Determine resolution for plots from data first, then from session (#49)

flexmeasures/data/queries/utils.py

@@ -209,7 +209,7 @@ def simplify_index(
                 else:
                     raise KeyError(f"Level {col} not found")
     bdf.index = bdf.index.get_level_values("event_start")
-    return pd.DataFrame(bdf)
+    return bdf
 
 
 def multiply_dataframe_with_deterministic_beliefs(

flexmeasures/data/tests/test_queries.py

@@ -9,6 +9,7 @@
 from flexmeasures.data.models.assets import Asset, Power
 from flexmeasures.data.queries.utils import (
     multiply_dataframe_with_deterministic_beliefs,
+    simplify_index,
 )
 
 
@@ -199,3 +200,18 @@ def test_multiplication_with_both_empty_dataframe():
 
     df = multiply_dataframe_with_deterministic_beliefs(df1, df2)
     pd.testing.assert_frame_equal(df, df_compare)
+
+
+def test_simplify_index():
+    """Check whether simplify_index retains the event resolution."""
+    wind_device_1 = Asset.query.filter_by(name="wind-asset-1").one_or_none()
+    bdf: tb.BeliefsDataFrame = Power.collect(
+        wind_device_1.name,
+        (
+            datetime(2015, 1, 1, tzinfo=pytz.utc),
+            datetime(2015, 1, 2, tzinfo=pytz.utc),
+        ),
+        resolution=timedelta(minutes=15),
+    )
+    df = simplify_index(bdf)
+    assert df.event_resolution == timedelta(minutes=15)

flexmeasures/ui/views/analytics.py

@@ -536,16 +536,6 @@ def make_power_figure(
     else:
         title = "Electricity production from %s" % resource_display_name
 
-    resolution_str = "?"
-    if hasattr(data.index, "freq") and data.index.freq is not None:
-        resolution_str = time_utils.freq_label_to_human_readable_label(
-            data.index.freqstr
-        )
-    elif "resolution" in session:
-        resolution_str = time_utils.freq_label_to_human_readable_label(
-            session["resolution"]
-        )
-
     return create_graph(
         data,
         unit="MW",
@@ -557,7 +547,7 @@ def make_power_figure(
         schedules=schedule_data,
         title=title,
         x_range=shared_x_range,
-        x_label="Time (resolution of %s)" % resolution_str,
+        x_label="Time (resolution of %s)" % determine_resolution(data),
         y_label="Power (in MW)",
         show_y_floats=True,
         tools=tools,
@@ -581,8 +571,7 @@ def make_prices_figure(
         forecasts=forecast_data,
         title=f"Prices for {selected_market.display_name}",
         x_range=shared_x_range,
-        x_label="Time (resolution of %s)"
-        % time_utils.freq_label_to_human_readable_label(session["resolution"]),
+        x_label="Time (resolution of %s)" % determine_resolution(data),
         y_label="Price (in %s)" % selected_market.unit,
         show_y_floats=True,
         tools=tools,
@@ -622,8 +611,7 @@ def make_weather_figure(
         forecasts=forecast_data,
         title=title,
         x_range=shared_x_range,
-        x_label="Time (resolution of %s)"
-        % time_utils.freq_label_to_human_readable_label(session["resolution"]),
+        x_label="Time (resolution of %s)" % determine_resolution(data),
         y_label=weather_axis_label,
         legend_location="top_right",
         show_y_floats=True,
@@ -657,8 +645,7 @@ def make_revenues_costs_figure(
         forecasts=forecast_data,
         title=f"{rev_cost_str} for {resource_display_name} (on {selected_market.display_name})",
         x_range=shared_x_range,
-        x_label="Time (resolution of %s)"
-        % time_utils.freq_label_to_human_readable_label(session["resolution"]),
+        x_label="Time (resolution of %s)" % determine_resolution(data),
         y_label="%s (in %s)" % (rev_cost_str, selected_market.unit[:3]),
         show_y_floats=True,
         tools=tools,
@@ -676,3 +663,23 @@ def revenue_unit_factor(quantity_unit: str, price_unit: str) -> float:
         return 1000
     else:
         raise NotImplementedError
+
+
+def determine_resolution(data: pd.DataFrame) -> str:
+    """
+    Determine the resolution to be displayed under the plot.
+    We try to get it from the DataFrame's meta data, or guess from the actual data.
+    Lastly, we try the session.
+    If nothing can be found this way, the resulting string is "?"
+    """
+    if hasattr(data, "event_resolution"):  # BeliefsDataFrame
+        freq_str = time_utils.timedelta_to_pandas_freq_str(data.event_resolution)
+    elif hasattr(data.index, "freqstr") and data.index.freqstr is not None:
+        freq_str = data.index.freqstr
+    elif hasattr(data.index, "inferred_freq") and data.index.inferred_freq is not None:
+        freq_str = data.index.inferred_freq
+    elif "resolution" in session:
+        freq_str = session["resolution"]
+    else:
+        return "?"
+    return time_utils.freq_label_to_human_readable_label(freq_str)

flexmeasures/ui/views/charts.py

@@ -73,6 +73,7 @@ def get_power_chart(chart_request):
             "resolution": "PT15M",
             "consumption_as_positive": true
             "resolution": "PT6H",
+            "show_individual_traces_for": "none"  // can be power or schedules
         }
 
     On your webpage, you need to include the Bokeh libraries, e.g.: