自变量范围内的最大值和最小值

Question

Based on the answer from @Peaceful James, I am attempting to reduce the confusion. Thus, editing the question.

Edited

I am trying to find a maximum (and minimum) in the range of an independent variable, ie X . My code looks like the following. Note, this is just a representative function.

import numpy as np
import matplotlib.pyplot as plt
from pandas import *

X = np.arange(2, 11, 0.2)

Z = np.zeros((len(X),1))

for i in range(0,len(X)):
    Z[i] = 0.1*np.sin(X[i]-5)

print(DataFrame(Z))
A = np.argmax(Z, axis = 0)
B = np.argmin(Z, axis = 0)

C = print("Maximum =",Z[A[0]])
D = print("Minimum =", Z[B[0]])

plt.plot(X,Z,'r-', linewidth = 2)
plt.xlabel('$X$ (-)')
plt.ylabel('$Z$ (-)')

1: A = np.argmax(Z, axis = 0) the maximum is 0.09995736 (index: (23,0)) which is between the X values 6 and 8 .

2: A = np.argmin(Z, axis = 0) the min is -0.09995736 (index: (7,0)) which is between the X values 2 and 4 . However, there is another minimum between the X values 8 and 10 . I am wondering if there is a way to pass some kind of upper and lower limit values of X to np.argmin (or to similar command) to get the second minimum of function Z .

Any help is appreciated. Thanks !

Answer 1

Use numpy.argsort : https://numpy.org/devdocs/reference/generated/numpy.argsort.html

import numpy as np

X = np.arange(2, 11, 0.2)

Z = np.zeros((len(X),1))

for i in range(0,len(X)):
    Z[i] = 0.1*np.sin(X[i]-5)

C = np.argsort(Z, axis=0)
C = C.flatten()  # flatten because it is currently an array of 1-dim arrays.

print("Maximum =",Z[C[-1]])
print("Second Maximum =",Z[C[-2]])

print("Second Minimum =",Z[C[1]])
print("Minimum =",Z[C[0]])