python and scheme, algorithm implementation
Budget: $30 – $250 USD
The algoritm to do is :
the algorithm : https://en.wikipedia.org/wiki/Matrix_exponential
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5. An algorithm for calculating the Matrix exponential.
Input: A matrix M of size n X n , epsilon (accuracy).
Output: e^M .
Languages for use:
- First language - Scheme
- Second language - Python
the inpust must be fast in 1000X1000 matrix input file
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- In Python, it is permitted to use libraries only from `numpy` and only for code demonstration and categorization purposes.
E.g., do not use `numpy.linalg`, `numpy.polynomial`, ...
- In Scheme, it is permitted to use libraries only from `flomat` and only for code demonstration and categorization purposes.
In Scheme, it is not allowed to use functions that use objects, particularly not in functions that receive the values of those objects as arguments.
- In projects, do not copy code from already implemented libraries, including those that implement algorithms.
---
the algorithm : https://en.wikipedia.org/wiki/Matrix_exponential
---
5. An algorithm for calculating the Matrix exponential.
Input: A matrix M of size n X n , epsilon (accuracy).
Output: e^M .
Languages for use:
- First language - Scheme
- Second language - Python
the inpust must be fast in 1000X1000 matrix input file
---
---
---
- In Python, it is permitted to use libraries only from `numpy` and only for code demonstration and categorization purposes.
E.g., do not use `numpy.linalg`, `numpy.polynomial`, ...
- In Scheme, it is permitted to use libraries only from `flomat` and only for code demonstration and categorization purposes.
In Scheme, it is not allowed to use functions that use objects, particularly not in functions that receive the values of those objects as arguments.
- In projects, do not copy code from already implemented libraries, including those that implement algorithms.
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