Metadata-Version: 2.1
Name: QuantumBlink
Version: 1.0.2
Summary: A Python package to analyze flouresence intermittency data of quantum dots
Home-page: https://github.com/AnoopANair/QuantumBlink
Author: Anoop A Nair {K.G.T. group}
Author-email: mailtoanoop71@gmail.com
License: MIT
Description: # QuantumBlink
        
        
        
        # **INTRODUCTION**
        
        QunatumBlink is a python module developed by **Anoop A Nair**, under the supervison of **Vishnu E K,Ph.D [@ K.G.T. Labs]**.  It helps in the **analysis of flouresence intermittency data** obtained from the MT-300 single photon detector. The module when provided with the Intensity vs Time trace derives the **ON/OFF event PDFs** and the correlations in data indicating the **memory effect**. 
        
        
        # **HOW TO INSTALL**
        
        The `Quantum Blink` module depends on the `numpy` module for most of it's functionality.
        
        To Install `numpy` use:
        
        
        ```
        pip install numpy
        ```
        
        To install `QuantumBlink` use: 
        
        ```
        pip install QuantumBlink
        ```
        
        
        To install `QuantumBlink` of a particular version say 1.x use: 
        
        ```
        pip install QuantumBlink==1.x
        ```
        
        # **HOW TO USE**
        
        The module can be imported after installation using:
        
        ```
        import QuantumBlink as qb
        ```
        The csv file should contain two columns the first one being the time and second one being the intesity values.
        
        
        # **KEYWORDS and METHODS**
        
         ## > **Data Acquisition**
        
        
         ### >> Intensity data
        
        ```
        IntensityData  =  IntensityDataAcquire(PATH)
        ```
        
        
        > 1.**INPUT**
        > * PATH = "the path to the csv data file"
        
        > 2.**OUTPUT**
        > * IntensityData = array of intesity values
        
        
        
        ## > **The ON/OFF Events**
        
        ### >> ON-OFF durations
        ```
        Positives , Negatives =  Power_dist_one(PATH,Threshold,exptime)
        ```
        
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * Positives = array of ON time durations
        > * Negatives = array of OFF time durations
        
        ### >> OFF-time distribution
        
        ```
        Pdf_accept_off,Offtime =  Offtime_pdf(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * Pdf_accept_off = The probability distribution of OFF-time durations
        > * Offtime = array of distinct OFF-time durations
        
        ### >> ON-time distribution
        
        ```
        Pdf_accept_on,Ontime =  Ontime_pdf(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * Pdf_accept_on = The probability distribution of ON-time durations
        > * Ontime = array of distinct ON-time durations
        
        
        ## > **Event Duration info**
        
        ### >> ON time ratio
        
        ```
        On_ratio =  OnTimeFraction(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * On_ratio = The fraction of ON events.  
        
        ### >> OFF time ratio
        
        
        ```
        Off_ratio =  OffTimeFraction(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * Off_ratio = The fraction of OFF events.  
        
        ### >> ON-OFF ratio
        
        
        ```
        ON_OFF_ratio =  OnOffRatio(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * ON_OFF_ratio = The ratio of ON to OFF events.  
        
        ### >> OFF-ON ratio
        
        
        ```
        OFF_ON_ratio =  OffOnRatio(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event.
        
        > 2.**OUTPUT**
        > * OFF_ON_ratio = The ratio of OFF to ON events.  
        
        ### >> TOTAL ONtime
        
        
        ```
        TOTAL_ONTIME =  TotalOnTime(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event.
        
        > 2.**OUTPUT**
        > * TOTAL_ONTIME = The total time occupied by ON events.  
        
        ### >>  TOTAL OFFtime
        
        
        ```
        TOTAL_OFFTIME =  TotalOffTime(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event.
        
        > 2.**OUTPUT**
        > * TOTAL_OFFTIME = The total time occupied by OFF events.  
        
        
        ## >  **Mean, Min, Max intensities**
        
        ### >> The min, max and average intesity of tthe data
        ```
        AverageIntensity = AverageIntensity(PATH)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        
        > 2.**OUTPUT**
        > * AverageIntensity = The Average intensity calculated from the data.  
        
        
        ```
        MaxIntensity = MaxIntensity(PATH)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        
        > 2.**OUTPUT**
        > * MaxIntensity = The maximum intensity calculated from the data.  
        
        
        ```
        MinIntensity = MinIntensity(PATH)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        
        > 2.**OUTPUT**
        > * MinIntensity = The minimum intensity calculated from the data.  
        
        ### >> The average intesity between two intensity levels
        
        ```
        Intensity_average = AverageIntensityBetween(PATH,Threshold1,Threshold2)
        ```
        
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold1 = The upper threshold
        > * Threshold2 = The lower threshold
        
        > 2.**OUTPUT**
        > * Intensity_average = The average intensity between the upper and lower threshold
        
        
        
        ## > **Memory Effect**
        
        
        
        ### >> ON-OFF Correlation
        
        ```
        XX,YY,R1 =  OnOffCorr(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event.
        
        > 2.**OUTPUT**
        > * XX = array of ON/OFF events .
        > * YY = array of ON/OFF events .
        > * R1 = The correlation coefficient. 
        
        ```
        X_x_log,Y_y_log,R1 = OnOffCorrLog(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * X_x_log = array of log value of ON/OFF events .
        > * Y_y_log = array of log value of ON/OFF events .
        > * R1 = The correlation coefficient. 
        
        
        
        ### >> ON-ON Correlation
        
        ```
        XX,YY,R1 OnOnCorr(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * XX = array of ON events .
        > * YY = array of ON events .
        > * R1 = The correlation coefficient. 
        
        ```
        X_x_log,Y_y_log,R1 = OnOnCorrLog(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * X_x_log = array of log value of ON events .
        > * Y_y_log = array of log value of ON events .
        > * R1 = The correlation coefficient. 
        
        ### >> OFF-OFF Correlation
        
        ```
        XX,YY,R1 =  OffOffCorr(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * XX = array of OFF events .
        > * YY = array of OFF events .
        > * R1 = The correlation coefficient. 
        
        ```
        X_x_log,Y_y_log,R1 OffOffCorrLog(PATH,Threshold,exptime)
        ```
        > 1.**INPUT**
        > * PATH = "the path to the csv data file".
        > * Threshold = This specifies the **instensity level** above which events are treated as **positve** and below which events are treated as **negative**.
        > * exptime = The time interval between each consecutive event. 
        
        > 2.**OUTPUT**
        > * X_x_log = array of log value of OFF events .
        > * Y_y_log = array of log value of OFF events .
        > * R1 = The correlation coefficient.
        """
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/markdown
