Bugs in supplychain module

[spjuhel]

1. The G matrix is not always part of the MRIOT object and leads to a confusing error (see error below)
2. "event_id" is not necessarily the name of the index of the intermediate results which lead to a KeyError: 'event_id' in the results.

Suggested fix:

1. Compute G when creating the MRIOT
2. Set the index name correctly

---

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
Cell In[13], line 1
----> 1 res = model.calc_indirect_impacts()

File [.../python3.11/site-packages/climada_petals/engine/supplychain/core.py:894](.../python3.11/site-packages/climada_petals/engine/supplychain/core.py#line=893), in StaticIOModel.calc_indirect_impacts(self, event_ids)
    883     return None
    885 df_leontief_rel, df_leontief_abs, df_leontief_shock, df_leontief_sec_shock = (
    886     create_df_metrics(
    887         event_ids,
   (...)    891     )
    892 )
    893 df_ghosh_rel, df_ghosh_abs, df_ghosh_shock, df_ghosh_sec_shock = (
--> 894     create_df_metrics(
    895         event_ids,
    896         "ghosh",
    897         self.mriot.x.iloc[:, 0],
    898         self.direct_shocks.impacted_assets,
    899     )
    900 )
    901 res = pd.concat(
    902     [
    903         df
   (...)    915     axis=0,
    916 )
    917 res = res.reset_index().sort_values(
    918     ["event_id", "region", "sector", "method", "metric"]
    919 )[["event_id", "region", "sector", "method", "metric", "value"]]

File [...), in StaticIOModel.calc_indirect_impacts.<locals>.create_df_metrics(event_ids, method, indout, abs_shock)
    840     df = self.calc_leontief(event_ids)
    841 elif method == "ghosh":
--> 842     df = self.calc_ghosh(event_ids)
    843 else:
    844     raise ValueError(f"Unrecognized methods: {method}")

File [...), in StaticIOModel.calc_ghosh(self, event_ids)
    803     if event_ids is None:
    804         event_ids = self.direct_shocks.event_ids
--> 805     res_ghosh = [
    806         (self.degraded_value_added.loc[event_id].dot(self.mriot.G))
    807         for event_id in event_ids
    808     ]
    809     return pd.DataFrame(res_ghosh, index=event_ids)
    810 else:

File [...), in <listcomp>(.0)
    803     if event_ids is None:
    804         event_ids = self.direct_shocks.event_ids
    805     res_ghosh = [
--> 806         (self.degraded_value_added.loc[event_id].dot(self.mriot.G))
    807         for event_id in event_ids
    808     ]
    809     return pd.DataFrame(res_ghosh, index=event_ids)
    810 else:

File [...), in Series.dot(self, other)
   3230     lvals = self.values
   3231     rvals = np.asarray(other)
-> 3232     if lvals.shape[0] != rvals.shape[0]:
   3233         raise Exception(
   3234             f"Dot product shape mismatch, {lvals.shape} vs {rvals.shape}"
   3235         )
   3237 if isinstance(other, ABCDataFrame):

IndexError: tuple index out of range