| Name | normtest JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | |
| Summary | Check that your data follows, at least approximately, the Normal distribution. |
| upload_time | 2023-11-25 14:08:36 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.10 |
| license | BSD 3-Clause License Copyright (c) 2023, puzzle-in-a-mug Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
normality
sample
test
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
contourpy
cycler
fonttools
kiwisolver
matplotlib
numpy
packaging
pandas
paramcheckup
Pillow
pyparsing
python-dateutil
pytz
scipy
six
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<img src="https://raw.githubusercontent.com/puzzle-in-a-mug/normtest/main/docs/_static/favicon-180x180.png" align="right" />
# normtest
This package has a series of tests used to check whether a set of sample data follows, at least approximately, the Normal distribution.
## Available tests (25/11/2023)
- Filliben
- Ryan-Joiner
- Looney-Gulledge
## Install
```
pip install normtest
```
## Usage
Each test has its own class and can be imported as follows:
```python
from normtest import RyanJoiner
from normtest import Filliben
from normtest import LooneyGulledge
```
To perform the test, just instantiate the class and apply the ``fit`` method, passing the data set as a ``NumpyArray``. For example:
```python
import numpy as np
test = RyanJoiner()
x_data = np.array([6, 1, -4, 8, -2, 5, 0])
test.fit(x_data)
```
After the ``fit`` method is applied, the ``test`` ``object`` now has a series of attributes with the test results. The main attribute is ``test.normality``, which contains the summarized results:
```python
print(test.normality)
RyanJoiner(statistic=0.9844829186140105, critical=0.8977794003662074, p_value='p > 0.100', conclusion='Fail to reject Hâ‚€')
```
The ``test`` ``object`` also has methods for graphical visualization of results, such as the ``line_up`` method. See the [documentation](https://normtest.readthedocs.io/en/latest/source/ryan_joiner/RyanJoiner.html) for details.
Each test has its individual module, and functions can be accessed through the modules. To import the module that contains all the RyanJoiner test functions, for example, use:
```python
from normtest import ryan_joiner
```
This way, it is possible to generate graphs and obtain intermediate values from the test calculations. For example:
```python
size = 7
pi = ryan_joiner._order_statistic(size)
print(pi)
[0.0862069 0.22413793 0.36206897 0.5 0.63793103 0.77586207
0.9137931 ]
```
## License
- [BSD 3-Clause License](https://github.com/puzzle-in-a-mug/normtest/blob/main/LICENSE)
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"description": "<img src=\"https://raw.githubusercontent.com/puzzle-in-a-mug/normtest/main/docs/_static/favicon-180x180.png\" align=\"right\" />\r\n\r\n# normtest\r\n\r\n\r\n\r\nThis package has a series of tests used to check whether a set of sample data follows, at least approximately, the Normal distribution.\r\n\r\n## Available tests (25/11/2023)\r\n\r\n- Filliben\r\n- Ryan-Joiner\r\n- Looney-Gulledge\r\n\r\n\r\n## Install\r\n\r\n```\r\npip install normtest\r\n```\r\n\r\n## Usage\r\n\r\nEach test has its own class and can be imported as follows:\r\n\r\n```python\r\nfrom normtest import RyanJoiner\r\nfrom normtest import Filliben\r\nfrom normtest import LooneyGulledge\r\n```\r\n\r\nTo perform the test, just instantiate the class and apply the ``fit`` method, passing the data set as a ``NumpyArray``. For example:\r\n\r\n```python\r\nimport numpy as np\r\ntest = RyanJoiner()\r\nx_data = np.array([6, 1, -4, 8, -2, 5, 0])\r\ntest.fit(x_data)\r\n```\r\n\r\n\r\nAfter the ``fit`` method is applied, the ``test`` ``object`` now has a series of attributes with the test results. The main attribute is ``test.normality``, which contains the summarized results:\r\n\r\n```python\r\nprint(test.normality)\r\nRyanJoiner(statistic=0.9844829186140105, critical=0.8977794003662074, p_value='p > 0.100', conclusion='Fail to reject H\u2080')\r\n```\r\n\r\nThe ``test`` ``object`` also has methods for graphical visualization of results, such as the ``line_up`` method. See the [documentation](https://normtest.readthedocs.io/en/latest/source/ryan_joiner/RyanJoiner.html) for details.\r\n\r\n\r\nEach test has its individual module, and functions can be accessed through the modules. To import the module that contains all the RyanJoiner test functions, for example, use:\r\n\r\n```python\r\nfrom normtest import ryan_joiner\r\n```\r\n\r\nThis way, it is possible to generate graphs and obtain intermediate values from the test calculations. For example:\r\n\r\n```python\r\nsize = 7\r\npi = ryan_joiner._order_statistic(size)\r\nprint(pi)\r\n[0.0862069 0.22413793 0.36206897 0.5 0.63793103 0.77586207\r\n 0.9137931 ]\r\n```\r\n\r\n\r\n\r\n\r\n## License\r\n\r\n- [BSD 3-Clause License](https://github.com/puzzle-in-a-mug/normtest/blob/main/LICENSE)\r\n",
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