From 3782adf10147913765a2562cae1b41cdf40a7b7e Mon Sep 17 00:00:00 2001
From: BaptisteDE <bdurandestebe@nobatek.inef4.com>
Date: Mon, 6 Oct 2025 17:13:06 +0200
Subject: [PATCH 1/4] =?UTF-8?q?=E2=9C=A8=20Sample=20=5F=5Frepr=5F=5F=20met?=
 =?UTF-8?q?hod?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 corrai/sampling.py     | 20 ++++++++++++++++++++
 tests/test_sampling.py | 15 +++++++++++++++
 2 files changed, 35 insertions(+)

diff --git a/corrai/sampling.py b/corrai/sampling.py
index 4f1c66f..ae4093d 100644
--- a/corrai/sampling.py
+++ b/corrai/sampling.py
@@ -133,6 +133,26 @@ class Sample:
     values: pd.DataFrame = field(init=False)
     results: pd.Series = field(default_factory=lambda: pd.Series(dtype=object))
 
+    def __repr__(self):
+        if not self.results.empty:
+            if not self.results[0].empty:
+                indicators_name = (
+                    self.results[0].columns
+                    if self.is_dynamic
+                    else self.results[0].index
+                )
+            else:
+                indicators_name = None
+        else:
+            indicators_name = None
+
+        return (
+            f"is dynamic: {self.is_dynamic} \n"
+            f"n computed sample: {len(self.results)} \n"
+            f"parameters: {[par.name for par in self.parameters]} \n"
+            f"indicators: {[None] if indicators_name is None else list(indicators_name)}"
+        )
+
     def __post_init__(self):
         self.values = pd.DataFrame(columns=[par.name for par in self.parameters])
 
diff --git a/tests/test_sampling.py b/tests/test_sampling.py
index 96ea613..787e245 100644
--- a/tests/test_sampling.py
+++ b/tests/test_sampling.py
@@ -48,6 +48,14 @@ class TestSample:
     def test_sample_methods(self):
         # Dynamic sample
         sample = Sample(REAL_PARAM)
+
+        assert sample.__repr__() == (
+            "is dynamic: True \n"
+            "n computed sample: 0 \n"
+            "parameters: ['param_1', 'param_2', 'param_3'] \n"
+            "indicators: [None]"
+        )
+
         assert sample.values.shape == (0, 3)
         pd.testing.assert_series_equal(sample.results, pd.Series())
 
@@ -168,6 +176,13 @@ def test_sample_methods(self):
             pd.DataFrame({"res": {0: np.nan, 1: 2.0}}),
         )
 
+        assert sample.__repr__() == (
+            "is dynamic: True \n"
+            "n computed sample: 2 \n"
+            "parameters: ['param_1', 'param_2', 'param_3'] \n"
+            "indicators: ['res']"
+        )
+
     def test_plot_sample(self):
         t = pd.date_range("2025-01-01 00:00:00", periods=2, freq="h")
         df1 = pd.DataFrame({"res": [1.0, 2.0]}, index=t)

From 9b3389907c41bfd381036f9ea07a3fe3a02c2732 Mon Sep 17 00:00:00 2001
From: BaptisteDE <bdurandestebe@nobatek.inef4.com>
Date: Mon, 6 Oct 2025 17:19:01 +0200
Subject: [PATCH 2/4] =?UTF-8?q?=F0=9F=92=A5=20renamed=20get=5Fscore=5Fdf?=
 =?UTF-8?q?=20method=20argument?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 corrai/sampling.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/corrai/sampling.py b/corrai/sampling.py
index ae4093d..f61c745 100644
--- a/corrai/sampling.py
+++ b/corrai/sampling.py
@@ -446,7 +446,7 @@ def get_score_df(
         reference_time_series: pd.Series,
         scoring_methods: list[str | Callable] = None,
         resample_rule: str | pd.Timedelta | dt.timedelta = None,
-        agg_method: str = "mean",
+        resample_agg_method: str = "mean",
     ) -> pd.DataFrame:
         """
         Compute scoring metrics for a given indicator across all sample results.
@@ -476,7 +476,7 @@ def get_score_df(
             Examples: ``"D"`` (daily), ``"h"`` (hourly), ``"ME"`` (month end).
             If None, no resampling is performed.
             Default is None.
-        agg_method : str, optional
+        resample_agg_method : str, optional
             Aggregation method to use when resampling. Common values include:
             ``"mean"``, ``"sum"``, ``"min"``, ``"max"``, ``"median"``.
             Default is ``"mean"``.
@@ -539,7 +539,7 @@ def get_score_df(
         ...     reference_time_series=reference,
         ...     scoring_methods=["r2", "rmse", "mae"],
         ...     resample_rule="D",
-        ...     agg_method="sum",
+        ...     resample_agg_method="sum",
         ... )
         >>> print(scores)
                   r2_score      rmse       mae
@@ -573,10 +573,10 @@ def get_score_df(
         for idx, sample_res in self.results.items():
             data = sample_res[indicator]
             if resample_rule:
-                data = data.resample(resample_rule).agg(agg_method)
+                data = data.resample(resample_rule).agg(resample_agg_method)
                 reference_time_series = reference_time_series.resample(
                     resample_rule
-                ).agg(agg_method)
+                ).agg(resample_agg_method)
 
             for method in method_func:
                 scores.loc[idx, method.__name__] = method(reference_time_series, data)

From ce876654bd653a97ba9285f6fdd8bc080365021b Mon Sep 17 00:00:00 2001
From: BaptisteDE <bdurandestebe@nobatek.inef4.com>
Date: Tue, 7 Oct 2025 15:03:54 +0200
Subject: [PATCH 3/4] =?UTF-8?q?=E2=99=BB=EF=B8=8F=20SampleMethodsMixin=20t?=
 =?UTF-8?q?o=20carry=20Sample=20method?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 corrai/optimize.py    |  83 ++---------------------
 corrai/sampling.py    | 151 ++++++++++++++++++++++++++----------------
 corrai/sensitivity.py | 101 ++--------------------------
 3 files changed, 105 insertions(+), 230 deletions(-)

diff --git a/corrai/optimize.py b/corrai/optimize.py
index 1b9a0ce..9674dd9 100644
--- a/corrai/optimize.py
+++ b/corrai/optimize.py
@@ -1,6 +1,5 @@
 from abc import ABC
 from typing import Callable
-from functools import wraps
 
 import numpy as np
 import pandas as pd
@@ -10,12 +9,10 @@
 from pymoo.core.problem import ElementwiseProblem
 from pymoo.core.variable import Integer, Real, Choice, Binary
 
-import plotly.graph_objects as go
-
 from corrai.base.math import METHODS
 from corrai.base.model import Model
 from corrai.base.utils import check_indicators_configs
-from corrai.sampling import Sample
+from corrai.sampling import Sample, SampleMethodsMixin
 from corrai.base.parameter import Parameter
 
 
@@ -577,7 +574,7 @@ def _evaluate(self, x, out, *args, **kwargs):
         self._post_evaluate(pairs, out)
 
 
-class SciOptimizer:
+class SciOptimizer(SampleMethodsMixin):
     """
     Optimization wrapper for models using SciPy.
 
@@ -635,6 +632,10 @@ def __init__(
     def parameters(self):
         return self.model_evaluator.parameters
 
+    @property
+    def sample(self):
+        return self.model_evaluator.sample
+
     @property
     def values(self):
         return self.model_evaluator.sample.values
@@ -787,75 +788,3 @@ def diff_evo_minimize(
             rng=rng,
             workers=workers,
         )
-
-    @wraps(Sample.plot_sample)
-    def plot_sample(
-        self,
-        indicator: str | None,
-        reference_timeseries: pd.Series | None = None,
-        title: str | None = None,
-        y_label: str | None = None,
-        x_label: str | None = None,
-        alpha: float = 0.5,
-        show_legends: bool = False,
-        round_ndigits: int = 2,
-        quantile_band: float = 0.75,
-        type_graph: str = "area",
-    ) -> go.Figure:
-        return self.model_evaluator.sample.plot_sample(
-            indicator=indicator,
-            reference_timeseries=reference_timeseries,
-            title=title,
-            y_label=y_label,
-            x_label=x_label,
-            alpha=alpha,
-            show_legends=show_legends,
-            round_ndigits=round_ndigits,
-            quantile_band=quantile_band,
-            type_graph=type_graph,
-        )
-
-    @wraps(Sample.plot_pcp)
-    def plot_pcp(
-        self,
-        indicators_configs: list[str]
-        | list[tuple[str, str | Callable] | tuple[str, str | Callable, pd.Series]],
-        color_by: str | None = None,
-        title: str | None = "Parallel Coordinates — Samples",
-        html_file_path: str | None = None,
-    ) -> go.Figure:
-        return self.model_evaluator.sample.plot_pcp(
-            indicators_configs=indicators_configs,
-            color_by=color_by,
-            title=title,
-            html_file_path=html_file_path,
-        )
-
-    @wraps(Sample.plot_hist)
-    def plot_hist(
-        self,
-        indicator: str,
-        method: str = "mean",
-        unit: str = "",
-        agg_method_kwarg: dict = None,
-        reference_time_series: pd.Series = None,
-        bins: int = 30,
-        colors: str = "orange",
-        reference_value: int | float = None,
-        reference_label: str = "Reference",
-        show_rug: bool = False,
-        title: str = None,
-    ):
-        return self.model_evaluator.sample.plot_hist(
-            indicator=indicator,
-            method=method,
-            unit=unit,
-            agg_method_kwarg=agg_method_kwarg,
-            reference_time_series=reference_time_series,
-            bins=bins,
-            colors=colors,
-            reference_value=reference_value,
-            reference_label=reference_label,
-            show_rug=show_rug,
-            title=title,
-        )
diff --git a/corrai/sampling.py b/corrai/sampling.py
index f61c745..610d08a 100644
--- a/corrai/sampling.py
+++ b/corrai/sampling.py
@@ -980,7 +980,99 @@ def plot_pcp(
         )
 
 
-class Sampler:
+class SampleMethodsMixin:
+    """Mixin to expose Sample plotting methods to classes that contain a Sample object."""
+
+    sample: Sample
+
+    @wraps(Sample.get_aggregated_time_series)
+    def get_sample_aggregated_time_series(
+        self,
+        indicator: str,
+        method: str = "mean",
+        agg_method_kwarg: dict = None,
+        reference_time_series: pd.Series = None,
+        freq: str | pd.Timedelta | dt.timedelta = None,
+        prefix: str = "aggregated",
+    ):
+        return self.sample.get_aggregated_time_series(
+            indicator, method, agg_method_kwarg, reference_time_series, freq, prefix
+        )
+
+    @wraps(Sample.plot_sample)
+    def plot_sample(
+        self,
+        indicator: str | None,
+        reference_timeseries: pd.Series | None = None,
+        title: str | None = None,
+        y_label: str | None = None,
+        x_label: str | None = None,
+        alpha: float = 0.5,
+        show_legends: bool = False,
+        round_ndigits: int = 2,
+        quantile_band: float = 0.75,
+        type_graph: str = "area",
+    ) -> go.Figure:
+        return self.sample.plot_sample(
+            indicator=indicator,
+            reference_timeseries=reference_timeseries,
+            title=title,
+            y_label=y_label,
+            x_label=x_label,
+            alpha=alpha,
+            show_legends=show_legends,
+            round_ndigits=round_ndigits,
+            quantile_band=quantile_band,
+            type_graph=type_graph,
+        )
+
+    @wraps(Sample.plot_pcp)
+    def plot_pcp(
+        self,
+        indicators_configs: list[str]
+        | list[tuple[str, str | Callable] | tuple[str, str | Callable, pd.Series]],
+        color_by: str | None = None,
+        title: str | None = "Parallel Coordinates — Samples",
+        html_file_path: str | None = None,
+    ) -> go.Figure:
+        return self.sample.plot_pcp(
+            indicators_configs=indicators_configs,
+            color_by=color_by,
+            title=title,
+            html_file_path=html_file_path,
+        )
+
+    @wraps(Sample.plot_hist)
+    def plot_hist(
+        self,
+        indicator: str,
+        method: str = "mean",
+        unit: str = "",
+        agg_method_kwarg: dict = None,
+        reference_time_series: pd.Series = None,
+        bins: int = 30,
+        colors: str = "orange",
+        reference_value: int | float = None,
+        reference_label: str = "Reference",
+        show_rug: bool = False,
+        title: str = None,
+    ):
+        return self.sample.plot_hist(
+            indicator,
+            method,
+            unit,
+            agg_method_kwarg,
+            reference_time_series,
+            bins,
+            colors,
+            reference_value,
+            reference_label,
+            show_rug,
+            title,
+        )
+
+
+class Sampler(SampleMethodsMixin):
     """
     Abstract base class for parameter samplers.
 
@@ -1180,63 +1272,6 @@ def simulate_pending(self, n_cpu: int = 1, simulation_kwargs: dict = None):
         unsimulated_idx = self.sample.get_pending_index()
         self.simulate_at(unsimulated_idx, n_cpu, simulation_kwargs)
 
-    @wraps(Sample.plot_sample)
-    def plot_sample(
-        self,
-        indicator: str | None,
-        reference_timeseries: pd.Series | None = None,
-        title: str | None = None,
-        y_label: str | None = None,
-        x_label: str | None = None,
-        alpha: float = 0.5,
-        show_legends: bool = False,
-        round_ndigits: int = 2,
-        quantile_band: float = 0.75,
-        type_graph: str = "area",
-    ) -> go.Figure:
-        return self.sample.plot_sample(
-            indicator=indicator,
-            reference_timeseries=reference_timeseries,
-            title=title,
-            y_label=y_label,
-            x_label=x_label,
-            alpha=alpha,
-            show_legends=show_legends,
-            round_ndigits=round_ndigits,
-            quantile_band=quantile_band,
-            type_graph=type_graph,
-        )
-
-    @wraps(Sample.get_aggregated_time_series)
-    def get_sample_aggregated_time_series(
-        self,
-        indicator: str,
-        method: str = "mean",
-        agg_method_kwarg: dict = None,
-        reference_time_series: pd.Series = None,
-        freq: str | pd.Timedelta | dt.timedelta = None,
-        prefix: str = "aggregated",
-    ):
-        return self.sample.get_aggregated_time_series(
-            indicator, method, agg_method_kwarg, reference_time_series, freq, prefix
-        )
-
-    @wraps(Sample.plot_pcp)
-    def plot_pcp(
-        self,
-        indicators_configs: list[str]
-        | list[tuple[str, str | Callable] | tuple[str, str | Callable, pd.Series]],
-        color_by: str | None = None,
-        title: str | None = "Parallel Coordinates — Samples",
-        html_file_path: str | None = None,
-    ) -> go.Figure:
-        return self.sample.plot_pcp(
-            indicators_configs=indicators_configs,
-            color_by=color_by,
-            title=title,
-            html_file_path=html_file_path,
-        )
-
 
 class RealSampler(Sampler):
     """
diff --git a/corrai/sensitivity.py b/corrai/sensitivity.py
index a68d53d..a61ce20 100644
--- a/corrai/sensitivity.py
+++ b/corrai/sensitivity.py
@@ -1,7 +1,5 @@
 import warnings
 from abc import ABC, abstractmethod
-from functools import wraps
-from typing import Callable
 
 import datetime as dt
 import numpy as np
@@ -10,7 +8,7 @@
 from SALib.analyze import morris, sobol, fast, rbd_fast
 from corrai.base.parameter import Parameter
 from corrai.sampling import (
-    Sample,
+    SampleMethodsMixin,
     SobolSampler,
     MorrisSampler,
     FASTSampler,
@@ -19,7 +17,7 @@
 from corrai.base.model import Model
 
 
-class Sanalysis(ABC):
+class Sanalysis(ABC, SampleMethodsMixin):
     """
     Abstract base class for Sensitivity Analysis workflows.
 
@@ -76,6 +74,10 @@ def __init__(
         self.analyser = self._set_analyser()
         self.x_needed = x_needed
 
+    @property
+    def sample(self):
+        return self.sampler.sample
+
     @property
     def parameters(self):
         return self.sampler.parameters
@@ -323,97 +325,6 @@ def salib_plot_dynamic_metric(
 
         return plot_dynamic_metric(metrics, sensitivity_metric, unit, title, stacked)
 
-    @wraps(Sample.get_aggregated_time_series)
-    def get_sample_aggregated_time_series(
-        self,
-        indicator: str,
-        method: str = "mean",
-        agg_method_kwarg: dict = None,
-        reference_time_series: pd.Series = None,
-        freq: str | pd.Timedelta | dt.timedelta = None,
-        prefix: str = "aggregated",
-    ) -> pd.DataFrame:
-        return self.sampler.sample.get_aggregated_time_series(
-            indicator,
-            method,
-            agg_method_kwarg,
-            reference_time_series,
-            freq,
-            prefix,
-        )
-
-    @wraps(Sample.plot_hist)
-    def plot_sample_hist(
-        self,
-        indicator: str,
-        method: str = "mean",
-        unit: str = "",
-        agg_method_kwarg: dict = None,
-        reference_time_series: pd.Series = None,
-        bins: int = 30,
-        colors: str = "orange",
-        reference_value: int | float = None,
-        reference_label: str = "Reference",
-        show_rug: bool = False,
-        title: str = None,
-    ):
-        return self.sampler.sample.plot_hist(
-            indicator=indicator,
-            method=method,
-            unit=unit,
-            agg_method_kwarg=agg_method_kwarg,
-            reference_time_series=reference_time_series,
-            bins=bins,
-            colors=colors,
-            reference_value=reference_value,
-            reference_label=reference_label,
-            show_rug=show_rug,
-            title=title,
-        )
-
-    @wraps(Sample.plot_sample)
-    def plot_sample(
-        self,
-        indicator: str | None,
-        reference_timeseries: pd.Series | None = None,
-        title: str | None = None,
-        y_label: str | None = None,
-        x_label: str | None = None,
-        alpha: float = 0.5,
-        show_legends: bool = False,
-        round_ndigits: int = 2,
-        quantile_band: float = 0.75,
-        type_graph: str = "area",
-    ) -> go.Figure:
-        return self.sampler.sample.plot_sample(
-            indicator=indicator,
-            reference_timeseries=reference_timeseries,
-            title=title,
-            y_label=y_label,
-            x_label=x_label,
-            alpha=alpha,
-            show_legends=show_legends,
-            round_ndigits=round_ndigits,
-            quantile_band=quantile_band,
-            type_graph=type_graph,
-        )
-
-    @wraps(Sample.plot_pcp)
-    def plot_pcp(
-        self,
-        indicators_configs: list[str]
-        | list[tuple[str, str | Callable] | tuple[str, str | Callable, pd.Series]],
-        color_by: str | None = None,
-        title: str | None = "Parallel Coordinates — Samples",
-        html_file_path: str | None = None,
-    ) -> go.Figure:
-        return self.sampler.sample.plot_pcp(
-            indicators_configs=indicators_configs,
-            color_by=color_by,
-            title=title,
-            html_file_path=html_file_path,
-        )
-
     def salib_plot_matrix(
         self,
         indicator: str,

From b95188b2fcb79ef04c6329f411396c68d57ac74b Mon Sep 17 00:00:00 2001
From: BaptisteDE <bdurandestebe@nobatek.inef4.com>
Date: Tue, 7 Oct 2025 16:37:21 +0200
Subject: [PATCH 4/4] =?UTF-8?q?=F0=9F=93=9D=20rtd=20updates=20!?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 docs/api_reference/base/math.rst            |  8 -----
 docs/api_reference/base/simulate.rst        |  6 ----
 docs/api_reference/base/utils.rst           |  8 -----
 docs/api_reference/index.rst                | 11 +++----
 docs/api_reference/{base => }/metrics.rst   |  0
 docs/api_reference/{base => }/model.rst     |  0
 docs/api_reference/optimize.rst             | 12 ++++++--
 docs/api_reference/{base => }/parameter.rst |  0
 docs/api_reference/sampling.rst             |  4 +++
 docs/api_reference/surrogate.rst            |  4 +++
 docs/index.rst                              | 33 +++++++--------------
 11 files changed, 33 insertions(+), 53 deletions(-)
 delete mode 100644 docs/api_reference/base/math.rst
 delete mode 100644 docs/api_reference/base/simulate.rst
 delete mode 100644 docs/api_reference/base/utils.rst
 rename docs/api_reference/{base => }/metrics.rst (100%)
 rename docs/api_reference/{base => }/model.rst (100%)
 rename docs/api_reference/{base => }/parameter.rst (100%)

diff --git a/docs/api_reference/base/math.rst b/docs/api_reference/base/math.rst
deleted file mode 100644
index 50834a1..0000000
--- a/docs/api_reference/base/math.rst
+++ /dev/null
@@ -1,8 +0,0 @@
-Math
-====
-
-The module provides convinient mathematical functions.
-
-.. automodule:: corrai.base.math
-   :members:
-   :show-inheritance:
diff --git a/docs/api_reference/base/simulate.rst b/docs/api_reference/base/simulate.rst
deleted file mode 100644
index 2d14c8f..0000000
--- a/docs/api_reference/base/simulate.rst
+++ /dev/null
@@ -1,6 +0,0 @@
-Simulate Module
-================
-
-.. automodule:: corrai.base.simulate
-   :members:
-   :show-inheritance:
diff --git a/docs/api_reference/base/utils.rst b/docs/api_reference/base/utils.rst
deleted file mode 100644
index 972ebd3..0000000
--- a/docs/api_reference/base/utils.rst
+++ /dev/null
@@ -1,8 +0,0 @@
-Utils Module
-================
-
-This module provides utility functions for data manipulation and transformation.
-
-.. automodule:: corrai.base.utils
-   :members:
-   :show-inheritance:
diff --git a/docs/api_reference/index.rst b/docs/api_reference/index.rst
index d3bc833..4c31015 100644
--- a/docs/api_reference/index.rst
+++ b/docs/api_reference/index.rst
@@ -5,14 +5,11 @@ API Reference
    :maxdepth: 3
    :caption: API Reference
 
-   base/parameter
-   base/model
-   base/simulate
+   parameter
+   model
    sampling
    sensitivity
-   fmu
    optimize
    surrogate
-   base/math
-   base/metrics
-   base/utils
+   fmu
+   metrics
diff --git a/docs/api_reference/base/metrics.rst b/docs/api_reference/metrics.rst
similarity index 100%
rename from docs/api_reference/base/metrics.rst
rename to docs/api_reference/metrics.rst
diff --git a/docs/api_reference/base/model.rst b/docs/api_reference/model.rst
similarity index 100%
rename from docs/api_reference/base/model.rst
rename to docs/api_reference/model.rst
diff --git a/docs/api_reference/optimize.rst b/docs/api_reference/optimize.rst
index e035539..b340eb3 100644
--- a/docs/api_reference/optimize.rst
+++ b/docs/api_reference/optimize.rst
@@ -1,10 +1,18 @@
 Optimize Module
 ==================
 
-.. autoclass:: corrai.optimize.Problem
+.. autoclass:: corrai.optimize.SciOptimizer
    :members:
    :show-inheritance:
 
-.. autoclass:: corrai.optimize.ObjectiveFunction
+.. autoclass:: corrai.optimize.ModelEvaluator
    :members:
    :show-inheritance:
+
+.. autoclass:: corrai.optimize.RealContinuousProblem
+   :members:
+   :show-inheritance:
+
+.. autoclass:: corrai.optimize.MixedProblem
+   :members:
+   :show-inheritance:
\ No newline at end of file
diff --git a/docs/api_reference/base/parameter.rst b/docs/api_reference/parameter.rst
similarity index 100%
rename from docs/api_reference/base/parameter.rst
rename to docs/api_reference/parameter.rst
diff --git a/docs/api_reference/sampling.rst b/docs/api_reference/sampling.rst
index 1355dbb..a83a112 100644
--- a/docs/api_reference/sampling.rst
+++ b/docs/api_reference/sampling.rst
@@ -9,6 +9,10 @@ Sampling Module
    :members:
    :show-inheritance:
 
+.. autoclass:: corrai.sampling.RealSampler
+   :members:
+   :show-inheritance:
+
 .. autoclass:: corrai.sampling.MorrisSampler
    :members:
    :show-inheritance:
diff --git a/docs/api_reference/surrogate.rst b/docs/api_reference/surrogate.rst
index 9750850..77e5848 100644
--- a/docs/api_reference/surrogate.rst
+++ b/docs/api_reference/surrogate.rst
@@ -8,3 +8,7 @@ Surrogate Module
 .. autoclass:: corrai.surrogate.MultiModelSO
    :members:
    :show-inheritance:
+
+.. autoclass:: corrai.surrogate.StaticScikitModel
+   :members:
+   :show-inheritance:
\ No newline at end of file
diff --git a/docs/index.rst b/docs/index.rst
index 32a7b0b..1a06b29 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -60,18 +60,10 @@ Quick Example
 
 .. code-block:: python
 
-    import pandas as pd
-
     from corrai.base.parameter import Parameter
-    from corrai.sensitivity import SobolSanalysis, MorrisSanalysis
+    from corrai.sensitivity import SobolSanalysis
     from corrai.base.model import Ishigami
 
-    SIMULATION_OPTIONS = {
-        "start": "2009-01-01 00:00:00",
-        "end": "2009-01-01 05:00:00",
-        "timestep": "h",
-    }
-
     PARAMETER_LIST = [
         Parameter("par_x1", (-3.14159265359, 3.14159265359), model_property="x1"),
         Parameter("par_x2", (-3.14159265359, 3.14159265359), model_property="x2"),
@@ -82,30 +74,27 @@ Quick Example
     sobol = SobolSanalysis(
         parameters=PARAMETER_LIST,
         model=Ishigami(),
-        simulation_options=SIMULATION_OPTIONS,
     )
 
     # Draw sample, and run simulations
-    sobol.add_sample(15**2, simulate=True, n_cpu=1, calc_second_order=True)
+    sobol.add_sample(2**10, simulate=True, n_cpu=1, calc_second_order=True)
 
-    # Corrai works for models that returns time series
-    # Ishigami model here will return the same value for the given parameters
-    # from START to END at 1h timestep
-    sobol.analyze('res', method="mean")["mean_res"]
+    # Corrai works for models that returns either time series or series
+    # depending on their static or dynamic nature
+    # Ishigami is a static model (see is_dynamic attribute)
+    sobol.analyze("res")
 
     # Default aggregation method is mean value of the timeseries
-    sobol.plot_bar('res')
+    sobol.plot_bar("res", sensitivity_metric="ST")
 
     # Display 2nd order matrix for parameters interaction
-    sobol.plot_s2_matrix('res')
+    sobol.plot_s2_matrix("res")
 
     # Display mean output values of the sample as hist
-    sobol.sampler.sample.plot_hist('res')
-
-    # Compute dynamic sensitivity analisys at plot
-    # Obviously, in this example indexes value do not vary
-    sobol.plot_dynamic_metric('res', sensitivity_metric="ST", freq="h")
+    sobol.sampler.sample.plot_hist("res")
 
+    # Display parallel coordinate plot
+    sobol.plot_pcp(["res"])
 
 
 .. toctree::