advances in computing will benefit weather forecasts

news about advances in computing abilities is always exciting news fore weather forecasters. Check out this article...

http://www.engadget.com/2014/08/07/ibm-synapse-supercomputing-chip-mimics-human-brain/?ncid=txtlnkusaolp00000618

Relative Maximun and MInimum

It's easy to find the max and min of an array, but sometimes you want to find all local max an mins.

From post here:

import numpy as np
from scipy.signal import argrelextrema

x = np.random.random(12)

# for local maxima
argrelextrema(x, np.greater)

# for local minima
argrelextrema(x, np.less)

Produces
>>> x
array([ 0.56660112,  0.76309473,  0.69597908,  0.38260156,  0.24346445,
    0.56021785,  0.24109326,  0.41884061,  0.35461957,  0.54398472,
    0.59572658,  0.92377974])
>>> argrelextrema(x, np.greater)
(array([1, 5, 7]),)
>>> argrelextrema(x, np.less)
(array([4, 6, 8]),)

Note, these are the indices of x that are local max/min. To get the values, try:
>>> x[argrelextrema(x, np.greater)[0]]

change tick mark size

http://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.tick_params
Example
# Create Figure
fig = plt.figure(1)
ax = fig.add_subplot(111)
#increase size of tick marks
ax.tick_params('both', length=20, width=2, which='major')
ax.tick_params('both', length=10, width=1, which='minor')

Python Accessing all the files in a directory

This is a handy link that gets file names from a directory:
http://stackoverflow.com/questions/18262293/python-open-every-file-in-a-folder

For example: 
path = 'C://Users/person/Pictures' for filename in glob.glob(os.path.join(path,'*.jpg')):

     print filename

results in:

C:\Users\Brian\Pictures\East.jpg
C:\Users\Brian\Pictures\North.jpg
C:\Users\Brian\Pictures\Rocketeer.jpg
C:\Users\Brian\Pictures\South.jpg
C:\Users\Brian\Pictures\WIN_20140711_105811_edited.jpg

etc.

Easy Legend

The easiest way to make a legend is to give the plot a label when you first make the plot.
Example:

plt.plot(times_utc,duchesne, label="Duchesne")
plt.plot(times_utc,mtn_home, label="Mountain Home")
plt.plot(times_utc,horsepool, label="Horsepool")

plt.legend(loc=2)