interpolation

Interpolating trajectory from unsorted array of 2D points where order matters

由 房东的猫 提交于 2019-12-01 09:47:31
问题 I need a way of obtaining a Lx2 trajectory from a Nx2 array of points, i.e. a way of connecting those points into a single trajectory (for example, create a 10000x2 array of points from a 5x2 array of points). I have tried using interp1 and interp2 but either I don't fully understand them or they don't do what I need. 回答1: It sounds like you need to be using interp1 in a loop (i.e. to preserve original order) interpolating between each consecutive pair of points: X = [10; 10.0001; 9; 48]; %//

spatial interpolation error using idw

由 爱⌒轻易说出口 提交于 2019-12-01 09:43:04
I am trying to spatially interpolate a dataset of seawater pH by lat & long: sample<-read.csv(file="Station locations 2016.csv", header=TRUE, sep=",", strip.white=T) head(sample) Station lat long pH 1 B17 -23.49174 152.0718 8.222411 2 B23 -23.49179 152.0718 8.199310 3 B26 -23.49182 152.0717 8.140428 4 B28 -23.49183 152.0717 8.100752 5 B30 -23.49185 152.0717 8.068141 6 B31 -23.49187 152.0717 8.048852 I have created a grid based on the existing ranges in lat/long data and want to interpolate the pH values so that I can produce a color-coded map of pH. The following code works until the spatial

Interpolate large irregular grid onto another irregular grid in Python

由 爷，独闯天下 提交于 2019-12-01 09:19:22
问题 I am trying to interpolate complex values from one irregular grid to another irregular grid using Python. The grids are in 2D and there are 103,113 data points. I am using Python 2.6.6, Scipy 0.7.2, Numpy 1.3.0, Matplotlib 0.99.3 In Matlab using griddata this is achieved in roughly 5 seconds. BnGRID2 = griddata(R_GRID1,Z_GRID1,BnGRID1,R_GRID2,Z_GRID2) (MATLAB) (Note all arrays are 201 x 513) However, if I try using matplotlib.mlab.griddata I get a memoryError even if I try to work with the

Interpolate and animate two svg path

由 走远了吗. 提交于 2019-12-01 09:03:18
问题 I have two svg path curves that I want to animate. I want that in 5 seconds dPathBefore becomes dPathNow with a smooth animation transition. That is my code: const dPathBefore = 'M 50 350 Q 150 0 200 250 Q 250 350 300 250 C 350 200 450 250 400 350 Z' const dPathNow = 'M 50 350 C 50 150 150 150 250 300 C 300 150 400 150 400 350 Z' export class PathAnimation extends React.Component { render() { return ( <svg width={500} height={400} className={'ba b--black'}> <path d={dPathBefore} fill={'cyan'}

Interpolate between 2 GPS locations based on walking speed

由 走远了吗. 提交于 2019-12-01 08:28:58
问题 Problem: Given two locations: L 1 = (latitude 1 , longitude 1 , timestamp 1 ) , L 2 = (latitude 2 , longitude 2 , timestamp 2 ) , and a configurable, but constant, movement speed: v = 1.39 meters per second (for instance). How can we interpolate between these two locations to estimate a users location as he travels from L 1 to L 2 ? I have been searching for solutions to this problem and so far I have found, that for small distances (away from the poles) linear interpolation can be used. So,

Python - Interpolation 2D array for huge arrays

由 倾然丶 夕夏残阳落幕 提交于 2019-12-01 08:05:32
I would like to interpolate 2D array "test" whose dimensions are 4x4 (just as example, in reality close to 1000x1000) with a grid of shape 8x8. import numpy as np X = np.arange(0,4,1) Y = np.arange(0,4,1) points = np.vstack((X,Y)) points = points.T #my coordinates #my values as a 2D array test = np.array([[ 1.2514318 , 1.25145821, 1.25148472, 1.25151133], [ 1.25087456, 1.25090105, 1.25092764, 1.25095435], [ 1.25031581, 1.25034238, 1.25036907, 1.25039586], [ 1.24975557, 1.24978222, 1.24980898, 1.24983587]]) I try with griddata but it seems work only 1D isnt it? as the errors tells me i have

Interpolating a 3d array in Python. How to avoid for loops?

由 笑着哭i 提交于 2019-12-01 06:37:12
问题 I have an array which I want to interpolate over the 1st axes. At the moment I am doing it like this example: import numpy as np from scipy.interpolate import interp1d array = np.random.randint(0, 9, size=(100, 100, 100)) new_array = np.zeros((1000, 100, 100)) x = np.arange(0, 100, 1) x_new = np.arange(0, 100, 0.1) for i in x: for j in x: f = interp1d(x, array[:, i, j]) new_array[:, i, j] = f(xnew) The data I use represents 10 years of 5-day averaged values for each latitude and longitude in

2D Array Interpolation

由 落爺英雄遲暮 提交于 2019-12-01 06:32:25
问题 i am currently working on a 3D game in c#. I have a 2 dimensional array called data where i get a z value for my x and y values. for example: data[x,y] = z; data[1,2] = 4; data[2,4] = 5; etc. my problem is that this is very vague and I also need the calculated (interpolated) values for example x=1.5 and y=2.5. How can I get to this value and are there any functions available? Thank you 回答1: Maybe Bilinear Interpolation can be used in your scenario: float fractionX = ... //the fraction part of

griddata runtime error — Python / SciPy (Interpolation)

由 寵の児 提交于 2019-12-01 06:19:17
问题 I use scipy's griddate-function for interpolation. What does the following error message means which appears when python is executing the griddata-function? File "C:\Python25\lib\site-packages\scipy\interpolate\ndgriddata.py", line 182, in griddata ip = LinearNDInterpolator(points, values, fill_value=fill_value) File "interpnd.pyx", line 192, in interpnd.LinearNDInterpolator.__init__ (scipy\interpolate\interpnd.c:2524) File "qhull.pyx", line 917, in scipy.spatial.qhull.Delaunay.__init__

Python - Interpolation 2D array for huge arrays

由 六眼飞鱼酱① 提交于 2019-12-01 05:30:58
问题 I would like to interpolate 2D array "test" whose dimensions are 4x4 (just as example, in reality close to 1000x1000) with a grid of shape 8x8. import numpy as np X = np.arange(0,4,1) Y = np.arange(0,4,1) points = np.vstack((X,Y)) points = points.T #my coordinates #my values as a 2D array test = np.array([[ 1.2514318 , 1.25145821, 1.25148472, 1.25151133], [ 1.25087456, 1.25090105, 1.25092764, 1.25095435], [ 1.25031581, 1.25034238, 1.25036907, 1.25039586], [ 1.24975557, 1.24978222, 1.24980898,
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