TypeError when converting an array of floats to ints

Question

I have a smooth function f(x) = sin(x / 5) * exp(x / 10) + 5 * exp(-x / 2) The task is to explore a non-smooth function h(x) = int(f(x)) on the interval of 1 to 30. In other words, each value of f (x) is converted to type int and the function takes only integer values. I am trying to build h(x) with help of matplotlib.

import math
import numpy as np
from scipy.optimize import minimize
from scipy.linalg import *
import matplotlib.pyplot as plt

def f(x):
    return np.sin(x / 5.0) * np.exp(x / 10.0) + 5 * np.exp((-x / 2.0))

def h(x):
    return int(f(x))

x = np.arange(1, 30)
y = h(x)

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

The code doesn't work. Running the code raises

TypeError: only length-1 arrays can be converted to Python scalars

Using VS I get:

"The code doesnt work." is not a proper problem description. In this case it's rather easy to guess what the error is, but in general questions without proper problem description are off topic. Here the problem is that your function f returns an array. To convert a numpy array to integer you need array.astype(int). — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented Jun 3, 2017 at 16:46

unutbu · Accepted Answer · 2017-06-03 16:50:47Z

2

int is a Python class which returns a single int instance. To convert a NumPy array of floats to a NumPy array of integers, use astype(int):

import numpy as np
import matplotlib.pyplot as plt

def f(x):
    return np.sin(x / 5.0) * np.exp(x / 10.0) + 5 * np.exp((-x / 2.0))

def h(x):
    return f(x).astype(int)

x = np.arange(1, 30)
y = h(x)

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

edited Jun 3, 2017 at 16:50

answered Jun 3, 2017 at 16:44

unutbu

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1 Comment

plywoods Over a year ago

Thank you so much!

Lutz Lehmann · Accepted Answer · 2017-06-03 17:00:18Z

1

Use rounding down,

def h(x):
    return np.floor(f(x));

or rounding towards zero

def h(x):
    return np.fix(f(x));

instead of the implicit rounding during integer conversion.

edited Jun 3, 2017 at 17:00

answered Jun 3, 2017 at 16:53

Lutz Lehmann

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