Changeset 3094
- Timestamp:
- Jan 25, 2005, 3:10:14 PM (21 years ago)
- Location:
- trunk/doc/pslib
- Files:
-
- 2 edited
-
ChangeLogADD.tex (modified) (1 diff)
-
psLibADD.tex (modified) (2 diffs)
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trunk/doc/pslib/ChangeLogADD.tex
r3070 r3094 19 19 \item Added section on astronomical object models 20 20 \end{itemize} 21 22 \subsection{Changes from version 08 to version 09} 23 24 \begin{itemize} 25 \item Added section on inverse and combined transformations. 26 \end{itemize} -
trunk/doc/pslib/psLibADD.tex
r3070 r3094 1 %%% $Id: psLibADD.tex,v 1.5 7 2005-01-22 01:57:42 eugene Exp $1 %%% $Id: psLibADD.tex,v 1.58 2005-01-26 01:09:07 price Exp $ 2 2 \documentclass[panstarrs]{panstarrs} 3 3 … … 1317 1317 1318 1318 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 1319 \subsubsection{2D transformations} 1320 1321 In PSLib, we implement 2-dimensional transformations using 1322 \code{psPlaneTransform}, which contains a matrix of polynomial 1323 coefficients for each dimension. Since we are using these to model 1324 the real world, where, for example, a particular point on the detector 1325 maps to a particular point on the sky, we consider only 1326 transformations that are ``one-to-one''. This makes it possible to 1327 speak of inverse transformations, and of combining multiple 1328 transformations. 1329 1330 Given a transformation, $f(x,y)$, the inverse transformation, 1331 $g(x,y)$, is that for which $g(f(x,y)) = (x,y)$ for $(x,y)$ over the 1332 range of interest (not necessarily the entire set of real numbers). 1333 1334 Given two transformations, $f(x,y)$ and $g(x,y)$, the combined 1335 transformation is the transformation, $h(x,y) = g(f(x,y))$ for $(x,y)$ 1336 over the range of interest (not necessarily the entire set of real 1337 numbers). 1338 1339 Both of these operations are straightforward if the transformation is 1340 linear. If the function $(u,v) = f(x,y)$ is: 1341 \begin{eqnarray} 1342 u & = & a + bx + cy \\ 1343 v & = & d + ex + fy 1344 \end{eqnarray} 1345 then the inverse transformation $(x,y) = g(u,v)$ is: 1346 \begin{eqnarray} 1347 x & = & (-fa+cd)/\Delta + fu/\Delta - cv/\Delta \\ 1348 y & = & (ae-bd)/\Delta - eu/\Delta + bv/\Delta 1349 \end{eqnarray} 1350 where $\Delta = bf - ce$ is the matrix determinant. Given two 1351 functions $f_i(x,y)$ for $i=1,2$: 1352 \begin{eqnarray} 1353 u & = & a_i + b_i x + c_i y \\ 1354 v & = & d_i + e_i x + f_i y 1355 \end{eqnarray} 1356 then the combined transformation, $(u,v) = f_2(f_1(x,y))$ is: 1357 \begin{eqnarray} 1358 u & = & (a_2 + b_2 a_1 + c_2 d_1) + (b_2 b_1 + c_2 e_1) x + (b_2 c_1 + c_2 f_1) y \\ 1359 v & = & (d_2 + e_2 a_1 + f_2 d_1) + (e_2 b_1 + f_2 e_1) x + (e_2 c_1 + f_2 f_1) y 1360 \end{eqnarray} 1361 1362 When the transformations are not linear, the inverse and combined 1363 transformations can be estimated by sampling a grid over the region of 1364 interest, calculating the transformation (or double transformation) 1365 for each sample, and using this information to derive the best fit 1366 transformation that produces the inverse or combined transformation. 1367 The inverse transformation should be of the same order as that of the 1368 forward transformation, while the combined transformation should be of 1369 the higher order of the two component transformations. 1370 1371 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 1319 1372 1320 1373 \subsubsection{Projections}
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