source]¶
Returns a randome float of an exponential distribution with parameter lamb
parcels.particlesets.baseparticleset module¶
- class parcels.particlesets.baseparticleset.BaseParticleSet(fieldset=None, pclass=None, lon=None, lat=None, depth=None, time=None, repeatdt=None, lonlatdepth_dtype=None, pid_orig=None, **kwargs)[source]¶
Bases:
parcels.particlesets.baseparticleset.NDCluster
Base ParticleSet.
- abstract Kernel(pyfunc, c_include='', delete_cfiles=True)[source]¶
Wrapper method to convert a pyfunc into a
parcels.kernel.Kernel
object based on fieldset and ptype of the ParticleSet :param delete_cfiles: Boolean whether to delete the C-files after compilation in JIT mode (default is True)
- abstract ParticleFile(*args, **kwargs)[source]¶
Wrapper method to initialise a
parcels.particlefile.ParticleFile
object from the ParticleSet
- abstract cstruct()[source]¶
‘cstruct’ returns the ctypes mapping of the combined collections cstruct and the fieldset cstruct. This depends on the specific structure in question.
- density(field_name=None, particle_val=None, relative=False, area_scale=False)[source]¶
Method to calculate the density of particles in a ParticleSet from their locations, through a 2D histogram.
- Parameters
field – Optional
parcels.field.Field
object to calculate the histogram on. Default is fieldset.Uparticle_val – Optional numpy-array of values to weigh each particle with, or string name of particle variable to use weigh particles with. Default is None, resulting in a value of 1 for each particle
relative – Boolean to control whether the density is scaled by the total weight of all particles. Default is False
area_scale – Boolean to control whether the density is scaled by the area (in m^2) of each grid cell. Default is False
- abstract property error_particles¶
Get an iterator over all particles that are in an error state.
This is a fallback implementation, it might be slow.
- Returns
Collection iterator over error particles.
- execute(pyfunc=<function AdvectionRK4>, endtime=None, runtime=None, dt=1.0, moviedt=None, recovery=None, output_file=None, movie_background_field=None, verbose_progress=None, postIterationCallbacks=None, callbackdt=None)[source]¶
Execute a given kernel function over the particle set for multiple timesteps. Optionally also provide sub-timestepping for particle output.
- Parameters
pyfunc – Kernel function to execute. This can be the name of a defined Python function or a
parcels.kernel.Kernel
object. Kernels can be concatenated using the + operatorendtime – End time for the timestepping loop. It is either a datetime object or a positive double.
runtime – Length of the timestepping loop. Use instead of endtime. It is either a timedelta object or a positive double.
dt – Timestep interval to be passed to the kernel. It is either a timedelta object or a double. Use a negative value for a backward-in-time simulation.
moviedt – Interval for inner sub-timestepping (leap), which dictates the update frequency of animation. It is either a timedelta object or a positive double. None value means no animation.
output_file –
parcels.particlefile.ParticleFile
object for particle outputrecovery – Dictionary with additional :mod:parcels.tools.error recovery kernels to allow custom recovery behaviour in case of kernel errors.
movie_background_field – field plotted as background in the movie if moviedt is set. ‘vector’ shows the velocity as a vector field.
verbose_progress – Boolean for providing a progress bar for the kernel execution loop.
postIterationCallbacks – (Optional) Array of functions that are to be called after each iteration (post-process, non-Kernel)
callbackdt – (Optional, in conjecture with ‘postIterationCallbacks) timestep inverval to (latestly) interrupt the running kernel and invoke post-iteration callbacks from ‘postIterationCallbacks’
- classmethod from_field(fieldset, pclass, start_field, size, mode='monte_carlo', depth=None, time=None, repeatdt=None, lonlatdepth_dtype=None)[source]¶
Initialise the ParticleSet randomly drawn according to distribution from a field
- Parameters
fieldset –
parcels.fieldset.FieldSet
object from which to sample velocitypclass – mod:parcels.particle.JITParticle or
parcels.particle.ScipyParticle
object that defines custom particlestart_field – Field for initialising particles stochastically (horizontally) according to the presented density field.
size – Initial size of particle set
mode – Type of random sampling. Currently only ‘monte_carlo’ is implemented
depth – Optional list of initial depth values for particles. Default is 0m
time – Optional start time value for particles. Default is fieldset.U.time[0]
repeatdt – Optional interval (in seconds) on which to repeat the release of the ParticleSet
lonlatdepth_dtype – Floating precision for lon, lat, depth particle coordinates. It is either np.float32 or np.float64. Default is np.float32 if fieldset.U.interp_method is ‘linear’ and np.float64 if the interpolation method is ‘cgrid_velocity’
- classmethod from_line(fieldset, pclass, start, finish, size, depth=None, time=None, repeatdt=None, lonlatdepth_dtype=None)[source]¶
Initialise the ParticleSet from start/finish coordinates with equidistant spacing Note that this method uses simple numpy.linspace calls and does not take into account great circles, so may not be a exact on a globe
- Parameters
fieldset –
parcels.fieldset.FieldSet
object from which to sample velocitypclass – mod:parcels.particle.JITParticle or
parcels.particle.ScipyParticle
object that defines custom particlestart – Starting point for initialisation of particles on a straight line.
finish – End point for initialisation of particles on a straight line.
size – Initial size of particle set
depth – Optional list of initial depth values for particles. Default is 0m
time – Optional start time value for particles. Default is fieldset.U.time[0]
repeatdt – Optional interval (in seconds) on which to repeat the release of the ParticleSet
lonlatdepth_dtype – Floating precision for lon, lat, depth particle coordinates. It is either np.float32 or np.float64. Default is np.float32 if fieldset.U.interp_method is ‘linear’ and np.float64 if the interpolation method is ‘cgrid_velocity’
- classmethod from_list(fieldset, pclass, lon, lat, depth=None, time=None, repeatdt=None, lonlatdepth_dtype=None, **kwargs)[source]¶
Initialise the ParticleSet from lists of lon and lat
- Parameters
fieldset –
parcels.fieldset.FieldSet
object from which to sample velocitypclass – mod:parcels.particle.JITParticle or
parcels.particle.ScipyParticle
object that defines custom particlelon – List of initial longitude values for particles
lat – List of initial latitude values for particles
depth – Optional list of initial depth values for particles. Default is 0m
time – Optional list of start time values for particles. Default is fieldset.U.time[0]
repeatdt – Optional interval (in seconds) on which to repeat the release of the ParticleSet
lonlatdepth_dtype – Floating precision for lon, lat, depth particle coordinates. It is either np.float32 or np.float64. Default is np.float32 if fieldset.U.interp_method is ‘linear’ and np.float64 if the interpolation method is ‘cgrid_velocity’
Other Variables can be initialised using further arguments (e.g. v=… for a Variable named ‘v’)
- abstract classmethod from_particlefile(fieldset, pclass, filename, restart=True, restarttime=None, repeatdt=None, lonlatdepth_dtype=None, **kwargs)[source]¶
Initialise the ParticleSet from a netcdf ParticleFile. This creates a new ParticleSet based on locations of all particles written in a netcdf ParticleFile at a certain time. Particle IDs are preserved if restart=True
- Parameters
fieldset –
parcels.fieldset.FieldSet
object from which to sample velocitypclass – mod:parcels.particle.JITParticle or
parcels.particle.ScipyParticle
object that defines custom particlefilename – Name of the particlefile from which to read initial conditions
restart – Boolean to signal if pset is used for a restart (default is True). In that case, Particle IDs are preserved.
restarttime – time at which the Particles will be restarted. Default is the last time written. Alternatively, restarttime could be a time value (including np.datetime64) or a callable function such as np.nanmin. The last is useful when running with dt < 0.
repeatdt – Optional interval (in seconds) on which to repeat the release of the ParticleSet
lonlatdepth_dtype – Floating precision for lon, lat, depth particle coordinates. It is either np.float32 or np.float64. Default is np.float32 if fieldset.U.interp_method is ‘linear’ and np.float64 if the interpolation method is ‘cgrid_velocity’
- abstract classmethod monte_carlo_sample(start_field, size, mode='monte_carlo')[source]¶
Converts a starting field into a monte-carlo sample of lons and lats.
- Parameters
start_field –
parcels.fieldset.Field
object for initialising particles stochastically (horizontally) according to the presented density field.
returns list(lon), list(lat)
- property num_error_particles¶
Get the number of particles that are in an error state.
- show(with_particles=True, show_time=None, field=None, domain=None, projection=None, land=True, vmin=None, vmax=None, savefile=None, animation=False, **kwargs)[source]¶
Method to ‘show’ a Parcels ParticleSet
- Parameters
with_particles – Boolean whether to show particles
show_time – Time at which to show the ParticleSet
field – Field to plot under particles (either None, a Field object, or ‘vector’)
domain – dictionary (with keys ‘N’, ‘S’, ‘E’, ‘W’) defining domain to show
projection – type of cartopy projection to use (default PlateCarree)
land – Boolean whether to show land. This is ignored for flat meshes
vmin – minimum colour scale (only in single-plot mode)
vmax – maximum colour scale (only in single-plot mode)
savefile – Name of a file to save the plot to
animation – Boolean whether result is a single plot, or an animation
parcels.particlesets.particlesetsoa module¶
- parcels.particlesets.particlesetsoa.ParticleSet¶
- class parcels.particlesets.particlesetsoa.ParticleSetSOA(fieldset=None, pclass=<class 'parcels.particle.JITParticle'>, lon=None, lat=None, depth=None, time=None, repeatdt=None, lonlatdepth_dtype=None, pid_orig=None, **kwargs)[source]¶
Bases:
parcels.particlesets.baseparticleset.BaseParticleSet
Container class for storing particle and executing kernel over them.
Please note that this currently only supports fixed size particle sets.
- Parameters
fieldset –
parcels.fieldset.FieldSet
object from which to sample velocity. While fieldset=None is supported, this will throw a warning as it breaks most Parcels functionalitypclass – Optional
parcels.particle.JITParticle
orparcels.particle.ScipyParticle
object that defines custom particlelon – List of initial longitude values for particles
lat – List of initial latitude values for particles
depth – Optional list of initial depth values for particles. Default is 0m
time – Optional list of initial time values for particles. Default is fieldset.U.grid.time[0]
repeatdt – Optional interval (in seconds) on which to repeat the release of the ParticleSet
lonlatdepth_dtype – Floating precision for lon, lat, depth particle coordinates. It is either np.float32 or np.float64. Default is np.float32 if fieldset.U.interp_method is ‘linear’ and np.float64 if the interpolation method is ‘cgrid_velocity’
pid_orig – Optional list of (offsets for) the particle IDs
partitions – List of cores on which to distribute the particles for MPI runs. Default: None, in which case particles are distributed automatically on the processors
Other Variables can be initialised using further arguments (e.g. v=… for a Variable named ‘v’)
- Kernel(pyfunc, c_include='', delete_cfiles=True)[source]¶
Wrapper method to convert a pyfunc into a
parcels.kernel.Kernel
object based on fieldset and ptype of the ParticleSet- Parameters
delete_cfiles – Boolean whether to delete the C-files after compilation in JIT mode (default is True)
- ParticleFile(*args, **kwargs)[source]¶
Wrapper method to initialise a
parcels.particlefile.ParticleFile
object from the ParticleSet
- add(particles)[source]¶
Add particles to the ParticleSet. Note that this is an incremental add, the particles will be added to the ParticleSet on which this function is called.
- Parameters
particles – Another ParticleSet containing particles to add to this one.
- Returns
The current ParticleSet
- cstruct()[source]¶
‘cstruct’ returns the ctypes mapping of the combined collections cstruct and the fieldset cstruct. This depends on the specific structure in question.
- data_indices(variable_name, compare_values, invert=False)[source]¶
Get the indices of all particles where the value of variable_name equals (one of) compare_values.
- Parameters
variable_name – Name of the variable to check.
compare_values – Value or list of values to compare to.
invert – Whether to invert the selection. I.e., when True, return all indices that do not equal (one of) compare_values.
- Returns
Numpy array of indices that satisfy the test.
- density(field_name=None, particle_val=None, relative=False, area_scale=False)[source]¶
Method to calculate the density of particles in a ParticleSet from their locations, through a 2D histogram.
- Parameters
field – Optional
parcels.field.Field
object to calculate the histogram on. Default is fieldset.Uparticle_val – Optional numpy-array of values to weigh each particle with, or string name of particle variable to use weigh particles with. Default is None, resulting in a value of 1 for each particle
relative – Boolean to control whether the density is scaled by the total weight of all particles. Default is False
area_scale – Boolean to control whether the density is scaled by the area (in m^2) of each grid cell. Default is False
- property error_particles¶
Get an iterator over all particles that are in an error state.
- Returns
Collection iterator over error particles.
- classmethod from_field(fieldset, pclass, start_field, size, mode='monte_carlo', depth=None, time=None, repeatdt=None, lonlatdepth_dtype=None)[source]¶
Initialise the ParticleSet randomly drawn according to distribution from a field
- Parameters
fieldset –
parcels.fieldset.FieldSet
object from which to sample velocitypclass – mod:parcels.particle.JITParticle or
parcels.particle.ScipyParticle
object that defines custom particlestart_field – Field for initialising particles stochastically (horizontally) according to the presented density field.
size – Initial size of particle set
mode – Type of random sampling. Currently only ‘monte_carlo’ is implemented
depth – Optional list of initial depth values for particles. Default is 0m
time – Optional start time value for particles. Default is fieldset.U.time[0]
repeatdt – Optional interval (in seconds) on which to repeat the release of the ParticleSet
lonlatdepth_dtype – Floating precision for lon, lat, depth particle coordinates. It is either np.float32 or np.float64. Default is np.float32 if fieldset.U.interp_method is ‘linear’ and np.float64 if the interpolation method is ‘cgrid_velocity’
- classmethod from_particlefile(fieldset, pclass, filename, restart=True, restarttime=None, repeatdt=None, lonlatdepth_dtype=None, **kwargs)[source]¶
Initialise the ParticleSet from a netcdf ParticleFile. This creates a new ParticleSet based on locations of all particles written in a netcdf ParticleFile at a certain time. Particle IDs are preserved if restart=True
- Parameters
fieldset –
parcels.fieldset.FieldSet
object from which to sample velocitypclass – mod:parcels.particle.JITParticle or
parcels.particle.ScipyParticle
object that defines custom particlefilename – Name of the particlefile from which to read initial conditions
restart – Boolean to signal if pset is used for a restart (default is True). In that case, Particle IDs are preserved.
restarttime – time at which the Particles will be restarted. Default is the last time written. Alternatively, restarttime could be a time value (including np.datetime64) or a callable function such as np.nanmin. The last is useful when running with dt < 0.
repeatdt – Optional interval (in seconds) on which to repeat the release of the ParticleSet
lonlatdepth_dtype – Floating precision for lon, lat, depth particle coordinates. It is either np.float32 or np.float64. Default is np.float32 if fieldset.U.interp_method is ‘linear’ and np.float64 if the interpolation method is ‘cgrid_velocity’
- classmethod monte_carlo_sample(start_field, size, mode='monte_carlo')[source]¶
Converts a starting field into a monte-carlo sample of lons and lats.
- Parameters
start_field –
parcels.fieldset.Field
object for initialising particles stochastically (horizontally) according to the presented density field.
returns list(lon), list(lat)
- property num_error_particles¶
Get the number of particles that are in an error state.
- Returns
The number of error particles.
- populate_indices()[source]¶
Pre-populate guesses of particle xi/yi indices using a kdtree.
This is only intended for curvilinear grids, where the initial index search may be quite expensive.
- remove_booleanvector(indices)[source]¶
Method to remove particles from the ParticleSet, based on an array of booleans
- remove_indices(indices)[source]¶
Method to remove particles from the ParticleSet, based on their indices
- set_variable_write_status(var, write_status)[source]¶
Method to set the write status of a Variable :param var: Name of the variable (string) :param write_status: Write status of the variable (True, False or
‘once’)
- show(with_particles=True, show_time=None, field=None, domain=None, projection=None, land=True, vmin=None, vmax=None, savefile=None, animation=False, **kwargs)[source]¶
Method to ‘show’ a Parcels ParticleSet
- Parameters
with_particles – Boolean whether to show particles
show_time – Time at which to show the ParticleSet
field – Field to plot under particles (either None, a Field object, or ‘vector’)
domain – dictionary (with keys ‘N’, ‘S’, ‘E’, ‘W’) defining domain to show
projection – type of cartopy projection to use (default PlateCarree)
land – Boolean whether to show land. This is ignored for flat meshes
vmin – minimum colour scale (only in single-plot mode)
vmax – maximum colour scale (only in single-plot mode)
savefile – Name of a file to save the plot to
animation – Boolean whether result is a single plot, or an animation
- to_dict(pfile, time, deleted_only=False)[source]¶
Convert all Particle data from one time step to a python dictionary. :param pfile: ParticleFile object requesting the conversion :param time: Time at which to write ParticleSet :param deleted_only: Flag to write only the deleted Particles returns two dictionaries: one for all variables to be written each outputdt,
and one for all variables to be written once
parcels.tools.statuscodes module¶
Collection of pre-built recovery kernels
- exception parcels.tools.statuscodes.FieldOutOfBoundError(x, y, z, field=None)[source]¶
Bases:
RuntimeError
Utility error class to propagate out-of-bound field sampling in Scipy mode
- exception parcels.tools.statuscodes.FieldSamplingError(x, y, z, field=None)[source]¶
Bases:
RuntimeError
Utility error class to propagate erroneous field sampling in Scipy mode
- exception parcels.tools.statuscodes.KernelError(particle, fieldset=None, msg=None)[source]¶
Bases:
RuntimeError
General particle kernel error with optional custom message
- exception parcels.tools.statuscodes.OutOfBoundsError(particle, fieldset=None, lon=None, lat=None, depth=None)[source]¶
Bases:
parcels.tools.statuscodes.KernelError
Particle kernel error for out-of-bounds field sampling
- exception parcels.tools.statuscodes.OutOfTimeError(particle, fieldset)[source]¶
Bases:
parcels.tools.statuscodes.KernelError
Particle kernel error for time extrapolation field sampling
- exception parcels.tools.statuscodes.ThroughSurfaceError(particle, fieldset=None, lon=None, lat=None, depth=None)[source]¶
Bases:
parcels.tools.statuscodes.KernelError
Particle kernel error for field sampling at surface
parcels.tools.converters module¶
- class parcels.tools.converters.Geographic[source]¶
Bases:
parcels.tools.converters.UnitConverter
Unit converter from geometric to geographic coordinates (m to degree)
- class parcels.tools.converters.GeographicPolar[source]¶
Bases:
parcels.tools.converters.UnitConverter
Unit converter from geometric to geographic coordinates (m to degree) with a correction to account for narrower grid cells closer to the poles.
- class parcels.tools.converters.GeographicPolarSquare[source]¶
Bases:
parcels.tools.converters.UnitConverter
Square distance converter from geometric to geographic coordinates (m2 to degree2) with a correction to account for narrower grid cells closer to the poles.
- class parcels.tools.converters.GeographicSquare[source]¶
Bases:
parcels.tools.converters.UnitConverter
Square distance converter from geometric to geographic coordinates (m2 to degree2)
- class parcels.tools.converters.TimeConverter(time_origin=0)[source]¶
Bases:
object
Converter class for dates with different calendars in FieldSets
- Param
time_origin: time origin of the class. Currently supported formats are float, integer, numpy.datetime64, and netcdftime.DatetimeNoLeap
parcels.tools.loggers module¶
Script to create a logger for Parcels
parcels.plotting module¶
- parcels.plotting.create_parcelsfig_axis(spherical, land=True, projection=None, central_longitude=0, cartopy_features=[])[source]¶
- parcels.plotting.plotfield(field, show_time=None, domain=None, depth_level=0, projection=None, land=True, vmin=None, vmax=None, savefile=None, **kwargs)[source]¶
Function to plot a Parcels Field
- Parameters
show_time – Time at which to show the Field
domain – dictionary (with keys ‘N’, ‘S’, ‘E’, ‘W’) defining domain to show
depth_level – depth level to be plotted (default 0)
projection – type of cartopy projection to use (default PlateCarree)
land – Boolean whether to show land. This is ignored for flat meshes
vmin – minimum colour scale (only in single-plot mode)
vmax – maximum colour scale (only in single-plot mode)
savefile – Name of a file to save the plot to
animation – Boolean whether result is a single plot, or an animation
- parcels.plotting.plotparticles(particles, with_particles=True, show_time=None, field=None, domain=None, projection=None, land=True, vmin=None, vmax=None, savefile=None, animation=False, **kwargs)[source]¶
Function to plot a Parcels ParticleSet
- Parameters
show_time – Time at which to show the ParticleSet
with_particles – Boolean whether particles are also plotted on Field
field – Field to plot under particles (either None, a Field object, or ‘vector’)
domain – dictionary (with keys ‘N’, ‘S’, ‘E’, ‘W’) defining domain to show
projection – type of cartopy projection to use (default PlateCarree)
land – Boolean whether to show land. This is ignored for flat meshes
vmin – minimum colour scale (only in single-plot mode)
vmax – maximum colour scale (only in single-plot mode)
savefile – Name of a file to save the plot to
animation – Boolean whether result is a single plot, or an animation
scripts.plottrajectoriesfile module¶
- scripts.plottrajectoriesfile.plotTrajectoriesFile(filename, mode='2d', tracerfile=None, tracerfield='P', tracerlon='x', tracerlat='y', recordedvar=None, movie_forward=True, bins=20, show_plt=True, central_longitude=0)[source]¶
Quick and simple plotting of Parcels trajectories
- Parameters
filename – Name of Parcels-generated NetCDF file with particle positions
mode – Type of plot to show. Supported are ‘2d’, ‘3d’, ‘hist2d’, ‘movie2d’ and ‘movie2d_notebook’. The latter two give animations, with ‘movie2d_notebook’ specifically designed for jupyter notebooks
tracerfile – Name of NetCDF file to show as background
tracerfield – Name of variable to show as background
tracerlon – Name of longitude dimension of variable to show as background
tracerlat – Name of latitude dimension of variable to show as background
recordedvar – Name of variable used to color particles in scatter-plot. Only works in ‘movie2d’ or ‘movie2d_notebook’ mode.
movie_forward – Boolean whether to show movie in forward or backward mode (default True)
bins – Number of bins to use in hist2d mode. See also https://matplotlib.org/api/_as_gen/matplotlib.pyplot.hist2d.html
show_plt – Boolean whether plot should directly be show (for py.test)
central_longitude – Degrees East at which to center the plot
scripts.get_examples module¶
Get example scripts, notebooks, and data files.
- scripts.get_examples.copy_data_and_examples_from_package_to(target_path)[source]¶
Copy example data from Parcels directory.
Return thos parths of the list file_names that were not found in the package.