from bokeh.models import WheelZoomTool, ResizeTool, PanTool, BoxZoomTool
from bokeh.models import WMTSTileSource
output_file("tile_source_example.html", title="Tile Source Example")
# set to roughly full extent of web mercator projection
x_range = Range1d(start=-20000000, end=20000000)
y_range = Range1d(start=-20000000, end=20000000)
# create tile source from templated url
tile_options = {}
tile_options['url'] = 'http://c.tile.openstreetmap.org/{z}/{x}/{y}.png'
tile_source = WMTSTileSource(**tile_options)
# instantiate plot and add tile source
p = Plot(x_range=x_range, y_range=y_range, plot_height=800, plot_width=800)
p.add_tools(ResizeTool(), WheelZoomTool(), PanTool(), BoxZoomTool())
tile_renderer_options = {}
p.add_tile(tile_source, **tile_renderer_options)
doc = Document()
doc.add(p)
if __name__ == "__main__":
filename = "tile_source.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Tile Source Example"))
print("Wrote %s" % filename)
view(filename)
points_source = ColumnDataSource(airports)
# create tile source
tile_options = {}
tile_options['url'] = 'http://otile2.mqcdn.com/tiles/1.0.0/sat/{Z}/{X}/{Y}.png'
tile_source = WMTSTileSource(**tile_options)
# set to roughly extent of points
x_range = Range1d(start=airports['x'].min() - 10000, end=airports['x'].max() + 10000)
y_range = Range1d(start=airports['y'].min() - 10000, end=airports['y'].max() + 10000)
# create plot and add tools
hover_tool = HoverTool(tooltips=[("Name", "@name"), ("Elevation", "@elevation (m)")])
p = Plot(x_range=x_range, y_range=y_range, plot_height=690, plot_width=990, title=title)
p.add_tools(ResizeTool(), WheelZoomTool(), PanTool(), BoxZoomTool(), hover_tool)
p.add_tile(tile_source)
# create point glyphs
point_options = {}
point_options['x'] = 'x'
point_options['y'] = 'y'
point_options['size'] = 9
point_options['fill_color'] = "#60ACA1"
point_options['line_color'] = "#D2C4C1"
point_options['line_width'] = 1.5
points_glyph = Circle(**point_options)
p.add_glyph(points_source, points_glyph)
doc = Document()
doc.add_root(p)
title = 'Dynamic Map: National Land Cover Dataset'
x_range = Range1d(start=-15473429, end=2108550)
y_range = Range1d(start=-6315661, end=7264686)
p = Plot(x_range=x_range,
y_range=y_range,
plot_height=700,
plot_width=700,
title=title)
p.background_fill = "black"
p.add_tools(WheelZoomTool(), PanTool())
# add base layer
tile_options = {}
tile_options['url'] = 'http://tile.stamen.com/toner/{Z}/{X}/{Y}.png'
tile_source = WMTSTileSource(**tile_options)
p.add_tile(tile_source)
# add dynamic data layer
# National Land Cover Dataset (http://www.mrlc.gov/nlcd2011.php)
service_url = 'http://raster.nationalmap.gov/arcgis/rest/services/LandCover/USGS_EROS_LandCover_NLCD/MapServer/export?'
service_url += 'bbox={XMIN},{YMIN},{XMAX},{YMAX}&bboxSR=102100&size={HEIGHT}%2C{WIDTH}&imageSR=102100&format=png32&transparent=true&f=image'
image_source_options = {}
image_source_options['url'] = service_url
image_source = ImageSource(**image_source_options)
p.add_dynamic_image(image_source)
# create labels layer
tile_label_options = {}
tile_label_options[
'url'] = 'http://tile.stamen.com/toner-labels/{Z}/{X}/{Y}.png'
tile_label_source = WMTSTileSource(**tile_label_options)
def plot_data(data_df, connections, year, geoSource_new):
data_df_countries = data_df #.drop_duplicates(subset=None, keep='first', inplace=True)
connections_df = connections
node_source = ColumnDataSource(
data_df_countries[["country_id", "Country", "Longitude", "Latitude"]])
edge_source = ColumnDataSource(connections_df[["start", "end"]])
node_renderer = GlyphRenderer(data_source=node_source,
glyph=node_glyph,
selection_glyph=node_selection,
nonselection_glyph=node_nonselection)
## Create edge_renderer
edge_renderer = GlyphRenderer(data_source=edge_source,
glyph=edge_glyph,
hover_glyph=edge_hover,
selection_glyph=edge_selection,
nonselection_glyph=edge_nonselection)
## Create layout_provider
graph_layout = dict(
zip(data_df_countries.country_id.astype(str),
zip(data_df_countries.Longitude, data_df_countries.Latitude)))
layout_provider = StaticLayoutProvider(graph_layout=graph_layout)
## Create graph renderer
graph = GraphRenderer(edge_renderer=edge_renderer,
node_renderer=node_renderer,
layout_provider=layout_provider,
inspection_policy=NodesAndLinkedEdges(),
selection_policy=NodesAndLinkedEdges())
plot = Plot(x_range=Range1d(-150, 150),
y_range=Range1d(15, 75),
plot_width=800,
plot_height=600,
background_fill_color=Set3_12[4],
background_fill_alpha=0.2)
plot.title.text = "Human Trafficing Visualization for " + str(year)
# plot.add_glyph( geoSource_data, Patches(xs='xs', ys='ys', line_color='grey'
# , line_width=.5, fill_color=Set3_12[6], fill_alpha=0.25))
plot.add_glyph(
geoSource_new,
Patches(xs='xs',
ys='ys',
line_color='grey',
line_width=.2,
fill_color={
'field': 'Tier',
'transform': mapper2
},
fill_alpha=0.25))
plot.renderers.append(graph)
plot.add_layout(LinearAxis(axis_label="Latitude"), "below")
plot.add_layout(LinearAxis(axis_label="Longitude"), "left")
hover = HoverTool(
show_arrow=True, # tooltips= # [("Country Involved: ", "@Country")],
tooltips="""
<div>
<div>
<span style="font-size: 15px;">Country Information </span>
<span style="font-size: 12px; color: #696;">@Destination_Country </span>
</div>
</div>
""",
renderers=[graph])
hover_no_tooltips = HoverTool(tooltips=None, renderers=[graph])
box_zoom = BoxZoomTool()
plot.add_tools(hover, hover_no_tooltips, box_zoom, TapTool(),
BoxSelectTool(), ResetTool(), WheelZoomTool())
plot.toolbar.active_inspect = [hover, hover_no_tooltips]
plot.toolbar.active_drag = box_zoom
plot.outline_line_color = "navy"
plot.outline_line_alpha = 0.3
plot.outline_line_width = 3
plot.add_tile(STAMEN_TONER_LABELS)
return plot
def plot_data(data_df, connections, year, geoSource_new, df):
d_yr = df[df['Years'] == year]
data_df_countries = d_yr.merge(data_df,
left_on='Origin_Country',
right_on='Country')
#data_df_countries = node_dt #.drop_duplicates(subset=None, keep='first', inplace=True)
connections_df = connections
# node_source = ColumnDataSource(data_df_countries[["country_id","Country", "Longitude", "Latitude"]])
node_source = ColumnDataSource(data_df_countries)
edge_source = ColumnDataSource(connections_df[["start", "end"]])
node_renderer = GlyphRenderer(data_source=node_source,
glyph=node_glyph,
selection_glyph=node_selection,
nonselection_glyph=node_nonselection)
## Create edge_renderer
edge_renderer = GlyphRenderer(data_source=edge_source,
glyph=edge_glyph,
hover_glyph=edge_hover,
selection_glyph=edge_selection,
nonselection_glyph=edge_nonselection)
## Create layout_provider
graph_layout = dict(
zip(data_df_countries.country_id.astype(str),
zip(data_df_countries.Longitude, data_df_countries.Latitude)))
layout_provider = StaticLayoutProvider(graph_layout=graph_layout)
## Create graph renderer
graph = GraphRenderer(edge_renderer=edge_renderer,
node_renderer=node_renderer,
layout_provider=layout_provider,
inspection_policy=NodesAndLinkedEdges(),
selection_policy=NodesAndLinkedEdges())
plot = Plot(x_range=Range1d(-150, 150),
y_range=Range1d(15, 75),
plot_width=800,
plot_height=600,
background_fill_color=Set3_12[4],
background_fill_alpha=0.2)
plot.title.text = "Human Trafficing Visualization for " + str(year)
plot.add_glyph(
geoSource_new,
Patches(xs='xs',
ys='ys',
line_color='grey',
line_width=.2,
fill_color={
'field': 'Tier',
'transform': mapper2
},
fill_alpha=0.40))
plot.renderers.append(graph)
plot.add_layout(LinearAxis(axis_label="Latitude"), "below")
plot.add_layout(LinearAxis(axis_label="Longitude"), "left")
# tooltips="""
# <div>
# <div>
# <span style="font-size: 17px; font-weight: bold;">@desc</span>
# <span style="font-size: 15px; color: #966;">[$index]</span>
# </div>
# <div>
# <span style="font-size: 15px;">Country Involved</span>
# <span style="font-size: 10px; color: #696;">@Country</span>
# </div>
# </div>
# """,
hover = HoverTool(
show_arrow=True, # tooltips= # [("Country Involved: ", "@Country")],
tooltips="""
<div>
<div>
<span style="font-size: 13px;">Country Info</span>
<span style="font-size: 12px; color: #696;">@Destination_Country, @Type_Of_Trafficking</span>
</div>
</div>
""",
renderers=[node_renderer],
name='Test')
hover_no_tooltips = HoverTool(tooltips=None, renderers=[graph])
box_zoom = BoxZoomTool()
plot.add_tools(hover, hover_no_tooltips, box_zoom, TapTool(),
BoxSelectTool(), ResetTool(), WheelZoomTool())
plot.toolbar.active_inspect = [hover, hover_no_tooltips]
plot.toolbar.active_drag = box_zoom
plot.outline_line_color = "navy"
plot.outline_line_alpha = 0.3
plot.outline_line_width = 1
select_overlay = plot.select_one(BoxSelectTool).overlay
select_overlay.fill_color = "firebrick"
select_overlay.line_color = None
zoom_overlay = plot.select_one(BoxZoomTool).overlay
zoom_overlay.line_color = "olive"
zoom_overlay.line_width = 3
zoom_overlay.line_dash = "solid"
zoom_overlay.fill_color = None
plot.add_tile(STAMEN_TONER_LABELS)
return plot
from bokeh.models import WheelZoomTool, PanTool
from bokeh.models import ImageSource, WMTSTileSource
# create plot object
title = 'Dynamic Map: National Land Cover Dataset'
x_range = Range1d(start=-15473429, end=2108550)
y_range = Range1d(start=-6315661, end=7264686)
p = Plot(x_range=x_range, y_range=y_range, plot_height=700, plot_width=700, title=title)
p.background_fill = "black"
p.add_tools(WheelZoomTool(), PanTool())
# add base layer
tile_options = {}
tile_options['url'] = 'http://tile.stamen.com/toner/{Z}/{X}/{Y}.png'
tile_source = WMTSTileSource(**tile_options)
p.add_tile(tile_source)
# add dynamic data layer
# National Land Cover Dataset (http://www.mrlc.gov/nlcd2011.php)
service_url = 'http://raster.nationalmap.gov/arcgis/rest/services/LandCover/USGS_EROS_LandCover_NLCD/MapServer/export?'
service_url += 'bbox={XMIN},{YMIN},{XMAX},{YMAX}&bboxSR=102100&size={HEIGHT}%2C{WIDTH}&imageSR=102100&format=png32&transparent=true&f=image'
image_source_options = {}
image_source_options['url'] = service_url
image_source = ImageSource(**image_source_options)
p.add_dynamic_image(image_source)
# create labels layer
tile_label_options = {}
tile_label_options['url'] = 'http://tile.stamen.com/toner-labels/{Z}/{X}/{Y}.png'
tile_label_source = WMTSTileSource(**tile_label_options)
p.add_tile(tile_label_source, **dict(render_parents=True))
