fix a few more typos (#130)

Author: m-fila

README.md

@@ -81,7 +81,7 @@ Three strategies are available for the different algorithms:
 | Strategy Name | Notes | Interface |
 |---|---|---|
 | `RecoStrategy.Best` | Dynamically switch strategy based on input particle density | `jet_reconstruct` |
-| `RecoStrategy.N2Plain` | Global matching of particles at each interation (works well for low $N$) | `plain_jet_reconstruct` |
+| `RecoStrategy.N2Plain` | Global matching of particles at each interaction (works well for low $N$) | `plain_jet_reconstruct` |
 | `RecoStrategy.N2Tiled` | Use tiles of radius $R$ to limit search space (works well for higher $N$) | `tiled_jet_reconstruct` |
 
 Generally one can use the `jet_reconstruct` interface, shown above, as the *Best* strategy safely as the overhead is extremely low. That interface supports a `strategy` option to switch to a different option.

docs/src/examples.md

@@ -64,7 +64,7 @@ jet reconstruction in the browser. This is a 3D plot where all the initial
 energy deposits are visualised, with colours that indicate in which final
 cluster the deposit ended up in.
 
-The first example is a Jupyter notbook, the second runs in Pluto.
+The first example is a Jupyter notebook, the second runs in Pluto.
 
 ### `animate-reconstruction.jl`
 

docs/src/strategy.md

@@ -7,7 +7,7 @@ to the reconstruction.
 | Strategy Name | Notes | Interface |
 |---|---|---|
 | `RecoStrategy.Best` | Dynamically switch strategy based on input particle density | `jet_reconstruct` |
-| `RecoStrategy.N2Plain` | Global matching of particles at each interation (works well for low $N$) | `plain_jet_reconstruct` |
+| `RecoStrategy.N2Plain` | Global matching of particles at each interaction (works well for low $N$) | `plain_jet_reconstruct` |
 | `RecoStrategy.N2Tiled` | Use tiles of radius $R$ to limit search space (works well for higher $N$) | `tiled_jet_reconstruct` |
 
 Generally one can use the `jet_reconstruct` interface, shown above, as the

test/_common.jl

@@ -19,7 +19,7 @@ const events_file_pp = joinpath(@__DIR__, "data", "events.pp13TeV.hepmc3.gz")
 const events_file_ee = joinpath(@__DIR__, "data", "events.eeH.hepmc3.gz")
 
 const pp_algorithms = Dict(-1 => "Anti-kt",
-                           0 => "Cambridge/Achen",
+                           0 => "Cambridge/Aachen",
                            1 => "Inclusive-kt",
                            1.5 => "Generalised-kt")
 

test/data/README.md

@@ -6,5 +6,5 @@
   - Unzip to `evemts.hepmc3` for actual use
 
 - `jet_collections_fastjet_akt.json` - JSON output from running anti-kt jet reconstruction using FastJet 3.4.1, with R=0.4 and p_t_min=5.0
-- `jet_collections_fastjet_ca.json` - JSON output from running Cambridge/Achen jet reconstruction using FastJet 3.4.1, with R=0.4 and p_t_min=5.0
+- `jet_collections_fastjet_ca.json` - JSON output from running Cambridge/Aachen jet reconstruction using FastJet 3.4.1, with R=0.4 and p_t_min=5.0
 - `jet_collections_fastjet_ikt.json` - JSON output from running inclusive-kt jet reconstruction using FastJet 3.4.1, with R=0.4 and p_t_min=5.0