class BokehPlot(object):
def __init__(self,
device,
points_list,
*,
title='My title',
show_notes=True,
update_data=True):
self.device = device
if len(points_list) < 3:
raise ValueError("Provide at least 3 objects to the chart")
self.points_list = points_list
self.title = title
self.units = {}
self.show_notes = show_notes
self.lst = self.points_list
self.multi_states = self.device.multi_states
self.binary_states = self.device.binary_states
self.analog_units = self.device.analog_units
plot = self.build_plot()
self.device.properties.network.bokeh_document.add_plot(
plot, infos=self.device.properties)
#curdoc().add_root(plot)
if update_data:
self.device.properties.network.bokeh_document.add_periodic_callback(
self.update_data, 100)
print('Chart created, please reload your web page to see changes')
# Get data
def read_lst(self):
df = self.device[self.lst]
try:
df = df.fillna(method='ffill').fillna(method='bfill').replace(
['inactive', 'active'], [0, 1])
except TypeError:
df = df.fillna(method='ffill').fillna(method='bfill')
df = df.reset_index()
df['name'] = 'nameToReplace'
df['units'] = 'waiting for refresh'
df['time_s'] = df['index'].apply(str)
return df
def read_notes(self):
notes_df = self.device.notes.reset_index()
notes_df['value'] = -5
notes_df['desc'] = 'Notes'
notes_df['time_s'] = notes_df['index'].apply(str)
return notes_df
def build_plot(self):
df = self.read_lst()
notes_df = self.read_notes()
TOOLS = "pan,box_zoom,wheel_zoom,save,reset"
self.p = Figure(x_axis_type="datetime",
x_axis_label="Time",
y_axis_label="Numeric Value",
title=self.title,
tools=TOOLS,
plot_width=700,
plot_height=600,
toolbar_location='above')
if self.show_notes:
self.notes_source = ColumnDataSource(
data=dict(x=notes_df['index'],
y=notes_df['value'],
time=notes_df['time_s'],
desc=notes_df['desc'],
units=notes_df[0]))
self.p.asterisk(
'x',
'y',
source=self.notes_source,
name='Notes',
#color = "#%06x" % random.randint(0x000000, 0x777777),
legend='Notes',
size=40)
self.p.legend.location = 'top_left'
self.p.extra_y_ranges = {
"bool": Range1d(start=0, end=1.1),
"enum": Range1d(start=0, end=10)
}
self.p.add_layout(LinearAxis(y_range_name="bool", axis_label="Binary"),
'left')
self.p.add_layout(
LinearAxis(y_range_name="enum", axis_label="Enumerated"), 'right')
self.p.legend.location = "bottom_left"
hover = HoverTool(tooltips=[
('name', '@desc'),
('value', '@y'),
('units', '@units'),
('time', '@time'),
])
self.p.add_tools(hover)
self.sources = {}
if len(self.lst) <= 10:
color_mapper = dict(zip(self.lst, d3['Category10'][len(self.lst)]))
else:
# This would be a very loaded trend...
color_mapper = dict(zip(self.lst, Spectral6[:len(self.lst)]))
for each in self.lst:
try:
df['name'] = df['name'].replace(
'nameToReplace',
('%s / %s' % (each, self.device[each]['description'])))
except TypeError:
continue
self.sources[each] = ColumnDataSource(data=dict(x=df['index'],
y=df[each],
time=df['time_s'],
name=df['name'],
units=df['units']))
if each in self.binary_states:
self.p.circle(
'x',
'y',
source=self.sources[each],
name=each,
color=color_mapper[each],
legend=("%s/%s (OFF-ON)" %
(each, self.device[each]['description'])),
y_range_name="bool",
size=10)
elif each in self.multi_states:
self.p.diamond(
'x',
'y',
source=self.sources[each],
name=each,
color=color_mapper[each],
legend=("%s/%s (%s)" %
(each, self.device[each]['description'],
self.device[each].properties.units_state)),
y_range_name="enum",
size=20)
else:
self.p.line(
'x',
'y',
source=self.sources[each],
name=each,
color=color_mapper[each],
legend=("%s/%s (%s)" %
(each, self.device[each]['description'],
self.device[each].properties.units_state)),
line_width=2)
if self.show_notes:
columns = [
TableColumn(field="x",
title="Date",
formatter=DateFormatter(format='yy-mm-dd')),
TableColumn(field="units", title="Notes"),
]
data_table = DataTable(source=self.notes_source, columns=columns)
return (self.p, data_table)
else:
return (self.p, None)
def update_data(self):
if self.device.properties.network._started:
df = self.read_lst()
for renderer in self.p.renderers:
name = renderer.name
glyph_renderer = renderer
new_data = {}
if name in self.points_list:
df['name'] = ('%s / %s' %
(name, self.device[name]['description']))
new_data['x'] = df['index']
new_data['y'] = df[name]
new_data['desc'] = df['name']
new_data['time'] = df['time_s']
if name in self.multi_states:
new_data['units'] = [
self.multi_states[name][int(math.fabs(x - 1))]
for x in df[name]
]
elif name in self.binary_states:
new_data['y'] = df[name]
new_data['units'] = [
self.binary_states[name][int(x / 1)]
for x in df[name]
]
else:
df['units'] = self.analog_units[name]
new_data['units'] = df['units']
glyph_renderer.data_source.data = new_data
elif name == 'Notes':
notes_df = self.read_notes()
new_data['x'] = notes_df['index']
new_data['y'] = notes_df['value']
new_data['desc'] = notes_df['desc']
new_data['units'] = notes_df[0]
new_data['time'] = notes_df['time_s']
glyph_renderer.data_source.data = new_data
def plot_waveform_bokeh(filename,waveform_list,metadata_list,station_lat_list,\
station_lon_list, event_lat, event_lon, boundary_data, style_parameter):
xlabel_fontsize = style_parameter['xlabel_fontsize']
#
map_station_location_bokeh = ColumnDataSource(data=dict(map_lat_list=station_lat_list,\
map_lon_list=station_lon_list))
dot_default_index = 0
selected_dot_on_map_bokeh = ColumnDataSource(data=dict(lat=[station_lat_list[dot_default_index]],\
lon=[station_lon_list[dot_default_index]],\
index=[dot_default_index]))
map_view = Figure(plot_width=style_parameter['map_view_plot_width'], \
plot_height=style_parameter['map_view_plot_height'], \
y_range=[style_parameter['map_view_lat_min'],\
style_parameter['map_view_lat_max']], x_range=[style_parameter['map_view_lon_min'],\
style_parameter['map_view_lon_max']], tools=style_parameter['map_view_tools'],\
title=style_parameter['map_view_title'])
# ------------------------------
# add boundaries to map view
# country boundaries
map_view.multi_line(boundary_data['country']['longitude'],\
boundary_data['country']['latitude'],color='gray',\
line_width=2, level='underlay', nonselection_line_alpha=1.0,\
nonselection_line_color='gray')
# marine boundaries
map_view.multi_line(boundary_data['marine']['longitude'],\
boundary_data['marine']['latitude'],color='gray',\
level='underlay', nonselection_line_alpha=1.0,\
nonselection_line_color='gray')
# shoreline boundaries
map_view.multi_line(boundary_data['shoreline']['longitude'],\
boundary_data['shoreline']['latitude'],color='gray',\
line_width=2, nonselection_line_alpha=1.0, level='underlay',
nonselection_line_color='gray')
# state boundaries
map_view.multi_line(boundary_data['state']['longitude'],\
boundary_data['state']['latitude'],color='gray',\
level='underlay', nonselection_line_alpha=1.0,\
nonselection_line_color='gray')
#
map_view.triangle('map_lon_list', 'map_lat_list', source=map_station_location_bokeh, \
line_color='gray', size=style_parameter['marker_size'], fill_color='black',\
selection_color='black', selection_line_color='gray',\
selection_fill_alpha=1.0,\
nonselection_fill_alpha=1.0, nonselection_fill_color='black',\
nonselection_line_color='gray', nonselection_line_alpha=1.0)
map_view.triangle('lon','lat', source=selected_dot_on_map_bokeh,\
size=style_parameter['selected_marker_size'], line_color='black',fill_color='red')
map_view.asterisk([event_lon], [event_lat], size=style_parameter['event_marker_size'], line_width=3, line_color='red', \
fill_color='red')
# change style
map_view.title.text_font_size = style_parameter['title_font_size']
map_view.title.align = 'center'
map_view.title.text_font_style = 'normal'
map_view.xaxis.axis_label = style_parameter['map_view_xlabel']
map_view.xaxis.axis_label_text_font_style = 'normal'
map_view.xaxis.axis_label_text_font_size = xlabel_fontsize
map_view.xaxis.major_label_text_font_size = xlabel_fontsize
map_view.yaxis.axis_label = style_parameter['map_view_ylabel']
map_view.yaxis.axis_label_text_font_style = 'normal'
map_view.yaxis.axis_label_text_font_size = xlabel_fontsize
map_view.yaxis.major_label_text_font_size = xlabel_fontsize
map_view.xgrid.grid_line_color = None
map_view.ygrid.grid_line_color = None
map_view.toolbar.logo = None
map_view.toolbar_location = 'above'
map_view.toolbar_sticky = False
# --------------------------------------------------------
max_waveform_length = 0
max_waveform_amp = 0
ncurve = len(waveform_list)
for a_sta in waveform_list:
for a_trace in a_sta:
if len(a_trace) > max_waveform_length:
max_waveform_length = len(a_trace)
if np.max(np.abs(a_trace)) > max_waveform_amp:
max_waveform_amp = np.max(np.abs(a_trace))
#
plotting_list = []
for a_sta in waveform_list:
temp = []
for a_trace in a_sta:
if len(a_trace) < max_waveform_length:
a_trace = np.append(a_trace,np.zeros([(max_waveform_length-len(a_trace)),1]))
temp.append(list(a_trace))
plotting_list.append(temp)
#
time_list = []
for ista in range(len(plotting_list)):
a_sta = plotting_list[ista]
temp = []
for itr in range(len(a_sta)):
a_trace = a_sta[itr]
delta = metadata_list[ista][itr]['delta']
time = list(np.arange(len(a_trace))*delta)
temp.append(time)
#
time_list.append(temp)
#
reftime_label_list = []
channel_label_list = []
for ista in range(len(metadata_list)):
temp_ref = []
temp_channel = []
a_sta = metadata_list[ista]
for a_trace in a_sta:
temp_ref.append('Starting from '+a_trace['starttime'])
temp_channel.append(a_trace['network']+'_'+a_trace['station']+'_'+a_trace['channel'])
reftime_label_list.append(temp_ref)
channel_label_list.append(temp_channel)
# --------------------------------------------------------
curve_fig01 = Figure(plot_width=style_parameter['curve_plot_width'], plot_height=style_parameter['curve_plot_height'], \
y_range=(-max_waveform_amp*1.05,max_waveform_amp*1.05), \
x_range=(0,max_waveform_length),\
tools=['save','box_zoom','ywheel_zoom','xwheel_zoom','reset','crosshair','pan'])
#
curve_index = 0
select_curve_data = plotting_list[dot_default_index][curve_index]
select_curve_time = time_list[dot_default_index][curve_index]
selected_curve_data_bokeh01 = ColumnDataSource(data=dict(time=select_curve_time,amp=select_curve_data))
select_reftime_label = reftime_label_list[dot_default_index][curve_index]
selected_reftime_label_bokeh01 = ColumnDataSource(data=dict(x=[style_parameter['curve_reftime_label_x']],\
y=[style_parameter['curve_reftime_label_y']],\
label=[select_reftime_label]))
select_channel_label = channel_label_list[dot_default_index][curve_index]
selected_channel_label_bokeh01 = ColumnDataSource(data=dict(x=[style_parameter['curve_channel_label_x']],\
y=[style_parameter['curve_channel_label_y']],\
label=[select_channel_label]))
all_curve_data_bokeh = ColumnDataSource(data=dict(t=time_list, amp=plotting_list))
all_reftime_label_bokeh = ColumnDataSource(data=dict(label=reftime_label_list))
all_channel_label_bokeh = ColumnDataSource(data=dict(label=channel_label_list))
# plot waveform
curve_fig01.line('time','amp', source=selected_curve_data_bokeh01,\
line_color='black')
# add refference time as a label
curve_fig01.text('x', 'y', 'label', source=selected_reftime_label_bokeh01)
# add channel label
curve_fig01.text('x', 'y', 'label', source=selected_channel_label_bokeh01)
# change style
curve_fig01.title.text_font_size = style_parameter['title_font_size']
curve_fig01.title.align = 'center'
curve_fig01.title.text_font_style = 'normal'
curve_fig01.xaxis.axis_label = style_parameter['curve_xlabel']
curve_fig01.xaxis.axis_label_text_font_style = 'normal'
curve_fig01.xaxis.axis_label_text_font_size = xlabel_fontsize
curve_fig01.xaxis.major_label_text_font_size = xlabel_fontsize
curve_fig01.yaxis.axis_label = style_parameter['curve_ylabel']
curve_fig01.yaxis.axis_label_text_font_style = 'normal'
curve_fig01.yaxis.axis_label_text_font_size = xlabel_fontsize
curve_fig01.yaxis.major_label_text_font_size = xlabel_fontsize
curve_fig01.toolbar.logo = None
curve_fig01.toolbar_location = 'above'
curve_fig01.toolbar_sticky = False
# --------------------------------------------------------
curve_fig02 = Figure(plot_width=style_parameter['curve_plot_width'], plot_height=style_parameter['curve_plot_height'], \
y_range=(-max_waveform_amp*1.05,max_waveform_amp*1.05), \
x_range=(0,max_waveform_length),\
tools=['save','box_zoom','ywheel_zoom','xwheel_zoom','reset','crosshair','pan'])
#
curve_index = 1
select_curve_data = plotting_list[dot_default_index][curve_index]
select_curve_time = time_list[dot_default_index][curve_index]
selected_curve_data_bokeh02 = ColumnDataSource(data=dict(time=select_curve_time,amp=select_curve_data))
select_channel_label = channel_label_list[dot_default_index][curve_index]
selected_channel_label_bokeh02 = ColumnDataSource(data=dict(x=[style_parameter['curve_channel_label_x']],\
y=[style_parameter['curve_channel_label_y']],\
label=[select_channel_label]))
# plot waveform
curve_fig02.line('time','amp', source=selected_curve_data_bokeh02,\
line_color='black')
# add channel label
curve_fig02.text('x', 'y', 'label', source=selected_channel_label_bokeh02)
# change style
curve_fig02.title.text_font_size = style_parameter['title_font_size']
curve_fig02.title.align = 'center'
curve_fig02.title.text_font_style = 'normal'
curve_fig02.xaxis.axis_label = style_parameter['curve_xlabel']
curve_fig02.xaxis.axis_label_text_font_style = 'normal'
curve_fig02.xaxis.axis_label_text_font_size = xlabel_fontsize
curve_fig02.xaxis.major_label_text_font_size = xlabel_fontsize
curve_fig02.yaxis.axis_label = style_parameter['curve_ylabel']
curve_fig02.yaxis.axis_label_text_font_style = 'normal'
curve_fig02.yaxis.axis_label_text_font_size = xlabel_fontsize
curve_fig02.yaxis.major_label_text_font_size = xlabel_fontsize
curve_fig02.toolbar.logo = None
curve_fig02.toolbar_location = 'above'
curve_fig02.toolbar_sticky = False
# --------------------------------------------------------
curve_fig03 = Figure(plot_width=style_parameter['curve_plot_width'], plot_height=style_parameter['curve_plot_height'], \
y_range=(-max_waveform_amp*1.05,max_waveform_amp*1.05), \
x_range=(0,max_waveform_length),\
tools=['save','box_zoom','ywheel_zoom','xwheel_zoom','reset','crosshair','pan'])
#
curve_index = 2
select_curve_data = plotting_list[dot_default_index][curve_index]
select_curve_time = time_list[dot_default_index][curve_index]
selected_curve_data_bokeh03 = ColumnDataSource(data=dict(time=select_curve_time,amp=select_curve_data))
select_channel_label = channel_label_list[dot_default_index][curve_index]
selected_channel_label_bokeh03 = ColumnDataSource(data=dict(x=[style_parameter['curve_channel_label_x']],\
y=[style_parameter['curve_channel_label_y']],\
label=[select_channel_label]))
# plot waveform
curve_fig03.line('time','amp', source=selected_curve_data_bokeh03,\
line_color='black')
# add channel label
curve_fig03.text('x', 'y', 'label', source=selected_channel_label_bokeh03)
# change style
curve_fig03.title.text_font_size = style_parameter['title_font_size']
curve_fig03.title.align = 'center'
curve_fig03.title.text_font_style = 'normal'
curve_fig03.xaxis.axis_label = style_parameter['curve_xlabel']
curve_fig03.xaxis.axis_label_text_font_style = 'normal'
curve_fig03.xaxis.axis_label_text_font_size = xlabel_fontsize
curve_fig03.xaxis.major_label_text_font_size = xlabel_fontsize
curve_fig03.yaxis.axis_label = style_parameter['curve_ylabel']
curve_fig03.yaxis.axis_label_text_font_style = 'normal'
curve_fig03.yaxis.axis_label_text_font_size = xlabel_fontsize
curve_fig03.yaxis.major_label_text_font_size = xlabel_fontsize
curve_fig03.toolbar.logo = None
curve_fig03.toolbar_location = 'above'
curve_fig03.toolbar_sticky = False
# --------------------------------------------------------
map_station_location_js = CustomJS(args=dict(selected_dot_on_map_bokeh=selected_dot_on_map_bokeh,\
map_station_location_bokeh=map_station_location_bokeh,\
selected_curve_data_bokeh01=selected_curve_data_bokeh01,\
selected_curve_data_bokeh02=selected_curve_data_bokeh02,\
selected_curve_data_bokeh03=selected_curve_data_bokeh03,\
selected_channel_label_bokeh01=selected_channel_label_bokeh01,\
selected_channel_label_bokeh02=selected_channel_label_bokeh02,\
selected_channel_label_bokeh03=selected_channel_label_bokeh03,\
selected_reftime_label_bokeh01=selected_reftime_label_bokeh01,\
all_reftime_label_bokeh=all_reftime_label_bokeh,\
all_channel_label_bokeh=all_channel_label_bokeh,\
all_curve_data_bokeh=all_curve_data_bokeh), code="""
var inds = cb_obj.indices
selected_dot_on_map_bokeh.data['index'] = [inds]
var new_loc = map_station_location_bokeh.data
selected_dot_on_map_bokeh.data['lat'] = [new_loc['map_lat_list'][inds]]
selected_dot_on_map_bokeh.data['lon'] = [new_loc['map_lon_list'][inds]]
selected_dot_on_map_bokeh.change.emit()
selected_curve_data_bokeh01.data['t'] = all_curve_data_bokeh.data['t'][inds][0]
selected_curve_data_bokeh01.data['amp'] = all_curve_data_bokeh.data['amp'][inds][0]
selected_curve_data_bokeh01.change.emit()
selected_curve_data_bokeh02.data['t'] = all_curve_data_bokeh.data['t'][inds][1]
selected_curve_data_bokeh02.data['amp'] = all_curve_data_bokeh.data['amp'][inds][1]
selected_curve_data_bokeh02.change.emit()
selected_curve_data_bokeh03.data['t'] = all_curve_data_bokeh.data['t'][inds][2]
selected_curve_data_bokeh03.data['amp'] = all_curve_data_bokeh.data['amp'][inds][2]
selected_curve_data_bokeh03.change.emit()
selected_reftime_label_bokeh01.data['label'] = [all_reftime_label_bokeh.data['label'][inds][0]]
selected_reftime_label_bokeh01.change.emit()
selected_channel_label_bokeh01.data['label'] = [all_channel_label_bokeh.data['label'][inds][0]]
selected_channel_label_bokeh01.change.emit()
selected_channel_label_bokeh02.data['label'] = [all_channel_label_bokeh.data['label'][inds][1]]
selected_channel_label_bokeh02.change.emit()
selected_channel_label_bokeh03.data['label'] = [all_channel_label_bokeh.data['label'][inds][2]]
selected_channel_label_bokeh03.change.emit()
""")
#
map_station_location_bokeh.selected.js_on_change('indices', map_station_location_js)
#
curve_slider_callback = CustomJS(args=dict(selected_dot_on_map_bokeh=selected_dot_on_map_bokeh,\
map_station_location_bokeh=map_station_location_bokeh,\
selected_curve_data_bokeh01=selected_curve_data_bokeh01,\
selected_curve_data_bokeh02=selected_curve_data_bokeh02,\
selected_curve_data_bokeh03=selected_curve_data_bokeh03,\
selected_channel_label_bokeh01=selected_channel_label_bokeh01,\
selected_channel_label_bokeh02=selected_channel_label_bokeh02,\
selected_channel_label_bokeh03=selected_channel_label_bokeh03,\
selected_reftime_label_bokeh01=selected_reftime_label_bokeh01,\
all_reftime_label_bokeh=all_reftime_label_bokeh,\
all_channel_label_bokeh=all_channel_label_bokeh,\
all_curve_data_bokeh=all_curve_data_bokeh),code="""
var inds = Math.round(cb_obj.value)
selected_dot_on_map_bokeh.data['index'] = [inds]
var new_loc = map_station_location_bokeh.data
selected_dot_on_map_bokeh.data['lat'] = [new_loc['map_lat_list'][inds]]
selected_dot_on_map_bokeh.data['lon'] = [new_loc['map_lon_list'][inds]]
selected_dot_on_map_bokeh.change.emit()
selected_curve_data_bokeh01.data['t'] = all_curve_data_bokeh.data['t'][inds][0]
selected_curve_data_bokeh01.data['amp'] = all_curve_data_bokeh.data['amp'][inds][0]
selected_curve_data_bokeh01.change.emit()
selected_curve_data_bokeh02.data['t'] = all_curve_data_bokeh.data['t'][inds][1]
selected_curve_data_bokeh02.data['amp'] = all_curve_data_bokeh.data['amp'][inds][1]
selected_curve_data_bokeh02.change.emit()
selected_curve_data_bokeh03.data['t'] = all_curve_data_bokeh.data['t'][inds][2]
selected_curve_data_bokeh03.data['amp'] = all_curve_data_bokeh.data['amp'][inds][2]
selected_curve_data_bokeh03.change.emit()
selected_reftime_label_bokeh01.data['label'] = [all_reftime_label_bokeh.data['label'][inds][0]]
selected_reftime_label_bokeh01.change.emit()
selected_channel_label_bokeh01.data['label'] = [all_channel_label_bokeh.data['label'][inds][0]]
selected_channel_label_bokeh01.change.emit()
selected_channel_label_bokeh02.data['label'] = [all_channel_label_bokeh.data['label'][inds][1]]
selected_channel_label_bokeh02.change.emit()
selected_channel_label_bokeh03.data['label'] = [all_channel_label_bokeh.data['label'][inds][2]]
selected_channel_label_bokeh03.change.emit()
""")
curve_slider = Slider(start=0, end=ncurve-1, value=style_parameter['curve_default_index'], \
step=1, title=style_parameter['curve_slider_title'], width=style_parameter['map_view_plot_width'],\
height=50, callback=curve_slider_callback)
# ==============================
# annotating text
annotating_fig01 = Div(text=style_parameter['annotating_html01'], \
width=style_parameter['annotation_plot_width'], height=style_parameter['annotation_plot_height'])
annotating_fig02 = Div(text=style_parameter['annotating_html02'],\
width=style_parameter['annotation_plot_width'], height=style_parameter['annotation_plot_height'])
# ==============================
output_file(filename,title=style_parameter['html_title'],mode=style_parameter['library_source'])
#
left_fig = Column(curve_slider, map_view, annotating_fig01, width=style_parameter['left_column_width'] )
right_fig = Column(curve_fig01, curve_fig02, curve_fig03, annotating_fig02, width=style_parameter['right_column_width'])
layout = Row(left_fig, right_fig)
save(layout)
class BokehPlot(object):
def __init__(self,
device,
points_list,
*,
title='My title',
show_notes=True,
update_data=True):
self.device = device
self.points_list = points_list
self.title = title
self.units = {}
self.show_notes = show_notes
self.lst = self.points_list
self.multi_states = self.device.multi_states
self.binary_states = self.device.binary_states
self.analog_units = self.device.analog_units
plot = self.build_plot()
self.device.properties.network.bokeh_document.add_plot(plot)
if update_data:
self.device.properties.network.bokeh_document.add_periodic_callback(
self.update_data, 100)
print('Chart created, please reload your web page to see changes')
# Get data
def read_lst(self):
df = self.device[self.lst]
try:
df = df.fillna(method='ffill').fillna(method='bfill').replace(
['inactive', 'active'], [0, 1])
except TypeError:
df = df.fillna(method='ffill').fillna(method='bfill')
df = df.reset_index()
df['name'] = 'nameToReplace'
df['units'] = 'waiting for refresh'
df['time_s'] = df['index'].apply(str)
return df
def read_notes(self):
notes_df = self.device.notes.reset_index()
notes_df['value'] = -5
notes_df['desc'] = 'Notes'
notes_df['time_s'] = notes_df['index'].apply(str)
return notes_df
def build_plot(self):
df = self.read_lst()
notes_df = self.read_notes()
TOOLS = "hover,resize,save,pan,box_zoom,wheel_zoom,reset"
#plot_width=800, plot_height=600,
self.p = Figure(x_axis_type="datetime", title=self.title, tools=TOOLS)
if self.show_notes:
self.notes_source = ColumnDataSource(
data=dict(x=notes_df['index'],
y=notes_df['value'],
time=notes_df['time_s'],
desc=notes_df['desc'],
units=notes_df[0]))
self.p.asterisk('x',
'y',
source=self.notes_source,
name='Notes',
color="#%06x" % random.randint(0x000000, 0x777777),
legend='Notes',
size=40)
self.p.legend.location = 'top_left'
self.p.extra_y_ranges = {
"bool": Range1d(start=0, end=1.1),
"enum": Range1d(start=0, end=10)
}
self.p.add_layout(LinearAxis(y_range_name="bool"), 'left')
self.p.add_layout(LinearAxis(y_range_name="enum"), 'right')
hover = self.p.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([
('name', '@desc'),
('value', '@y'),
('units', '@units'),
('time', '@time'),
])
self.sources = {}
for each in self.lst:
try:
df['name'] = df['name'].replace(
'nameToReplace',
('%s / %s' % (each, self.device[each]['description'])))
except TypeError:
continue
self.sources[each] = ColumnDataSource(data=dict(x=df['index'],
y=df[each],
time=df['time_s'],
name=df['name'],
units=df['units']))
if each in self.binary_states:
self.p.circle('x',
'y',
source=self.sources[each],
name=each,
color="#%06x" %
random.randint(0x000000, 0x777777),
legend=each,
y_range_name="bool",
size=10)
elif each in self.multi_states:
self.p.diamond('x',
'y',
source=self.sources[each],
name=each,
color="#%06x" %
random.randint(0x000000, 0x777777),
legend=each,
y_range_name="enum",
size=20)
else:
self.p.line('x',
'y',
source=self.sources[each],
name=each,
color="#%06x" % random.randint(0x000000, 0x777777),
legend=each,
line_width=2)
return self.p
def update_data(self):
if self.device.properties.network._started:
df = self.read_lst()
for renderer in self.p.renderers:
name = renderer.name
if name in self.points_list:
glyph_renderer = renderer
df['name'] = ('%s / %s' %
(name, self.device[name]['description']))
glyph_renderer.data_source.data['x'] = df['index']
glyph_renderer.data_source.data['y'] = df[name]
glyph_renderer.data_source.data['desc'] = df['name']
glyph_renderer.data_source.data['time'] = df['time_s']
if name in self.multi_states:
glyph_renderer.data_source.data['units'] = [
self.multi_states[name][int(math.fabs(x - 1))]
for x in df[name]
]
elif name in self.binary_states:
glyph_renderer.data_source.data['y'] = df[name]
glyph_renderer.data_source.data['units'] = [
self.binary_states[name][int(x / 1)]
for x in df[name]
]
else:
df['units'] = self.analog_units[name]
glyph_renderer.data_source.data['units'] = df['units']
elif name == 'Notes':
notes_df = self.read_notes()
glyph_renderer = renderer
glyph_renderer.data_source.data['x'] = notes_df['index']
glyph_renderer.data_source.data['y'] = notes_df['value']
glyph_renderer.data_source.data['desc'] = notes_df['desc']
glyph_renderer.data_source.data['units'] = notes_df[0]
glyph_renderer.data_source.data['time'] = notes_df[
'time_s']
a_rad = 2.7 * rv['mstar']
rv_syms = p1.circle(rv['semi'] / a_rad,
rv['msini'] * mjup,
color='red',
fill_alpha=0.4,
line_alpha=1.,
size=8)
# microlens
ulens = Table.read(
'/Users/tumlinson/Dropbox/LUVOIR_STDT/luvoir_simtools/planetspace/ulens.dat',
format='ascii',
names=['name', 'msini', 'semi', 'mstar'])
a_rad = 2.7 * ulens['mstar']
ulens_syms = p1.asterisk(ulens['semi'] / a_rad,
ulens['msini'] * mjup,
color='green',
size=8)
# imaging
ulens = Table.read(
'/Users/tumlinson/Dropbox/LUVOIR_STDT/luvoir_simtools/planetspace/imaging.dat',
format='ascii',
names=['name', 'msini', 'semi', 'mstar'])
a_rad = 2.7 * ulens['mstar']
ulens_syms = p1.square(ulens['semi'] / a_rad,
ulens['msini'] * mjup,
fill_alpha=0.4,
line_alpha=0.9,
color='purple',
size=8)
class BokehPlot(object):
def __init__(self, device, points_list, *, title = 'My title', show_notes = True, update_data = True):
self.device = device
self.points_list = points_list
self.title = title
self.units = {}
self.show_notes = show_notes
self.lst = self.points_list
self.multi_states = self.device.multi_states
self.binary_states = self.device.binary_states
self.analog_units = self.device.analog_units
plot = self.build_plot()
self.device.properties.network.bokeh_document.add_plot(plot)
if update_data:
self.device.properties.network.bokeh_document.add_periodic_callback(self.update_data, 100)
print('Chart created, please reload your web page to see changes')
# Get data
def read_lst(self):
df = self.device[self.lst]
try:
df = df.fillna(method='ffill').fillna(method='bfill').replace(['inactive', 'active'], [0, 1])
except TypeError:
df = df.fillna(method='ffill').fillna(method='bfill')
df = df.reset_index()
df['name'] = 'nameToReplace'
df['units'] = 'waiting for refresh'
df['time_s'] = df['index'].apply(str)
return df
def read_notes(self):
notes_df = self.device.notes.reset_index()
notes_df['value'] = -5
notes_df['desc'] = 'Notes'
notes_df['time_s'] = notes_df['index'].apply(str)
return notes_df
def build_plot(self):
df = self.read_lst()
notes_df = self.read_notes()
TOOLS = "hover,resize,save,pan,box_zoom,wheel_zoom,reset"
#plot_width=800, plot_height=600,
self.p = Figure(x_axis_type="datetime", title = self.title, tools = TOOLS)
if self.show_notes:
self.notes_source = ColumnDataSource(
data=dict(
x = notes_df['index'],
y = notes_df['value'],
time = notes_df['time_s'],
desc = notes_df['desc'],
units = notes_df[0]
)
)
self.p.asterisk('x',
'y',
source = self.notes_source,
name = 'Notes',
color = "#%06x" % random.randint(0x000000, 0x777777),
legend='Notes',
size = 40)
self.p.legend.location = 'top_left'
self.p.extra_y_ranges = {"bool": Range1d(start=0, end=1.1),
"enum": Range1d(start=0, end=10)}
self.p.add_layout(LinearAxis(y_range_name="bool"), 'left')
self.p.add_layout(LinearAxis(y_range_name="enum"), 'right')
hover = self.p.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([
('name', '@desc'),
('value', '@y'),
('units', '@units'),
('time', '@time'),
])
self.sources = {}
for each in self.lst:
try:
df['name'] = df['name'].replace('nameToReplace', ('%s / %s' % (each, self.device[each]['description'])))
except TypeError:
continue
self.sources[each] = ColumnDataSource(
data=dict(
x = df['index'],
y = df[each],
time = df['time_s'],
name = df['name'],
units = df['units']
)
)
if each in self.binary_states:
self.p.circle('x',
'y',
source = self.sources[each],
name = each,
color = "#%06x" % random.randint(0x000000, 0x777777),
legend=each,
y_range_name="bool",
size = 10)
elif each in self.multi_states:
self.p.diamond('x',
'y',
source = self.sources[each],
name = each,
color = "#%06x" % random.randint(0x000000, 0x777777),
legend=each,
y_range_name="enum",
size = 20)
else:
self.p.line('x',
'y',
source = self.sources[each],
name = each,
color = "#%06x" % random.randint(0x000000, 0x777777),
legend=each,
line_width = 2)
return self.p
def update_data(self):
if self.device.properties.network._started:
df = self.read_lst()
for renderer in self.p.renderers:
name = renderer.name
if name in self.points_list:
glyph_renderer = renderer
df['name'] = ('%s / %s' % (name, self.device[name]['description']))
glyph_renderer.data_source.data['x'] = df['index']
glyph_renderer.data_source.data['y'] = df[name]
glyph_renderer.data_source.data['desc'] = df['name']
glyph_renderer.data_source.data['time'] = df['time_s']
if name in self.multi_states:
glyph_renderer.data_source.data['units'] = [self.multi_states[name][int(math.fabs(x-1))] for x in df[name]]
elif name in self.binary_states:
glyph_renderer.data_source.data['y'] = df[name]
glyph_renderer.data_source.data['units'] = [self.binary_states[name][int(x/1)] for x in df[name]]
else:
df['units'] = self.analog_units[name]
glyph_renderer.data_source.data['units'] = df['units']
elif name == 'Notes':
notes_df = self.read_notes()
glyph_renderer = renderer
glyph_renderer.data_source.data['x'] = notes_df['index']
glyph_renderer.data_source.data['y'] = notes_df['value']
glyph_renderer.data_source.data['desc'] = notes_df['desc']
glyph_renderer.data_source.data['units'] = notes_df[0]
glyph_renderer.data_source.data['time'] = notes_df['time_s']