import numpy as np

sl=[np.sin(x) for x in np.arange(0,10,.1)]

import matplotlib.pyplot as plt

plt.plot(sl)
plt.show()

%matplotlib inline

#If you remove the semicolon and it is the last line, the next line will print out the values
[[np.sin(x)*np.cos(y) for x in np.arange(0,1,.1)] for y in np.arange(0,1,.1)];

#but it won't if you assign a variable name to the array

sl2=[[np.sin(x)*np.cos(y) for x in np.arange(0,1,.1)] for y in np.arange(0,1,.1)];

#make a vector with 5 rows and 6 columns
sl3=np.array([[x+y*6 for x in np.arange(0,6,1)] for y in np.arange(0,5,1)])
#what happens if you don't use np.array() in the above line?

print np.array(sl3),'\n\n(#rows, #columns)=',np.shape(sl3),"# elements:",np.size(sl3)

#note that unlike Mathematica and Matlab (but like C), indexing starts with 0
#first row
sl3[0]

#first column
sl3[:,0]

#Try accessing the element in the 3rd row, 4th column. It isn't sl3[3,4]|

#Get the first 2 elements of sl. It isn't sl[0:1].

#Now get the submatrix 3rd and 4th row, 4th through 6th columns
sl3[2:4,3:6]

def f(x,y):
    return([[np.sin(3*x)*np.cos(4*y) for x in np.arange(0,1,.1)] for y in np.arange(0,1,.1)])

#Visualize f(x,y) using imshow()

import matplotlib.cm as cm

n = 10
x = np.linspace(-3,3,4*n)
y = np.linspace(-3,3,3*n)
X, Y = np.meshgrid(x,y)
plt.imshow(f(X,Y),cmap = cm.Greys_r,origin='lower',interpolation='nearest');