diff --git a/_typos.toml b/_typos.toml new file mode 100644 index 00000000..04422f44 --- /dev/null +++ b/_typos.toml @@ -0,0 +1,9 @@ +[default] +extend-ignore-identifiers-re = [ + "allk", + "als", + "Nd", + "iy", + "pn", + "MIRTio", +] diff --git a/doc/start-juno.md b/doc/start-juno.md index aebc8453..ee024bd2 100644 --- a/doc/start-juno.md +++ b/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: diff --git a/doc/start.md b/doc/start.md index 2596e9a1..518bca8f 100644 --- a/doc/start.md +++ b/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 diff --git a/src/algorithm/general/pogm_restart.jl b/src/algorithm/general/pogm_restart.jl index 47f9520e..40e9e3f0 100644 --- a/src/algorithm/general/pogm_restart.jl +++ b/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] diff --git a/src/mri/kspace-spiral.jl b/src/mri/kspace-spiral.jl index 2602c030..7389d77e 100644 --- a/src/mri/kspace-spiral.jl +++ b/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 diff --git a/src/regularize/diffl.jl b/src/regularize/diffl.jl index bd8ab91c..5886347a 100644 --- a/src/regularize/diffl.jl +++ b/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.