ocean_data_gateway.readers.local.region

class ocean_data_gateway.readers.local.region(kwargs)

Bases: ocean_data_gateway.readers.local.LocalReader

Inherits from LocalReader to search over a region of space and time.

kw

Contains space and time search constraints: min_lon, max_lon, min_lat, max_lat, min_time, max_time.

Type

dict

variables

Variable names if you want to limit the search to those. This is currently ignored.

Type

string or list

approach

approach is defined as ‘region’ for this class.

Type

string

Attributes

catalog

Write then open catalog.

dataset_ids

Find dataset_ids for catalog.

meta

Rearrange the individual metadata into a dataframe.

Methods

data()	Read in data for all dataset_ids.
data_by_dataset(dataset_id)	Return the data for a single dataset_id.
meta_by_dataset(dataset_id)	Return the catalog metadata for a single dataset_id.
write_catalog()	Write catalog file.

__init__(kwargs)

Parameters

kwargs (dict) –

Can contain arguments to pass onto the base AxdsReader class (catalog_name, parallel, filenames). The dict entries to initialize this class are:

• kw: dict Contains space and time search constraints: min_lon, max_lon, min_lat, max_lat, min_time, max_time. Not used to filter data currently.

• variables: string or list, optional Variable names if you want to limit the search to those. This is not used to filter data currently.

Methods

__init__(kwargs)	param kwargs Can contain arguments to pass onto the base AxdsReader class
data()	Read in data for all dataset_ids.
data_by_dataset(dataset_id)	Return the data for a single dataset_id.
meta_by_dataset(dataset_id)	Return the catalog metadata for a single dataset_id.
write_catalog()	Write catalog file.

Attributes

catalog	Write then open catalog.
dataset_ids	Find dataset_ids for catalog.
meta	Rearrange the individual metadata into a dataframe.

property catalog

Write then open catalog.

data()

Read in data for all dataset_ids.

Returns

• A dictionary with keys of the dataset_ids and values the data of type

• If `filename` is a csv file (a pandas DataFrame)

• If `filename` is a netcdf file (an xarray Dataset)

Notes

This is either done in parallel with the multiprocessing library or in serial.

data_by_dataset(dataset_id)

Return the data for a single dataset_id.

Returns

Return type

A tuple of (dataset_id, data), where data type is a pandas DataFrame.

Notes

Data is read into memory.

TODO: SHOULD I INCLUDE TIME RANGE?

property dataset_ids

Find dataset_ids for catalog.

Notes

The dataset_ids are read from the catalog, so the catalog is created before this can happen.

property meta

Rearrange the individual metadata into a dataframe.

meta_by_dataset(dataset_id)

Return the catalog metadata for a single dataset_id.

TODO: Should this return intake-style or a row of the metadata dataframe?

write_catalog()

Write catalog file.