naught101

def lat_lon_hex_mesh(bounds, d=3):
    """Creates a hexagonal lat/lon mesh within bounds that has a radial separation of d"""

    lone, lonw, lats, latn = bounds

    # heigt of equilatral triangle from radial distance sqrt(r^2 - (r/2)^2)
    h = np.sqrt(0.75) * d
    w = d / 2

    lat_vals = np.arange(lats, latn, h)

naught101

$if($and($eq(%compilation%,1), $eq(%albumartist%,Various Artists)),
    $set(albumartist, $if2(%compiler%, %djmixer%, %label%)))
    $set(albumartistsort, $if2(%compiler%, %djmixer%, %label%))))

naught101

'''
Non-parametric computation of entropy and mutual-information

Adapted by G Varoquaux for code created by R Brette, itself
from several papers (see in the code).

These computations rely on nearest-neighbor statistics
'''
import numpy as np

naught101

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Scikit-Learn Model-by-Cluster wrapper.

Original code by jnorthman: https://gist.github.com/jnothman/566ebde618ec18f2bea6
"""

import numpy as np

naught101

%% AMS pandoc template.
%% https://gist.github.com/naught101/f369e9796c36965b0cf6
%% Converts pandoc to a latex file along the lines of the templates from
%% https://www2.ametsoc.org/ams/index.cfm/publications/authors/journal-and-bams-authors/author-resources/latex-author-info/preparing-a-latex-manuscript-for-submission/
%% The results of this template should work with ametsoc.cls and ametsoc2014.bst
%% out of the box.


%% amssamp1.tex is nearly identical to amssamp2.tex, except
%% that amssamp2.tex uses the [twocol] option to produce

naught101

# -*- coding: utf-8 -*-
"""
Created on Wed Aug 26 12:12:37 2015

@author: naught101
"""

import numpy as np
import matplotlib.pyplot as pl

naught101

# -*- coding: utf-8 -*-
"""
Created on Mon Aug 17 10:53:51 2015

Population projections with low-discrepancy sequence based colour scheme.
http://www.storytellingwithdata.com/blog/2015/8/3/visualization-challenge-world-population-forecast

@author: naught101
"""

naught101

"""
Benchmarking the methods at
http://stackoverflow.com/questions/5284646/rank-items-in-an-array-using-python-numpy
"""

import timeit
from scipy.stats import rankdata
import pandas as pd
import numpy as np

naught101

#!/usr/bin/env python3

import poppler
import sys
import urllib.request, urllib.parse, urllib.error
import os

def main():
  input_filename = sys.argv[1]
    # http://blog.hartwork.org/?p=612

naught101

*-blx.bib
*.acn
*.acr
*.alg
*.aux
*.bbl
*.bcf
*.blg
*.dvi
*.fdb_latexmk