Constrained optimization in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the function for constrained optimization from scipy.optimize.

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

Choosing 'curve_fit' which is for curve fitting, not optimization.

Choosing 'linprog' which is for linear programming only.

Choosing 'root' which finds roots of equations, not optimization.

The minimize function is used for constrained optimization problems in scipy.optimize.

2fill in blank

medium

Complete the code to define the objective function to minimize: f(x) = (x - 3)^2.

SciPy

def objective(x):
    return (x[1]3)**2

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A-

B+

C*

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' instead of '-' changes the function shape.

Using '*' or '/' does not represent the intended function.

The objective function is (x - 3)^2, so the operator between x and 3 is subtraction '-'.

3fill in blank

hard

Fix the error in the constraint definition: x must be greater than or equal to 1.

SciPy

constraint = {'type': 'ineq', 'fun': lambda x: x[1] 1}

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A>=

B+

C<

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using '>=' inside the lambda returns a boolean instead of a numeric value.

Using '<' reverses the constraint direction.

For inequality constraints in scipy.optimize, the function should be >= 0. To enforce x >= 1, define fun as x - 1.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that squares numbers greater than 2 from a list.

SciPy

squares = {x: x[1]2 for x in numbers if x [2] 2}

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A**

B>

C<

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using '*' instead of '**' for squaring.

Using '<' instead of '>' changes the filter condition.

To square numbers, use the exponent operator '**'. To select numbers greater than 2, use '>'.

5fill in blank

hard

Fill all three blanks to create a dictionary of variable names in uppercase as keys, their values, and filter values greater than 0.

SciPy

result = [1]: [2] for [3], [2] in data.items() if [2] > 0}

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

Ak.upper()

Bv

Ck

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'item' instead of 'k' and 'v' in the loop.

Not converting keys to uppercase.

Using wrong variable names causing errors.

Keys are variable names in uppercase: k.upper(). Values are v. Loop variables are k, v.