Patowhiz
commented
5 months ago I'd like to add there are 3 common mapping tools used in African NMHS and Regional centers; ArcGIS, CDT and GeoClim.
The users I have asked have given me the following reasons for using these 3 tools:
- ArcGIS is good at giving high quality maps.
- CDT is good in giving blended spatial data.
- GeoClim is easy to use when it comes to Climate spatial data.
So when working on maps, I think it's good we evaluate the above 3 products and learn from their strengths. I intend to evaluate ArcGIS and GeoClim.
This issue is initially not for R-Instat. But it is an analysis that R-Instat users should be able to draw on.
The task is first to document the code used by @dannyparsons that uses R (presumably RStudio) to read netcdf files, of daily data (gridded data), produce summaries, such as annual totals, or means or total number of rain days, or mean rain per rain day. Then produce a map of the results.
In its current form it does not use R-Instat, partly because R-Instat is limited to problems that involve data frames, and I think this analysis does not - and indeed it is not practical to put the data into data frames as the starting point.
It may be that this is an example of an analysis that is not possible in or using just R-Instat. That's fine, as it is important to be realistic about the limite of any tool. In that case R-Instat users simply need to use RStudio for those problems. It may be that there is a way to use R-Instat later, perhaps simply using an R script from R-Instat. We can now run multiple instances of R-Instat, so perhaps we just leave it to run. But let's start with RStudio, to simply follow the analyses done by Danny.