def create_objects(cls, securities):
ranks = utils.get_pumps_rank()
quotient_metrics = utils.get_quotient_metrics()
ranks['quotient'] = quotient_metrics['quotient']
foo = lambda x: utils.spam_counts.get(x, 0)
ranks['spams'] = map(foo, ranks['symbol'])
ranks = ranks.sort('quotient', ascending=False)
cls._pre_filtered_ranks = {
'All': {k: ranks[k]
for k in ranks.columns},
'Stocks with Spam':
dict(ranks[ranks['symbol'].isin(plugins.spam_counts.keys())].sort(
'quotient', ascending=False)),
'Stocks without Spam':
dict(ranks[~ranks['symbol'].isin(plugins.spam_counts.keys())].sort(
'quotient', ascending=False)),
}
source_stocks_rank = ColumnDataSource(
cls._pre_filtered_ranks['Stocks with Spam'])
table_stocks_rank = DataTable(source=source_stocks_rank,
width=785,
height=400,
selectable=True,
editable=True,
columns=[
TableColumn(field='symbol',
title='symbol',
editor=StringEditor()),
TableColumn(field='quotient',
title='quotient',
editor=StringEditor()),
TableColumn(field='rank',
title='rank',
editor=StringEditor()),
TableColumn(field='spams',
title='spams',
editor=StringEditor()),
])
callback = Callback(args={
'tr': table_stocks_rank,
'sr': source_stocks_rank
},
code=callbacks.source_stocks_rank)
source_stocks_rank.callback = callback
return locals()
def create_selection_plot(main_plot, theme):
static_source = ColumnDataSource(data)
selection_plot = figure(height=100,
tools="box_select",
x_axis_location="above",
x_axis_type="datetime",
toolbar_location=None,
outline_line_color=None,
name="small_plot")
selection_source = ColumnDataSource()
for k in ['end', 'values', 'start', 'bottom']:
selection_source.add([], k)
if theme == 'default':
selection_color = '#c6dbef'
elif theme == 'dark':
selection_color = "#FFAD5C"
selection_plot.quad(top='values',
bottom='bottom',
left='start',
right='end',
source=selection_source,
color=selection_color,
fill_alpha=0.5)
selection_plot.line('Date', 'Price', color='#A6CEE3', source=static_source)
selection_plot.circle('Date',
'Price',
color='#A6CEE3',
source=static_source,
size=1)
style_selection_plot(selection_plot, theme)
select_tool = selection_plot.select(dict(type=BoxSelectTool))
select_tool.dimensions = ['width']
code = """
if (window.xrange_base_start == undefined){
window.xrange_base_start = main_plot.get('x_range').get('start');
}
if (window.xrange_base_end == undefined){
window.xrange_base_end = main_plot.get('x_range').get('end');
}
data = source.get('data');
sel = source.get('selected')['1d']['indices'];
var mi = 1000000000;
var ma = -100000;
if (sel.length == 0){
var url = "http://127.0.0.1:5000/alldata";
source_data = selection_source.get('data');
source_data.bottom = []
source_data.values = [];
source_data.start = [];
source_data.end = [];
// reset main plot ranges
main_range.set('start', window.xrange_base_start);
main_range.set('end', window.xrange_base_end);
}else{
for (i=0; i<sel.length; i++){
if (mi>sel[i]){
mi = sel[i];
}
if (ma<sel[i]){
ma = sel[i];
}
}
var url = "http://127.0.0.1:5000/subsample/"+data.Date[mi]+"/"+data.Date[ma];
source_data = selection_source.get('data');
source_data.bottom = [0]
source_data.values = [700];
source_data.start = [data.Date[mi]];
source_data.end = [data.Date[ma]];
main_range = main_plot.get('x_range');
main_range.set('start', data.Date[mi]);
main_range.set('end', data.Date[ma]);
}
xmlhttp = new XMLHttpRequest();
xmlhttp.open("GET", url, true);
xmlhttp.send();
selection_source.trigger('change');
if (sel.length==0){
$("#details_panel").addClass("hidden");
$("#details_panel").html("");
}else{
var url = "http://127.0.0.1:5000/details";
xhr = $.ajax({
type: 'GET',
url: url,
contentType: "application/json",
// data: jsondata,
header: {
client: "javascript"
}
});
xhr.done(function(details) {
$("#details_panel").removeClass("hidden");
$("#details_panel").html("<h3>Selected Region Report</h3>");
$("#details_panel").append("<div>From " + details.start + " to " + details.end + "</div>");
$("#details_panel").append("<div>Number of original samples " + details.original_samples_no + "</div>");
$("#details_panel").append("<div>Number of samples " + details.samples_no + "</div>");
$("#details_panel").append("<div>Factor " + details.factor + "</div>");
});
}
"""
callback = Callback(args={
'source': static_source,
'selection_source': selection_source,
'main_plot': main_plot
},
code=code)
static_source.callback = callback
return selection_plot
x = np.linspace(0, 10, 500)
y = np.sin(x)
source = ColumnDataSource(data=dict(x=x, y=y))
plot = figure(y_range=(-10, 10), plot_width=400, plot_height=400)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)
callback = Callback(args=dict(source=source),
code="""
var data = source.get('data');
var A = amp.get('value')
var k = freq.get('value')
var phi = phase.get('value')
var B = offset.get('value')
x = data['x']
y = data['y']
for (i = 0; i < x.length; i++) {
y[i] = B + A*Math.sin(k*x[i]+phi);
}
source.trigger('change');
""")
amp_slider = Slider(start=0.1,
end=10,
value=1,
step=.1,
title="Amplitude",
callback=callback)
callback.args["amp"] = amp_slider
def test_actions_callback_returns_callbacks_customjs(self):
callback = Callback()
self.assertIsInstance(callback, callbacks.CustomJS)
# NOTE: the JS functions for converting RGB to hex are taken from the excellent answer
# by Tim Down at http://stackoverflow.com/questions/5623838/rgb-to-hex-and-hex-to-rgb
callback = Callback(args=dict(source=source),
code="""
function componentToHex(c) {
var hex = c.toString(16);
return hex.length == 1 ? "0" + hex : hex;
}
function rgbToHex(r, g, b) {
return "#" + componentToHex(r) + componentToHex(g) + componentToHex(b);
}
var data = source.get('data');
var RS = red_slider;
var GS = green_slider;
var BS = blue_slider;
color = data['color'];
var red_from_slider = RS.get('value');
var green_from_slider = GS.get('value');
var blue_from_slider = BS.get('value');
text_color = data['text_color'];
color[0] = rgbToHex(red_from_slider, green_from_slider, blue_from_slider);
if ((red_from_slider > 127) || (green_from_slider > 127) || (blue_from_slider > 127)) {
text_color[0] = '#000000';
}
else {
text_color[0] = '#ffffff';
}
source.trigger('change');
""")
# create slider tool objects to control the RGB levels for first plot. Set callback function to allow refresh
def create_objects(cls, symbol, df, securities):
descr_box = Paragraph(text='content loading...')
btn_close_loading = Button(label='Close Loading')
dialog_loading = Dialog(title='loading',
content=vplot(descr_box),
name='loading_dialog',
buttons=[btn_close_loading],
visible=False)
source_data = dict(df)
main_source = ColumnDataSource(dict(df))
source = ColumnDataSource(source_data)
# TODO: REMOVE THIS COMMENTED CODE! IT'S JUST THE PREVIOUS
# VERSION USED BEFORE NEW P&D Cached results and algorithm
# get the cached results of the P&D algorithm computed with the
# "default" configuration
# intervals = utils.cached_pumps.get(symbol, pumps.to_dicts(((),(),(),(),(),())))
# intervals['bottom'] = [0] * len(intervals['start'])
# intervals['values'] = [max(df['price'])] * len(intervals['start'])
#
# intervals = pd.DataFrame(intervals)
# new version
stats = utils.get_symbols_cached_stats()[symbol]
intervals = pd.DataFrame(stats)
intervals['bottom'] = [0] * len(intervals['start'])
intervals['values'] = [max(df['price'])] * len(intervals['start'])
conv = lambda x: utils.to_seconds(pd.to_datetime(x))
intervals = intervals[
(pd.to_datetime(intervals['start']) > conv(config.date_range[0])) &
(pd.to_datetime(intervals['start']) < conv(config.date_range[1]))]
# Create P&Ds intervals DataSource
intervals_source = ColumnDataSource(intervals)
source.tags = ['main_source']
trends = utils.load_trends_data(symbol, start_date=min(df['dt']))
trends_source = ColumnDataSource(trends)
trades = Slider(title="trades",
name='trades',
value=0,
start=0,
end=124,
step=1)
# Selectors
symbol = Select.create(options=securities,
value=symbol,
name='symbol',
title="")
window_selector = Select.create(options=['---'],
name='period_selector',
title="Search intervals with:")
symbol_filter = Select.create(
options=['All', 'Stocks with Spam', 'Stocks without Spam'],
name='symbol_filter',
title="Filter Symbols:",
value='Stocks with Spam')
callback = Callback(args={
'symbol_filter': symbol_filter,
'dialog_loading': dialog_loading
},
code=callbacks.symbol_filter)
symbol_filter.callback = callback
btn_detect_pumps = Button(label='Configure P&D Detection',
name='config_pumps')
main_tab = Panel(title="Main")
tabs = Tabs()
# Create STOCKS TABLE
ranks = utils.get_pumps_rank()
# quotient_metrics = utils.get_quotient_metrics()
# ranks['quotient'] = quotient_metrics['quotient']
foo = lambda x: utils.spams_count.get(x, 0)
ranks['spams'] = map(foo, ranks['symbol'])
ranks = ranks.sort(['spams', 'vol_quotient'], ascending=False)
cls._pre_filtered_ranks = {
'All': {k: ranks[k]
for k in ranks.columns},
'Stocks with Spam':
dict(ranks[ranks['spams'] > 0].sort('vol_quotient',
ascending=False)),
'Stocks without Spam':
dict(ranks[ranks['spams'] == 0].sort('vol_quotient',
ascending=False)),
}
source_stocks_rank = ColumnDataSource(cls._pre_filtered_ranks['All'])
table_stocks_rank = DataTable(
source=source_stocks_rank,
width=560,
height=450,
selectable=True,
editable=True,
columns=[
TableColumn(field='symbol',
title='symbol',
width=130,
editor=StringEditor()),
TableColumn(field='vol_quotient',
title='volume ratio',
editor=StringEditor(),
default_sort='descending'),
TableColumn(field='risk_score',
title='risk',
width=100,
editor=StringEditor(),
default_sort='descending'),
TableColumn(field='spams',
title='spams',
width=130,
editor=StringEditor(),
default_sort='descending'),
])
callback = Callback(args={
'tr': table_stocks_rank,
'sr': source_stocks_rank,
'symb': symbol,
'dialog_loading': dialog_loading
},
code=callbacks.source_stocks_rank)
source_stocks_rank.callback = callback
return locals()
var url = "http://127.0.0.1:5000/subsample/"+data.Date[mi]+"/"+data.Date[ma];
source_data = selection_source.get('data');
source_data.bottom = [0]
source_data.values = [700];
source_data.start = [data.Date[mi]];
source_data.end = [data.Date[ma]];
main_range = main_plot.get('x_range');
main_range.set('start', data.Date[mi]);
main_range.set('end', data.Date[ma]);
}
xmlhttp = new XMLHttpRequest();
xmlhttp.open("GET", url, true);
xmlhttp.send();
selection_source.trigger('change');
"""
callback = Callback(args={
'source': static_source,
'selection_source': selection_source,
'main_plot': p
},
code=code)
static_source.callback = callback
layout = vplot(selection_plot, p)
show(layout)
line_color=None,
fill_alpha=0.8))
text_y = text_y - 5
# Add the slider
code = """
var year = slider.get('value'),
sources = %s,
new_source_data = sources[year].get('data');
renderer_source.set('data', new_source_data);
renderer_source.trigger('change');
text_source.set('data', {'year': [String(year)]});
text_source.trigger('change');
""" % js_source_array
callback = Callback(args=sources, code=code)
slider = Slider(start=years[0],
end=years[-1],
value=1,
step=1,
title="Year",
callback=callback,
name='testy')
callback.args["slider"] = slider
callback.args["renderer_source"] = renderer_source
callback.args["text_source"] = text_source
# Stick the plot and the slider together
layout = vplot(plot, slider)
# Open our custom template
