This new filtered designed for bi-variate analysis builds the continuous scatterplot of a 3D tetrahedralized mesh for two given scalar point fields. The continuous scatterplot is an extension of the discrete scatterplot for continuous bi-variate analysis.
While adding checks to the size of implicit arrays, it was discovered
that some of the Mask and ScatterPermutation arrays were constructed
with the wrong sizes during dispatch. In particular, these arrays were
supposed to be sized on the output, but were instead sized on the input.
They went unnoticed because they were using implicit arrays that worked
even if the array access went out of bounds.
The clip filter used to copy the input points and point fields as is,
regardless of if they were actually part of the output. With this change,
we track which input points are actually part of the output and copy
only those values.
Address: #112
014c429eb Make divide by volume in particle density estimate a little safer
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Li-Ta Lo <ollie@lanl.gov>
Merge-request: !3022
While going through the VTK-m code to identify where a cast-and-call was
happening against VTKM_DEFAULT_TYPE_LIST, I ran into a subtle case in
`ParticleDensityBase` that was calling a worklet with an
`UnknownArrayHandle`. This works OK, but was probably compiling for
unnecessary types (for example, vectors). Changed the field resolution
to be more intentional.
MR !2969 was meant to update the clip filters such that their field
mapping works on any field type and preserves the value type. Although
this was done for `ClipWithField`, it was not fully implemented for
`ClipWithImplicitFunction`. These changes update
`ClipWithImplicitFunction` to match its sibling.
ac889b500 Implement VecTraits class for all types
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Li-Ta Lo <ollie@lanl.gov>
Merge-request: !3018
f545feba8 Add changelog for documenting data license
a24358a1a Document source of WarpX files
60559ce9b Document the source of venn250.vtk
796ec9638 Document data that comes from VisIt tutorial
06391c4e6 Clarify license for ECL data
Acked-by: Kitware Robot <kwrobot@kitware.com>
Acked-by: Vicente Bolea <vicente.bolea@kitware.com>
Merge-request: !3016
The `VecTraits` class allows templated functions, methods, and classes to
treat type arguments uniformly as `Vec` types or to otherwise differentiate
between scalar and vector types. This only works for types that `VecTraits`
is defined for.
The `VecTraits` templated class now has a default implementation that will
be used for any type that does not have a `VecTraits` specialization. This
removes many surprise compiler errors when using a template that, unknown
to you, has `VecTraits` in its implementation.
One potential issue is that if `VecTraits` gets defined for a new type, the
behavior of `VecTraits` could change for that type in backward-incompatible
ways. If `VecTraits` is used in a purely generic way, this should not be an
issue. However, if assumptions were made about the components and length,
this could cause problems.
Fixes#589
Some of the data sets that are included from VTK-m are derived from the
VisIt Tutorial Data (https://www.visitusers.org/index.php?title=Tutorial_Data).
These are covered by the VisIt license, as communicated by Eric Brugger.
Although the license for these data is compatible with VTK-m's license,
we should still attribute the source of the data and make clear the
copyrights. The data are moved into the third_party directory, and
readmes are added to document everything.
The noise.vtk and noise.bov files have been renamed example.vtk and
example_temp.bov to match the name of the file in the VisIt tutorial
data archive. The ucd3d.vtk file, which is similar to the curv3d.silo
data but altered, has been removed. It was not used for any tests. It
was referenced in a couple of example programs, but the reference is
easily changed.
Some of the test data sets are derived from data sets that are commonly
distributed to test visualization algorithms and are featured in
numerous papers. However, I am unable to track down the original source
let alone identify what license, if any, they were released under. To
avoid any complications with data ownership, remove these data sets and
replace them with in house data sets that we explicitly own.
