sort table going into Accumulation, modify UpCat column naming

StreamCat.py

@@ -154,6 +154,10 @@
                     cat = appendConnectors(cat, Connector, zone, inter_vpu)
                 accum = np.load("accum_npy/bastards/accum_%s.npz" % zone)
 
+                cat.COMID = cat.COMID.astype(accum["comids"].dtype)
+                cat.set_index("COMID",inplace=True)
+                cat = cat.loc[accum["comids"]].reset_index().copy()
+
                 up = Accumulation(
                     cat, accum["comids"], accum["lengths"], accum["upstream"], "Up"
                 )

StreamCat_functions.py

@@ -817,9 +817,8 @@ def Accumulation(tbl, comids, lengths, upstream, tbl_type, icol="COMID"):
         data[:, index] = values
     data = data[np.in1d(data[:, 0], coms), :]  # Remove the extra comids
     outDF = pd.DataFrame(data)
-    outDF.columns = np.append(
-        icol, map(lambda x: x.replace("Cat", tbl_type), cols.values)
-    )
+    prefix = "UpCat" if tbl_type == "Up" else "Ws"
+    outDF.columns = [icol] + [c.replace("Cat", prefix) for c in cols.tolist()]
     areaName = outDF.columns[outDF.columns.str.contains("Area")][0]
     # identifies that there is no area in catchment mask,
     # then NA values for everything past Area, covers upcats w. no area AND