Latest state as sensor property

flexmeasures/api/v1_3/implementations.py

@@ -151,7 +151,7 @@ def get_device_message_response(generic_asset_name_groups, duration):
             #           event_starts_after=schedule_start,
             #           event_ends_before=schedule_start + planning_horizon,
             #           source=scheduler_source,
-            #           most_recent_only=True,
+            #           most_recent_beliefs_only=True,
             #       )
 
             # Subquery to get the most recent schedule only

flexmeasures/data/models/assets.py

@@ -1,4 +1,5 @@
-from typing import Dict, List, Tuple, Union
+from datetime import datetime, timedelta
+from typing import Dict, List, Optional, Tuple, Union
 
 import isodate
 import timely_beliefs as tb
@@ -144,6 +145,20 @@ def __init__(self, **kwargs):
     )
     market = db.relationship("Market", backref=db.backref("assets", lazy=True))
 
+    def latest_state(self, event_ends_before: Optional[datetime] = None) -> "Power":
+        """Search the most recent event for this sensor, optionally before some datetime."""
+        # todo: replace with Sensor.latest_state
+        power_query = (
+            Power.query.filter(Power.asset == self)
+            .filter(Power.horizon <= timedelta(hours=0))
+            .order_by(Power.datetime.desc())
+        )
+        if event_ends_before is not None:
+            power_query = power_query.filter(
+                Power.datetime + self.event_resolution <= event_ends_before
+            )
+        return power_query.first()
+
     @property
     def power_unit(self) -> float:
         """Return the 'unit' property of the generic asset, just with a more insightful name."""

flexmeasures/data/models/time_series.py

@@ -63,16 +63,30 @@ def __init__(
     def entity_address(self) -> str:
         return build_entity_address(dict(sensor_id=self.id), "sensor")
 
+    def latest_state(
+        self,
+    ) -> tb.BeliefsDataFrame:
+        """Search the most recent event for this sensor, and return the most recent ex-post belief."""
+        return self.search_beliefs(
+            horizons_at_most=timedelta(0),
+            most_recent_beliefs_only=True,
+            most_recent_events_only=True,
+        )
+
     def search_beliefs(
         self,
         event_starts_after: Optional[datetime_type] = None,
         event_ends_before: Optional[datetime_type] = None,
         beliefs_after: Optional[datetime_type] = None,
         beliefs_before: Optional[datetime_type] = None,
+        horizons_at_least: Optional[timedelta] = None,
+        horizons_at_most: Optional[timedelta] = None,
         source: Optional[
             Union[DataSource, List[DataSource], int, List[int], str, List[str]]
         ] = None,
-        most_recent_only: bool = False,
+        most_recent_beliefs_only: bool = False,
+        most_recent_events_only: bool = False,
+        most_recent_only: bool = False,  # deprecated
         as_json: bool = False,
     ) -> Union[tb.BeliefsDataFrame, str]:
         """Search all beliefs about events for this sensor.
@@ -81,19 +95,33 @@ def search_beliefs(
         :param event_ends_before: only return beliefs about events that end before this datetime (inclusive)
         :param beliefs_after: only return beliefs formed after this datetime (inclusive)
         :param beliefs_before: only return beliefs formed before this datetime (inclusive)
+        :param horizons_at_least: only return beliefs with a belief horizon equal or greater than this timedelta (for example, use timedelta(0) to get ante knowledge time beliefs)
+        :param horizons_at_most: only return beliefs with a belief horizon equal or less than this timedelta (for example, use timedelta(0) to get post knowledge time beliefs)
         :param source: search only beliefs by this source (pass the DataSource, or its name or id) or list of sources
-        :param most_recent_only: only return the most recent beliefs for each event from each source (minimum belief horizon)
+        :param most_recent_beliefs_only: only return the most recent beliefs for each event from each source (minimum belief horizon)
+        :param most_recent_events_only: only return (post knowledge time) beliefs for the most recent event (maximum event start)
         :param as_json: return beliefs in JSON format (e.g. for use in charts) rather than as BeliefsDataFrame
         :returns: BeliefsDataFrame or JSON string (if as_json is True)
         """
+        # todo: deprecate the 'most_recent_only' argument in favor of 'most_recent_beliefs_only' (announced v0.8.0)
+        most_recent_beliefs_only = tb_utils.replace_deprecated_argument(
+            "most_recent_only",
+            most_recent_only,
+            "most_recent_beliefs_only",
+            most_recent_beliefs_only,
+            required_argument=False,
+        )
         bdf = TimedBelief.search(
             sensor=self,
             event_starts_after=event_starts_after,
             event_ends_before=event_ends_before,
             beliefs_after=beliefs_after,
             beliefs_before=beliefs_before,
+            horizons_at_least=horizons_at_least,
+            horizons_at_most=horizons_at_most,
             source=source,
-            most_recent_only=most_recent_only,
+            most_recent_beliefs_only=most_recent_beliefs_only,
+            most_recent_events_only=most_recent_events_only,
         )
         if as_json:
             df = bdf.reset_index()
@@ -219,10 +247,14 @@ def search(
         event_ends_before: Optional[datetime_type] = None,
         beliefs_after: Optional[datetime_type] = None,
         beliefs_before: Optional[datetime_type] = None,
+        horizons_at_least: Optional[timedelta] = None,
+        horizons_at_most: Optional[timedelta] = None,
         source: Optional[
             Union[DataSource, List[DataSource], int, List[int], str, List[str]]
         ] = None,
-        most_recent_only: bool = False,
+        most_recent_beliefs_only: bool = False,
+        most_recent_events_only: bool = False,
+        most_recent_only: bool = False,  # deprecated
     ) -> tb.BeliefsDataFrame:
         """Search all beliefs about events for a given sensor.
 
@@ -231,9 +263,20 @@ def search(
         :param event_ends_before: only return beliefs about events that end before this datetime (inclusive)
         :param beliefs_after: only return beliefs formed after this datetime (inclusive)
         :param beliefs_before: only return beliefs formed before this datetime (inclusive)
+        :param horizons_at_least: only return beliefs with a belief horizon equal or greater than this timedelta (for example, use timedelta(0) to get ante knowledge time beliefs)
+        :param horizons_at_most: only return beliefs with a belief horizon equal or less than this timedelta (for example, use timedelta(0) to get post knowledge time beliefs)
         :param source: search only beliefs by this source (pass the DataSource, or its name or id) or list of sources
-        :param most_recent_only: only return the most recent beliefs for each event from each source (minimum belief horizon)
+        :param most_recent_beliefs_only: only return the most recent beliefs for each event from each source (minimum belief horizon)
+        :param most_recent_events_only: only return (post knowledge time) beliefs for the most recent event (maximum event start)
         """
+        # todo: deprecate the 'most_recent_only' argument in favor of 'most_recent_beliefs_only' (announced v0.8.0)
+        most_recent_beliefs_only = tb_utils.replace_deprecated_argument(
+            "most_recent_only",
+            most_recent_only,
+            "most_recent_beliefs_only",
+            most_recent_beliefs_only,
+            required_argument=False,
+        )
         parsed_sources = parse_source_arg(source)
         return cls.search_session(
             session=db.session,
@@ -242,8 +285,11 @@ def search(
             event_ends_before=event_ends_before,
             beliefs_after=beliefs_after,
             beliefs_before=beliefs_before,
+            horizons_at_least=horizons_at_least,
+            horizons_at_most=horizons_at_most,
             source=parsed_sources,
-            most_recent_only=most_recent_only,
+            most_recent_beliefs_only=most_recent_beliefs_only,
+            most_recent_events_only=most_recent_events_only,
         )
 
     @classmethod

flexmeasures/data/services/time_series.py

@@ -266,7 +266,7 @@ def convert_query_window_for_demo(
         else:
             end = query_window[-1]
 
-    if start >= end:
+    if start > end:
         start, end = (end, start)
     return start, end
 

flexmeasures/ui/utils/plotting_utils.py

@@ -23,8 +23,9 @@
 import numpy as np
 import timely_beliefs as tb
 
-from flexmeasures.data.models.assets import Asset, Power
+from flexmeasures.data.models.assets import Asset
 from flexmeasures.data.models.data_sources import DataSource
+from flexmeasures.data.services.time_series import convert_query_window_for_demo
 from flexmeasures.utils.flexmeasures_inflection import capitalize
 from flexmeasures.utils.time_utils import (
     server_now,
@@ -563,27 +564,13 @@ def get_latest_power_as_plot(asset: Asset, small: bool = False) -> Tuple[str, st
     """Create a plot of an asset's latest power measurement as an embeddable html string (incl. javascript).
     First returned string is the measurement time, second string is the html string."""
 
-    if current_app.config.get("FLEXMEASURES_MODE", "") == "demo":
-        demo_year = current_app.config.get("FLEXMEASURES_DEMO_YEAR", None)
-        if demo_year is None:
-            before = server_now()
-        else:
-            before = server_now().replace(year=demo_year)
-    elif current_app.config.get("FLEXMEASURES_MODE", "") == "play":
+    if current_app.config.get("FLEXMEASURES_MODE", "") == "play":
         before = None  # type:ignore
     else:
         before = server_now()
+        _, before = convert_query_window_for_demo((before, before))
 
-    power_query = (
-        Power.query.filter(Power.asset == asset)
-        .filter(Power.horizon <= timedelta(hours=0))
-        .order_by(Power.datetime.desc())
-    )
-    if before is not None:
-        power_query = power_query.filter(
-            Power.datetime + asset.event_resolution <= before
-        )
-    latest_power = power_query.first()
+    latest_power = asset.latest_state(event_ends_before=before)
     if latest_power is not None:
         latest_power_value = latest_power.value
         if current_app.config.get("FLEXMEASURES_MODE", "") == "demo":

requirements/app.in

@@ -32,7 +32,7 @@ netCDF4
 siphon
 tables
 timetomodel>=0.7.1
-timely-beliefs>=1.6.0
+timely-beliefs>=1.7.0
 python-dotenv
 # a backport, not needed in Python3.8
 importlib_metadata

requirements/app.txt

@@ -352,7 +352,7 @@ tables==3.6.1
     # via -r requirements/app.in
 threadpoolctl==3.0.0
     # via scikit-learn
-timely-beliefs==1.6.0
+timely-beliefs==1.7.0
     # via -r requirements/app.in
 timetomodel==0.7.1
     # via -r requirements/app.in