Browsing the web I've found that some tools to use Kriging in Python are pyKriging and Gaussian Process Regression. However, I couldn't make any of them to work. The first one doesn't work for me (...

My source data files are weather radar images captured every 15 minutes. I'm trying to make a smooth interpolation of intermediate frames and I'm trying to extrapolate the motion onwards from the l...

I'm using opencv remap function to map an image to another coordinate system. However, my initial tests indicate that there are some issues with the interpolation. Here, I give a simple example of...

I have many lines of georeferenced hydrological data with weekly resolution: Station name, Lat, Long, Week 1 average, Week 2 average ... Week 52 average Unfortunately, I also have some data with ...

I have a 2-dimensional array of data, with some missing values. There are three columns: x y intensity I can plot x against y in ggplot2, with intensity as a colour scale. I’d like to smooth...

I am a Geologist needing to create few hundred consistent contour maps in a project with varying x y z data sets. Contouring irregular x y z data points involves creation of a 'grid' of interpolat...

This question was edited after answers for show final solution I used I have unstructured 2D datasets coming from different sources, like by example: Theses datasets are 3 numpy.ndarray (X, Y co...

I have been struggling to inteprolate the data for "empty" pixels in my 2D matrix. Basically, I understand (but not deeply) interpolation techniques such as Inverse Distance Weighting, Krigin...

I have survey data of species richness that was taken at various sites in the Chesapeake Bay, USA, and I would like to graphically present the data as a "heat map." I have a dataframe of lat/long ...

I am relatively new to ggplot, so please forgive me if some of my problems are really simple or not solvable at all. What I am trying to do is generate a "Heat Map" of a country where the filling ...