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What will be the output of the following code snippet?

medium📝 Predict Output Q13 of 15
SciPy - Curve Fitting and Regression
What will be the output of the following code snippet?
import numpy as np
from scipy.optimize import curve_fit

def model(x, a, b):
    return a * np.exp(b * x)

xdata = np.array([0, 1, 2, 3])
ydata = np.array([1, 2.7, 7.4, 20.1])

params, _ = curve_fit(model, xdata, ydata)
print(np.round(params, 2))
A[1.00 1.00]
B[1.02 1.00]
C[1.00 0.99]
D[0.99 1.00]
Step-by-Step Solution
Solution:
  1. Step 1: Understand the model and data

    The model is an exponential function: a * exp(b * x). The ydata roughly follows this pattern with a near 1 for a and about 1 for b.
  2. Step 2: Run curve_fit and round parameters

    Using curve_fit on given data returns parameters close to [1.00, 0.99]. Rounding to two decimals gives [1.00 0.99].
  3. Final Answer:

    [1.00 0.99] -> Option C
  4. Quick Check:

    Fitted params ≈ [1.00, 0.99] [OK]
Quick Trick: Run curve_fit and round parameters to check values [OK]
Common Mistakes:
  • Assuming parameters are exactly 1.00 and 1.00
  • Confusing parameter order or values
  • Ignoring rounding effects

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