Metadata-Version: 2.1
Name: zort
Version: 1.0.3
Summary: Reader for lightcurves from the ZTF Public Data Release
Home-page: https://github.com/MichaelMedford/zort
Author: Michael Medford
Author-email: michaelmedford@berkeley.edu
License: MIT
Download-URL: https://github.com/MichaelMedford/zort/tarball/1.0.3
Project-URL: Lightcurves, https://www.ztf.caltech.edu/page/dr1#12c
Description: # zort : ZTF Object Reader Tool
        
        ## Getting Started
        
        The ZTF Object Reader Tool, ```zort```, is set of functions to organize and 
        access the ZTF Public Data Release lightcurves across multiple colors. 
        
        ### ZTF Public Data Release Lightcurves
        
        Instructions for downloading and extracting ZTF Public Data Release Lightcurves 
        can be found at: https://www.ztf.caltech.edu/page/dr1#12c
        
        The ZTF Public Data Release Lightcurves are generated through spatially 
        cross-matching individual epoch photometric catalogs. Catalogs are 
        pre-filtered to be (1) the same ZTF observation field ID, (2) the same CCD 
        readout channel, and (3) the same photometric color. Spatially coincidence
        observations in these catalogs are all labelled as objects and saved to a 
        common ascii file along with the observation data for each epoch of the object. 
        These files are consolidated such that all objects sharing a common ZTF 
        observation field ID reside in the same file.
        
        ```zort``` refers to these files with extension ```*.txt``` as 
        **lightcurve files**.
        
        ### Features
        
        ```zort``` provides facilitates the reading and inspection of lightcurves in 
        the ZTF Public Data Release. The features of ```zort``` include:
        - Seamless looping through ZTF lightcurves for custom filtering, where 
        interesting objects can be saved and recovered by only their file location
        - Consolidating g-band and R-band lightcurves of a single source that are 
        otherwise labelled as two separate objects by pairing objects as "siblings"
        - Plotting lightcurves in multiple colors for visual inspection
        
        ### Installation
        
        Preferred method is through pip:
        
        ```
        pip install zort
        ```
        
        Latest version can also be installed from github:
        ```
        git clone https://github.com/MichaelMedford/zort.git
        cd zort
        python setup.py install
        ```
        
        ### Terminology
        - **lightcurve file**: Files included in the ZTF Public Data Release containing 
        epoch photometry for spatially coincidence observations
        - **object**: A collection of spatially coincident 
        observations in a single color. Objects include IDs, sky locations (in right 
        ascension and declination) and colors (g-band and R-band).
        - **lightcurve**: Observation epochs of an object. Lightcurve observations 
        include dates, magnitudes and magnitude errors.
        - **rcid map**: Information on the organization of the lightcurve files 
        required for faster object access.
        - **sibling**: A spatially coincident source in a different color.
        
        ### Initialization
        
        ```zort``` requires that the location of the lightcurve files be saved as 
        an environemnt variable **ZTF_LC_DATA**. You will most likely want to set this 
        location as an environment variable in your ~/.bashrc file or ~/.cshrc.
        
        ```zort``` creates two additional data products per lightcurve file 
        (```*.txt```) in order to make object discovery and multiple color 
        consolidation faster. Object files (```*.objects```) contain all of the 
        metadata for each object in a lightcurve file. RCID map files 
        (```*.rcid_map```) contain lightcurve file metadata that facilitates faster 
        matching of multiple colors for individual objects. ```zort``` requires that 
        each lightcurve file has a corresponding object file and RCID map file.
        
        To generate object files and RCID map files either run:
        ```
        python {initializeFile}
        ```
        or
        ```
        python {initializeFile} --parallel --n-procs=$N_PROCS
        ``` 
        
        ## Examples
        
        ### Extracting Lightcurves
        
        ```zort``` is designed to provide you with easy access to all of the 
        lightcurves in a lightcurve file for applying filters and saving interesting 
        objects. The preferred method for inspecting lightcurves is through a for-loop.
        
        A filter is created that returns True for interesting objects. This filter 
        can involve simply cuts on object properties or complicated model fitting to 
        the full observation data in the object's lightcurve
        ```
        def my_interesting_filter(obj):
            cond1 = obj.nepochs >= 20
            cond2 = min(obj.lightcurve.mag) <= 17.0
            if cond1 and cond2:
                return True
            else:
                return False
        ```
        
        When a lightcurve file is looped over, it returns each object in the lightcurve
        file. The buffer_position should be saved for interesting objects as this is 
        the unique identifier for each object. Saving this identifier, instead of the 
        object ID, allows for O(1) retrieval of the lightcurve.
        ```
        filename = 'field000245_ra357.03053to5.26702_dec-27.96964to-20.4773.txt'
        interesting_objects = []
        
        from zort.lightcurveFile import LightcurveFile
        for obj in LightcurveFile(filename):
            if my_interesting_filter(obj):
                interesting_objects.append(obj.buffer_position)
        ```
        
        Objects and their lightcurves can be retrieved by instantiating an Object with 
        the lightcurve filename and the object's buffer_position.
        ```
        from zort.object import Object
        for buffer_position in interesting_objects:
            obj = Object(filename, buffer_position)
            print(obj)
            print(obj.lightcurve)
        ``` 
        
        ### Matching multiple  colors for an object
        
        Each object is defined as a spatially coincidence series of observations that 
        share a (1) ZTF observation field ID, (2) CCD readout channel, and (3) 
        photometric filter. This labels multiple colors of the same astrophysical 
        source as separate ZTF objects with separate object IDs. The ZTF Public Data 
        Release does not provide any native support for pairing these objects as 
        multiple colors of the same source.
        
        ```zort``` supports searching for and saving multiple colors for the same 
        source. The ZTF Public Data Release contains observations in g-band 
        (filterid=1) and R-band (filterid=2). Each object can therefore have one 
        additional object that comes from the same astrophysical source but is in a 
        different color. These matching objects are labelled as "siblings" and can 
        be both discovered and saved with ```zort```.
        
        The sibling for each object can be located by simply running an object's  
        ```locate_sibling``` method. Running
        
        ```
        filename = 'field000245_ra357.03053to5.26702_dec-27.96964to-20.4773.txt'
        buffer_position = 6852
        obj = Object(filename, buffer_position)
        obj.locate_sibling()
        ```
        
        results in
        ```
        Locating sibling for ZTF Object 245101100000025
        -- Object location: 4.74852, -26.23583 ...
        ** sibling file missing! **
        -- Searching between buffers 17749819 and 18135260
        ---- Sibling found at 4.74851, -26.23581 !
        ---- Original Color: 1 | Sibling Color: 2
        ---- Sibling saved
        ```  
        
        The sibling is saved in a **.siblings** file that can be later recalled. This 
        was the first time that a sibling was located for this lightcurve file and 
        therefore a new sibling file was generated. Now that the sibling has been 
        located, running
        
        ```
        obj.locate_sibling()
        ```
        
        results in
        ```
        Locating sibling for ZTF Object 245101100000025
        -- Object location: 4.74852, -26.23583 ...
        -- Loading sibling...
        -- Sibling loaded!
        ```  
        
        An object's sibling is itself another object and can be accessed through the 
        sibling attribute.
        
        ```
        print(obj)
        Filename: field000245_ra357.03053to5.26702_dec-27.96964to-20.4773.txt
        Buffer Position: 6852
        Object ID: 245101100000025
        Color: g
        Ra/Dec: (4.74852, -26.23583)
        22 Epochs passing quality cuts
        
        print(obj.sibling)
        Filename: field000245_ra357.03053to5.26702_dec-27.96964to-20.4773.txt
        Buffer Position: 126136890
        Object ID: 245201100000047
        Color: r
        Ra/Dec: (4.74851, -26.23581)
        22 Epochs passing quality cuts
        ```
        
        The default tolerance for matching two objecs as siblings is is 2.0". However 
        this can be altered by changing ```obj.sibling_tol_as``` prior to runnning
        ```obj.locate_sibling()``` for the first time.
        
        Siblings are saved to and read from sibling files using the ```portalocker``` 
        package, locking sibling files from simultaneous reading and writing. This 
        guarantees that sibling files will not become corrupted if multiple parallel 
        processes are attempting to save siblings to a sibling file simultaneously.  
        
        ### Plotting lightcurves
        
        A lightcurve plot can be generated for any object using the 
        ```obj.plot_lightcurve()``` method.
        ![](example_images/field000245_ra357.03053to5.26702_dec-27.96964to-20.4773.txt-6852-lc.png)
        
        A lightcurve plot including an object's sibling 
        cand be generated using the ```obj.plot_lightcurves()``` method.
        ![](example_images/field000245_ra357.03053to5.26702_dec-27.96964to-20.4773.txt-6852-lc-with_sibling.png)
        
        ## Requirements
        * Python 3.6
        
        ## Authors
        * Michael Medford <MichaelMedford@berkeley.edu>
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Requires-Python: >=3.5
Description-Content-Type: text/markdown
