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# Installing environment as ipykernel:
export ENV_NAME=feature_name
pixi add --feature $ENV_NAME ipykernel
pixi run -e $ENV_NAME python -m ipykernel install --user --name pixi_$ENV_NAME --display-name "$ENV_NAME (pixi)"

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API_KEY=`cat ~/path/to/apikey_file` && export API_KEY

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# First time cloning repo
git clone --branch <branch-name> <url|ssh>

# If already cloned
git fetch
git switch <branch-name>

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## Install conda environment as Jupyter kernel using ipykernel

source activate {env_name}
conda install ipykernel -y -q
ipython kernel install --user --name $CONDA_DEFAULT_ENV

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import numpy
import xarray
import pandas

fname = "data.npy"
arr = numpy.load(fname)
df = pandas.DataFrame({"lon":arr[:,0], "lat":arr[:,1], "data":arr[:,3]})
ds = df.set_index(["lat","lon"]).to_xarray()
ds.to_netcdf("data.nc")

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import numpy as np

def reverse_piecewise_linear_sigmoid(self, x, upper, lower):
    '''
    Reverse piecewise linear sigmoid function to filter a value between two thresholds in a vectorised manner according to:
    
    if x <= lower:
        y = 1
    else:
        y = (upper-x)/(upper-lower)

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#!/path/to/miniconda3/bin python3
'''
A commandline tool to install all available conda environments as ipython kernels
- Checks for which conda envs and ipython kernels are available
- Installs the conda envs not yet installed as ipython kernels (including ipykernel if missing)
- Uninstalls ipython kernels which no longer have a corresponding conda env
'''

import jupyter_client
import subprocess

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# (C) Crown Copyright, Met Office. All rights reserved. 2020
#
# Python code written for demonstrative purposes only.
# Authored by Kevin Donkers (@kaedonkers) and Peter Killick (@DPeterK)
# See https://gist.github.com/DPeterK/c5061f336a91a3ce9790c206a5459b4a

import iris
import numpy as np
import cartopy.crs as ccrs

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