I have some random signal (for example sin signal) with the time scale.
t=0:0.1:2*pi
y=sin(t)
plot(t,y)
Now I want to draw this signal on this circle. So the time vector actually becomes an envelope of the circle. Envelope of the circle represents "y = 0" in cartesian coordinate system.
Here is an example of what I expect the output to look like:
Thank in advanced!
You need to add "noise" to the radius of the circle, roughly around r=1:
th = linspace( 0, 2*pi, N ); %// N samples
noise = rand( 1, N ) * .1; %// random noise in range [0..0.1]
r = 1+noise; %// add noise to r=1
figure;
plot( r.*cos(th), r.*sin(th) ); title('noise on circle');
An example plot would look like:
See docs for unique. Assuming widths and heights are column vectors, [C,ia,ic] = unique([widths, heights],'rows') In contrary, if widths and heights are row vectors, [C,ia,ic] = unique([widths; heights].','rows') ...
As rth suggested, define x1 = np.linspace(0, 1, 1000) x2 = np.linspace(0, 1, 100) and then plot raw versus x1, and smooth versus x2: plt.plot(x1, raw) plt.plot(x2, smooth) np.linspace(0, 1, N) returns an array of length N with equally spaced values from 0 to 1 (inclusive). import numpy as np...
python,csv,matplotlib,graph,plot
you need to turn x and y into type np.array before you calculate above_threshold and below_threshold, and then it works. In your version, you don't get an array of bools, but just False and True. I added comma delimiters to your input csv file to make it work (I assume...
Rewrite the quantity to minimise as ||Xa - b||^2 = (definition of the Frobenius norm) Tr{(Xa - b) (Xa - b)'} = (expand matrix-product expression) Tr{Xaa'X' - ba'X' - Xab' + bb'} = (linearity of the trace operator) Tr{Xaa'X'} - Tr{ba'X'} - Tr{Xab'} + Tr{bb'} = (trace of transpose of...
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matlab,distribution,sampling,random-sample
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You can extract the numerator and denominator with numden, then get their coefficiens with coeffs, normalize the polynomials, and divide again. [n,d] = numden(T); cn = coeffs(n); cd = coeffs(d); T = (n/cn(end))/(d/cd(end)); The output of latex(T) (note: no simplifyFraction now; it would undo things): Of course this isn't equal...
Combining the example by @Robert and code from the answer featured here: How to get a reversed, log10 scale in ggplot2? library("scales") library(ggplot2) reverselog_trans <- function(base = exp(1)) { trans <- function(x) -log(x, base) inv <- function(x) base^(-x) trans_new(paste0("reverselog-", format(base)), trans, inv, log_breaks(base = base), domain = c(1e-100, Inf)) }...
Not the fastest way, but you could do it as follows: Saving the desired variables in a temporary file Loading that file to get all those variables in a struct array Converting that struct array to a cell array That is, save temp_file -regexp data\d+ %// step 1 allData =...
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Morphological operations are suitable but i would suggest line structuring element as your arrangement is horizontal and you do not want overlaps between lines: clear clc close all BW = im2bw(imread('Silhouette.png')); BW = imclearborder(BW); se = strel('line',10,0); dilateddBW = imdilate(BW,se); img= imerode(BW,se); figure; imshow(img) ...
python,matplotlib,plot,google-visualization,heatmap
you need to set the origin of both the imshow instances. But, you also need to change the yedges around in your extent implot = plt.imshow(im,origin='upper') ... extent = [xedges[0], xedges[-1], yedges[-1], yedges[0]] plt.imshow(heatmap, extent=extent,alpha=.5,origin='upper') ...
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This is called "skeletonization" and you can do it with the function bwmorph: bwmorph(Img, 'skel', Inf); Best...
plot,shiny,reactive-programming,weight
there should be 70*nrow(labelSub()) instead 70*ncol(labelSub()) Thanks to Joe Cheng from shiny discuss group https://groups.google.com/forum/#!topic/shiny-discuss/hW4uw51r1Ak
The "weird behavior and lag" you see is almost always a result of callbacks interrupting each other's execution, and repeated unnecessary executions of the same callbacks piling up. To avoid this, you can typically set the Interruptible property of the control/component to 'off' instead of the default 'on', and set...
Your code works for me, just fixed some } and ]. http://jsfiddle.net/3qo8kg2o/ But I think you should use polyline instead....
http://www.mathworks.com/help/matlab/matlab_prog/continue-long-statements-on-multiple-lines.html Continue Long Statements on Multiple Lines This example shows how to continue a statement to the next line using ellipsis (...). s = 1 - 1/2 + 1/3 - 1/4 + 1/5 ... - 1/6 + 1/7 - 1/8 + 1/9; ...
From the Matlab forums, the dir command output sorting is not specified, but it seems to be purely alphabetical order (with purely I mean that it does not take into account sorter filenames first). Therefore, you would have to manually sort the names. The following code is taken from this...
As the documentation states fill_between returns a PolyCollection instance. Collections are stored in ax.collections. So ax.collections.pop() should do the trick. However, I think you have to be careful that you remove the right thing, in case there are multiple objects in either ax.lines or ax.collections. You could save a reference...
image,matlab,image-processing,mask,boundary
It's very simple. I actually wouldn't use the code above and use the image processing toolbox instead. There's a built-in function to remove any white pixels that touch the border of the image. Use the imclearborder function. The function will return a new binary image where any pixels that were...
matlab,loops,for-loop,while-loop,do-while
You could do this using conv without loops avg_2 = mean([A(1:end-1);A(2:end)]) avg_4 = conv(A,ones(1,4)/4,'valid') avg_8 = conv(A,ones(1,8)/8,'valid') Output for the sample Input: avg_2 = 0.8445 5.9715 -0.6205 -3.5505 2.5530 6.9475 10.6100 12.5635 6.4600 avg_4 = 0.1120 1.2105 0.9662 1.6985 6.5815 9.7555 8.5350 avg_8 = 3.3467 5.4830 4.7506 Finding Standard Deviation...
The following code implements only a part of what I can see in the description. It generates the noise processes and does what is described in the first part. The autocorrelation is not calculated with the filter coefficients but with the actual signal. % generate noise process y y =...
M =[0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 1 0 1 0 0 0 1 0 4 0 0 0 0 0 3 0 0 6 0 0 4 0 0 3 0 0...
You would need to change your back slashes \ to forward slashes /, otherwise some \ followed by a letter may be commands in the sprintffunction, like for example \N or \a. See sprintf documentation in the formatSpecarea for more information. original_image=imread(sprintf('D:/Academics/New folder/CUB_200_2011/images/%s', C{1}{2*(image_count)})); ...
I assume with "2d-line" you mean a 2d-plot. This is done by the plot-function, so there is no need of surf or mesh. Sorry, when I got you wrong. The following code does what I think you asked for: % Generate some propagating wave n = 20; t = linspace(0,10,100);...
python,numpy,matplotlib,graph,plot
You can use the condition z=='some tag' to index the x and y array Here's an example (based on the code in your previous question) that should do it. Use a set to automate the creation of tags: import csv import datetime as dt import numpy as np import matplotlib.pyplot...
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I think you are missing the x limit. xlim([0 2.5*a]) ...
You need to add "noise" to the radius of the circle, roughly around r=1: th = linspace( 0, 2*pi, N ); %// N samples noise = rand( 1, N ) * .1; %// random noise in range [0..0.1] r = 1+noise; %// add noise to r=1 figure; plot( r.*cos(th), r.*sin(th)...
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While you're creating your temperature data arrays, you need to parse the temperature value as a float. Make sure to parse the value as a float for both graphs. You're doing this for your humidity variable, and that is why the tooltip is working for that series. var temperature =...
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You should be able to use properties s = 100; d = zeros(1,100); end right? If you already have the 100 as a default for s, you should also be able to provide this as part of the default for d. I'm guessing that you're trying to avoid doing that...
matlab,matrix,multidimensional-array,scalar
Errr, why you multiply indexes instead of values? I tried this: comDatabe(:,:,[1 2 3],:,8) = comDatabe(:,:,[1 2 3],:,8)*-1 And it worked....
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image,matlab,image-processing,computer-vision
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