Metadata-Version: 2.1
Name: psd2
Version: 0.0.4
Summary: Estimate power spectral density characteristics using Welch's method
Home-page: https://github.com/demotu/psd2
Author: Marcos Duarte
Author-email: duartexyz@gmail.com
License: UNKNOWN
Description: # [psd2](https://pypi.org/project/psd2/)
        
        Estimation of power spectral density characteristics using Welch's method
        
        The function psd2.py from Python module psd2 estimates power spectral density characteristics using Welch's method. This function is just a wrap of the scipy.signal.welch function with estimation of some frequency characteristics and a plot.
        The psd2.py returns power spectral density data, frequency percentiles of the power spectral density (for example, Fpcntile[50] gives the median power frequency in Hz); mean power frequency; maximum power frequency; total power, and plots power spectral density data.
        
        ## Installation
        
        ```bash
        pip install psd2
        ```
        
        Or
        
        ```bash
        conda install -c duartexyz psd2
        ```
        
        ## Examples
        
        ```python
        #Generate a test signal, a 2 Vrms sine wave at 1234 Hz, corrupted by
        # 0.001 V**2/Hz of white noise sampled at 10 kHz and calculate the PSD:
        >>> fs = 10e3
        >>> N = 1e5
        >>> amp = 2*np.sqrt(2)
        >>> freq = 1234.0
        >>> noise_power = 0.001 * fs / 2
        >>> time = np.arange(N) / fs
        >>> x = amp*np.sin(2*np.pi*freq*time)
        >>> x += np.random.normal(scale=np.sqrt(noise_power), size=time.shape)
        >>> psd2(x, fs=freq);
        ```
        
        - [psd2.ipynb](https://github.com/demotu/psd2/blob/master/docs/psd2.ipynb)
        
        ## How to cite this work
        
        Here is a suggestion to cite this GitHub repository:
        
        > Duarte, M. (2020) psd2: A Python module for estimation of power spectral density characteristics using Welch's method. GitHub repository, <https://github.com/demotu/psd2>.
        
        And a possible BibTeX entry:
        
        ```tex
        @misc{Duarte2020,  
            author = {Duarte, M.},
            title = {psd2: A Python module for estimation of power spectral density characteristics using Welch's method},  
            year = {2020},  
            publisher = {GitHub},  
            journal = {GitHub repository},  
            howpublished = {\url{https://github.com/demotu/psd2}}  
        }
        ```
        
        ## License
        
        The non-software content of this project is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/), and the software code is licensed under the [MIT license](https://opensource.org/licenses/mit-license.php).
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
