def get_date_range_plot(source_time):
data_time_ws = sql_con.get_data_tm(cs.time_column_name_weewx,
cs.time_int_data_range,
cs.data_base_name_weewx,
cs.table_name_weewx
) * 1000
data_time_bs = sql_con.get_data_tm(cs.time_column_name_ceil,
cs.time_int_data_range,
cs.data_base_name_ceil,
cs.bs_table_name_ceil
) * 1000
y_factors=['weather','ceilometer']
data_time_ws['y'] = y_factors[0]
data_time_bs['y'] = y_factors[1]
data_time_bs.rename(columns={0: 'x'}, inplace=True)
data_time_ws.rename(columns={0: 'x'}, inplace=True)
source_df = pd.concat([data_time_ws, data_time_bs],
ignore_index=True)
source_df.sort_values('x', inplace=True)
source_time.data = ColumnDataSource(data=source_df).data
source_time.name = 'source_time'
toolset = "crosshair , xpan ,reset, xwheel_zoom"
t_min_mili = float(source_df['x'].min())
t_max_mili = float(source_df['x'].max())
t_span_mili=t_max_mili-t_min_mili
# Generate a figure container
plot = figure(plot_height=cs.data_range_plot_height,
plot_width=cs.plot_width,
tools=toolset,
x_axis_type="datetime",
y_range=y_factors,
toolbar_location="right",
x_range=[t_min_mili-.1*t_span_mili,
t_max_mili+.1*t_span_mili],
logo=None)
plot.add_tools(BoxSelectTool(dimensions=['width']))
plot.circle('x', 'y', source=source_time, color="red")
plot.title = "select interval from below"
# df=source_time.to_df()
# t_max,t_min = get_first_time_interval()
# index=df[df.x>=t_min*1000].index.values
# source_time.selected['1d']['indices']=index
return plot
def get_date_range_plot(source_time):
data_time_ws = sql_con.get_data_tm(
cs.time_column_name_weewx, cs.time_int_data_range,
cs.data_base_name_weewx, cs.table_name_weewx) * 1000
data_time_bs = sql_con.get_data_tm(
cs.time_column_name_ceil, cs.time_int_data_range,
cs.data_base_name_ceil, cs.bs_table_name_ceil) * 1000
y_factors = ['weather', 'ceilometer']
data_time_ws['y'] = y_factors[0]
data_time_bs['y'] = y_factors[1]
data_time_bs.rename(columns={0: 'x'}, inplace=True)
data_time_ws.rename(columns={0: 'x'}, inplace=True)
source_df = pd.concat([data_time_ws, data_time_bs], ignore_index=True)
source_df.sort_values('x', inplace=True)
source_time.data = ColumnDataSource(data=source_df).data
source_time.name = 'source_time'
toolset = "crosshair , xpan ,reset, xwheel_zoom"
t_min_mili = float(source_df['x'].min())
t_max_mili = float(source_df['x'].max())
t_span_mili = t_max_mili - t_min_mili
# Generate a figure container
plot = figure(
plot_height=cs.data_range_plot_height,
plot_width=cs.plot_width,
tools=toolset,
x_axis_type="datetime",
y_range=y_factors,
toolbar_location="right",
x_range=[t_min_mili - .1 * t_span_mili, t_max_mili + .1 * t_span_mili],
logo=None)
plot.add_tools(BoxSelectTool(dimensions=['width']))
plot.circle('x', 'y', source=source_time, color="red")
plot.title = "select interval from below"
# df=source_time.to_df()
# t_max,t_min = get_first_time_interval()
# index=df[df.x>=t_min*1000].index.values
# source_time.selected['1d']['indices']=index
return plot
from ceil_bokeh import sql_con
# df=sql_con.get_data_bs(time_int=600)
# df=sql_con.get_data_ws(time_int=1)
df=sql_con.get_data_tm(
'dateTime',600,'weewx_ceilometer02',
'archive',"mysql://*****:*****@10.8.3.1/")
print df
from ceil_bokeh import sql_con
# df=sql_con.get_data_bs(time_int=600)
# df=sql_con.get_data_ws(time_int=1)
df = sql_con.get_data_tm('dateTime', 600, 'weewx_ceilometer02', 'archive',
"mysql://*****:*****@10.8.3.1/")
print df
