[gnuastro-commits] master da21f8bb: Book: minor edits in Moire pattern tutorial

[Mohammad Akhlaghi]

branch: master
commit da21f8bbe44186f772b0cfa486631963774415b9
Author: Mohammad Akhlaghi <mohammad@akhlaghi.org>
Commit: Mohammad Akhlaghi <mohammad@akhlaghi.org>

    Book: minor edits in Moire pattern tutorial
    
    Until now, the printed demonstration values of the Moire pattern tutorial
    didn't include the new plain-text formatting for the outputs of Statistics
    (in scientific notation).
    
    With this commit, this has been corrected and some minor edits have been
    made in the text to make it more clear.
---
 doc/gnuastro.texi | 26 ++++++++++++++------------
 1 file changed, 14 insertions(+), 12 deletions(-)

diff --git a/doc/gnuastro.texi b/doc/gnuastro.texi
index 933c3458..c9c2e6e1 100644
--- a/doc/gnuastro.texi
+++ b/doc/gnuastro.texi
@@ -10673,7 +10673,7 @@ For example when observing time-variable phenomena 
where cutting the exposures t
 If this is not the case for you (for example in galaxy evolution), continue 
with the rest of this section.
 
 Because we have multiple exposures that are slightly (sub-pixel) shifted, we 
can also increase the spatial resolution of the output.
-For example, let's set the output coordinate-delta (or pixel scale) to be 1/2 
of the input.
+For example, let's set the output coordinate-delta (@option{--cdelt}, or pixel 
scale) to be 1/2 of the input.
 In other words, the number of pixels in each dimension of the output is double 
the first Warp command of this section:
 
 @example
@@ -10682,7 +10682,7 @@ $ astwarp jplus-exp1.fits.fz 
--center=107.62920,39.72472 \
           --checkmaxfrac
 
 $ aststatistics jplus-e1.fits -hMAX-FRAC --minimum --maximum
-0.06263604388 0.2506802701
+6.26360438764095e-02 2.50680270139128e-01
 
 $ astscript-fits-view jplus-e1.fits
 @end example
@@ -10706,7 +10706,7 @@ This is why you don't see any Moir@'e pattern in the 
warped image.
 
 In J-PLUS, each part of the sky was observed with a three-point pointing 
pattern (very small shifts in each pointing).
 Let's download the other two exposures and warp the same region of the sky to 
the same pixel grid (using the @option{--gridfile} feature).
-Then, let's open all three cropped images in one DS9 instance:
+Then, let's open all three warped images in one DS9 instance:
 
 @example
 $ wget $jplusdr2/get_fits?id=771465 -Ojplus-exp2.fits.fz
@@ -10725,24 +10725,26 @@ In the three warped images, you don't see any Moir@'e 
pattern, so far so good...
 now, take the following steps:
 @enumerate
 @item
+In the small ``Cube'' window, click the ``Next'' button so you see the 
@code{MAX-FRAC} extension/HDU.
+@item
 Click on the ``Frame'' button (in the top row of buttons just on top of the 
image), and select the ``Single'' button in the bottom row.
 @item
-Open the ``Zoom'' menu, and select ``Zoom 16''.
+Open the ``Zoom'' menu (not button), and select ``Zoom 16''.
 @item
-In the bottom row of buttons right on top of the image, press the ``next'' 
button to flip through each exposure's @code{MAX-FRAC} extension.
+Press the @key{TAB} key to flip through each exposure.
 @item
-Focus your eyes on the pixels with the largest value (white colored pixels), 
while pressing the ``next'' button to flip between the exposures.
-You will see that in each exposure they cover different pixels.
+Focus your eyes on the pixels with the largest value (white colored pixels), 
while pressing @key{TAB} to flip between the exposures.
+You will see that in each exposure they cover different pixels (nicely getting 
averaged out after stacking).
 @end enumerate
 
-The exercise above shows that the effect varying smoothing level (that had 
already shrank to a per-pixel level) will be further decreased after we stack 
the images.
+The exercise above shows that the Moir@'e pattern (that had already decreased 
significantly) will be further decreased after we stack the images.
 So let's stack these three images with the commands below.
-First, we need to remove the sky-level from each image using 
@ref{NoiseChisel}, then we'll stack the @code{INPUT-NO-SKY} extensions using 
sigma-clipping (to reject outliers by @ref{Sigma clipping}, using the 
@ref{Stacking operators}).
+First, we need to remove the sky-level from each image using 
@ref{NoiseChisel}, then we'll stack the @code{INPUT-NO-SKY} extensions using 
filled MAD-clipping (to reject outliers, and especially diffuse outliers, 
robustly, see @ref{Clipping outliers}).
 
 @example
-$ astnoisechisel jplus-e1.fits -ojplus-nc1.fits
-$ astnoisechisel jplus-e2.fits -ojplus-nc2.fits
-$ astnoisechisel jplus-e3.fits -ojplus-nc3.fits
+$ for i in $(seq 3); do \
+   astnoisechisel jplus-e$i.fits -ojplus-nc$i.fits; \
+  done
 
 $ astarithmetic jplus-nc*.fits 3 5 0.2 sigclip-mean \
                 -gINPUT-NO-SKY -ojplus-stack.fits