interpolation

I've got a dataframe with the following information: filename val1 val2 t 1 file1.csv 5 10 2 file1.csv NaN NaN 3 file1.csv 15 20 6 file2.csv NaN NaN 7 file2.csv 10 20 8 file2.csv 12 15 I would like to interpolate the values in the dataframe based on the indices, but only within each file group . To interpolate, I would normally do df = df.interpolate(method="index") And to group, I do grouped = df.groupby("filename") I would like the interpolated dataframe to look like this: filename val1 val2 t 1 file1.csv 5 10 2 file1.csv 10 15 3 file1.csv 15 20 6 file2.csv NaN NaN 7 file2.csv 10 20 8 file2

I'm currently working on an little project in C++ and OpenGL and am trying to implement a colour selection tool similar to that in photoshop, as below. However I am having trouble with interpolation of the large square. Working on my desktop computer with a 8800 GTS the result was similar but the blending wasn't as smooth. This is the code I am using: GLfloat swatch[] = { 0,0,0, 1,1,1, mR,mG,mB, 0,0,0 }; GLint swatchVert[] = { 400,700, 400,500, 600,500, 600,700 }; glVertexPointer(2, GL_INT, 0, swatchVert); glColorPointer(3, GL_FLOAT, 0, swatch); glDrawArrays(GL_QUADS, 0, 4); Moving onto my

I have read an article about difference between property and attribute bindings. From what I understood, most of the time, Angular2 prefers property bindings, because after each change in data, the DOM would be updated. (If I am mistaken, please correct me). I have a custom component and use it from the parent component. In it, I have an @Input named truevalue . when I initiate truevalue from the parent via property binding, sometimes, it does not change. I used following code: <my-checkbox [(ngModel)]="chkItems" [disabled]="!editMode" [trueValue]="Y"></my-checkbox> If I send true or "1" into

Users, I'd like to have some tips for a ternaryplot ("vcd"). I have this dataframe: a <- c(0.1, 0.5, 0.5, 0.6, 0.2, 0, 0, 0.004166667, 0.45) b <- c(0.75,0.5,0,0.1,0.2,0.951612903,0.918103448,0.7875,0.45) c <- c(0.15,0,0.5,0.3,0.6,0.048387097,0.081896552,0.208333333,0.1) d <- c(500,2324.90,2551.44,1244.50, 551.22,-644.20,-377.17,-100, 2493.04) df <- data.frame(a, b, c, d) and I'm building a ternary plot: ternaryplot(df[,1:3], df$d) How can I map the continuous variable d , obtaining a result similar to this one? This is probably not the most elegant way to do this but it works (from scratch and

I would like to perform blinear interpolation using python. Example gps point for which I want to interpolate height is: B = 54.4786674627 L = 17.0470721369 using four adjacent points with known coordinates and height values: n = [(54.5, 17.041667, 31.993), (54.5, 17.083333, 31.911), (54.458333, 17.041667, 31.945), (54.458333, 17.083333, 31.866)] z01 z11 z z00 z10 and here's my primitive attempt: import math z00 = n[0][2] z01 = n[1][2] z10 = n[2][2] z11 = n[3][2] c = 0.016667 #grid spacing x0 = 56 #latitude of origin of grid y0 = 13 #longitude of origin of grid i = math.floor((L-y0)/c) j =

I am currently trying to convert colours between RGB (red, green, blue) colour space and RYB (red, yellow, blue) colour space and back again. Based on the details in the following paper, I am able to convert from RYB to RGB using trilinear interpolation - where the parametric weightings (s,t,u) are the RYB colors, and the vertices of the cube are 3d points in RGB space. Paint Inspired Color Mixing and Compositing for Visualisation - Gossett and Chen - Section 2.1 - Realization Details My difficulties are in reversing the conversion process. A second paper references the use of this technique