@@ -284,7 +288,7 @@
getPolygon: d => d.polygon,
lineWidthUnits: "common",
getLineWidth: d => d.size * d.size,
- lineWidthScale: 5e-5,
+ lineWidthScale: {{cluster_boundary_line_width}} * 5e-5,
lineJointRounded: true,
lineWidthMaxPixels: 4,
lineWidthMinPixels: 0.0,
@@ -509,6 +513,7 @@ def render_html(
point_line_width_min_pixels=0.1,
point_line_width_max_pixels=8,
point_line_width=0.001,
+ cluster_boundary_line_width=1,
initial_zoom_fraction=1.0,
background_color=None,
darkmode=False,
@@ -636,6 +641,10 @@ def render_html(
point_line_width: float (optional, default=0.001)
The absolute line-width in common coordinates of the outline around points.
+ cluster_boundary_line_width: float (optional, default=1.0)
+ The linewidth to use for cluster boundaries. Note that cluster boundaries scale with respect
+ to cluster size, so this is a scaling factor applied over this.
+
initial_zoom_fraction: float (optional, default=1.0)
The fraction of the total zoom (containing allm the data) to start the
map in. A lower value will initialize the plot zoomed in, while values
@@ -790,7 +799,7 @@ def render_html(
if on_click is not None:
on_click = '({index}, event) => ' + on_click.format_map(replacements)
else:
- hover_data = pd.DataFrame()
+ hover_data = pd.DataFrame(columns=("hover_text",))
get_tooltip = "null"
if inline_data:
@@ -891,6 +900,7 @@ def render_html(
font_family=font_family,
text_collision_size_scale=text_collision_size_scale,
cluster_boundary_polygons="polygon" in label_dataframe.columns,
+ cluster_boundary_line_width=cluster_boundary_line_width,
zoom_level=zoom_level,
data_center_x=data_center[0],
data_center_y=data_center[1],