🔀 Feature/set axis language from class

CHANGELOG.md

@@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 ### Added
+- Spanish language support — `Plotter_Population_Trend_Model` and `Plotter_Population_Trend_Model_From_CPUE` now accept a language parameter "english" / "spanish") controlling axis label language.
 
 ### Fixed
 

Makefile

@@ -72,7 +72,7 @@ setup: clean install
 tests:
 	pytest --verbose
 
-tdd_current_test_file = tests/test_cli.py
+tdd_current_test_file = tests/test_Population_trend.py
 red: format
 	pytest --verbose $(tdd_current_test_file) \
 	&& git restore tests/*.py \
@@ -87,7 +87,7 @@ green: format
 
 refactor: format
 	pytest --verbose $(tdd_current_test_file) \
-	&& (git add ${module}/*.py tests/*.py && git commit -m "♻️ Refactor") \
+	&& (git add ${module}/*.py tests/*.py && git commit -m "♻️ Refactor ${m}") \
 	|| git restore ${module}/*.py tests/*.py
 	chmod g+w -R .
 

population_trend/plotter_population_trend_from_cpue.py

@@ -4,8 +4,8 @@
 
 
 class Plotter_Population_Trend_Model_From_CPUE(Plotter_Population_Trend_Model):
-    def __init__(self, data, population_model, tick_mode="full"):
-        super().__init__(data, population_model, tick_mode)
+    def __init__(self, data, population_model, tick_mode="full", language="english"):
+        super().__init__(data, population_model, tick_mode, language)
 
     def set_labels(self):
         plt.ylabel("CPUE", size=20)

population_trend/population_growth_model.py

@@ -46,13 +46,14 @@ def max_model(self):
 
 
 class Plotter_Population_Trend_Model:
-    def __init__(self, data, population_model, tick_mode):
+    def __init__(self, data, population_model, tick_mode, language="english"):
         self.fig, self.ax = geci_plot()
         self.fill_missing_seasons(data)
         self.tick_mode = tick_mode
+        self.language = language
         self.seasons_to_plot = self.filled_data.index.values + 1
         self.ticks_positions = ticks_positions_array(self.filled_data)
-        self.plot_domain = np.linspace(self.ticks_positions.min(), self.ticks_positions.max(), 100)
+        self.domain_plot = np.linspace(self.ticks_positions.min(), self.ticks_positions.max(), 100)
         self.population_model = population_model
         self.interest_variable = population_model.interest_variable
 
@@ -67,48 +68,48 @@ def fill_missing_seasons(self, data):
 
     def plot_smooth(self):
         self.ax.fill_between(
-            self.plot_domain,
+            self.domain_plot,
             self.population_model.min_model,
             self.population_model.med_model,
             label="Confidence zone",
             color="powderblue",
         )
         self.ax.fill_between(
-            self.plot_domain,
+            self.domain_plot,
             self.population_model.med_model,
             self.population_model.max_model,
             color="powderblue",
         )
         self.ax.fill_between(
-            self.plot_domain,
+            self.domain_plot,
             self.population_model.min_model,
             self.population_model.max_model,
             color="powderblue",
         )
         number_of_samples = len(self.population_model.bootstrap_distribution)
         for i in range(0, number_of_samples - 1, 10):
             self.ax.fill_between(
-                self.plot_domain,
+                self.domain_plot,
                 self.population_model.intern_model(i),
                 self.population_model.med_model,
                 color="powderblue",
             )
             self.ax.fill_between(
-                self.plot_domain,
+                self.domain_plot,
                 self.population_model.intern_model(i),
                 self.population_model.intern_model(i + 1),
                 color="powderblue",
             )
         self.ax.fill_between(
-            self.plot_domain,
+            self.domain_plot,
             self.population_model.intern_model(i + 1),
             self.population_model.med_model,
             color="powderblue",
         )
 
     def plot_model(self):
         plt.plot(
-            self.plot_domain,
+            self.domain_plot,
             self.population_model.med_model,
             label="Population growth model",
             color="b",
@@ -147,9 +148,12 @@ def set_x_lim(self):
         )
 
     def set_labels(self):
-        labels = {"english": {"ylabel": "Number of breeding pairs", "xlabel": "Seasons"}}
-        plt.ylabel(labels["english"]["ylabel"], size=20)
-        plt.xlabel(labels["english"]["xlabel"], size=20)
+        labels = {
+            "english": {"ylabel": "Number of breeding pairs", "xlabel": "Seasons"},
+            "spanish": {"ylabel": "Número de parejas reproductivas", "xlabel": "Temporadas"},
+        }
+        self.ax.set_ylabel(labels[self.language]["ylabel"], size=20)
+        self.ax.set_xlabel(labels[self.language]["xlabel"], size=20)
 
     def set_ticks(self):
         self.get_tick_step()

tests/test_Population_trend.py

@@ -64,7 +64,6 @@ def tests_calculate_upper_limit():
 
 
 class Tests_Plotter_Population_Trend_Model:
-
     def tests_init_(self):
         fig, ax = geci_plot()
         assert type(fig) == type(Plotter.fig)  # noqa
@@ -80,12 +79,23 @@ def test_Plotter_plot_data(self):
         assert len(Plotter.ax.get_lines()) == expected_one_line
 
     def tests_time_to_model(self):
-        obtained = Plotter.plot_domain
+        obtained = Plotter.domain_plot
         expected_first_point = 1
         assert obtained[0] == expected_first_point
         expected_last_point = 4.05
         assert obtained[-1] == expected_last_point
 
+    def tests_set_labels(self):
+        Plotter.set_labels()
+        obtained_labels = [Plotter.ax.get_xlabel(), Plotter.ax.get_ylabel()]
+        expected_labels = ["Seasons", "Number of breeding pairs"]
+        assert obtained_labels == expected_labels
+        Plotter.language = "spanish"
+        Plotter.set_labels()
+        obtained_labels = [Plotter.ax.get_xlabel(), Plotter.ax.get_ylabel()]
+        expected_labels = ["Temporadas", "Número de parejas reproductivas"]
+        assert obtained_labels == expected_labels
+
     def tests_savefig(self):
         islet = "morro"
         default_path = f"reports/figures/cormorant_population_trend_{islet}.png"