def __init__(self, **kwargs):
super(WeatherPlot, self).__init__(**kwargs)
# def __init__(self,
# data,
# column_names=cs.column_names_weewx,
# column_time=cs.time_column_name_weewx,
# plot_height=300,
# plot_width=800,
# border_left=150,
# **kwargs):
# if "tool_events" not in kwargs:
# kwargs["tool_events"] = ToolEvents()
# super(WeatherPlot,self).__init__(x_range=DataRange1d(),
# y_range=DataRange1d(),
# plot_width=800,
# plot_height=500,
# min_border_left=150,
# **kwargs)
time_int = 3600
t_max = int(time.time())
t_min = t_max - 3600 * 24
data = sql_con.get_data_ws(time_int=time_int, t_max=t_max, t_min=t_min)
self._data = data
column_names = cs.column_names_weewx
column_time = cs.time_column_name_weewx
data_seconds = data
data_seconds.iloc[:, 0] = data_seconds.iloc[:, 0] * 1000
add_glyphs_to_plot(column_names, column_time, data_seconds, self)
self.add_layout(DatetimeAxis(), "below")
self.add_tools(PanTool(), WheelZoomTool(), ResizeTool(), CrosshairTool())
def __init__(self,**kwargs):
super(WeatherPlot,self).__init__(**kwargs)
# def __init__(self,
# data,
# column_names=cs.column_names_weewx,
# column_time=cs.time_column_name_weewx,
# plot_height=300,
# plot_width=800,
# border_left=150,
# **kwargs):
# if "tool_events" not in kwargs:
# kwargs["tool_events"] = ToolEvents()
# super(WeatherPlot,self).__init__(x_range=DataRange1d(),
# y_range=DataRange1d(),
# plot_width=800,
# plot_height=500,
# min_border_left=150,
# **kwargs)
time_int = 3600
t_max = int(time.time())
t_min = t_max - 3600 * 24
data = sql_con.get_data_ws(time_int=time_int,
t_max=t_max,
t_min=t_min)
self._data = data
column_names=cs.column_names_weewx
column_time=cs.time_column_name_weewx
data_seconds = data
data_seconds.iloc[:, 0] = data_seconds.iloc[:, 0] * 1000
add_glyphs_to_plot(column_names, column_time, data_seconds, self)
self.add_layout(DatetimeAxis(), 'below')
self.add_tools(PanTool(), WheelZoomTool(), ResizeTool(), CrosshairTool())
def get_weather_plot(time_int=None, t_min=None, t_max=None):
plot_height = cs.plot_height
plot_width = cs.plot_width
border_left = cs.border_left
column_names = cs.column_names_weewx
column_time = cs.time_column_name_weewx
if t_max == None or t_min == None:
t_max, t_min = get_first_time_interval()
t_span = t_max - t_min
if time_int == None:
time_int = cs.time_int
data_seconds = sql_con.get_data_ws(time_int=time_int,
t_min=t_min,
t_max=t_max)
data_seconds.iloc[:, 0] = data_seconds.iloc[:, 0] * 1000
plot = Plot(
x_range=DataRange1d(start=(t_min - t_span * .1) * 1000,
end=(t_max + t_span * .1) * 1000),
y_range=DataRange1d(),
plot_width=plot_width,
plot_height=plot_height,
# x_axis_type="datetime",
min_border_left=border_left,
toolbar_location="right")
add_glyphs_to_plot(column_names, column_time, data_seconds, plot,
'source_weather')
plot.add_layout(DatetimeAxis(name="date_time_axis"), 'below')
plot.add_tools(
PanTool(),
WheelZoomTool(),
# ResizeTool(),
CrosshairTool(),
PreviewSaveTool())
Grid(plot=plot,
dimension=0,
ticker=plot.select('date_time_axis')[0].ticker)
Grid(plot=plot,
dimension=1,
ticker=plot.select(type=LinearAxis, name=column_names[0])[0].ticker)
set_legends(plot)
plot.title = cs.plot_title_weewx + ' averaged to {} seconds'.format(
time_int)
return plot
def get_weather_plot(time_int=None,t_min=None,t_max=None):
plot_height = cs.plot_height
plot_width = cs.plot_width
border_left = cs.border_left
column_names = cs.column_names_weewx
column_time = cs.time_column_name_weewx
if t_max == None or t_min == None:
t_max, t_min = get_first_time_interval()
t_span = t_max - t_min
if time_int == None:
time_int = cs.time_int
data_seconds = sql_con.get_data_ws(time_int=time_int, t_min=t_min, t_max=t_max)
data_seconds.iloc[:, 0] = data_seconds.iloc[:, 0] * 1000
plot = Plot(x_range=DataRange1d(start=(t_min-t_span*.1)*1000,
end=(t_max+t_span*.1)*1000),
y_range=DataRange1d(),
plot_width=plot_width,
plot_height=plot_height,
# x_axis_type="datetime",
min_border_left=border_left,
toolbar_location="right")
add_glyphs_to_plot(column_names, column_time, data_seconds, plot,'source_weather')
plot.add_layout(DatetimeAxis(name="date_time_axis"), 'below')
plot.add_tools(PanTool(),
WheelZoomTool(),
# ResizeTool(),
CrosshairTool(),
PreviewSaveTool()
)
Grid(plot=plot,dimension=0,ticker=plot.select('date_time_axis')[0].ticker)
Grid(plot=plot,
dimension=1,
ticker=plot.select(type=LinearAxis,name=column_names[0])[0].ticker
)
set_legends(plot)
plot.title = cs.plot_title_weewx + ' averaged to {} seconds'.format(time_int)
return plot
from __future__ import print_function
from ceil_bokeh import sql_con, plots
from bokeh.browserlib import view
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.resources import INLINE
data_weather = sql_con.get_data_ws(time_int=3600)
plot_weather = plots.get_weather_plot(data_weather)
# data_ceil = sql_con.get_data_bs()
# plot_ceil = plots.get_bs_plot(data_ceil)
# link x_range both plots
# plot_weather.x_range = plot_ceil.x_range
doc = Document()
doc.add(plot_weather)
# doc.add(plot_ceil)
if __name__ == "__main__":
filename = "twin_axis.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Twin Axis Plot"))
print("Wrote %s" % filename)
view(filename)
from __future__ import print_function
from ceil_bokeh import sql_con, plots
from bokeh.browserlib import view
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.resources import INLINE
data_weather = sql_con.get_data_ws(time_int=3600)
plot_weather = plots.get_weather_plot(data_weather)
# data_ceil = sql_con.get_data_bs()
# plot_ceil = plots.get_bs_plot(data_ceil)
# link x_range both plots
# plot_weather.x_range = plot_ceil.x_range
doc = Document()
doc.add(plot_weather)
# doc.add(plot_ceil)
if __name__ == "__main__":
filename = "twin_axis.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Twin Axis Plot"))
print("Wrote %s" % filename)
view(filename)
