[gnuastro-commits] master 961776e: Book: improved documentation of the match.h library

[Mohammad Akhlaghi]

branch: master
commit 961776eadd54e71a6c8b7c22a231e002cf64497a
Author: Mohammad Akhlaghi <mohammad@akhlaghi.org>
Commit: Mohammad Akhlaghi <mohammad@akhlaghi.org>

    Book: improved documentation of the match.h library
    
    Until now, the documentation of the 'gal_match_coordinates' function didn't
    really describe the format of the output too well and was very
    long. However, we will soon have a new k-d tree based matching function and
    the formats of its inputs and outputs are the same as this function (to
    allow users to easy switch between the two).
    
    With this commit, the description of the inputs and outputs of
    'gal_match_coordinates' have been brought outside/before the function, and
    the description of this function only contains the arguments related to its
    particular matching algorithm.
---
 doc/gnuastro.texi | 133 +++++++++++++++++++++++++-----------------------------
 1 file changed, 62 insertions(+), 71 deletions(-)

diff --git a/doc/gnuastro.texi b/doc/gnuastro.texi
index 015905c..70ae474 100644
--- a/doc/gnuastro.texi
+++ b/doc/gnuastro.texi
@@ -25940,87 +25940,78 @@ Apply the inverse of @code{permutation} on the 
@code{input} dataset (can
 have any type), see above for the definition of permutation.
 @end deftypefun
 
+
+
+
+
 @node Matching, Statistical operations, Permutations, Gnuastro library
 @subsection Matching (@file{match.h})
 
-Matching is often necessary when the measurements have been done using
-different instruments, different software or different configurations of
-the same software. The functions in this part of Gnuastro's library will be
-growing to allow matching of images and finding a match between different
-catalogs (register them). Currently it only provides the  The high-level
-measurements are stored in tables with positions (commonly in RA and Dec
-with units of degrees).
+@cindex Matching
+@cindex Coordinate matching
+Matching is often necessary when two measurements of the same points have been 
done using different instruments (or hardware), different software or different 
configurations of the same software.
+In other words, you have two catalogs or tables and each has N columns 
containing the N-dimensional ``positional'' values of each point.
+Each can have other columns too, for example one can have brightness 
measurements in one filter, and another can have brightness measurements in 
another filter as well as morphology measurements or etc.
+
+The matching functions here will use the positional columns to find the 
permutation necessary to apply to both tables.
+This will enable you to match by the positions, then apply the permutation to 
the brightness or morphology columns in the example above.
+The input and output data formats of the functions below are the some and 
described below before the actual functions.
+Each function also has extra arguments due to the particular algorithm it uses 
for the matching.
+
+The two inputs of the functions (@code{coord1} and @code{coord2}) must be 
@ref{List of gal_data_t}.
+Each @code{gal_data_t} node in @code{coord1} or @code{coord2} should be a 
single dimensional dataset (column in a table) and all the nodes must have the 
same number of elements (rows).
+In other words, each column can be visualized as having the coordinates of 
each point in its respective dimension.
+The dimensions of the coordinates is determined by the number of 
@code{gal_data_t} nodes in the two input lists (which must be equal).
+The number of rows (or the number of elements in each @code{gal_data_t}) in 
the columns of @code{coord1} and @code{coord2} can be different.
+All these functions will all be satisfied if you use @code{gal_table_read} to 
read the two coordinate columns, see @ref{Table input output}.
+
+@cindex Permutation
+The functions below return a simply-linked list of three 1D datasets (see 
@ref{List of @code{gal_data_t}}), let's call the returned dataset @code{ret}.
+The first two (@code{ret} and @code{ret->next}) are permutaitons.
+In other words, the @code{array} elements of both have a type of 
@code{size_t}, see @ref{Permutations}.
+The third node (@code{ret->next->next}) is the calculated distance for that 
match and its array has a type of @code{double}.
+The number of matches will be put in the space pointed by the 
@code{nummatched} argument.
+If there wasn't any match, this function will return @code{NULL}.
+
+The two permutations can be applied to the rows of the two inputs: the first 
one (@code{ret}) should be applied to the rows of the table containing 
@code{coord1} and the second one (@code{ret->next}) to the table containing 
@code{coord2}.
+After applying the returned permutations to the inputs, the top 
@code{nummatched} elements of both will match with each other.
+The ordering of the rest of the elements is undefined (depends on the matching 
funciton used).
+The third node is the distances between the respective match (which may be 
elliptical distance, see discussion of ``aperture'' below).
+
+The functions will not simply return the nearest neighbor as a match.
+The nearest neighbor may be too far to be a meaningful.
+They will check the distance between the distance of the nearest neighbor of 
each point and only return a match for it it is within an acceptable 
N-dimensional distance (or ``aperture'').
+The matching aperture is defined by the @code{aperture} array that is an input 
argument to the functions.
+If several points of one catalog lie within this aperture of a point in the 
other, the  nearest is defined as the match.
+In a 2D situation (where the input lists have two nodes), for the most generic 
case, it must have three elements: the major axis length, axis ratio and 
position angle (see @ref{Defining an ellipse and ellipsoid}).
+If @code{aperture[1]==1}, the aperture will be a circle of radius 
@code{aperture[0]} and the third value won't be used.
+When the aperture is an ellipse, distances between the points are also 
calculated in the respective elliptical distances (@mymath{r_{el}} in 
@ref{Defining an ellipse and ellipsoid}).
+
+
+
 
 @deftypefun {gal_data_t *} gal_match_coordinates (gal_data_t @code{*coord1}, 
gal_data_t @code{*coord2}, double @code{*aperture}, int @code{sorted_by_first}, 
int @code{inplace}, size_t @code{minmapsize}, int @code{quietmmap}, size_t 
@code{*nummatched})
 
-Return the permutations that when applied, the first @code{nummatched} rows
-of both inputs match with each other (are the nearest within the given
-aperture). The two inputs (@code{coord1} and @code{coord2}) must be
-@ref{List of gal_data_t}. Each @code{gal_data_t} node in the list should be
-a single dimensional dataset (column in a table). The dimensions of the
-coordinates is determined by the number of @code{gal_data_t} nodes in the
-two input lists (which must be equal). Note that the number of rows (or the
-number of elements in each @code{gal_data_t}) in the columns of
-@code{coord1} and @code{coord2} can be different.
-
-The matching aperture is defined by the @code{aperture} array. If several
-points of one catalog lie within this aperture of a point in the other, the
-nearest is defined as the match. In a 2D situation (where the input lists
-have two nodes), for the most generic case, it must have three elements:
-the major axis length, axis ratio and position angle (see @ref{Defining an
-ellipse and ellipsoid}). If @code{aperture[1]==1}, the aperture will be a
-circle of radius @code{aperture[0]} and the third value won't be used. When
-the aperture is an ellipse, distances between the points are also
-calculated in the respective elliptical distances (@mymath{r_{el}} in
-@ref{Defining an ellipse and ellipsoid}).
-
-To speed up the search, this function will sort the input coordinates by
-their first column (first axis). If @emph{both} are already sorted by their
-first column, you can avoid the sorting step by giving a non-zero value to
-@code{sorted_by_first}.
-
-When sorting is necessary and @code{inplace} is non-zero, the actual input
-columns will be sorted. Otherwise, an internal copy of the inputs will be
-made, used (sorted) and later freed before returning. Therefore, when
-@code{inplace==0}, inputs will remain untouched, but this function will
-take more time and memory.
-
-If internal allocation is necessary and the space is larger than
-@code{minmapsize}, the space will be not allocated in the RAM, but in a
-file, see description of @option{--minmapsize} and @code{--quietmmap} in
-@ref{Processing options}.
-
-The number of matches will be put in the space pointed by
-@code{nummatched}. If there wasn't any match, this function will return
-@code{NULL}. If match(s) were found, a list with three @code{gal_data_t}
-nodes will be returned. The top two nodes in the list are the permutations
-that must be applied to the first and second inputs respectively. After
-applying the permutations, the top @code{nummatched} elements will match
-with each other. The third node is the distances between the respective
-match. Note that the three nodes of the list are all one-dimensional (a
-column) and can have different lengths.
+Use a basic sort-based match to find the matching points of two input 
coordinates.
+See the descriptions above on the format of the inputs and outputs.
+To speed up the search, this function will sort the input coordinates by their 
first column (first axis).
+If @emph{both} are already sorted by their first column, you can avoid the 
sorting step by giving a non-zero value to @code{sorted_by_first}.
+
+When sorting is necessary and @code{inplace} is non-zero, the actual input 
columns will be sorted.
+Otherwise, an internal copy of the inputs will be made, used (sorted) and 
later freed before returning.
+Therefore, when @code{inplace==0}, inputs will remain untouched, but this 
function will take more time and memory.
+If internal allocation is necessary and the space is larger than 
@code{minmapsize}, the space will be not allocated in the RAM, but in a file, 
see description of @option{--minmapsize} and @code{--quietmmap} in 
@ref{Processing options}.
 
 @cartouche
 @noindent
-@strong{Output permutations ignore internal sorting}: the output
-permutations will correspond to the initial inputs. Therefore, even when
-@code{inplace!=0} (and this function re-arranges the inputs), the output
-permutation will correspond to original (possibly non-sorted) inputs.
-
-The reason for this is that you rarely want the actual positional columns
-after the match. Usually, you also have other columns (measurements, for
-example magnitudes) for higher-level processing after the match (that
-correspond to the input order before sorting). Once you have the
-permutations, they can be applied to those other columns (see
-@ref{Permutations}) and the higher-level processing can continue.
-@end cartouche
-
-When you read the coordinates from a table using @code{gal_table_read} (see
-@ref{Table input output}), and only ask for the coordinate columns, the
-inputs to this function are the returned @code{gal_data_t *} from two
-different tables.
-
+@strong{Output permutations ignore internal sorting}: the output permutations 
will correspond to the initial inputs.
+Therefore, even when @code{inplace!=0} (and this function re-arranges the 
inputs in place), the output permutation will correspond to original (possibly 
non-sorted) inputs.
 
+The reason for this is that you rarely want to permute the actual positional 
columns after the match.
+Usually, you also have other columns (for example the brightness, morphology 
and etc) and you want to find how they differ between the objects that match.
+Once you have the permutations, they can be applied to those other columns 
(see @ref{Permutations}) and the higher-level processing can continue.
+So if you don't need the coordinate columns for the rest of your analysis, it 
is better to set @code{inplace=1}.
+@end cartouche
 @end deftypefun
 
 @node Statistical operations, Binary datasets, Matching, Gnuastro library