2026.02.0 2026.02.0.rc2 (#541)

Author: corneel27

dao/CHANGELOG.md

@@ -1,5 +1,16 @@
 # Changelog 刀 DAO
 # Day Ahead Optimizer
+# 2026.02.0
+- Update several python modules
+- Fix error api predict pv_dc (reported by @Dogooder)
+- Adjustments in documentation (#521, @storeman)
+- Fix error calculation of pv-prognose in api should be done with ml_prediction if configured (reported by @Dogooder)
+- Fix error when HA-sensor has unit_of_measurement="MWh" (reported by @itavero)
+- Catched error when ml_prediction=true and there is no trained model: with warning-logging and use dao-prediction as fallback
+- Fixed groupby-error with mysql(with "ONLY_FULL_GROUP_BY") and postgresql
+- Fixed error in Wh-correction when no ha-data are present
+- Correct sensordata from HA with unit_of_measurement="Wh" to "kWh"
+
 # 2026.01.2
 Correct sensordata from HA with unit_of_measurement="Wh" to "kWh"
 

dao/config.yaml

@@ -1,6 +1,6 @@
 ---
 name: 刀 Day Ahead Optimizer
-version: 2026.01.2
+version: 2026.02.0
 slug: day_ahead_opt
 description: Home Assistant Community Add-ons for day ahead optimizations
 url: https://github.com/corneel27/day-ahead

dao/prog/da_graph.py

@@ -188,7 +188,9 @@ def build(self, df, options, show=True):
                         ymax_left = math.ceil(max(ymax_left, max(data_array)))
                         ymin_left = math.floor(min(ymin_left, min(data_array)))
                     if vax == "right":
-                        ymax_right = math.ceil(max(ymax_right, max(data_array)))
+                        ymax_right = (
+                            math.ceil(max(ymax_right, max(data_array)) * 10) / 10
+                        )
                         ymin_right = math.floor(min(ymin_right, min(data_array)))
                     if s_type == "bar" or s_type == "stacked":
                         nr_bar += 1
@@ -313,8 +315,15 @@ def build(self, df, options, show=True):
             # axis.legend(loc = 'center left', bbox_to_anchor=(1, 0.5))
 
             if axis_right:
-                ylim = math.ceil(
-                    max(np.max(stacked_plus_right), -np.min(stacked_neg_right))
+                ylim = (
+                    math.ceil(
+                        max(
+                            max(np.max(stacked_plus_right), ymax_right),
+                            -min(np.min(stacked_neg_right), ymin_right),
+                        )
+                        * 10
+                    )
+                    / 10
                 )
                 if ylim > 0:
                     if np.min(stacked_neg_right) < 0:
@@ -324,9 +333,19 @@ def build(self, df, options, show=True):
                 else:
                     axis_right.set_ylim([min(0, ymin_right), ymax_right])
                 axis_right.set_ylabel(g_options["vaxis"][1]["title"])
+                if "format" in g_options["vaxis"][1]:
+                    f_str = g_options["vaxis"][1]["format"]
+                    axis_right.yaxis.set_major_formatter(
+                        ticker.FormatStrFormatter(f_str)
+                    )
 
             if stacked_plus is not None:
-                ylim = math.ceil(max(np.max(stacked_plus), -np.min(stacked_neg)))
+                ylim = math.ceil(
+                    max(
+                        max(np.max(stacked_plus), ymax_left),
+                        -min(np.min(stacked_neg), ymin_left),
+                    )
+                )
                 if ylim > 0:
                     if np.min(stacked_neg) < 0:
                         ax.set_ylim([-ylim, ylim])
@@ -345,5 +364,4 @@ def build(self, df, options, show=True):
 
         if show:
             plt.show()
-        else:
-            return fig
+        return fig

dao/prog/da_prices.py

@@ -21,33 +21,45 @@ def __init__(self, config: Config, db_da: DBmanagerObj):
         self.interval = self.config.get(["interval"], None, "1hour")
         self.country = self.config.get(["country"], None, "NL")
 
-    def get_prices(self, source):
+    def get_prices(
+        self, source, _start: datetime.datetime = None, _end: datetime.datetime = None
+    ):
         if self.interval == "1hour":
             resolution = 60
         else:
             resolution = 15
         now = datetime.datetime.now()
         # start
-        if len(sys.argv) > 2:
-            arg_s = sys.argv[2]
-            start = datetime.datetime.strptime(arg_s, "%Y-%m-%d")
+        if _start is None:
+            if len(sys.argv) > 2:
+                arg_s = sys.argv[2]
+                start = datetime.datetime.strptime(arg_s, "%Y-%m-%d")
+            else:
+                start = pd.Timestamp(
+                    year=now.year, month=now.month, day=now.day, tz="CET"
+                )
         else:
-            start = pd.Timestamp(year=now.year, month=now.month, day=now.day, tz="CET")
+            start = _start
         # end
-        if len(sys.argv) > 3:
-            arg_s = sys.argv[3]
-            end = datetime.datetime.strptime(arg_s, "%Y-%m-%d")
-        else:
-            if now.hour < 12:
-                end = start + datetime.timedelta(days=1)
+        if _end is None:
+            if len(sys.argv) > 3:
+                arg_s = sys.argv[3]
+                end = datetime.datetime.strptime(arg_s, "%Y-%m-%d")
             else:
-                end = start + datetime.timedelta(days=2)
+                if now.hour < 12:
+                    end = start + datetime.timedelta(days=1)
+                else:
+                    end = start + datetime.timedelta(days=2)
+        else:
+            end = _end
 
         if len(sys.argv) <= 2:
             present = self.db_da.get_time_border_record("da")
             if not (present is None):
                 tz = pytz.timezone("CET")
                 present = tz.normalize(tz.localize(present))
+                if end.tzinfo is None:
+                    end = tz.normalize(tz.localize(end))
                 if present >= (end - datetime.timedelta(hours=1)):
                     logging.info(f"Day ahead data already present")
                     return

dao/prog/db_manager.py

@@ -557,7 +557,7 @@ def get_column_data(
             result = connection.execute(query)
         df = pd.DataFrame(result.fetchall(), columns=result.keys())
         if agg_func is not None:
-            df.groupby("uur").agg(
+            df = df.groupby("uur").agg(
                 {
                     "uur": "min",
                     "time": "min",

release-testing/CHANGELOG.md

@@ -1,5 +1,8 @@
 # Changelog 刀 DAO
 # Day Ahead Optimizer
+# 2026.02.0.rc2
+Update several python modules
+
 # 2026.02.0.rc1
 Fix error api predict pv_dc (reported by @Dogooder)
 

release-testing/config.yaml

@@ -1,6 +1,6 @@
 ---
 name: 刀 Day Ahead Optimizer (TESTING)
-version: 2026.02.0.rc1
+version: 2026.02.0.rc2
 stage: experimental
 slug: day_ahead_opt-testing
 description: Beta version of DAO. Use only for testing!