FIX: typo

docs/source/mayavi/auto/changes.rst

@@ -966,7 +966,7 @@ Enhancements
 14 Aug, 2009 (GV):
  - ENH: Stop gap solution to limit the cost of auto-scaling the glyph
  size with large arrays in barchart, when the positioning is
- implicite, and thus distance calculation is pointless [24526]
+ implicit, and thus distance calculation is pointless [24526]
  - ENH: Do not update the rendering of the scene when using mlab
  helper functions that build one object after another [24529]
  - ENH: Add an argument to barchart to avoid expensive scaling computation
@@ -1519,7 +1519,7 @@ Mayavi 3.1.0
  - API: Change defaults [22513]:
  - CellToPointData and PointToCellData filters to pass the existing
  dataset.
- - The ouline of the implicite plane is no longer draggable by
+ - The ouline of the implicit plane is no longer draggable by
  default.
 
 15-16 November, 2008 (PR)

docs/source/mayavi/auto/example_flight_graph.rst

@@ -6,7 +6,7 @@ Flight graph example
 --------------------------------------------------------------------
 
 
-An example showing a graph display between cities positionned on the
+An example showing a graph display between cities positioned on the
 Earth surface.
 
 This graph displays the longest fligh routes operated by Boing

docs/source/mayavi/auto/example_surface_from_irregular_data.rst

@@ -16,12 +16,12 @@ regular grid for parameters 'x' and 'y', it can simply be view with the
 mlab.surf function. However, when there are some missing points, or the
 data has been acquired at random, the surf function cannot be used.
 
-The difficulty stems from the fact that points positionned in 3D do
+The difficulty stems from the fact that points positioned in 3D do
 not define a surface if no connectivity information is given. With the
-surf function, this information is implicite from the shape of the input
+surf function, this information is implicit from the shape of the input
 arrays.
 
-In this example, randomly-positionned points in the (x, y) plane are
+In this example, randomly-positioned points in the (x, y) plane are
 embedded in a surface in the z axis. We first visualize the points using
 mlab.points3d. We then use the delaunay2d filter to extract the mesh by
 nearest-neighboor matching, and visualize it using the surface module.

docs/source/mayavi/auto/examples.rst

@@ -294,7 +294,7 @@ Advanced mlab examples
 
 |0021| :ref:`example_flight_graph`
  An example showing a graph display
- between cities positionned on the Earth
+ between cities positioned on the Earth
  surface.
 
 ======= =============================================

docs/source/mayavi/auto/flight_graph.py

@@ -1,5 +1,5 @@
 """
-An example showing a graph display between cities positionned on the
+An example showing a graph display between cities positioned on the
 Earth surface.
 
 This graph displays the longest fligh routes operated by Boing

docs/source/mayavi/auto/mlab_other_functions.rst

@@ -385,7 +385,7 @@ text
  x, and y are the position of the origin of the text. If no z
  keyword argument is given, x and y are the 2D projection of the
  figure, they belong to [0, 1]. If a z keyword argument is given, the
- text is positionned in 3D, in figure coordinates.
+ text is positioned in 3D, in figure coordinates.
 
  **Keyword arguments:**
 
@@ -424,7 +424,7 @@ text3d
  text3d(x, y, z, text, ...)
  
  x, y, and z are the position of the origin of the text. The
- text is positionned in 3D, in figure coordinates.
+ text is positioned in 3D, in figure coordinates.
 
  **Keyword arguments:**
 

docs/source/mayavi/auto/surface_from_irregular_data.py

@@ -9,12 +9,12 @@
 mlab.surf function. However, when there are some missing points, or the
 data has been acquired at random, the surf function cannot be used.
 
-The difficulty stems from the fact that points positionned in 3D do
+The difficulty stems from the fact that points positioned in 3D do
 not define a surface if no connectivity information is given. With the
-surf function, this information is implicite from the shape of the input
+surf function, this information is implicit from the shape of the input
 arrays.
 
-In this example, randomly-positionned points in the (x, y) plane are
+In this example, randomly-positioned points in the (x, y) plane are
 embedded in a surface in the z axis. We first visualize the points using
 mlab.points3d. We then use the delaunay2d filter to extract the mesh by
 nearest-neighboor matching, and visualize it using the surface module.

docs/source/mayavi/mlab_changing_object_looks.rst

@@ -44,7 +44,7 @@ Adding color or size variations
  the data points. 
 
  **A caveat: Clamping: relative or absolute scaling**
- Given six points positionned on a line with interpoint spacing 1::
+ Given six points positioned on a line with interpoint spacing 1::
 
  x = [1, 2, 3, 4, 5, 6]
  y = [0, 0, 0, 0, 0, 0]

examples/mayavi/mlab/flight_graph.py

@@ -1,5 +1,5 @@
 """
-An example showing a graph display between cities positionned on the
+An example showing a graph display between cities positioned on the
 Earth surface.
 
 This graph displays the longest fligh routes operated by Boing

examples/mayavi/mlab/surface_from_irregular_data.py

@@ -9,12 +9,12 @@
 mlab.surf function. However, when there are some missing points, or the
 data has been acquired at random, the surf function cannot be used.
 
-The difficulty stems from the fact that points positionned in 3D do
+The difficulty stems from the fact that points positioned in 3D do
 not define a surface if no connectivity information is given. With the
-surf function, this information is implicite from the shape of the input
+surf function, this information is implicit from the shape of the input
 arrays.
 
-In this example, randomly-positionned points in the (x, y) plane are
+In this example, randomly-positioned points in the (x, y) plane are
 embedded in a surface in the z axis. We first visualize the points using
 mlab.points3d. We then use the delaunay2d filter to extract the mesh by
 nearest-neighboor matching, and visualize it using the surface module.

mayavi/tools/data_wizards/data_source_factory.py

@@ -20,7 +20,7 @@ class DataSourceFactory(HasStrictTraits):
  organisation of the data is given by setting the public traits.
  """
 
- # Whether the position is implicitely inferred from the array indices
+ # Whether the position is implicitly inferred from the array indices
  position_implicit = false
 
  # Whether the data is on an orthogonal grid
@@ -37,7 +37,7 @@ class DataSourceFactory(HasStrictTraits):
  position_y = ArrayOrNone
  position_z = ArrayOrNone
 
- # Connectivity array. If none, it is implicitely inferred from the array
+ # Connectivity array. If none, it is implicitly inferred from the array
  # indices
  connectivity_triangles = ArrayOrNone
 

mayavi/tools/decorations.py

@@ -448,7 +448,7 @@ class Text(ModuleFactory):
  x, and y are the position of the origin of the text. If no z
  keyword argument is given, x and y are the 2D projection of the
  figure, they belong to [0, 1]. If a z keyword argument is given, the
- text is positionned in 3D, in figure coordinates.
+ text is positioned in 3D, in figure coordinates.
  """
 
  width = Trait(None, None, CFloat, adapts='width',
@@ -489,7 +489,7 @@ class Text3D(ModuleFactory):
  text3d(x, y, z, text, ...)
 
  x, y, and z are the position of the origin of the text. The
- text is positionned in 3D, in figure coordinates.
+ text is positioned in 3D, in figure coordinates.
  """
 
  _target = Instance(modules.Text3D, ())