如何使用 Python 和 Matplotlib 绘制数值函数？

Question

I'm trying to graph the Sigmoid Function used in machine learning by using the Matplotlib library. My problem is that I haven't visualized a mathematical function before so I'm humbly asking for your guidance.

I've tried to directly plot the following function:

def Sigmoid(x):
  a=[]
  for i in x:
    a.append(1/(1+math.exp(-i)))
  return a

using the command plt.plot(Sigmoid) . But that gave me the error:

TypeError: float() argument must be a string or a number, not 'function'

The final result should look something like this:

Answer 1

Sigmoid is a function, Matplotlib expects numerical values, ie, the results of a function evaluation, eg

x = [i/50 - 1 for i in range(101)]
plt.plot(x, Sigmoid(x))

That said, you probably want to familiarize with the Numpy library

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-1, 1, 101)
plt.plot(x, 1/(1+np.exp(-x))

Answer 2

import numpy as np
import matplotlib.pyplot as plt

def sigmoid(arr, scale=1):
    arr = np.asarray(arr)
    result = 1/(1 + np.exp(-arr*scale))
    return result

x = np.linspace(-5, 5)
y = sigmoid(x)

fig, ax = plt.subplots()
ax.plot(x, y)

Result:

The ax.plot method takes a pair of 1-D array-likes that are of the same length to create the lines. Matplotlib is not like Mathematica in which you can give an analytic function and a domain of its arguments. You have to give (in this case) xy pairs (or rather, lists/arrays that can be turned into xy pairs) And in this case, order matters.