Metadata-Version: 2.1
Name: adampy
Version: 0.0.4
Summary: Python Adam API
Home-page: https://git.services.meeo.it/sistema/adampy
Author: MEEO s.r.l.
Author-email: info@meeo.it
License: UNKNOWN
Description: 
        # Documentation for Adampy_devel
        
        ## Description
        
        Adampy allows to retrieve, analyze and download data hosted within the ADAM environment.
        
        ## Installation Procedure
        ```
        virtualenv -p `which python3` venv
        source venv/bin/activate
        python3 -m pip install --upgrade pip
        pip3 install adampy
        ```
        **********
        
        ## Functions
        
        ***********
        
        ### getCollections
        
        The getCollections function returns all available collections in the selected endpoint.
        
        ```
        adam.getCollections(endpoint).get_data()
        ```
        #### Parameters
        
        * endpoint (str) - The name of the endpoint to get the collections from.
        
        #### Returns
        
        * List with name of all collections
        
        #### Examples
        
        To get the list of collections:
        
        ```python
        import adampy as adam
        
        collections = adam.getCollections('wcs-eo4sdcr.adamplatform.eu').get_data()
        
        print(collections)
        
        ```
        
        ------------------------------------------------------------------
        
        ### getImage
        
        The getImage function returns a numpy array containing the requested image. The image can be saved using Rasterio.
        ```
        adam.getImage(endpoint, collection, time_t, min_lat = -90, max_lat = 90, min_long = -180, max_long = 180, token = 'None', geometry = 'None', masking = False, fname = 'image.tif').get_data()
        ```
        
        #### Parameters
        
        * endpoint (str) - The name of the endpoint to get the collections from.
        * collection (str) - The name of the collection
        * time_t (str) - The time or time range in the format yyyy-mm-ddThh:mm:ss
        * min_lat (int or float; optional) - Minimum latitude of the bounding box (range -90 to 90)
        * max_lat (int or float; optional) - Maximum latitude of the bounding box (range -90 to 90)
        * min_long (int or float; optional) - Minimum longitude of the bounding box (range -180 to 180)
        * max_long (int or float; optional) - Maximum longitude of the bounding box (range -180 to 180)
        * token (str; optional) - Token to access restricted collections
        * geometry (shp, geojson or kml file; optional) - Geometry to mask the output image
        * masking (True or False; Default False ; optional) - Activate the masking option
        * fname (str; optional) - Name for the output file, if not stated fname = image.tif
        
        #### Returns
        
        * Numpy array with the requested image and Metadata information for the image
        
        #### Examples
        
        Get a global image for a particular time
        
        ```python
        import adampy as adam
        import matplotlib
        import matplotlib.pyplot as plt
        
        image, out_meta = adam.getImage('wcs-eo4sdcr.adamplatform.eu', 'Z_CAMS_C_ECMF_PM10_4326_04','2019-03-26T00:00:00').get_data()
        
        plt.subplots(figsize=(13,13))
        plt.imshow(image)
        
        
        ```
        
        Get a bounding box for a particular time
        
        ```python
        import adampy as adam
        import matplotlib
        import matplotlib.pyplot as plt
        
        image, out_meta = adam.getImage('wcs-eo4sdcr.adamplatform.eu', 'Z_CAMS_C_ECMF_PM10_4326_04','2019-03-26T00:00:00',10,20,-10,50).get_data()
        
        plt.subplots(figsize=(13,13))
        plt.imshow(image)
        
        ```
        
        Get a bounding box for a time range
        
        ```python
        import adampy as adam
        import matplotlib
        import matplotlib.pyplot as plt
        
        image, out_meta = adam.getImage('wcs-eo4sdcr.adamplatform.eu', 'Z_CAMS_C_ECMF_PM10_4326_04','2019-03-26T00:00:00,2019-03-27T23:59:59',10,20,-10,50).get_data()
        
        plt.subplots(figsize=(13,13))
        plt.imshow(image)
        
        ```
        
        Get a masked image for a time range
        
        ```python
        import adampy as adam
        import matplotlib
        import matplotlib.pyplot as plt
        
        image, out_meta = adam.getImage('wcs-eo4sdcr.adamplatform.eu', 'Z_CAMS_C_ECMF_PM10_4326_04','2019-03-26T00:00:00,2019-03-27T23:59:59', geometry = 'polygon.shp', masking = True).get_data()
        
        plt.subplots(figsize=(13,13))
        plt.imshow(image)
        
        ```
        -----------
        
        ### getTimeSeries
        
        The getTimeSeries function returns two arrays containing the values and time stamps for the request Latitude and Longitude location.
        ```
        adam.getTimeSeries(endpoint, collection, time_t, lat, long, token = 'None').get_data()
        ```
        
        #### Parameters
        
        * endpoint (str) - The name of the endpoint to get the collections from.
        * collection (str) - The name of the collection
        * time_t (str) - The time or time range in the format yyyy-mm-ddThh:mm:ss
        * lat (int or float; optional) - Minimum latitude of the bounding box (range -90 to 90)
        * long (int or float; optional) - Minimum longitude of the bounding box (range -180 to 180)
        * token (str; optional) - Token to access restricted collections
        
        #### Returns
        
        * Two arrays containing the values and time stamps for the request Latitude and Longitude location
        
        #### Examples
        
        ```python
        import adampy as adam
        
        data, times = adam.getTimeSeries('wcs-eo4sdcr.adamplatform.eu', 'ERA-Interim_temp2m_4326_05','2014-03-26T00:00:00,2014-03-30T23:59:59', 25, 60).get_data()
        
        ```
        
        -----------
        
        ### getAnimation
        
        The getAnimation function crates an animated gif of a dataset given a start and end date.
        ```
        adam.getTimeSeries(endpoint, collection, start_date, end_date, min_lat = -90, max_lat = 90, min_long = -180, max_long = 180, token = 'None', frame_duration = 0.1, legend = False).get_data()
        ```
        
        #### Parameters
        
        * endpoint (str) - The name of the endpoint to get the collections from.
        * collection (str) - The name of the collection
        * start_date (date object) - The start date of the animation
        * end_date (date object) - The end date of the animation
        * min_lat (int or float; optional) - Minimum latitude of the bounding box (range -90 to 90)
        * max_lat (int or float; optional) - Maximum latitude of the bounding box (range -90 to 90)
        * min_long (int or float; optional) - Minimum longitude of the bounding box (range -180 to 180)
        * max_long (int or float; optional) - Maximum longitude of the bounding box (range -180 to 180)
        * token (str; optional) - Token to access restricted collections
        * frame_duration (float or int; optional) - Frame duration in seconds
        * legend (True or False; optional) - Add legend to the animation
        
        
        #### Returns
        
        * An animated GIF of the dataset for a given start and end date.
        
        #### Examples
        
        ```python
        import adampy as adam
        from datetime import datetime, timedelta, date
        
        start_date = date(2014,3,1)
        end_date = date(2014,3,5)
        
        gif_fname = adam.getAnimation('wcs-eo4sdcr.adamplatform.eu', 'NEXGDDP-pr_4326_025',start_date = start_date, end_date=end_date, frame_duration = 0.3, legend = False).get_data()
        
        ```
        
        
        ```python
        
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Unix
Requires-Python: >=3.6
Description-Content-Type: text/markdown
