xtl | The x template library

This is not possible as seaborn.clustermap is a figure level plotting function. There is one axes for the heat map and one for each tree.

What exactly would you like to achieve? You can always create your clustermap first and then modify it to add other axes.

Disclaimer: I'm far from a Windows expert (I just use it in Continuous Integration for testing).

You should be able to use the target provided by xtensor-blas. So what should be possible is to do (on any platform):

Never use commas in the FROM clause. Always use proper, explicit, standard, readable JOIN syntax. You should fix this query and learn proper SQL syntax for your future queries.

You can use conditional aggregation:

The reason the Numpy implementation is much faster is that it does not compute the same thing as the two others.

Indeed, the python version does not read z in the expression np.sin(x) * np.cos(x). As a result, the Numba JIT is clever enough to execute the loop only once justifying a factor of 100 between Fastor and Numba. You can check that by replacing range(100) by range(10000000000) and observing the same timings.

Finally, XTensor is faster than Fastor in this benchmark as it seems to use its own fast SIMD implementation of exp/sin/cos while Fastor seems to use a scalar implementation from libm justifying the factor of 2 between XTensor and Fastor.

Answer to the update:

Fastor/Xtensor performs really bad in exp, sin, cos, which was surprising.

No. We cannot conclude that from the benchmark. What you are comparing is the ability of compilers to optimize your code. In this case, Numba is better than plain C++ compilers as it deals with a high-level SIMD-aware code while C++ compilers have to deals with a huge low-level template-based code coming from the Fastor/Xtensor libraries. Theoretically, I think that it should be possible for a C++ compiler to apply the same kind of high-level optimization than Numba, but it is just harder. Moreover, note that Numpy tends to create/allocate temporary arrays while Fastor/Xtensor should not.

In practice, Numba is faster because u is a constant and so is exp(u), sin(u) and cos(u). Thus, Numba precompute the expression (computed only once) and still perform the sum in the loop. The following code give the same timing:

Some of the ratios that you set (via figsize and dendrogram_ratio) affect how big the box becomes. I've left them out for now but if you want to optimize these ratios to your liking you will get the desired size for the colorbar. I've also added tight_layout which additionally helps.

Try adding some sleep time (say 3 seconds) every n number of tickers.

To improve the code you can:

• compute the ratios before the loop
• remove useless float conversions
• remove the division (division by a division is a multiplication)
• rounding of the float may not be necessary
• group the statements in a coherent order
• rename allBoxes to box as it represents only one box

Here is a possible code:

See below