All Questions

I have a function apply_dask_function() that I use to apply the function dask_function() on a xarray dataset (ds_example). dask_function() takes 3 inputs, which are two 1D arrays (length "time&...

I am developing a relatively large model using xarray and therefore want to make use of chunks. Most of my operations run a lot faster when chunked but there is one that keeps running (a lot) slower ...

Hello I am trying to sort the data inside some netCDF4 (.nc) files into bins as efficiently as possible. I am currently trying this with xarray and NumPy's digitize function. Since I want to process a ...

I'm trying to use dask to conduct larger-than-memory processing in xarray. Concretely, I'm trying to: Concatenate several NetCDF files (on the same geo grid, same variables) by time Regrid them to a ...

I have a 3D xarray DataArray that I've saved to to zarr using DataArray.to_zarr(). However, the resulting format is not readable by my tools, in this case napari. The structure of the zarr has one ...

# Template xarray based on Earth Engine import numpy as np import pandas as pd import dask import xarray as xr # Define the dimensions time = pd.date_range("2020-12-29T18:57:32.281000", ...

I am trying to create a python function that opens a remote dataset (in a opendap server) using xarray and automatically creates new variables lazily. A use case would be to calculate magnitude and ...

I am trying to do a simple calculation on a very large netcdf file, and am struggling to speed it up -- probably because I program primarily in julia and R. I think xarray/dask are the best approach ...

I'm using xarray.open_mfdataset() to open tens of thousands of (fairly small) netCDF files, and it's taking quite some time. Being of an impatient nature, I would like to at least be assured that ...

I have just started using 'dask', and I am running into some memory issues. I would like to share my problem along with a dummy code snippet that illustrates what I’ve done. My goal is to read a large ...

I'm currently doing an internship where I need to create large datasets, often hundreds of GB in size. I'm collecting temporal samples for cartography, where I collect 500 samples for each ...

I am trying to cloud access MODIS LST data through stackstac (code below). But, for my selected date range, in the output ds, I get lets say 5-6 different tiles (covering the entire bbox), which are ...

Currently, I am using ERA5-land data to calculate wind related variables. While I am able to calculate what I want, I do struggle with an efficient implementation to lift this heavy data in a feasible ...

I am running a function in a Dask cluster to compute the normalized difference between two of my data variables in my xarray Dataset object. However, I need this to be in a Dask DataFrame format first ...

I am using climate data from the Levante Supercomputer in a JupyterNotebook, but I am having some problems regarding the computational time. Therefore, I was wondering if someone had some knowledge of ...