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wildintellect commented on 2024-04-25T23:27:09Z
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"for to" probably "to"?

"within the memory limits of the notebook"? Is this really the notebook memory or the Jupyter instance memory? Also can we clarify that Dask is being used to parallel compute with local dask cluster, hence the memory limits of running instance matter.

I find the Downsample and Coarsen terminology a little foreign (seems like other tools might call this something else).

Coarsen aka aggregate?

Downsample aka Sub-select?

Is this still using Datashader? The calls below only use hvplot now (directly)

jsignell commented on 2024-04-26T12:59:47Z
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Yeah I didn't touch the language in this PR, but these are good thoughts. I can try to make it clearer. It is still using datashader, it's just internal now (via the rasterize kwarg)

jsignell commented on 2024-05-01T19:12:38Z
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I think aggregate implies that the whole dimension will be collapsed. So I left "coarsening"

wildintellect commented on 2024-05-01T20:13:42Z
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I think this is just a terminology difference with GIS uers

https://pro.arcgis.com/en/pro-app/3.1/tool-reference/data-management/resample.htm <- aggregate

https://rspatial.github.io/terra/reference/aggregate.html

GDAL doesn't even differentiate and just calls it resampling https://gis.stackexchange.com/a/262318 though users clearly call it downsampling

I see why it gets confusing in GRASS r.resample like GDAL, but if it's time it's t.rast.aggregate

jsignell commented on 2024-05-01T20:41:56Z
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I also decided downsample was correct for the time dimension. I think the name is based off the resample method in xarray (and pandas) then there is "upsample" for when you end up with more values than you started with, and "downsample" for when you end up with fewer. To me subselect should more like taking an aoi or a particular month. More like taking a piece of the data with the existing resolution rather than changing the resolution. Obviously you can use select to change the step, but that's not what first comes to my mind.

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wildintellect commented on 2024-04-25T23:27:10Z
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Use a markdown Note block?

jsignell commented on 2024-04-26T13:00:08Z
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👍

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wildintellect commented on 2024-04-25T23:27:10Z
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bold mean so it's clear that's the function being used to coarsen/aggregate the data

jsignell commented on 2024-04-26T13:01:38Z
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👍

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wildintellect commented on 2024-04-25T23:36:16Z
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Didn't you drop GeoViews in favor of HVplot?

jsignell commented on 2024-04-26T13:01:25Z
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yeah similar to the datashader it is being used internally, but I agree that in the text needs an update.

Yeah I didn't touch the language in this PR, but these are good thoughts. I can try to make it clearer. It is still using datashader, it's just internal now (via the rasterize kwarg)

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👍

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yeah similar to the datashader it is being used internally, but I agree that in the text needs an update.

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👍

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I think aggregate implies that the whole dimension will be collapsed. So I left "coarsening"

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I think this is just a terminology difference with GIS uers

https://pro.arcgis.com/en/pro-app/3.1/tool-reference/data-management/resample.htm <- aggregate

https://rspatial.github.io/terra/reference/aggregate.html

GDAL doesn't even differentiate and just calls it resampling https://gis.stackexchange.com/a/262318 though users clearly call it downsampling

I see why it gets confusing in GRASS r.resample like GDAL, but if it's time it's t.rast.aggregate

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I also decided downsample was correct for the time dimension. I think the name is based off the resample method in xarray (and pandas) then there is "upsample" for when you end up with more values than you started with, and "downsample" for when you end up with fewer. To me subselect should more like taking an aoi or a particular month. More like taking a piece of the data with the existing resolution rather than changing the resolution. Obviously you can use select to change the step, but that's not what first comes to my mind.

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@wildintellect ready for another look