Fix typos

_typos.toml

@@ -0,0 +1,9 @@
+[default]
+extend-ignore-identifiers-re = [
+    "allk",
+    "als",
+    "Nd",
+    "iy",
+    "pn",
+    "MIRTio",
+]

doc/start-juno.md

@@ -43,7 +43,7 @@ jim(x, title="test")
 * This test should produce a grayscale image of the famous
 [Shepp-Logan phantom](https://en.wikipedia.org/wiki/Shepp%E2%80%93Logan_phantom) in the Plots tab of Atom.
 * To learn about the jiffy image display function `jim`, type `?jim` at the REPL.
-* Juno and Atom have lots of online documention.
+* Juno and Atom have lots of online documentation.
 I use the `vim-mode-plus` key bindings, installed using Atom preferences.
 
 * To start a Jupyter notebook for Julia, type at the REPL:

doc/start.md

@@ -1,17 +1,22 @@
-* Install Julia (1.5 or later recommended) from https://julialang.org/
-* Explore the extensive documentation at https://docs.julialang.org/
+* Install Julia (1.10 or later recommended) from https://julialang.org
+* Explore the extensive documentation at https://docs.julialang.org
 * Launch Julia and use the `]` key to enter its package manager.
 * Add any packages needed for these notebooks using the `add` command.
 * For example `add Plots` to add the `Plots` package.
 * Other crucial standard packages are `FFTW` `FFTViews`
 * You will also need the package `IJulia` to run any Jupyter demo notebooks.
 * Add MIRT by typing `add MIRT`
-(Automatically loads from https://github.com/JeffFessler/MIRT.jl because MIRT.jl is a registered package.)
+  (Automatically loads from https://github.com/JeffFessler/MIRT.jl
+  because MIRT.jl is a registered package.)
 * Type `precompile` to have Julia precompile the added packages.
-* After you are done adding packages, press the backspace key to return to the REPL prompt.
-* Later if you need to add more packages just type the `]` key again at the REPL prompt to enter the package manager.
-* Julia is under active development so code is updated frequently.  It is a wise to type `up` (short for `update`) at the package manager prompt every week or so to get automatic updates of any packages you have intalled.
+* After you are done adding packages, press the backspace key
+  to return to the REPL prompt.
+* Later if you need to add more packages just type the `]` key again
+  at the REPL prompt to enter the package manager.
+* Julia is under active development so code is updated frequently.
+  It is a wise to type `up` (short for `update`) at the package manager prompt
+  every week or so to get automatic updates of any packages you have installed.
 * For some Julia tutorials see
-http://web.eecs.umich.edu/~fessler/course/551/julia/tutor/
+  http://web.eecs.umich.edu/~fessler/course/551/julia/tutor
 * For some signal processing demos in Julia see
-http://web.eecs.umich.edu/~fessler/course/551/julia/demo/
+  http://web.eecs.umich.edu/~fessler/course/551/julia/demo

src/algorithm/general/pogm_restart.jl

@@ -71,7 +71,7 @@ iterate as below for given coefficients ``(\\alpha, \\beta_k, \\gamma_k)``
   - ``x_{k+1} = y_{k+1} + \\beta_k  (y_{k+1} - y_k) + \\gamma_k  (y_{k+1} - x_k)`` : momentum update
 
 Proximal versions of the above for ``g(x) \\neq 0`` are in the below references,
-and use the proximal operater
+and use the proximal operator
 ``prox_g(z) = argmin_x {1/2\\|z-x\\|^2 + g(x)}``.
 
 - Proximal Gradient method (PGM or ISTA) - ``\\beta_k = \\gamma_k = 0``. [BT09]

src/mri/kspace-spiral.jl

@@ -17,7 +17,7 @@ using Interpolations
 Make k-space spiral trajectory based on GE 3T scanner constraints
 
 Option:
-- `N` dimention of reconstructed image
+- `N` dimension of reconstructed image
 - `Nt` # of time points
 - `fov` field of view in cm
 - `dt` time sampling interval out; default `5e-6` sec
@@ -163,7 +163,7 @@ to gradients at 4us.
 
 Multi-shot spiral design
 uses Duyn's approximate slewrate limited design
-augmented with archimedian `gmax` limit
+augmented with archimedean `gmax` limit
 
 # in [args]
 * `D` = FOV; cm

src/regularize/diffl.jl

@@ -1,6 +1,6 @@
 #=
 diffl.jl
-Left finite differences "in-place" (pre-allocated outpus)
+Left finite differences "in-place" (pre-allocated outputs)
 
 Could use StaticKernels.jl for this; see timing test in ../../time.