only read the values we need

modules/util/util.py

@@ -411,6 +411,75 @@ def get_cartopy_crs(satellite, domain):
     return geos, xlen, xmin, xmax, ylen, ymin, ymax
 
 
+def get_grid_values(h5f, grid_name, j_c, i_c, half_width, num_j=None, num_i=None, scale_factor_name='scale_factor', add_offset_name='add_offset',
+                    fill_value_name='_FillValue', range_name='actual_range', fill_value=None):
+    hfds = h5f[grid_name]
+    attrs = hfds.attrs
+    if attrs is None:
+        raise GenericException('No attributes object for: '+grid_name)
+
+    ylen, xlen = hfds.shape
+
+    if half_width is not None:
+        j_l = j_c-half_width
+        i_l = i_c-half_width
+        if j_l < 0 or i_l < 0:
+            return None
+
+        j_r = j_c+half_width+1
+        i_r = i_c+half_width+1
+        if j_r >= ylen or i_r >= xlen:
+            return None
+    else:
+        j_l = j_c
+        j_r = j_c + num_j + 1
+        i_l = i_c
+        i_r = i_c + num_i + 1
+
+    grd_vals = hfds[j_l:j_r, i_l:i_r]
+    if fill_value is not None:
+        grd_vals = np.where(grd_vals == fill_value, np.nan, grd_vals)
+
+    if scale_factor_name is not None:
+        attr = attrs.get(scale_factor_name)
+        if attr is None:
+            raise GenericException('Attribute: '+scale_factor_name+' not found for dataset: '+grid_name)
+        if np.isscalar(attr):
+            scale_factor = attr
+        else:
+            scale_factor = attr[0]
+        grd_vals = grd_vals * scale_factor
+
+    if add_offset_name is not None:
+        attr = attrs.get(add_offset_name)
+        if attr is None:
+            raise GenericException('Attribute: '+add_offset_name+' not found for dataset: '+grid_name)
+        if np.isscalar(attr):
+            add_offset = attr
+        else:
+            add_offset = attr[0]
+        grd_vals = grd_vals + add_offset
+
+    if range_name is not None:
+        attr = attrs.get(range_name)
+        if attr is None:
+            raise GenericException('Attribute: '+range_name+' not found for dataset: '+grid_name)
+        low = attr[0]
+        high = attr[1]
+        grd_vals = np.where(grd_vals < low, np.nan, grd_vals)
+        grd_vals = np.where(grd_vals > high, np.nan, grd_vals)
+    elif fill_value_name is not None:
+        attr = attrs.get(fill_value_name)
+        if attr is None:
+            raise GenericException('Attribute: '+fill_value_name+' not found for dataset: '+grid_name)
+        if np.isscalar(attr):
+            fill_value = attr
+        else:
+            fill_value = attr[0]
+        grd_vals = np.where(grd_vals == fill_value, np.nan, grd_vals)
+
+    return grd_vals
+
 # Example GOES file to retrieve GEOS parameters in MetPy form (CONUS)
 exmp_file_conus = '/Users/tomrink/data/OR_ABI-L1b-RadC-M6C14_G16_s20193140811215_e20193140813588_c20193140814070.nc'
 # Full Disk
@@ -460,7 +529,7 @@ def make_for_full_domain_predict(h5f, name_list=None, satellite='GOES16', domain
 
     cnt_a = 0
     for didx, ds_name in enumerate(name_list):
-        gvals = get_grid_values_all(h5f, ds_name, j_0, i_0, None, num_j=ylen, num_i=xlen)
+        gvals = get_grid_values(h5f, ds_name, j_0, i_0, None, num_j=ylen, num_i=xlen)
         if gvals is not None:
             grd_dct[ds_name] = gvals
             cnt_a += 1