Nearest Neighbor methods used for 2-dimensional interpolation. These methods
include two methods of neighbor selection and two methods of weighting. To
access any of the functionality, use the Nearest Neighbor Averaging (NNA
)
class.
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#!/bin/bash | |
def_yes=n | |
while getopts ":hy" opt; do | |
case ${opt} in | |
h ) # process option h | |
PRINT_HELP=y | |
;; | |
y ) # process option y | |
def_yes=y | |
;; |
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import matplotlib.pyplot as plt | |
import matplotlib.colors as mc | |
import numpy as np | |
pmedges = np.asarray([0.0, 12.1, 35.5, 55.5, 150.5, 250.5, 500.5]) | |
o8edges = np.asarray([0.0, 55, 71, 86, 106, 201, 500.]) | |
o1edges = np.asarray([0.0, 60, 125,165,205, 405, 604.]) | |
aqicolors = ['#00e400', '#ffff00', '#ff7e00', '#ff0000', '#8f3f97', '#7e0023'] | |
colors = ['grey'] + aqicolors + ['k'] |
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__all__ = ['usstdatmdf', 'usstdatmds', 'M0', 'R', 'Rs', 'g', '__version__'] | |
__version__ = '0.1.0' | |
__doc__ = """ | |
This GIST implements the US Standard Atmosphere for Temperature, Pressure, | |
and Density. The constants and equations are implemented according to the U.S. | |
Standard Atmosphere (1976) and are only implemented through 84km. The results | |
can be presented as a Pandas DataFrame or an xarray Dataset. | |
Requirements |
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__all__ = ['open_modis'] | |
__version__ = '0.1.0' | |
def parse_hdfeos_metadata(string): | |
""" | |
Borrowed from ARSET training materials | |
""" | |
out = dict() | |
lines = [i.replace('\t','') for i in string.split('\n')] |
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__all__ = ['URSSession', 'asdc_downloader'] | |
class URSSession: | |
""" | |
Class to store URS credentials: | |
* for use with requests | |
* for use with netrc and dodsrc | |
""" |
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