| Name | meanlib JSON |
| Version |
1.0.0
JSON |
| download |
| home_page | https://github.com/PinkPantherPC/meanlib.git |
| Summary | A Python package for calculating simple and weighted means, featuring classes for dynamic updates and sliding window functionality. |
| upload_time | 2024-08-02 17:34:50 |
| maintainer | None |
| docs_url | None |
| author | Tobia Petrolini |
| requires_python | >=3.7 |
| license | MIT |
| keywords |
|
| VCS |
 |
| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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# meanlib
`meanlib` is a Python library designed to facilitate the computation of various types of means, including simple means, rolling means, and weighted means. It provides easy-to-use classes and functions to update, compute, and retrieve means dynamically as new data becomes available.
## Features
- SimpleMean: Calculate and update a simple arithmetic mean with each new value.
- Mean: Calculate a rolling mean with an optional limit on the number of values stored.
- Weighted Mean Function: Calculate the weighted mean of a list of values.
## Usage
Here are some basic examples of how to use the library.
### Simple Mean Calculation
```python
from meanlib import SimpleMean
# Initialize the SimpleMean object
simple_mean = SimpleMean()
# Update the mean with new values
simple_mean.update(5)
simple_mean.update(10)
print(simple_mean.get_mean()) # Output: 7.5
```
### Rolling Mean with a Maximum Limit
```python
from meanlib import Mean
# Initialize the Mean object with a maximum of 3 values
mean = Mean(max_size=3)
# Update the mean with new values
mean.update(10)
mean.update(20)
mean.update(30)
print(mean.get_mean()) # Output: 20.0
# Adding another value, which will remove the oldest value (10)
mean.update(40)
print(mean.get_mean()) # Output: 30.0
```
### Weighted Mean Calculation
```python
from meanlib import weighted_mean
# Define values and their corresponding weights
values = [1, 2, 3, 4]
weights = [1, 2, 1, 1]
# Calculate the weighted mean
wm = weighted_mean(values, weights)
print(wm) # Output: 2.5
```
## API Reference
### `weighted_mean(values, weights)`
Calculates the weighted mean of a list of values.
#### Parameters
- `values` (list or array-like): The list of values for which the weighted mean is to be calculated.
- `weights` (list or array-like): The list of weights associated with each value.
#### Returns
- `float` or `complex`: The calculated weighted mean.
#### Raises
- `TypeError`: If values or weights are not list or array-like.
- `ValueError`: If values and weights do not have the same length.
- `ZeroDivisionError`: If the total of values is zero.
### `class SimpleMean`
A class for calculating a simple arithmetic mean that can be updated incrementally.
#### `SimpleMean.__init__()`
Initializes a `SimpleMean` object with initial sum and count set to zero.
#### `SimpleMean.update(number)`
Updates the mean with a new value.
#### Parameters:
- `number` (int, float, or complex): The new value to be added to the mean.
#### Returns:
- `float` or `complex`: The updated mean.
#### Raises:
- `TypeError`: If `number` is not of a compatible type.
#### `SimpleMean.get_mean()`
Returns the current mean.
#### Returns:
- `float` or `complex`: The current mean.
- `None`: If the count is zero.
### `class Mean`
A class for calculating a rolling mean with an optional limit on the number of values stored.
#### `Mean.__init__(max_size=None)`
Initializes a `Mean` object.
#### Parameters:
- `max_size` (int or str, optional): The maximum number of values to store in the array. If `None`, there is no limit.
#### Raises:
- `ValueError`: If `max_size` is not an integer or a string of an integer.
#### `Mean.update(number)`
Updates the mean with a new value, maintaining the array size within the maximum limit.
#### Parameters:
- `number` (int, float, or complex): The new value to be added to the mean.
#### Returns:
- `float` or `complex`: The updated mean.
#### Raises:
- `TypeError`: If `number` is not of a compatible type.
#### `Mean.update_list(_list)`
Updates the mean with a list of values, maintaining the array size within the maximum limit.
#### Parameters:
- `_list` (list or tuple): The new value to be added to the mean.
#### Returns:
- `float` or `complex`: The updated mean.
- `None`: If the count is zero.
#### Raises:
- `TypeError`: If an element in `_list` is not of the correct type or if the value is not of a compatible type.
#### `Mean.get_mean()`
Returns the current mean.
#### Returns:
- `float` or `complex`: The current mean.
- `None`: If the count is zero.
## License
This library is licensed under the MIT License.
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"description": "# meanlib\r\n\r\n`meanlib` is a Python library designed to facilitate the computation of various types of means, including simple means, rolling means, and weighted means. It provides easy-to-use classes and functions to update, compute, and retrieve means dynamically as new data becomes available.\r\n\r\n## Features\r\n\r\n- SimpleMean: Calculate and update a simple arithmetic mean with each new value.\r\n- Mean: Calculate a rolling mean with an optional limit on the number of values stored.\r\n- Weighted Mean Function: Calculate the weighted mean of a list of values.\r\n\r\n## Usage\r\n\r\nHere are some basic examples of how to use the library.\r\n\r\n### Simple Mean Calculation\r\n\r\n```python\r\nfrom meanlib import SimpleMean\r\n\r\n# Initialize the SimpleMean object\r\nsimple_mean = SimpleMean()\r\n\r\n# Update the mean with new values\r\nsimple_mean.update(5)\r\nsimple_mean.update(10)\r\nprint(simple_mean.get_mean()) # Output: 7.5\r\n```\r\n\r\n### Rolling Mean with a Maximum Limit\r\n\r\n```python\r\nfrom meanlib import Mean\r\n\r\n# Initialize the Mean object with a maximum of 3 values\r\nmean = Mean(max_size=3)\r\n\r\n# Update the mean with new values\r\nmean.update(10)\r\nmean.update(20)\r\nmean.update(30)\r\nprint(mean.get_mean()) # Output: 20.0\r\n\r\n# Adding another value, which will remove the oldest value (10)\r\nmean.update(40)\r\nprint(mean.get_mean()) # Output: 30.0\r\n```\r\n\r\n### Weighted Mean Calculation\r\n\r\n```python\r\nfrom meanlib import weighted_mean\r\n\r\n# Define values and their corresponding weights\r\nvalues = [1, 2, 3, 4]\r\nweights = [1, 2, 1, 1]\r\n\r\n# Calculate the weighted mean\r\nwm = weighted_mean(values, weights)\r\nprint(wm) # Output: 2.5\r\n```\r\n## API Reference\r\n\r\n### `weighted_mean(values, weights)`\r\n\r\nCalculates the weighted mean of a list of values.\r\n\r\n#### Parameters\r\n\r\n- `values` (list or array-like): The list of values for which the weighted mean is to be calculated.\r\n- `weights` (list or array-like): The list of weights associated with each value.\r\n\r\n#### Returns\r\n\r\n- `float` or `complex`: The calculated weighted mean.\r\n\r\n#### Raises\r\n\r\n- `TypeError`: If values or weights are not list or array-like.\r\n- `ValueError`: If values and weights do not have the same length.\r\n- `ZeroDivisionError`: If the total of values is zero.\r\n\r\n### `class SimpleMean`\r\n\r\nA class for calculating a simple arithmetic mean that can be updated incrementally.\r\n\r\n#### `SimpleMean.__init__()`\r\n\r\nInitializes a `SimpleMean` object with initial sum and count set to zero.\r\n\r\n#### `SimpleMean.update(number)`\r\n\r\nUpdates the mean with a new value.\r\n\r\n#### Parameters:\r\n\r\n- `number` (int, float, or complex): The new value to be added to the mean.\r\n\r\n#### Returns:\r\n\r\n- `float` or `complex`: The updated mean.\r\n\r\n#### Raises:\r\n\r\n- `TypeError`: If `number` is not of a compatible type.\r\n\r\n#### `SimpleMean.get_mean()`\r\n\r\nReturns the current mean.\r\n\r\n#### Returns:\r\n\r\n- `float` or `complex`: The current mean.\r\n- `None`: If the count is zero.\r\n\r\n### `class Mean`\r\n\r\nA class for calculating a rolling mean with an optional limit on the number of values stored.\r\n\r\n#### `Mean.__init__(max_size=None)`\r\n\r\nInitializes a `Mean` object.\r\n\r\n#### Parameters:\r\n\r\n- `max_size` (int or str, optional): The maximum number of values to store in the array. If `None`, there is no limit.\r\n\r\n#### Raises:\r\n\r\n- `ValueError`: If `max_size` is not an integer or a string of an integer.\r\n\r\n#### `Mean.update(number)`\r\n\r\nUpdates the mean with a new value, maintaining the array size within the maximum limit.\r\n\r\n#### Parameters:\r\n\r\n- `number` (int, float, or complex): The new value to be added to the mean.\r\n\r\n#### Returns:\r\n\r\n- `float` or `complex`: The updated mean.\r\n\r\n#### Raises:\r\n\r\n- `TypeError`: If `number` is not of a compatible type.\r\n\r\n#### `Mean.update_list(_list)`\r\n\r\nUpdates the mean with a list of values, maintaining the array size within the maximum limit.\r\n\r\n#### Parameters:\r\n\r\n- `_list` (list or tuple): The new value to be added to the mean.\r\n\r\n#### Returns:\r\n\r\n- `float` or `complex`: The updated mean.\r\n- `None`: If the count is zero.\r\n\r\n#### Raises:\r\n\r\n- `TypeError`: If an element in `_list` is not of the correct type or if the value is not of a compatible type.\r\n\r\n#### `Mean.get_mean()`\r\n\r\nReturns the current mean.\r\n\r\n#### Returns:\r\n\r\n- `float` or `complex`: The current mean.\r\n- `None`: If the count is zero.\r\n\r\n## License\r\n\r\nThis library is licensed under the MIT License.\r\n",
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