diff --git a/README.md b/README.md index 5ad9c80..d8472bf 100644 --- a/README.md +++ b/README.md @@ -140,14 +140,18 @@ from the project's root. We compare the Rormula to the well-established and way more mature package [Formulaic](https://github.com/matthewwardrop/formulaic). The [tests](rormula/test/test_wilkinson.py) create a formula in Wilkinson notation and sample 100 random data points. The output on my machine is ``` -- test just numerical -Rormula took 0.0020s -Rormula asdf took 0.0247s -Formulaic took 0.2037s -- test numerical and categorical -Rormula took 0.0045s -Rormula asdf took 0.0300s -Formulaic took 0.3403s +- test just numerical 100 rows +Rormula took 0.0009s +Rormula asdf took 0.0213s +Formulaic took 0.1193s +- test numerical and categorical 100 rows +Rormula took 0.0032s +Rormula asdf took 0.0149s +Formulaic took 0.1705s +- test just numerical 100000 rows +Rormula took 0.2240s +Rormula asdf took 0.2895s +Formulaic took 0.2300s ``` For the first and forth lines that start with `Rormula took`, we have separated categorical and numerical data beforehand. For the result in the second and fifth lines that start with `Rormula asdf took`, we pass and receive pandas dataframes. @@ -162,6 +166,7 @@ maturin develop --release --features print_timings python test/test_wilkinson.py 2> counts.txt counts -i -e counts.txt ``` +see [`rormula/profile.sh`](rormula/profile.sh). To profile other specific parts of the Rust-code use the `timing!`-macro. ```rust let res = timing!(some_calculation(), "name of some calculation"); diff --git a/rormula/test/test_wilkinson.py b/rormula/test/test_wilkinson.py index 28e96de..e202910 100644 --- a/rormula/test/test_wilkinson.py +++ b/rormula/test/test_wilkinson.py @@ -196,9 +196,9 @@ def test_separated(): if __name__ == "__main__": - print("- test just numerical") + print("- test just numerical 100 rows") test_numerical() - print("- test numerical and categorical") + print("- test numerical and categorical 100 rows") test_num_cat() print("- test just numerical 100000 rows") test_numerical_100000()