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Hi,
I tried to applied your [turotial](https://scikit-gstat.readthedocs.io/en/latest/tutorials/01_getting_started.html) to a personnal dataset (see attached both .csv dataset & script .ipynb
[test…
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Hi there!
First, thanks for all the work on scikit-gstat :+1:.
It's great and I'm very happy to see geostatistics emerging in Python!
I used `skgstat` quite a bit recently (moving away from R), c…
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Add option to sample_multirange_empirical_variogram():
Pick random point in raster + sample in rings of varying sizes to allow for a good distribution of samples for all distances and increase speed
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I'll open an issue, still no access to the project board. This is a *discussion* issue for the GS-Framework v2.
To bring gstools and scikit-gstat work well together I see a few avenues we could tak…
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**Submitting author:** @SimonMolinsky (Szymon Moliński)
**Repository:** https://github.com/szymon-datalions/pyinterpolate
**Branch with paper.md** (empty if default branch):
**Version:** v0.2.5.po…
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Sample the point pairs randomly to speed up handling of big datasets. Method:
* Repeat
* Sample datapoints
* Build & filter pairs
* Append pairs to total list of pairs
This way, it woul…
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I've been thinking a bit about the class structure and how things could/should be structured to make more optimizations possible, esp in the case where you have multiple variograms for different measu…
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Hi, I am Civil Engineering graduate student, I would like to use kriging to obtain the correlation and the surface between 2 laboratory input data and one laboratory result output data. However, I do …
ghost updated
3 years ago
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This is just a note, so we don't forget and can talk about it:
My proposal for default bining:
- number of bins calculated by either:
- (a) Sturges rule:
n_bins = 2 * np.log2(n_poi…
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So I'm trying to get up and running with this software, and I'm finding it rather difficult to produce a dirty ordinary kriging result. I learned geostats/kriging using SGeMS and I'm realizing much of…