CODEWITHSUNDEEP
pythonnumpy
Tomasz Przemski
Tomasz Przemski

Reputation: 1127

How to round polynomial coefficients when using the polyfit() function?

I fit a polynomial to points from list data using the polyfit() function:

import numpy as np

data = [1,4,5,7,8,11,14,15,16,19]

x = np.arange(0,len(data))
y = np.array(data)
z = np.polyfit(x,y,2)

print (z)
print ("{0}x^2 + {1}x + {2}".format(*z))

Output:

[0.00378788  1.90530303  1.31818182]
0.003787878787878751x^2 + 1.9053030303030298x + 1.3181818181818175

How to get a fit to points, with rounded coefficients for example to three decimal places? For example, to get:

[0.004  1.905  1.318]
0.004x^2 + 1.905x + 1.318

Upvotes: 1

Views: 1610

Answers (1)

Tai
Tai

Reputation: 7994

There is no option in the polyfit method for the purpose of rounding. IIUC, you can use round after applying polyfit.

import numpy as np

data = [1,4,5,7,8,11,14,15,16,19]

x = np.arange(0,len(data))
y = np.array(data)
z = np.polyfit(x,y,2).round(decimals=3)
array([0.004, 1.905, 1.318])

For values exactly halfway between rounded decimal values, NumPy rounds to the nearest even value. Thus 1.5 and 2.5 round to 2.0, -0.5 and 0.5 round to 0.0, etc. Results may also be surprising due to the inexact representation of decimal fractions in the IEEE floating point standard [R9] and errors introduced when scaling by powers of ten. -- Cited from numpy.around

Upvotes: 2

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