pyvista · tkoyama010 · Aug 22, 2022 · Jul 24, 2022 · Jul 24, 2022 · Jul 24, 2022
diff --git a/README.md b/README.md
@@ -8,7 +8,7 @@
 
 [PyVista](https://github.com/pyvista/pyvista) is a general purpose 3D visualization library used for over 500+ open source projects and many closed source projects for the visualization of everything from [computer aided engineering and geophysics to volcanoes and digital artwork](https://dev.pyvista.org/getting-started/external_examples.html).
 
-PyVista exposes a Pythonic API to the [Visualization Toolkit (VTK)](http://www.vtk.org) to provide tooling that is immediately usable without any prior knowledge of VTK and is being built as the 3D equivalent of [matplotlib](https://matplotlib.org/), with plugins to [Jupyter](https://jupyter.org/) to enable visualization of 3D data using both server and client-side rendering.
+PyVista exposes a Pythonic API to the [Visualization Toolkit (VTK)](http://www.vtk.org) to provide tooling that is immediately usable without any prior knowledge of VTK and is being built as the 3D equivalent of [Matplotlib](https://matplotlib.org/), with plugins to [Jupyter](https://jupyter.org/) to enable visualization of 3D data using both server and client-side rendering.
 
 We will provide a hands-on tutorial accessible to anyone with internet access and a computer via many of PyVista's existing [example Jupyter notebooks](https://docs.pyvista.org/examples/index.html) and new material through a comprehensive overview highlighting popular 3D visualization use cases.
 
@@ -111,7 +111,7 @@ Past experience as a speaker:
 - [PyConJP 2019 speaker "Introduction to FEM Analysis with Python"](https://youtu.be/6JuB1GiDLQQ)
 - [PyConJP 2020 speaker "How to plot unstructured mesh file on Jupyter Notebook"](https://youtu.be/X3Z54Kw4I6Y)
 - [SciPy Japan 2020 speaker "Translation Project of Mayavi2 documents"](https://youtu.be/epxm9SjLMS0)
-- [PyConJP 2021 speaker "Visualize 3D scientific data in a Pythonic way like matplotlib"](https://youtu.be/ru-nENLgleo)
+- [PyConJP 2021 speaker "Visualize 3D scientific data in a Pythonic way like Matplotlib"](https://youtu.be/ru-nENLgleo)
 
 
 

diff --git a/doc/source/index.rst b/doc/source/index.rst
@@ -100,7 +100,7 @@ Tutorial Description
 - Use PyVista to create 3D visualizations from a variety of datasets in common
   formats.
 - Overview the classes and data structures of PyVista with real-world examples.
-- Be familiar of the various filters and features of PyVista.
+- Be familiar with the various filters and features of PyVista.
 - Know which Python libraries are used and can be used by PyVista (meshio,
   trimesh etc).
 
@@ -113,7 +113,7 @@ domain, and this ranges from basic Python users to advanced power users.
    <https://numpy.org/>`_ and other libraries that are compatible with PyVista,
    like `trimesh <https://trimsh.org/examples.html>`_ or `meshio
    <https://github.com/nschloe/meshio>`_.
-3. Advanced users should be familiar the Visualization Toolkit (VTK), general
+3. Advanced users should be familiar with the Visualization Toolkit (VTK), general
    data science, and GUI frameworks like Qt.
 
 

diff --git a/tutorial/00_intro/README.rst b/tutorial/00_intro/README.rst
@@ -11,9 +11,9 @@ This section includes a brief explanation of the background and history of PyVis
     <https://docs.pyvista.org/getting-started/index.html>`_ chapter of the
     PyVista documentation.
 
-PyVista is one of many visulization libraries built on top `VTK - The
+PyVista is one of many visualization libraries built on top `VTK - The
 Visualization Toolkit <https://vtk.org/>`_. It's primary intent was to be an
-abstraction layer over VTK to provide conviencece and functionality to VTK
+abstraction layer over VTK to provide convenience and functionality to VTK
 exposed "Pythonically".
 
 
@@ -81,7 +81,7 @@ Read a Surface Mesh and Plot it
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 VTK is powerful, really powerful! You can do just about anything within VTK and
 PyVista just wants to make it easier to do it using ``numpy``-like and
-``matplotlib``-like syntax. For example, if you wanted to be able to plot a
+``Matplotlib``-like syntax. For example, if you wanted to be able to plot a
 simple surface mesh:
 
 

diff --git a/tutorial/02_mesh/README.rst b/tutorial/02_mesh/README.rst
@@ -32,7 +32,7 @@ do not have to get bogged down in the nuances.
    This is a very high level overview of the PyVista API to familiarize users
    with PyVista's data structures.  For further details regarding our data
    model, how it relates to the underlying VTK data model, and how to create
-   your own meshes, please see `this detailed guide of of the Data Model <https://docs.pyvista.org/user-guide/data_model.html>`_.
+   your own meshes, please see `this detailed guide of the Data Model <https://docs.pyvista.org/user-guide/data_model.html>`_.
 
 
 What is a point?

diff --git a/tutorial/03_figures/README.rst b/tutorial/03_figures/README.rst
@@ -14,7 +14,7 @@ Demonstrate many features of the PyVista plotting API to create compelling 3D vi
 PyVista enables many possibilities for altering how you display 3D data, a few of our
 most common features include:
 
-* Color mapping scalar values with ``matplotlib`` colormaps
+* Color mapping scalar values with ``Matplotlib`` colormaps
 * Showing the edges and nodes of different mesh types
 * Label points in 3D space along side your meshes
 * Creating side-by-side comparisons
@@ -32,13 +32,13 @@ The Basics
 ----------
 
 PyVista's plotting API is data-centric, where the 3D data are individually added to the scene with different display parameters
-in a matplotlib-like fashion.
+in a Matplotlib-like fashion.
 
 
 ``add_mesh``
 ~~~~~~~~~~~~
 
-When plotting, users must first create a :class:`pyvista.Plotter` instance (much like a matplotlib figure). Then data are added to the plotter instance through the :func:`pyvista.Plotter.add_mesh` method. This workflow typically looks like:
+When plotting, users must first create a :class:`pyvista.Plotter` instance (much like a Matplotlib figure). Then data are added to the plotter instance through the :func:`pyvista.Plotter.add_mesh` method. This workflow typically looks like:
 
 .. jupyter-execute::
    :hide-code:
@@ -235,7 +235,7 @@ Controlling the Scene
 Axes and Bounds
 ~~~~~~~~~~~~~~~
 
-Aexs can be added to the scene with :func:`pyvista.Plotter.show_axes`
+Axes can be added to the scene with :func:`pyvista.Plotter.show_axes`
 
 .. pyvista-plot::
 

diff --git a/tutorial/03_figures/a_lesson_figures.py b/tutorial/03_figures/a_lesson_figures.py
@@ -111,7 +111,7 @@
 # Axes and Bounds
 # +++++++++++++++
 #
-# Aexs can be added to the scene with :func:`pyvista.Plotter.show_axes`
+# Axes can be added to the scene with :func:`pyvista.Plotter.show_axes`
 
 
 mesh = examples.load_random_hills()

diff --git a/tutorial/03_figures/exercises/b_lighting_mesh.py b/tutorial/03_figures/exercises/b_lighting_mesh.py
@@ -52,7 +52,7 @@
 mesh.plot(..., cpos=cpos, show_scalar_bar=False)
 
 ###############################################################################
-# Demonstration of all diffues, specular, and ambient in use together
+# Demonstration of all diffuse, specular, and ambient in use together
 # (feel free to adjust)
 mesh.plot(..., cpos=cpos, show_scalar_bar=False)
 

diff --git a/tutorial/03_figures/solutions/b_lighting_mesh.py b/tutorial/03_figures/solutions/b_lighting_mesh.py
@@ -54,7 +54,7 @@
 mesh.plot(specular=0.5, specular_power=15, cpos=cpos, show_scalar_bar=False)
 
 ###############################################################################
-# Demonstration of all diffues, specular, and ambient in use together
+# Demonstration of all diffuse, specular, and ambient in use together
 # (feel free to adjust)
 mesh.plot(diffuse=0.5, specular=0.5, ambient=0.5, cpos=cpos, show_scalar_bar=False)
 

diff --git a/tutorial/06_vtk/README.rst b/tutorial/06_vtk/README.rst
@@ -292,7 +292,7 @@ you may want to use VTK classes directly.
 PyVista and VTK Together
 ------------------------
 
-PyVista is best known for is easy to use plotting API -- being familiar to most Python users already experienced with libraries like matplotlib. Many people benefit from combining the power of VTK's Python bindings for their data pipelines and the flexibility and simplicity of PyVista for 3D rendering. The following section demonstrates this usage scenario.
+PyVista is best known for is easy to use plotting API -- being familiar to most Python users already experienced with libraries like Matplotlib. Many people benefit from combining the power of VTK's Python bindings for their data pipelines and the flexibility and simplicity of PyVista for 3D rendering. The following section demonstrates this usage scenario.
 
 .. tip::
 

diff --git a/tutorial/06_vtk/c_vtk_algorithms.py b/tutorial/06_vtk/c_vtk_algorithms.py
@@ -70,6 +70,6 @@
 # ^^^^^^^^^^^^^^^^^^^^
 #
 # Take a look at VTK's examples and documentation to find a filter you'd like
-# to apply to you mesh. The instructors will be around to help you implement.
+# to apply to your mesh. The instructors will be around to help you implement.
 #
 # See https://kitware.github.io/vtk-examples/site/Python/
diff --git a/tutorial/07_sphinx/README.rst b/tutorial/07_sphinx/README.rst
@@ -15,13 +15,13 @@ Leverage PyVista to make some awesome interactive web documentation.
 Dynamically Generating 3D Plots in your Documentation
 -----------------------------------------------------
 PyVista allows you to generate static or dynamic images directly within Sphinx
-much like the `matplotlib plot_directive
+much like the `Matplotlib plot_directive
 <https://matplotlib.org/stable/api/sphinxext_plot_directive_api.html>`_. Rather
 than manually creating and adding plots after code sections, you can instead
 dynamically generate images and embed them directly within your
 documentation. This also works seamlessly with `sphinx-gallery
 <https://sphinx-gallery.github.io/>`_, so you can create notebook examples just
-like the `matplotlib Example Gallery
+like the `Matplotlib Example Gallery
 <https://matplotlib.org/stable/gallery/index.html>`_.
 
 As an added side benefit, you can be sure that the documentation you generate

diff --git a/tutorial/09_qt/README.rst b/tutorial/09_qt/README.rst
@@ -139,7 +139,7 @@ Examples
    .. tab:: VesselVio
 
       `VesselVio <https://jacobbumgarner.github.io/VesselVio/>`_ is open-source
-      application for the analysis and visualization of segemented vasculature
+      application for the analysis and visualization of segmented vasculature
       datasets.
 
       .. image:: https://user-images.githubusercontent.com/70919881/149365137-fd526326-3d01-4588-a91f-1dc0f44bcb21.png