added buffer raster function

benb.py

@@ -148,7 +148,6 @@ def colrow2xy(colrow, rio_object=None, affine_in=None):
     return x, y
 
 
-
 def progress_bar(iterable, prefix='', suffix='', decimals=1, length=100, fill='#', printEnd="\r"):
     """
     Call in a loop to create terminal progress bar
@@ -230,4 +229,3 @@ def file_of_type(x, ext):
         raise argparse.ArgumentTypeError('{} is not a file'.format(x))
     if not ext_match:
         raise argparse.ArgumentTypeError('{} is not a correct file'.format(x))
-

buffer_raster.py

+import rasterio as rio
+import numpy as np
+import os
+
+
+def buffer_raster(raster_path: str, crs, padding: int = 100):
+    """
+
+    Parameters
+    ----------
+    raster_path : str
+        filepath for raster to buffer
+    crs
+        crs specification
+    padding : int
+        amount of cells to buffer around raster
+
+    Returns
+    -------
+    buffered raster : rasterio.io.DatasetReader
+
+
+    """
+    raster = rio.open(raster_path)
+    raster_buffered = raster.read(1)
+    for i in range(padding):
+        raster_buffered = np.insert(raster_buffered, [0], -9999, axis=1)
+        raster_buffered = np.insert(raster_buffered, [0], -9999, axis=0)
+        raster_buffered = np.insert(raster_buffered, [-1], -9999, axis=1)
+        raster_buffered = np.insert(raster_buffered, [-1], -9999, axis=0)
+    raster_buffered = np.where(raster_buffered == -9999, np.nan, raster_buffered)
+    origin_x, origin_y = raster.xy(-padding, -padding)
+
+    outputpath = os.path.splitext(raster_path)[0] + ".tif"
+    with rio.open(
+            outputpath,
+            "w",
+            driver="GTiff",
+            height=raster_buffered.shape[0],
+            width=raster_buffered.shape[1],
+            count=1,
+            dtype=raster_buffered.dtype,
+            crs=crs,
+            transform=rio.transform.from_origin(origin_x - 12.5, origin_y + 12.5, 25, 25),
+    ) as outputraster:
+        outputraster.write(raster_buffered, 1)
+    return rio.open(outputpath)

mnp_hokaggregation.py

@@ -9,7 +9,7 @@ from mpl_toolkits.axes_grid1 import make_axes_locatable
 import os
 
 
-def mnp_hokaggregation(hok_csv, hokken_polygon_path, background_raster_path, outputdir):
+def mnp_hokaggregation(hok_csv, hokken_polygon_path, background_raster_path, outputdir, gridcell_count=False):
     """
     make aggregationplots for use in manual validation of mnp runs. can both aggregate validation data and species
     model gridcells per hok.
@@ -46,19 +46,26 @@ def mnp_hokaggregation(hok_csv, hokken_polygon_path, background_raster_path, out
         extend = "max"
         ylabel_text = "Number of observations in SOVON"
 
-    elif "COUNT_KEY_VALUE" in colnames:
+    elif "OPS_COUNT" in colnames:
+        bounds = np.array([1, 10, 50, 100, 500, 1000])
+        explabel = "_validation"
+        valuecolumn = "OPS_COUNT"
+        extend = "max"
+        ylabel_text = "number of observations in NDFF"
+
+    elif gridcell_count:
         bounds = np.array([1, 10, 100, 1000, 10000, 40000])
         explabel = "_"
         valuecolumn = "COUNT_KEY_VALUE"
         extend = "neither"
         ylabel_text = "Number of gridcells in Hok"
 
-    elif "OPS_COUNT" in colnames:
-        bounds = np.array([1, 10, 50, 100, 500, 1000])
-        explabel = "_validation"
-        valuecolumn = "OPS_COUNT"
+    elif "MAX_KEY_VALUE" in colnames:
+        bounds = np.array([0, 0.1, 0.5, 1, 1.5, 2])
+        explabel = "_"
+        valuecolumn = "MAX_KEY_VALUE"
         extend = "max"
-        ylabel_text = "number of observations in NDFF"
+        ylabel_text = "Largest key population in cell"
 
     else:
         raise Exception("no value column in columns")