A short Python intro

# start Python (python -E, ipython --quick)
python -E  # don't load rc file for the time being

# use as a calculator
a = 3 + 4
2**4
_ + 5

a, b = 1, 2
a, b = b, a  # swap
a, b = c, d = 11, 22  

# check out Ctrl-p ! Type "2" and "Ctrl-p"

t = (33, 44)
type(t)

a, b = t  # unpack a tuple

2/3  # I don't like it and Guido also doesn't like it

# get rid of /-integer division: 

from __future__ import division

2/3, 2//3  # "real" vs integer division
exp(2)  # we will solve this problem later
        # to have mathematical functions (sum, sin, cos)

s = 'abc'
type(s)
s + 'def' 

dir()

s<Crtl-p>  # Crtl-p is the magic key to get back matching previous commands
           # TAB-completion will work in ipython (see below)

l = [1,2] + [3,4]  # a list of length 4
range(5)
for i in range(1, 10):  # caveat: doesn't print 10
    print(i)

for c in 'hello world': 
    print(c)

# dict data type: dictionary, look-up table, key-value-map, associative array, 
# (like a list container, but with freely chosen keys and no fixed order)
d = {}
d[1] = (2, 3)
d['2'] = 44
d[(3,4)] = 55  # keys must be immutable (tuples are)
d
d2 = d  # d and d2 now refer to the same object
d2 is d
d.copy()
d3 = d.copy()
d3 == d
d3 is d

# in the OS system shell (ctrl-z might work to get there):
echo "print('  ---printing in test.py---  ')" > test.py

# back in the Python shell: 
exec(open('test.py'))  # in ipython also: %run test.py or just run test.py 
# (clean way: with open('test.py') as fh: exec(fh))

# we can "import test", but there is nothing interesting defined in test

import numpy as np  # np is just an alias, like setting np = numpy
# check also `reload` for modules which (we) have changed after the last import

np.exp(2)  # this is how to use math functions in code
exp = np.exp
exp(2)  # "from numpy import *" let us use everything "in" numpy, see below

# defining a function is as easy as this and can be done everywhere:
def f(x):  
    """this is the help for f: f returns x**2"""
    return x**2
f(3)
help(f)

quit()  # ctrl-d works as well

ipython  # from OS shell

# same things work, ipython is a python shell plus other useful stuff

who
whos

# back to math...
# ipython magic commands start with %, often also work without it
%pylab  # switching the "(mat)lab"-mode on, see http://ipython.org/ipython-doc/2/api/generated/IPython.core.magics.pylab.html
# pylab mode executes also "from numpy import *"

sin(1)
exp(2)
2 * pi
x = arange(0, 2, 0.01)  # x is a numpy array, not a list
plot(x, sin(x))

# CAVEATs: 
a = [1,2,3]  # == range(1, 4)
a + a  # len(a+a) == 6
a = array([1,2,3])  # == arange(1, 4)
a + a  # len(a+a) == 3

a = array([1,2,3])
b = [1,2,3]
a + a
a + b  # a.__add__(b)
b + b
b + a  # a.__radd__(b), because b.__add__(a) fails
3 * a
3 * b
min is not np.min  # they have different user interfaces!

import cma  # use "pip install cma" if necessary (and sudo if necessary)
cma?  # same as ?cma or help(cma)
cma.CMAEvolutionStrategy
# implementation: object-oriented approach 
cma.OOOptimizer?
cma.OOOptimizer??  # shows the source code
quit()

pip install appnope  # can be useful for Mac in ipython notebook to remain responsive

ipython notebook  # notebook file should be in the current folder

# see the copenhagen-cma.ipynb notebook file for the rest of it 

# solving an "unknown" function f = cma.FF2.Unknown()
# run from typical x0
# large sigma: worse results
# small sigma: same, sometimes better results
# conclusion: getting the same results: seeing the same local optimum
# investigate plots and rescale -> about 4 times faster runs
# Sections, zoom, then semilogy, then different do(locations=...)
# Sections with rescaling 
# What now? popsize as means to keep the initial ss large without 
#   becoming extremely slow or diverge

# what else:
debug  # into debug mode to the point where the last error occurred 
# l=list, u=up, d=down, q=quit are useful commands in debug mode