Parametric interpolation in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the parametric spline function from scipy.

SciPy

from scipy.interpolate import [1]

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AUnivariateSpline

Bsplprep

Cgriddata

Dinterp1d

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing interpolation functions meant for 1D data like interp1d.

Confusing griddata with parametric spline functions.

The splprep function is used for parametric spline interpolation in scipy.

2fill in blank

medium

Complete the code to create a parametric spline representation of points x and y.

SciPy

tck, u = splprep([x, y], s=[1])

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A0

B1

CNone

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using None or negative values for smoothing which are invalid here.

Using smoothing > 0 which allows approximation, not exact fit.

Setting s=0 forces the spline to pass through all points exactly.

3fill in blank

hard

Fix the error in the code to evaluate the spline at new parameter values u_new.

SciPy

x_new, y_new = splev([1], tck)

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Au_new

Btck

Cx

Dy

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the spline representation tck as the first argument instead of the parameter values.

Passing original data points instead of parameter values.

The splev function evaluates the spline at the new parameter values u_new.

4fill in blank

hard

Fill both blanks to create a smooth parametric curve and evaluate it at 100 points.

SciPy

tck, u = splprep([x, y], s=[1])
u_new = np.linspace(0, 1, [2])

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A0

B50

C100

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using smoothing > 0 which approximates instead of fitting exactly.

Choosing too few points for evaluation leading to a rough curve.

Use s=0 for exact fit and 100 points for smooth evaluation.

5fill in blank

hard

Fill all three blanks to create a parametric spline, evaluate it, and plot the smooth curve.

SciPy

tck, u = splprep([x, y], s=[1])
u_new = np.linspace(0, 1, [2])
x_new, y_new = splev([3], tck)
plt.plot(x_new, y_new)
plt.show()

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

A0

B50

Cu_new

D100

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong variable for evaluation in splev.

Choosing smoothing > 0 which changes the curve shape.

Set smoothing to zero for exact fit, evaluate at 100 points, and use u_new for evaluation.