def _get_provincial_map(
plot_width, source, tibet_source, legend_data, fill_color,
line_color='black', line_width=0.5, tooltip_text=''
):
p_map = get_map_plot(plot_width)
provinces = Patches(
xs='xs',
ys='ys',
fill_color=fill_color,
line_color=line_color,
line_width=line_width,
line_join='round',
)
pr = p_map.add_glyph(source, provinces)
tibet = Patches(
xs='xs',
ys='ys',
fill_color='white',
line_color='gray',
line_dash='dashed',
line_width=0.5,
)
tr = p_map.add_glyph(tibet_source, tibet)
# Add legend
legend_source = ColumnDataSource(legend_data)
rect = Rect(
x='x',
y=map_legend_y,
height=1,
width=0.3,
fill_color='color',
line_color=None,
)
p_map.add_glyph(legend_source, rect)
# Add start val
text_start = [legend_data.vals[0][:-2]]
p_map.add_glyph(
ColumnDataSource(
dict(x=[map_legend_x], y=[map_legend_y - 3.5], text=text_start)
), Text(x='x', y='y', text='text', text_font_size='7pt', text_align='left')
)
# Add end val
text_end = [legend_data.vals[99][:-2]] # Note the 99 is dependent on legend having 100 points
if len(text_end[0]) > 5:
text_end = [legend_data.vals[99][0:5]]
p_map.add_glyph(
ColumnDataSource(
dict(x=[map_legend_x + 25], y=[map_legend_y - 3.5], text=text_end)
), Text(x='x', y='y', text='text', text_font_size='8pt', text_align='right')
)
# Add hovers
tooltips = "<span class='tooltip-text'>@name_en</span>"
tooltips = tooltips + "<span class='tooltip-text'>%s</span>" % tooltip_text
p_map.add_tools(HoverTool(tooltips=tooltips, renderers=[pr]))
tibet_tooltips = "<span class='tooltip-text'>@name_en (No data)</span>"
p_map.add_tools(HoverTool(tooltips=tibet_tooltips, renderers=[tr]))
return p_map
def mapa(dfsource, indice_label, indice_name, color_mapper, plot_width,
plot_height):
mapa_vulnerabilidade = figure(
tools="pan,box_zoom,wheel_zoom,undo,reset,hover,tap",
plot_width=plot_width,
plot_height=plot_height,
)
my_tile = bokeh.models.tiles.WMTSTileSource(
url=
'https://api.mapbox.com/styles/v1/rdferrari/cj78ytz6l51pw2so2o3bj2d09/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoicmRmZXJyYXJpIiwiYSI6ImNpcDQ4Nm12YjAwNnJsZ20zOXdmc29obmcifQ.Shb8a3P1XAV8cPWR1yGDTA'
)
# tile=mapa_vulnerabilidade.add_tile(my_tile)
mapa_vulnerabilidade.grid.grid_line_color = None
mapa_vulnerabilidade.axis[0].visible = False
mapa_vulnerabilidade.axis[1].visible = False
mapa_renderer = mapa_vulnerabilidade.patches(
'x',
'y',
source=dfsource,
fill_color={
'field': 'indice',
'transform': color_mapper
},
fill_alpha=1.0,
line_color="white",
line_width=0.5,
)
mapa_renderer.nonselection_glyph = Patches(
fill_color={
'field': 'indice',
'transform': color_mapper
},
fill_alpha=1.0,
line_color="white",
line_width=0.5,
)
mapa_renderer.selection_glyph = Patches(
fill_color={
'field': 'indice',
'transform': color_mapper
},
fill_alpha=1.0,
line_color="gray",
line_width=5.0,
line_alpha=0.8,
)
hover_mapa = mapa_vulnerabilidade.select_one(HoverTool)
hover_mapa.point_policy = "follow_mouse"
hover_mapa.tooltips = [
("Município", "@municipio"),
('Índice', '@indice{0.00}'),
('Meta Financeira', 'R$ @meta{0,0.00}'),
('Realizado', 'R$ @realizado{0,0.00}'),
]
mapa_vulnerabilidade.toolbar.logo = None
mapa_vulnerabilidade.axis[0].visible = False
mapa_vulnerabilidade.toolbar_location = 'above'
return mapa_vulnerabilidade
def altitude_profile(data):
plot = Plot(plot_width=800, plot_height=400)
plot.title.text = "%s - Altitude Profile" % name
plot.y_range.range_padding = 0
xaxis = LinearAxis(axis_label="Distance (km)")
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis(axis_label="Altitude (m)")
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker)) # x grid
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker)) # y grid
plot.add_tools(PanTool(), WheelZoomTool(), ResetTool())
X, Y = data.dist, data.alt
y0 = min(Y)
patches_source = ColumnDataSource(
dict(xs=[[X[i], X[i + 1], X[i + 1], X[i]] for i in range(len(X[:-1]))],
ys=[[y0, y0, Y[i + 1], Y[i]] for i in range(len(Y[:-1]))],
color=data.colors[:-1]))
patches = Patches(xs="xs", ys="ys", fill_color="color", line_color="color")
plot.add_glyph(patches_source, patches)
line_source = ColumnDataSource(dict(x=data.dist, y=data.alt))
line = Line(x='x', y='y', line_color="black", line_width=1)
plot.add_glyph(line_source, line)
return plot
def construct_map(source, fill_string='water_color', selected_color=ORANGE):
assert isinstance(source, ColumnDataSource), "Require ColumnDataSource"
# Plot and axes
x_start, x_end = (-18, 55)
y_start, y_end = (-35, 38)
xdr = Range1d(x_start, x_end)
ydr = Range1d(y_start, y_end)
aspect_ratio = (x_end - x_start) / (y_end - y_start)
plot_height = 600
plot_width = int(plot_height * aspect_ratio)
plot = Plot(x_range=xdr,
y_range=ydr,
title="",
plot_width=plot_width,
plot_height=plot_height,
min_border=0,
**PLOT_FORMATS)
borders = Patches(
xs='xs',
ys='ys',
fill_color=fill_string,
fill_alpha=1,
line_color="#FFFFFF",
line_width=1,
)
selected_borders = Patches(
xs='xs',
ys='ys',
fill_color=fill_string,
fill_alpha=1,
line_color=selected_color,
line_width=3,
)
plot.add_glyph(source,
borders,
selection_glyph=selected_borders,
nonselection_glyph=borders) # nopep8
return plot
def mapa(source,color_mapper,plot_width,plot_height):
mapa_fig = figure(
tools="hover",
plot_width=plot_width,
plot_height=plot_height,
)
mapa_fig.grid.grid_line_color = None
mapa_fig.axis[0].visible=False
mapa_fig.axis[1].visible=False
mapa_renderer=mapa_fig.patches(
'x', 'y', source=source,
fill_color={'field': 'indicador_selecionado', 'transform': color_mapper},
fill_alpha=1.0,
line_color="gray",
line_width=0.5,
)
mapa_renderer.nonselection_glyph=Patches(
fill_color={'field': 'indicador_selecionado', 'transform': color_mapper},
fill_alpha=1.0,
line_color="gray",
line_width=0.5,
)
mapa_renderer.selection_glyph=Patches(
fill_color={'field': 'indicador_selecionado', 'transform': color_mapper},
fill_alpha=1.0,
line_color="gray",
line_width=2.0,
line_alpha=0.8,
)
hover_mapa = mapa_fig.select_one(HoverTool)
hover_mapa.point_policy = "follow_mouse"
hover_mapa.tooltips = [
("Centro Rede CEDES:", "@nome_universidade"),
('Indicador','@indicador_selecionado{0.00}'),
]
mapa_fig.toolbar.logo=None
mapa_fig.axis[0].visible=False
mapa_fig.toolbar_location=None
return mapa_fig
def plot_map(df, fname):
"""
Generate the heat map
"""
map_options = GMapOptions(lat=40.75,
lng=-73.9,
map_type='roadmap',
zoom=11)
API_KEY = 'AIzaSyC-4SnwvK3u2CR-zh-4zl7J_msCmDfq_Sg'
palette = PuRd[7]
palette.reverse()
color_mapper = LinearColorMapper(palette=palette)
plot = GMapPlot(
x_range=DataRange1d(),
y_range=DataRange1d(),
map_options=map_options,
api_key=API_KEY,
plot_width=1000,
plot_height=1000,
)
source = ColumnDataSource(data=dict(
lat=df['lat'].tolist(),
lng=df['lng'].tolist(),
grp=df['district'],
dur=df['duration'],
durt=df['durt'],
ct=df['ct'],
))
patches = Patches(xs='lng',
ys='lat',
fill_color={
'field': 'dur',
'transform': color_mapper
},
fill_alpha=0.7,
line_color="blue",
line_width=1.0)
plot.add_glyph(source, patches, name='patches')
hover = HoverTool(names=['patches'],
tooltips=[("Neighborhood", "@grp"),
("Avg Trip Duration", "@durt"),
("Trip Count", "@ct")])
plot.add_tools(PanTool(), WheelZoomTool(), BoxSelectTool(), hover)
output_file(fname)
return plot
def populate_glyphs(self):
self.plot.renderers = []
self.plot.tools = []
if self._show_counties:
print "showing you the counties"
#datasource = ColumnDataSource(county_data)
#apatch = Patches(xs=county_xs, ys=county_ys, fill_color='white')
#apatch = Patches(xs='xs', ys='ys', fill_color='colors', fill_alpha="alpha")
apatch = Patches(xs='xs',
ys='ys',
fill_color='thecolors',
fill_alpha='alpha')
self.plot.add_glyph(self.county_source, apatch, name='counties')
if self._show_hotels:
print "showing you the hotels"
circle2 = Circle(x="lon",
y="lat",
size=10,
fill_color="fill2",
fill_alpha=1.0,
line_color="black")
circle = Circle(x="lon",
y="lat",
size=10,
fill_color="fill",
fill_alpha=1.0,
line_color="black")
#print "source is ", self.source['lon'], self.source['lat'], self.source['f1ll']
self.plot.add_glyph(self.source,
circle2,
nonselection_glyph=circle,
name='hotels')
#county_xs, county_ys = get_some_counties()
rndr = self.plot.renderers[-1]
pan = PanTool()
wheel_zoom = WheelZoomTool()
box_select = BoxSelectTool()
box_select.renderers = [rndr]
tooltips = "@name"
tooltips = "<span class='tooltip-text'>@names</span>\n<br>"
tooltips += "<span class='tooltip-text'>Reviews: @num_reviews</span>"
hover = HoverTool(tooltips=tooltips, names=['hotels'])
tap = TapTool(names=['hotels'])
self.plot.add_tools(pan, wheel_zoom, box_select, hover, tap)
overlay = BoxSelectionOverlay(tool=box_select)
self.plot.add_layout(overlay)
def test_patches_hover_still_works_when_a_seleciton_is_preselcted(
output_file_url, selenium):
# This tests an edge case interaction when Patches (specifically) is used
# with a tool that requires hit testing e.g. HitTool AND a selection is
# pre-made on the data source driving it.
plot = Plot(x_range=Range1d(0, 100), y_range=Range1d(0, 100), min_border=0)
source = ColumnDataSource(
dict(xs=[[0, 50, 50, 0], [50, 100, 100, 50]],
ys=[[0, 0, 100, 100], [0, 0, 100, 100]],
color=['pink', 'blue']))
source.selected = {
'0d': {
'glyph': None,
'indices': []
},
'1d': {
'indices': [1]
},
'2d': {
'indices': {}
},
}
plot.add_glyph(source, Patches(xs='xs', ys='ys', fill_color='color'))
plot.add_tools(HoverTool())
plot.add_layout(LinearAxis(), 'below')
plot.add_layout(LinearAxis(), 'left')
save(plot)
selenium.get(output_file_url)
assert has_no_console_errors(selenium)
# Hover plot and test no error
canvas = selenium.find_element_by_tag_name('canvas')
actions = ActionChains(selenium)
actions.move_to_element_with_offset(canvas, 100, 100)
actions.perform()
# If this assertion fails then there were likely errors on hover
assert has_no_console_errors(selenium)
rate=[
unemployment[code] for code in us_counties if us_counties[code]
["state"] not in ["ak", "hi", "pr", "gu", "vi", "mp", "as"]
],
))
plot = Plot(min_border=0,
border_fill_color="white",
plot_width=1300,
plot_height=700)
plot.title.text = "2009 Unemployment Data"
plot.toolbar_location = None
county_patches = Patches(xs="county_xs",
ys="county_ys",
fill_color=transform("rate", cmap),
fill_alpha=0.7,
line_color="white",
line_width=0.5)
plot.add_glyph(county_source, county_patches)
state_patches = Patches(xs="state_xs",
ys="state_ys",
fill_alpha=0.0,
line_color="#884444",
line_width=2)
plot.add_glyph(state_source, state_patches)
cbar = ColorBar(color_mapper=cmap, location=(0, 0))
plot.add_layout(cbar, 'left')
doc = Document()
def make_patches_plot(x_range, y_range, source):
with make_plot(x_range, y_range, source) as plot:
glyph = Patches(xs='xs', ys='ys', fill_color='value', fill_alpha=0.8, line_color='#CCCCCC', line_alpha=0.8)
plot.add_glyph(source, glyph)
return plot
plot_height=300,
min_border=0,
title="Hover and tap discontinuous patches.")
patches_dis_data = pd.DataFrame(
{
'xs': [[0, 49, 49, 0, NAN, 51, 89, 89, 51], [90, 100, 100, 90],
[92, 98, 98, 92]],
'ys': [[0, 0, 80, 80, NAN, 0, 0, 90, 90], [0, 0, 100, 100],
[20, 20, 90, 90]],
'value':
['I am one object split in two', 'I am wheat', 'I am steelblue'],
'fill_color': ['firebrick', 'wheat', 'steelblue']
}, )
plot_patches_dis = Plot(**PLOT_FORMATS)
plot_patches_dis.add_glyph(
ColumnDataSource(patches_dis_data),
Patches(
xs='xs',
ys='ys',
fill_color='fill_color',
line_color=value('wheat'),
))
plot_patches_dis.add_tools(HoverTool(tooltips='@value'))
plot_patches_dis.add_tools(TapTool())
filename = '2376_hover_on_discontinuous_patches.html'
output_file(filename, title='Discontinuous Patches', mode='relative-dev')
save(plot_patches_dis)
view(filename)
print("HERE?")
# Have to add the patches after the tiles
input_areas = p.patches('xs',
'ys',
source=geosource,
fill_color='red',
line_color='gray',
line_width=0.25,
fill_alpha=.3)
taptool = TapTool(renderers=[input_areas])
hovertool = HoverTool(renderers=[input_areas], tooltips=[('Site', '@name')])
selected_patches = Patches(fill_color="yellow",
fill_alpha=.8,
line_width=1,
line_color="green")
input_areas.selection_glyph = selected_patches
geosource.selected.on_change('indices', tapselect_handler)
print("HERE?")
# CustomJS(code="""
# // comment....
# console.log("Somewhere to stop!");
# """)
# Create hover tool
p.add_tools(taptool, hovertool)
xpts = np.array([-.09, -.12, .0, .12, .09])
ypts = np.array([-.1, .02, .1, .02, -.1])
source = ColumnDataSource(
dict(
xs=[xpts * (1 + i / 10.0) + xx for i, xx in enumerate(x)],
ys=[ypts * (1 + i / 10.0) + yy for i, yy in enumerate(y)],
))
plot = Plot(title=None,
plot_width=300,
plot_height=300,
min_border=0,
toolbar_location=None)
glyph = Patches(xs="xs", ys="ys", fill_color="#fb9a99")
plot.add_glyph(source, glyph)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
curdoc().add_root(plot)
show(plot)
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
y="y",
w=0.4,
h=0.4,
url=dict(value="https://static.bokeh.org/logos/logo.png"),
anchor="center")),
("line", Line(x="x", y="y", line_color="#F46D43")),
("multi_line",
MultiLine(xs="xs", ys="ys", line_color="#8073AC", line_width=2)),
("multi_polygons",
MultiPolygons(xs="xsss",
ys="ysss",
line_color="#8073AC",
fill_color="#FB9A99",
line_width=2)),
("patch", Patch(x="x", y="y", fill_color="#A6CEE3")),
("patches", Patches(xs="xs", ys="ys", fill_color="#FB9A99")),
("quad",
Quad(left="x", right="xp01", top="y", bottom="ym01",
fill_color="#B3DE69")),
("quadratic",
Quadratic(x0="x",
y0="y",
x1="xp02",
y1="y",
cx="xp01",
cy="yp01",
line_color="#4DAF4A",
line_width=3)),
("ray",
Ray(x="x",
y="y",
renderer = p.patches('x',
'y',
source=source,
fill_color={
'field': 'veges',
'transform': color_mapper
},
selection_line_color="blue",
fill_alpha=0.7,
line_color="white",
line_width=0.5)
selected_patches = Patches(fill_color={
'field': 'veges',
'transform': color_mapper
},
fill_alpha=0.7,
line_color="white",
line_width=2)
nonselected_patches = Patches(fill_color={
'field': 'veges',
'transform': color_mapper
},
fill_alpha=0.3,
line_color="white",
line_width=0.5)
renderer.selection_glyph = selected_patches
renderer.nonselection_glyph = nonselected_patches
hover = p.select_one(HoverTool)
