ecoscope.io.raster
==================

.. py:module:: ecoscope.io.raster








Module Contents
---------------

.. py:data:: logger

.. py:data:: RioPixelType

.. py:class:: RasterExtent(x_min = 33.0, x_max = 37.0, y_min = 2.0, y_max = -2.0)

   .. py:attribute:: x_min
      :value: 33.0



   .. py:attribute:: x_max
      :value: 37.0



   .. py:attribute:: y_min
      :value: 2.0



   .. py:attribute:: y_max
      :value: -2.0



   .. py:method:: __repr__()


   .. py:method:: create_from_origin(pixel_size = 0.5, x_min = 0.0, y_min = 0.0, num_rows = 100, num_columns = 100)
      :classmethod:



.. py:class:: RasterProfile(pixel_size = 1000.0, pixel_dtype = rio.float64, crs = 'EPSG:8857', nodata_value = 0.0, band_count = 1, raster_extent = None)

   Bases: :py:obj:`collections.UserDict`


   A class for holding raster properties
   At present this class is only valid for non-rotated rasters with a north-up orientation and square sized pixels
   defined by the E-W pixel size


   .. py:method:: _recompute_transform_(key)

      Recomputes the affine transformation matrix when the pixel_size or raster_extent value is updated.



   .. py:method:: __getattr__(name)


   .. py:method:: __setattr__(name, value)


   .. py:method:: __setitem__(key, item)


.. py:class:: RasterData

   .. py:attribute:: data
      :type:  numpy.ndarray


   .. py:attribute:: crs
      :type:  str


   .. py:attribute:: transform
      :type:  rasterio.Affine


   .. py:method:: from_raster_file(raster_path)
      :classmethod:



.. py:class:: RasterPy

   .. py:method:: write(ndarray, fp, columns, rows, band_count, driver = 'GTiff', dtype = rio.float64, crs = None, transform = None, nodata = None, sharing = False, indexes = 1, **kwargs)
      :classmethod:



   .. py:method:: read(fp, driver = None, **kwargs)
      :classmethod:



   .. py:method:: read_write(fp, driver = None, **kwargs)
      :classmethod:



.. py:function:: reduce_region(gdf, raster_path_list, reduce_func)

   A function to apply the reduce_func to the values of the pixels within each of the rasters for every
   shape within the input geopandas dataframe 'geometry' column
   :param gdf: geopandas dataframe. The geometry column will be used to mask the areas of the input
   raster to be used
   in the reduction
   :param raster_path_list: a list of raster files on disc to analyse
   :param reduce_func: a single-value function to apply to the values of the input raster
   :return: dataframe with a column of reduce values for each raster and a row for each region


.. py:function:: raster_to_gdf(raster_path)

.. py:function:: grid_to_raster(grid, xlen, ylen, val_column = '', out_dir = '', raster_name = None)

   Save a GeoDataFrame grid to a raster.

   Args:
   grid (gpd.GeoDataFrame): The grid to rasterize
   xlen (int): The width of the raster cells, units must be valid in the CRS of the provided grid
   ylen (int): The height of the raster cells, units must be valid in the CRS of the provided grid
   val_column (str): The dataframe column of values to fill the raster cells
   out_dir (str): The directory to save the raster to - inert if raster_name is not provided
   raster_name (str): The filename name of the output raster

   Returns:
   A rio.MemoryFile if raster_name is provided


.. py:function:: raster_to_grid(raster_path)

.. py:function:: get_crs(raster_path)