@@ -92,10 +92,10 @@ compilers = "*"
92
92
compilers = " *"
93
93
94
94
[tool .pixi .tasks ]
95
- time-h = " python -m timeit -n 5 -s 'import numpy as np; from fastcan import FastCan; X = np.random.rand(3000, 100); y = np.random.rand(3000, 20); s = FastCan(100, verbose=0).fit(X, y)'"
96
- time-eta = " python -m timeit -n 5 -s 'import numpy as np; from fastcan import FastCan; X = np.random.rand(3000, 100); y = np.random.rand(3000, 20); s = FastCan(100, eta=True, verbose=0).fit(X, y)'"
95
+ time-h = " python -m timeit -n 5 -s 'import numpy as np; from fastcan import FastCan; X = np.random.rand(3000, 100); y = np.random.rand(3000, 20)' ' s = FastCan(100, verbose=0).fit(X, y)'"
96
+ time-eta = " python -m timeit -n 5 -s 'import numpy as np; from fastcan import FastCan; X = np.random.rand(3000, 100); y = np.random.rand(3000, 20)' ' s = FastCan(100, eta=True, verbose=0).fit(X, y)'"
97
97
profile-minibatch = { cmd = ''' python -c "import cProfile; import numpy as np; from fastcan import minibatch; X = np.random.rand(100, 3000); y = np.random.rand(100, 20); cProfile.run('minibatch(X, y, 1000, 10, verbose=0)', sort='$SORT')"''' , env = { SORT = " cumtime" } }
98
- time-narx = ''' python -m timeit -n 1 -s "import numpy as np; from fastcan.narx import make_narx; rng = np.random.default_rng(5); X = rng.random((1000, 10)); y = rng.random((1000, 2)); s = make_narx(X, y, 10, max_delay=2, poly_degree=2, verbose=0).fit(X, y, coef_init='one_step_ahead', verbose=1)"'''
98
+ time-narx = ''' python -m timeit -n 1 -s "import numpy as np; from fastcan.narx import make_narx; rng = np.random.default_rng(5); X = rng.random((1000, 10)); y = rng.random((1000, 2)); m = make_narx(X, y, 10, max_delay=2, poly_degree=2, verbose=0)" "m .fit(X, y, coef_init='one_step_ahead', verbose=1)"'''
99
99
100
100
[tool .pixi .feature .test .tasks ]
101
101
test = { cmd = " pytest" , cwd = " tests" }
0 commit comments