kaedonkers

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

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

kaedonkers

## 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

kaedonkers

kaedonkers

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")

kaedonkers

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)

kaedonkers

#!/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

kaedonkers

# (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

kaedonkers

kaedonkers

import iris
import copy

# Main rename_cubelist() function
def rename_cubelist(cubelist, cubenames=None, new_coordnames=None, dryrun=False, verbose=True):
    '''Rename cubes and coordinates in place where necessary'''
    
    if cubenames==None:
        cubenames = [cube.name() for cube in cubelist]
        

kaedonkers

# Courtesy of @tam203

conda create --name my-new-env -y
conda activate my-new-env

# Install ipykernel to use environment with Jupytr Lab. 
# Add any other packages here (or you can install more later).
conda install ipykernel -y 

# Install the kernel to make it avaliable to Jupyter Lab