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Optimize block map construction and multiplication (#52)
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.travis.yml

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- 1.0
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- 1.1
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- 1.2
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- 1.3
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- nightly
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matrix:

Project.toml

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name = "LinearMaps"
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uuid = "7a12625a-238d-50fd-b39a-03d52299707e"
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version = "2.4.0"
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version = "2.5.0"
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[deps]
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LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

README.md

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A Julia package for defining and working with linear maps, also known as linear transformations or linear operators acting on vectors. The only requirement for a LinearMap is that it can act on a vector (by multiplication) efficiently.
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## What's new in v2.5.0
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* New feature: concatenation of `LinearMap`s objects with `UniformScaling`s,
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consistent with (h-, v-, and hc-)concatenation of matrices. Note, matrices
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`A` must be wrapped as `LinearMap(A)`, `UniformScaling`s are promoted to
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`LinearMap`s automatically.
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## What's new in v2.4.0
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* Support restricted to Julia v1.0+.
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## What's new in v2.3.0
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* Fully Julia v0.7/v1.0/v1.1 compatible.
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* Full support of noncommutative number types such as quaternions.
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Applying the adjoint or transpose of `A` (if defined) to `x` works exactly as in the usual matrix case: `transpose(A) * x` and `mul!(y, A', x)`, for instance.
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* Horizontal, vertical, and hv-concatenation as known for regular matrices,
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where `UniformScaling`s are automatically promoted to `LinearMap`s and their
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sizes are inferred, if possible.
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## Types
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None of the types below need to be constructed directly; they arise from performing

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