Till Korten

It would be great to implement the [skimage.filters.sato](https://scikit-image.org/docs/stable/api/skimage.filters.html#skimage.filters.sato) filter in pyclesperanto. the filter takes an image and a range of sigmas (by default `range(1,10,2)`) It then calculates the hessian matrix...

it would be great if down-scaling would also de-noise the data at the same time. hence, a cle.average_pooling see [skimage.transform.downscale_local_mean](https://scikit-image.org/docs/stable/api/skimage.transform.html#skimage.transform.downscale_local_mean)

added standard error of the mean to statistics_of_labelled_pixels

4

I think this should calculate the SEM, but please double check. If I read the code correctly, this automagically adds SEM also to `statistics_of_background_and_labelled_pixels`

standard deviation vs. standard error of the mean

3

Some feature extraction functions return the standard deviation (STD). In some cases (i.e. when you want to know the accuracy of your measurement rather than the variance of your data)...

Recommendation to remove index 9 for a 9-element list

3

On slides 5 - 18 and 23-24 of [Python_data_structures.pdf](https://github.com/BiAPoL/Bio-image_Analysis_with_Python/blob/main/02_python_data_structures/Python_data_structures.pdf), there is a 9-element list ("A" - "I") as an example for indexing: I recommend to remove the index number 9:

open source & open access

1

maybe emphasize more what **the students** get out of making their code open source and their data openly accessible.

From the back, I often have difficulties reading the text on the slides - in particular on text-heavy slides. I would try to reduce the amount of text where possible...

screenshots with black background are hard to read on a beamer

2

the contrast in the screenshots with black background is not very good - on a beamer some parts are impossible to read (equal signs in particular disappear completely

Statistics session comments

1

When we mention filtering a pandas table, also mention, that the criteria should be independent of the thing that you are filtering. Wrong: ```python pd['area, pd['area'] > 5].mean() ``` likely...

refactored into a python package

3

created pyproject.toml and refactored the code into an installable python package. the code can be installed like this: ```bash git clone ... cd Time-Series-Library pip install -e . ``` afterwards...