# Jean-Baptiste Juin
# Astronomy Python course
# Practice 2

#------------------------
#------------------------
# Title: Numpy ndim-arrays
#------------------------
#------------------------

# if not in ipython:
# from numpy import *

#------------------------
# Creating array
#------------------------
# From scratch
t=arange(0.0,10.0,10.0/20.0)
z=zeros(5)
m=rand(5,6)
# From lists
Values=[[2,4,5],[3,-6,9]]
print Values
v=array(Values)
print v

#------------------------
# Accessing by index
#------------------------
print v[0,0]
print m[3,5]
print t
print t[1]
print t[-1]
t[-1]=-33
print t

#------------------------
# Slicing
#------------------------
# 1D
t2=t[0:5]
print t
print t2
# 2D
m2=m[1:3,1:4]
print m
print m2
m2[0,0]=-33
print m2
print m
# Array are not copied when slicing: link
m3=m[1:3,-2:-1]
print m3

#------------------------
# Some methods
#------------------------
m=rand(2,3)
# Shape and size
print m
print m.size
print m.shape
print m.flatten()
print m.reshape(6,1)
print m.reshape(1,6)
# Minimum/Maximum
print m
print m.min(),m.max()
# Some statistics
print m.mean(),m.var()
# Sorting
v=rand(10)
print v
v.sort()
print v
# Getting sub array
index=numpy.where(v > 0.5)
print index
print v[index]

#------------------------
# I/O to ASCII
#------------------------
v1=arange(0,6)
v2=arange(1,7)
# Writing
# Using scipy.io
io.write_array("./Test.scipy-io.txt",m,separator=' ')
io.write_array("./Test.scipy-io.csv",m,separator=',')
# Using matplotlib
pylab.save("./Test.pylab.txt",m,fmt='%5.2f')
pylab.save("./Test2.pylab.txt",(v1,v2),fmt='%5.2f')
# Using numpy tofile method
v1.tofile("./Test.numpy-tofile.txt",sep=' ', format = "%5.2f")
# Reading
# Using scipy.io
data=io.read_array("./Test.scipy-io.txt")
print data
# Using matplotlib
data=pylab.load("./Test2.pylab.txt")
print data
# Reading a CSV file (SDSS public data for instance)
# Using matplotlib
data = pylab.load("./Test.scipy-io.csv",delimiter=',',skiprows=1)

#------------------------
# I/O to fits format
#------------------------
# Using pyfits
import pyfits
# Writing
pyfits.writeto("./Test.fits",m)
# Reading
data=pyfits.getdata("./Test.fits")
# Getting the header
header=pyfits.getheader("./Test.fits")
print header
print header['NAXIS']
print header['NAXIS1']