ds format

Python API

The ds-format Python package provides API for reading, writing and manipulating data fies. The library can be imported with:

import ds_format as ds

Contents

Constants

ds.drivers.netcdf.JD_UNITS

days since -4713-11-24 12:00 UTC

NetCDF units for storing Julian date time variables.

ds.drivers.netcdf.JD_CALENDAR

proleptic_greogorian

NetCDF calendar for storing Julian date time variables.

Functions

get_dims

ds.get_dims(d)

Get all dimension names in a dataset.

Arguments:

• d - Dataset (dict).

Returns dimension names (list of str).

get_vars

ds.get_vars(d)

Get all variable names in a dataset.

Arguments:

• d - Dataset (dict).

Returns variable names (list of str).

group_by

ds.group_by(d, dim, group, func)

Group values along a dimension. Each variable with a given dimension dim is split by group into subsets. Each subset is replaced with a value computed by func.

Arguments:

• d - Dataset (dict).
• dim - Dimension to group along (str).
• group - Groups (ndarray or list). Array of the same length as the dimension.
• func - Group function (function). func(y, axis=i) is called for each subset y, where i is the index of the dimension.

Returns None.

merge

ds.merge(dd, dim, new=None, variables=None)

Merge datasets along a dimension dim. If the dimension is not defined in the dataset, merge along a new dimension dim. If new is None and dim is not new, variables without the dimension are set with the first occurrence of the variable. If new is not None and dim is not new, variables without the dimension dim are merged along a new dimension new. If variables is not None, only those variables are merged along a new dimension and other variables are set to the first occurrence of the variable.

Arguments:

• dd - Datasets (list).
• dim - Name of a dimension to merge along (str).
• new - Name of a new dimension (str) or None.
• variables - Variables to merge along a new dimension (list) or None for all variables.

Returns a dataset (dict).

read

ds.read(filename, variables=None, sel=None, full=False, jd=False)

Read dataset from a file.

Arguments:

• filename - Filename (str).
• variables - Variable names to read (list of str).
• sel - Selector (see select).
• full - Read all metadata (bool).
• jd - Convert time variables to Julian dates (see Aquarius Time) (bool).

Supported formats:

• NetCDF4 (.nc, .nc4, .nc3, .netcdf, .hdf, .h5)
• JSON (.json)

Returns dataset (dict).

readdir

ds.readdir(dirname, variables=None, merge=None, warnings=[], ...)

Read multiple files in a directory.

Arguments:

• dirname - Directory name.
• variables - Variable names to read (list of str).
• merge - Dimension name to merge datasets by.
• warnings - Array to be populated with warnings.
• … - Optional keyword arguments passed to read.

Returns a list of datasets (list of dict) if merge is None or a merged dataset (dict) if merge is a dimension name.

rename

ds.rename(d, old, new)

Rename a variable. Any dimension with the same name is also renamed.

Arguments:

• d - Dataset (dict).
• old - Old variable name (str).
• new - New variable name (str).

Returns None.

rename_dim

ds.rename_dim(d, old, new)

Rename a dimension.

Arguments:

• d - Dataset (dict).
• old - Old variable name (str).
• new - New variable name (str).

Returns None.

select

ds.select(d, sel)

Filter dataset by a selector.

Arguments:

• d - Dataset (dict).
• sel - Selector (dict).

Selector is a dictionary where each key is a dimension name and value is a mask to apply along the dimension or a list of indexes.

Returns None.

write

ds.write(filename, d)

Write dataset to a file. The file type is determined from the file extension.

Arguments:

• filename - Filename (str).
• d - Dataset (dict).

Supported formats:

• NetCDF4 (.nc, .nc4, .netcdf)
• JSON (.json)

Returns None.