python,numpy,scipy,interpolate

By default, RectBivariateSpline uses a degree 3 spline. By providing only 3 points along the y-axis it cannot do that. Adding ky=2 to the argument list fixes the problem, as does having more data.

java,javafx,transition,equivalent,interpolate

I'd use java.util.Timer for that. You can give it a TimerTask (basically a Runnable) that it will execute every x ms (its period). It also runs on a background thread, which I assume is what you meant with asynchronously? API: http://docs.oracle.com/javase/8/docs/api/java/util/Timer.html...

d3.js,three.js,smooth,interpolate

I've found the answer. With tween.js, i can do something very close to interpolate("basis") -> D3.js CatmullRom is the answer and the link is here -> array interpolation. More information about CatmullRom here...

python,scipy,nearest-neighbor,interpolate

When the data is 1-dimensional, griddata defers to interpolate.interp1d: if ndim == 1 and method in ('nearest', 'linear', 'cubic'): from .interpolate import interp1d points = points.ravel() ... ip = interp1d(points, values, kind=method, axis=0, bounds_error=False, fill_value=fill_value) return ip(xi) So even though method='nearest' griddata will not extrapolate since interp1d behaves this way....

r,ggplot2,geospatial,interpolate

The problem is that akima::interp does not fill in every entry. So as you look in the only one "corner" of your data, you only see NA's. You need to "scroll down" to see the interpolated values. It only fills in the region where there is data: library(akima) # should...

No, I don't think this indicates that there is any sort of problem with using interpn, or any of the other MATLAB interpolation functions. Over the last few releases MathWorks has been introducing some new/better functionality for interpolation (for example the griddedInterpolant, scatteredInterpolant and delaunayTriangulation classes). This has been going...

If you were willing to impute by finding the nearest neighbor and using its value, I think the trick would be to use an efficient nearest neighbors implementation that allows you to find the nearest neighbor among n alternatives in O(log(n)) time. The k-d tree provides this sort of performance,...

python,pandas,linear,interpolate

Pandas' method='linear' interpolation will do what I call "1D" interpolation If you want to interpolate a "dependent" variable over an "independent" variable, make the "independent" variable; i.e. the Index of a Series, and use the method='index' (or method='values', they're the same) In other words: pd.Series(index=df.size, data=df.cost.values) #Make size the independent...

I'd try to unstack the data frame at the OptionType level of index. df.unstack(level=1) This way you should obtain a single index dataframe which will have both call and put categories moved to columns. Maybe it's not the most elegant way of solving the problem, but it should work things...

arrays,matlab,statistics,graphing,interpolate

I'm going to take a stab at this, although you really do need to provide a real working example of your code and an actual version of the input data that throws the error. The code and data you posted work just fine: f = 2.95 3.325 3.9 3.95 The...

matlab,interpolation,interpolate,function-interposition

Your computations are correct, but you are not plotting the function the right way. The blue line in your generated plot is piecewise linear. That's because you are only evaluating your polynomial p at the interpolation points x2. The plot command then draws line segments between those points and you...

You have the number of positions between the points, and then you have the current position. Think of mu as a percentage of the linear distance between the first point and the second that is determined by the current position, and the total number of positions. That is: mu =...

python,arrays,interpolation,indices,interpolate

Does Numpy interp do what you want?: import numpy as np x = [0,1,2] y = [2,3,4] np.interp(0.56, x, y) Out[81]: 2.56 ...