linear-interpolation

I am trying to create a heat map with python. For this I have to assign an RGB value to every value in the range of possible values. I thought of changing the color from blue (minimal value) over green to red (maximal value). The picture example below explains how I thought of the color composition: We have a range from 1 (pure blue) to 3 (pure red), 2 is in between resembled by green. I read about linear interpolation and wrote a function that (more or less) handles the calculation for a certain value in the range between a minimum and a maximum and returns an RGB tuple. It uses if and elif

Is there a simple, efficient way to implement a piecewise linear integer-to-integer curve interpolation in C# (for Unity3D, if it matters) ? Details are as follows: The piecewise linear curve representation has to be built over time. The first interpolation request comes before we have all data points The curve is strictly monotonous The first point is always (0, 0) The data points' first coordinates are also strictly monotonous w.r.t arrival time, i.e. the points are naturally ordered by their first coordinate. The data points are not in ranges that would cause cause overflow problems for 4

I have a time series problem which I hope someone can help with! The problem revolves around two sets of data with different time stamps. One set of data contains calibration data, the other contains sample data. The calibration is much less frequent than the samples. What I would like to do is interpolate the calibration data (low freq) onto the sample time series (high freq). sam <- textConnection("time, value 01:00:52, 256 01:03:02, 254 01:05:23, 255 01:07:42, 257 01:10:12, 256") cal <- textConnection("time, value 01:01:02, 252.3 01:05:15, 249.8 01:10:02, 255.6") sample <- read.csv(sam)

I have a time series in pandas that looks like this: Values 1992-08-27 07:46:48 28.0 1992-08-27 08:00:48 28.2 1992-08-27 08:33:48 28.4 1992-08-27 08:43:48 28.8 1992-08-27 08:48:48 29.0 1992-08-27 08:51:48 29.2 1992-08-27 08:53:48 29.6 1992-08-27 08:56:48 29.8 1992-08-27 09:03:48 30.0 I would like to resample it to a regular time series with 15 min times steps where the values are linearly interpolated. Basically I would like to get: Values 1992-08-27 08:00:00 28.2 1992-08-27 08:15:00 28.3 1992-08-27 08:30:00 28.4 1992-08-27 08:45:00 28.8 1992-08-27 09:00:00 29.9 However using the resample

If linear interpolation happens during the rasterization stage in the OpenGL pipeline, and the vertices have already been transformed to screen-space, where does the depth information used for perspectively correct interpolation come from? Can anybody give a detailed description of how OpenGL goes from screen-space primitives to fragments with correctly interpolated values? The output of a vertex shader is a four component vector, vec4 gl_Position . From Section 13.6 Coordinate Transformations of core GL 4.4 spec: Clip coordinates for a vertex result from shader execution, which yields a

Say I am given data as follows: x = [1, 2.5, 3.4, 5.8, 6] y = [2, 4, 5.8, 4.3, 4] I want to design a function that will interpolate linearly between 1 and 2.5 , 2.5 to 3.4 , and so on using Python. I have tried looking through this Python tutorial , but I am still unable to get my head around it. As I understand your question, you want to write some function y = interpolate(x_values, y_values, x) , which will give you the y value at some x ? The basic idea then follows these steps: Find the indices of the values in x_values which define an interval containing x . For instance, for x=3 with