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Integral is defined for any AbstractInterpolation but then calls samples on that interpolation which only has methods for ::LinearInterpolation{<:AbstractVector} types.
It would be useful to be able to get the integral of multi-dimensional interpolations. Derivetives returns a vector with element for each data dimension. Integral could do the same though this may not be a useful output for every use case.
I'd like to be able to use this to calculate means and standard deviations for each signal in an interpolation.
Example code:
u =rand(3,20)
t =sort(rand(20))
X1 =LinearInterpolation(u[1,:],t)
DataInterpolations.integral(X1, 0, 0.5) # Works
X =LinearInterpolation(u,t)
# MethodError: no method matching samples(::LinearInterpolation{Matrix{Float64}, Vector{Float64}, true, Float64})
DataInterpolations.integral(X, 0, 0.5)
Thanks,
Aaron.
The text was updated successfully, but these errors were encountered:
Integral on matrix interpolations throws error
Integral is defined for any AbstractInterpolation but then calls samples on that interpolation which only has methods for
::LinearInterpolation{<:AbstractVector}
types.It would be useful to be able to get the integral of multi-dimensional interpolations. Derivetives returns a vector with element for each data dimension. Integral could do the same though this may not be a useful output for every use case.
I'd like to be able to use this to calculate means and standard deviations for each signal in an interpolation.
Example code:
Thanks,
Aaron.
The text was updated successfully, but these errors were encountered: