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Identify the error in the following code snippet that attempts to fit a custom exponential model:

medium📝 Debug Q6 of 15
SciPy - Curve Fitting and Regression
Identify the error in the following code snippet that attempts to fit a custom exponential model:
import numpy as np
from scipy.optimize import curve_fit

def exp_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])

popt, pcov = curve_fit(exp_model, xdata, ydata)
print(popt)
AUsing <code>np.exp</code> inside model is not supported by <code>curve_fit</code>
BFunction <code>exp_model</code> has incorrect parameter order
CMissing initial guess <code>p0</code> may cause poor fitting or warnings
DData arrays <code>xdata</code> and <code>ydata</code> have different lengths
Step-by-Step Solution
Solution:
  1. Step 1: Check function and data correctness

    The model and data arrays are correctly defined and of equal length.
  2. Step 2: Identify missing initial guess

    Without p0, fitting exponential models may fail or warn due to poor starting points.
  3. Final Answer:

    Missing initial guess p0 may cause poor fitting or warnings -> Option C
  4. Quick Check:

    Always provide p0 for nonlinear fits [OK]
Quick Trick: Provide initial guesses for nonlinear models to ensure convergence [OK]
Common Mistakes:
  • Ignoring need for p0 in nonlinear fits
  • Assuming np.exp is unsupported
  • Not checking data array lengths

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