from IPython.display import Image
Image("IPy_header.png")

%run talktools

# Create a [list] 
days_of_the_week = ['Monday',
                    'Tuesday',
                    'Wednesday',
                    'Thursday',
                    'Friday',
                    'Saturday',
                    'Sunday', ]

days_of_the_week

# Simple for-loop
for day in days_of_the_week:
    print day

# Double for-loop
for day in days_of_the_week:
    for letter in day:
        print letter,

for day in days_of_the_week:
    for letter in day:
        print letter.lower(),

letters = [letter for day in days_of_the_week 
                       for letter in day]


letters = [letter for day in days_of_the_week for letter in day]
print letters

sorted_letters = sorted([x.lower() for x in letters])
print sorted_letters

unique_sorted_letters = sorted(set(sorted_letters))
print "There are", len(unique_sorted_letters), "unique letters in the days of the week."
print "They are:", ''.join(unique_sorted_letters)

def first_three(input_string):
    """Takes an input string and returns the first 3 characters."""
    return input_string[:3]

[first_three(day) for day in days_of_the_week]

def last_N(input_string, number=2):
    """Takes an input string and returns the last N characters."""
    return input_string[-number:]

[last_N(day, 153) for day in days_of_the_week if len(day) > 6]

from math import pi

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

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

# Let this be a warning to you!

# If you see python code like the following in your work:

for x in range(len(list_of_lists)):
    print "Decimals:", list_of_lists[x][0], 
    print "expression:", list_of_lists[x][1]
    

# Change it to look more like this: 

for decimal, rounded_pi in list_of_lists:
    print "Decimals:", decimal, "expression:", rounded_pi
    
print list_of_lists

import numpy as np
import matplotlib.pyplot as plt

# The following line is an ipython notebook trick
%matplotlib inline 

plt.rcParams['figure.figsize'] = 12, 8  # plotsize

x = np.arange(10000)

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)

# Single physical cloud with following physical parameters
def GaussFunc(x, amplitude, centroid, sigma):
    """Takes an array, and calculates a Gaussian with the following parameters. """
    return amplitude * np.exp(-0.5 * ((x - centroid) / sigma)**2)

feature_centroid = 5315.3
feature_amplitude = 2.3
feature_sigma = 1.5

wavelength = np.linspace(5305., 5330., 120)
tau = GaussFunc(wavelength, feature_amplitude, feature_centroid, feature_sigma)

flux = np.exp(-tau)
sigma = 0.05
noise = np.random.randn(len(flux)) * sigma
observed = flux + noise
error = np.ones_like(wavelength) * sigma

plt.plot(wavelength, flux) 
plt.plot(wavelength, observed) 

np.savetxt("example.txt", np.transpose((wavelength, observed, flux, error, noise)))

# np.random.randn?

%less example.txt

wave = []
observed_flux = []
error = []
for line in open("example.txt", 'r'):
    wave.append(line[0])
    observed_flux.append(line[1])
    error.append(line[3])
    
wave[:10] # Whoops! 

wave = []
observed_flux = []
error = []
for line in open("example.txt", 'r'):
    line = line.split()
    wave.append(line[0])
    observed_flux.append(line[1])
    error.append(line[3])
    
wave[:10] # Dang! still strings!

# If you see yourself doing this kind of thing... 

wave = []
observed_flux = []
error = []

for line in open("example.txt", 'r'):
    line = line.split()
    wave.append(float(line[0]))
    observed_flux.append(float(line[1]))
    error.append(float(line[3]))
    
wave = np.array(wave)
observed_flux = np.array(observed_flux)
error = np.array(error)

# Do this instead
wave, observed_flux, error = np.loadtxt("example.txt", usecols=(0, 1, 3), unpack=True)

# Run this cell
%load http://matplotlib.org/mpl_examples/pylab_examples/polar_legend.py

# And it loads the code here, ready to run (obviously without this comment). 

#!/usr/bin/env python

import numpy as np
from matplotlib.pyplot import figure, show, rc

# radar green, solid grid lines
rc('grid', color='#316931', linewidth=1, linestyle='-')
rc('xtick', labelsize=15)
rc('ytick', labelsize=15)

# force square figure and square axes looks better for polar, IMO
fig = figure(figsize=(8,8))
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True, axisbg='#d5de9c')

r = np.arange(0, 3.0, 0.01)
theta = 2*np.pi*r
ax.plot(theta, r, color='#ee8d18', lw=3, label='a line')
ax.plot(0.5*theta, r, color='blue', ls='--', lw=3, label='another line')
ax.legend()

show()


Image("../../../../Screenshots/Screenshot 2014-07-18 14.51.30.png")