fix conflict

Author: cbur24

docs/config_ndvi_ls_median.yaml

@@ -30,4 +30,4 @@ cog_opts:
     # If you're making an RGBA image, compress better
     rgba:
       compress: JPEG
-      jpeg_quality: 90
+      jpeg_quality: 90

odc/stats/plugins/ls_ndvi_median.py

@@ -2,7 +2,7 @@
 Simple odc-stats plugin example, with excessive
 documentation. Creates temporal median NDVI
 from DEA Landsat Collection 3
-    
+
 """
 
 import xarray as xr
@@ -14,11 +14,13 @@
     enum_to_bool
 )
 
+
 class StatsNDVI(StatsPluginInterface):
     """
-    Define a class for summarising time 
+    Define a class for summarising time
     series of NDVI using the median.
     """
+
     NAME = "ndvi_median"
     SHORT_NAME = NAME
     VERSION = "1.0"
@@ -33,21 +35,24 @@ def __init__(
         group_by: str = "solar_day",
         **kwargs,
     ):
-        
+
         self.input_bands = input_bands
         self.output_bands = output_bands
         self.mask_band = mask_band
         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
+        #  base StatsPluginInterface class
+>>>>>>> refs/remotes/origin/plugin_documentation
         super().__init__(
-            input_bands=tuple(input_bands)+(mask_band,)+(contiguity_band,),
-            **kwargs
+            input_bands=tuple(input_bands) + (mask_band,) + (contiguity_band,), **kwargs
         )
 
-        
     @property
     def measurements(self) -> Tuple[str, ...]:
         """
@@ -56,7 +61,7 @@ def measurements(self) -> Tuple[str, ...]:
         but equally we could define the outputs ames within this function.
         For example, by adding a suffix to the input bands.
         """
-        
+
         return (self.output_bands,)
 
     def native_transform(self, xx):
@@ -67,22 +72,27 @@ def native_transform(self, xx):
         step of data and is usually used for things like
         masking clouds, nodata, and contiguity masking.
         """
-        #grab the QA band from the Landsat data
+        # grab the QA band from the Landsat data
         mask = xx[self.mask_band]
 
         # create boolean arrays from the mask for cloud
         # and cloud shadows, and nodata
         bad = enum_to_bool(mask, ("nodata",))
         non_contiguent = xx.get(self.contiguity_band, 1) == 0
         bad = bad | non_contiguent
-        
+
         cloud_mask = enum_to_bool(mask, ("cloud", "shadow"))
-        bad =  cloud_mask | bad
+        bad = cloud_mask | bad
 
         # 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
         xx = erase_bad(xx, bad)
 
         return xx
@@ -93,14 +103,24 @@ def reduce(self, xx: xr.Dataset) -> xr.Dataset:
         """
         # convert to float by and convert nodata to NaN
         xx = mask_invalid_data(xx)
-        
-        ndvi = (xx['nbart_nir'] - xx['nbart_red']) / (xx['nbart_nir'] + xx['nbart_red'])
 
+<<<<<<< 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
+        # !!!!!!!!!!!!!!!!!!!!!!!!!!!!
+        ndvi = ndvi.median("spec").rename(self.output_bands)
+
+>>>>>>> refs/remotes/origin/plugin_documentation
         return ndvi.to_dataset()
 
+
 # now lets 'register' the function with odc-stats
 register("ndvi-median", StatsNDVI)