Fitting custom models in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the function used for curve fitting from scipy.

SciPy

from scipy.optimize import [1]

Drag options to blanks, or click blank then click option'

Aminimize

Bcurve_fit

Clinprog

Droot

Attempts:

3 left

💡 Hint

Common Mistakes

Importing a different optimization function like minimize or root.

Forgetting to import from scipy.optimize.

The curve_fit function from scipy.optimize is used to fit custom models to data.

2fill in blank

medium

Complete the code to define a custom linear model function with parameters a and b.

SciPy

def linear_model(x, a, b):
    return [1]

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Aa + b * x

Ba / x + b

Ca * b + x

Da * x + b

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the order of multiplication and addition.

Using division instead of multiplication.

The linear model is defined as a * x + b, where a is the slope and b is the intercept.

3fill in blank

hard

Fix the error in the code to fit the model to data using curve_fit.

SciPy

params, covariance = curve_fit([1], x_data, y_data)

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Alinear_model

Bnp.array

Cx_data

Dy_data

Attempts:

3 left

💡 Hint

Common Mistakes

Passing data arrays instead of the model function.

Using numpy arrays as the model argument.

The first argument to curve_fit must be the model function to fit, here linear_model.

4fill in blank

hard

Fill both blanks to extract the fitted parameters and print the slope.

SciPy

a, b = [1]
print('Slope:', [2])

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Aparams

Ba

Cb

Dcovariance

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to unpack covariance instead of params.

Printing the wrong variable for slope.

The fitted parameters are stored in params. The slope is the first parameter a.

5fill in blank

hard

Fill all three blanks to create a dictionary of parameters with keys 'slope' and 'intercept', and print it.

SciPy

fit_params = [1]({'slope': [2], 'intercept': [3])
print(fit_params)

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Adict

Ba

Cb

Dparams

Attempts:

3 left

💡 Hint

Common Mistakes

Using params instead of individual variables a and b.

Not using dict to create the dictionary.

We create a dictionary with keys 'slope' and 'intercept' using the fitted parameters a and b. The dict function builds the dictionary.