import numpy as np
import pylab as pl

# you can, but don't have to declare the type 
dave = 5 
print dave, type(dave)

# dynamically updated -- good/bad
dave = 5.
print dave, type(dave)

dave = "David Lagattuta"
print dave, type(dave)

# a few string examples
print "split example:", dave.split()
print "join example:", '__'.join(dave.split())

# Bracket-types tell you about the "thing" it's storing
dave = [2.3, 4.5, 6.9]
print dave, type(dave)

dave = [2.3, 4.5, 6.9, "hey there", 4]
print dave, type(dave)

dave = [2.3, 4.5, 6.9, "hey there", [2.1, 7.8], ]
print dave, type(dave)

eight_int = 8
five_int = 5
print "8/5 =", eight_int / five_int # Integer division

five_float = 5.0
print "8/5.0 =", eight_int / five_float # changes everything

blank_list = [] # how to create a blank list

#add list comprehensions
dave = [x**2 for x in xrange(5)]

print dave, type(dave)

from math import pi

print [str(round(pi, i)) for i in xrange(2, 9)]

# Unnecessarily complicated example to show off.
print [(i, str(round(pi, i)), round(pi, i)) for i in xrange(2, 9)]

tuple_example = ('Jonathan', 'Whitmore', 30, 'AR_building_rocks@wow.com')
print tuple_example
print type(tuple_example)
first_name, last_name, age, email = tuple_example

print last_name, first_name
print age
print email

list_comp_example = [i**2 for i in xrange(10)]
print list_comp_example

print sum([i**2 for i in xrange(10)])

# Generator version!
print sum(i**2 for i in xrange(10))

# TODO  numpy

# http://stackoverflow.com/questions/3394835/args-and-kwargs
def print_everything(*args):
    for count, thing in enumerate(args):
        print '{0}. {1}'.format(count, thing)
print_everything('apple', 'banana', 'cabbage')

# Similarly, **kwargs allows you to handle named arguments that you have not defined in advance:

def table_things(title_string, **kwargs):
    print title_string
    print "-" * len(title_string)
    for name, value in kwargs.items():
        print '{0} = {1}'.format(name, value)
    
table_things("Classifying stuff", apple = 'fruit', cabbage = 'vegetable')

dave = "Hi there people! "
print dave.startswith("hi  ")
print dave.splitlines()
print dave.strip()
jw = dave.split()
[x for x in jw if x.startswith('p')]

# You can import modules/subpackages as whatever name you want to call them.
from scipy import ndimage as dave_sucks

print numpy.arange(12)

print numpy.arange(12) ** 2

print type(np.arange(12))

# python
x = range(10000)
%timeit [item + 1 for item in x]

# numpy
x = np.arange(10000)
%timeit x + 1

print "x      -> ", x  # notice the smart printing
print "x[:]   -> ", x[:]
print "x[0]   -> ", x[0] # first element 
print "x[0:5] -> ", x[0:5] # first 5 elements
print "x[-1]  -> ", x[-1] # last element

# A bit more complicated slicing
print x[-5:] # last five elements
print x[-5:-2] # 
print x[-5:-1] # last 4 elements (not final value)

# create evenly spaced arrays
print np.arange(5, 50, step=3, )
print np.linspace(5, 50, num=3, endpoint=True, )
print np.linspace(5, 50, num=3, endpoint=False, )

np.array([[x, x**2, x/2.0] for x in range(10)]) + 5

input_data = np.random.random(50) * 2 * np.pi
response_data = np.sin(input_data)

pl.plot(input_data, response_data)

pl.scatter(input_data, response_data)

index_order = input_data.argsort()
index_order

pl.plot(input_data[index_order], response_data[index_order])











# TODO: Explain this in some detail



import cPickle as pickle
test = np.arange(1e7)

# This should take a bit
with open('myjunkfile', 'w') as filehandle:
    pickle.dump(test, filehandle)

with open('myjunkfile2','wb') as filehandle:
    pickle.dump(test, filehandle, protocol=-1)

with open('myjunkfile2', 'rb') as filehandle:
    new_variable = pickle.load(test)
    

mygenerator = (x**2 for x in range(3))

for item in mygenerator:
    print item

for item in mygenerator:
    print item
    # Can't reuse w/o reloading them!

# some from: http://stackoverflow.com/questions/101268/hidden-features-of-python?lq=1# <headingcell level=3># Chaining comparison operators
x = 5
print 1 < x < 10
print 10 < x < 20
print 10 > x <= 9
print 5 == x > 4

### Index slicing ###
a = np.arange(12)
a[::2]
# reverse
a[::-1]

for x in reversed(a):
    print x
    

print a[:]
print a[0:]
print a[-1]
print a[-2]
print a[1:-2]

a = 10
b = 5
print a, b
a, b = b, a
print a, b


x = 5
#y = 5
y = 1
x = 3 if (y == 1) else 2
print x

# VECTORIZE
def test(a,b):
    if a>b:
        return a
    else:
        return b

print test(10,-3)
print test(-5,-3)



#x = np.array(r_[-10:10:2])
x = np.arange(-10,10.1,2)
y = np.ones(x.shape)*-3.

print test(x,y) # error

#long way
out = np.empty(x.shape)
for i in range(x.size):
    out[i] = test(x[i],y[i])
print out

#short way
vtest = np.vectorize(test)
print vtest(x,3)

out = vtest(x,y)
print out

import itertools
def coolguys(name):
    if (name == 'David')|(name=='Spider Man'):
        return 'cool'
    else:
        return 'lame'

guys = np.array(['David','Jonathan', 'Fred','Bob','Steve','Spider Man'])

vcool = vectorize(coolguys)  #vectorize the function, for simplicity
results = vcool(guys)

for guy, result in itertools.izip(guys, results):
    print guy, "is", result

coolness = {'name':guys, 'status':results} #turn the results into a dictionary

# save dictionary to a pickle for later use
with open('whoiscool','w') as ff:
    pickle.dump(coolness,ff)

with open('whoiscool') as fnew: 
    data = pickle.load(fnew)
    
    
print data # Notice this is the data structure as saved!