def get_ceil_plot(time_int=None, t_min=None, t_max=None):
if time_int == None:
time_int = cs.time_int
plot_height = cs.plot_height
plot_width = cs.plot_width
border_left = cs.border_left
if t_min == None or t_max == None:
t_max, t_min = get_first_time_interval()
t_span = t_max - t_min
data = sql_con.get_data_bs(time_int=time_int, t_min=t_min, t_max=t_max)
# print data
ll = len(data)
toolset = [CrosshairTool(), WheelZoomTool(), PreviewSaveTool(), PanTool()]
plot = figure(x_range=DataRange1d(start=(t_min - t_span * .1) * 1000,
end=(t_max + t_span * .1) * 1000),
y_range=[0, 250 * 15],
plot_height=plot_height,
plot_width=plot_width,
x_axis_type="datetime",
min_border_left=border_left,
toolbar_location="right",
tools=toolset)
plot.yaxis.axis_label = "meters above ground"
dd = []
tt = []
y = []
dw = []
dh = []
for i in range(ll):
dd.append(data.iloc[i:i + 1, 1:].T.values)
tt.append(int(data.iloc[i, 0]) * 1000 - time_int * 1000 / 2)
y.append(0)
dw.append(time_int * 1000)
dh.append(250 * 15)
plot.image(image=dd,
x=tt,
y=y,
dw=dw,
dh=dh,
palette="Spectral11",
dilate=True)
plot.title = cs.plot_title_ceil + ' averaged to {} seconds'.format(
time_int)
return plot
def get_ceil_plot(time_int=None,t_min=None,t_max=None):
if time_int == None:
time_int = cs.time_int
plot_height = cs.plot_height
plot_width = cs.plot_width
border_left = cs.border_left
if t_min == None or t_max == None:
t_max, t_min = get_first_time_interval()
t_span = t_max-t_min
data = sql_con.get_data_bs(time_int=time_int, t_min=t_min, t_max=t_max)
# print data
ll = len(data)
toolset = [CrosshairTool(),WheelZoomTool(),PreviewSaveTool(),PanTool()]
plot = figure(x_range=DataRange1d(start=(t_min-t_span*.1)*1000,
end=(t_max+t_span*.1)*1000
),
y_range=[0, 250 * 15],
plot_height=plot_height,
plot_width=plot_width,
x_axis_type="datetime",
min_border_left=border_left,
toolbar_location="right",
tools=toolset
)
plot.yaxis.axis_label = "meters above ground"
dd = []
tt = []
y = []
dw = []
dh = []
for i in range(ll):
dd.append(data.iloc[i:i + 1, 1:].T.values)
tt.append(int(data.iloc[i, 0]) * 1000 - time_int * 1000 / 2)
y.append(0)
dw.append(time_int * 1000)
dh.append(250 * 15)
plot.image(image=dd, x=tt, y=y, dw=dw, dh=dh, palette="Spectral11", dilate=True)
plot.title = cs.plot_title_ceil + ' averaged to {} seconds'.format(time_int)
return plot
from __future__ import print_function
from bokeh.browserlib import view
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.resources import INLINE
from ceil_bokeh import sql_con, plots
border_left = 150
time_int = 3600
data_weather = sql_con.get_data_ws(time_int=time_int)
plot_weather = plots.get_weather_plot(data_weather, border_left=border_left)
data_ceil = sql_con.get_data_bs(time_int=time_int)
plot_ceil = plots.get_ceil_plot(data_ceil, time_int=time_int, border_left=border_left)
# 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)
from __future__ import print_function
from bokeh.browserlib import view
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.resources import INLINE
from ceil_bokeh import sql_con, plots
border_left = 150
time_int = 3600
data_weather = sql_con.get_data_ws(time_int=time_int)
plot_weather = plots.get_weather_plot(data_weather, border_left=border_left)
data_ceil = sql_con.get_data_bs(time_int=time_int)
plot_ceil = plots.get_ceil_plot(data_ceil,
time_int=time_int,
border_left=border_left)
# 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:
