interp1d for 1D interpolation in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the interpolation function from scipy.

SciPy

from scipy.interpolate import [1]

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Ainterp1d

Binterpolate1d

Cinterp2d

Dinterpolate

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'interpolate1d' which does not exist.

Confusing with 'interp2d' which is for 2D interpolation.

The function interp1d is the correct import for 1D interpolation in scipy.

2fill in blank

medium

Complete the code to create an interpolation function for given x and y arrays.

SciPy

f = [1](x, y)

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Ainterpolate1d

Binterp1d

Cinterp2d

Dinterpolate

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'interp2d' which is for 2D interpolation.

Using 'interpolate' which is a module, not a function.

The interp1d function creates a callable interpolation function from x and y data.

3fill in blank

hard

Fix the error in the code to evaluate the interpolation function at new points.

SciPy

y_new = f([1])

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Ay_new

Bx

Cx_new

Df

Attempts:

3 left

💡 Hint

Common Mistakes

Passing y-values instead of x-values to the interpolation function.

Passing the function itself as argument.

To get interpolated values, call the function f with new x-values, here x_new.

4fill in blank

hard

Fill both blanks to create an interpolation function with linear method and evaluate it at new points.

SciPy

f = interp1d(x, y, kind=[1])
y_new = f([2])

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A'linear'

Bx_new

C'nearest'

Dy_new

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'nearest' instead of 'linear' for the kind parameter.

Passing y_new instead of x_new to the function.

Use kind='linear' to specify linear interpolation and call the function with x_new to get interpolated values.

5fill in blank

hard

Fill all three blanks to create a cubic interpolation function, evaluate it at new points, and convert the result to a list.

SciPy

f = interp1d(x, y, kind=[1])
y_new = f([2])
y_list = [3](y_new)

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A'cubic'

Bx_new

Clist

Darray

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'linear' or 'nearest' instead of 'cubic' for kind.

Not converting the result to a list.

Passing y_new instead of x_new to the function.

Use kind='cubic' for cubic interpolation, evaluate at x_new, and convert the result to a list with list().