jfburkhart

def closest(val, vallist, index=True):
    """ returns the closest value or index to a date in a list

    ===========         ======================
    keyword             description
    -----------         ----------------------
    index               [True] returns index
    ===========         ======================

    """

jfburkhart

In [62]: empty = xr.DataArray(zed, dims=['ageclass', 'pointspec', 'time', 'latitude', 'longitude'], coords={'time':taxis, 'latitude': dset.l
    ...: atitude, 'longitude':dset.longitude})

In [63]: empty
Out[63]: 
<xarray.DataArray (ageclass: 1, pointspec: 1, time: 2557, latitude: 360, longitude: 720)>
array([[[[[ 0., ...,  0.],
          ..., 
          [ 0., ...,  0.]],

jfburkhart

         Starting Load Kernel Modules...
         Starting Load/Save RF Kill Switch Status...
[FAILED] Failed to start Load Kernel Modules.
See 'systemctl status systemd-modules-load.service' for details.
[  OK  ] Started File System Check Daemon to report status.
         Starting Load Kernel Modules...
[FAILED] Failed to start Load Kernel Modules.
See 'systemctl status systemd-modules-load.service' for details.
[  OK  ] Reached target Sound Card.
         Starting Load Kernel Modules...

jfburkhart

Trying to merge / combine to xray.Datasets:

In [161]: o1 = xray.Dataset({'x':(('t'), (np.ones(10)))}, coords={'t':np.arange(10)})

In [162]: o2 = xray.Dataset({'x':(('t'), (np.ones(10) * 2))}, coords={'t':np.arange(5,15)})

In [163]: o1
Out[163]: 
<xray.Dataset>
Dimensions:  (t: 10)

jfburkhart

In [15]: em1
Out[15]:
<xray.Dataset>
Dimensions:    (lat: 720, lon: 1440, time: 4)
Coordinates:
  * lat        (lat) float32 89.875 89.625 89.375 89.125 88.875 88.625 ...
  * lon        (lon) float32 -179.875 -179.625 -179.375 -179.125 -178.875 ...
  * time       (time) datetime64[ns] 2004-08-01 2004-08-02 2004-08-03 2004-08-04
Data variables:
    emissions  (time, lat, lon) float64 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...

jfburkhart

class Structure(dict, object):
    """ A ditionary that acts like a matlab structure.

    """
    def __getattr__(self, attr):
        # Fake a __getstate__ method that returns None
        if attr == "__getstate__":
            return lambda: None
        try:

jfburkhart

#!/usr/bin/env python

"""


jfb, 2010.10.20
"""
from copy import copy
import shutil
import datetime as dt

jfburkhart

"""
Series of data are loaded from a .csv file, and their names are
displayed in a checkable list view. The user can select the series
it wants from the list and plot them on a matplotlib canvas.

Use the sample .csv file that comes with the script for an example
of data series.

Eli Bendersky (eliben@gmail.com)
License: this code is in the public domain

jfburkhart

def remove_dups(x, y, z):
    """
    ## for regridding need to remove any duplicates
    ## First make sure there is enough data
    """
    if len(z) > 10:
        vals = zip(x, y, z)
        vals.sort()
        z0 = zip(x, y)