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@yuyichao
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Not sure if this is the best long term solution but at least it makes all tests pass and IMHO produce the least breakage for users.

@mlubin
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mlubin commented Apr 28, 2015

gradient is on 0.3 also, no need to special case for 0.4.

@yuyichao
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I C. So it's the recently introduced handling of conflict export that breaks this, rather than the conflicting names themselves......

@mlubin
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mlubin commented Apr 28, 2015

Appears so

@yuyichao
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Updated

mlubin added a commit that referenced this pull request Apr 28, 2015
Extend Base.gradient instead of defining a new one on 0.4
@mlubin mlubin merged commit 88370c6 into JuliaMath:master Apr 28, 2015
mlubin referenced this pull request in JuliaDiff/ForwardDiff.jl Aug 3, 2015
… use assertions to circumvent passing in Dim to ensure type stability
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mlubin commented Aug 3, 2015

I don't think this was the right solution. There's more than one method to compute the gradient of a function. I don't think the Calculus version should be any special and take over the gradient(::Function) method.

@johnmyleswhite
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I agree.

@mlubin: What do you think of trying to pull this package apart into separate packages for finite differentiation and symbolic differentiation? Now that ForwardDiff is out, I feel like I could take the work I did long ago on Calculus2 and try to adopt your API. We could then start to deprecate this package.

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mlubin commented Sep 9, 2015

Splitting into FiniteDiff and SymbolicDiff seems like a good idea. Both
could be hosted under JuliaDiff. Are the integration features in Calculus
useful?
@jrevels
On Sep 9, 2015 9:43 AM, "John Myles White" notifications@github.com wrote:

I agree.

@mlubin https://github.com/mlubin: What do you think of trying to pull
this package apart into separate packages for finite differentiation and
symbolic differentiation? Now that ForwardDiff is out, I feel like I could
take the work I did long ago on Calculus2 and try to adopt your API. We
could then start to deprecate this package.


Reply to this email directly or view it on GitHub
#66 (comment)
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@johnmyleswhite
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No, the integration functionality is far inferior to what's in Base.

@jrevels
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jrevels commented Sep 9, 2015

What do you think of trying to pull this package apart into separate packages for finite differentiation and symbolic differentiation?

Splitting into FiniteDiff and SymbolicDiff seems like a good idea.

I like this idea.

Now that ForwardDiff is out, I feel like I could take the work I did long ago on Calculus2 and try to adopt your API.

That would be great. I stumbled upon Calculus2 a while ago and was hoping the effort would be revived soon! Let me know how I can help, and feel free to file issues in ForwardDiff.jl if anything needs to change API-wise there to make things work out.

@yuyichao yuyichao deleted the gradient-fix branch October 25, 2015 15:13
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4 participants