Evaluating properties based on an array of input parameters

For example, if I have a large numpy array of temperature values (say a million-element long), other than calling thermo in a for loop, is there a vectorized way to extract properties from thermo?

Many thanks, Amin

[CalebBell]

Hi,

I added an example of using multiprocessing to speed up multiple phase equilibria calculations: https://thermo.readthedocs.io/Examples/Performing Large Numbers of Calculations with Thermo in Parallel.html I hope this is helpful. I don’t have any plans to vectorize calculations further or add a convenience wrapper which allows numpy arrays as inputs. I don’t know what broadcasting rules would be best for that sort of an interface, and I don’t think using a loop is too onerous on users. The numba backend will hopefully continue to be developed for those who want to use numba’s parallelization features. I can try to answer specific questions about parallelism here if you have questions.

Sincerely, Caleb

[CalebBell]

Hi Amin,

My experience with CFD suggests tabular interpolation is the way to go. Calculating these properties will definitely be one of the slowest steps, and applying simplifications is normal - calling thermo directly would be too slow no matter what happened.

So you might make a lookup table of say T, P, and composition; and fill it out with values from thermo. Then during the simulation, interpolate with the nearest values. Some of numpy’s interpolation routines might be suitable but more likely would also be too slow.

Sincerely, Caleb