[gnuastro-commits] master 28d72c59: Book: spell check on edited parts from version 0.20

[Mohammad Akhlaghi]

branch: master
commit 28d72c59cf977ff78e26084fae589514f987d92b
Author: Mohammad Akhlaghi <mohammad@akhlaghi.org>
Commit: Mohammad Akhlaghi <mohammad@akhlaghi.org>

    Book: spell check on edited parts from version 0.20
    
    Until now, the newly added/edited weren't checked for typos.
    
    With this commit, a spell check was run on those parts and the discovered
    typos have been fixed.
---
 doc/gnuastro.texi | 94 +++++++++++++++++++++++++++----------------------------
 1 file changed, 47 insertions(+), 47 deletions(-)

diff --git a/doc/gnuastro.texi b/doc/gnuastro.texi
index 6ebf7f93..b5e60105 100644
--- a/doc/gnuastro.texi
+++ b/doc/gnuastro.texi
@@ -1140,7 +1140,7 @@ They can be run just like a program and behave very 
similarly (with minor differ
 
 @table @code
 @item astscript-pointing-simulate
-(See @ref{Pointing pattern simulation}) Given a table of pointings on the sky, 
create and a reference image that contain's your camera's distortions and 
properties, generate a stacked exposure map.
+(See @ref{Pointing pattern simulation}) Given a table of pointings on the sky, 
create and a reference image that contains your camera's distortions and 
properties, generate a stacked exposure map.
 This is very useful in testing the coverage of dither patterns when designing 
your observing strategy and it is highly customizable, see the tutorial in 
@ref{Pointing pattern design}.
 
 @item astscript-ds9-region
@@ -1216,7 +1216,7 @@ Anscombe uses this (now famous) quartet, which was 
introduced in the paper quote
 Echoing Anscombe's concern after 44 years, some of the highly recognized 
statisticians of our time (Leek, McShane, Gelman, Colquhoun, Nuijten and 
Goodman), wrote in Nature that:
 
 @quotation
-We need to appreciate that data analysis is not purely computational and 
algorithmic -- it is a human behaviour....Researchers who hunt hard enough will 
turn up a result that fits statistical criteria -- but their discovery will 
probably be a false positive.
+We need to appreciate that data analysis is not purely computational and 
algorithmic -- it is a human behavior....Researchers who hunt hard enough will 
turn up a result that fits statistical criteria -- but their discovery will 
probably be a false positive.
 @author Five ways to fix statistics, Nature, 551, Nov 2017.
 @end quotation
 
@@ -2023,8 +2023,8 @@ But they need to be as realistic as possible, so this 
tutorial is dedicated to t
 
 There are other tutorials also, on things that are commonly necessary in 
astronomical research:
 In @ref{Detecting lines and extracting spectra in 3D data}, we use MUSE cubes 
(an IFU dataset) to show how you can subtract the continuum, detect 
emission-line features, extract spectra and build pseudo narrow-band images.
-In @ref{Color channels in same pixel grid} we demonstrate how you can warp 
multiple images into a single pixel grid (often necessary with mult-wavelength 
data), and build a single color image.
-In @ref{Moire pattern in stacking and its correction} we show how you can 
avoid the un-wanted Moir@'e pattern which happens when warping separate 
exposures to build a stacked/co-add deeper image.
+In @ref{Color channels in same pixel grid} we demonstrate how you can warp 
multiple images into a single pixel grid (often necessary with multi-wavelength 
data), and build a single color image.
+In @ref{Moire pattern in stacking and its correction} we show how you can 
avoid the unwanted Moir@'e pattern which happens when warping separate 
exposures to build a stacked/co-add deeper image.
 In @ref{Zero point of an image} we review the process of estimating the zero 
point of an image using a reference image or catalog.
 Finally, in @ref{Pointing pattern design} we show the process by which you can 
simulate a dither pattern to find the best observing strategy for your next 
exciting scientific project.
 
@@ -9381,7 +9381,7 @@ In other words, after astrometry, but before warping into 
any other pixel grid (
 The image will give us the default number of the camera's pixels, its pixel 
scale (width of pixel in arcseconds) and the camera distortion.
 These are reference parameters that are independent of the position of the 
image on the sky.
 
-Because the actual position of the reference image is irrelevant, let's assume 
that in a previous project, persumably on 
@url{https://en.wikipedia.org/wiki/NGC_4395, NGC 4395}, you already had the 
download command of the following single exposure image.
+Because the actual position of the reference image is irrelevant, let's assume 
that in a previous project, presumably on 
@url{https://en.wikipedia.org/wiki/NGC_4395, NGC 4395}, you already had the 
download command of the following single exposure image.
 With the last command, please take a look at this image before continuing and 
explore it.
 
 @example
@@ -9506,7 +9506,7 @@ If you are interested in the low surface brightness parts 
of this galaxy, it is
 To be able to accurately calibrate the image (in particular to estimate the 
flat field pattern and subtract the sky), you do not want this to happen!
 You want each exposure to cover very different sources of astrophysical 
signal, so you can accurately calibrate the artifacts created by the instrument 
or environment (for example flat field) or of natural causes (for example the 
Sky).
 
-For an example of how these calibration issues can ruine low surface 
brightness science, please see the image of M94 in the 
@url{https://www.legacysurvey.org/viewer,Legacy Survey interactive viewer}.
+For an example of how these calibration issues can ruin low surface brightness 
science, please see the image of M94 in the 
@url{https://www.legacysurvey.org/viewer,Legacy Survey interactive viewer}.
 After it is loaded, at the bottom-left corner of the window, write ``M94'' in 
the box of ``Jump to object'' and press ENTER.
 At first, M94 looks good with a black background, but as you increase the 
``Brightness'' (by scrolling it to the right and seeing what is under the 
originally black pixels), you will see the calibration artifacts clearly.
 
@@ -9566,7 +9566,7 @@ $ astarithmetic deep-pix-area.fits deep.fits isblank nan 
where -g1 \
 
 Therefore, the actual area that is covered is less than the simple 
multiplication above.
 At these declinations, the dominant cause of this difference is the first 
point above (that RA needs correction), this will be discussed in more detail 
later in this tutorial (see @ref{Pointings that account for sky curvature}).
-Genearlly, using this method to measure the area of your non-NAN pixels in an 
image is very easy and robust (automatically takes into account the curvature, 
coordinate system, projection and blank pixels of the image).
+Generally, using this method to measure the area of your non-NAN pixels in an 
image is very easy and robust (automatically takes into account the curvature, 
coordinate system, projection and blank pixels of the image).
 
 @node Script with pointing simulation steps so far, Larger steps sizes for 
better calibration, Area of non-blank pixels on sky, Pointing pattern design
 @subsection Script with pointing simulation steps so far
@@ -9579,7 +9579,7 @@ Therefore, it is better to write the steps above (after 
downloading the referenc
 In this way, you can simply change those variables and see the final result 
fast by running your script.
 For more on writing scripts, see as described in @ref{Writing scripts to 
automate the steps}.
 
-Here is a summary of some points to remember when transfering the code in the 
sections before into a script:
+Here is a summary of some points to remember when transferring the code in the 
sections before into a script:
 
 @itemize
 @item
@@ -9606,7 +9606,7 @@ Here is the script that summarizes the steps in 
@ref{Preparing input and generat
 # provided the copyright notice and this notice are preserved.  This
 # file is offered as-is, without any warranty.
 
-# Paramters of the script
+# Parameters of the script
 deep_thresh=5
 step_arcmin=1
 center_ra=192.721250
@@ -9619,7 +9619,7 @@ bdir=build
 # Abort the script in case of an error.
 set -e
 
-# Make the build directory if it doesn't alreay exist.
+# Make the build directory if it doesn't already exist.
 if ! [ -d $bdir ]; then mkdir $bdir; fi
 
 # Build the 5-pointing pointing pattern (with the step size above).
@@ -9657,7 +9657,7 @@ astarithmetic $pixarea $deep isblank nan where -g1 \
               sumvalue --quiet
 @end verbatim
 
-For a description of how to make it exectable and how to run it, see 
@ref{Writing scripts to automate the steps}.
+For a description of how to make it executable and how to run it, see 
@ref{Writing scripts to automate the steps}.
 Note that as you start adding your own text to the script, be sure to add your 
name (and year that you modified) in the copyright notice at the start of the 
script (this is very important!).
 
 @node Larger steps sizes for better calibration, Pointings that account for 
sky curvature, Script with pointing simulation steps so far, Pointing pattern 
design
@@ -9751,7 +9751,7 @@ This is because the surface brightness limit in the 
single-exposure regions is @
 This almost one magnitude difference in surface brightness is significant and 
clearly visible in the stacked image (recall that magnitudes are measured in a 
logarithmic scale).
 
 Thanks to the argument above, we can now have a sufficiently large area with a 
usable depth.
-However, each pointing's center will still contain the central part of the 
galaxy.
+However, each the center of each pointing will still contain the central part 
of the galaxy.
 In other words, M94 will be present in all the exposures while doing the 
calibrations.
 Even in not-too-deep observations, we already see a large ring around this 
galaxy.
 When we do a low surface brightness optimized reduction, there is a good 
chance that the size of the galaxy is much larger than that ring.
@@ -9779,7 +9779,7 @@ $ astscript-fits-view build/deep.fits --ds9scale=minmax
 
 You will see that the region with 5 exposure depth is a horizontally elongated 
rectangle now!
 Also, the vertical component of the cross with four exposures is much thicker 
than the horizontal component!
-Where does this assymmetry come from? All the steps in our pointing strategy 
had the same (fixed) size of 40 arc minutes.
+Where does this asymmetry come from? All the steps in our pointing strategy 
had the same (fixed) size of 40 arc minutes.
 
 This happens because the same change in RA and Dec (defined on the curvature 
of a sphere) will result in different absolute changes on the equator.
 To visually see this, let's look at the pointing positions in TOPCAT:
@@ -9800,8 +9800,8 @@ $ astscript-fits-view build/pointing.fits
 
 After TOPCAT opens, under the ``graphics'' window, select ``Plane Plot''.
 In the newly opened window, click on the ``Axes'' item on the bottom-left list 
of items.
-Then activate the ``Aspect lock'' box so the vertical and horizontal axises 
have the same scaling.
-You will see what you expect from the numbers: we have a beautifully symmetic 
set of 5 points shaped like a `+' sign.
+Then activate the ``Aspect lock'' box so the vertical and horizontal axes have 
the same scaling.
+You will see what you expect from the numbers: we have a beautifully symmetric 
set of 5 points shaped like a `+' sign.
 
 Keep the previous window, and let's go back to the original TOPCAT window.
 In the first TOPCAT window, click on ``Graphics'' again, but this time, select 
``Sky plot''.
@@ -9872,7 +9872,7 @@ When the minimum and maximum RA and Dec differ by larger 
than half a degree, you
 For more, see the description of these operators in @ref{Column arithmetic}.
 @end cartouche
 
-Try slighly increasing @code{step_arcmin} to make the cross-like region with 4 
exposures as thin as possible.
+Try to slightly increase @code{step_arcmin} to make the cross-like region with 
4 exposures as thin as possible.
 For example, set it to @code{step_arcmin=42}.
 When you open @file{deep.fits}, you will see that the depth across this image 
is almost contiguous (which is another positive factor!).
 Try increasing it to 43 arc minutes to see that the central cross will become 
almost fully NaN in @file{deep.fits} (which is bad!).
@@ -9899,7 +9899,7 @@ In @ref{Accounting for non-exposed pixels}, we will show 
how this can be done wi
 @cindex Vignetting
 @cindex Bad pixels
 At the end of @ref{Pointings that account for sky curvature} we were able to 
maximize the region of same depth in our stack.
-But we noticed that issues like strong 
@url{https://en.wikipedia.org/wiki/Vignetting,vignetting} can create 
discontiuity in our final stacked data product.
+But we noticed that issues like strong 
@url{https://en.wikipedia.org/wiki/Vignetting,vignetting} can create 
discontinuity in our final stacked data product.
 In this section, we'll review the steps to account for such effects.
 Generally, the full area of a detector is not usually used in the final stack.
 Vignetting is one cause, it can be due to other problems also.
@@ -20196,13 +20196,13 @@ See 
@url{https://en.wikipedia.org/wiki/Fine-structure_constant, Wikipedia}.
 Different celestial coordinate systems are useful for different scenarios.
 For example, assume you have the RA and Dec of large sample of galaxies that 
you plan to study the halos of galaxies from.
 For such studies, you prefer to stay as far away as possible from the Galactic 
plane, because the density of stars and interstellar filaments (cirrus) 
significantly increases as you get close to the Milky way's disk.
-But the @url{https://en.wikipedia.org/wiki/Equatorial_coordinate_system, 
Equatorial coordinate system} which defines the RA and Dec and is based on 
Earth's equator; and does not show the position of your objects in relationt to 
the galactic disk.
+But the @url{https://en.wikipedia.org/wiki/Equatorial_coordinate_system, 
Equatorial coordinate system} which defines the RA and Dec and is based on 
Earth's equator; and does not show the position of your objects in relation to 
the galactic disk.
 
 The best way forward in the example above is to convert your RA and Dec table 
into the @url{https://en.wikipedia.org/wiki/Galactic_coordinate_system, 
Galactic coordinate system}; and select those with a large (positive or 
negative) Galactic latitude.
-Alternatively, if you observe a bright point on a galaxy and want to confirm 
if it was actually a super-nova and not a moving asteriod, a first step is to 
convert your RA and Dec to the 
@url{https://en.wikipedia.org/wiki/Ecliptic_coordinate_system, Ecliptic 
coordinate system} and confirm if you are sufficiently distant from the 
ecliptic (plane of the Solar System; where fast moving objects are most common).
+Alternatively, if you observe a bright point on a galaxy and want to confirm 
if it was actually a super-nova and not a moving asteroid, a first step is to 
convert your RA and Dec to the 
@url{https://en.wikipedia.org/wiki/Ecliptic_coordinate_system, Ecliptic 
coordinate system} and confirm if you are sufficiently distant from the 
ecliptic (plane of the Solar System; where fast moving objects are most common).
 
 The operators described in this section are precisely for the purpose above: 
to convert various celestial coordinate systems that are supported within 
Gnuastro into each other.
-For example, if you want to convert the RA and Dec equatorial (at the Julian 
year 2000 equinox) coordinates (within the @code{RA} and @code{DEC} columns) of 
@file{points.fits} into Galactic longitude and latitutde, you can use the 
command below (the column metadata are not mandatory, but to avoid later 
confusion, it is always good to have them in your output.
+For example, if you want to convert the RA and Dec equatorial (at the Julian 
year 2000 equinox) coordinates (within the @code{RA} and @code{DEC} columns) of 
@file{points.fits} into Galactic longitude and latitude, you can use the 
command below (the column metadata are not mandatory, but to avoid later 
confusion, it is always good to have them in your output.
 
 @example
 $ asttable points.fits -c'arith RA DEC eq-j2000-to-galactic' \
@@ -20216,14 +20216,14 @@ Therefore these two (equatorial and ecliptic) 
coordinate systems are defined wit
 So when dealing with these coordinates one of the `@code{-b1950}' or 
`@code{-j2000}' suffixes are necessary (for example @code{eq-j2000} or 
@code{ec-b1950}).
 
 @cindex ICRS
-The Galactic or Supergalactic coordiantes are not defined based on the Earth's 
dynamics; therefore they do not have any epoch associated with them.
+The Galactic or Supergalactic coordinates are not defined based on the Earth's 
dynamics; therefore they do not have any epoch associated with them.
 Extra-galactic studies do not depend on the dynamics of the earth, but the 
equatorial coordinate system is the most dominant in that field.
 Therefore in its 23rd General Assembly, the International Astronomical Union 
approved the 
@url{https://en.wikipedia.org/wiki/International_Celestial_Reference_System_and_its_realizations,
 International Celestial Reference System} or ICRS based on quasars (which are 
static within our observational limitations)viewed through long baseline radio 
interferometry (the most accurate method of observation that we currently have).
 ICRS is designed to be within the errors of the Equatorial J2000 coordinate 
system, so they are currently very similar; but ICRS has much better accuracy.
 We will be adding ICRS in the operators below soon.
 
 @strong{Floating point errors:} The operation to convert between the 
coordinate systems involves many sines, cosines (and their inverse).
-Therefore, floating point errors (due to the limited precision of the 
definition of floating points in bits) can cause small offests.
+Therefore, floating point errors (due to the limited precision of the 
definition of floating points in bits) can cause small offsets.
 For example see the code below were we convert equatorial to galactic and 
back, then compare the input and output (which is in the 5th and 6th decimal of 
a degree; or about 0.2 or 0.01 arcseconds).
 
 @example
@@ -21695,7 +21695,7 @@ Add a Gaussian noise with pre-defined @mymath{\sigma} 
to each element of the inp
 @mymath{\sigma} is the standard deviation of the 
@url{https://en.wikipedia.org/wiki/Normal_distribution, Gaussian or Normal 
distribution}.
 This operator takes two arguments: the top/first popped operand is the noise 
standard deviation, the next popped operand is the dataset that the noise 
should be added to.
 
-For example, with the first command below, let's put a S@'ersic profile with 
S@'ersic index 1 and effective radius 10 pixels, tructated at 5 times the 
effective radius in the center of a mock image that is @mymath{100\times100} 
pixels wide.
+For example, with the first command below, let's put a S@'ersic profile with 
S@'ersic index 1 and effective radius 10 pixels, truncated at 5 times the 
effective radius in the center of a mock image that is @mymath{100\times100} 
pixels wide.
 We will also give it a position angle of 45 degrees and an axis ratio of 0.8, 
and set it to have a total electron count of 10000 (@code{1e4} in the command).
 Note that this example is focused on this operator, for a robust simulation, 
see the tutorial in @ref{Sufi simulates a detection}.
 With the second command, let's add noise to this image and with the third 
command, we'll subtract the raw image from the noised image.
@@ -21722,7 +21722,7 @@ These behaviors will be different in the case for 
@code{mknoise-sigma-from-mean}
 @cindex Poisson noise
 Replace each input element (e.g., pixel in an image) of the input with a 
random value taken from a Gaussian distribution (for pixel @mymath{i}) with 
mean @mymath{\mu_i} and standard deviation @mymath{\sigma_i}.
 Where, @mymath{\sigma_i=\sqrt{I_i+B_i}} and @mymath{\mu_i=I_i+B_i} and 
@mymath{I_i} and @mymath{B_i} are respectively the values of the input image, 
and background in that same pixel.
-In other words, this can be seen as approximating a Poisson distribution at 
high mean values (where the Poisson distribution becomes identical to the 
Guassian distribution).
+In other words, this can be seen as approximating a Poisson distribution at 
high mean values (where the Poisson distribution becomes identical to the 
Gaussian distribution).
 
 This operator takes two arguments: 1. the first popped operand (just before 
the operator) is the @emph{per-pixel} background value (in units of electron 
counts).
 2. The second popped operand is the dataset that the noise should be added to.
@@ -21743,7 +21743,7 @@ $ astscript-fits-view diff-sigma.fits \
 @end example
 
 You clearly see how the noise in the center of the S@'ersic profile is much 
stronger than the outer parts.
-As described, above, this is behaviour we would expect in a ``real'' 
observation: the regions with stronger signal, also have stronger noise as 
defined through the @url{https://en.wikipedia.org/wiki/Poisson_distribution, 
Poisson distribution}!
+As described, above, this is behavior we would expect in a ``real'' 
observation: the regions with stronger signal, also have stronger noise as 
defined through the @url{https://en.wikipedia.org/wiki/Poisson_distribution, 
Poisson distribution}!
 The reason we described this operator as ``Poisson-like'' is that, it has some 
shortcomings as opposed to the @code{mknoise-poisson} operator (that is 
described below):
 @itemize
 @item
@@ -21803,7 +21803,7 @@ $ astarithmetic raw.fits 4 mknoise-poisson \
 
 $ astscript-fits-view sigma-from-mean.fits poisson.fits
 
-$ astatistics sigma-from-mean.fits --lessthan=10
+$ aststatistics sigma-from-mean.fits --lessthan=10
 -------
 Histogram:
  |                       ***
@@ -21836,7 +21836,7 @@ Histogram:
  |------------------------------------------------------------
 @end example
 
-The extra skew-ness in the Poisson distribution, and the fact that it only 
returns integers is therefore clear with the commands above.
+The extra skewness in the Poisson distribution, and the fact that it only 
returns integers is therefore clear with the commands above.
 The comparison was further made above in the description of 
@code{mknoise-sigma-from-mean}.
 In summary, you should prefer the Poisson distribution when you are simulating 
the following scenarios:
 @itemize
@@ -27910,7 +27910,7 @@ Therefore the measurements discussed here are commonly 
used in units of magnitud
 @subsubsection Standard deviation vs error
 The error and the standard deviation are sometimes confused with each other.
 Therefore, before continuing with the various measurement limits below, let's 
review these two fundamental concepts.
-Instead of going into the theoretical defitions of the two (which you can see 
in their resepctive Wikipedia pages), we'll discuss the concepts in a hands-on 
and practical way here.
+Instead of going into the theoretical definitions of the two (which you can 
see in their respective Wikipedia pages), we'll discuss the concepts in a 
hands-on and practical way here.
 
 Let's simulate an observation of the sky, but without any astronomical sources!
 In other words, where we only a background flux level (from the sky emission).
@@ -27932,7 +27932,7 @@ $ astscript-fits-view 1.fits
 Each pixel shows the result of one sampling from the Poisson distribution.
 In other words, assuming the sky emission in our simulation is constant over 
our field of view, each pixel's value shows one measurement of the sky emission.
 Statistically speaking, a ``measurement'' is a sampling from an underlying 
distribution of values.
-Through our measurements, we aim to identfy that underlying distribution (the 
``truth'')!
+Through our measurements, we aim to identify that underlying distribution (the 
``truth'')!
 With the command below, let's look at the pixel statistics of @file{1.fits} 
(output is shown immediately under it).
 
 @c If you change this output, replace the standard deviation (10.09) below
@@ -27971,7 +27971,7 @@ As expected, you see that the ASCII histogram nicely 
resembles a normal distribu
 The measured mean and standard deviation (@mymath{\sigma_x}) are also very 
similar to the input (mean of 100, standard deviation of @mymath{\sigma=10}).
 But the measured mean (and standard deviation) aren't exactly equal to the 
input!
 
-Every time we make a different simulated image from the same distribution, the 
measured mean and standrad deviation will slightly differ.
+Every time we make a different simulated image from the same distribution, the 
measured mean and standard deviation will slightly differ.
 With the second command below, let's build 500 images like above and measure 
their mean and standard deviation.
 The outputs will be written into a file (@file{mean-stds.txt}; in the first 
command we are deleting it to make sure we write into an empty file within the 
loop).
 With the third command, let's view the top 10 rows:
@@ -28069,7 +28069,7 @@ In astronomical literature, this is simply referred to 
as the ``error''.
 
 In other words, when asking for an ``error'' measurement with MakeCatalog, a 
separate standard deviation dataset should be always provided.
 This dataset should take into account all sources of scatter.
-For example, during the reduction of an image, the standard deviation dataset 
should take into account the dispersion of each pixel that cames from the bias, 
dark, flat fielding, etc.
+For example, during the reduction of an image, the standard deviation dataset 
should take into account the dispersion of each pixel that comes from the bias, 
dark, flat fielding, etc.
 If this image is not available, it is possible to use the  @code{SKY_STD} 
extension from NoiseChisel as an estimation.
 For more see @ref{NoiseChisel output}.
 @end table
@@ -32904,7 +32904,7 @@ However, the Earth is orbiting the Sun at a very high 
speed of roughly 15 degree
 Keeping the (often very large!) telescopes in track with this fast moving sky 
is not easy; such that most cannot continue accurate tracking more than 10 
minutes.
 @item
 @cindex Seeing
-For ground-based observations, the turbulance of the atmosphere changes very 
fast (on the scale of minutes!).
+For ground-based observations, the turbulence of the atmosphere changes very 
fast (on the scale of minutes!).
 So if you plan to observe at 10 minutes and at the start of your observations 
the seeing is good, it may happen that on the 8th minute, it becomes bad.
 This will affect the quality of your final exposure!
 @item
@@ -32913,7 +32913,7 @@ When an exposure is taken, the instrument/environment 
imprint a lot of artifacts
 One common example that we also see in normal cameras is 
@url{https://en.wikipedia.org/wiki/Vignetting, vignetting}; where the center 
receives a larger fraction of the incoming light than the periphery).
 In order to characterize and remove such artifacts (which depend on many 
factors at the precision that we need in astronomy!), we need to take many 
exposures of our science target.
 @item
-By taking many exposures we can build a stack that has a higher resolution; 
this is often done in under-sampled data, like those in the hubble space 
telescope or JWST.
+By taking many exposures we can build a stack that has a higher resolution; 
this is often done in under-sampled data, like those in the Hubble Space 
Telescope (HST) or James Webb Space Telescope (JWST).
 @item
 The scientific target can be larger than the field of view of your telescope 
and camera.
 @end itemize
@@ -32922,7 +32922,7 @@ The scientific target can be larger than the field of 
view of your telescope and
 In the jargon of observational astronomers, each exposure is also known as a 
``dither'' (literally/generally meaning ``trembling'' or ``vibration'').
 This name was chosen because two exposures are not usually taken on exactly 
the same position of the sky (known as ``pointing'').
 In order to improve all the item above, we often move the center of the field 
of view from one exposure to the next.
-In most cases this movement is small compared to the field of view, so most of 
the central part of the final stack has a fixed depth, but the edges are 
shallower (conveying a sence of vibration).
+In most cases this movement is small compared to the field of view, so most of 
the central part of the final stack has a fixed depth, but the edges are 
shallower (conveying a sense of vibration).
 When the spacing between pointings is large, they are known as an ``offset''.
 A ``pointing'' is used to refer to either a dither or an offset.
 
@@ -32965,7 +32965,7 @@ $ astscript-pointing-simulate pointing.fits 
--output=stack.fits \
 
 The default output of this script is a stacked image that results from placing 
the given image (given to @option{--img}) in the pointings of a pointing 
pattern.
 The Right Ascension (RA) and Declination (Dec) of each pointing is given in 
the main input catalog (@file{pointing.fits} in the example above).
-The center and width of the final stack (both in degrees by default) should be 
speficied using the @option{--width} option.
+The center and width of the final stack (both in degrees by default) should be 
specified using the @option{--width} option.
 Therefore, in order to successfully run, this script at least needs the 
following four inputs:
 @table @asis
 @item Pointing positions
@@ -33028,7 +33028,7 @@ The central RA and Declination of the final stack in 
degrees.
 
 @item -w FLT,FLT
 @itemx --width=FLT,FLT
-The width of the final stack in degress.
+The width of the final stack in degrees.
 If @option{--widthinpix} is given, the two values given to this option will be 
interpreted as degrees.
 
 @item --widthinpix
@@ -33052,7 +33052,7 @@ If it is not created by your script, the script will 
complain and abort.
 This file will be given to Warp to be warped into the output pixel grid.
 @end table
 
-For an example of using hooks with an exteded discussion, see @ref{Pointing 
pattern design} and @ref{Accounting for non-exposed pixels}.
+For an example of using hooks with an extended discussion, see @ref{Pointing 
pattern design} and @ref{Accounting for non-exposed pixels}.
 
 To develop your command, you can use @command{--hook-warp-before='...; echo 
GOOD; exit 1'} (where @code{...} can be replaced by any command) and run the 
script on a single thread (with @option{--numthreads=1}) to produce a single 
file and simplify the checking that your desired operation works as expected.
 All the files will be within the temporary directory (see @option{--tmpdir}).
@@ -33103,7 +33103,7 @@ Keep the temporary directory (and do not delete it).
 
 @item -?
 @itemx --help
-Print a list of all the options, along with a short descrioption and context 
for the program.
+Print a list of all the options, along with a short description and context 
for the program.
 For more, see @option{Operating mode options}.
 
 @item -N INT
@@ -33113,7 +33113,7 @@ If not given (by default), the script will try to find 
the number of available t
 For more, see @option{Operating mode options}.
 
 @item --cite
-Give BibTeX and Acknowledgement information for citing this script within your 
paper.
+Give BibTeX and acknowledgment information for citing this script within your 
paper.
 For more, see @option{Operating mode options}.
 
 @item -q
@@ -35689,7 +35689,7 @@ Return a ``flag'' dataset with the same size as the 
input, but with an @code{uin
 
 @deftypefun {size_t *} gal_blank_not_minmax_coords (gal_data_t @code{*input})
 Find the minimum and maximum coordinates of the non-blank regions within the 
input dataset.
-The coordinates are in C order: starting from 0, and with the slowest dimsion 
being first.
+The coordinates are in C order: starting from 0, and with the slowest 
dimension being first.
 The output is an allocated array (that should be freed later) with 
@mymath{2\times N} elements; where @mymath{N} is the number of dimensions.
 The first two elements contain the minimum and maximum of regions containing 
non-blank elements along the 0-th dimension (the slowest), the second two 
elements contain the next dimension's extrema; and so on.
 @end deftypefun
@@ -38708,7 +38708,7 @@ If you want the operation to be done in place (without 
allocating a new dataset)
 
 @deftypefun void gal_wcs_coordsys_sys1_ref_in_sys2 (int @code{sys1}, int 
@code{sys2}, double @code{*lng2}, double @code{*lat2})
 Return the longitude and latitude of the reference point (on the equator) of 
the first coordinate system (@code{sys1}) within the second system 
(@code{sys2}).
-Coordinate systems are identifed by the @code{GAL_WCS_COORDSYS_*} macros above.
+Coordinate systems are identified by the @code{GAL_WCS_COORDSYS_*} macros 
above.
 @end deftypefun
 
 @cindex WCS distortion
@@ -41282,7 +41282,7 @@ This will allow easy (non-confusing) access to the 
indices of each (meaningful)
 
 @code{numlabs} is the number of labels in the dataset.
 If it is given a value of zero, then the maximum value in the input (largest 
label) will be found and used.
-Therefore if it is given, but smaller than the actual number of labels, this 
function may/will crash (it will write in unallocated space).
+Therefore if it is given, but smaller than the actual number of labels, this 
function may/will crash (it will write in un-allocated space).
 @code{numlabs} is therefore useful in a highly optimized/checked environment.
 
 For example, if the returned array is called @code{indexs}, then
@@ -41449,7 +41449,7 @@ When @code{conv_on_blank} is non-zero, this function 
will also attempt convoluti
 @subsection Pooling functions (@file{pool.h})
 
 Pooling is the process of reducing the complexity of the input image (its size 
and variation of pixel values).
-Its underlying concepts and an analysis of its usefuless is fully descibed in 
@ref{Pooling operators}.
+Its underlying concepts, and an analysis of its usefulness, is fully described 
in @ref{Pooling operators}.
 The following functions are available pooling in Gnuastro.
 Just note that unlike the Arithmetic operators, the output of these functions 
should contain a correct WCS in their output.
 
@@ -41558,12 +41558,12 @@ The number of terms in the interpolating polynomial 
is equal to the number of po
 @cindex Cubic spline interpolation
 @cindex Spline (cubic) interpolation
 [From GSL:] Cubic spline with natural boundary conditions.
-The resulting curve is piecewise cubic on each interval, with matching first 
and second derivatives at the supplied data-points.
+The resulting curve is piece-wise cubic on each interval, with matching first 
and second derivatives at the supplied data-points.
 The second derivative is chosen to be zero at the first point and last point.
 @end deffn
 @deffn Macro GAL_INTERPOLATE_1D_CSPLINE_PERIODIC
 [From GSL:] Cubic spline with periodic boundary conditions.
-The resulting curve is piecewise cubic on each interval, with matching first 
and second derivatives at the supplied data-points.
+The resulting curve is piece-wise cubic on each interval, with matching first 
and second derivatives at the supplied data-points.
 The derivatives at the first and last points are also matched.
 Note that the last point in the data must have the same y-value as the first 
point, otherwise the resulting periodic interpolation will have a discontinuity 
at the boundary.
 @end deffn
@@ -41584,7 +41584,7 @@ This method uses the non-rounded corner algorithm of 
Wodicka.
 @cindex Interpolation: monotonic
 [From GSL:] Steffen's 
method@footnote{@url{http://adsabs.harvard.edu/abs/1990A%26A...239..443S}} 
guarantees the monotonicity of the interpolating function between the given 
data points.
 Therefore, minima and maxima can only occur exactly at the data points, and 
there can never be spurious oscillations between data points.
-The interpolated function is piecewise cubic in each interval.
+The interpolated function is piece-wise cubic in each interval.
 The resulting curve and its first derivative are guaranteed to be continuous, 
but the second derivative may be discontinuous.
 @end deffn
 
@@ -43385,7 +43385,7 @@ If a research project begins using Python 3.x today, 
there is no telling how com
 @cindex JVM: Java virtual machine
 @cindex Java Virtual Machine (JVM)
 Java is also fully object-oriented, but uses a different paradigm: its 
compilation generates a hardware-independent @emph{bytecode}, and a @emph{Java 
Virtual Machine} (JVM) is required for the actual execution of this bytecode on 
a computer.
-Java also evolved with time, and tried to remain backward compatible, but 
inevitably some evolutions required discontinuities and replacements of a few 
Java components which were first declared as becoming @emph{deprecated}, and 
removed from later versions.
+Java also evolved with time, and tried to remain backward compatible, but 
inevitably this evolution required discontinuities and replacements of a few 
Java components which were first declared as becoming @emph{deprecated}, and 
removed from later versions.
 
 @cindex Reproducibility
 This stems from the core principles of high-level languages like Python or 
Java: that they evolve significantly on the scale of roughly 5 to 10 years.