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Get dim range

get_dim_range#

def get_dim_range(cube: xr.DataArray, dim: str) -> Union[Tuple[float, float], Tuple[str, str]]

Description#

Calculates and returns the minimum and maximum values of a specified dimension within an xarray.Dataset. This function supports dimensions with numerical or datetime data types, making it versatile for a range of data analysis contexts.

Parameters#

  • cube (xarray.DataArray): The input data cube from which the dimension range is to be calculated.
  • dim (str): The name of the dimension for which the range is to be determined.

Returns#

  • Union[Tuple[float, float], Tuple[str, str]]: The minimum and maximum values of the dimension. For datetime dimensions, these values are formatted as strings; for numerical dimensions, they are returned as numbers.

Example#

Here's how you might use the get_dim_range function to find the range of the 'time' dimension in a dataset: 

import numpy as np
import xarray as xr
from ml4xcube.utils import get_dim_range

# Create a sample DataArray with datetime and numerical data
times = np.array(['2020-01-01', '2020-01-02', '2020-01-03'], dtype='datetime64[D]')
data = np.random.rand(3, 2, 2)  # Random data for 3 days, 2 latitudes, and 2 longitudes
cube = xr.DataArray(data, dims=['time', 'latitude', 'longitude'], coords={'time': times})

# Get the range of the 'time' dimension
time_range = get_dim_range(cube, 'time')
print("Time Dimension Range:", time_range)
A simple xarray.DataArray with a 'time' dimension is created and get_dim_range is used to extract and print the date range.