Metadata-Version: 2.1
Name: cygnsslib
Version: 1.1.20
Summary: Toolset for working with CYGNSS data and downloading CYGNSS data from PODAAC
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. The package can be used for downloading SRTM data. Please see How to use the package for more details.
        
        
        ## Installation
        you can install it using `pip`.
        
        ```console
        pip install -U cygnsslib
        ```
        or you can clone the repository and install it using the following command
        ```console
        pip install .  
        ```
        To use it with anaconda, install the environment as follows:
        ```console
        conda create -n cygnss  
        source activate cygnss  
        conda install -c conda-forge --files requiremnts.txt
        ```
        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
        ```
        ### Required packages
        Here the required Python packages:
        ```console
        gdal geographiclib lxml matplotlib netcdf4 numpy openpyxl pandas pbkdf2 pycrypto requests tqdm
        ```
        
        ## How to Use The Package
        The cygnsslib has several modules:  
        1. Identify CYGNSS DDMs within a specific region  
        2. Group DDMs within a specific distance  
        3. Download CYGNSS antenna pattern  
        4. CygDdmId Class, which work as CYGNSS DDM ID  
        5. Download CYGNSS data from PO.DAAC  
        6. Download SRTM data from NASA Earth Data
        7. Other functionality related to CYGNSS data  
          
        For most of the library, you need to set the environment variable ``CYGNSS_L1_PATH`` to the path of the CYGNSS L1 data. i.e.
        ```console 
        CYGNSS_L1_PATH=/cygnss_data/L1/v3.0
        ```
        Note the folder needs to be named as the version (e.g. `v3.0`)name in PODAAC, and the parent folder need to be `L1`
        You can set the environment variable for the session in python as follows:
        ```python
        import os
        os.environ['CYGNSS_L1_PATH'] = '/cygnss_data/L1/v3.0'
        ```
        
        For SRTM you can specify the main path by specifying the environment variable ``SRTM_PATH``. The files will be saved in `SRTM_PATH\hgt`
        ### Identify CYGNSS DDMs within a specific region
        
        There are several ways to find the DDM within a region.  
        1. find all the DDMs that their SP location within a specific distance from a specific location.  
        2. find all the DDMs that their SP location is within the polygon in the specified kml file.  
        
        Below an example of the usage:  
        ```python
        import cygnsslib
        import numpy as np
        import datetime as dt
        
        cygnss_l1_path = None  # this will make the strip get the path from os.environ["CYGNSS_L1_PATH"]
        year = 2019
        days_list = np.arange(1,100)
        ref_pos = [37.1906, -105.9921] #  [lat,long]
        radius = 10e3 # [m]
        thesh_ddm_snr = 3.0 # split DDMs into above thesh_ddm_snr and below thesh_ddm_snr. Above this value the DDM image will be saved
        thesh_noise = 1  # noise threshold, each pixel in the DDM below this value will be replaced by this value
        kml_out_tag = f'my_data' # tag for all the output files, ex: my_data_above_thresh.kml
        save_podaac_pass = True  # if True and download_cygnss_data is True the PO DAAC username/password will be saved
        # The default options are: 
        options = {'save_cvs': False, 
                   'save_ddm_img': True, 
                   'plt_tag': '',
                   'title_img_inc_ddm_time': False,
                   'img_save_type': ['png'],
                   'sheet_type': 'xls'} 
        
        cygnsslib.write_sp_within_radius(cygnss_l1_path, year=2019, daylist=days_list, ref_pos=ref_pos, 
                                         radius=radius, out_root=kml_out_tag, thresh_ddm_snr=thesh_ddm_snr, 
                                         thresh_noise=thesh_noise, download_cygnss_data=True, 
                                         out_options=options, save_podaac_pass=save_podaac_pass)
        
        start_date = dt.date(year=2019,month=1,day=1)
        end_date = dt.date(year=2019,month=6,day=10)  # the end date included in the search
        cygnsslib.write_sp_within_radius_between_dates(cygnss_l1_path,start_date, end_date, ref_pos=ref_pos, 
                                                       radius=radius, out_root=kml_out_tag, thresh_ddm_snr=thesh_ddm_snr,
                                                       thresh_noise=thesh_noise, download_cygnss_data=True,
                                                       out_options=options, save_podaac_pass=save_podaac_pass)
        
        in_kml = f'my_poly.kml'
        cygnsslib.write_sp_from_kml(cygnss_l1_path, year, days_list, in_kml=in_kml, out_root=kml_out_tag,
                                    thresh_ddm_snr=thesh_ddm_snr, thresh_noise=thesh_noise, download_cygnss_data=True,
                                    out_options=options, save_podaac_pass=save_podaac_pass)
        cygnsslib.write_sp_from_kml_between_dates(cygnss_l1_path, start_date, end_date, in_kml=in_kml, out_root=kml_out_tag,
                                    thresh_ddm_snr=thesh_ddm_snr, thresh_noise=thesh_noise, download_cygnss_data=True,
                                    out_options=options, save_podaac_pass=save_podaac_pass)
        ```
        ### Group DDMs within a specific distance
        
        This will group DDMs within specific distance in one group. The kml file need to be the output of `write_sp_from_kml()` or `write_sp_within_radius_between_dates()` or `write_sp_from_kml()` or `write_sp_from_kml_between_dates()`  
        This function need to be used after identifying the DDMs within a specific region
        ```python
        import cygnsslib
        in_kml = f'my_data_above_thresh.kml'
        max_dist = 1e3
        out_kml = f'{in_kml[:-4]}_grp{max_dist:d}'
        cygnsslib.group_sp_within_distance(in_kml, out_kml, max_dist, save_cvs=True, sheet_type=f'xls')
        ```
        
        ### Download CYGNSS antenna pattern
        This function will download cygnss antenna patterns
        
        ```python
        import cygnsslib
        antenna_patterns_folder_path = f'/data/cygnss_antenna_patterns'
        cygnsslib.download_cyg_antenna_patterns(antenna_patterns_folder_path)
        ```
        
        ### CygDdmId Class  
        The ``CygDdmId`` class is basically work as an ID for the DDMs, with some features.  
        There are multiple static functions, which are 
        1. `get_land_prod_info_from_ocean_prod()`  
        2. `find_cygnss_file()`  
        3. `get_sample_id_from_time_rltv_tcs()`  
        4. `cyg_id_list_from_kml()`  
        
        The function `cyg_id_list_from_kml()` generate a list of objects of `CygDdmId` from a kml file. The kml file from  The kml file need to be the output of `write_sp_from_kml()` or `write_sp_within_radius_between_dates()` or `write_sp_from_kml()` or `write_sp_from_kml_between_dates()`
        
        #### Input parameters
        THe input parameters are:  
        1. `file_name` [req]: `None` or the file name. It's better to set it to `None`.  
        2. `year` [req]: data year  
        3. `day` [req]: day of the year  
        4. `sc_num` [req]: spacecraft id, (1-8)  
        5. `ch_id` [req]: channel id (1-4)  
        6. `samp_id` [req]: sample id (zero-based)  
        7. `land_samp_id` [optional]: sample id of the land product (zero-based)  
        8. `sample_time_sec` [optional]: time (in seconds) of the selected DDM (sample) from the beginning of the day  
        9. `land_file_name` [optional]: land product file name  
        10. `ddm_tag` [optional]: DDM tag  
           
        
        ### Methods 
        The current implemented methods are:  
        1. `set_land_sample_id()`: set `land_samp_id`  
        2. `set_ddm_time()`: set `sample_time_sec`  
        3. `set_land_file_name()`: set `land_file_name`  
        4. `fill_file_name()`: fill file name automatically  
        5. `fill_land_parameters()`: fill land product parameters, which are `land_file_name`, `land_samp_id` and `sample_time_sec`  
        6. `get_utc_time()`: return DDM time  
        
        ### Examples  
        There are many usage for this class here few   
        
        ```python
        from cygnsslib import CygDdmId
        year = 2019
        day = 123
        sc_num = 2
        ch_id = 3
        sample_id = 440
        cyg_ddm_id = CygDdmId.CygDdmId(None, year, day, sc_num, ch_id, sample_id)
        ```
           
        
        ```python
        from cygnsslib import CygDdmId
        
        in_kml = f'my_data_above_thresh.kml'
        cyg_ddmid_list = CygDdmId.cyg_id_list_from_kml(in_kml)
        for cyg_ddmid in cyg_ddmid_list:
            cyg_ddmid.fill_file_name()
            cyg_ddmid.fill_land_parameters(l1_land_folder_name=f'v3Land')
        ```
        
        ### Download CYGNSS data from PO.DAAC
        
        You can download both the standard DDMs and the rawif data. You can choose to download data between two dates or a list of days in the year.  
        If a file exists, the code will not re-download it.  
        Note if you select `check_md5_exist_file=True`, then the code will do an md5 check for existing files. This will ensure existing files are good. However, this will make it very slow.
        
        Below an example of downloading DDMs and the rawif files. The files will be organized as they're in PODAAC.
        ```python
        from cygnsslib import cygnss_download
        import datetime as dt
        import numpy as np
        
        # Download data in the same year and range of days
        days_list = np.arange(5, 10)
        data_year = 2020
        # list_sc_num = [3]
        list_sc_num = None  # Will download all the 8 spacecrafts 
        cyg_data_ver = f'v3.0'
        cygnss_download.download_cyg_files(data_year, days_list, list_sc_num=list_sc_num, cyg_data_ver=cyg_data_ver, 
                                           check_md5_exist_file=False, cyg_data_lvl=f'L1', save_podaac_pass=True)
        # 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)
        
        cygnss_download.download_cyg_files_between_date(st_date, end_date, list_sc_num=list_sc_num, cyg_data_ver=cyg_data_ver, 
                                                        check_md5_exist_file=False, cyg_data_lvl=f'L1', save_podaac_pass=True)
        
        # Downloading rawif data 
        download_l1_data = True  # This will download the corresponding L1 data
        cygnss_download.download_cyg_rawif_files(data_year,days_list, list_sc_num, save_podaac_pass=True, 
                                                 download_l1_data=download_l1_data)
        cygnss_download.download_rawif_cyg_files_between_date(st_date,end_date, list_sc_num, save_podaac_pass=True, 
                                                              download_l1_data=download_l1_data)
        
        ```
        #### PODAAC user/pass related notes
        You can get the PO.DAAC Drive API Credentials from https://podaac-tools.jpl.nasa.gov/drive/  
        If you entered the wrong PODAAC user/pass, you'll be asked to re-enter them again. However, you need to re-start the code after that so the saved user/pass are loaded again.  
        
        You can reset your PODAAC user/pass and enter new user/pass using the following code. Note when you run the code, you'll be asked to enter the new user/pass  
        
        Note: if you want to remove the current user/pass, set `save_pass=False`  
        ```python
        from cygnsslib import cygnss_download
        
        cygnss_download.get_podaac_cred(save_pass=True, reset_pass=True) 
        ```
        
        ### Download SRTM data from NASA Earth Data
        The files are in this URL: https://e4ftl01.cr.usgs.gov/MEASURES/SRTMGL1.003/2000.02.11/  
        The username/password can be obtained from https://urs.earthdata.nasa.gov/home  
        
        ```python
        from cygnsslib import srtm_download
        import os
        os.environ['SRTM_PATH'] = '/data/srtm_data'  # The files will be downloaded into SRTM_PATH/hgt path
        files_lat = [21, 22, 20]
        files_lon = [29, 30]
        srtm_download.download_srtm_ght_files(files_lat, files_lon, save_pass=True, unzipfile=False, remove_zippedfile=True)  
        
        
        ```
        #### EarthData username and pass related notes  
        You can reset your EarthData user/pass and enter new user/pass using the following code. Note when you run the code, you'll be asked to enter the new user/pass  
        ```python
        from cygnsslib import srtm_download
        
        srtm_download.get_earthdata_cred(save_pass=True, reset_pass=True) 
        ```
        ### Other functionality related to CYGNSS data   
        
        Create a circle or a square on the ground and export it to kml file  
        ```python
        import cygnsslib
        ref_pos = [37.1906, -105.9921] #  [lat,long]
        radius = 10e3 # [m]
        out_kml = f'my_circle.kml'
        cygnsslib.create_centered_polygon(ref_pos, radius, out_kml, shape=f"circle")
        ```
        Create a kml file from a list of positions  
        ```python
        import cygnsslib
        import numpy as np
        lyr_name = f"my_pos"
        point_names = ["Y1", "Y2", "Y3"]
        loc_list = np.array([[-34.0, 145.0], [-34.0, 146.0], [-34.0, 148]])
        out_kml = f"my_pos.kml"
        cygnsslib.create_kml_from_list_points(loc_list, loc_names=point_names, out_kml=out_kml, lyr_name=lyr_name)
        ```
        
        Get DDMs info from the kml file. The kml file need to be the output of `write_sp_from_kml()` or `write_sp_within_radius_between_dates()` or `write_sp_from_kml()` or `write_sp_from_kml_between_dates()`
        The main goal of this function is extract the DDMs' parameters from the kml file. See ``CygDdmId`` Class for more functionality
        ```python
        import cygnsslib
        
        ddm_list = cygnsslib.get_list_ddm_info_from_kml(in_kml=f'my_data_above_thresh.kml')
        
        ```
        Find CYGNSS Land product (experimental) from the standard ocean product. This function is still in developing.
        ```python
        import cygnsslib
        xls_in = f'my_xls.xlsx'
        cygnsslib.find_land_prod_sample_id_from_excel(xls_in, xls_out=None, start_col=1, st_row=1)
        ```
        
        ## Contact Info  
        For more info, please contact:   
        Amer Melebari   
        Microwave Systems, Sensors and Imaging Lab (MiXiL)  
        University of Southern California  
        amelebar[AT]usc.edu  
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
