import numpy as np

rg = np.random.default_rng(1)

'''a = np.floor(10 * rg.random((3, 4)))
print(a)

# shape: displays the dimensions of the array
print(a.shape)

# ravel: like flattening in wl
print(a.ravel())

# sum: add the values in an axis
# axis = 0: process by column
print(a.sum(axis = 0))

# axis = 1: process by row
print(a.sum(axis = 1))

# cumsum: cumulative sum across the axis
print(a.cumsum(axis = 1))

# min: return the minimum value in the axis
print(a.min(axis = 1))

# Slicing: getting values by index (starting at 0)
print("\nSlicing\n")
print("array:")
print(a)
print("index 1,2")
print(a[1,2])
print("index 2,2")
print(a[2,2])
print()

# T: transpose the array
print(a.T)

# Stacking
b = np.floor(10 * rg.random((2, 2)))
print("\nArray b:")
print(b)
c = np.floor(10 * rg.random((2, 2)))
print("\nArray c:")
print(c)

# vstack: stack vertical
print("\nvstack b & c")
print(np.vstack((b, c)))

# hstack: stack horizontal
print("\nhstack b & c")
print(np.hstack((b, c)))'''

