import numpy as np

from numpy import *

v = [1,2,3,4]
av = np.array(v)
av

m = [[1,2],[3,4]]
am = array(m)
am

am.size #total number of elements

am.shape   #array shape (equivalent to Matlab's size)

am.size

am.shape

am.ndim

len(dir(am))

am.dtype

array([1,2,3]).dtype

array([1.1,2.2,3.4]).dtype

array([1+2j,2+4j,3]).dtype

array([True,False]).dtype

sctypes

arange(0,10,2)

arange(-1,1,0.1)

linspace(0,10,6)

_.dtype

linspace(0,10,6,dtype='uint32')

_.dtype

linspace(-1,10,6,dtype='uint32')

finfo('float64')

iinfo(np.int8), iinfo('uint8')

logspace(0,1,10)

x,y = mgrid[0:5,0:5]
x, y

x = linspace(0,1,10)
y = linspace(-1,1,5)
meshgrid(x,y)

from numpy import random

random.normal(0,1)

random.normal(-1,0.001)

random.normal(0,1,[2,3])

random.poisson()

random.rand(5,5)

a = random.rand(5,5)
a

a[0,0]

a[0]

a[:,0]

aview1 = a[[0],:]
aview1

aview2 = a[0]
aview2

aview3 = a[[0]]
aview3

print aview1.shape, aview2.shape, aview3.shape

from IPython.display import YouTubeVideo
YouTubeVideo('q_2TBbfMLzs',start=15)

a

a[:,:]

a[0:2,1:3]

a = arange(10)

a[1:6:3]

a[::2]

a[::-1]

%%timeit 
a[::-1]

%%timeit
reversed(a)

print a[5:], a[:4], a[-2:], a[:-4]

a = random.rand(5,5)
a

a[0]

rows = [1,3]
cols = [0,2]
a[rows], a[:,cols], a[rows,cols]

mask = np.around(a)
mask = mask.astype('bool')

a[mask]

mask = a > 1.0
a[mask]

mask = a < 1.0
a[mask]

mask = a > 0.7
a[mask]

where(mask)

from numpy.linalg import *

x = arange(10)
b = random.rand(10,1)
A = random.randn(10,10)
print x

x*2

x+5

x**2

x*x

from IPython.display import Image
Image('https://scipy-lectures.github.io/_images/numpy_broadcasting.png',width=800)

x.shape, b.shape

x+b

x2 = solve(A,b)

A*x2-b

A.dot(x2)-b

np.allclose(A.dot(x2),b)

invA = inv(A)
np.allclose(invA.dot(A),identity(shape(A)[0]))

A.transpose()

A.sum()

np.sum(A)

sum(A)

sum is np.sum













from IPython.core.display import HTML
def css_styling():
    styles = open("./styles/custom.css", "r").read()
    return HTML(styles)
css_styling()