* Add new algorithm index_2d_array_in_1d
* Add doctest for iter function
* The power of dataclasses
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* Update cocktail_shaker_sort.py
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* Added test case for tuple
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* Added Lens formulae to the Physics repository
* Resolved the commented issues
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* added mean absolute error to loss_functions.py
* added doctest to mean absolute error to loss_functions.py
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* Add error tests in doctest and fix error message
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* Code Enhancements in merge_sort.py
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* Improved Equilibrium Index of an Array.
This is the modifications made to the original code:
1. Create Doctest Instructions: Python "doctest" can be executed by running the following command: python -m doctest -v equilibrium_index.py.
2. Deleted Argument {size}: Deleted the `size` argument because `len(arr)} allows the array's length to be determined inside the function, simplifying and improving the readability of the function signature.
3. Used {enumerate}: To improve code readability and indicate that we're working with element-index pairs, we iterated through the array using both elements and their indices using the `enumerate` function.
4. Optimized the Loop: To prevent pointless additions, the loop was improved by initializing {left_sum} with the value of the first element (arr[0]). Furthermore, since the beginning and last items (0 and size - 1) cannot be equilibrium indices, there is no need to check them, saving further computations.
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* Add function docstrings, comments and type hints
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* Fix float to int error
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* Tried new TESTS for the binomial_coefficient
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* Add `Invert a Binary Tree` solution
* Add type
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* Add New Algorithm: Triangular Numbers
* Calculate nth triangular number instead of generating a list
* Handle 0th position and update function name and docstring
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This commit adds a Python script for calculating the Simple Moving Average (SMA) of a time series data.
The script also includes a doctest that verifies the correctness of the SMA calculations for a sample dataset.
Usage:
- Run the script with your own time series data and specify the window size for SMA calculations.
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* don't need to return list because list is mutable
* Don't need to return list as list is mutable
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* filter blank inputs from input list
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* Remove eval from arithmetic_analysis/newton_raphson.py
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algorithms for linear algebra, numerical analysis, and physics.
Relocated the directory's linear algebra algorithms to linear_algebra/,
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* added the algorithm to compute the terminal velocity of an object falling in a fluid
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* Added Binary Focal Cross Entropy
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