num_py.py

import numpy as np
print(np.array([1,2,3,5,6]))

# array_dimensions
a = np.array(42)
b = np.array([1, 2, 3, 4, 5])
c = np.array([[1, 2, 3], [4, 5, 6]])
d = np.array([[[1, 2, 3], [4, 5, 6]], [[1, 2, 3], [4, 5, 6]]])
# arange()
np.arange(1, 20 , 2,
          dtype = np.float32)
# linespace
np.linspace(3.5, 10, 3)
# empty()
np.empty([4, 3],
         dtype = np.int32)
# ones()
np.ones([4, 3],
        dtype = np.int32,
        order = 'f')
#zeros()
np.zeros([4, 3],
         dtype = np.int32)
# Access Array Elements
# 1D
arr = np.array([1, 2, 3, 4])
print(arr[1])
# 2D
arr = np.array([[1,2,3,4,5], [6,7,8,9,10]])
print('2nd element on 1st dim: ', arr[0, 1])
# 3D
arr = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
print(arr[0, 1, 2])

# Slicing
# 1D
arr = np.array([1, 2, 3, 4, 5, 6, 7])
print(arr[1:5])

# negative slicing
arr = np.array([1, 2, 3, 4, 5, 6, 7])
print(arr[-3:-1])
# 2D
arr = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
print(arr[1, 1:4])
arr = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
print(arr[0:2, 2])
arr = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
print(arr[0:2, 1:4])

# boolean array indexing example
cond = arr > 0 # cond is a boolean array
temp = arr[cond]
print(temp)




# copy&view
# Make a copy, change the original array, and display both arrays
arr = np.array([1, 2, 3, 4, 5])
x = arr.copy()
arr[0] = 42
print(arr)
print(x)
# view
# Make a view, change the both original and view array, and display both arrays
arr = np.array([1, 2, 3, 4, 5])
x = arr.view()
arr[0] = 42
print(arr)
print(x)

# shape
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
print(arr.shape)
# reshape
arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
newarr = arr.reshape(4, 3)
# 1D to 3D
arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
newarr1 = arr.reshape(2, 3, 2)

# iterating
arr = np.array([1, 2, 3])

for x in arr:
  print(x)

# 2D
arr = np.array([[1, 2, 3], [4, 5, 6]])

for x in arr:
  for y in x:
    print(y)
# 3d
arr = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])

for x in arr:
  print(x)

# split
arr = np.array([1, 2, 3, 4, 5, 6])
newarr = np.array_split(arr, 3)
print(newarr)

# split array
arr = np.array([1, 2, 3, 4, 5, 6])

newarr = np.array_split(arr, 3)

print(newarr[0])
print(newarr[1])
print(newarr[2])


# sort
arr = np.array([[3, 2, 4], [5, 0, 1]])
print(np.sort(arr))

a = np.array([[1, 4, 2],
            [3, 4, 6],
              [0, -1, 5]])
print ("Row-wise sorted array:\n",
                np.sort(a, axis = 0))

# create an array of sine values
a = np.array([0, np.pi / 2, np.pi])
print("Sine values of array elements:", np.sin(a))

# exponential values
a = np.array([0, 1, 2, 3])
print("Exponent of array elements:", np.exp(a))

# square root of array values
print("Square root of array elements:", np.sqrt(a))