def plot1():
# copy/pasted from Bokeh Getting Started Guide - used as an example
grouped = autompg.groupby("yr")
mpg = grouped.mpg
avg, std = mpg.mean(), mpg.std()
years = list(grouped.groups)
american = autompg[autompg["origin"] == 1]
japanese = autompg[autompg["origin"] == 3]
p = Figure(title="MPG by Year (Japan and US)")
p.vbar(x=years,
bottom=avg - std,
top=avg + std,
width=0.8,
fill_alpha=0.2,
line_color=None,
legend="MPG 1 stddev")
p.circle(x=japanese["yr"],
y=japanese["mpg"],
size=10,
alpha=0.5,
color="red",
legend="Japanese")
p.triangle(x=american["yr"],
y=american["mpg"],
size=10,
alpha=0.3,
color="blue",
legend="American")
p.legend.location = "top_left"
return json.dumps(json_item(p, "myplot"))
def make_plot(yscale='linear'):
# configure the tools
width_zoom={'dimensions':['width']}
tools = [tool(**width_zoom) for tool in [BoxZoomTool, WheelZoomTool]]
hover_pos = HoverTool(
names=['buy','sell'],
tooltips=[
('Position','@pos'),
('Date','@date'),
('Price','@price')
]
)
hover_pos.name = 'Postions'
tools.extend([PanTool(), hover_pos, ResetTool(), CrosshairTool()])
# prepare plot
p = Figure(plot_height=600, plot_width=800, title="Moving Average Positions",
x_axis_type='datetime', y_axis_type=yscale, tools=tools)
p.line(x='date', y='price', alpha=0.3, color='Black', line_width=2, source=source, legend='Close', name='price')
p.line(x='date', y='mav_short', color='DarkBlue', line_width=2, source=source, legend='Short MAV')
p.line(x='date', y='mav_long', color='FireBrick', line_width=2, source=source, legend='Long MAV')
p.inverted_triangle(x='x', y='y', color='Crimson', size=20, alpha=0.7, source=sell, legend='Sell', name='sell')
p.triangle(x='x', y='y', color='ForestGreen', size=20, alpha=0.7, source=buy, legend='Buy', name='buy')
return p
def add_direction_map(fig: Figure, mgrid, direction_map, freq=2, **kwargs):
"""Quiver plot of direction map
http://bokeh.pydata.org/en/latest/docs/gallery/quiver.html
Args:
fig:
mgrid:
direction_map:
**kwargs:
"""
X, Y = mgrid.values
U, V = direction_map
x0 = X[::freq, ::freq].flatten()
y0 = Y[::freq, ::freq].flatten()
x1 = x0 + 0.9 * freq * mgrid.step * U[::freq, ::freq].flatten()
y1 = y0 + 0.9 * freq * mgrid.step * V[::freq, ::freq].flatten()
fig.segment(x0, y0, x1, y1, **kwargs)
fig.triangle(x1,
y1,
size=4.0,
angle=np.arctan2(V[::freq, ::freq].flatten(),
U[::freq, ::freq].flatten()) - np.pi / 2)
def plot_crossover_signals(data, signals, ticker=None, notebook=False):
# create a new plot with a title and axis labels
p = Figure(title=ticker + ' Moving Crossover Strategy',
x_axis_label='Date',
x_axis_type='datetime',
y_axis_label='Price in $',
plot_height=500,
plot_width=950,
tools=['pan', 'wheel_zoom'],
toolbar_location='below')
# configure so that Bokeh chooses what (if any) scroll tool is active
p.toolbar.active_scroll = "auto"
# add a line renderer with legend and line thickness
p.line(data.index,
data['Close'],
line_width=2,
legend='Close',
line_color='black')
p.line(signals.index,
signals['short_mavg'],
line_width=2,
legend='Slow MA',
line_color='orange')
p.line(signals.index,
signals['long_mavg'],
line_width=2,
legend='Fast MA',
line_color='blue')
p.triangle(signals.loc[signals.positions == 1.0].index,
signals.short_mavg[signals.positions == 1.0],
size=15,
fill_color='green',
legend='Bullish Crossover')
p.inverted_triangle(signals.loc[signals.positions == -1.0].index,
signals.short_mavg[signals.positions == -1.0],
size=15,
fill_color='red',
legend='Bearish Crossover')
p.legend.location = "top_left"
p.legend.click_policy = "hide"
if notebook:
# show the results
show(p, notebook_handle=True)
push_notebook()
else:
# output the results
output_file('%s Moving Crossover Strategy.html' % ticker)
save(p)
def construct_best_odds_figure(self, x, y, z, t, trade_id, sticker):
# workaround to format date in the hover tool at the moment bokeh does not supported in the tool tips
source_back_odds = ColumnDataSource(data=dict(x=x, y=y, time=[e.strftime('%d-%m-%Y %H:%M:%S') for e in x]))
hover = HoverTool(
tooltips=[
("index", "$index"),
("x", "@time"),
("y", "@y"),
],
active=False
)
# create a new plot with a a datetime axis type
p2 = Figure(plot_width=1000, plot_height=600, title=sticker, toolbar_location="above", x_axis_type="datetime",
tools=[hover, 'box_zoom, box_select, crosshair, resize, reset, save, wheel_zoom'])
orders = self.map_trade_id_to_orders[trade_id, sticker]
for order in orders:
a = [order.placed_dt]
b = [order.price]
source_placed = ColumnDataSource(data=dict(a=a, b=b, time=[a[0].strftime('%d-%m-%Y %H:%M:%S')]))
p2.square(a, b, legend="placed", fill_color="red", line_color="red", size=8, source=source_placed)
p2.circle(x, y, size=8, color='navy', alpha=0.2, legend="best back odds", source=source_back_odds)
p2.line(x, y, color='navy', legend="best back odds", source=source_back_odds)
# lay odds
source_lay_odds = ColumnDataSource(data=dict(z=z, t=t, time=[e.strftime('%d-%m-%Y %H:%M:%S') for e in z]))
p2.triangle(z, t, size=8, color='green', alpha=0.2, legend="best lay odds", source=source_lay_odds)
p2.line(z, t, color='green', legend="best lay odds", source=source_lay_odds)
# NEW: customize by setting attributes
# p2.title = sticker
p2.legend.location = "top_left"
p2.grid.grid_line_alpha = 0
p2.xaxis.axis_label = 'Date'
p2.yaxis.axis_label = "Best odds"
p2.ygrid.band_fill_color = "olive"
p2.ygrid.band_fill_alpha = 0.1
return p2
def plot_bollinger_signals(data, signals, ticker=None, notebook=False):
# create a new plot with a title and axis labels
p = Figure(title=ticker + ' Bollinger Bands Strategy',
x_axis_label='Date',
x_axis_type='datetime',
y_axis_label='Price in $',
plot_height=500,
plot_width=950,
tools=['pan', 'wheel_zoom'],
toolbar_location='below')
inc = data['Close'] > data['Open']
dec = data['Open'] > data['Close']
w = 12 * 60 * 60 * 1000 # half day in ms
p.segment(data.index, data['High'], data.index, data['Low'], color="black")
p.vbar(data.index[inc],
w,
data['Open'][inc],
data['Close'][inc],
fill_color="#D5E1DD",
line_color="black")
p.vbar(data.index[dec],
w,
data['Open'][dec],
data['Close'][dec],
fill_color="#F2583E",
line_color="black")
# configure so that Bokeh chooses what (if any) scroll tool is active
p.toolbar.active_scroll = "auto"
# add a line renderer with legend and line thickness
p.line(signals.index,
signals['mediumband'],
line_width=2,
legend='Mediumband',
line_color='black')
p.line(signals.index,
signals['upperband'],
line_width=2,
legend='Upperband',
line_color='orange')
p.line(signals.index,
signals['lowerband'],
line_width=2,
legend='Lowerband',
line_color='blue')
p.triangle(signals.loc[signals.positions == 1.0].index,
signals.lowerband[signals.positions == 1.0],
size=15,
fill_color='green',
legend='Buy')
p.inverted_triangle(signals.loc[signals.positions == -1.0].index,
signals.upperband[signals.positions == -1.0],
size=15,
fill_color='red',
legend='Sell')
p.legend.location = "top_left"
p.legend.click_policy = "hide"
if notebook:
# show the results
show(p, notebook_handle=True)
push_notebook()
else:
# output the results
output_file('%s Bollinger Bands Strategy.html' % ticker)
save(p)
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)
loc_slider.value = loc_val
changer = 0
f1.arrow_source.data = dict(xS=[], xE=[], yS=[], yE=[], lW = [])
f2.arrow_source.data = dict(xS=[], xE=[], yS=[], yE=[], lW = [])
button.on_click(button_fun)
rbutton.on_click(init)
init()
create_orig(orig)
ps = 0.3
plot = Figure(tools = "",title="Maxwell",title_location = "above", x_range=(0.1-ps,0.8+ps), y_range=(0.0,1.0))
plot.line(x='x', y='y', source=orig.pts, color='Black',line_width=3)
plot.line(x='x', y='y', source=f1.pts, color="#808080",line_width=5)
plot.line(x='x', y='y', source=f2.pts, color="#E37222",line_width=5)
plot.line(x='x', y='y', source=t_line, color="Black",line_width=5)
plot.triangle(x='x', y='y', size = 'size', source= f1.tri,color="#808080", line_width=2)
plot.triangle(x='x', y='y', size = 'size', source= f2.tri,color="#E37222", line_width=2)
plot.axis.visible = False
plot.outline_line_width = 7
plot.outline_line_alpha = 0.3
plot.outline_line_color = "Black"
plot.title.text_color = "black"
plot.title.text_font_style = "bold"
plot.title.align = "center"
labels1 = LabelSet(x='x', y='y', text='name', level='glyph',
x_offset=0, y_offset=0, source=f1.label, render_mode='canvas')
labels2 = LabelSet(x='x', y='y', text='name', level='glyph',
x_offset=0, y_offset=0, source=f2.label, render_mode='canvas')
plot.line(x='x', y='y', source=col2.floor, color='black', line_width=6)
plot.line(x='x', y='y', source=col3.floor, color='black', line_width=6)
plot.line(x='x', y='y', source=col4.floor, color='black', line_width=6)
#Create walls for columns that require a wall:
plot.line(x='x', y='y', source=col2.wall, color='black', line_width=6)
plot.line(x='x', y='y', source=col3.wall, color='black', line_width=6)
plot.multi_line(xs='x', ys='y', source=col4.wall, color='black', line_width=6)
#Create circles for columns that have pins:
plot.circle(x='x', y='y', source=col2.cir1, color='#0065BD', size=10)
plot.circle(x='x', y='y', source=col2.cir2, color='#0065BD', size=10)
plot.circle(x='x', y='y', source=col3.cir2, color='#0065BD', size=10)
#Create the shapes of the ends of the columns:
plot.triangle(x='x',
y='y',
source=col2.tri1,
color='black',
angle=0.0,
fill_alpha=0,
size=20)
plot.triangle(x='x',
y='y',
source=col2.tri2,
color='black',
angle=np.pi / 2,
fill_alpha=0,
size=20)
plot.triangle(x='x',
y='y',
source=col3.tri2,
color='black',
angle=np.pi / 2,
'RV', 'Space Transits', 'Ground Transits', 'Microlensing', 'Direct Imaging'
]
checkbox_button_group = CheckboxGroup(
labels=["RV", "Transits", "Microlensing", "Direct Imaging"],
active=[0, 1, 2, 3])
# transits - ground
tground = Table.read(
'/Users/tumlinson/Dropbox/LUVOIR_STDT/luvoir_simtools/planetspace/transit_ground.dat',
format='ascii',
names=['name', 'msini', 'semi', 'mstar'])
a_rad = 2.7 * tground['mstar']
tground_syms = p1.triangle(tground['semi'] / a_rad,
tground['msini'] * mjup,
color='lightblue',
fill_alpha=0.8,
line_alpha=1.,
size=8)
# transits - space
tspace = Table.read(
'/Users/tumlinson/Dropbox/LUVOIR_STDT/luvoir_simtools/planetspace/transit_space.dat',
format='ascii',
names=['name', 'msini', 'semi', 'mstar'])
a_rad = 2.7 * tspace['mstar']
tground_syms = p1.diamond(tspace['semi'] / a_rad,
tspace['msini'] * mjup,
color='darkblue',
fill_alpha=0.4,
line_alpha=1.,
size=8)
#creation of the a and b scale reference things:
plot.multi_line(
[[orig.x0, orig.xf], [orig.x0, orig.x0], [orig.xf, orig.xf]],
[[0, 0], [0 - abshift, 0 + abshift], [0 - abshift, 0 + abshift]],
color=["black", "black", "black"],
line_width=1)
plot.multi_line(
[[xb, xb], [xb - abshift, xb + abshift], [xb - abshift, xb + abshift]],
[[orig.y0, orig.yf], [orig.y0, orig.y0], [orig.yf, orig.yf]],
color=["black", "black", "black"],
line_width=1)
#Frame bases
plot.triangle(x='x',
y='y',
size='size',
source=default,
color="grey",
line_width=2)
plot.triangle(x='x',
y='y',
size='size',
source=MBD.f1.tri,
color=MBD.f1color,
line_width=2)
plot.triangle(x='x',
y='y',
size='size',
source=MBD.f2.tri,
color=MBD.f2color,
line_width=2)
# set visual properties for selected glyphs
selection_color=c_ztfr,
selection_alpha=a_ztfr,
# set visual properties for non-selected glyphs
nonselection_color=c_ztfr,
nonselection_alpha=a_ztfr,
legend = 'ZTF-r')
# Plot LCO g and r light curve data
f_lcog = fig_lc.triangle('x', 'y', source=source_lco_g, size=7,
# Set defaults
fill_color=c_lcog, line_color=c_lcog,
fill_alpha=a_lcog, line_alpha=a_lcog,
# set visual properties for selected glyphs
selection_color=c_lcog,
selection_alpha=a_lcog,
# set visual properties for non-selected glyphs
nonselection_color=c_lcog,
nonselection_alpha=a_lcog,
legend = 'LCOGT-g')
f_lcor = fig_lc.diamond('x', 'y', source=source_lco_r, size=9,
# Set defaults
fill_color=c_lcor, line_color=c_lcor,
fill_alpha=a_lcor, line_alpha=a_lcor,
# set visual properties for selected glyphs
selection_color=c_lcor,
selection_alpha=a_lcor,
# set visual properties for non-selected glyphs
nonselection_color=c_lcor,
nonselection_alpha=a_lcor,
