Python GMapPlot.add_layout方法代码示例

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
def trail_map(data):
    lon = (min(data.lon) + max(data.lon))/2
    lat = (min(data.lat) + max(data.lat))/2

    map_options = GMapOptions(lng=lon, lat=lat, zoom=13)
    plot = GMapPlot(title="%s - Trail Map" % title, map_options=map_options, plot_width=800, plot_height=800)

    xaxis = LinearAxis()
    plot.add_layout(xaxis, 'below')

    yaxis = LinearAxis()
    plot.add_layout(yaxis, 'left')

    xgrid = Grid(plot=plot, dimension=0, ticker=xaxis.ticker, grid_line_dash="dashed", grid_line_color="gray")
    ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker, grid_line_dash="dashed", grid_line_color="gray")
    plot.renderers.extend([xgrid, ygrid])

    plot.add_tools(PanTool(), WheelZoomTool(), ResetTool(), BoxSelectTool())

    line_source = ColumnDataSource(dict(x=data.lon, y=data.lat, dist=data.dist))

    line = Line(x="x", y="y", line_color="blue", line_width=2)
    plot.add_glyph(line_source, line)

    plot.x_range = DataRange1d(sources=[line_source.columns("x")])
    plot.y_range = DataRange1d(sources=[line_source.columns("y")])

    return plot

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
    def create_map_plot(self):
        lat=39.8282
        lng=-98.5795
        zoom=6
        xr = Range1d()
        yr = Range1d()
        x_range = xr
        y_range = yr
        #map_options = GMapOptions(lat=39.8282, lng=-98.5795, zoom=6)
        map_options = GMapOptions(lat=lat, lng=lng, zoom=zoom)
        #map_options = GMapOptions(lat=30.2861, lng=-97.7394, zoom=15)
        plot = GMapPlot(
            x_range=x_range, y_range=y_range,
            map_options=map_options,
            plot_width=680,
            plot_height=600,
            title=" "
        )
        plot.map_options.map_type="hybrid"
        xaxis = LinearAxis(axis_label="lon", major_tick_in=0, formatter=NumeralTickFormatter(format="0.000"))
        plot.add_layout(xaxis, 'below')
        yaxis = LinearAxis(axis_label="lat", major_tick_in=0, formatter=PrintfTickFormatter(format="%.3f"))
        plot.add_layout(yaxis, 'left')

        self.plot = plot

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
def drawMap(title, datas):
    """
    color : [(lat, lon)]
    """ 
    lat = []
    lon = []
    c = []
    
    for color in datas:
        c_lat, c_lon = zip(*datas[color])
        #print (c_lat)
        lat.extend(map(float, c_lat))
        lon.extend(map(float, c_lon))
        c.extend([color]*len(datas[color]))
        
    center_lat = np.median(lat)
    center_lon = np.median(lon)

    x_range = Range1d()
    y_range = Range1d()
    
    source = ColumnDataSource(
        data=dict(
            lat=lat,
            lon=lon,
            fill=c
        )
    )

    map_options = GMapOptions(lat=center_lat, lng=center_lon, map_type="roadmap", zoom=11)
    plot = GMapPlot(
        x_range=x_range, y_range=y_range,
        map_options=map_options,
        title=title
    )

    # Glyphs (dots on graph)
    circle = Circle(x="lon", y="lat", size=6, line_width=0, fill_color="fill", fill_alpha=0.5, line_alpha=0.0)
    plot.add_glyph(source, circle)

    #Navigation
    pan = PanTool()
    wheel_zoom = WheelZoomTool()
    box_select = BoxSelectTool()

    plot.add_tools(pan, wheel_zoom, box_select)
    overlay = BoxSelectionOverlay(tool=box_select)
    plot.add_layout(overlay)

    return display.HTML(file_html(plot, INLINE, "Google Maps Example"))

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
def create_village_map(survey):
    s = survey[["village_name", "_gps_point_latitude" , "_gps_point_longitude"]]
    g = s.groupby("village_name")
    mean = g.agg([np.mean])
    mean = mean.reset_index()
    mean.columns = ['_'.join(col).strip() for col in mean.columns.values]
    mean.columns = ['vn', 'lat_mean', 'lon_mean']
    x_range = Range1d()
    y_range = Range1d()
    map_options = GMapOptions(lat= -2.588, lng=140.5170, zoom=11)
    plot = GMapPlot(
        x_range = x_range,
        y_range = y_range,
        map_options=map_options,
        title = "Lake Sentani"
    )
    dot_source = ColumnDataSource(
        data=dict(
            lat = [float(x) for x in survey['_gps_point_latitude']],
            lon = [float(y) for y in survey['_gps_point_longitude']],
            uuid = [str(x) for x in survey['_uuid']],
            vName = [str(x) for x in survey['village_name']],
            size = [.0001 for x in survey['_uuid']],
        )
    )
    plot.map_options.map_type="terrain"
    circle = Circle(x='lon', y='lat', radius='size', fill_color = 'red', fill_alpha = 0.9)
    plot.add_glyph(dot_source, circle)
    text_source = ColumnDataSource(
        data=dict(
            vn = [str(x) for x in mean['vn']],
            lat = [float(x) for x in mean['lat_mean']],
            lon = [float(x) for x in mean['lon_mean']]
        )
    )
    text = Text(x="lon", y="lat", text="vn", text_color="maroon")
    plot.add_glyph(text_source, text)
    reset = ResetTool()
    pan = PanTool()
    wheel_zoom = WheelZoomTool()
    box_zoom = BoxZoomTool()

    plot.add_tools(pan, wheel_zoom, box_zoom, reset)

    xaxis = LinearAxis(axis_label="lon.", major_tick_in=0)
    plot.add_layout(xaxis, 'below')
    yaxis = LinearAxis(axis_label="lat.", major_tick_in=0)
    plot.add_layout(yaxis, 'left')
    return plot

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
    def create_map_plot(self):
        lat=39.8282
        lng=-98.5795
        zoom=6
        xr = Range1d()
        yr = Range1d()
        x_range = xr
        y_range = yr
        #map_options = GMapOptions(lat=39.8282, lng=-98.5795, zoom=6)
        map_options = GMapOptions(lat=lat, lng=lng, zoom=zoom)
        #map_options = GMapOptions(lat=30.2861, lng=-97.7394, zoom=15)
        plot = GMapPlot(
            x_range=x_range, y_range=y_range,
            map_options=map_options,
            title = "Hotel Review Explorer",
            plot_width=680,
            plot_height=600
        )
        plot.map_options.map_type="hybrid"
        xaxis = LinearAxis(axis_label="lon", major_tick_in=0, formatter=NumeralTickFormatter(format="0.000"))
        plot.add_layout(xaxis, 'below')
        yaxis = LinearAxis(axis_label="lat", major_tick_in=0, formatter=PrintfTickFormatter(format="%.3f"))
        plot.add_layout(yaxis, 'left')

        #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="@num_reviews")
        #hover = HoverTool(tooltips="@names")
        #hover = HoverTool(tooltips=tooltips)
        #tap = TapTool()
        #plot.add_tools(pan, wheel_zoom, box_select, hover, tap)
        #plot.add_tools(hover, tap)
        #overlay = BoxSelectionOverlay(tool=box_select)
        #plot.add_layout(overlay)
        #plot.add_glyph(self.source, circle)
        #county_xs, county_ys = get_some_counties()
        #apatch = Patch(x=county_xs, y=county_ys, fill_color=['white']*len(county_xs))
        #plot.add_glyph(apatch)
        self.plot = plot

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
def trail_map(data):
    lon = (min(data.lon) + max(data.lon)) / 2
    lat = (min(data.lat) + max(data.lat)) / 2

    map_options = GMapOptions(lng=lon, lat=lat, zoom=13)
    plot = GMapPlot(plot_width=800, plot_height=800, map_options=map_options, api_key=API_KEY)
    plot.title.text = "%s - Trail Map" % name
    plot.x_range = Range1d()
    plot.y_range = Range1d()
    plot.add_tools(PanTool(), WheelZoomTool(), ResetTool())

    line_source = ColumnDataSource(dict(x=data.lon, y=data.lat, dist=data.dist))
    line = Line(x="x", y="y", line_color="blue", line_width=2)
    plot.add_glyph(line_source, line)

    if plot.api_key == "GOOGLE_API_KEY":
        plot.add_layout(Label(x=240, y=700, x_units='screen', y_units='screen',
                              text='Replace GOOGLE_API_KEY with your own key',
                              text_color='red'))

    return plot

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
)

source = ColumnDataSource(
    data=dict(
        lat=[30.2861, 30.2855, 30.2869],
        lon=[-97.7394, -97.7390, -97.7405],
        fill=['orange', 'blue', 'green']
    )
)

circle = Circle(x="lon", y="lat", size=15, fill_color="fill", line_color="black")
plot.add_glyph(source, circle)

pan = PanTool()
wheel_zoom = WheelZoomTool()
box_select = BoxSelectTool()

plot.add_tools(pan, wheel_zoom, box_select)
overlay = BoxSelectionOverlay(tool=box_select)
plot.add_layout(overlay)

doc = Document()
doc.add_root(plot)

if __name__ == "__main__":
    filename = "maps.html"
    with open(filename, "w") as f:
        f.write(file_html(doc, INLINE, "Google Maps Example"))
    print("Wrote %s" % filename)
    view(filename)

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
)
plot.map_options.map_type="hybrid"

source = ColumnDataSource(data=data)

circle = Circle(x="lon", y="lat", size=10, line_color=None, fill_color='cyan', fill_alpha=0.1)
plot.add_glyph(source, circle)

pan = PanTool()
wheel_zoom = WheelZoomTool()
box_select = BoxSelectTool()

plot.add_tools(pan, wheel_zoom, box_select)

xaxis = LinearAxis(axis_label="lon", major_tick_in=0, formatter=NumeralTickFormatter(format="0.000"))
plot.add_layout(xaxis, 'below')

yaxis = LinearAxis(axis_label="lat", major_tick_in=0, formatter=PrintfTickFormatter(format="%.3f"))
plot.add_layout(yaxis, 'left')

overlay = BoxSelectionOverlay(tool=box_select)
plot.add_layout(overlay)

doc = Document()
doc.add(plot)


if __name__ == "__main__":
    filename = "maps_cities.html"
    with open(filename, "w") as f:
        f.write(file_html(doc, INLINE, "Google Maps All US cities Example"))

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
map_options = GMapOptions(lat=15, lng=0, zoom=2)

plot = GMapPlot(
    x_range=x_range,
    y_range=y_range,
    plot_width=1000,
    plot_height=500,
    map_options=map_options,
    api_key=API_KEY,
    webgl=True,
)

if plot.api_key == "GOOGLE_API_KEY":
    plot.add_layout(Label(x=500, y=320, x_units='screen', y_units='screen',
                          text='Replace GOOGLE_API_KEY with your own key',
                          text_color='red', text_align='center'))

plot.title.text = "Cities of the world with a population over 5,000 people."

circle = Circle(x="lng", y="lat", size=5, line_color=None, fill_color='firebrick', fill_alpha=0.2)
plot.add_glyph(ColumnDataSource(data), circle)
plot.add_tools(PanTool(), WheelZoomTool())

doc = Document()
doc.add_root(plot)

if __name__ == "__main__":
    doc.validate()
    filename = "maps_cities.html"
    with open(filename, "w") as f:

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
from bokeh.resources import INLINE

# JSON style string taken from: https://snazzymaps.com/style/1/pale-dawn
map_options = GMapOptions(lat=30.2861, lng=-97.7394, map_type="roadmap", zoom=13, styles="""
[{"featureType":"administrative","elementType":"all","stylers":[{"visibility":"on"},{"lightness":33}]},{"featureType":"landscape","elementType":"all","stylers":[{"color":"#f2e5d4"}]},{"featureType":"poi.park","elementType":"geometry","stylers":[{"color":"#c5dac6"}]},{"featureType":"poi.park","elementType":"labels","stylers":[{"visibility":"on"},{"lightness":20}]},{"featureType":"road","elementType":"all","stylers":[{"lightness":20}]},{"featureType":"road.highway","elementType":"geometry","stylers":[{"color":"#c5c6c6"}]},{"featureType":"road.arterial","elementType":"geometry","stylers":[{"color":"#e4d7c6"}]},{"featureType":"road.local","elementType":"geometry","stylers":[{"color":"#fbfaf7"}]},{"featureType":"water","elementType":"all","stylers":[{"visibility":"on"},{"color":"#acbcc9"}]}]
""")

# Google Maps now requires an API key. You can find out how to get one here:
# https://developers.google.com/maps/documentation/javascript/get-api-key
API_KEY = "GOOGLE_API_KEY"

plot = GMapPlot(map_options=map_options, api_key=API_KEY)

if plot.api_key == "GOOGLE_API_KEY":
    plot.add_layout(Label(x=140, y=400, x_units='screen', y_units='screen',
                          text='Replace GOOGLE_API_KEY with your own key',
                          text_color='red'))

plot.title.text = "Austin"

source = ColumnDataSource(
    data=dict(
        lat=[30.2861, 30.2855, 30.2869],
        lon=[-97.7394, -97.7390, -97.7405],
        fill=['orange', 'blue', 'green']
    )
)

circle = Circle(x="lon", y="lat", size=15, fill_color="fill", line_color="black")
plot.add_glyph(source, circle)

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
def get_gmap_points():
    '''Try to overlay a grid of points.  This grid needs to scale with the
    plot zoom, and move with the pan.  Select points from poly, box, or lasso
    Construct convex hull from points, overlay on plot
    input hull coords to osm and download map
        # plot extent?
        https://github.com/bokeh/bokeh/blob/7cc925df6676e959f02d0842c5abb8cbdfab9df7/bokehjs/src/coffee/common/gmap_plot.coffee    
    !! Can't figure out what plot range is upon zoom! !!
    
    Could also just use:
    https://www.openstreetmap.org/export#map=13/38.8935/-77.0702
    '''

    # GOOGLE MAP
    mapzoom = 14
    x_mid, y_mid = -77.046998, 38.888214    # Washington DC
    map_options = GMapOptions(lat=y_mid, lng=x_mid, zoom=mapzoom) 
    mapzoom = 14
    
    #def center_coords():
    #    '''center map?'''
    #    global x_mid, y_mid
    #    return
    
    title = 'Select Polygon'
    htmlout = 'tst.html'
    show = True

    #################
    # Box Select
    source_rect_sel = ColumnDataSource(data=dict(x=[], y=[], width=[], height=[]))
    
    rect_callback = Callback(args=dict(source=source_rect_sel), code="""
        // get data source from Callback args
        var data = source.get('data');
    
        /// get BoxSelectTool dimensions from cb_data parameter of Callback
        var geometry = cb_data['geometry'];
    
        /// calculate Rect attributes
        var width = geometry['x1'] - geometry['x0'];
        var height = geometry['y1'] - geometry['y0'];
        var x = geometry['x0'] + width/2;
        var y = geometry['y0'] + height/2;
    
        /// update data source with new Rect attributes (if we want multiple rects)
        ///data['x'].push(x);
        ///data['y'].push(y);
        ///data['width'].push(width);
        ///data['height'].push(height);
        
        /// replace values
        data['x'] = [x];
        data['y'] = [y];
        data['width'] = [width];
        data['height'] = [height];
        
        // trigger update of data source
        source.trigger('change');
    """)
    
    box_select = BoxSelectTool(callback=rect_callback)
    #################
    
    # get gmap
    # https://github.com/bokeh/bokeh/blob/master/examples/glyphs/maps.py
    #https://github.com/bokeh/bokeh/blob/master/examples/glyphs/trail.py
    # set map height, options
    plot_height = int(0.75*plot_width)   
    map_options = GMapOptions(lat=y_mid, lng=x_mid, zoom=mapzoom)   

    x_range = Range1d()
    y_range = Range1d()           
    plot = GMapPlot(x_range=x_range, y_range=y_range, 
                    map_options=map_options, 
                    plot_height=plot_height, plot_width=plot_width, 
                    title=title) 
    plot.map_options.map_type='hybrid'
    # !! Reset Tool goes to lat, lon = 0,0 !! 
    plot.add_tools(PanTool(), WheelZoomTool(), BoxZoomTool(), box_select,
                   PolySelectTool(), 
                   LassoSelectTool(),
                   PreviewSaveTool(), ResizeTool())#, ResetTool())   

    # add axes          
    xaxis = LinearAxis(axis_label='Longitude')
    plot.add_layout(xaxis, 'below')
    yaxis = LinearAxis(axis_label='Latitude')
    plot.add_layout(yaxis, 'left')
    
    # add grid
    xgrid = Grid(plot=plot, dimension=0, ticker=xaxis.ticker, \
            grid_line_dash="dashed", grid_line_color="gray")
    ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker, \
            grid_line_dash="dashed", grid_line_color="gray")
    plot.renderers.extend([xgrid, ygrid])  

    # add rect
    rect = Rect(x='x',
            y='y',
#.........这里部分代码省略.........

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
def country_map(business, business_subset):
	my_category = session['category_name']
	if session['category_or_city'] == 'Category_typed':
		my_category = session['category_typed']
	lat_avg = business_subset['latitude'].mean()
	lon_avg = business_subset['longitude'].mean()
	my_lat = business_subset['latitude']
	my_lon = business_subset['longitude']
	my_stars =  business_subset['stars']
	star_avg = business_subset['stars'].mean()

	my_colors_stars = list(map(map_star, my_stars))
	my_lat = np.array(my_lat)
	my_lon = np.array(my_lon)
	my_stars = np.array(my_stars)

	map_options = GMapOptions(lat=lat_avg, lng=lon_avg, map_type="roadmap", zoom=4)

	plot = GMapPlot(
   	 x_range=DataRange1d(), y_range=DataRange1d(), map_options=map_options, api_key=API_KEY
	)
	plot.title.text = 'Locations and Star ratings of ' + my_category + ' category. Average rating = ' + str(star_avg)
	my_colors = my_colors_stars
	source = ColumnDataSource( data=dict(lat = my_lat, lon = my_lon, stars = my_stars, the_colors=my_colors))
	circle = Circle(x="lon", y="lat", size=5, fill_color="the_colors", fill_alpha=0.2, line_color=None)
	plot.add_glyph(source, circle)
	label1 = Label(x=410, y=530, x_units='screen', y_units='screen', text='green: 5 stars', render_mode='css', border_line_color='white', background_fill_color='white')
	label2 = Label(x=410, y=510, x_units='screen', y_units='screen', text='blue:  4 stars', render_mode='css', border_line_color='white', background_fill_color='white')
	label3 = Label(x=410, y=490, x_units='screen', y_units='screen', text='yellow: 3 stars', render_mode='css', border_line_color='white', background_fill_color='white')
	label4 = Label(x=410, y=470, x_units='screen', y_units='screen', text='red:  < 2 stars', render_mode='css', border_line_color='white', background_fill_color='white')
	plot.add_layout(label1)
	plot.add_layout(label2)
	plot.add_layout(label3)
	plot.add_layout(label4)
	plot.add_tools(PanTool(), WheelZoomTool(), BoxSelectTool())

	#################################################
	#################################################
	
	lat_avg = business['latitude'].mean()
	lon_avg = business['longitude'].mean()
	my_lat = business['latitude']
	my_lon = business['longitude']
	my_lat = np.array(my_lat)
	my_lon = np.array(my_lon)
	
	my_attributes = business['attributes_combined'].tolist()
	my_colors_att = list(map(map_attribute, my_attributes))
	my_colors = my_colors_att
		
	plot2 = GMapPlot(
   	 x_range=DataRange1d(), y_range=DataRange1d(), map_options=map_options, api_key=API_KEY
	)
	plot2.title.text = 'Locations of Businesses with other Various Attributes'
	source = ColumnDataSource( data=dict(lat = my_lat, lon = my_lon, stars = my_stars, the_colors=my_colors))
	circle = Triangle(x="lon", y="lat", size=5, fill_color="the_colors", fill_alpha=0.2, line_color=None)
	plot2.add_glyph(source, circle)
	label1 = Label(x=410, y=530, x_units='screen', y_units='screen', text='green: casual', render_mode='css', border_line_color='white', background_fill_color='white')
	label2 = Label(x=410, y=510, x_units='screen', y_units='screen', text='blue:  upscale', render_mode='css', border_line_color='white', background_fill_color='white')
	label3 = Label(x=410, y=490, x_units='screen', y_units='screen', text='yellow: touristy', render_mode='css', border_line_color='white', background_fill_color='white')
	label4 = Label(x=410, y=470, x_units='screen', y_units='screen', text='red:  hipster', render_mode='css', border_line_color='white', background_fill_color='white')
	plot2.add_layout(label1)
	plot2.add_layout(label2)
	plot2.add_layout(label3)
	plot2.add_layout(label4)
	plot2.add_tools(PanTool(), WheelZoomTool(), BoxSelectTool())

	
	plots = row(plot, plot2)
	script, div = components(plots)
	return script, div

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
def city_map(business):
	my_city = session['city_name']
	
	business_subset = business[business['city'] == my_city]
	
	lat_avg = business_subset['latitude'].mean()
	lon_avg = business_subset['longitude'].mean()
	my_lat = business_subset['latitude']
	my_lon = business_subset['longitude']
	my_stars =  business_subset['stars']
	star_avg = business_subset['stars'].mean()

	my_colors_stars = list(map(map_star, my_stars))
	my_lat = np.array(my_lat)
	my_lon = np.array(my_lon)
	my_stars = np.array(my_stars)

	
	my_categories = business_subset['categories'].tolist()
	my_colors_cuisine = list(map(map_cuisine, my_categories))

	map_options = GMapOptions(lat=lat_avg, lng=lon_avg, map_type="roadmap", zoom=11)

	plot = GMapPlot(
   	 x_range=DataRange1d(), y_range=DataRange1d(), map_options=map_options, api_key=API_KEY
	)
	plot.title.text = my_city + ' business ratings. Average rating out of five stars = ' + str(star_avg)
	my_colors = my_colors_stars
	source = ColumnDataSource( data=dict(lat = my_lat, lon = my_lon, stars = my_stars, the_colors=my_colors))
	circle = Circle(x="lon", y="lat", size=5, fill_color="the_colors", fill_alpha=0.2, line_color=None)
	plot.add_glyph(source, circle)
	label1 = Label(x=410, y=530, x_units='screen', y_units='screen', text='green:  5 stars', render_mode='css', border_line_color='white', background_fill_color='white')
	label2 = Label(x=410, y=510, x_units='screen', y_units='screen', text='blue:   4 stars', render_mode='css', border_line_color='white', background_fill_color='white')
	label3 = Label(x=410, y=490, x_units='screen', y_units='screen', text='yellow: 3 stars', render_mode='css', border_line_color='white', background_fill_color='white')
	label4 = Label(x=410, y=470, x_units='screen', y_units='screen', text='red:  < 2 stars', render_mode='css', border_line_color='white', background_fill_color='white')
	plot.add_layout(label1)
	plot.add_layout(label2)
	plot.add_layout(label3)
	plot.add_layout(label4)
	plot.add_tools(PanTool(), WheelZoomTool(), BoxSelectTool())

	plot2 = GMapPlot(
   	 x_range=DataRange1d(), y_range=DataRange1d(), map_options=map_options, api_key=API_KEY
	)
	plot2.title.text = my_city + ' locations of various cuisines'
	my_colors = my_colors_cuisine
	source = ColumnDataSource( data=dict(lat = my_lat, lon = my_lon, stars = my_stars, the_colors=my_colors))
	circle = Triangle(x="lon", y="lat", size=5, fill_color="the_colors", fill_alpha=0.2, line_color=None)
	plot2.add_glyph(source, circle)
	label1 = Label(x=410, y=530, x_units='screen', y_units='screen', text='green: American', render_mode='css', border_line_color='white', background_fill_color='white')
	label2 = Label(x=410, y=510, x_units='screen', y_units='screen', text='blue:  Mexican', render_mode='css', border_line_color='white', background_fill_color='white')
	label3 = Label(x=410, y=490, x_units='screen', y_units='screen', text='red: Italian', render_mode='css', border_line_color='white', background_fill_color='white')
	label4 = Label(x=410, y=470, x_units='screen', y_units='screen', text='yellow: Chinese', render_mode='css', border_line_color='white', background_fill_color='white')
	label5 = Label(x=410, y=450, x_units='screen', y_units='screen', text='brown: Japanese', render_mode='css', border_line_color='white', background_fill_color='white')
	plot2.add_layout(label1)
	plot2.add_layout(label2)
	plot2.add_layout(label3)
	plot2.add_layout(label4)
	plot2.add_layout(label5)
	plot2.add_tools(PanTool(), WheelZoomTool(), BoxSelectTool())

	plots = row(plot, plot2)
	script, div = components(plots)
	return script, div

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]
prost= ColumnDataSource(data=dict(lat=lat37,lon=lon37,cat=sfcat37['Category'],date=sfcat37['Dates']))
SUICIDE=ColumnDataSource(data=dict(lat=lat34,lon=lon34,cat=sfcat34['Category'],date=sfcat34['Dates']))

circle = Circle(x="lon", y="lat", size=4, fill_color="blue", fill_alpha=0.5, line_color=None)
circle2 = Circle(x="lon", y="lat", size=4, fill_color='red', fill_alpha=0.5, line_color=None)
circle34 = Circle(x="lon", y="lat", size=4, fill_color='lime', fill_alpha=0.5, line_color=None)

dui_plot=plot.add_glyph(dui, circle)
prost_plot=plot.add_glyph(prost, circle2)
suicide_plot=plot.add_glyph(SUICIDE, circle34)

plot.add_tools(PanTool(), WheelZoomTool(), BoxSelectTool(),PreviewSaveTool(),HoverTool())
hover = plot.select_one(HoverTool)
hover.point_policy = "follow_mouse"
hover.tooltips = [("Category", "@cat"),("Date", "@date"),("(Long, Lat)", "($x, $y)"),]
plot.add_layout(Legend(legends=[("PROSTITUTION", [prost_plot]),("DUI", [dui_plot]),("SUICIDE", [suicide_plot])]))

output_notebook()
#output_file("gmap_plot.html")
#show(plot)
#I don't show it because the file gets too big for displaying in my Git!


# ### Now Lets plot the weekly probability density distribution of these 3 crime categories. 
# I used the data the whole city, and all years and months, just look at the occurence day and time of each crime. 
# The result is interesting. Apparently, each day DUI peaks after midnight with the largest probability at Friday and Saturday. However, The peak of prostitution is during the week! The suicide has lower statistic. We still can see the peridoc behavior though. It is kind of surprising (to me at least) that the peak of the suicide is not during the dark hours! 

# In[44]:

p1 = figure(width=900,height=660)#x_axis_type = "datetime")
p1.xaxis.axis_label ='Week Day'

# 需要导入模块: from bokeh.models import GMapPlot [as 别名]
# 或者: from bokeh.models.GMapPlot import add_layout [as 别名]

#.........这里部分代码省略.........
            app.timeofday = app.timeofday +24
        
        if app.direction == "from":
            n0 = network_df[app.timeofday][my_center_id]
            n0.sort(ascending=False,axis=1)
            n0 = n0.irow(range(20))
        elif app.direction == "to":
            n0 = network_df[app.timeofday][:,my_center_id]
            n0.sort(ascending=False,axis=1)
            n0 = n0.irow(range(20))
        
        #widths = [9,8,8,7,6,5,4,3,2,1]
        ww = 0.
        for index, row in n0.iteritems():
            ww += 0.3
            #p_i = get_center_coordinates(my_center_id,x_min=x_min, x_max=x_max, y_min=y_min, y_max=y_max,mesh_space=mesh_space)
            p_f = get_center_coordinates(index,x_min=x_min, x_max=x_max, y_min=y_min, y_max=y_max,mesh_space=mesh_space)

            ss = ColumnDataSource(
            data=dict(
                lat=[my_latitude,p_f[1]],
                lon=[my_longitude,p_f[0]],
            ))
            line = Line(x="lon", y="lat", line_width=ww)
            plot.add_glyph(ss, line)
            
        pan = PanTool()
        wheel_zoom = WheelZoomTool()
        box_select = BoxSelectTool()
        
        plot.add_tools(pan, wheel_zoom, box_select)
        
        #xaxis = LinearAxis(axis_label="lat", major_tick_in=0, formatter=NumeralTickFormatter(format="0.000"))
        #plot.add_layout(xaxis, 'below')
        
        #yaxis = LinearAxis(axis_label="lon", major_tick_in=0, formatter=PrintfTickFormatter(format="%.3f"))
        #plot.add_layout(yaxis, 'left')
        
        overlay = BoxSelectionOverlay(tool=box_select)
        plot.add_layout(overlay)
                
        app.script, app.div = components(plot)

        ##################################################
        ##################################################
            
        
        ##################################################
        ########Bokeh FIG block##############################
    
        # select the tools we want
        TOOLS="pan,wheel_zoom,box_zoom,reset,save"
    
        #print datetime.datetime(hour=int(33)/2, minute=int(33)%2*30)
        #print data_df.index
        
        p1 = figure(tools=TOOLS, plot_width=400, plot_height=400, x_axis_label='Time',y_axis_label='Number of trips')#,x_axis_type='datetime')
        p1.line((data_df.index)/2, data_df['number_of_pickups_at_time_slot'],line_width=2, color="blue", legend="Total number of pickups in NYC in a typical day")
        p1.line((data_df.index)/2, data_df['number_of_dropoffs_at_time_slot'],line_width=2, color="red",legend="Total number of dropoffs in NYC in a typical day")
        #p1.circle(dates, closing_prices, fill_color="red", size=6)

        #plots = {'Red': p1}
    
        #script_graph1, div_graph1 = components(plots)        
        #app.script_graph1 = script_graph1
        #app.div_graph1 = div_graph1.values()[0]
        ##################################################
        
        ##################################################

        ###ADD plot of NUMBER OF TRIPS (PICK UP AND DROPOFF FROM LOCATION)
        pickup_count = [0 for i in range(48)]
        dropoff_count = [0 for i in range(48)]
        for ind in network_df.index.levels[0]:
            try:
                pickup_count[ind] = network_df[ind][my_center_id].count()
            except KeyError:
                pass
            try:
                dropoff_count[ind] = network_df[ind][:,my_center_id].count()
            except KeyError:
                continue
        
        TOOLS="pan,wheel_zoom,box_zoom,reset,save"
                
        p2 = figure(tools=TOOLS, plot_width=400, plot_height=400, x_axis_label='Time',y_axis_label='Number of trips')#,x_axis_type='datetime')
        p2.line(np.array(range(48))/2, pickup_count,line_width=2, color="blue", legend="Average pickups from your location")
        p2.line(np.array(range(48))/2, dropoff_count,line_width=2, color="red",legend="Average dropoffs at your location")
        #p1.circle(dates, closing_prices, fill_color="red", size=6)
        
        
        #plots2 = {'Red': p2}
        
        plots1and2 = gridplot([[p1, p2]])
        
        script_graph2, div_graph2 = components(plots1and2)        
        app.script_graph2 = script_graph2
        app.div_graph2 = div_graph2
        
        return redirect('/graph_page')