Metadata-Version: 1.1
Name: pypeaks
Version: 0.2.3
Summary: Python module with different methods to identify peaks from data like histograms and time-series data
Home-page: https://github.com/gopalkoduri/pypeaks
Author: Gopala Krishna Koduri
Author-email: gopala.koduri@gmail.com
License: GNU Affero GPL v3
Description: pypeaks
        =======
        
        Identifying peaks from data is one of the most common tasks in many
        research and development tasks. **pypeaks** is a python module to detect
        peaks from any data like histograms and time-series.
        
        Following are the available methods implemented in this module for peak
        detection: \* Slope based method, where peaks are located based on how
        the data varies. \* Intervals based method, where a set of intervals can
        be passed to provide apriori information that there will be at most one
        peak in each interval, and we just pick the maximum in each interval,
        filtering out irrelevant peaks at the end. \* A hybrid method which
        combines these two methods.
        
        Installation
        ------------
        
        ::
        
            $ sudo pip install --upgrade pypeaks
        
        Usage
        -----
        
        There is an example case included along with the code. If you don't have
        this folder, please load your data instead. Or get it from
        `https://github.com/gopalkoduri/pypeaks <https://github.com/gopalkoduri/pypeaks>`_.
        
        Important note
        ~~~~~~~~~~~~~~
        
        The peak finding function expects a normalized smoothed histogram. It
        does smoothing by default. If you want to change the smoothness,
        customize the corresponding argument. If the data is not normalized (so
        that the area under the curve comes to 1), there is a function provided
        to do that. If you don't get any peaks, then you probably overlooked
        this!
        
        ::
        
            import pickle
            from pypeaks import Data, Intervals
        
            [x, y] = pickle.load(file('examples/sample-histogram.pickle'))
            data_obj = Data(x, y, smoothness=11)
        
            #Peaks by slope method
            data_obj.get_peaks(method='slope')
            #print data_obj.peaks
            data_obj.plot()
        
            #Peaks by interval method
            ji_intervals = pickle.load('examples/ji_intervals.pickle')
            ji_intervals = Intervals(ji_intervals)
            data_obj.get_peaks(method='interval', intervals=ji_intervals)
            #print data_obj.peaks
            data_obj.plot(intervals=ji_intervals)
        
            #Read the help on Data object, and everything else is explained there.
            help(Data)
        
        In case you face some issue, report it on
        `github <https://github.com/gopalkoduri/pypeaks>`_, or write to me at
        **gopala [dot] koduri [at] gmail [dot] com**!
        
        `|Bitdeli Badge| <https://bitdeli.com/free>`_
        
        .. |Bitdeli
        Badge| image:: https://d2weczhvl823v0.cloudfront.net/gopalkoduri/pypeaks/trend.png
        
Keywords: python peaks histogram time-series maxima minima
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries :: Python Modules
