addresses #409, adding option to view and interact with spatial indic…

…ator choropleth map for analysed regions in the GHSCI web app

process/configuration/assets/output_data_dictionary.csv

@@ -17,24 +17,24 @@ Linked covariates,"Semi-colon separated list of names of Köppen-Geiger climate
 Linked covariates,"Average temperature calculated from annual average estimates for time interval centred on the year 2015 (the interval spans from 2012 to 2015) within the spatial domain of the Urban Centre, and expressed in Celsius degrees (°C) (Harris et al., 2014).",E_WR_T_14,city
 Linked covariates,"Average precipitations calculated from annual average estimates for time interval centred on the year 2015 (the interval spans from 2012 to 2015) within the spatial domain of the Urban Centre; and expressed in millimetres (mm), the amount of rain per square meter in one hour) (Harris et al., 2014).",E_WR_P_14,city
 Analytical statistic,Sample points used in this analysis (generated along pedestrian network for populated grid areas),urban_sample_point_count,"city, grid"
-Indicator estimates,Score (/1) for access within 500 m to a  fresh food market / supermarket (source: OpenStreetMap or custom),access_500m_fresh_food_market_score,grid
-Indicator estimates,Score (/1) for access within 500 m to a  convenience store (source: OpenStreetMap or custom),access_500m_convenience_score,grid
-Indicator estimates,Score (/1) for access within 500 m to a  public transport (source: OpenStreetMap or custom),access_500m_pt_osm_any_score,grid
-Indicator estimates,Score (/1) for access within 500 m to a  any public open space (source: OpenStreetMap),access_500m_public_open_space_any_score,grid
-Indicator estimates,Score (/1) for access within 500 m to a  public open space larger than 1.5 hectares (source: OpenStreetMap),access_500m_public_open_space_large_score,grid
-Indicator estimates,Score (/1) for access within 500 m to a  public transport (source: GTFS),access_500m_pt_gtfs_any_score,grid
-Indicator estimates,Score (/1) for access within 500 m to a  public transport with average daytime weekday service frequency of 30 minutes or better (source: GTFS),access_500m_pt_gtfs_freq_30_score,grid
-Indicator estimates,Score (/1) for access within 500 m to a  public transport with average daytime weekday service frequency of 20 minutes or better (source: GTFS),access_500m_pt_gtfs_freq_20_score,grid
-Indicator estimates,Score (/1) for access within 500 m to a  any public transport stop (source: GTFS or OpenStreetMap/custom),access_500m_pt_any_score,grid
-Indicator estimates,Percentage of population with access within 500 m to a  fresh food market / supermarket (source: OpenStreetMap or custom),pop_pct_access_500m_fresh_food_market_score,city
-Indicator estimates,Percentage of population with access within 500 m to a  convenience store (source: OpenStreetMap or custom),pop_pct_access_500m_convenience_score,city
-Indicator estimates,Percentage of population with access within 500 m to a  public transport (source: OpenStreetMap or custom),pop_pct_access_500m_pt_osm_any_score,city
-Indicator estimates,Percentage of population with access within 500 m to a  any public open space (source: OpenStreetMap),pop_pct_access_500m_public_open_space_any_score,city
-Indicator estimates,Percentage of population with access within 500 m to a  public open space larger than 1.5 hectares (source: OpenStreetMap),pop_pct_access_500m_public_open_space_large_score,city
-Indicator estimates,Percentage of population with access within 500 m to a  public transport (source: GTFS),pop_pct_access_500m_pt_gtfs_any_score,city
-Indicator estimates,Percentage of population with access within 500 m to a  public transport with average daytime weekday service frequency of 30 minutes or better (source: GTFS),pop_pct_access_500m_pt_gtfs_freq_30_score,city
-Indicator estimates,Percentage of population with access within 500 m to a  public transport with average daytime weekday service frequency of 20 minutes or better (source: GTFS),pop_pct_access_500m_pt_gtfs_freq_20_score,city
-Indicator estimates,Percentage of population with access within 500 m to a  any public transport stop (source: GTFS or OpenStreetMap/custom),pop_pct_access_500m_pt_any_score,city
+Indicator estimates,Score (/1) for access within 500 m to a fresh food market / supermarket (source: OpenStreetMap or custom),access_500m_fresh_food_market_score,grid
+Indicator estimates,Score (/1) for access within 500 m to a convenience store (source: OpenStreetMap or custom),access_500m_convenience_score,grid
+Indicator estimates,Score (/1) for access within 500 m to public transport (source: OpenStreetMap or custom),access_500m_pt_osm_any_score,grid
+Indicator estimates,Score (/1) for access within 500 m to any public open space (source: OpenStreetMap),access_500m_public_open_space_any_score,grid
+Indicator estimates,Score (/1) for access within 500 m to a public open space larger than 1.5 hectares (source: OpenStreetMap),access_500m_public_open_space_large_score,grid
+Indicator estimates,Score (/1) for access within 500 m to public transport (source: GTFS),access_500m_pt_gtfs_any_score,grid
+Indicator estimates,Score (/1) for access within 500 m to public transport with average daytime weekday service frequency of 30 minutes or better (source: GTFS),access_500m_pt_gtfs_freq_30_score,grid
+Indicator estimates,Score (/1) for access within 500 m to public transport with average daytime weekday service frequency of 20 minutes or better (source: GTFS),access_500m_pt_gtfs_freq_20_score,grid
+Indicator estimates,Score (/1) for access within 500 m to any public transport stop (source: GTFS or OpenStreetMap/custom),access_500m_pt_any_score,grid
+Indicator estimates,Percentage of population with access within 500 m to a fresh food market / supermarket (source: OpenStreetMap or custom),pop_pct_access_500m_fresh_food_market_score,city
+Indicator estimates,Percentage of population with access within 500 m to a convenience store (source: OpenStreetMap or custom),pop_pct_access_500m_convenience_score,city
+Indicator estimates,Percentage of population with access within 500 m to public transport (source: OpenStreetMap or custom),pop_pct_access_500m_pt_osm_any_score,city
+Indicator estimates,Percentage of population with access within 500 m to any public open space (source: OpenStreetMap),pop_pct_access_500m_public_open_space_any_score,city
+Indicator estimates,Percentage of population with access within 500 m to public open space larger than 1.5 hectares (source: OpenStreetMap),pop_pct_access_500m_public_open_space_large_score,city
+Indicator estimates,Percentage of population with access within 500 m to public transport (source: GTFS),pop_pct_access_500m_pt_gtfs_any_score,city
+Indicator estimates,Percentage of population with access within 500 m to public transport with average daytime weekday service frequency of 30 minutes or better (source: GTFS),pop_pct_access_500m_pt_gtfs_freq_30_score,city
+Indicator estimates,Percentage of population with access within 500 m to public transport with average daytime weekday service frequency of 20 minutes or better (source: GTFS),pop_pct_access_500m_pt_gtfs_freq_20_score,city
+Indicator estimates,Percentage of population with access within 500 m to any public transport stop (source: GTFS or OpenStreetMap/custom),pop_pct_access_500m_pt_any_score,city
 Indicator estimates,Average walkable neighbourhood poulation density (population weighted) ,pop_nh_pop_density,city
 Indicator estimates,Average walkable neighbourhood intersection density (population weighted) ,pop_nh_intersection_density,city
 Indicator estimates,Average daily living score (population weighted),pop_daily_living,city

process/gui.py

@@ -75,6 +75,66 @@ def get_region(codename) -> dict:
         return region
 
 
+def map_to_html(m, title, file=None, wrap_length=80) -> str:
+    """Convert folium map to html and reformat for display."""
+    import re
+
+    # m.get_root().html.add_child(folium.Element(map_style_html_css))
+    # html = m.get_root().render()
+    html = m.get_root()._repr_html_()
+    ## Wrap legend text if too long
+    ## 65 chars seems to work well, conservatively)
+    if len(title) > wrap_length:
+        import textwrap
+
+        legend_lines = textwrap.wrap(title, wrap_length)
+        legend_length = len(title)
+        n_lines = len(legend_lines)
+        legend_height = 25 + 15 * n_lines
+        old = f'''.attr("class", "caption")\n        .attr("y", 21)\n        .text("{title}");'''
+        new = '.append("tspan")'.join(
+            [
+                '''.attr("class","caption")
+        .attr("x", 0)
+        .attr("y", {pos})
+        .text("{x}")
+        '''.format(
+                    x=x, pos=21 + 15 * legend_lines.index(x),
+                )
+                for x in legend_lines
+            ],
+        )
+        html = html.replace(old, new)
+        html = html.replace(
+            '.attr("height", 40);',
+            f'.attr("height", {legend_height});',
+        )
+
+    # move legend to lower right corner
+    html = html.replace(
+        '''legend = L.control({position: 'topright''',
+        '''legend = L.control({position: 'bottomright''',
+    )
+
+    # give legend white background
+    old = '''</style>'''
+    new = '''    .legend.leaflet-control {
+                            background-color: #FFF;
+                        }
+                 .leaflet-control-attribution.leaflet-control {
+                            width: 72%;
+                        }
+                    </style>'''
+    html = html.replace(old, new)
+    # export or return
+    if file is not None:
+        # save map
+        fid = open(f'{file}.html', 'wb')
+        fid.write(html.encode('utf8'))
+    else:
+        return html
+
+
 async def get_regions(map):
     global regions
     regions = {}
@@ -166,8 +226,9 @@ def summary_table():
             return None
         region['summary'] = region['summary'].transpose().dropna()
         row_key = region['summary'].index.name
+        indicator_dictionary = ghsci.dictionary['Description'].to_dict()
         region['summary'].index = region['summary'].index.map(
-            ghsci.dictionary['Description'].to_dict(), na_action='ignore',
+            indicator_dictionary, na_action='ignore',
         )
         region['summary'] = region['summary'].reset_index()
         values = region['summary'].to_dict('records')
@@ -208,6 +269,64 @@ def toggle() -> None:
                         icon='fullscreen',
                         on_click=toggle,
                     ).props('flat')
+                with table.add_slot('top-right'):
+
+                    async def get_choropleth(indicator) -> None:
+                        if (
+                            indicator
+                            in ghsci.indicators['output'][
+                                'neighbourhood_variables'
+                            ]
+                        ):
+                            r = ghsci.Region(region['codename'])
+                            choropleth = r.choropleth(
+                                field=indicator,
+                                layer=r.config['grid_summary'],
+                                title=indicator_dictionary[
+                                    indicator.replace('pct', 'pop_pct')
+                                ],
+                                save=False,
+                            )
+                            choropleth = map_to_html(
+                                choropleth,
+                                title=indicator_dictionary[
+                                    indicator.replace('pct', 'pop_pct')
+                                ],
+                            )
+                            return choropleth
+
+                    async def popup_choropleth(indicator) -> None:
+                        if indicator is not None:
+                            print(indicator)
+                            choropleth = await get_choropleth(indicator)
+                            if choropleth is not None:
+                                with ui.dialog() as map_dialog, ui.card().style(
+                                    'min-width: 75%',
+                                ):
+                                    ui.html(choropleth).style(
+                                        'min-width: 100%;',
+                                    )
+                                    map_dialog.open()
+
+                    with ui.select(
+                        options=ghsci.indicators['output'][
+                            'neighbourhood_variables'
+                        ],
+                        label='View indicator map',
+                        value='None',
+                        with_input=True,
+                    ).props('flat') as indicator:
+                        ui.tooltip(
+                            'For example, "AU_Melbourne_2023" is a codename for the city of Melbourne, Australia in 2023',
+                        ).props(
+                            'anchor="bottom middle" self="bottom left"',
+                        ).style(
+                            'color: white;background-color: #6e93d6;',
+                        )
+                        indicator.on(
+                            'update:model-value',
+                            lambda e: popup_choropleth(indicator.value),
+                        )
                 dialog.open()
 
 

process/subprocesses/_utils.py

@@ -2131,32 +2131,49 @@ def generate_pdf(
 
 def plot_choropleth_map(
     r,
-    field: str,
-    layer: str = 'indicators_grid_100m',
+    field: str = 'local_walkability',
+    layer: str = None,
     layer_id: str = 'grid_id',
-    fill_color: str = 'YlGn',
-    fill_opacity: float = 0.7,
-    line_opacity: float = 0.1,
     title: str = '',
-    attribution: str = '',
+    auto_alias: bool = True,
+    aliases: list = None,
+    **args,
 ):
     """Given a region, field, layer and layer id, plot an interactive map."""
+    from ghsci import dictionary
+
+    if layer is None:
+        layer = r.config['grid_summary']
+    columns = [layer_id, field]
+    if auto_alias:
+        indicator_dictionary = dictionary['Description'].to_dict()
+        try:
+            aliases = [
+                layer_id,
+                indicator_dictionary[field.replace('pct', 'pop_pct')],
+            ]
+        except KeyError:
+            print(
+                'Attempted to use indicator dictionary for choropleth tooltip alias but did not succeed; using column names instead.',
+            )
+            aliases = columns
+    elif aliases is None:
+        aliases = columns
+
     geojson = r.get_geojson(
         f'(SELECT {layer_id},{field},geom FROM {layer}) as sql',
-        include_columns=[layer_id, field],
+        include_columns=columns,
     )
-    df = r.get_df(layer)[[layer_id, field]]
+    df = r.get_df(layer, columns=columns)
     map = choropleth_map(
         geojson=geojson,
-        df=df[[layer_id, field]],
+        df=df,
         boundary_centroid=tuple(r.get_centroid()),
         key_on=layer_id,
-        fields=[layer_id, field],
-        fill_color=fill_color,
-        fill_opacity=fill_opacity,
-        line_opacity=line_opacity,
+        fields=columns,
         title=title,
-        attribution=attribution,
+        aliases=aliases,
+        **args,
     )
     return map
 
@@ -2167,11 +2184,13 @@ def choropleth_map(
     key_on: str,
     fields: list,
     boundary_centroid: tuple,
-    fill_color: str,
-    fill_opacity: float,
-    line_opacity: float,
     title: str,
-    attribution: str,
+    aliases: list,
+    line_opacity: float = 0.1,
+    fill_color: str = 'YlGn',
+    fill_opacity: float = 0.7,
+    attribution: str = 'Global Healthy and Sustainable City Indicators Collaboration',
+    **args,
 ):
     import folium
 
@@ -2217,9 +2236,14 @@ def choropleth_map(
         fill_opacity=fill_opacity,
         line_opacity=0.1,
         legend_name=title,
+        **args,
     ).add_to(m)
     folium.features.GeoJsonTooltip(
-        fields=fields, labels=True, sticky=True,
+        fields=fields,
+        aliases=aliases,
+        labels=True,
+        sticky=True,
+        localize=True,
     ).add_to(data_layer.geojson)
     folium.LayerControl(collapsed=True).add_to(m)
     m.fit_bounds(m.get_bounds())

process/subprocesses/ghsci.py

@@ -1278,37 +1278,24 @@ def raster_to_db(
 
     def choropleth(
         self,
-        field: str,
-        layer: str,
-        id: str,
-        fill_color: str,
-        fill_opacity: float,
-        line_opacity: float,
-        title: str,
-        save=True,
-        attribution: str = 'Global Healthy and Sustainable City Indicators Collaboration',
+        field: str = 'local_walkability',
+        layer: str = None,
+        save: bool = True,
+        **args,
     ):
         """Plot a choropleth map of a specified field in a specified layer, with a custom title and attribution, with optional saving to an html file."""
         from _utils import plot_choropleth_map
 
+        if layer is None:
+            layer = self.config['grid_summary']
         tables = self.get_tables()
         if layer not in tables:
             print(
                 f"Layer {layer} not found in current list of database tables ({', '.join(tables)}).",
             )
             return None
         else:
-            map = plot_choropleth_map(
-                self,
-                field=field,
-                layer=layer,
-                layer_id=id,
-                title=title,
-                fill_color=fill_color,
-                fill_opacity=fill_opacity,
-                line_opacity=line_opacity,
-                attribution=attribution,
-            )
+            map = plot_choropleth_map(self, field=field, layer=layer, **args)
             if save:
                 file = f'{self.config["region_dir"]}/{layer} - {field}.html'
                 map.save(file)

process/subprocesses/leaflet.py

@@ -12,20 +12,26 @@ def __init__(self) -> None:
         super().__init__()
         ui.add_head_html(
             """<link rel="stylesheet" href="https://unpkg.com/leaflet@1.9.4/dist/leaflet.css"
-     integrity="sha256-p4NxAoJBhIIN+hmNHrzRCf9tD/miZyoHS5obTRR9BMY="
-     crossorigin=""/>""",
+integrity="sha256-p4NxAoJBhIIN+hmNHrzRCf9tD/miZyoHS5obTRR9BMY="
+crossorigin=""/>""",
         )
         ui.add_head_html(
             """<script src="https://unpkg.com/leaflet@1.9.4/dist/leaflet.js"
-     integrity="sha256-20nQCchB9co0qIjJZRGuk2/Z9VM+kNiyxNV1lvTlZBo="
-     crossorigin=""></script>""",
+integrity="sha256-20nQCchB9co0qIjJZRGuk2/Z9VM+kNiyxNV1lvTlZBo="
+crossorigin=""></script>""",
         )
         ui.add_head_html(
             """<style>
-            .leaflet-tile {
-                filter: grayscale(100%);
-            }
-            </style>""",
+.leaflet-tile {
+    filter: grayscale(100%);
+}
+.legend.leaflet-control {
+    background-color: #FFF;
+}
+.leaflet-control-attribution.leaflet-control {
+    width: 50%;
+}
+</style>""",
         )
 
     def set_location(self, location: Tuple[float, float], zoom: int) -> None: