Skip to content

Separate the function writing challenge into two challenges #127

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
andrewgait merged 2 commits into from
Nov 13, 2026
Merged

Separate the function writing challenge into two challenges #127

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
f272e1a
Separate the function writing challenge into two challenges
andrewgait Nov 13, 2026
ffbb849
Remove extraneous closing line
andrewgait Nov 13, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
26 changes: 17 additions & 9 deletions episodes/03-numpy_essential.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -183,12 +183,6 @@ where **x** is an array, **µ** is the position of the centre of the curve/peak
1. Create a function called `gauss` which will take three arguments (inputs):
**x**, **µ**, and **σ**,
as defined above. *Hint*: you may wish to use the NumPy constant `pi`, and NumPy functions `square`, `sqrt` and `exp` for calcuating the square, square-root and exponential of **e** respectively for all elements in an array.
2. Create a NumPy array using the Numpy function `linspace` which will contain 1000
points equally spaced between **x**=-100 and **x**=100. *Hint*: You can print the help
documentation of a function with 'help(name\_of\_the\_function)'.
3. Using the above gauss function and the array, create an array which contains the values
of the Gaussian from **x**=-100 to **x**=100.
4. Use the 'matplotlib' library to plot the curve with **µ**=0 and **σ**=10.

::::::::::::::: solution

Expand All @@ -203,9 +197,23 @@ def gauss(x, mu=0, sigma=1):

:::::::::::::::::::::::::

::::::::::::::::::::::::::::::::::::::::::::::::::


::::::::::::::::::::::::::::::::::::::: challenge

## Using your Gaussian Function

1. Create a NumPy array using the Numpy function `linspace` which will contain 1000
points equally spaced between **x**=-100 and **x**=100. *Hint*: You can print the help
documentation of a function with 'help(name\_of\_the\_function)'.
2. Using the above gauss function and the array, create an array which contains the values
of the Gaussian from **x**=-100 to **x**=100.
3. Use the 'matplotlib' library to plot the curve with **µ**=0 and **σ**=10.

::::::::::::::: solution

## challenge 2:
## challenge 1:

```python
x = np.linspace(-100, 100, 1000)
Expand All @@ -215,7 +223,7 @@ x = np.linspace(-100, 100, 1000)

::::::::::::::: solution

## challenge 3:
## challenge 2:

```python
mu = 0 # the position of the center of the peak
Expand All @@ -227,7 +235,7 @@ g = gauss(x, mu, sigma)

::::::::::::::: solution

## challenge 4:
## challenge 3:

```python
plt.plot(x, g)
Expand Down
Loading