Arthur Mwai bolshoibooze

The issue:

..mobile browsers will wait approximately 300ms from the time that you tap the button to fire the click event. The reason for this is that the browser is waiting to see if you are actually performing a double tap.

(from a new defunct https://developers.google.com/mobile/articles/fast_buttons article)

touch-action CSS property can be used to disable this behaviour.

touch-action: manipulation The user agent may consider touches that begin on the element only for the purposes of scrolling and continuous zooming. Any additional behaviors supported by auto are out of scope for this specification.

from scipy.spatial import Delaunay
import networkx as nx
 
points = [ [0,0],[0,50],[50,50],[50,0],[0,400],[0,450],[50,400],[50,450],[700,300],[700,350],[750,300],[750,350],
          [900,600],[950,650],[950,600],[900,650]
]
def concave(points,alpha_x=150,alpha_y=250):
  points = [(i[0],i[1]) if type(i) <> tuple else i for i in points]
  de = Delaunay(points)

if you are using linux, unix, os x:

pip install -U setuptools
pip install -U pip

pip install numpy
pip install scipy
pip install matplotlib
#pip install PySide


	Bits and pieces i collected while trying to install scipy,numpy and pandas on a VPS (digitalocean):

	Scipy has some funny dependencies: http://www.netlib.org/lapack/ and http://www.netlib.org/blas/, so if you want to avoid
	the hassle of building BLAS and LAPACK, install linear algebra libraries from repository (for Ubuntu/debian).
	# credits:: <http://stackoverflow.com/questions/7496547/does-python-scipy-need-blas>


	sudo apt-get install gfortran libopenblas-dev liblapack-dev

	"""quick way to create a data frame to try things out"""
	df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd'])

	df['A'] """ will bring out a col """ df.ix[0] """will bring out a row, #0 in this case"""

	"""to get an array from a data frame or a series use values, note it is not a function here, so no parans ()"""
	point = df_allpoints[df_allpoints['names'] == given_point] # extract one point row.
	point = point['desc'].values[0] # get its descriptor in array form.

	"""Information Retrieval metrics

	Useful Resources:
	http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
	http://www.nii.ac.jp/TechReports/05-014E.pdf
	http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
	http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
	Learning to Rank for Information Retrieval (Tie-Yan Liu)
	"""
	import numpy as np

	#List unique values in a DataFrame column
	pd.unique(df.column_name.ravel())

	#Convert Series datatype to numeric, getting rid of any non-numeric values
	df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

	#Grab DataFrame rows where column has certain values
	valuelist = ['value1', 'value2', 'value3']
	df = df[df.column.isin(value_list)]

	import urllib2

	"""
	#Usage:
	in a python shell
	>> import get_pepperstone_data
	>> get_pepperstone_data.run()

	# Notes:
	1: Selection of pairs is highly opinionated

	#One of those handy scripts, see:http://djangotricks.blogspot.co.ke/2013/12/how-to-export-data-as-excel.html


	from .models import *
	from django.http import *

	"""
	# Quick 'how-to' guide
	# model in question
	class Duplicate(models.Model):

	//simple_list_item_1
	<TextView xmlns:android="http://schemas.android.com/apk/res/android"
	android:id="@android:id/text1"
	style="?android:attr/listItemFirstLineStyle"
	android:paddingTop="2dip"
	android:paddingBottom="3dip"
	android:layout_width="fill_parent"
	android:layout_height="wrap_content" />

	//simple_list_item_2