Plotter inside class so it does not generate every time a function is…

… called

garpar/optimize.py

@@ -177,6 +177,14 @@ def _get_optimizer(self, pf):
             weight_bounds=weight_bounds,
         )
         return optimizer
+
+    def _get_market_neutral(self):
+        """Get the market_neutral parameter."""
+        return self.market_neutral
+
+    def _get_method(self):
+        """Get current optimization method"""
+        return this.method
 
     def __calculate_weights_by_risk(self, pf):
         """Calculate weights based on the risk of the portfolio.
@@ -256,9 +264,10 @@ def __calculate_weights_general(self, pf):
             A tuple containing the optimal weights and optimizer metadata.
         """
         optimizer = self._get_optimizer(pf)
+        market_neutral = self._get_market_neutral()
         # market_neutral = self.market_neutral FIXME comentario pasarlo a acc
 
-        weights_dict = getattr(optimizer, self.method)()  # TODO Pasarlo a acc
+        weights_dict = getattr(optimizer, self._get_method())()  # TODO Pasarlo a acc
         weights = [weights_dict[stock] for stock in pf.stocks]
 
         optimizer_metadata = {
@@ -358,7 +367,8 @@ def _calculate_weights(self, pf):
         """
         optimizer = self._get_optimizer(pf)
         target_return = self._coerce_target_return(pf)
-        market_neutral = self.market_neutral
+        market_neutral = self._get_market_neutral()
+        # market_neutral = self.market_neutral
 
         weights_dict = optimizer.efficient_return(
             target_return, market_neutral=market_neutral

tests/core/test_plot_acc.py

@@ -5,7 +5,6 @@
 # License: MIT
 #   Full Text: https://github.com/quatrope/garpar/blob/master/LICENSE
 
-# TODO: Meter en una clase para no crear todo el tiempo el plotter
 
 from garpar.core.plot_acc import PortfolioPlotter
 
@@ -15,189 +14,134 @@
 
 import seaborn as sns
 
-
-@check_figures_equal()
-@pytest.mark.parametrize("returns", [True, False])
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_line(
-    fig_test, fig_ref, risso_portfolio, returns, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.line(returns=returns, ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._ddf(returns=returns)
-    ax_ref = sns.lineplot(data=data)
-    ax_ref.set_title(title)
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("returns", [True, False])
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_heatmap(
-    fig_test, fig_ref, risso_portfolio, returns, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.heatmap(returns=returns, ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._ddf(returns=returns)
-    ax_ref = sns.heatmap(data=data)
-    ax_ref.set_title(title)
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_wheatmap(
-    fig_test, fig_ref, risso_portfolio, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.wheatmap(ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._wdf()
-    ax_ref = sns.heatmap(data=data.T)
-    ax_ref.set_title(title)
-    ax_ref.set_xlabel("Stocks")
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("returns", [True, False])
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_hist(
-    fig_test, fig_ref, risso_portfolio, returns, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.hist(returns=returns, ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._ddf(returns=returns)
-    ax_ref = sns.histplot(data=data)
-    ax_ref.set_title(title)
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_whist(
-    fig_test, fig_ref, risso_portfolio, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.whist(ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._wdf()
-    ax_ref = sns.histplot(data=data.T)
-    ax_ref.set_title(title)
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("returns", [True, False])
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_box(
-    fig_test, fig_ref, risso_portfolio, returns, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.box(returns=returns, ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._ddf(returns=returns)
-    ax_ref = sns.boxplot(data=data)
-    ax_ref.set_title(title)
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_wbox(
-    fig_test, fig_ref, risso_portfolio, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.wbox(ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._wdf()
-    ax_ref = sns.boxplot(data=data)
-    ax_ref.set_title(title)
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("returns", [True, False])
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_kde(
-    fig_test, fig_ref, risso_portfolio, returns, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.kde(returns=returns, ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._ddf(returns=returns)
-    ax_ref = sns.kdeplot(data=data)
-    ax_ref.set_title(title)
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_wkde(
-    fig_test, fig_ref, risso_portfolio, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.wkde(ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._wdf()
-    ax_ref = sns.kdeplot(data=data)
-    ax_ref.set_title(title)
-
-
-@check_figures_equal()
-@pytest.mark.parametrize("returns", [True, False])
-@pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
-def test_PortfolioPlotter_ogive(
-    fig_test, fig_ref, risso_portfolio, returns, distribution
-):
-    pf = risso_portfolio(random_state=3, distribution=distribution)
-
-    plotter = PortfolioPlotter(pf)
-
-    ax_test = fig_test.subplots()
-    plotter.ogive(returns=returns, ax=ax_test)
-
-    ax_ref = fig_ref.subplots()
-    data, title = plotter._ddf(returns=returns)
-    ax_ref = sns.ecdfplot(data=data)
-    ax_ref.set_title(title)
+class TestPortfolioPlotter:
+    @pytest.fixture(autouse=True)
+    def setup_plotter(self, risso_portfolio, distribution):
+        self.pf = risso_portfolio(random_state=3, distribution=distribution)
+        self.plotter = PortfolioPlotter(self.pf)
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("returns", [True, False])
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_line(self, fig_test, fig_ref, returns):
+        ax_test = fig_test.subplots()
+        self.plotter.line(returns=returns, ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._ddf(returns=returns)
+        sns.lineplot(data=data, ax=ax_ref)
+        ax_ref.set_title(title)
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("returns", [True, False])
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_heatmap(self, fig_test, fig_ref, returns):
+        ax_test = fig_test.subplots()
+        self.plotter.heatmap(returns=returns, ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._ddf(returns=returns)
+        ax_ref = sns.heatmap(data=data)
+        ax_ref.set_title(title)
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_wheatmap(self, fig_test, fig_ref):
+        ax_test = fig_test.subplots()
+        self.plotter.wheatmap(ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._wdf()
+        ax_ref = sns.heatmap(data=data.T)
+        ax_ref.set_title(title)
+        ax_ref.set_xlabel("Stocks")
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("returns", [True, False])
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_hist(self, fig_test, fig_ref, returns):
+        ax_test = fig_test.subplots()
+        self.plotter.hist(returns=returns, ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._ddf(returns=returns)
+        ax_ref = sns.histplot(data=data)
+        ax_ref.set_title(title)
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_whist(self, fig_test, fig_ref):
+        ax_test = fig_test.subplots()
+        self.plotter.whist(ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._wdf()
+        ax_ref = sns.histplot(data=data.T)
+        ax_ref.set_title(title)
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("returns", [True, False])
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_box(self, fig_test, fig_ref, returns):
+        ax_test = fig_test.subplots()
+        self.plotter.box(returns=returns, ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._ddf(returns=returns)
+        ax_ref = sns.boxplot(data=data)
+        ax_ref.set_title(title)
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_wbox(self, fig_test, fig_ref):
+        ax_test = fig_test.subplots()
+        self.plotter.wbox(ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._wdf()
+        ax_ref = sns.boxplot(data=data)
+        ax_ref.set_title(title)
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("returns", [True, False])
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_kde(self, fig_test, fig_ref, returns):
+        ax_test = fig_test.subplots()
+        self.plotter.kde(returns=returns, ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._ddf(returns=returns)
+        ax_ref = sns.kdeplot(data=data)
+        ax_ref.set_title(title)
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_wkde(self, fig_test, fig_ref):
+        ax_test = fig_test.subplots()
+        self.plotter.wkde(ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._wdf()
+        ax_ref = sns.kdeplot(data=data)
+        ax_ref.set_title(title)
+
+
+    @check_figures_equal()
+    @pytest.mark.parametrize("returns", [True, False])
+    @pytest.mark.parametrize("distribution", pytest.DISTRIBUTIONS)
+    def test_ogive(self, fig_test, fig_ref, returns):
+        ax_test = fig_test.subplots()
+        self.plotter.ogive(returns=returns, ax=ax_test)
+
+        ax_ref = fig_ref.subplots()
+        data, title = self.plotter._ddf(returns=returns)
+        ax_ref = sns.ecdfplot(data=data)
+        ax_ref.set_title(title)