Polynomial fitting in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the polynomial fitting function from numpy.

SciPy

from numpy import [1]

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

Apolyfit

Binterpolate

Cstats

Doptimize

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to import from scipy submodules like optimize or stats.

Using interpolate which is for interpolation, not fitting.

The polynomial fitting function polyfit can be imported directly from numpy.

2fill in blank

medium

Complete the code to fit a polynomial of degree 2 to data points x and y.

SciPy

coefficients = [1](x, y, 2)

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

Acurve_fit

Bpolyfit

Cminimize

Dlinregress

Attempts:

3 left

💡 Hint

Common Mistakes

Using curve_fit which is for general curve fitting, not specifically polynomials.

Using linregress which fits only linear regression.

The polyfit function fits a polynomial of specified degree to data points.

3fill in blank

hard

Fix the error in the code to evaluate the polynomial at points x_new using the coefficients. Assume polyval is imported from numpy.

SciPy

y_new = [1](coefficients, x_new)

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

Apolyval1d

Bpolyfit

Cpolyval2d

Dpolyval

Attempts:

3 left

💡 Hint

Common Mistakes

Using polyfit instead of polyval to evaluate values.

Using polyval2d which is for 2D polynomials.

The polyval function evaluates a polynomial at given points using coefficients.

4fill in blank

hard

Fill both blanks to create a dictionary of polynomial coefficients for degrees 1 and 3 from data x and y.

SciPy

coeffs = {1: [1](x, y, 1), 3: [2](x, y, 3)}

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

Apolyfit

Bcurve_fit

Dminimize

Attempts:

3 left

💡 Hint

Common Mistakes

Using different functions for each degree.

Using curve_fit which requires a function definition.

Use polyfit to fit polynomials of different degrees.

5fill in blank

hard

Fill all three blanks to create a dictionary of polynomial fits for degrees 1, 2, and 4, then evaluate degree 2 polynomial at x_new. Assume polyfit and polyval imported from numpy.

SciPy

coeffs = {1: [1](x, y, 1), 2: [2](x, y, 2), 4: [3](x, y, 4)}
y_new = polyval(coeffs[2], x_new)

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

Apolyfit

Dcurve_fit

Attempts:

3 left

💡 Hint

Common Mistakes

Using curve_fit for polynomial fitting.

Mixing different fitting functions.

Use polyfit for all polynomial fits. Then use polyval to evaluate the polynomial.