I hereby claim:
- I am andersy005 on github.
- I am andersy005 (https://keybase.io/andersy005) on keybase.
- I have a public key ASA6MpC7M7i67D6zZeY9fWDj-1fF_lNTOwjBKhPFQ8Uefwo
To claim this, I am signing this object:
I hereby claim:
To claim this, I am signing this object:
#!/bin/bash | |
usage="$(basename "$0") [-h] [-s n] -- program to calculate the answer to life, the universe and everything | |
where: | |
-h show this help text | |
-s set the seed value (default: 42)" | |
seed=42 | |
while getopts ':hs:' option; do | |
case "$option" in |
name: dask-dev | |
channels: | |
- conda-forge | |
- defaults | |
dependencies: | |
- dask | |
- dask-ml | |
- numpy | |
- python=3.6 | |
- bokeh |
import pandas as pd | |
import dask.dataframe as dd | |
import numpy as np | |
import dask.array as da | |
import inspect | |
from numpydoc.docscrape import NumpyDocString | |
import pydoc | |
def maybe_build_signature(obj, name): |
import dask | |
import dask.array as da | |
import dask.dataframe as dd | |
import sparse | |
@dask.delayed(pure=True) | |
def corr_on_chunked(chunk1, chunk2, corr_thresh=0.9): | |
return sparse.COO.from_numpy((np.dot(chunk1, chunk2.T) > corr_thresh)) | |
def chunked_corr_sparse_dask(data, chunksize=5000, corr_thresh=0.9): |
#!/bin/bash | |
#PBS -N dask-scheduler | |
#PBS -q economy | |
#PBS -A NIOW0001 | |
#PBS -l select=1:ncpus=36:mpiprocs=6:ompthreads=6 | |
#PBS -l walltime=00:30:00 | |
#PBS -j oe | |
# module purge | |
module load gnu |
from __future__ import absolute_import, division, print_function | |
import numpy as np | |
import xarray as xr | |
#------------------------------------------------------------------------------- | |
#-- function | |
#------------------------------------------------------------------------------- | |
def weighted_rmsd(da_x,da_y,weights,avg_over_dims=[]): |
#! /usr/bin/env python | |
from __future__ import absolute_import, division, print_function | |
import xarray as xr | |
import numpy as np | |
import cftime | |
xr_open_ds = {'chunks' : {'time':1}, | |
'decode_coords' : False, | |
'decode_times' : False, | |
'data_vars' : 'minimal'} |