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# For overlaying two colorbars on the same figure
plt.rcParams['hatch.color'] = (1, 1, 1, .33)
plt.rcParams['hatch.linewidth'] = 8
plt.bar([1,2], [2,5], color='.1', label='first')
plt.bar([1,2], [3,4], hatch='/', alpha=.33, color='g', label='second')

plt.legend()

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#==========================================================================
## Simple method, just deal with the '~' notation for home
#==========================================================================
import os
FILE = "~/path/to/file.data"
FILE = FILE.replace('~', os.environ['HOME'])
#==========================================================================

#==========================================================================
## More involved, but deals with other environment variables

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def str_operator(left, operator_str, right):
    """
    Performs an operation when you have an operator as a string.

    An alternative method is to use the `eval()` function, if you aren't
    worried about the security vulnerabilities. 
    Example, `eval('a + b')` where a=5 and b=6 will result in 11.
    
    Parameters
    ----------

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def border(array, corner=0, direction='cw'):
    """
    Extract the values arround the border of a 2d array.
    
    Default settings start from top left corner and move clockwise. 
    Corners are only used once.
    
    Parameters
    ----------
    array : array_like

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from datetime import datetime
DATE = datetime(2019, 1, 1, 12, 35)
print(DATE)

# The most common way, with formatters
# https://docs.python.org/2/library/datetime.html#strftime-and-strptime-behavior

d1 = DATE.strftime('%Y %b %d, %H:%M')
print('The date and time is %s' % d1)

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def xr_infer_interval_breaks(coord, axis=0):
    """
    Code from xarray: (github/pydata/xarray/plot/utils)    
    Usage: if x is a 2d array of longitudes...
    x = _infer_interval_breaks(x, axis=1)
    x = _infer_interval_breaks(x, axis=0) # repeat for second axis
    """
    deltas = 0.5 * np.diff(coord, axis=axis)
    first = np.take(coord, [0], axis=axis) - np.take(deltas, [0], axis=axis)
    last = np.take(coord, [-1], axis=axis) + np.take(deltas, [-1], axis=axis)

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# Brian Blaylock
# Requres `s3fs`
# Website: https://s3fs.readthedocs.io/en/latest/
# In Anaconda, download via conda-forge.

import s3fs

# Use the anonymous credentials to access public data
fs = s3fs.S3FileSystem(anon=True)

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# For a .csv file where there are mixed data types (column of floats, column of strings i.e. Dates) 
# then if you set the encoding='UTF-8', the dates or column of strings will return as a string
# rather than a "bytes" type.

FILENAME = 'some_csv_file.csv'
data = np.genfromtxt(FILENAME, delimiter=',', names=True, dtype=None, encoding='UTF-8')

# Since names is set to True, the returned data can be accessed by header column name.
# If a column is labeled 'DATES', you can access the dates like you do a dictionary...
get_dates = data['DATES']

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import matplotlib

# Generate a list of colors
cmap = matplotlib.cm.get_cmap('Spectral')

# Retrieve 19 colors from the colormap
colors = cmap(np.arange(19)/19)

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# Print a progress bar for a loop completion

from time import sleep
F = range(10)
num = len(F)
for i in F:
  sleep(1)
  sys.stdout.write('\r%.1f%% Complete (%s of %s)' % (i/num*100, i, num))