fix merging issue

Author: cbur24

odc/stats/plugins/ls_ndvi_median.py

@@ -9,11 +9,7 @@
 from typing import Sequence, Tuple
 from datacube.utils.masking import mask_invalid_data
 from odc.stats.plugins._registry import register, StatsPluginInterface
-from odc.algo._masking import (
-    erase_bad,
-    enum_to_bool
-)
-
+from odc.algo._masking import erase_bad, enum_to_bool
 
 class StatsNDVI(StatsPluginInterface):
     """
@@ -42,13 +38,8 @@ def __init__(
         self.contiguity_band = contiguity_band
         self.group_by = group_by
 
-<<<<<<< HEAD
-        # These params get passed to the upstream 
-        # base class StatsPluginInterface
-=======
-        ## These params get passed to the upstream
+        # These params get passed to the upstream
         #  base StatsPluginInterface class
->>>>>>> refs/remotes/origin/plugin_documentation
         super().__init__(
             input_bands=tuple(input_bands) + (mask_band,) + (contiguity_band,), **kwargs
         )
@@ -86,13 +77,8 @@ def native_transform(self, xx):
 
         # drop masking bands
         xx = xx.drop_vars([self.mask_band] + [self.contiguity_band])
-<<<<<<< HEAD
-        
-        # Mask the bad data (clouds etc)
-=======
 
-        ## Mask the bad data (clouds etc)
->>>>>>> refs/remotes/origin/plugin_documentation
+        # Mask the bad data (clouds etc)
         xx = erase_bad(xx, bad)
 
         return xx
@@ -104,21 +90,12 @@ def reduce(self, xx: xr.Dataset) -> xr.Dataset:
         # convert to float by and convert nodata to NaN
         xx = mask_invalid_data(xx)
 
-<<<<<<< HEAD
-        # calculate temporal median NDVI. Note that we use
-        # 'spec' and not 'time', this is an odc-stats thing
-        ndvi = ndvi.median('spec').rename(self.output_bands)
-        
-=======
         ndvi = (xx["nbart_nir"] - xx["nbart_red"]) / (xx["nbart_nir"] + xx["nbart_red"])
 
-        # calculate temporal median NDVI.
-        # !!!!!!!!!!!!!!!!!!!!!!!!!!!!
-        # Note that we use 'spec' and not 'time', this is an odc-stats thing
-        # !!!!!!!!!!!!!!!!!!!!!!!!!!!!
+        # calculate temporal median NDVI. Note that we use
+        # 'spec' and not 'time', this is an odc-stats thing
         ndvi = ndvi.median("spec").rename(self.output_bands)
 
->>>>>>> refs/remotes/origin/plugin_documentation
         return ndvi.to_dataset()