dask

This is a suggestion to simplify reporting the dask version in the issue template by providing a suggested code snippet to run (in the Environment section of the issue template):

import dask; print("- Dask version:", dask.__version__)
import sys; print("- Python version:", sys.version)

The use of an mr parameter in inplace_bitmask_and, which calls inplace_bitmask_binop, is a little misleading. The allocations there are always temporary and are not part of the return value. It is only used for a few temporary arrays/scalars: https://github.com/rapidsai/cudf/blob/1f8a03e69704562dfac38de40b7172650280c6ea/cpp/include/cudf/detail/null_mask.cuh#L169-L171

It should be possible

Is your feature request related to a problem? Please describe.
Implements classification_report for classification metrics.(https://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html)

The stumpy.snippets feature is now completed in #283 which follows this work:

• The original published paper
• The supporting website with data examples

We have a rough notebook t

Currently users call client.wait to wait for a certain number of workers.

Currently a common pattern is:

cluster.scale(100)
client.wait_for_workers(100)

Cluster managers (like Coiled) would like to include custom handling to give users nice information about what's happening (including especially failures) while waiting for workers. At the moment, this isn't possible.

Prop

Feature Request

Is your feature request related to a problem? Please describe.

Whenever I report a bug, I need to confirm what satpy version I am using. This is of course important, but it's also an extra step that could be semi-automated.

Describe the solution you'd like

I would like that debug_on() prints the relevant versions. When we report bugs, we anyway call `debu

Is your feature request related to a problem? Please describe.
Look at here

If taking just one row with our sorting, we may use GROUP BY and FIRST to solve this problem, it can be a lot faster. Let's add this special handling.

Code Sample, a minimal, complete, and verifiable piece of code

from pyresample.boundary import Boundary
b = Boundary(my_lons, my_lats)
print(b.contour_poly.area())

Problem description

The above code doesn't fail if the provided lons/lats are 2D (not sure on 3D+), but the class and all functions/utilities underneath it assume 1D arrays. The end results are incor

Based on the discussion in dask-contrib/dask-sql#508 (review) we should add the argument for the rust version in our gpuci scrips.

from dask_jobqueue import SLURMCluster 
cluster = SLURMCluster(cores=1, memory='1GB') 
print(cluster.job_script()) 

#!/usr/bin/env bash

#SBATCH -J dask-worker
#SBATCH -n 1
#SBATCH --cpus-per-task=1
#SBATCH --mem=954M
#SBATCH -t 00:30:00

/home/lesteve/miniconda3/bin/python -m distributed.cli.dask_worker tcp://192.168.0.11:44065 --nthreads 1 --memory-limit 1000.00MB -

Problem description

Reading a dataset with eager's read functionality raises a ValueError when providing columns.

Example code (ideally copy-pastable)

import pandas as pd

from tempfile import TemporaryDirectory
from functools import partial
from storefact import get_store_from_url

from kartothek.io.eager import store_dataframes_as_dataset, read_dataset_as_data

Example for numerical weather prediction

to be added to initialised datasets

Data sources (to) implement(ed):

• GEFS https://www.ncei.noaa.gov/thredds/catalog/model-gefs-003/202008/20200831/catalog.html
• DWD https://opendata.dwd.de/weather/nwp/

relates to #600

Without thinking I put resampling="bilinear" and got an error when I called .compute()

Traceback (most recent call last):
  File "carajas.py", line 92, in <module>
    band_medianNP = band_median.compute()
  File "/home/ubuntu/anaconda3/envs/richard/lib/python3.8/site-packages/xarray/core/dataarray.py", line 899, in compute
    return new.load(**kwargs)
  File "/home/ubuntu/anaco

https://forum.image.sc/t/imsave-tifffile-imwrite-returns-tiff-files-of-wrong-shape-in-imagej-cellprofiler/65332/9?u=jacksonmaxfield

The dim_order parameter should be used as the parameter to aicsimageio.transforms.reshape_data with TCZYX as the return order (optional S)

As per @krfricke, we should create a single RayCommunication actor class that holds both an asyncio Queue and asyncio Event. This way we only need one remote actor for all communication between training workers and the driver, and we don't have to be dependent on ray.util.Queue