Fdmsstar private sector

fdms/computation/country/annual/external_sector.py

@@ -0,0 +1,88 @@
+import pandas as pd
+
+from fdms.utils.mixins import SumAndSpliceMixin
+from fdms.utils.splicer import Splicer
+from fdms.utils.operators import Operators
+from fdms.utils.series import export_to_excel
+
+
+# STEP 16
+class ExternalSector(SumAndSpliceMixin):
+    def perform_computation(self, result_1, result_3, ameco_h_df):
+        # TODO: Check the scales of the output variables
+        splicer = Splicer()
+        operators = Operators()
+
+        # UBYA.1.0.0.0
+
+        addends = {'UBYA.1.0.0.0': ['UBRA.1.0.0.0', 'UBTA.1.0.0.0']}
+        self._sum_and_splice(addends, result_1, ameco_h_df, splice=False)
+        new_input_df = self.result.set_index(['Country Ameco', 'Variable Code'], drop=True)
+        new_input_df = pd.concat([new_input_df, result_1, result_3], sort=True)
+
+
+        # UBCA.1.0.0.0
+
+        addends = {'UBCA.1.0.0.0': ['UXGS.1.0.0.0', '-UMGS.1.0.0.0', 'UBYA.1.0.0.0']}
+        self._sum_and_splice(addends, new_input_df, ameco_h_df, splice=False)
+        new_input_df = self.result.set_index(['Country Ameco', 'Variable Code'], drop=True)
+        new_input_df = pd.concat([new_input_df, result_1, result_3], sort=True)
+
+        # UBLA.1.0.0.0
+
+        addends = {'UBLA.1.0.0.0': ['UBCA.1.0.0.0', 'UBKA.1.0.0.0']}
+        self._sum_and_splice(addends, new_input_df, ameco_h_df, splice=False)
+
+        # DXGT.1.0.0.0
+
+        dxge_data = self.get_data(new_input_df, 'DXGE.1.0.0.0')
+        dxgi_data = self.get_data(new_input_df, 'DXGI.1.0.0.0')
+        dxgt_data = dxge_data + dxgi_data
+        series_meta = self.get_meta('DXGT.1.0.0.0')
+        series = pd.Series(series_meta)
+        series = series.append(dxgt_data)
+        self.result = self.result.append(series, ignore_index=True, sort=True)
+        new_input_df = self.result.set_index(['Country Ameco', 'Variable Code'], drop=True)
+        new_input_df = pd.concat([new_input_df, result_1], sort=True)
+
+        # DMGT.1.0.0.0
+
+        dmge_data = self.get_data(new_input_df, 'DMGE.1.0.0.0')
+        dmgi_data = self.get_data(new_input_df, 'DMGI.1.0.0.0')
+        dmgt_data = dmge_data + dmgi_data
+        series_meta = self.get_meta('DMGT.1.0.0.0')
+        series = pd.Series(series_meta)
+        series = series.append(dmgt_data)
+        self.result = self.result.append(series, ignore_index=True, sort=True)
+        new_input_df = self.result.set_index(['Country Ameco', 'Variable Code'], drop=True)
+        new_input_df = pd.concat([new_input_df, result_1], sort=True)
+
+        # DBGT.1.0.0.0
+
+        dxgt_data = self.get_data(new_input_df, 'DXGT.1.0.0.0')
+        dmgt_data = self.get_data(new_input_df, 'DMGT.1.0.0.0')
+        dbgt_data = dxgt_data - dmgt_data
+        series_meta = self.get_meta('DBGT.1.0.0.0')
+        series = pd.Series(series_meta)
+        series = series.append(dbgt_data)
+        self.result = self.result.append(series, ignore_index=True, sort=True)
+
+        # DBGE.1.0.0.0
+
+        dxge_data = self.get_data(new_input_df, 'DXGT.1.0.0.0')
+        dmge_data = self.get_data(new_input_df, 'DMGT.1.0.0.0')
+        dbge_data = dxge_data - dmge_data
+        series_meta = self.get_meta('DBGE.1.0.0.0')
+        series = pd.Series(series_meta)
+        series = series.append(dbge_data)
+        self.result = self.result.append(series, ignore_index=True, sort=True)
+
+        # TODO: DBGI.1.0.0.0
+
+        self.result.set_index(['Country Ameco', 'Variable Code'], drop=True, inplace=True)
+        self.apply_scale()
+
+        export_to_excel(self.result, step=16)
+
+
+        return self.result

fdms/computation/country/annual/fiscal_sector.py

@@ -66,6 +66,22 @@ def perform_computation(self, df, ameco_h_df):
             'UDGGL.1.0.0.0': ['UDGG.1.0.0.0', ]
         }
         self._sum_and_splice(addends, df, ameco_h_df)
+        new_input_df = self.result.set_index(['Country Ameco', 'Variable Code'], drop=True)
+        new_input_df = pd.concat([new_input_df, df], sort=True)
+
+        # UUCG.1.0.0.0
+
+        addends = {'UUCG.1.0.0.0': ['UWCG.1.0.0.0', 'UYTGH.1.0.0.0','UYIG.1.0.0.0','UYVG.1.0.0.0','UUOG.1.0.0.0','UCTGI.1.0.0.0','UYTGM.1.0.0.0']}
+        self._sum_and_splice(addends, new_input_df, ameco_h_df)
+        new_input_df = self.result.set_index(['Country Ameco', 'Variable Code'], drop=True)
+        new_input_df = pd.concat([new_input_df, df], sort=True)
+
+        # USGG.1.0.0.0
+
+        addends = {'USGG.1.0.0.0': ['-URCG.1.0.0.0', '-UUCG.1.0.0.0']}
+        self._sum_and_splice(addends, new_input_df, ameco_h_df)
+
+        # UDGG.1.0.0.0
 
         variable = 'UDGG.1.0.0.0'
         series_meta = self.get_meta(variable)
@@ -84,5 +100,8 @@ def perform_computation(self, df, ameco_h_df):
 
         self.result.set_index(['Country Ameco', 'Variable Code'], drop=True, inplace=True)
         self.apply_scale()
+
         export_to_excel(self.result, 'output/outputvars12.txt', 'output/output12.xlsx')
+
         return self.result
+

fdms/computation/country/annual/private_sector.py

@@ -0,0 +1,44 @@
+import pandas as pd
+
+from fdms.utils.mixins import SumAndSpliceMixin
+from fdms.utils.splicer import Splicer
+from fdms.utils.operators import Operators
+from fdms.utils.series import export_to_excel
+
+
+# STEP 15
+class PrivateSector(SumAndSpliceMixin):
+    def perform_computation(self, result_1, result_12, result_13, result_14, ameco_h_df):
+        breakpoint()
+        # TODO: Check the scales of the output variables
+        splicer = Splicer()
+        operators = Operators()
+
+        # USGN.1.0.0.0
+
+        addends = {'USGN.1.0.0.0': ['UVGD', 'UBRA', 'UBTA', '-UCPH', '-UCTG']}
+
+        self._sum_and_splice(addends, result_1, ameco_h_df, splice=False)
+        new_input_df = self.result.set_index(['Country Ameco', 'Variable Code'], drop=True)
+        new_input_df = pd.concat([new_input_df, result_1, result_13, result_14], sort=True)
+
+        # UBLP.1.0.0.0
+
+        addends = {'UBLP.1.0.0.0': ['UBLC.1.0.0.0', 'UBLH.1.0.0.0']}
+
+        self._sum_and_splice(addends, new_input_df, ameco_h_df, splice=False)
+        new_input_df = self.result.set_index(['Country Ameco', 'Variable Code'], drop=True)
+        new_input_df = pd.concat([new_input_df, result_1, result_12], sort=True)
+
+        # USGP.1.0.0.0
+
+        addends = {'USGP.1.0.0.0': ['USGN.1.0.0.0','USGG.1.0.0.0']}
+
+        self._sum_and_splice(addends, new_input_df, ameco_h_df, splice=False)
+
+        self.result.set_index(['Country Ameco', 'Variable Code'], drop=True, inplace=True)
+        self.apply_scale()
+
+        export_to_excel(self.result, step=15)
+
+        return self.result

fdms/tests/test_country_calculations.py

@@ -18,6 +18,9 @@
 from fdms.computation.country.annual.fiscal_sector import FiscalSector
 from fdms.computation.country.annual.corporate_sector import CorporateSector
 from fdms.computation.country.annual.household_sector import HouseholdSector
+from fdms.computation.country.annual.private_sector import PrivateSector
+from fdms.computation.country.annual.external_sector import ExternalSector
+
 from fdms.config import YEARS
 from fdms.config.scale_correction import fix_scales
 from fdms.config.variable_groups import NA_VO, T_VO
@@ -201,6 +204,17 @@ def test_country_calculation_BE(self):
         missing_vars = [v for v in variables if v not in list(result_14.loc[self.country].index)]
         self.assertFalse(missing_vars)
 
+        # STEP 15
+        step_15 = PrivateSector(scales=self.scales)
+        result_15 = step_15.perform_computation(self.result_1, result_12, result_13, result_14, self.ameco_df)
+
+        # STEP 16
+        step_16 = ExternalSector(scales=self.scales)
+        result_16 = step_16.perform_computation(self.result_1, result_3, self.ameco_df)
+
+        breakpoint()
+
+
         # TODO: Fix all scales
         result = pd.concat([self.result_1, result_2, result_3, result_4, result_5, result_6, result_7, result_8,
                             result_9, result_10, result_11, result_12, result_13, result_14], sort=True)
@@ -227,3 +241,5 @@ def test_country_calculation_BE(self):
         wrong_names = [series.name for series in wrong_series]
         res_wrong, exp_wrong = res.loc[wrong_names].copy(), exp.loc[wrong_names].copy()
         report_diff(res_wrong, exp_wrong)
+
+        #breakpoint()