def show(sample_size):
global session
global scatter_plot
global source
global pie_chart_source
global line_chart_source
global slider
DB.__init__(sample_size)
min_time = DB.min_time()
max_time = DB.max_time()
print min_time
print min_time
xs, ys, color, time = DB.get_current()
xs = [xs[i] for i,v in enumerate(time) if time[i] == min_time]
ys = [ys[i] for i,v in enumerate(time) if time[i] == min_time]
color = [color[i] for i,v in enumerate(time) if time[i] == min_time]
time_dict = Counter(time)
pie_chart_source = ColumnDataSource(data=ChartMath.compute_color_distribution('x', 'y', 'color', color))
line_chart_source = ColumnDataSource(data=dict(x=[key for key in time_dict], y=[time_dict[key] for key in time_dict]))
source = ColumnDataSource(data=dict(x=xs, y=ys, color=color))
scatter_plot = Figure(plot_height=800,
plot_width=1200,
title="Plot of Voters",
tools="pan, reset, resize, save, wheel_zoom",
)
scatter_plot.circle('x', 'y', color='color', source=source, line_width=0, line_alpha=0.001, fill_alpha=0.5, size=15)
scatter_plot.patches('x', 'y', source=state_source, fill_alpha=0.1, line_width=3, line_alpha=1)
scatter_plot.x_range.on_change('end', update_coordinates)
line_chart = Figure(title="Distribution over Time", plot_width=350, plot_height=350)
line_chart.line(x='x', y='y', source=line_chart_source)
pie_chart_plot = Figure(plot_height=350,
plot_width=350,
title="Voter Distribution",
x_range=(-1, 1),
y_range=(-1, 1))
pie_chart_plot.wedge(x=0, y=0, source=pie_chart_source, radius=1, start_angle="x", end_angle="y", color="color")
slider = Slider(start=min_time, end=max_time, value=min_time, step=1, title="Time")
slider.on_change('value', update_coordinates)
h = hplot(scatter_plot, vplot(pie_chart_plot, line_chart))
vplot(slider, h, width=1600, height=1800)
session = push_session(curdoc())
session.show()
#script = autoload_server(scatter_plot, session_id=session.id)
session.loop_until_closed()
def update_coordinates(attrname, old, name):
global N
xbeg, xend = scatter_plot.x_range.start, scatter_plot.x_range.end
ybeg, yend = scatter_plot.y_range.start, scatter_plot.y_range.end
time_bin = slider.value
xs, ys, color, time = DB.fetch(xbeg, xend, ybeg, yend, time_bin)
if len(xs) > 0 and len(ys) > 0:
xs = [xs[i] for i,v in enumerate(time) if time[i] == time_bin]
ys = [ys[i] for i,v in enumerate(time) if time[i] == time_bin]
color = [color[i] for i,v in enumerate(time) if time[i] == time_bin]
source.data = dict(x=xs, y=ys, color=color)
pie_chart_source.data = ChartMath.compute_color_distribution('x', 'y', 'color', color)
time_dict = Counter(time)
line_chart_source.data = dict(x=[key for key in time_dict], y=[time_dict[key] for key in time_dict])
print time_dict
else:
source.data = dict(x=[], y=[], color=[])
pie_chart_source.data = ChartMath.compute_color_distribution('x', 'y', 'color', [])
print xbeg, xend
print ybeg, yend
from bokeh.io import output_file, show
from bokeh.models import (
GMapPlot, GMapOptions, ColumnDataSource, Circle, DataRange1d, PanTool, WheelZoomTool, BoxSelectTool
)
from Backend import DB
DB.__init__()
SAMPLE_SIZE = 1000
xs, ys = DB.get_current(SAMPLE_SIZE)
source = ColumnDataSource(data=dict(x=xs, y=ys))
map_options = GMapOptions(lat=30.29, lng=-97.73, map_type="roadmap", zoom=11)
scatter_plot = GMapPlot(
x_range=DataRange1d(), y_range=DataRange1d(), map_options=map_options, title="Plot of Stations"
)
circle = Circle(x="x", y="y", size=15, fill_color="blue", fill_alpha=0.8, line_color=None)
scatter_plot.add_glyph(source, circle)
scatter_plot.add_tools(PanTool(), WheelZoomTool(), BoxSelectTool())
output_file("gmap_plot.html")
print type(source)