aaronspring

brews

"""
Demo using cartopy.util.add_cyclic_point with an xarray Dataset to 
add a cyclic or wrap-around pixel to the `lon` dimension. This can be useful
for plotting with `cartopy` or regridding with `xesmf`.
"""

import xarray as xr
from cartopy.util import add_cyclic_point

rabernat

import xarray as xr

def detrend_dim(da, dim, deg=1):
    # detrend along a single dimension
    p = da.polyfit(dim=dim, deg=deg)
    fit = xr.polyval(dim, p.polyfit_coefficients)
    return da - fit

def detrend(da, dims, deg=1):
    # detrend along multiple dimensions

jthielen

from wrf import getvar
from netCDF4 import Dataset
import xarray as xr
import pyproj

# Extract the variables of interest at time index 17
ds = Dataset('../wrfout_d02_2015-07-12_1200.nc')
variables = [getvar(ds, var, 17) for var in ('z', 'dbz', 'pressure', 'ter', 'ua',
                                             'va', 'wa', 'temp', 'rh')]
data = xr.merge(variables)

johnhw

### JHW 2018
import numpy as np
import umap



# This code from the excellent module at:
# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module
    
import random

macoj

From here: https://ga7g08.github.io/2015/06/25/ipython-nbconvert-latex-template-to-hide-code/

1. Create a file named hidecode.tplx in the directory of your notebook with the following content:

((*- extends 'article.tplx' -*))

((* block input_group *))
    ((*- if cell.metadata.get('nbconvert', {}).get('show_code', False) -*))
        ((( super() )))
 ((*- endif -*))

mrocklin

mrocklin

shoyer

lukegre

def dataset_encoding(xds):
    cols = ['source', 'original_shape', 'dtype', 'zlib', 'complevel', 'chunksizes']
    info = pd.DataFrame(columns=cols, index=xds.data_vars)
    for row in info.index:
        var_encoding = xds[row].encoding
        for col in info.keys():
            info.ix[row, col] = var_encoding.pop(col, '')
    
    return info