Python15_Numpy

## Python
## Numpy


## Arrays
import numpy

# # Option 1:
# def arrays(arr):
#     return(numpy.array(arr[::-1], float))

# Option 2:
def arrays(arr):
    arr.reverse()
    arr_new = numpy.array(arr, float)
    return arr_new

arr = input().strip().split(' ')
result = arrays(arr)
print(result)


## Shape and Reshape
# # Option 1
# import numpy as np
# print(np.array(input().split(),int).reshape(3,3))

# # Option 2
# import numpy as np
# arr = np.array(list(map(int, input().split())))
# arr.shape = (3,3)
# print(arr)

# Option 3
import numpy as np
arr = np.array(list(map(int, input().split())))
arr = np.array(arr).reshape(3,3)
print(arr)


## Transpose and Flatten
# # Option 1
# import numpy as np
# row, col = map(int, input().split())
# arr = np.array([input().split() for _ in range(row)], int)
# print (arr.transpose())
# print (arr.flatten())

# Option 2
import numpy as np
row, col = map(int, input().split())
arr = []
for _ in range(row):
    inp = [input().split()]
    arr.extend(inp)
arr = np.array(arr, int)
print (arr.transpose())
print (arr.flatten())


## Concatenate
# Option 1
import numpy as np
n, m, p = map(int,input().split())
arr1 = np.array([input().split() for _ in range(n)], int)
arr2 = np.array([input().split() for _ in range(m)], int)
print(np.concatenate( (arr1, arr2), axis=0) )

# # Option 2
# import numpy as np
# n, m, p = map(int, input().split())
# arr = np.array([input().split() for _ in range(n+m)], int)
# print(arr)


## Zeros and Ones
import numpy as np
nums = tuple(map(int, input().split()))
print (np.zeros(nums, dtype = np.int))
print (np.ones(nums, dtype = np.int))


## Eye and Identity
# # Option 1
# import numpy as np
# print(str(np.eye(*map(int,input().split()))).replace('1',' 1').replace('0',' 0'))
"""
use replace() function because there's a bug with the test cases, e.g. an error on the part of the problem creator, where there's too much whitespace in the expected output; in expected output every element is shifted one unit right
"""

# # Option 2
# import numpy as np
# np.set_printoptions(legacy='1.13')
# print(np.eye(*map(int,input().split())))

# Option 3
import numpy as np
np.set_printoptions(legacy='1.13')
n, m = map(int,input().split())
print(np.eye(n,m))


## Array Mathematics
# # Option 1
# import numpy as np
# n,m = map(int, input().split())
# a,b = (np.array([input().split() for _ in range(n)], dtype=int) for _ in range(2))
# print(a+b, a-b, a*b, a//b, a%b, a**b, sep='\n')

# Option 2
import numpy as np
n,m = map(int,input().split())
a = np.array([input().split() for _ in range(n)], dtype=int)
b = np.array([input().split() for _ in range(n)], dtype=int)
print(a+b)
print(a-b)
print(a*b)
print(a//b)
print(a%b)
print(a**b)

# # Option 3
# import numpy as np
# n,m = map(int,input().split())
# lst1=[]
# lst2=[]
# for _ in range(n):
#     lst=list(map(int, input().split()))
#     lst1.append(lst)
# a = np.array(lst1)
# for _ in range(n):
#     lst=list(map(int, input().split()))
#     lst2.append(lst)
# b = np.array(lst2)
# print(np.add(a,b))
# print(np.subtract(a, b))
# print(np.multiply(a, b))
# print(np.floor_divide(a, b))
# print(np.mod(a, b))
# print(np.power(a, b))


## Floor, Ceil and Rint
import numpy as np
np.set_printoptions(sign=' ')    # output offset with a space
arr = np.array(input().split(), float)
print(np.floor(arr))
print(np.ceil(arr))
print(np.rint(arr))


## Sum and Prod
# Option 1
import numpy as np
N, M = map(int, input().split())
arr = np.array([input().split() for _ in range(N)], int)
total = np.sum(arr, axis=0)
print(np.prod(total, axis=0))

# # Option 2
# import numpy as np
# N, M = map(int, input().split())
# lis = [np.array(input().split(), int) for _ in range(N)]
# print(np.prod(np.sum(lis, axis = 0)))

"""
range(N): [0, 1, 2, .... N-1]
for x in range(N): loop x = 0, x = 1, ..., x = N-1
for _ in range(N): loop N times
input().split(): Split input by spaces and prepare list (fr ex 1 2 3 becomes ['1', '2', '3'])
input().split() for _ in range(N): Read n lines and prepare n lists
[input().split() for _ in range(N)]: Prepare a list from n lines input containing N times where each item itself is list of strings
numpy.array([input().split() for _ in range(N)],int): Prepare 2d array from n lines of input with each item of type int
A = numpy.array([input().split() for _ in range(N)],int): Assign the result to A
"""


## Min and Max
# # Option 1
# import numpy as np
# print(np.max(np.min(np.array([input().split() for _ in range(int(input().split()[0]))],int),axis=1)))

# Option 2
import numpy as np
# n, m = map(int, input().split())
n = int(input().split()[0])
arr = np.array([input().split() for _ in range(n)], int)
print(np.max(np.min(arr, axis=1)))


## Mean, Var, and Std
import numpy as np
np.set_printoptions(legacy='1.13')
# n,m = map(int, input().split())
n = int(input().split()[0])
arr = np.array([input().split() for _ in range(n)], int)
print(np.mean(arr, axis=1))
print(np.var(arr, axis=0))
print(np.std(arr, axis=None))


## Dot and Cross
# Option 1
import numpy as np
n = int(input())
A=np.array([list(map(int,input().split())) for _ in range(n)])
B=np.array([list(map(int,input().split())) for _ in range(n)])
print( np.dot(A,B) )

# # Option 2
# import numpy as np
# n = int(input())
# A,B = [np.array([input().split() for _ in range(n)], int) for _ in range(2)]
# print(np.dot(A,B))


## Inner and Outer
# # Option 1
# import numpy as np
# A,B = [np.array([input().split()],int) for _ in range(2)]
# print(np.inner(A,B)[0][0], np.outer(A,B), sep='\n')

# # Option 2
# import numpy as np
# A,B = [np.array(input().split(), int) for _ in range(2)]
# print(np.inner(A,B), np.outer(A,B), sep='\n')

# Option 3
import numpy as np
A=np.array(input().split(),int)
B=np.array(input().split(),int)
print(np.inner(A,B))
print(np.outer(A,B))


## Polynomials
"""
You are given the coefficients of a polynomial Y = a x^n + b x^(n-1) + … + k.
Your task is to find the value of Y at point x.
"""
# # Option 1
# print(__import__('numpy').polyval(list(map(float,input().split())),float(input())))

# Option 2
import numpy as np
coeff = list(map(float,input().split()))
x = int(input())
print( np.polyval(coeff,x) )

# # Option 3
# import numpy as np
# if __name__ == '__main__':
#     coefficients = np.array(list(map(float, input().split())))
#     poly = np.poly1d(coefficients)
#     print(poly(int(input())))


## Linear Algebra
## output needs to be rounded to 2 decimal points
# # Option 1
# import numpy as np
# print(round(np.linalg.det(np.array([input().split() for _ in range(int(input()))],float)),2))

# Option 2
import numpy as np
n=int(input())
a=np.array([input().split() for _ in range(n)],float)
np.set_printoptions(legacy='1.13') #version issues in this exercise
print(np.linalg.det(a))

# # Option 3
# import numpy as np   # importing numpy package
# n = int(input())   # nxn array.
# a = []   # init array
# for i in range(n):
#     c = list(map(float, input().split()))
#     a.append(c)
# print(round(np.linalg.det(a),2))  # determinant round to 2 places


## end ##