Merge branch 'main' into get_template

Author: Gigaszi

CHANGELOG.md

@@ -38,6 +38,7 @@
     - now uses topic specific thresholds for bin creation ([#668])
     - plot now shows relative and absolute contributions ([#668])
     - further improvements to description and plot ([#668])
+- mapping-saturation: now shows the estimated total data in the plot ([#658])
 
 [#589]: https://github.com/GIScience/ohsome-quality-analyst/pull/589
 [#600]: https://github.com/GIScience/ohsome-quality-analyst/pull/600
@@ -54,6 +55,7 @@
 [#650]: https://github.com/GIScience/ohsome-quality-analyst/pull/650
 [#653]: https://github.com/GIScience/ohsome-quality-analyst/pull/653
 [#656]: https://github.com/GIScience/ohsome-quality-analyst/pull/656
+[#658]: https://github.com/GIScience/ohsome-quality-analyst/pull/658
 [#659]: https://github.com/GIScience/ohsome-quality-analyst/pull/659
 [#668]: https://github.com/GIScience/ohsome-quality-analyst/pull/668
 [#669]: https://github.com/GIScience/ohsome-quality-analyst/pull/669

ohsome_quality_analyst/indicators/mapping_saturation/indicator.py

@@ -162,15 +162,43 @@ def create_figure(self) -> None:
             pgo.Scatter(
                 x=self.timestamps,
                 y=self.best_fit.fitted_values.tolist(),
-                name="Fitted data",
+                name="Modelled saturation curve",
             ),
         )
         fig.update_layout(title_text="Mapping Saturation")
-        fig.update_xaxes(title_text="Date")
+        fig.update_xaxes(
+            title_text="Date",
+            ticks="outside",
+        )
         if isinstance(self.topic, TopicData):
             fig.update_yaxes(title_text="Value")
         else:
             fig.update_yaxes(title_text=self.topic.aggregation_type.capitalize())
+
+        # plot asymptote
+        asymptote = self.data["best_fit"]["asymptote"]
+        if asymptote < max(self.values) * 5:
+            fig.add_shape(
+                type="line",
+                x0=min(self.timestamps),
+                x1=max(self.timestamps),
+                y0=asymptote,
+                y1=asymptote,
+                line=dict(color="red", width=2, dash="dash"),
+                name="Estimated total data",
+                showlegend=True,
+            )
+            y_max = max(max(self.values), max(self.best_fit.fitted_values))
+            padding_percentage = 1 - (y_max / asymptote)
+            if 0 < padding_percentage < 0.5:
+                padding = y_max * (padding_percentage + 0.05)
+            else:
+                padding = y_max * 0.05
+            fig.update_yaxes(range=[min(self.values), y_max + padding])
+        fig.update_layout(showlegend=True)
+        # fixed legend, because we do not expect high contributions in 2008
+        fig.update_legends(x=0.02, y=0.85, bgcolor="rgba(255,255,255,0.66)")
+
         raw = fig.to_dict()
         raw["layout"].pop("template")  # remove boilerplate
         self.result.figure = raw

ohsome_quality_analyst/oqt.py

@@ -35,7 +35,10 @@ async def create_indicator(
             feature["id"] = i
         # Only enforce size limit if ohsome API data is not provided
         # Disable size limit for the Mapping Saturation indicator
-        if isinstance(topic, TopicDefinition) and key != "mapping-saturation":
+        if isinstance(topic, TopicDefinition) and key not in [
+            "mapping-saturation",
+            "currentness",
+        ]:
             validate_area(feature)
         tasks.append(_create_indicator(key, feature, topic, include_figure))
     return await gather_with_semaphore(tasks)

poetry.lock

@@ -43,10 +43,10 @@ uvicorn = "^0.20.0"
 schema = "^0.7.5"
 building-completeness-model = {version = "^0.1.0rc4", source = "gistools-ohsome-machine-learning-models"}
 kaleido = "0.2.1"
-plotly = "^5.14.0"
 pyproj = "^3.6.0"
 pydantic = "^2.1.1"
 geojson-pydantic = "^1.0.0"
+plotly = "^5.16.1"
 
 [tool.poetry.dev-dependencies]
 black = "^23.3.0"