Graph a custom function in python

Question

I would like to graph a custom function including min and max :

import numpy as np
import matplotlib.pyplot as plt

f = lambda x: max(0, x)
x = np.linspace(-10, 10)
y = f(x)

plt.plot(x, y)
plt.show()

Result:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Some help will be welcome

Answer 1

use vectorized np.clip() instead of f - this way you can set both lower (a_min) and upper (a_max) boundaries in one step:

y = np.clip(x, a_min=0, a_max=None)

or try to vectorize your scalar funcion:

In [146]: x = np.linspace(-1000, 1000, 10**6)

In [147]: x.shape
Out[147]: (1000000,)

In [148]: vf = np.vectorize(f)

In [149]: %timeit [f(i) for i in x]
1.46 s ± 5.42 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

In [150]: %timeit vf(x)
1.03 s ± 8.73 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

Answer 2

Instead of max, use np.maximum:

from matplotlib import pyplot as plt
import numpy as np

f = lambda x: np.maximum(0, x)
x = np.linspace(-10,10)
y = f(x)

plt.plot(x,y)
plt.show()

EDIT:

In case of more complex functions, look out for the numpy equivalents of the functions you intend to use. Most of the time the names are the same as in the math module, e.g. math.sin would become np.sin etc. However, as in the example, max should be replaced by np.maximum not np.max, the latter of which returns the maximum value of an np.ndarray.