refactor: merge functionality for results

src/libecalc/common/tabular_time_series.py

@@ -0,0 +1,56 @@
+import itertools
+from typing import Protocol, TypeVar
+
+from libecalc.common.utils.rates import TimeSeries
+from typing_extensions import Self
+
+
+class TabularTimeSeries(Protocol):
+    def copy(self, deep: bool = False) -> Self:
+        """
+        Duplicate a model
+        Args:
+            deep: set to `True` to make a deep copy of the model
+
+        Returns: new model instance
+
+        """
+        ...
+
+
+ObjectWithTimeSeries = TypeVar("ObjectWithTimeSeries", bound=TabularTimeSeries)
+
+
+class TabularTimeSeriesUtils:
+    """
+    Utility functions for objects containing TimeSeries
+    """
+
+    @classmethod
+    def merge(cls, *objects_with_time_series: ObjectWithTimeSeries):
+        """
+        Merge objects containing TimeSeries. Other attributes will be copied from the first object.
+        Args:
+            *objects_with_time_series: list of objects to merge
+
+        Returns: a merged object of the same type
+
+        """
+        # Verify that we are merging the same types
+        if len({type(object_with_time_series) for object_with_time_series in objects_with_time_series}) != 1:
+            raise ValueError("Can not merge objects of differing types.")
+
+        first, *others = objects_with_time_series
+        merged_object = first.copy(deep=True)
+
+        for key, value in first.__dict__.items():
+            for other in others:
+                accumulated_value = merged_object.__getattribute__(key)
+                other_value = other.__getattribute__(key)
+                if key == "timesteps":
+                    merged_timesteps = sorted(itertools.chain(accumulated_value, other_value))
+                    merged_object.__setattr__(key, merged_timesteps)
+                elif isinstance(value, TimeSeries):
+                    merged_object.__setattr__(key, accumulated_value.merge(other_value))
+
+        return merged_object

src/libecalc/common/utils/rates.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import itertools
 import math
 from abc import ABC, abstractmethod
 from collections import defaultdict
@@ -173,6 +174,41 @@ def extend(self, other: TimeSeries) -> Self:
             unit=self.unit,
         )
 
+    def merge(self, other: TimeSeries) -> Self:
+        """
+        Merge two TimeSeries with differing timesteps
+        Args:
+            other:
+
+        Returns:
+
+        """
+        if not isinstance(other, type(self)):
+            raise ValueError(f"Can not merge {type(self)} with {type(other)}")
+
+        if self.unit != other.unit:
+            raise ValueError(f"Mismatching units: '{self.unit}' != '{other.unit}'")
+
+        if len(set(self.timesteps).intersection(other.timesteps)) != 0:
+            raise ValueError("Can not merge two TimeSeries with common timesteps")
+
+        merged_timesteps = sorted(itertools.chain(self.timesteps, other.timesteps))
+        merged_values = []
+
+        for timestep in merged_timesteps:
+            if timestep in self.timesteps:
+                timestep_index = self.timesteps.index(timestep)
+                merged_values.append(self.values[timestep_index])
+            else:
+                timestep_index = other.timesteps.index(timestep)
+                merged_values.append(other.values[timestep_index])
+
+        return self.__class__(
+            timesteps=merged_timesteps,
+            values=merged_values,
+            unit=self.unit,
+        )
+
     def datapoints(self) -> Iterator[Tuple[datetime, TimeSeriesValue]]:
         yield from zip(self.timesteps, self.values)
 
@@ -426,7 +462,8 @@ def resample(self, freq: Frequency) -> TimeSeriesVolumesCumulative:
         ds_resampled = ds_interpolated.reindex(new_index)
 
         return TimeSeriesVolumesCumulative(
-            timesteps=ds_resampled.index.to_pydatetime().tolist(),  # Are we sure this is always an DatetimeIndex? type: ignore
+            timesteps=ds_resampled.index.to_pydatetime().tolist(),
+            # Are we sure this is always an DatetimeIndex? type: ignore
             values=ds_resampled.values.tolist(),
             unit=self.unit,
         )
@@ -669,6 +706,58 @@ def extend(self, other: TimeSeriesRate) -> Self:  # type: ignore[override]
             rate_type=self.rate_type,
         )
 
+    def merge(self, other: TimeSeries) -> TimeSeriesRate:
+        """
+        Merge two TimeSeries with differing timesteps
+        Args:
+            other:
+
+        Returns:
+
+        """
+
+        if not isinstance(other, TimeSeriesRate):
+            raise ValueError(f"Can not merge {type(self)} with {type(other)}")
+
+        if self.unit != other.unit:
+            raise ValueError(f"Mismatching units: '{self.unit}' != '{other.unit}'")
+
+        if not self.rate_type == other.rate_type:
+            raise ValueError(
+                "Mismatching rate type. Currently you can not merge stream/calendar day rates with calendar/stream day rates."
+            )
+
+        if len(set(self.timesteps).intersection(other.timesteps)) != 0:
+            raise ValueError("Can not merge two TimeSeries with common timesteps")
+
+        merged_timesteps = sorted(itertools.chain(self.timesteps, other.timesteps))
+        merged_values = []
+        merged_regularity = []
+
+        for timestep in merged_timesteps:
+            if timestep in self.timesteps:
+                timestep_index = self.timesteps.index(timestep)
+                merged_values.append(self.values[timestep_index])
+                if self.regularity is not None:
+                    merged_regularity.append(self.regularity[timestep_index])
+                else:
+                    merged_regularity.append(1)  # whaaaaaaaaaa
+            else:
+                timestep_index = other.timesteps.index(timestep)
+                merged_values.append(other.values[timestep_index])
+                if other.regularity is not None:
+                    merged_regularity.append(other.regularity[timestep_index])
+                else:
+                    merged_regularity.append(1)  # whaaaaaaaaaa
+
+        return self.__class__(
+            timesteps=merged_timesteps,
+            values=merged_values,
+            regularity=merged_regularity,
+            unit=self.unit,
+            rate_type=self.rate_type,
+        )
+
     def for_period(self, period: Period) -> Self:
         start_index, end_index = period.get_timestep_indices(self.timesteps)
         end_index = end_index + 1  # Include end as we need it to calculate cumulative correctly