Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation (AMISC) technique.
Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation (AMISC) technique.
Ensure you are using Python 3.11 or later. You can install the package from PyPI using pip:
pip install amisc
If you are using pdm in your own project, then you can use:
pdm add amisc
# Or in editable mode from a local clone...
pdm add -e ./amisc --dev
import numpy as np
from amisc import System
def fun1(x):
y = x * np.sin(np.pi * x)
return y
def fun2(y):
z = 1 / (1 + 25 * y ** 2)
return z
system = System(fun1, fun2)
system.inputs()['x'].domain = (0, 1) # set domain of surrogate for `x`
system.outputs()['y'].domain = (0, 1) # set domain of surrogate for `y`
system.fit()
x_test = system.sample_inputs(10)
y_test = system.predict(x_test)
See the contribution guidelines.
AMISC paper [1].
Made with the copier-numpy template.
FAQs
Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation (AMISC) technique.
We found that amisc demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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