spectral | flexible JSON/YAML linter | REST library

I'm trying to use Skimage to segment an image with watershed, but I always get this error. Do you have a solution please?

AttributeError: module 'skimage.morphology' has no attribute 'watershed'

Source code : https://scikit-image.org/docs/0.12.x/auto_examples/xx_applications/plot_coins_segmentation.html

I have the following problem. I want to build a model for landcover classification. My data are multitemporal Remote Sensing data with several bands. For training I created stratified randomly distributed points to extract spectral data at their positions. With these data a Random Forrest (Rpart) was trained using mlr3 package. For accuracy measurement a repeated spatial cross validation using mlr3spatiotempcv was performed. The resulting model of the training step is, after extraction, stored in an R Object of type rpart. In the terms field of this object are the variable names stored. These are all my used bands but also the spatial x and y coordinates. This brings problems when predicting new data. I used terra package and got an error the x and y layer are missing in my input data. Which kind of makes sense because they are stored in the terms field of the model. But from my understanding, the coordinates should not be a variable of the model. The coordinates are just used for spatial resampling and not for predicting. I "solved" this problem by removing x and y coordinates during the training process and perform just an ordinary non-spatial cross validation. After that I performed the prediction and it works perfectly.

So, my Question is, how can I train a model, using mlr3 package, with data containing coordinates, to perform spatial cross validation?, and then use this model to predict a new Raster.

I am working on a code of a stacked histogram and I need help arranging the bins in the order if this is possible.

I do different plots with ggplot2 and want them all to have the same colour. The thing is that I use different geoms that sometimes work with fill and sometimes with col. See here:

I want to create color legend using linear gradient > https://bl.ocks.org/HarryStevens/6eb89487fc99ad016723b901cbd57fde . But how can I pass my d3 colors here because its in the form like d3.scaleSequential(d3.interpolateViridis).domain([0,1]). In linear gradient the colors are passed as below :

I'm looking to write a function that takes an audio signal (assuming it contains a single instrument playing), out of which I would like to extract the instrument-like features out of the audio and into a vector space. So in theory, if I had two signals with similar-sounding instruments (such as two pianos), their respective vectors should be fairly similar (by euclidian distance/cosine similarity/etc.). How would one go about doing this?

What I've tried: I'm currently extracting (and temporally averaging) the chroma energy, spectral contrast, MFCC (and their 1st and 2nd derivatives), as well as the Mel spectrogram and concatenating them into a single representation vector:

I created a script that reads and plots .txt files and their content (numbers/values). Each .txt file is located in a different folder. Each folder, in turn, represents one subject from which the data stems.

This code works fine. Python reads each single .txt. file and plots 23 individual graphs/lines into one single plot. Python uses some standard colors here, i.e., each graph is automatically presented in a different color.

What I would like to do is the following: Instead of using the standard colors that are assigned by python automatically without adding any color related code, I would like to use a specific colormap (for example "plasma") from matplotlib.

The problem: no matter what code from the internet I use, all graphs/lines/subjects always receive the same color (e.g. the first color or last color from the plasma colormap).

How do I specify the code so that every line gets one distinct color from a colormap of choice?

Here is my code:

I've got a time series of sunspot numbers, where the mean number of sunspots is counted per month, and I'm trying to use a Fourier Transform to convert from the time domain to the frequency domain. The data used is from https://wwwbis.sidc.be/silso/infosnmtot. The first thing I'm confused about is how to express the sampling frequency as once per month. Do I need to convert it to seconds, eg. 1/(seconds in 30 days)? Here's what I've got so far:

In ggplot2/geom_tile, how to change fill color whice exceed the limits？ As the image, Region_4/5 are out of limis(1,11) , so the fill color is default grey, how to change 'Region_4' to 'darkblue', 'Region_5' to 'black' . Thanks!