Comments (4)
@GParolini could help out with this issue (see scikit-image/scikit-image#7330 (comment)). Many thanks to her!
from image-processing.
I would personally favor this change for several reasons, but I would like it to be something the curriculum advisory committee encourage for the carpentries as a whole rather than just this lesson. As @JeremyPike surmised, that line was originally added as a hack to eliminate the need to scroll to the top of the jupyter file every time you displayed a new image. Perhaps there is another way to accomplish that without using an oo style line, and retain the r-style if that is what the CAC ultimately favored.
I think during the move to beta we assumed this was like a 201 level carpentries workshop building on what they learned previously, so retaining the ggplot style they likely learned from more introductory carpentries workshops would be a good thing as it eliminates some cognitive load as they grapple with many other new concepts. New learners might also feel like they are just being asked to unlearn what they just learned.
I assume the introductory lessons adopt the ggplot approach because it is seen as slightly less complicated, especially for a subset that used ggplot with R, but I think front loading them with a little bit more will be worth it in the long run because I always encourage workshop attendees to use https://matplotlib.org/stable/gallery/ as a means to jumpstart their own plotting, and it relies almost exclusively on oo method when it is not using SNS or some other wrapper library.
from image-processing.
I believe that we should use the "object-oriented (OO) style" throughout the lesson, since we have created figure and axis objects. At the moment, we are mixing up the OO-style with the pyplot-style. For instance, 328d544 adds figure and axis objects, but we still have all the pyplot-style legacy. I would change, e.g.,
I personally would also favor @mkcor's suggestion. I think the current mix-up is due to the history of the lesson. Originally, the lesson used pyplot-style but when we transitioned to using Jupyter notebooks with %matplotlib widget
it became necessary to create fig and ax objects for each cell. On that note, when I recently taught the lesson, I realized that %matplotlib widget
does not suit certain platforms including Google Colab and Spyder. I intend to investigate alternatives when I find time.
from image-processing.
It seems we have (lazy) consensus and I would welcome a PR to address this across all episodes, whether from @mkcor or anyone else reading this who is willing to take the time.
@uschille please let us know what you discover regarding %matplotlib widget
. Perhaps a good discussion point at a Maintainer call soon?
from image-processing.
Related Issues (20)
- Ep3: Image not writeable HOT 6
- Ep3: Wrong file name `data/sudoku.jpg` HOT 5
- Ep3: iio.imread is unreliable HOT 8
- Convert sudoku.png image to pure RGB (without alpha channel) HOT 9
- Release new version of image dataset on FigShare HOT 2
- Use `uint8` or `float64` for grayscale images? HOT 1
- Using image as a variable name HOT 7
- Carpentries Workbench Transition HOT 22
- Showcase image processing at AUNZ community call HOT 7
- Links need to be fixed in CONTRIBUTING.md
- latest version of lesson using "import imageio.v3 as iio" causes error HOT 4
- 'code' folder should be re-established/replaced HOT 5
- Code snippet docstring formatting HOT 4
- Transition to new import convention for sckit-image? HOT 4
- Contributing guide should be customised further
- Ep 5 - Using a Mask for a Histogram exercise error in solution HOT 3
- Link to image publication & analysis checklists HOT 2
- Mask in episode 4 has no shadow HOT 1
- Add Exiftool in list of software that can help handle metadata
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from image-processing.