Metadata-Version: 2.1
Name: cygnsslib
Version: 1.1.6
Summary: Toolset for working with CYGNSS data and downloading CYGNSS data from PODAC
Home-page: https://bitbucket.org/usc_mixil/cygnsslib
Author: Amer Melebari and James D. Campbell
Author-email: amelebar@usc.edu
License: UNKNOWN
Description: # CYGNSS Library
        
        CYGNSS Library is a Python package for working with CYGNSS data.  
        
        ## Installation
        you can install it using `pip`  
        
        ```console
        $ pip install -U -i https://test.pypi.org/simple/ cygnsslib
        ```
         or you can clone the repository and install it using the following command  
        ```console
        pip install .  
        ```
        You can then remove the local copy if you wish. Alternatively, if you wish to be able to make changes to your local copy without having to reinstall the package for the changes to take effect (e.g., for development purposes), you can use the following instead:
        ```console
        pip uninstall cygnsslib
        ```
        To use it with anaconda, install the environment as follows:  
        ```console
        conda create -n cygnss  
        source activate cygnss  
        conda install -c conda-forge python matplotlib simplejson numpy netcdf4 geographiclib lxml setuptools  
        ```
        ## How to use the code
        Example usage:
        You can see some examples in the testing folder, also the code below  
        
        ```python
        import cygnsslib 
        import os
        
        cygnss_l1_dir = os.environ["CYGNSS_L1_PATH"]  # Default path 
        
        cygnsslib.write_sp_from_kml(cygnss_l1_dir, year=[2019], daylist=[50,51,52], in_kml='salar_poly.kml', out_root='salar_sp',
         thresh_ddm_snr=-9999., thresh_noise=3, out_options=None)
        cygnsslib.plot_brcs(cygnss_l1_dir,year=2018,day=52,sc_num=7,ch_num=1,samp_num=38789,tag_png="salar",tag_title="Salar")
        ```
        
        To download CYGNSS data see the following example
        ```python
        from getpass import getpass
        import cygnsslib
        import datetime as dt
        import numpy as np
        import os
        
        
        # Download data in the same year and range of days
        data_day = np.arange(5, 10)
        data_year = 2020
        # sc_num = [3]
        sc_num = None  # Will download all the 8 spacecrafts 
        re_download = False
        cyg_data_ver = 'v2.1'
        cygnss_l1_path = os.environ["CYGNSS_L1_PATH"]
        cygnsslib.download_cyg_files(data_year, data_day, list_sc_num=sc_num, cyg_data_ver=cyg_data_ver,
                           cyg_data_lvl='L1', cygnss_l1_path=cygnss_l1_path, re_download=re_download)
        
        # Downloading data between two dates (including end date)
        st_date = dt.date(year=2019, month=1, day=12)
        end_date = dt.date(year=2020, month=1, day=3)
        
        cygnsslib.download_cyg_files_between_date(st_date, end_date, list_sc_num=sc_num, cyg_data_ver=cyg_data_ver,
                                        cyg_data_lvl='L1', cygnss_l1_path=cygnss_l1_path, re_download=re_download)
        
        ```
        
        where
        - CYGNSS Level 1 data are available in [PPODAAC](https://podaac-tools.jpl.nasa.gov/drive/files/allData/cygnss/L1) 
        - `salar_poly.kml` file can be generated by drawing a polygon in Google Earth Pro (e.g., inside the Salar de Uyuni in Bolivia) and saving as a KML file.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
