plot multivariate function based on max-CodePudding

I would like to create a multivariate function that takes the max value of 2 functions and then to plot it. However by using the max function there is an error when applying the function on the meshgrid. I have tried this on other multivariate function without the max function and it worked.

import numpy as np
import pandas as pd
import plotly.graph_objects as go

def f(x,y):
    return max(np.cos(x),np.sin(y))

x=np.linspace(0,5,20)
y=np.linspace(-3,2,20)
X, Y = np.meshgrid(x, y)
Z=f(X,Y)

fig = go.Figure(data=[go.Surface(x=X, y=Y, z=Z)])
fig.show()

The error I get is : The truth value of an array with more than one element is ambiguous. Use a.any() or a.all(). However, I don't think that the suggestion is adapted to my case. I also tried by defining the max function with if statement but as I expected I get the same error. Does anyone could help?

CodePudding user response：

The np.sin and np.cos functions work with arrays and the max function would produce an ambiguous answer (do you want the maximum of both functions or a comparison - numpy doesn't know). I recommend doing the built-in math.sin, math.cos on each of the values in the arrays and compare to get the desired max value .

def f(x,y):
    max_values = []
    for x_value, y_value in zip(x,y): #(iterate both together)
        max_values.append(max(math.cos(x_value), math.sin(y_value)))

This may run slower than before, but does this help?

CodePudding user response：

try using ax.scatter3D with

from mpl_toolkits import mplot3d
import matplotlib.pyplot as plt

x=np.linspace(0,5,20)
y=np.linspace(-3,2,20)

def f(x,y):
    max_values = []
    for x_value, y_value in zip(x,y): #(iterate both together)
        max_values.append(max(math.cos(x_value), math.sin(y_value)))

X, Y = np.meshgrid(x, y)

max_values = []
for x_value, y_value in zip(X,Y):
    Z=zip([math.cos(item) for item in x_value],[math.sin(item) for item in y_value])
    max_values.append([max(x,y) for x,y in Z])
        

fig = plt.figure()
ax = plt.axes(projection="3d")

ax.scatter3D(X, Y,max_values, c=max_values, cmap='Greens');
plt.show()