Error function (erf) in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the error function from scipy.special.

SciPy

from scipy.special import [1]

result = erf(1.0)
print(result)

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

Aerror_function

Berror_func

Cerf

Dspecial_erf

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to import a non-existent function name like 'error_func'.

Using a wrong module instead of scipy.special.

The error function is named erf in scipy.special. You import it directly by that name.

2fill in blank

medium

Complete the code to calculate the error function value for 0.5.

SciPy

from scipy.special import erf

value = erf([1])
print(value)

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

A0.5

B1.0

C2.0

D-0.5

Attempts:

3 left

💡 Hint

Common Mistakes

Using 1.0 or 2.0 instead of 0.5.

Passing a negative value when positive was asked.

The error function is calculated at the input value 0.5 as requested.

3fill in blank

hard

Fix the error in the code to correctly compute the error function for an array of values.

SciPy

import numpy as np
from scipy.special import erf

arr = np.array([0, 0.5, 1.0])
result = [1](arr)
print(result)

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

Aerror_func

Berf_array

Cspecial_erf

Derf

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent function name like 'error_func'.

Trying to call a method that does not exist on numpy arrays.

The correct function to compute the error function is erf. It works element-wise on numpy arrays.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps numbers to their error function values for numbers greater than 0.

SciPy

from scipy.special import erf

numbers = [-1, 0, 0.5, 1]
erf_values = {num: [1](num) for num in numbers if num [2] 0}
print(erf_values)

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

Aerf

B>

C<

Dabs

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' in the condition.

Using 'abs' instead of 'erf' for the function.

The dictionary comprehension uses erf to compute values and filters numbers greater than zero with >.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps the uppercase string of numbers to their error function values if the value is positive.

SciPy

from scipy.special import erf

numbers = {'a': 0.5, 'b': -0.5, 'c': 1.0}
erf_dict = { [1]: [2] for key, val in numbers.items() if val [3] 0 }
print(erf_dict)

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Akey.upper()

Bval

C>

Derf(val)

Attempts:

3 left

💡 Hint

Common Mistakes

Using val instead of erf(val) for the dictionary values.

Not converting keys to uppercase.

Using '<' instead of '>' in the condition.

The dictionary keys are uppercase versions of the original keys, the values are the error function of val, and the condition filters positive values with >.