pywatershed.parameters.StarfitParameters#

class pywatershed.parameters.StarfitParameters(dims, coords, data_vars, metadata, encoding={})[source]#

Starfit parameter class

The GRanD data https://sedac.ciesin.columbia.edu/data/set/grand-v1-dams-rev01

The istarf data https://zenodo.org/record/4602277#.ZCtYj-zMJqs

The resops data https://zenodo.org/record/5893641#.ZCtakuzMJqs

# add citiatons. add this information to the starfit model too # add a working example

Parameters:

  • parameter_dict (dict) –

    parameters dictionary: either structure

    • param: value

    • process: {param: value … }

    where the later is a parameter dictionary grouped by process. The keys for process should be either the class itself, class.name, or type(class.__name__).

  • parameter_dimensions_dict (dict) – parameters dimensions dictionary with a structure mirring the parameter dict as described above but with shape tuples in place of parameter value data.

  • Returns – StarfitParameters object

__init__(dims, coords, data_vars, metadata, encoding={})[source]#

Methods

__init__(dims, coords, data_vars, metadata)

drop_var(var_names)

Drop variables

from_dict(dict_in[, copy])

Return this class from a passed dictionary. :type dict_in: :param dict_in: a dictionary from which to create an instance of this class :type copy: :param copy: boolean if the passed dictionary should be deep copied.

from_ds(ds)

Get this class from a dataset (nc4 or xarray).

from_netcdf(resops_domain, istarf_conus, ...)

Load this class from a netcdf file.

get_dim_values([keys])

Get the values of the dimensions by keys.

get_param_values([keys])

Get the values of the parameters (coords or data_vars) by keys

merge(*args[, copy, del_global_src])

Merge Parameter classes

rename_dim(name_maps[, in_place])

Rename dimensions.

rename_var(name_maps[, in_place])

Rename variables.

subset(keys[, copy, keep_global, ...])

Subset a DatasetDict to keys in data_vars or coordinates

subset_on_coord(coord_name, where)

Subset DatasetDict to a np.where along a named coordinate in-place

to_dd([copy])

Export Parameters to a DatasetDict (for editing).

to_nc4_ds(filename)

Export Parameters to a netcdf4 dataset

to_netcdf(filename[, use_xr])

Write parameters to a netcdf file

to_xr_dd()

Export to an xarray DatasetDict (xr.Dataset.to_dict()).

to_xr_ds()

Export Parameters to an xarray dataset

validate()

Check that a DatasetDict is internally consistent.

Attributes

coords

Return the coordinates

data

dims, coords, data_vars, metadata, encoding

data_vars

Return the data_vars.

dims

Return the dimensions

encoding

Return the encoding

metadata

Return the metadata

parameters

spatial_coord_names

Return the spatial coordinate names.

variables

Return coords and data_vars together
property coords: dict#

Return the coordinates

property data: dict#

dims, coords, data_vars, metadata, encoding

Parameters:

copy – boolean if a deepcopy is desired

Returns:

A dict of dicts containing all the data

Type:

Return a dict of dicts

property data_vars: dict#

Return the data_vars.

property dims: dict#

Return the dimensions

drop_var(var_names)#

Drop variables

property encoding: dict#

Return the encoding

classmethod from_dict(dict_in, copy=False)#

Return this class from a passed dictionary. :type dict_in: :param dict_in: a dictionary from which to create an instance of this

class

Parameters:

copy – boolean if the passed dictionary should be deep copied

Returns:

A object of this class.

classmethod from_ds(ds)#

Get this class from a dataset (nc4 or xarray).

static from_netcdf(resops_domain, istarf_conus, grand_dams, grand_ids=None, param_names=None)[source]#

Load this class from a netcdf file.

Return type:

dict

get_dim_values(keys=None)#

Get the values of the dimensions by keys.

Return type:

Union[dict, ndarray]

get_param_values(keys=None)#

Get the values of the parameters (coords or data_vars) by keys

Return type:

Union[dict, ndarray]

Also see:

subset() method is a Parameter object is desired.

classmethod merge(*args, copy=True, del_global_src=True)#

Merge Parameter classes

Parameters:

  • *args – several Parameters objects as individual objects.

  • copy – bool if the args should be copied?

  • del_golbal_src – bool delete the file source attribute to avoid meaningless merge conflicts?

property metadata: dict#

Return the metadata

property parameters: dict#
rename_dim(name_maps, in_place=True)#

Rename dimensions.

rename_var(name_maps, in_place=True)#

Rename variables.

property spatial_coord_names: dict#

Return the spatial coordinate names. :param None:

Returns:

Dictionary of spatial coordinates with names.

subset(keys, copy=False, keep_global=False, keep_global_metadata=None, keep_global_encoding=None, strict=False)#

Subset a DatasetDict to keys in data_vars or coordinates

Parameters:

  • keys (Iterable) – Iterable to subset on

  • copy (bool) – bool to copy the input or edit it

  • keep_global (bool) – bool that sets both keep_global_metadata and keep_global_encoding

  • keep_global_metadata (Optional[bool]) – bool retain the global metadata in the subset

  • keep_global_encoding (Optional[bool]) – bool retain the global encoding in the subset

Return type:

DatasetDict

Returns:

A subset Parameter object on the passed keys.

subset_on_coord(coord_name, where)#

Subset DatasetDict to a np.where along a named coordinate in-place

Parameters:

  • coord_name (str) – string name of a coordinate

  • where (ndarray) – the result of an np.where along that coordinate (or likewise constructed)

Return type:

None

Returns:

None

to_dd(copy=True)#

Export Parameters to a DatasetDict (for editing).

Parameters can NOT be edited, but DatasetDicts can. To convert back pws.Parameters(**dataset_dict.data).

Parameters:

copy – return a copy or a reference?

Return type:

DatasetDict

to_nc4_ds(filename)#

Export Parameters to a netcdf4 dataset

Parameters:

filename (Union[str, Path]) – a file to write to as nc4 is not in memory

Return type:

None

to_netcdf(filename, use_xr=False)#

Write parameters to a netcdf file

Return type:

None

to_xr_dd()#

Export to an xarray DatasetDict (xr.Dataset.to_dict()).

Return type:

dict

to_xr_ds()#

Export Parameters to an xarray dataset

Return type:

Dataset

validate()#

Check that a DatasetDict is internally consistent.

Return type:

None

Returns:

None

property variables: dict#

Return coords and data_vars together