Merge pull request #33 from gisce/NEW_get_summer/winter_curve

New Extraer curvas de verano/invierno de una curva

powerprofile/powerprofile.py

@@ -540,6 +540,31 @@ def extract(self, cols):
 
         return new
 
+    def get_summer_curve(self):
+        return self.get_season_curve(dst=True)
+
+    def get_winter_curve(self):
+        return self.get_season_curve(dst=False)
+
+    def get_season_curve(self, dst=True):
+        """
+        Returns a new partial profile with only the summer registers (dst=True) or the winter registers (false) using
+        DST change time of local timezone
+        :param dst: boolean True(summer) False(winter)
+        :return: new profile
+        """
+        df = self.curve.copy()
+        df['dst'] = df.apply(
+            lambda row: True if TIMEZONE.normalize(row[self.datetime_field]).dst() else False, axis=1
+        )
+        df = df[df['dst'] == dst]
+
+        res = self.__class__(datetime_field=self.datetime_field)
+        data = df.to_dict('records')
+        res.load(data)
+
+        return res
+
     # Dump data
     def to_csv(self, cols=None, header=True):
         """

spec/powerprofile_spec.py

@@ -449,6 +449,45 @@ def read_csv(txt):
                 pp = self.powpro_subcurve_testing3.get_complete_daily_subcurve()
                 expect((pp.curve)).to(equal(None))
 
+        with context('complete season curve'):
+            with before.all:
+                self.curve_season_testing = []
+                self.start = LOCAL_TZ.localize(datetime(2020, 1, 1, 1, 0, 0))
+                self.end = LOCAL_TZ.localize(datetime(2022, 1, 1, 0, 0, 0))
+
+                num_hours = int((self.end - self.start).total_seconds() / 3600) + 1
+                for hours in range(0, num_hours):
+                    self.curve_season_testing.append(
+                        {'timestamp': LOCAL_TZ.normalize(self.start + timedelta(hours=hours)), 'value': 100 + hours}
+                    )
+                self.powpro_season_testing = PowerProfile(datetime_field='timestamp')
+                self.powpro_season_testing.load(self.curve_season_testing)
+
+                self.total_registers = self.powpro_season_testing.samples
+
+                winter_pp = self.powpro_season_testing.get_winter_curve()
+                # Abril no és hivern
+                expect(LOCAL_TZ.localize(datetime(2020, 4, 1, 0)) not in winter_pp.curve.timestamp).to(be_true)
+                # Novembre és hivern
+                expect(LOCAL_TZ.localize(datetime(2020, 11, 1, 0)) not in winter_pp.curve.timestamp).to(be_true)
+
+                self.winter_registers = winter_pp.samples
+                expect(self.winter_registers).to(be_below(self.total_registers))
+
+                summer_pp = self.powpro_season_testing.get_summer_curve()
+                # Abril és estiu"
+                expect(LOCAL_TZ.localize(datetime(2020, 4, 1, 0)) in summer_pp.curve.timestamp).to(be_true)
+                # Novembre no és estiu
+                expect(LOCAL_TZ.localize(datetime(2020, 11, 1, 0)) not in summer_pp.curve.timestamp).to(be_true)
+
+                self.summer_registers = summer_pp.samples
+                expect(self.summer_registers).to(be_below(self.total_registers))
+
+
+                expect(self.summer_registers + self.winter_registers).to(be_equal(self.total_registers))
+
+
+
     with context('accessing data'):
         with before.all:
             self.curve = []