Speed up CreateWorkspace

[Russell Taylor]

From Garrett:

Create Workspace is particularly slow when creating large workspaces.

for a workspace with 115712 spectra and 8000 histograms, It is taking roughly 4hours and 128G of ram.

[Russell Taylor]

(In [12194]) Reduce vector copying and resizing in CreateWorkspace algorithm. Re #3118.

[Russell Taylor]

The previous change sped up exec() by 30%

[Russell Taylor]

(In [12326]) CreateWorkspace now 65% faster, and also has options to provide common X values only once for all the spectra and to skip the E values. Re #3118.

[Mathieu Doucet]

(In [12331]) Re #3118 Fix PythonAlgorithmTest

[Russell Taylor]

(In [12390]) Add progress reporting to CreateWorkspace. Re #3118.

[Russell Taylor]

The algorithm itself is much improved, but there are still issues with generating the history (see #3136) and with running it from python, both of which require the (potentially very long) input vector properties to be turned into strings (which is very slow). Really, this algorithm is never likely to be suitable for the size of workspace Garrett was creating since it requires all data points to be concatenated into a very large contiguous array.

On my machine, creating a 10k x 10k workspace (as I do in the performance test that's been added) takes:

• 2.3s as a C++ child algorithm (so no history)
• 215s as a regular C++ algorithm
• 133s as a Python subalgorithm creating the data in numpy arrays and passing those in

It takes 81s to make a SEQ sized workspace as a C++ child algorithm.

[Janik Zikovsky]

Works with the caveats indicated by Russell. It takes 17 seconds from a Python script on my machine for a 1000x1000 workspace. Those massive strings are the real problem. In the longer term, a smarter way to set array properties from Python that uses the Numpy array directly instead of converting to string could be considered....

[Stuart Campbell]

This ticket has been transferred to github issue ​3965