Detailed API Documentation

catalogue — Database core management

Note

This module needs a lot of cleanups !

Catalogue class manages coherency of the database and underlying storage (i.e. storagesets).

A Catalogue instance has a connection to database (conn) and is able to insert a new dataset (Catalogue.register()) or query database with DAP-like projection and selection constraints (Catalogue.getQueryFileList()).

All configuration parameters are read from pyctoh.ini.

class pyctoh.catalogue.Catalogue

A connection to a database.

check_dataset(name)

Check if dataset is already registered in database.

Returns:dataset_id if dataset is in db, None otherwise

getMissionId(mission_name)

getVariableId(mission_id, param_name)

getXId(sql, args)

get_dataset_ids(projection, selection)

Get ids of datasets that match the given constraints.

Parameters:

• projection (iterator on strings) – list of wanted variables
• selection (opendap-style selection string (c.f. http://www.opendap.org/user/guide-html/guide_33.html)) – request constraint

Returns:

a list of dataset_ids matching the given projection and constraints.

register(dataset)

Register a dataset in database.

dataset — PyCTOH’s internal format

Note

This module needs a lot of cleanups !

Dataset is PyCTOH’s pivot format for data from GDR.

Dataset loosely maps netCDF concepts of globals, variables, dimensions and attributes.

class pyctoh.dataset.Dataset(mission)

Bases: object

Convert native GDR to netCDF.

Parameters:

• mission – mission name
• dimensions – a dictionnary of Dimension objects, keyed by name
• globals – dictionnary of global variables for this dataset
• variables – dictionnary of Variable instances, keyed by parameter name.

bbox()

Get dataset bounding box.

Return (lat_min, lon_min, lat_max, lon_max), or None for empty dataset. lon_min means western bound. lon_max, eastern.

crop(bbox)

Crop dataset to bounding box.

TODO: handle time_hf (using lon_hf and lat_hf) as well... : if a variable is independant from lon and lat, it is kept as it.

get_bounds(variable)

Get min and max values of variable. If variable is “lon”, min and max are the western and eastern bounds longitudes, respectively.

Parameter:variable – variable name Returns:(min, max ) tuple

reduce(projection, selection)

Reduce dataset according to selection

TODO : handle projection

class pyctoh.dataset.Dimension(name, size, sorted=False)

Bases: object

Dimension object

class pyctoh.dataset.Variable(dtype, dimensions, attributes, values)

Bases: object

PyCTOH’s representation of a variable.

Parameters:

• dtype – netcdf type of data
• dimensions – tuple of dimension names
• attributes – dictionnary of variable’s attributes, keyed by name
• values – numpy array of content

pyctoh.dataset.np2cdf(typename)

Utility converter : convert type to netCDF type name.

>>> np2cdf(bool)
'i1'

pyctoh.fetch.fetch.cmd_fetch(options)