Fix most typos in non-code files

.typos.toml

@@ -24,4 +24,5 @@ extend-exclude = [
 IDAES = "IDAES"
 FO = "FO"  # TODO: probably an abbreviation?
 sur = "sur"  # abbreviation for 'surrogate'
-nd = "nd"  # used as a variable name in sdoeAnalysisDialog
+nd = "nd"  # used as a variable name in sdoeAnalysisDialog
+astroid = "astroid"  # Python package name

README.md

@@ -34,13 +34,13 @@ See our [FAQ](FAQs.md) for frequently asked questions and answers
 See also the list of [contributors](../../graphs/contributors) who participated in this project.
 
 ## Development Practices
-* Code development will be peformed in a forked copy of the repo. Commits will not be 
+* Code development will be performed in a forked copy of the repo. Commits will not be 
   made directly to the repo. Developers will submit a pull request that is then merged
   by another team member, if another team member is available.
 * Each pull request should contain only related modifications to a feature or bug fix.  
 * Sensitive information (secret keys, usernames etc) and configuration data 
   (e.g database host port) should not be checked in to the repo.
-* A practice of rebasing with the main repo should be used rather that merge commmits.
+* A practice of rebasing with the main repo should be used rather that merge commits.
 
 ## Versioning
 We use [SemVer](http://semver.org/) for versioning. For the versions available, 

docs/source/chapt_dev/index.rst

@@ -3,7 +3,7 @@
 Developer Documentation
 =======================
 
-Since the `source code for all of FOQUS is publically available
+Since the `source code for all of FOQUS is publicly available
 <https://github.com/CCSI-Toolset/FOQUS>`_, the more adventurous user may wish to look at the
 inner-workings of FOQUS to get a better understand how it works, contribute a fix to a bug, or add
 new features to the source tree. Other members of our CCSI partnership (national laboratories,

docs/source/chapt_flowsheet/reference/settings.rst

@@ -22,7 +22,7 @@ FOQUS** tab.
 
 Options in the **Settings, FOQUS** tab are described below.
 
-#. **Save settings to working directoy**, when checkbox is selected the
+#. **Save settings to working directory**, when checkbox is selected the
    settings file will be read from the specified working directory. This
    setting is useful for running multiple copies of FOQUS to ensure the
    settings do not conflict. When starting additional copies of FOQUS,

docs/source/chapt_install/run_foqus.rst

@@ -58,4 +58,4 @@ e.g., for the Bash shell:
 
 If, on the contrary, a graphical interface *is* desired but the errors above occur, it is possible that the system is not yet configured to support graphical applications.
 In this case, try installing the :code:`libgl1-mesa-glx` and/or :code:`libxkbcommon-x11-0` packages using
-the package manager appropriate for your Linux distrubution (i.e. :code:`apt-get install` on Ubuntu).
+the package manager appropriate for your Linux distribution (i.e. :code:`apt-get install` on Ubuntu).

docs/source/chapt_matlab/reference/matlab_foqus_intro.rst

@@ -54,7 +54,7 @@ If the MATLAB engine package was installed correctly, a similar message to the F
 
 .. figure:: ../figs/terminal_window_msg.png
 
-   Figure 1 - Terminal window message after installating the MATLAB engine package
+   Figure 1 - Terminal window message after installing the MATLAB engine package
 
 Now, to run MATLAB models within FOQUS follow the steps below:
 

docs/source/chapt_odoe/tutorial-createcand.rst

@@ -111,7 +111,7 @@ In this example, the user will generate a new candidate set.
 
    Browse and load the EvaluationSet.csv file from the examples folder. Similar to the candidate set
    section, the user can select the evaluation set and click on the **Delete Selection** button in
-   case they want to delete the evaulation set. To visualize the data, just click the **View**
+   case they want to delete the evaluation set. To visualize the data, just click the **View**
    button under the **Visualize** column.
 
    .. figure:: figs/9b_ODoE_Cand&EvalSets.png

docs/source/chapt_odoe/tutorial-loadcand.rst

@@ -98,7 +98,7 @@ In this example, the user will provide an existing candidate set.
 
    Browse and load the EvaluationSet.csv file from the examples folder. Similar to the candidate set
    section, the user can select the evaluation set and click on the **Delete Selection** button in
-   case they want to delete the evaulation set. To visualize the data, just click the **View**
+   case they want to delete the evaluation set. To visualize the data, just click the **View**
    button under the **Visualize** column.
 
    .. figure:: figs/9a-2_ODoE_Cand&EvalSets.png

docs/source/chapt_sdoe/basics-runorder.rst

@@ -2,7 +2,7 @@ Efficient Implementation of Experimental Run Order
 ==================================================
 
 Once designs have been created, it is often important to optimize the run order to efficiently reach equilibrium and 
-allow for the maximum number of runs to be implemented within a constrainted budget or time period. While statisticians 
+allow for the maximum number of runs to be implemented within a constrained budget or time period. While statisticians 
 generally recommend using a randomized order for the experimental runs, it can sometimes mean the difference of a small 
 randomized experiment versus a larger non-randomized experiment. 
 

docs/source/chapt_surrogates/mlaiplugin.rst

@@ -99,7 +99,7 @@ Currently, FOQUS supports the following custom attributes:
   bounds for each output variable (default: (0, 1E5))
 - *normalized* – Boolean flag for whether the user is passing a normalized
   neural network model; to use this flag, users must train their models with
-  data normalized according to a specifc scaling form and add all input and
+  data normalized according to a specific scaling form and add all input and
   output bounds custom attributes. The section below details scaling options.
 - *normalization_form* - string flag required when *normalization* is *True*
   indicating a scaling option for FOQUS to automatically scale flowsheet-level

docs/source/chapt_surrogates/tutorial/alamo.rst

@@ -139,7 +139,7 @@ data is provided and adaptive sampling is used.
 
    Sample Distributions
 
-19. The **Sampling schem\ e** dialog should display (Figure
+19. The **Sampling scheme** dialog should display (Figure
     :ref:`fig.tut.sur.new.uq.sample2`).
     Select “Latin Hypercube” from the list.
 
@@ -216,15 +216,15 @@ other and for the model building, selecting one output is the same as
 selecting more.
 
 30. Select the **Variable\ s** tab (Figure
-    :ref:`fig.tut.sur.vaiables`).
+    :ref:`fig.tut.sur.variables`).
 
 31. Select the checkbox for both input variables.
 
 32. Select the checkbox for both output variables.
 
 .. figure:: ../figs/variables.svg
    :alt: Variable Selection
-   :name: fig.tut.sur.vaiables
+   :name: fig.tut.sur.variables
 
    Variable Selection
 

docs/source/chapt_vector_support/example2/Aspen_Model_Vectors_Handling.rst

@@ -77,8 +77,8 @@ Vectorize" will be displayed as shown in Figure 3.
           elements required as a part of the vector.
 
           In this case, "B_TEMP" is the variable name corresponding to the
-          liquid phase temerature along the absorber column, and "TVAP" is the
-          variable name corresponding to the vapor phase temerature along the
+          liquid phase temperature along the absorber column, and "TVAP" is the
+          variable name corresponding to the vapor phase temperature along the
           absorber column, according to their path in SimSinter.
           These vector variables are indexed over the absorber stages, which is
           why the number of elements in each of them would be 90.
@@ -104,7 +104,7 @@ steps 3 and 4 with the correct user inputs. If it is created, open the json file
 directly to check whether it has been modified correctly.
 
 In the json file, the dictionary corresponding to the "outputs" key must contain
-180 scalar variables 90 each corrsponding to the vector variables "B_TEMP" and
+180 scalar variables 90 each corresponding to the vector variables "B_TEMP" and
 "TVAP". Each scalar output variable corresponding to the vector must contain a
 "vector" field which includes the vector variable it is associated with, and an
 "index" field, which defines its location in the vector. The indices range from