interpolation

Swift String Interpolation displaying optional?

由 我是研究僧i 提交于 2019-11-27 03:55:05
问题 When i use the following code and have nameTextField be "Jeffrey" (or any other name) @IBAction func helloWorldAction(nameTextField: UITextField) { nameLabel.text = "Hello, \(nameTextField.text)" } nameLabel displays... Hello, Optional("Jeffrey") But, when I change the previous code to include a "!" like this: @IBAction func helloWorldAction(nameTextField: UITextField) { nameLabel.text = "Hello, \(nameTextField.text!)" } The code works as expected and nameLabel displays.... Hello, Jeffrey Why

In Ruby, can you perform string interpolation on data read from a file?

由 允我心安 提交于 2019-11-27 03:45:12
问题 In Ruby you can reference variables inside strings and they are interpolated at runtime. For example if you declare a variable foo equals "Ted" and you declare a string "Hello, #{foo}" it interpolates to "Hello, Ted" . I've not been able to figure out how to perform the magic "#{}" interpolation on data read from a file. In pseudo code it might look something like this: interpolated_string = File.new('myfile.txt').read.interpolate But that last interpolate method doesn't exist. 回答1: Instead

Interpolation over an irregular grid

由 自作多情 提交于 2019-11-27 03:41:28
So, I have three numpy arrays which store latitude, longitude, and some property value on a grid -- that is, I have LAT(y,x), LON(y,x), and, say temperature T(y,x), for some limits of x and y. The grid isn't necessarily regular -- in fact, it's tripolar. I then want to interpolate these property (temperature) values onto a bunch of different lat/lon points (stored as lat1(t), lon1(t), for about 10,000 t...) which do not fall on the actual grid points. I've tried matplotlib.mlab.griddata, but that takes far too long (it's not really designed for what I'm doing, after all). I've also tried scipy

Spline Interpolation with Python

由 你离开我真会死。 提交于 2019-11-27 03:20:34
问题 I wrote the following code to perform a spline interpolation: import numpy as np import scipy as sp x1 = [1., 0.88, 0.67, 0.50, 0.35, 0.27, 0.18, 0.11, 0.08, 0.04, 0.04, 0.02] y1 = [0., 13.99, 27.99, 41.98, 55.98, 69.97, 83.97, 97.97, 111.96, 125.96, 139.95, 153.95] x = np.array(x1) y = np.array(y1) new_length = 25 new_x = np.linspace(x.min(), x.max(), new_length) new_y = sp.interpolate.interp1d(x, y, kind='cubic')(new_x) but I am getting: ValueError: A value in x_new is below the

Multivariate spline interpolation in python/scipy?

由 半世苍凉 提交于 2019-11-27 03:12:15
Is there a library module or other straightforward way to implement multivariate spline interpolation in python? Specifically, I have a set of scalar data on a regularly-spaced three-dimensional grid which I need to interpolate at a small number of points scattered throughout the domain. For two dimensions, I have been using scipy.interpolate.RectBivariateSpline , and I'm essentially looking for an extension of that to three-dimensional data. The N-dimensional interpolation routines I have found are not quite good enough: I would prefer splines over LinearNDInterpolator for smoothness, and I

Resample time series in pandas to a weekly interval

由 若如初见. 提交于 2019-11-27 02:47:15
问题 How do I resample a time series in pandas to a weekly frequency where the weeks start on an arbitrary day? I see that there's an optional keyword base but it only works for intervals shorter than a day. 回答1: You can pass anchored offsets to resample, among other options they cover this case. For example the weekly frequency from Monday: ts.resample('W-MON') 回答2: You will be much safer with resampling based on days and then slicing every 7th day, e.g: ts.resample('D').interpolate()[::7] See

Math: Ease In, ease Out a displacement using Hermite curve with time constraint

由 ﹥＞﹥吖頭↗ 提交于 2019-11-27 01:56:21
问题 I'm trying to write a method that interpolates from 0 to x (position of an object in one dimension) over time using acceleration at the beginning and deceleration at the end (ease out / ease in) with the only constraints that the total time is provided , as well as the duration of the acceleration and deceleration . the motion should replicate the inertia effect and I'm considering a Hermite curve for the non-linear portions. double Interpolate( double timeToAccel, double timeCruising, double

Interpolate NA values

由 ⅰ亾dé卋堺 提交于 2019-11-27 01:52:14
I have two set of samples that are time independent. I would like to merge them and calculate the missing values for the times where I do not have values of both. Simplified example: A <- cbind(time=c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100), Avalue=c(1, 2, 3, 2, 1, 2, 3, 2, 1, 2)) B <- cbind(time=c(15, 30, 45, 60), Bvalue=c(100, 200, 300, 400)) C <- merge(A,B, all=TRUE) time Avalue Bvalue 1 10 1 NA 2 15 NA 100 3 20 2 NA 4 30 3 200 5 40 2 NA 6 45 NA 300 7 50 1 NA 8 60 2 400 9 70 3 NA 10 80 2 NA 11 90 1 NA 12 100 2 NA By assuming linear change between each sample, it is possible to calculate

Equidistant points across Bezier curves

由 风格不统一 提交于 2019-11-27 01:29:27
问题 Currently, I'm attempting to make multiple beziers have equidistant points. I'm currently using cubic interpolation to find the points, but because the way beziers work some areas are more dense than others and proving gross for texture mapping because of the variable distance. Is there a way to find points on a bezier by distance rather than by percentage? Furthermore, is it possible to extend this to multiple connected curves? 回答1: distance between P_0 and P_3 (in cubic form), yes, but I

Smoothing out ggplot2 map

由 微笑、不失礼 提交于 2019-11-27 01:11:03
问题 Previous Posts Cleaning up a map using geom_tile Get boundaries to come through on states Problem/Question I'm trying to smooth out some data to map with ggplot2. Thanks to @MrFlick and @hrbrmstr, I've made a lot of progress, but am having problems getting a "gradient" effect over the states I need listed. Here is an example to give you an idea about what I'm looking for : **** This is exactly what I'm trying to achieve. http://nrelscience.org/2013/05/30/this-is-how-i-did-it-mapping-in-r-with
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