allow high rh_diff for surge_noadapt lookup

Author: bolliger32

pyCIAM/run.py

@@ -333,7 +333,13 @@ def calc_costs(
             surge_noadapt = []
             surge = []
 
-            def _check_vals(rh_diff_arr, lslr_arr, seg):
+            def _check_vals(rh_diff_arr, lslr_arr, seg, check_rh_diff_max=True):
+                # for surge_noadapt, rh_diff can be greater than max. This happens when
+                # a segment chooses retreat10000 in their refA (initial adaptation) and
+                # also has a declining no-climate-change SLR scenario (e.g. for
+                # no-climate-change scenarios). However, we automatically assign 0
+                # expected storm impacts for retreat10000, so this is acceptable and
+                # does not need to exist in the surge lookup table.
                 error_str = (
                     "{0} value is {1} than {2} in storm damage lookup "
                     f"table for segment {seg}. Please investigate why this is. You may "
@@ -343,7 +349,10 @@ def _check_vals(rh_diff_arr, lslr_arr, seg):
                 )
                 # lslr is allowed to be below min surge lookup value b/c we created
                 # lookup such that < min value will be 0 impact
-                if rh_diff_arr.max() > this_surge_lookup.rh_diff.max():
+                if (
+                    check_rh_diff_max
+                    and rh_diff_arr.max() > this_surge_lookup.rh_diff.max()
+                ):
                     raise ValueError(error_str.format("rh_diff", "higher", "maximum"))
                 if rh_diff_arr.min() < this_surge_lookup.rh_diff.min():
                     raise ValueError(error_str.format("rh_diff", "lower", "minimum"))
@@ -357,13 +366,16 @@ def _check_vals(rh_diff_arr, lslr_arr, seg):
                     .reset_coords(drop=True)
                     .frac_losses.rename(lslr_by_seg="lslr", rh_diff_by_seg="rh_diff")
                 )
-                lslr_too_low = lslr.sel(seg=seg) < this_surge_lookup.lslr.min()
                 if this_surge_lookup.sum() == 0:
                     continue
 
                 this_rh_diff_noadapt = rh_diff_noadapt.sel(seg=seg, drop=True)
                 this_lslr = lslr.sel(seg=seg, drop=True)
-                _check_vals(this_rh_diff_noadapt, this_lslr, seg)
+                _check_vals(
+                    this_rh_diff_noadapt, this_lslr, seg, check_rh_diff_max=False
+                )
+
+                lslr_too_low = this_lslr < this_surge_lookup.lslr.min()
 
                 this_surge_noadapt = (
                     this_surge_lookup.sel(adapttype="retreat", drop=True)
@@ -376,8 +388,13 @@ def _check_vals(rh_diff_arr, lslr_arr, seg):
                     .expand_dims(seg=[seg])
                 )
 
-                # ensure nans are only at the beginning
-                assert (this_surge_noadapt.notnull() | lslr_too_low).all(), seg
+                # ensure nans are only at the low end of LSLR or high end of rh_diff
+                rh_diff_too_high = (
+                    this_rh_diff_noadapt > this_surge_lookup.rh_diff.max()
+                )
+                assert (
+                    this_surge_noadapt.notnull() | lslr_too_low | rh_diff_too_high
+                ).all(), seg
 
                 surge_noadapt.append(this_surge_noadapt.fillna(0))
 
@@ -399,7 +416,7 @@ def _check_vals(rh_diff_arr, lslr_arr, seg):
                         .reset_coords(drop=True)
                     )
 
-                    # ensure nans are only at the beginning
+                    # ensure nans are only at the low end of lslr
                     assert (this_surge_adapt.notnull() | lslr_too_low).all(), seg
 
                     surge_adapt.append(this_surge_adapt.fillna(0))
@@ -1500,9 +1517,11 @@ def get_refA(
             **params.refA_scenario_selectors,
         )
         slr = slr.unstack("scen_mc")
-    slr = slr.squeeze(drop=True)
+    slr = slr.squeeze(
+        [d for d in slr.dims if len(slr[d]) == 1 and d != "seg"], drop=True
+    )
 
-    costs, refA = calc_costs(
+    return calc_costs(
         inputs, slr, surge_lookup=surge, return_year0_hts=True, **model_kwargs
     )