interpolation

Eliminate sudden additions/deletions in D3 basis line chart transition

由 為{幸葍}努か 提交于 2019-12-10 10:57:28
问题 I have exactly similar SO question Eliminate sudden additions/deletions in D3 line chart transition One difference is that, I have line interpolated as "basis" var line = d3.svg.line().interpolate('basis') Struggling with this exactly 13 hours :/ please help <html> <head> <title>Chart</title> <style> path { stroke: #f00; } .line { stroke: #0f0; fill: none; stroke-width: 2px; } .rule { stroke: #ccc; stroke-width: 1px; } </style> </head> <body> <p>I want to get the chart below to transition

interpolate points on a height map

由 心已入冬 提交于 2019-12-10 10:46:46
问题 I have some values (bytes) over a plane evenly distributed (the come from real measures) like for instance temperature. I'm trying to generate the whole surface. But I'm not successful. The main condition is that the number and position of the points will not be known and that the surface MUST keep the value in the points where is measured and the points in between will be interpolated. Ideally, if only one point is set the final surface should be a mountain. By the way, and just in the case

Explanation of Interpolate Hermite method

由 前提是你 提交于 2019-12-10 10:35:42
问题 I've currently got this bounty running on how to resample audio data with the intention of increasing the pitch. Many solutions have been made and I have to admit I'm feeling a bit overwhelmed by the choices and information. I was directed to this solution and found this chunk of code: public static float InterpolateCubic(float x0, float x1, float x2, float x3, float t) { float a0, a1, a2, a3; a0 = x3 - x2 - x0 + x1; a1 = x0 - x1 - a0; a2 = x2 - x0; a3 = x1; return (a0 * (t * t * t)) + (a1 *

Pandas: interpolation where first and last data point in column is NaN

由 给你一囗甜甜゛ 提交于 2019-12-10 10:27:44
问题 I would like to use the interpolate function, but only between known data values in a pandas DataFrame column. The issue is that the first and last values in the column are often NaN and sometimes it can be many rows before a value is not NaN: col 1 col 2 0 NaN NaN 1 NaN NaN ... 1000 1 NaN 1001 NaN 1 <----- 1002 3 NaN <----- only want to fill in these 'in between value' rows 1003 4 3 ... 3999 NaN NaN 4000 NaN NaN I am tying together a dataset which is updated 'on event' but separately for

How do I create a new scale() function in d3.js? I would like to create a cumulative distribution function

由 大憨熊 提交于 2019-12-10 10:17:20
问题 How do I create my own scale() function in d3? I am trying to replace the nice linear scale in d3 d3.scale.linear() with a different function that I would like to create myself. My new scale would be based on a cumulative distribution function, so that the median value would appear in the center of the x axis, and a value that was two standard deviations from the median would appear twice as far from the center of the x axis as something that was one standard deviation from the mean. Here is

Angular 2 binding within binding. Interpolation within event

由 落爺英雄遲暮 提交于 2019-12-10 03:38:39
问题 Trying to do the following and getting "Got interpolation ({{}}) where expression was expected" error. <ul> <li *ngFor="#item of items"> <a href='' (click)="foo('{{item.name}}')">{{item.name}}</a> </li> </ul> Thanks! 回答1: Don't use {{}} (interpolation) inside any event handler code (on a view), do pass expression directly which will get evaluated against Component context( this ), like over here you're trying to pass item.name to foo function. So removing {{}} parenthesis would do the trick.

How to improve performance when interpolating on 3d data with SciPy

由 馋奶兔 提交于 2019-12-09 18:50:10
问题 I have 3d-data representing the atmosphere. Now I want to interpolate this data to a common Z coordinate (what I mean by that should be clear from the function's doctring). The following code works fine, but I was wondering if there were a way to improve the performance ... def interpLevel(grid,value,data,interp='linear'): """ Interpolate 3d data to a common z coordinate. Can be used to calculate the wind/pv/whatsoever values for a common potential temperature / pressure level. grid : numpy

Sparse Matrix Interpolation With MATLAB

由 独自空忆成欢 提交于 2019-12-09 11:31:01
问题 If I have a matrix like this A = [1 2; 3 4]; I can use interp2 to interpolate it like this newA = interp2(A,2); and I get a 5x5 interpolated matrix. But what if I have a matrix like this: B = zeros(20); B(3,2) = 5; B(17,4) = 3; B(16, 19) = 2.3; B(5, 18) = 4.5; How would I interpolate (or fill-in the blanks) this matrix. I've looked into interp2 as well as TriScatteredInterp but neither of these seem to fit my needs exactly. 回答1: A good solution is to use my inpaint_nans. Simply supply NaN

Stretching out an array

由 风格不统一 提交于 2019-12-09 10:32:17
问题 I've got a vector of samples that form a curve. Let's imagine there are 1000 points in it. If I want to stretch it to fill 1500 points, what is the simplest algorithm that gives decent results? I'm looking for something that is just a few lines of C/C++. I'll always want to increase the size of the vector, and the new vector can be anywhere from 1.1x to 50x the size of the current vector. Thanks! 回答1: Here's C++ for linear and quadratic interpolation. interp1( 5.3, a, n ) is a[5] + .3 * (a[6]

Contour plot data (lat,lon,value) within boundaries and export GeoJSON

由 你离开我真会死。 提交于 2019-12-09 07:18:32
问题 I'm trying to interpolate data within boundaries and plot contour lines (polygons) based on Latitude, longitude, value data from csv files. Results I want print as geojson. I'm stuck on the basic contour plot from csv. I really appreciate help here. This is what I got in this moment but can't make it work. import numpy as np import matplotlib.pyplot as plt data = np.genfromtxt('temp.csv', delimiter=',') x = data[:1] y = data[:2] [x,y] = meshgrid(x,y); z = data[:3]; plt.contour(x,y,z) plt.show
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