From b896216813aac9c8b1e3c985b8889f89a4884653 Mon Sep 17 00:00:00 2001
From: dphogan <6313241+dphogan@users.noreply.github.com>
Date: Fri, 21 Aug 2020 12:33:55 -0400
Subject: [PATCH] Update raster_tile.py

---
 solaris/tile/raster_tile.py | 43 -------------------------------------
 1 file changed, 43 deletions(-)

diff --git a/solaris/tile/raster_tile.py b/solaris/tile/raster_tile.py
index 80793d36..47cf884b 100644
--- a/solaris/tile/raster_tile.py
+++ b/solaris/tile/raster_tile.py
@@ -458,49 +458,6 @@ def save_tile(self, tile_data, mask, profile, dest_fname_base=None):
         #                      os.path.join(self.dest_dir, dest_fname))
         #     os.remove(os.path.join(self.dest_dir, 'tmp.tif'))
         
-    def fill_all_nodata(self, nodata_fill):
-        """
-        Fills all tile nodata values with a fill value.
-        
-        The standard workflow is to run this function only after generating label masks and using the original output 
-        from the raster tiler to filter out label pixels that overlap nodata pixels in a tile. For example, 
-        solaris.vector.mask.instance_mask will filter out nodata pixels from a label mask if a reference_im is provided,
-        and after this step nodata pixels may be filled by calling this method.
-        
-        nodata_fill : int, float, or str, optional
-            Default is to not fill any nodata values. Otherwise, pixels outside of the aoi_boundary and pixels inside 
-            the aoi_boundary with the nodata value will be filled. "mean" will fill pixels with the channel-wise mean. 
-            Providing an int or float will fill pixels in all channels with the provided value.
-            
-        Returns: list
-            The fill values, in case the mean of the src image should be used for normalization later.
-        """
-        src = _check_rasterio_im_load(self.src_name)
-        if nodata_fill == "mean":
-            arr = src.read()
-            arr_nan = np.where(arr!=src.nodata, arr, np.nan)
-            fill_values = np.nanmean(arr_nan, axis=tuple(range(1, arr_nan.ndim)))
-            print('Fill values set to {}'.format(fill_values))
-        elif isinstance(nodata_fill, (float, int)):
-            fill_values = src.meta['count'] * [nodata_fill]
-            print('Fill values set to {}'.format(fill_values))
-        else:
-            raise TypeError('nodata_fill must be "mean", int, or float. {} was supplied.'.format(nodata_fill))
-        src.close()
-        for tile_path in self.tile_paths:
-            tile_src = rasterio.open(tile_path, "r+")
-            tile_data = tile_src.read()
-            for i in np.arange(tile_data.shape[0]):
-                tile_data[i,...][tile_data[i,...] == tile_src.nodata] = fill_values[i] # set fill value for each band
-            if tile_src.meta['count'] == 1:
-                tile_src.write(tile_data[0, :, :], 1)
-            else:
-                for band in range(1, tile_src.meta['count'] + 1):
-                    # base-1 vs. base-0 indexing...bleh
-                    tile_src.write(tile_data[band-1, :, :], band)
-            tile_src.close()
-        return fill_values
-
     def fill_all_nodata(self, nodata_fill):
         """
         Fills all tile nodata values with a fill value.