diff --git a/CHANGELOG.md b/CHANGELOG.md
index 8fa3c413..bfd72c1a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,13 @@
 # Changelog
 
+### 3.0.0 [#241](https://github.com/openfisca/openfisca-france-data/pull/241)
+- Breaking changes
+
+Adapte le dépôt au passage à openfisca-survey-manager 2.0.0 qui constitue une refactorisation de l'objet survey-scenario et des simulations qui sont dedans. Cela concerne donc les parties de ce dépôts qui héritent d'objets d'openfisca-survey-manager :
+- `openfisca_france_data/aggregates.py`
+- `openfisca_france_data/surveys.py`
+Les autres modifications sont des adaptions syntaxique mineurs du fait de cette adaptation
+
 ### 2.0.7 [#239](https://github.com/openfisca/openfisca-france-data/pull/239/files)
 * New features
 - Ajoute des nouveaux agrégats pour FranceAggregates
diff --git a/openfisca_france_data/__init__.py b/openfisca_france_data/__init__.py
index 81ef2499..43389933 100644
--- a/openfisca_france_data/__init__.py
+++ b/openfisca_france_data/__init__.py
@@ -1,10 +1,12 @@
 import inspect
+from importlib import metadata
 import logging
 import os
-import pkg_resources
 import pandas
+from pathlib import Path
 
 from openfisca_core import reforms  # type: ignore
+from openfisca_core.errors import VariableNameConflictError
 
 import openfisca_france  # type: ignore
 
@@ -13,6 +15,9 @@
 from openfisca_france_data.model.base import * # noqa  analysis:ignore
 
 
+openfisca_france_data_location = Path(__file__).parent.parent
+
+
 log = logging.getLogger(__name__)
 
 
@@ -141,7 +146,8 @@ def apply(self):
                 continue
             try:
                 self.add_variable(variable)
-            except AttributeError:
+            except VariableNameConflictError:
+                # log.debug(f"{variable.__name__} has been updated in openfisca-france-data")
                 self.update_variable(variable)
 
 
@@ -206,7 +212,7 @@ def apply(self):
 
 COUNTRY_DIR = os.path.dirname(os.path.abspath(__file__))
 DATA_DIR = os.path.join(
-    pkg_resources.get_distribution('openfisca-france-data').location,
+    openfisca_france_data_location,
     'openfisca_france_data',
     'plugins',
     'aggregates',
diff --git a/openfisca_france_data/aggregates.py b/openfisca_france_data/aggregates.py
index ae47df5d..f46a5ebc 100644
--- a/openfisca_france_data/aggregates.py
+++ b/openfisca_france_data/aggregates.py
@@ -3,14 +3,12 @@
 import json
 from pathlib import Path
 
-import numpy as np
-import pandas as pd
-import pkg_resources
 import os
 from datetime import datetime
+import pandas as pd
 
 from openfisca_survey_manager.aggregates import AbstractAggregates
-from openfisca_france_data import AGGREGATES_DEFAULT_VARS  # type: ignore
+from openfisca_france_data import openfisca_france_data_location, AGGREGATES_DEFAULT_VARS  # type: ignore
 
 
 log = logging.getLogger(__name__)
@@ -38,14 +36,14 @@ def __init__(self, survey_scenario = None, target_source = None):
         super().__init__(survey_scenario = survey_scenario)
         self.target_source = target_source
 
-    def load_actual_data(self, year = None):
+    def load_actual_data(self, period = None):
         target_source = self.target_source
         assert target_source in ["ines", "taxipp", "france_entiere"], "les options possible pour source_cible sont ines, taxipp ou france_entiere"
-        assert year is not None
+        assert period is not None
 
         if target_source == "taxipp":
             taxipp_aggregates_file = Path(
-                pkg_resources.get_distribution("openfisca-france_data").location,
+                openfisca_france_data_location,
                 "openfisca_france_data",
                 "assets",
                 "aggregats",
@@ -62,15 +60,15 @@ def load_actual_data(self, year = None):
                 .rename(columns = {"unnamed: 0": "description"})
                 .dropna(subset = ["annee 2019", "annee 2018", "annee 2017", "annee 2016"], how = "all")
                 )
-            if f"annee {year}" not in df:
+            if f"annee {period}" not in df:
                 return
 
             df = (
-                df[["variable_openfisca", f"annee {year}"]]
+                df[["variable_openfisca", f"annee {period}"]]
                 .dropna()
                 .rename(columns = {
                     "variable_openfisca": "variable",
-                    f"annee {year}": year,
+                    f"annee {period}": period,
                     })
                 )
 
@@ -78,25 +76,25 @@ def load_actual_data(self, year = None):
                 df.loc[df.variable.str.startswith("nombre")]
                 .set_index("variable")
                 .rename(index = lambda x : x.replace("nombre_", ""))
-                .rename(columns = {year: "actual_beneficiaries"})
+                .rename(columns = {period: "actual_beneficiaries"})
                 ) / self.beneficiaries_unit
 
             amounts = (
                 df.loc[~df.variable.str.startswith("nombre")]
                 .set_index("variable")
-                .rename(columns = {year: "actual_amount"})
+                .rename(columns = {period: "actual_amount"})
                 ) / self.amount_unit
 
             result = amounts.merge(beneficiaries, on = "variable", how = "outer").drop("PAS SIMULE")
 
         elif target_source == "ines":
             ines_aggregates_file = Path(
-                pkg_resources.get_distribution("openfisca-france_data").location,
+                openfisca_france_data_location,
                 "openfisca_france_data",
                 "assets",
                 "aggregats",
                 "ines",
-                f"ines_{year}.json"
+                f"ines_{period}.json"
                 )
 
             with open(ines_aggregates_file, 'r') as f:
@@ -110,12 +108,12 @@ def load_actual_data(self, year = None):
 
         elif target_source == "france_entiere":
             ines_aggregates_file = Path(
-                pkg_resources.get_distribution("openfisca-france_data").location,
+                openfisca_france_data_location,
                 "openfisca_france_data",
                 "assets",
                 "aggregats",
                 "france_entiere",
-                f"france_entiere_{year}.json"
+                f"france_entiere_{period}.json"
                 )
 
             with open(ines_aggregates_file, 'r') as f:
@@ -123,12 +121,16 @@ def load_actual_data(self, year = None):
 
             result = pd.DataFrame(data['data']).drop(['source'], axis = 1)
             result['actual_beneficiaries'] = result. actual_beneficiaries / self.beneficiaries_unit
-            result['actual_amount'] = result. actual_amount / self.amount_unit
+            result['actual_amount'] = result.actual_amount / self.amount_unit
 
-            result = result[["variable","actual_amount","actual_beneficiaries"]].set_index("variable")
+            result = result[[
+                "variable",
+                "actual_amount",
+                "actual_beneficiaries",
+                ]].set_index("variable")
 
         return result
-    
+
     def to_csv(self, path = None, absolute = True, amount = True, beneficiaries = True, default = 'actual',
             relative = True, target = "reform"):
         """Saves the table to csv."""
@@ -136,7 +138,7 @@ def to_csv(self, path = None, absolute = True, amount = True, beneficiaries = Tr
 
         if os.path.isdir(path):
             now = datetime.now()
-            file_path = os.path.join(path, 'Aggregates_%s_%s_%s.%s' % (self.target_source,self.year,now.strftime('%d-%m-%Y'), "csv"))
+            file_path = os.path.join(path, 'Aggregates_%s_%s_%s.%s' % (self.target_source, self.period, now.strftime('%d-%m-%Y'), "csv"))
         else:
             file_path = path
 
diff --git a/openfisca_france_data/erfs/input_data_builder/step_08_final.py b/openfisca_france_data/erfs/input_data_builder/step_08_final.py
index 3ff828a7..4f7c160c 100644
--- a/openfisca_france_data/erfs/input_data_builder/step_08_final.py
+++ b/openfisca_france_data/erfs/input_data_builder/step_08_final.py
@@ -10,6 +10,7 @@
 
 
 from openfisca_survey_manager.temporary import temporary_store_decorator
+from openfisca_france_data import openfisca_france_data_location
 from openfisca_france_data.utils import (
     check_structure,
     control,
@@ -20,6 +21,7 @@
     set_variables_default_value,
     )
 
+
 log = logging.getLogger(__name__)
 
 
@@ -202,8 +204,6 @@ def final(temporary_store = None, year = None, check = True):
     print_id(final2)
 # # TODO: merging with patrimoine
     log.info('    traitement des zones apl')
-    import pkg_resources
-    openfisca_france_data_location = pkg_resources.get_distribution('openfisca-france-data').location
     zone_apl_imputation_data_file_path = os.path.join(
         openfisca_france_data_location,
         'openfisca_france_data',
diff --git a/openfisca_france_data/erfs/old/datatable.py b/openfisca_france_data/erfs/old/datatable.py
index b2eac78b..3de1bee4 100644
--- a/openfisca_france_data/erfs/old/datatable.py
+++ b/openfisca_france_data/erfs/old/datatable.py
@@ -1,5 +1,4 @@
 import os
-import pkg_resources
 import sys
 import gc
 
@@ -18,8 +17,9 @@
 
 #from openfisca_france.data.sources.config import DATA_DIR
 
-openfisca_france_location = pkg_resources.get_distribution('openfisca-france-data').location
-CONFIG_DIR = os.path.join(openfisca_france_location)
+from openfisca_france_data import openfisca_france_data_location
+
+CONFIG_DIR = os.path.join(openfisca_france_data_location)
 
 #ERF_HDF5_DATA_DIR = os.path.join(SRC_PATH,'countries','france','data', 'erf')
 
diff --git a/openfisca_france_data/erfs/scenario.py b/openfisca_france_data/erfs/scenario.py
index 46ad488b..d3d6148a 100644
--- a/openfisca_france_data/erfs/scenario.py
+++ b/openfisca_france_data/erfs/scenario.py
@@ -41,5 +41,5 @@ class ErfsSurveyScenario(AbstractErfsSurveyScenario):
         'zone_apl',
         ]
 
-    def __init__(self, year: int) -> None:
-        self.year = year
+    def __init__(self, period: int) -> None:
+        self.period = period
diff --git a/openfisca_france_data/erfs_fpr/get_survey_scenario.py b/openfisca_france_data/erfs_fpr/get_survey_scenario.py
index 448467fc..ed626143 100644
--- a/openfisca_france_data/erfs_fpr/get_survey_scenario.py
+++ b/openfisca_france_data/erfs_fpr/get_survey_scenario.py
@@ -10,6 +10,7 @@
 from openfisca_france_data.erfs_fpr.scenario import ErfsFprSurveyScenario
 from openfisca_france_data import france_data_tax_benefit_system
 
+from openfisca_survey_manager import default_config_files_directory
 
 from openfisca_france_data.model.id_variables import (
     idmen_original,
@@ -102,6 +103,7 @@ def get_survey_scenario(
         variation_factor: float = 0.03,
         varying_variable: str = None,
         survey_name: str = "input",
+        config_files_directory : str = default_config_files_directory,
         ) -> ErfsFprSurveyScenario:
     """Helper pour créer un `ErfsFprSurveyScenario`.
 
@@ -126,14 +128,14 @@ def get_survey_scenario(
         survey_scenario = ErfsFprSurveyScenario.create(
             tax_benefit_system = tax_benefit_system,
             baseline_tax_benefit_system = baseline_tax_benefit_system,
-            year = year,
+            period = year,
             )
     else:
         assert varying_variable is not None, "You need to specify the varying variable."
         survey_scenario = ErfsFprSurveyScenario.create(
             tax_benefit_system = tax_benefit_system,
             baseline_tax_benefit_system = baseline_tax_benefit_system,
-            year = year,
+            period = year,
             )
         # taux marginaux !!
         survey_scenario.variation_factor = variation_factor
@@ -153,6 +155,8 @@ def get_survey_scenario(
             input_data_table_by_entity_by_period = input_data_table_by_entity_by_period,
             survey = survey_name
             )
+        data["config_files_directory"] = config_files_directory
+        
 
     # Les données peuvent venir en différents formats :
     #
diff --git a/openfisca_france_data/erfs_fpr/scenario.py b/openfisca_france_data/erfs_fpr/scenario.py
index 7e9711d3..eef10cd5 100644
--- a/openfisca_france_data/erfs_fpr/scenario.py
+++ b/openfisca_france_data/erfs_fpr/scenario.py
@@ -63,8 +63,9 @@ class ErfsFprSurveyScenario(AbstractErfsSurveyScenario):
         "wprm_init",
         ]
 
-    def __init__(self, year: int) -> None:
-        self.year = year
+    def __init__(self, period: int) -> None:
+        # self.year = period
+        self.period = period
 
     @classmethod
     def build_input_data(cls, year: int) -> None:
diff --git a/openfisca_france_data/model/common.py b/openfisca_france_data/model/common.py
index 13049ba8..c798e5f8 100644
--- a/openfisca_france_data/model/common.py
+++ b/openfisca_france_data/model/common.py
@@ -190,10 +190,10 @@ def formula(foyer_fiscal, period):
         weight_foyers = foyer_fiscal('weight_foyers', period)
         menage_ordinaire_foyers_fiscaux = foyer_fiscal('menage_ordinaire_foyers_fiscaux', period)
         labels = arange(1, 11)
+        method = 2
+        decile, values = mark_weighted_percentiles(rfr, labels, weight_foyers * menage_ordinaire_foyers_fiscaux, method, return_quantiles = True)
         # Alternative method
-        # method = 2
-        # decile, values = mark_weighted_percentiles(niveau_de_vie, labels, pondmen, method, return_quantiles = True)
-        decile, values = weighted_quantiles(rfr, labels, weight_foyers * menage_ordinaire_foyers_fiscaux, return_quantiles = True)
+        # decile, values = weighted_quantiles(rfr, labels, weight_foyers * menage_ordinaire_foyers_fiscaux, return_quantiles = True)
         return decile
 
 
@@ -228,11 +228,9 @@ def formula(foyer_fiscal, period):
         weight_foyers = foyer_fiscal('weight_foyers', period)
         menage_ordinaire_foyers_fiscaux = foyer_fiscal('menage_ordinaire_foyers_fiscaux', period)
         labels = arange(1, 11)
-        # Alternative method
-        # method = 2
-        # decile, values = mark_weighted_percentiles(niveau_de_vie, labels, pondmen, method, return_quantiles = True)
-        decile, values = weighted_quantiles(
-            rfr / nbptr, labels, weight_foyers * menage_ordinaire_foyers_fiscaux, return_quantiles = True)
+        method = 2
+        decile, values = mark_weighted_percentiles(
+            rfr / nbptr, labels, weight_foyers * menage_ordinaire_foyers_fiscaux, method, return_quantiles = True)
         return decile
 
 
diff --git a/openfisca_france_data/model/survey_variables.py b/openfisca_france_data/model/survey_variables.py
index e9cde28c..16ef928b 100644
--- a/openfisca_france_data/model/survey_variables.py
+++ b/openfisca_france_data/model/survey_variables.py
@@ -4,7 +4,7 @@
 class menage_ordinaire(Variable):
     value_type = int
     is_period_size_independent = True
-    default_value = True
+    default_value = 1
     entity = Menage
     definition_period = YEAR
 
diff --git a/openfisca_france_data/surveys.py b/openfisca_france_data/surveys.py
index a595570d..32e9b156 100644
--- a/openfisca_france_data/surveys.py
+++ b/openfisca_france_data/surveys.py
@@ -7,12 +7,13 @@
 from openfisca_core.model_api import Enum  # type: ignore
 from openfisca_core.taxbenefitsystems import TaxBenefitSystem  # type: ignore
 from openfisca_france_data import base_survey as base  # type: ignore
-from openfisca_survey_manager.scenarios import AbstractSurveyScenario  # type: ignore
+from openfisca_survey_manager.scenarios.reform_scenario import ReformScenario  # type: ignore
+
 
 log = logging.getLogger(__name__)
 
 
-class AbstractErfsSurveyScenario(AbstractSurveyScenario):
+class AbstractErfsSurveyScenario(ReformScenario):
     """
     Parties communes entre ERFS et ERFS PFR
 
@@ -61,7 +62,7 @@ def build_input_data_from_test_case(self, test_case_scenario):
             )
 
         array_by_variable = dict()
-        period = periods.period(str(self.year))
+        period = periods.period(str(self.period))
 
         for variable in self.used_as_input_variables:
             array_by_variable[variable] = simulation.calculate_add(
@@ -87,10 +88,10 @@ def create(
             input_data_type = None,
             reform = None,
             reform_key = None,
-            year: int = None,
+            period: int = None,
             ):
 
-        assert year is not None
+        assert period is not None
         assert not ((reform is not None) and (reform_key is not None))
 
         reform_is_provided = (reform is not None) or (reform_key is not None)
@@ -111,18 +112,22 @@ def create(
             tax_benefit_system = reform
 
         if input_data_type is not None:
-            survey_scenario = cls(input_data_type = input_data_type, year = year)
+            survey_scenario = cls(input_data_type = input_data_type, period = period)
 
         else:
-            survey_scenario = cls(year = year)
+            survey_scenario = cls(period = period)
 
-        survey_scenario.set_tax_benefit_systems(
-            tax_benefit_system = tax_benefit_system,
-            baseline_tax_benefit_system = baseline_tax_benefit_system,
-            )
+        if baseline_tax_benefit_system:
+            survey_scenario.set_tax_benefit_systems(dict(
+                reform = tax_benefit_system,
+                baseline = baseline_tax_benefit_system,
+                ))
+        else:
+            survey_scenario.set_tax_benefit_systems(dict(
+                baseline = tax_benefit_system,
+                ))
 
-        survey_scenario.year = year
-        survey_scenario.period = year
+        survey_scenario.period = period
 
         return survey_scenario
 
@@ -155,22 +160,22 @@ def custom_initialize(self, simulation):
             # 'chomage_brut',
             ]
 
-        three_year_span_variables = input_variables + computed_variables_used_as_input
+        three_period_span_variables = input_variables + computed_variables_used_as_input
 
-        simulation_period = periods.period(self.year)
-        for variable in three_year_span_variables:
+        simulation_period = periods.period(self.period)
+        for variable in three_period_span_variables:
             assert variable in self.used_as_input_variables, \
                 f"{variable} is not a in the input_varaibles to be used {self.used_as_input_variables}"  # noqa: E501
 
-            if self.tax_benefit_system.variables[variable].value_type == Enum:
+            if simulation.tax_benefit_system.variables[variable].value_type == Enum:
                 permanent_value = simulation.calculate(
                     variable,
-                    period = periods.period(self.year).first_month,
+                    period = periods.period(self.period).first_month,
                     )
             else:
                 permanent_value = simulation.calculate_add(
                     variable,
-                    period = self.year,
+                    period = self.period,
                     )
 
             for offset in [-1, -2]:
@@ -183,7 +188,6 @@ def custom_initialize(self, simulation):
                 except ValueError as e:
                     log.debug(f"Dealing with: {e}")
                     if sum(simulation.calculate_add(variable, simulation_period.offset(offset))) != sum(permanent_value):
-                        use_baseline = self.baseline_simulation == simulation
                         simulation.delete_arrays(variable, simulation_period.offset(offset))
                         simulation.set_input(
                             variable,
diff --git a/setup.py b/setup.py
index 47c9ea66..a49ead52 100644
--- a/setup.py
+++ b/setup.py
@@ -6,7 +6,7 @@
 
 setup(
     name = "OpenFisca-France-Data",
-    version = "2.0.7",
+    version = "3.0.0",
     description = "OpenFisca-France-Data module to work with French survey data",
     long_description = long_description,
     long_description_content_type="text/markdown",
@@ -42,9 +42,8 @@
     python_requires = ">=3.9",
     install_requires = [
         "multipledispatch >=0.6.0, <1.0.0",
-        "OpenFisca-France >=150.0.0, <154.0.0",
-        "openFisca-survey-manager >=1, <2.0.0",
-        "wquantiles >=0.3.0, <1.0.0",  # To compute weighted quantiles
+        "OpenFisca-France >=150.0.0, <155.0.0",
+        "openFisca-survey-manager >=2.0.0, <2.1.0",
         ],
     extras_require = {
         "test": [
diff --git a/tests/conftest.py b/tests/conftest.py
index 1b6cc218..933e6350 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -35,7 +35,7 @@ def survey_scenario(tax_benefit_system: TaxBenefitSystem):
     def _survey_scenario(year: int) -> ErfsFprSurveyScenario:
         return ErfsFprSurveyScenario.create(
             tax_benefit_system = tax_benefit_system,
-            year = year,
+            period = year,
             )
 
     return _survey_scenario
diff --git a/tests/erfs_fpr/integration/test_pivot_table.py b/tests/erfs_fpr/integration/test_pivot_table.py
index 4ba92652..81b0bc04 100644
--- a/tests/erfs_fpr/integration/test_pivot_table.py
+++ b/tests/erfs_fpr/integration/test_pivot_table.py
@@ -60,4 +60,4 @@ def get_survey_scenario(kind = 'erfs_fpr', year = None):
         year = 2009
         SurveyScenario = ErfsSurveyScenario
 
-    return SurveyScenario.create(year = year)
+    return SurveyScenario.create(period = year)
diff --git a/tests/test_aggregate.py b/tests/test_aggregate.py
index 61adb5a4..1e6d3fc0 100644
--- a/tests/test_aggregate.py
+++ b/tests/test_aggregate.py
@@ -8,12 +8,13 @@
     )
 
 
-@pytest.mark.skip(
-    reason = "FileNotFoundError: [Errno 2] No such file or directory: '/opt/hostedtoolcache/Python/3.9.9/x64/lib/python3.9/site-packages/openfisca_france_data/assets/agregats_tests_taxipp_2_0.xlsx'",
-    )
 def test_erfs_survey_simulation(survey_scenario, fake_input_data, year: int = 2009):
     # On ititialise le survey scenario
-    survey_scenario = ErfsFprSurveyScenario.create(year)
+    survey_scenario = ErfsFprSurveyScenario.create(
+        tax_benefit_system = france_data_tax_benefit_system,
+
+        period = year,
+        )
 
     # On charge les données
     input_data = fake_input_data(year)
@@ -23,16 +24,13 @@ def test_erfs_survey_simulation(survey_scenario, fake_input_data, year: int = 20
 
     # On calcule les agrégats
     aggregates = Aggregates(survey_scenario = survey_scenario, target_source = 'taxipp')
-    aggregates.compute_aggregates(use_baseline = False)
+    aggregates.compute_aggregates()
     return aggregates.base_data_frame
 
 
-@pytest.mark.skip(
-    reason = "FileNotFoundError: [Errno 2] No such file or directory: '/opt/hostedtoolcache/Python/3.9.9/x64/lib/python3.9/site-packages/openfisca_france_data/assets/agregats_tests_taxipp_2_0.xlsx'",
-    )
 def test_erfs_fpr_aggregates_reform(fake_input_data, year:int = 2013):
     survey_scenario = ErfsFprSurveyScenario.create(
-        year = year,
+        period = year,
         reform_key = 'plf2015',
         baseline_tax_benefit_system = france_data_tax_benefit_system,
         )
diff --git a/tests/test_calibration.py b/tests/test_calibration.py
index c56f0308..a9293435 100644
--- a/tests/test_calibration.py
+++ b/tests/test_calibration.py
@@ -1,14 +1,16 @@
-import pkg_resources
 import os
 
 import pytest
 
 from openfisca_survey_manager.calibration import Calibration  # type: ignore
+from openfisca_france_data import openfisca_france_data_location
+
+
 
 
 @pytest.fixture
 def location() -> str:
-    return pkg_resources.get_distribution("openfisca-france-data").location
+    return openfisca_france_data_location
 
 
 def test_calibration(survey_scenario, fake_input_data, location, year: int = 2009):
@@ -22,16 +24,14 @@ def test_calibration(survey_scenario, fake_input_data, location, year: int = 200
     survey_scenario.init_from_data(data = dict(input_data_frame = input_data))
 
     # On fait la calibration
-    calibration = Calibration(survey_scenario)
-    calibration.parameters["method"] = "linear"
-    calibration.total_population = calibration.initial_total_population * 1.123
-
-    calibration.set_parameters("invlo", 3)
-    calibration.set_parameters("up", 3)
-    calibration.set_parameters("method", "logit")
+    parameters = dict(
+        method = "logit",
+        invlo = 3,
+        up = 3,
+        )
 
-    calibration.calibrate()
     pre_cal_weight = survey_scenario.calculate_variable("wprm", period = year)
-    calibration.set_calibrated_weights()
-    assert pre_cal_weight * 1.123 == survey_scenario.calculate_variable("wprm", period = year)
+    target_entity_count = pre_cal_weight.sum() * 1.123
+    survey_scenario.calibrate(target_entity_count = target_entity_count, entity = "menage", parameters = parameters, period = year)
 
+    assert pre_cal_weight * 1.123 == survey_scenario.calculate_variable("wprm", period = year)
diff --git a/tests/test_fake_survey_simulation.py b/tests/test_fake_survey_simulation.py
index 47694fcf..9eacf4d0 100644
--- a/tests/test_fake_survey_simulation.py
+++ b/tests/test_fake_survey_simulation.py
@@ -10,29 +10,13 @@
 from openfisca_france_data.reforms.old_openfisca_france_reforms.plf2015 import plf2015  # type: ignore
 
 
-@pytest.fixture
-def fake_calibration(tax_benefit_system):
-    def _fake_calibration(fake_input_data: pandas.DataFrame, year: int) -> Calibration:
-        input_data_frame = fake_input_data(year)
-
-        survey_scenario = ErfsSurveyScenario.create(
-            tax_benefit_system = tax_benefit_system,
-            year = year,
-            )
-
-        survey_scenario.init_from_data(data = dict(input_data_frame = input_data_frame))
-
-        calibration = Calibration(survey_scenario = survey_scenario, period = year)
-        calibration.set_parameters("invlo", 3)
-        calibration.set_parameters("up", 3)
-        calibration.set_parameters("method", "logit")
-
-        return calibration
-
-    return _fake_calibration
+parameters = dict(
+    invlo = 3,
+    up = 3,
+    method = "logit",
+    )
 
 
-@pytest.mark.skip(reason = "AssertionError: [0. 0.] != [20000. 10000.]")
 def test_fake_survey_simulation(tax_benefit_system, fake_input_data, year: int = 2006):
     input_data_frame = fake_input_data(year)
     assert input_data_frame.salaire_imposable.loc[0] == 20000
@@ -40,7 +24,7 @@ def test_fake_survey_simulation(tax_benefit_system, fake_input_data, year: int =
 
     survey_scenario = ErfsSurveyScenario.create(
         tax_benefit_system = tax_benefit_system,
-        year = year,
+        period = year,
         )
 
     survey_scenario.init_from_data(data = dict(input_data_frame = input_data_frame))
@@ -48,7 +32,7 @@ def test_fake_survey_simulation(tax_benefit_system, fake_input_data, year: int =
     assert (input_data_frame.salaire_imposable.loc[0] == 20000).all()
     assert (input_data_frame.salaire_imposable.loc[1] == 10000).all()
 
-    simulation = survey_scenario.simulation
+    simulation = survey_scenario.simulations["baseline"]
 
     salaire_imposable = simulation.calculate_add("salaire_imposable", period = year)
 
@@ -60,29 +44,34 @@ def test_fake_survey_simulation(tax_benefit_system, fake_input_data, year: int =
     assert age[0] == 77
     assert age[1] == 37
 
-    sal_2003 = simulation.calculate_add("salaire_imposable", period = 2003)
-    sal_2004 = simulation.calculate_add("salaire_imposable", period = 2004)
-    sal_2005 = simulation.calculate_add("salaire_imposable", period = 2005)
-    sal_2006 = simulation.calculate_add("salaire_imposable", period = 2006)
+    retraite_2003 = simulation.calculate_add("retraite_imposable", period = 2003)
+    retraite_2004 = simulation.calculate_add("retraite_imposable", period = 2004)
+    retraite_2005 = simulation.calculate_add("retraite_imposable", period = 2005)
+    retraite_2006 = simulation.calculate_add("retraite_imposable", period = 2006)
 
-    assert (sal_2003 == 0).all()
-    assert (sal_2004 == sal_2006).all()
-    assert (sal_2005 == sal_2006).all()
+    assert (retraite_2003 == 0).all()
+    assert (retraite_2004 == retraite_2006).all()
+    assert (retraite_2005 == retraite_2006).all()
 
     for year, month in itertools.product(range(2003, 2004), range(1, 13)):
-        period = f"{year}-{month}"
+        if month < 10:
+            period = f"{year}-0{month}"
+        else:
+            period = f"{year}-{month}"
 
         assert (
             simulation
-            .calculate_add("salaire_imposable", period = period) == 0
+            .calculate_add("retraite_imposable", period = period) == 0
             ).all()
 
     for year, month in itertools.product(range(2004, 2007), range(1, 13)):
-        period = f"{year}-{month}"
+        if month < 10:
+            period = f"{year}-0{month}"
+        else:
+            period = f"{year}-{month}"
 
         assert (
-            simulation
-            .calculate("salaire_imposable", period = period) == sal_2006 / 12
+            simulation.calculate("retraite_imposable", period = period) == retraite_2006 / 12
             ).all()
 
     data_frame_by_entity = survey_scenario.create_data_frame_by_entity(
@@ -91,6 +80,7 @@ def test_fake_survey_simulation(tax_benefit_system, fake_input_data, year: int =
             "activite",
             "rsa_base_ressources_i",
             "menage_ordinaire_individus",
+            "retraite_imposable",
             "salaire_imposable",
             "salaire_net",
             "autonomie_financiere",
@@ -106,66 +96,84 @@ def test_fake_survey_simulation(tax_benefit_system, fake_input_data, year: int =
             "weight_familles",
             "revenu_disponible",
             "impo",
-            ]
+            ],
         )
-
     return data_frame_by_entity, simulation
 
 
-@pytest.mark.skip(
-    reason = "AttributeError: 'Calibration' object has no attribute 'simulation'",
-    )
-def test_fake_calibration_float(fake_calibration, year: int = 2006):
-    calibration = fake_calibration(year)
-    calibration.total_population = calibration.initial_total_population * 1.123
+def test_fake_calibration_float(tax_benefit_system, fake_input_data, year: int = 2006):
+    input_data_frame = fake_input_data(year)
+    survey_scenario = ErfsSurveyScenario.create(
+        tax_benefit_system = tax_benefit_system,
+        period = year,
+        )
+    survey_scenario.init_from_data(data = dict(input_data_frame = input_data_frame))
 
-    revenu_disponible_target = 7e6
-    calibration.set_target_margin("revenu_disponible", revenu_disponible_target)
-    calibration.calibrate()
-    calibration.set_calibrated_weights()
+    initial_count = survey_scenario.compute_aggregate("revenu_disponible", aggfunc = "count", period = year)
+    target_entity_count = initial_count * 1.123
 
-    simulation = calibration.survey_scenario.simulation
+    revenu_disponible_target = 7.7e6
+    target_margins_by_variable = dict(revenu_disponible = revenu_disponible_target)
+
+    survey_scenario.calibrate(
+        period = year,
+        target_margins_by_variable = target_margins_by_variable,
+        target_entity_count = target_entity_count,
+        parameters=parameters,
+        )
 
     assert_near(
-        simulation.calculate("wprm", period=year).sum(),
-        calibration.total_population,
+        survey_scenario.calculate_variable("wprm", period=year).sum(),
+        target_entity_count,
         absolute_error_margin = None,
         relative_error_margin = 0.00001,
         )
 
     assert_near(
         (
-            + simulation.calculate("revenu_disponible", period = year)
-            * simulation.calculate("wprm", period = year)
+            + survey_scenario.calculate_variable("revenu_disponible", period = year)
+            * survey_scenario.calculate_variable("wprm", period = year)
             ).sum(),
         revenu_disponible_target,
         absolute_error_margin = None,
         relative_error_margin = 0.00001,
         )
 
-
 @pytest.mark.skip(
-    reason = "ValueError: Length of values does not match length of index",
+    reason = "ValueError: Unable to compute variable 'age' for period 2006: 'age' must be computed for a whole month. Should use an ge with year definition period",
     )
-def test_fake_calibration_age(fake_calibration, fake_input_data, year: int = 2006):
-    calibration = fake_calibration(fake_input_data, year)
-    survey_scenario = calibration.survey_scenario
-    calibration.total_population = calibration.initial_total_population * 1.123
-    calibration.set_target_margin("age", [95, 130])
-    calibration.calibrate()
-    calibration.set_calibrated_weights()
+def test_fake_calibration_age(tax_benefit_system, fake_input_data, year: int = 2006):
+    input_data_frame = fake_input_data(year)
+    period = year
+    survey_scenario = ErfsSurveyScenario.create(
+        tax_benefit_system = tax_benefit_system,
+        period = period,
+        )
+    survey_scenario.init_from_data(data = dict(input_data_frame = input_data_frame))
 
-    simulation = survey_scenario.simulation
+    initial_count = survey_scenario.compute_aggregate("wprm", aggfunc = "count", period = year)
+    target_entity_count = initial_count * 1.123
+
+    target_margins_by_variable = {
+        "age": [95, 130]
+        }
+
+    survey_scenario.calibrate(
+        period = period,
+        target_margins_by_variable = target_margins_by_variable,
+        target_entity_count = target_entity_count,
+        parameters=parameters,
+        )
 
     assert_near(
-        simulation.calculate("wprm").sum(),
-        calibration.total_population,
+        survey_scenario.calculate_variable("wprm", period=period).sum(),
+        target_entity_count,
         absolute_error_margin = None,
         relative_error_margin = 0.00001,
         )
 
-    age = (survey_scenario.simulation.calculate("age"),)
-    weight_individus = survey_scenario.simulation.calculate("weight_individus")
+    age = survey_scenario.calculate_variable("age", period = period)
+    weight_individus = survey_scenario.calculate_variable("weight_individus", period = year)
 
     for category, target in calibration.margins_by_variable["age"]["target"].items():
         actual = ((age == category) * weight_individus).sum() / weight_individus.sum()
@@ -197,7 +205,7 @@ def test_calculate_irpp_before_and_after_plf2015(
     survey_scenario = ErfsSurveyScenario.create(
         tax_benefit_system = reform,
         baseline_tax_benefit_system = tax_benefit_system,
-        year = year,
+        period = year,
         )
 
     # On charge les données