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Update benchmarks to help with optimal control tuning #800

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Merged
murrayrm merged 5 commits into from
Nov 26, 2022
Merged

Update benchmarks to help with optimal control tuning #800

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e14d7b3
move optimal_bench.py to steering_bench.py + small fixes
murrayrm Aug 27, 2022
08f6464
improved flat system benchmarking (+ docstring, unit test updates)
murrayrm Aug 27, 2022
efca9ca
new optimal benchmarks (replace steering with rss)
murrayrm Aug 28, 2022
2860d89
add error for using solve_ivp for discrete time + formatting tweaks
murrayrm Aug 29, 2022
54de2a3
allow print_summary to be set in solve_ocp
murrayrm Aug 30, 2022
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move optimal_bench.py to steering_bench.py + small fixes
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@murrayrm
murrayrm committed Nov 19, 2022
commit e14d7b37ae9b3958d7adbc970f0f57fbda593d84
2 changes: 1 addition & 1 deletion benchmarks/README
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Expand Up @@ -11,7 +11,7 @@ you can use the following command from the root directory of the repository:

PYTHONPATH=`pwd` asv run --python=python

You can also run benchmarks against specific commits usuing
You can also run benchmarks against specific commits using

asv run <range>

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0 benchmarks/optimal_bench.py → benchmarks/steering_bench.py
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2 changes: 1 addition & 1 deletion control/flatsys/bezier.py
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Expand Up @@ -73,7 +73,7 @@ def eval_deriv(self, i, k, t, var=None):
raise ValueError("Basis function index too high")
elif k >= self.N:
# Higher order derivatives are zero
return np.zeros(t.shape)
return 0 * t

# Compute the variables used in Bezier curve formulas
n = self.N - 1
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2 changes: 1 addition & 1 deletion control/flatsys/poly.py
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Expand Up @@ -66,6 +66,6 @@ def __init__(self, N, T=1):
# Compute the kth derivative of the ith basis function at time t
def eval_deriv(self, i, k, t, var=None):
"""Evaluate the kth derivative of the ith basis function at time t."""
if (i < k): return 0; # higher derivative than power
if (i < k): return 0 * t # higher derivative than power
return factorial(i)/factorial(i-k) * \
np.power(t/self.T, i-k) / np.power(self.T, k)