diff --git a/docs/src/index.md b/docs/src/index.md
index 9c6a3b7f..dfa66f5c 100644
--- a/docs/src/index.md
+++ b/docs/src/index.md
@@ -8,7 +8,7 @@ CurrentModule = PowerNetworkMatrices
`PowerNetworkMatrices.jl` is a [`Julia`](http://www.julialang.org) package for
the evaluation of network matrices given the system's data. The package allows to compute
-the matrices according to different methods, providing a flexibe and powerful tool.
+the matrices according to different methods, providing a flexible and powerful tool.
The documentation and code are organized according to the needs of different
users depending on their skillset and requirements. In broad terms there are three categories:
diff --git a/docs/src/tutorials/tutorial_Incidence_BA_ABA_matrices.md b/docs/src/tutorials/tutorial_Incidence_BA_ABA_matrices.md
index c4cd49f1..806cb5cc 100644
--- a/docs/src/tutorials/tutorial_Incidence_BA_ABA_matrices.md
+++ b/docs/src/tutorials/tutorial_Incidence_BA_ABA_matrices.md
@@ -41,13 +41,13 @@ incidence_matrix.axes
# data: Incidence Matrix
incidence_matrix.data
-# lookup: dictionary linking the branche names and bus numbers with the row
+# lookup: dictionary linking the branches names and bus numbers with the row
# and column numbers, respectively.
incidence_matrix.axes
# ref_bus_positions: set containing the positions of the reference buses.
# this represents the positions where to add the column of zeros. Please refer to the
-# exaple in the BA matrix for more details.
+# example in the BA matrix for more details.
incidence_matrix.ref_bus_positions
```
@@ -63,7 +63,7 @@ the column related to the reference bus is discarded.
## BA_Matrix
The `BA_Matrix` is a structure containing the matrix coming from the product of the
-`IncidenceMatrix` and the diagonal matrix contianing the impedence of the system's branches ("B" matrix).
+`IncidenceMatrix` and the diagonal matrix containing the impedence of the system's branches ("B" matrix).
The `BA_Matrix` is computed as follows:
diff --git a/docs/src/tutorials/tutorial_LODF_matrix.md b/docs/src/tutorials/tutorial_LODF_matrix.md
index 348edc35..303b6494 100644
--- a/docs/src/tutorials/tutorial_LODF_matrix.md
+++ b/docs/src/tutorials/tutorial_LODF_matrix.md
@@ -7,7 +7,7 @@ Before diving into this tutorial we encourage the user to load `PowerNetworkMatr
As for the `PTDF` matrix, the `LODF` one can be evaluated according to two different approaches:
- `Dense`: considers functions for dense matrix multiplication and inversion
-- `KLU`: considers functions for sparse matrix multiplication and inversion(**default**)
+- `KLU`: considers functions for sparse matrix multiplication and inversion (**default**)
The evaluation of the `LODF` matrix can be easily performed starting from importing the system's data and then by simply calling the `LODF` method.
@@ -69,7 +69,7 @@ lodf_5 = LODF(a, aba, ba);
For those methods that either require the evaluation of the `PTDF` matrix, or that execute this evaluation internally, two different approaches casen be used.
-As for the `PTDF` matrix, here too the optional argument `linear_solver` can be specified with either `KLU` (for spars matrix calculation) or `Dense` (for sparse matrix calculation).
+As for the `PTDF` matrix, here too the optional argument `linear_solver` can be specified with either `KLU` (for sparse matrix calculation) or `Dense` (for sparse matrix calculation).
``` @repl tutorial_PTDF_matrix
lodf_dense = LODF(sys, linear_solver="Dense");
@@ -97,4 +97,4 @@ Please consider that 0.4 was used for the purpose of this tutorial. In practice
**NOTE (2):** the `tol` argument does not refer to the "sparsification" tolerance of the `PTDF` matrix that is computed in the `LODF` method.
-**NOTE (3):** in case the method `LODF(a::IncidenceMatrix, ptdf::PTDF)` is considerd, an error will be thrown whenever the `tol` argument in the `PTDF` structure used as input is different then 1e-15.
\ No newline at end of file
+**NOTE (3):** in case the method `LODF(a::IncidenceMatrix, ptdf::PTDF)` is considered, an error will be thrown whenever the `tol` argument in the `PTDF` structure used as input is different than `1e-15`.
\ No newline at end of file
diff --git a/docs/src/tutorials/tutorial_PTDF_matrix.md b/docs/src/tutorials/tutorial_PTDF_matrix.md
index ac286691..47603692 100644
--- a/docs/src/tutorials/tutorial_PTDF_matrix.md
+++ b/docs/src/tutorials/tutorial_PTDF_matrix.md
@@ -1,7 +1,7 @@
# PTDF matrix
In this tutorial the methods for computing the Power Transfer Distribution Factors (`PTDF`) are presented.
-Before diving into this tutorial we encourage the user to load `PowerNetworkMatrices`, hit the `?` key in the REPL terminal and look for the documentiont of the different `PTDF` methods avialable.
+Before diving into this tutorial we encourage the user to load `PowerNetworkMatrices`, hit the `?` key in the REPL terminal and look for the documention of the different `PTDF` methods available.
## Evaluation of the `PTDF` matrix
@@ -59,11 +59,11 @@ get_ptdf_data(ptdf_klu)
```
By default the "KLU" method is selected, which appeared to require significant less time and memory with respect to "Dense".
-Please note that either the `KLU` or `Dense` method isi used, the resultig `PTDF` matrix is stored as a dense one.
+Please note that either the `KLU` or `Dense` method is used, the resulting `PTDF` matrix is stored as a dense one.
## Evaluating the `PTDF` matrix considering distributed slack bus
-Whenever needed, the `PTDF` matrix can be computed with a distributed slack bus. To do so, a vecotr of type `Vector{Float64}` needs to be defined, specifying the weights for each bus of the system. These weights identify how the load on the slakc bus is redistributed accross the system.
+Whenever needed, the `PTDF` matrix can be computed with a distributed slack bus. To do so, a vector of type `Vector{Float64}` needs to be defined, specifying the weights for each bus of the system. These weights identify how the load on the slakc bus is redistributed accross the system.
``` @repl tutorial_PTDF_matrix
# consider equal distribution accross each bus for this example
@@ -78,7 +78,7 @@ Once the vector of the weights is defined, the `PTDF` matrix can be computed by
ptdf_distr = PTDF(sys, dist_slack=dist_slack_array);
```
-The diffrence between a the matrix computed with and without the `dist_slack` field defined can be seen as follows:
+The difference between a the matrix computed with and without the `dist_slack` field defined can be seen as follows:
``` @repl tutorial_PTDF_matrix
# with no distributed slack bus
diff --git a/docs/src/tutorials/tutorial_VirtualLODF_matrix.md b/docs/src/tutorials/tutorial_VirtualLODF_matrix.md
index 803feddc..20567227 100644
--- a/docs/src/tutorials/tutorial_VirtualLODF_matrix.md
+++ b/docs/src/tutorials/tutorial_VirtualLODF_matrix.md
@@ -8,7 +8,7 @@ Refer to the different arguments of the `VirtualLODF` methods by looking at the
The `VirtualLODF` structure retains many of the similarities of the `VirtualPTDF`. However, its computation is more complex and requires some additional data.
-Starting from the system data, the `IncidenceMatrix`, `BA_Matrix` and `ABA_Matrix` (with relative LU factorization matrices) are evaluated. The `ABA_Matrix` and `BA_Matrix` are used for the computation of the diagonal elements of the `PTDF` matrix, and this vector is stored in the `VirtualLODF` structure together with the other structures abovementioned.
+Starting from the system data, the `IncidenceMatrix`, `BA_Matrix` and `ABA_Matrix` (with relative LU factorization matrices) are evaluated. The `ABA_Matrix` and `BA_Matrix` are used for the computation of the diagonal elements of the `PTDF` matrix, and this vector is stored in the `VirtualLODF` structure together with the other structures mentioned above.
Once the `VirtualLODF` is initialized, each row of the matrix can be evaluated separately and on user request. The algorithmic procedure is the following:
1. Define the `VirtualPTDF` structure
@@ -19,12 +19,12 @@ Regarding point 2, if the row has been stored previosly then the desired element
The flowchart below shows how the `VirtualLODF` is structured and how it works. Examples will be presented in the following sections.
```@raw html
-
+
```
## Initialize `VirtualLODF` and compute/access row/element
-As for the `LODF` matrix, at first the `System` data must be loaded. The "RTS GMLC" systems is considered as example:
+As for the `LODF` matrix, at first the `System` data must be loaded. The "RTS-GMLC" systems is considered as example:
``` @repl tutorial_VirtualPTDF_matrix
using PowerNetworkMatrices
@@ -58,9 +58,9 @@ col_number = v_lodf.lookup[2]["A3"]
el_C31_2_105_bis = v_lodf[row_number, col_number]
```
-**NOTE**: this example was made for the sake of completeness and considering the actual branch names is reccomended.
+**NOTE**: this example was made for the sake of completeness and considering the actual branch names is recommended.
-As previosly mentioned, in order to evalute a single element of the `VirtualLODF`, the entire row related to the selected branch must be considered. For this reason it is cached for later calls.
+As previosly mentioned, in order to evaluate a single element of the `VirtualLODF`, the entire row related to the selected branch must be considered. For this reason it is cached for later calls.
This is evident by looking at the following example:
``` @repl tutorial_VirtualPTDF_matrix
diff --git a/docs/src/tutorials/tutorial_VirtualPTDF_matrix.md b/docs/src/tutorials/tutorial_VirtualPTDF_matrix.md
index 7afcb5d6..443a6568 100644
--- a/docs/src/tutorials/tutorial_VirtualPTDF_matrix.md
+++ b/docs/src/tutorials/tutorial_VirtualPTDF_matrix.md
@@ -18,12 +18,12 @@ Regarding point 2, if the row has been stored previosly then the desired element
The flowchart below shows how the `VirtualPTDF` is structured and how it works. Examples will be presented in the following sections.
```@raw html
-
+
```
## Initialize `VirtualPTDF` and compute/access row/element
-As for the `PTDF` matrix, at first the `System` data must be loaded. The "RTS GMLC" systems is considered as example:
+As for the `PTDF` matrix, at first the `System` data must be loaded. The "RTS-GMLC" systems is considered as example:
``` @repl tutorial_VirtualPTDF_matrix
using PowerNetworkMatrices
@@ -57,7 +57,7 @@ el_C31_2_105_bis = v_ptdf[row_number, col_number]
**NOTE**: this example was made for the sake of completeness and considering the actual branch name and bus number is reccomended.
-As previosly mentioned, in order to evalute a single element of the `VirtualPTDF`, the entire row related to the selected branch must be considered. For this reason it is cached in the `VirtualPTDF` structure for later calls.
+As previosly mentioned, in order to evaluate a single element of the `VirtualPTDF`, the entire row related to the selected branch must be considered. For this reason it is cached in the `VirtualPTDF` structure for later calls.
This is evident by looking at the following example:
``` @repl tutorial_VirtualPTDF_matrix
@@ -75,7 +75,7 @@ v_ptdf_2k = VirtualPTDF(sys_2k);
## `VirtualPTDF` with distributed slack bus
As for the `PTDF` matrix, here too each row can be evaluated considering distibuted slack buses.
-A vecotr of type `Vector{Float64}` is defined, specifying the weights for each bus of the system.
+A vector of type `Vector{Float64}` is defined, specifying the weights for each bus of the system.
``` @repl tutorial_VirtualPTDF_matrix
# smaller system for the next examples
@@ -94,7 +94,7 @@ v_ptdf_distr = VirtualPTDF(sys_2, dist_slack=dist_slack_array);
v_ptdf_orig = VirtualPTDF(sys_2);
```
-Now check the difference with the same row related to the branch `"1"` evaluated withou considering distributed slack bus.
+Now check the difference with the same row related to the branch `"1"` evaluated without considering distributed slack bus.
``` @repl tutorial_VirtualPTDF_matrix
row_distr = [v_ptdf_distr["1", j] for j in v_ptdf_distr.axes[2]]
diff --git a/src/virtual_ptdf_calculations.jl b/src/virtual_ptdf_calculations.jl
index 13deeee3..afc37c7e 100644
--- a/src/virtual_ptdf_calculations.jl
+++ b/src/virtual_ptdf_calculations.jl
@@ -24,7 +24,7 @@ matrix.
- `axes<:NTuple{2, Dict}`:
Tuple containing two vectors: the first one showing the branches names,
the second showing the buses numbers. There is no link between the
- order of the vector of the branche names and the way the PTDF rows are
+ order of the vector of the branches names and the way the PTDF rows are
stored in the cache.
- `lookup<:NTuple{2, Dict}`:
Tuple containing two dictionaries, mapping the branches