xarray-dataclasses

xarray data creation by data classes

Overview

xarray-dataclasses is a Python package that makes it easy to create xarray's DataArray and Dataset objects that are "typed" (i.e. fixed dimensions, data type, coordinates, attributes, and name) using the Python's dataclass:

```python from dataclasses import dataclass from typing import Literal from xarray_dataclasses import AsDataArray, Coord, Data

X = Literal["x"] Y = Literal["y"]

@dataclass class Image(AsDataArray): """2D image as DataArray."""

data: Data[tuple[X, Y], float]
x: Coord[X, int] = 0
y: Coord[Y, int] = 0

```

Features

• Typed DataArray or Dataset objects can easily be created: python image = Image.new([[0, 1], [2, 3]], [0, 1], [0, 1])
• NumPy-like filled-data creation is also available: python image = Image.zeros([2, 2], x=[0, 1], y=[0, 1])
• Support for features by the Python's dataclass.
• Support for static type check by Pyright.

Installation

shell pip install xarray-dataclasses

Basic usage

xarray-dataclasses uses the Python's dataclass. Data (or data variables), coordinates, attributes, and a name of DataArray or Dataset objects will be defined as dataclass fields by special type hints (Data, Coord, Attr, Name), respectively. Note that the following code is supposed in the examples below.

```python from dataclasses import dataclass from typing import Literal from xarraydataclasses import AsDataArray, AsDataset from xarraydataclasses import Attr, Coord, Data, Name

X = Literal["x"] Y = Literal["y"] ```

Data field

Data field is a field whose value will become the data of a DataArray object or a data variable of a Dataset object. The type hint Data[TDims, TDtype] fixes the dimensions and the data type of the object. Here are some examples of how to specify them.

Type hint | Inferred dimensions --- | --- Data[tuple[()], ...] | () Data[Literal["x"], ...] | ("x",) Data[tuple[Literal["x"]], ...] | ("x",) Data[tuple[Literal["x"], Literal["y"]], ...] | ("x", "y")

Type hint | Inferred data type --- | --- Data[..., Any] | None Data[..., None] | None Data[..., float] | numpy.dtype("float64") Data[..., numpy.float128] | numpy.dtype("float128") Data[..., Literal["datetime64[ns]"]] | numpy.dtype("<M8[ns]")

Coordinate field

Coordinate field is a field whose value will become a coordinate of a DataArray or a Dataset object. The type hint Coord[TDims, TDtype] fixes the dimensions and the data type of the object.

Attribute field

Attribute field is a field whose value will become an attribute of a DataArray or a Dataset object. The type hint Attr[TAttr] specifies the type of the value, which is used only for static type check.

Name field

Name field is a field whose value will become the name of a DataArray object. The type hint Name[TName] specifies the type of the value, which is used only for static type check.

DataArray class

DataArray class is a dataclass that defines typed DataArray specifications. Exactly one data field is allowed in a DataArray class. The second and subsequent data fields are just ignored in DataArray creation.

```python @dataclass class Image(AsDataArray): """2D image as DataArray."""

data: Data[tuple[X, Y], float]
x: Coord[X, int] = 0
y: Coord[Y, int] = 0
units: Attr[str] = "cd / m^2"
name: Name[str] = "luminance"

```

A DataArray object will be created by a class method new():

```python Image.new([[0, 1], [2, 3]], x=[0, 1], y=[0, 1])

array([[0., 1.], [2., 3.]]) Coordinates: * x (x) int64 0 1 * y (y) int64 0 1 Attributes: units: cd / m^2 ```

NumPy-like class methods (zeros(), ones(), ...) are also available:

```python Image.ones((3, 3))

array([[1., 1., 1.], [1., 1., 1.], [1., 1., 1.]]) Coordinates: * x (x) int64 0 0 0 * y (y) int64 0 0 0 Attributes: units: cd / m^2 ```

Dataset class

Dataset class is a dataclass that defines typed Dataset specifications. Multiple data fields are allowed to define the data variables of the object.

```python @dataclass class ColorImage(AsDataset): """2D color image as Dataset."""

red: Data[tuple[X, Y], float]
green: Data[tuple[X, Y], float]
blue: Data[tuple[X, Y], float]
x: Coord[X, int] = 0
y: Coord[Y, int] = 0
units: Attr[str] = "cd / m^2"

```

A Dataset object will be created by a class method new():

```python ColorImage.new( [[0, 0], [0, 0]], # red [[1, 1], [1, 1]], # green [[2, 2], [2, 2]], # blue )

Dimensions: (x: 2, y: 2) Coordinates: * x (x) int64 0 0 * y (y) int64 0 0 Data variables: red (x, y) float64 0.0 0.0 0.0 0.0 green (x, y) float64 1.0 1.0 1.0 1.0 blue (x, y) float64 2.0 2.0 2.0 2.0 Attributes: units: cd / m^2 ```

Advanced usage

Coordof and Dataof type hints

xarray-dataclasses provides advanced type hints, Coordof and Dataof. Unlike Data and Coord, they specify a dataclass that defines a DataArray class. This is useful when users want to add metadata to dimensions for plotting. For example:

```python from xarray_dataclasses import Coordof

@dataclass class XAxis: data: Data[X, int] long_name: Attr[str] = "x axis" units: Attr[str] = "pixel"

@dataclass class YAxis: data: Data[Y, int] long_name: Attr[str] = "y axis" units: Attr[str] = "pixel"

@dataclass class Image(AsDataArray): """2D image as DataArray."""

data: Data[tuple[X, Y], float]
x: Coordof[XAxis] = 0
y: Coordof[YAxis] = 0

```

General data variable names in Dataset creation

Due to the limitation of Python's parameter names, it is not possible to define data variable names that contain white spaces, for example. In such cases, please define DataArray classes of each data variable so that they have name fields and specify them by Dataof in a Dataset class. Then the values of the name fields will be used as data variable names. For example:

```python @dataclass class Red: data: Data[tuple[X, Y], float] name: Name[str] = "Red image"

@dataclass class Green: data: Data[tuple[X, Y], float] name: Name[str] = "Green image"

@dataclass class Blue: data: Data[tuple[X, Y], float] name: Name[str] = "Blue image"

@dataclass class ColorImage(AsDataset): """2D color image as Dataset."""

red: Dataof[Red]
green: Dataof[Green]
blue: Dataof[Blue]

```

```python ColorImage.new( [[0, 0], [0, 0]], [[1, 1], [1, 1]], [[2, 2], [2, 2]], )

Dimensions: (x: 2, y: 2) Dimensions without coordinates: x, y Data variables: Red image (x, y) float64 0.0 0.0 0.0 0.0 Green image (x, y) float64 1.0 1.0 1.0 1.0 Blue image (x, y) float64 2.0 2.0 2.0 2.0 ```

Customization of DataArray or Dataset creation

For customization, users can add a special class attribute, __dataoptions__, to a DataArray or Dataset class. A custom factory for DataArray or Dataset creation is only supported in the current implementation.

```python import xarray as xr from xarray_dataclasses import DataOptions

class Custom(xr.DataArray): """Custom DataArray."""

__slots__ = ()

def custom_method(self) -> bool:
    """Custom method."""
    return True

@dataclass class Image(AsDataArray): """2D image as DataArray."""

data: Data[tuple[X, Y], float]
x: Coord[X, int] = 0
y: Coord[Y, int] = 0

__dataoptions__ = DataOptions(Custom)

image = Image.ones([3, 3]) isinstance(image, Custom) # True image.custom_method() # True ```

DataArray and Dataset creation without shorthands

xarray-dataclasses provides functions, asdataarray and asdataset. This is useful when users do not want to inherit the mix-in class (AsDataArray or AsDataset) in a DataArray or Dataset dataclass. For example:

```python from xarray_dataclasses import asdataarray

@dataclass class Image: """2D image as DataArray."""

data: Data[tuple[X, Y], float]
x: Coord[X, int] = 0
y: Coord[Y, int] = 0

image = asdataarray(Image([[0, 1], [2, 3]], [0, 1], [0, 1])) ```