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Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.

Following Julia convention, the main Julia code is in the directory src/ and the tests are in the directory test/.

Following Python convention, the main Python code is in the directory smolyak/.

Following both Julia and Python convention the documentation is found in the doc/. The goal of this project is to write a consistent and interface for both Python and Julia, which would allow us to have a single documentation suite. There may be cases where this is not possible, in which case any differences between the two implementations will be documented in separate files for each language.

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GitHub - EconForge/Smolyak: Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia. · GitHub
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Smolyak
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Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Following Julia convention, the main Julia code is in the directory src/ and the tests are in the directory test/.
Following Python convention, the main Python code is in the directory smolyak/.
Following both Julia and Python convention the documentation is found in the doc/. The goal of this project is to write a consistent and interface for both Python and Julia, which would allow us to have a single documentation suite. There may be cases where this is not possible, in which case any differences between the two implementations will be documented in separate files for each language.
About
Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
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33 stars
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18 forks
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GitHub - EconForge/Smolyak: Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia. · GitHub
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Smolyak
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Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Following Julia convention, the main Julia code is in the directory src/ and the tests are in the directory test/.
Following Python convention, the main Python code is in the directory smolyak/.
Following both Julia and Python convention the documentation is found in the doc/. The goal of this project is to write a consistent and interface for both Python and Julia, which would allow us to have a single documentation suite. There may be cases where this is not possible, in which case any differences between the two implementations will be documented in separate files for each language.
About
Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
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33 stars
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GitHub - EconForge/Smolyak: Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia. · GitHub
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Smolyak
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Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Following Julia convention, the main Julia code is in the directory src/ and the tests are in the directory test/.
Following Python convention, the main Python code is in the directory smolyak/.
Following both Julia and Python convention the documentation is found in the doc/. The goal of this project is to write a consistent and interface for both Python and Julia, which would allow us to have a single documentation suite. There may be cases where this is not possible, in which case any differences between the two implementations will be documented in separate files for each language.
About
Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Resources
Readme
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33 stars
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15 watching
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18 forks
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GitHub - EconForge/Smolyak: Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia. · GitHub
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Smolyak
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Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Following Julia convention, the main Julia code is in the directory src/ and the tests are in the directory test/.
Following Python convention, the main Python code is in the directory smolyak/.
Following both Julia and Python convention the documentation is found in the doc/. The goal of this project is to write a consistent and interface for both Python and Julia, which would allow us to have a single documentation suite. There may be cases where this is not possible, in which case any differences between the two implementations will be documented in separate files for each language.
About
Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Resources
Readme
License
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33 stars
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15 watching
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18 forks
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GitHub - EconForge/Smolyak: Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia. · GitHub
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Smolyak
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Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Following Julia convention, the main Julia code is in the directory src/ and the tests are in the directory test/.
Following Python convention, the main Python code is in the directory smolyak/.
Following both Julia and Python convention the documentation is found in the doc/. The goal of this project is to write a consistent and interface for both Python and Julia, which would allow us to have a single documentation suite. There may be cases where this is not possible, in which case any differences between the two implementations will be documented in separate files for each language.
About
Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Resources
Readme
License
Activity
Custom properties
Stars
33 stars
Watchers
15 watching
Forks
18 forks
Report repository
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GitHub - EconForge/Smolyak: Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia. · GitHub
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Smolyak
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Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Following Julia convention, the main Julia code is in the directory src/ and the tests are in the directory test/.
Following Python convention, the main Python code is in the directory smolyak/.
Following both Julia and Python convention the documentation is found in the doc/. The goal of this project is to write a consistent and interface for both Python and Julia, which would allow us to have a single documentation suite. There may be cases where this is not possible, in which case any differences between the two implementations will be documented in separate files for each language.
About
Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
Resources
Readme
License
Activity
Custom properties
Stars
33 stars
Watchers
15 watching
Forks
18 forks
Report repository
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