R_010 — NumPy Basics (Reproducible)

Purpose: reproduce key NumPy operations from the note.
Outputs: small arrays + sanity prints (shape/dtype) + simple plot.

import numpy as np
import matplotlib.pyplot as plt

print("numpy:", np.__version__)

numpy: 2.2.6

a = np.array([1, 2, 3])
b = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float64)

print("a:", a, "shape=", a.shape, "dtype=", a.dtype)
print("b:\n", b, "\nshape=", b.shape, "dtype=", b.dtype)

zeros = np.zeros((2, 3))
ones = np.ones((2, 3))
ar = np.arange(0, 10, 2)

print("zeros:\n", zeros)
print("ones:\n", ones)
print("arange:", ar)

a: [1 2 3] shape= (3,) dtype= int64
b:
 [[1. 2. 3.]
 [4. 5. 6.]] 
shape= (2, 3) dtype= float64
zeros:
 [[0. 0. 0.]
 [0. 0. 0.]]
ones:
 [[1. 1. 1.]
 [1. 1. 1.]]
arange: [0 2 4 6 8]

x = np.arange(1, 13).reshape(3, 4)
print("x:\n", x)

print("x[0, :]:", x[0, :])
print("x[:, 2]:", x[:, 2])
print("x[1:, 1:3]:\n", x[1:, 1:3])

x:
 [[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]]
x[0, :]: [1 2 3 4]
x[:, 2]: [ 3  7 11]
x[1:, 1:3]:
 [[ 6  7]
 [10 11]]

y = np.arange(1, 7)
y2 = y.reshape(2, 3)
yt = y2.T

print("y:", y)
print("y2:\n", y2)
print("y2.T:\n", yt)

y: [1 2 3 4 5 6]
y2:
 [[1 2 3]
 [4 5 6]]
y2.T:
 [[1 4]
 [2 5]
 [3 6]]

m = np.arange(1, 13).reshape(3, 4)
v = np.array([1, 10, 100, 1000])

out = m + v
print("m:\n", m)
print("v:", v)
print("m + v:\n", out)

m:
 [[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]]
v: [   1   10  100 1000]
m + v:
 [[   2   12  103 1004]
 [   6   16  107 1008]
 [  10   20  111 1012]]

t = np.linspace(0, 2*np.pi, 200)
s = np.sin(t)

plt.figure()
plt.plot(t, s)
plt.title("NumPy + Matplotlib sanity")
plt.xlabel("t")
plt.ylabel("sin(t)")
plt.show()