![idl gaussian idl gaussian](https://raw.githubusercontent.com/mcfit/idl_emcee/master/examples/images/histogram1.jpg)
X may be of type integer, floating point, or double-precision floating-point. ArgumentsĪn n-element vector containing the independent variable values. The coefficients of the fit are returned in the argument A. The result is a vector with the same length as X that contains the function f(x) evaluated at each X value. When this program is compiled and executed, IDL generates the plots at the top of this topic, and then prints the following results: IDL>. switch nterms of 6: y = y + a*x^ 2 5: y = y + a*x 4: y = y + a 3: y = y + a* exp(-z^ 2/ 2) endswitch Fit the data to the function, storing coefficients in coeff: yfit = GAUSSFIT(x, y, coeff, NTERMS=nterms) print, 'Result: ', coeff Plot the original data and the fitted curve: p1 = PLOT(x, y, TITLE= 'nterms='+ STRTRIM(nterms, 2), $ LAYOUT=, CURRENT=(nterms gt 3), $ DIMENSIONS=, MARGIN=) p2 = PLOT(x, yfit, THICK= 2, /OVERPLOT) endfor end y = 0.4* RANDOMN(seed, n) Use a switch statement so we fall through to each term. a = print, 'Expect: ', a z = (x - a)/a Gaussian variable seed = 123321 Pick a starting seed value for nterms= 3, 6 do begin Define the dependent variables.
![idl gaussian idl gaussian](https://reference.wolfram.com/language/ref/Files/GaussianFilter.en/O_2.png)
![idl gaussian idl gaussian](https://www.kwasan.kyoto-u.ac.jp/~asai/manual/rhessi/forwardfit.jpg)
n = 101 x = ( FINDGEN(n)-(n/ 2))/ 4 Define the coefficients.
IDL GAUSSIAN CODE
Save the code in a file named "ex_gaussfit.pro". To simulate actual data, random noise has been added to each function.
IDL GAUSSIAN HOW TO
The following example shows how to use GAUSSFIT to fit to four different functions, with NTERMS=3,4,5,6. Its source code can be found in the file gaussfit.pro in the lib subdirectory of the IDL distribution. This routine is written in the IDL language. f ( x) is a linear combination of a Gaussian and a quadratic the number of terms is controlled by the keyword parameter NTERMS. To get a different number, just multiply the output of PSF_GAUSSIAN by the actual amplitude you want.The GAUSSFIT function computes a non-linear least-squares fit to a function f ( x) with from three to six unknown parameters. Oh, one obvious bit that I missed - PSF_GAUSSIAN will give you a peak value of 1 (or, if /NORMALIZE is set, a total integral of 1). psf1 = PSF_GAUSSIAN(NPIXEL=, CENTROID=, ST_DEV=3.0) FWHM= for a PSF that is slightly elongated in the y-direction).Į.g. ST_DEV=3.0 for a 3-pixel standard deviation), or for an anisotropic PSF you can give a separate x- and y-width (e.g. For an isotropic PSF, just give one value (e.g. For example for a center at x=10.5, y=186 (note they don't have to be at pixel centers).įWHM or ST_DEV: Width of the Gaussian - you can specify it either using the FWHM or Gaussian sigma.
![idl gaussian idl gaussian](https://www.researchgate.net/profile/Henry-Loescher/publication/259780741/figure/fig2/AS:297159690866693@1447859799522/Histogram-of-simulated-data-following-a-Gaussian-distribution-with-normalized-mean-0_Q320.jpg)
So you could use to make an array the same size as above.ĬENTROID: The position on the iamge of the center of the PSF. NPIXEL: The dimensions of the output array. For example, if your noise level is 2.5 electrons, you might say:Ģ) PSF_GAUSSIAN takes a few options. Seed = 1L set it to something so your results are repeatableīy default RANDOMU gives you a uniform random deviate, but you probably want a Poisson distribution, which requires giving the POISSON keyword with the mean expected value. So, for example, if you wanted to get a 256 x 512 random array, you could do: Can you please give me a sample code?ġ) RANDOMU takes as its first argument a random seed, and then the dimensions of the output array. Thanks Jeremy! But I am very new to IDL and I am not so familiar with its functions. I want to create this to test a source extraction algorithm that I have developed. The rest of the image has to be filled with constant background and noise, as present in the entire image, but devoid of stars. I want to create a synthetic image to resemble a stellar field (say covering an area of 255 by 255 pixels, with a total of about 4 stars having Gaussian PSF).