| DATE |
Description |
|---|---|
Wed Jan 23 |
Intro to to the course: outline, contents, rationale. HARDOPY HANDOUT: topics_to_cover_2008. |
Mon Jan 28 |
Intro to IDL. Datatypes, structures. Sav files, FITS files. The GSFC website and other accessible libraries. The startup file. Paths. Managing IDL on multiple platforms. HARDCOPY HANDOUT idlessentials_2008.notes You should know what's in: unixprimer.ps, idltut1.ps, idldatatypes.ps, the contents of our website UNIX, EMACS, AND LATEX . HOMEWORK PROBLEM: the eclipse problem "moonproblem.ps". (see "reading/homework") |
Wed Jan 30 |
BRING THE FIRST 4 HANDOUTS TO CLASS of our 5 handouts on images, making ps files, annotating images, multidimensional color images, and projectiions. Plots and images -- it's worth some thought! Making PostScript files of plots and images. Basic image display and processing on Xwindow. Color schemes--RBG and CMYK. |
Mon Feb 04 | Recap of eclipse problem. Visual classes: Pseudocolor, Truecolor, Directcolor. Color tables. Using color in plots. Color images: one-dimensional, two-d, and three-d. HOMEWORK PROBLEM: annotated image of a FITS file "irproj.ps" |
Wed Feb 06 |
Annotating images. Projections. |
Mon Feb 11 |
Monovariate PDFs. Basics, Examples, transformations, |
Wed Feb 13 |
Random number generating, Monte Carlo basics. Discrete PDFs (i.e., data histograms). Parent and sample populations, mean, variance, median, chi-square and KS tests. |
Mon Feb 18 |
EMPORER'S DAY (the former president's day) -- NO CLASS |
Wed Feb 20 |
Famous/important PDFs: binomial, poisson, Gaussian, log-normal, chi-squared |
Mon Feb 25 | Bivariate PDFs and their transformations. Examples: PDF of thickness of randomly oriented disks; PDF of sum of two variables with different PDFs. The very important case of PDF of sqrt of sum of squares of 2 variables. |
Wed Feb 27 |
Multivariate Gaussian statistics. Covariance, correlation, uncertainties of those in a sample. Discrete distributions: mean, variance, variance of variance, variance of correlation coefficients. |
Mon Mar 3 |
Error propagation including covariance. Eigenvector diagonalizing the covariance matrix. |
Wed Mar 5 |
Maximum Likelihood (ML) for Gaussian and double-sided exponential statistics. Virtues of the median. The chi-square PDF. |
Mon Mar 10 |
The chi-square test for histograms in more detail. Three waays to express uncertainty (sigma, confidence, and Delta chisq). Glorification of Delta chisq. Introduction to multivariate Least-squares fitting; |
Wed Mar 12 |
Illustrative example of least-squares: a polynomial fit. covariance. orthogonal functions; legendre fit. formulating least squares properly: two examples. Looking at the matrices to chase down problems. Proof (and conditions required) for the covariance matrix to reflect the true covariance. |
Mon Mar 17 |
Nonlinear least-squares fitting using Taylor expansion. Multiple minima. Levenberg-Marquardt/Craig Markwardt's mpfit.pro. |
Wed Mar 19 |
Chi-square fitting and weighted fitting. Covariance and error degree of confidence for multivariate fitting. |
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-------------- SPRING BREAK -------------------------------------------------- --------------------------------------------------- |
Mon Mar 31 |
Numerical derivatives: accuracy considerations in computing. Use of Singular Value Decomposition to handle degeneracies in least-squares fitting. |
Wed Apr 2 | Fitting when there is no independent variable--all variables have uncertainties (Jefferys's method). Weighted iterative fitting: constraints; a modified Chauvenet's criterion. Minimum Absolute Residual Sum (MARS) fitting. |
Mon Apr 7 |
Fitting arbitrary curves with rational functions. Cubic splines. Least squares with cubic splines: bsplines. Least squares cubic splines using Schlegel/Burles IDL procedure "bspline_iterfit". |
Wed Apr 9 |
Fourier transforms: basic math aspects. A few important transform pairs. Scaling. convolution and correlation theorems with real-life astronomical examples. Aliasing in discrete sampling. |
Mon Apr 14 |
Digital Fourier transforms as applied to CDs, movies, and optical gratings. Example of crab optical pulsar data. Wiener filtering, optimum filtering. binning. The FFT. |
Wed Apr 16 |
Digital convolution and correlation Deconvolution, noise. Irregular sampling and Fourier transforms. The window function. |
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-----NO CLASS DURING WEEK OF APRIL 21!!!! ---------------------- -------------------------------------------------------------------- |
Mon Apr 28 |
The Lomb periodogram. Clean. Maximum Entropy. |
Wed Apr 30 |
Maximum Entropy. |
Mon May 5 |
Wavelets I: continuous wavelets |
Wed May 7 |
Wavelets II: discrete wavelets. |
Mon May 12 |
Wrap up wavelets. Introduction to Principal Components Analysis (PCA) |
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Mon May 12 |
Wrap up PCA. Brief description of what we haven't covered. |