def set_input_selector(self):
# print ("set_input_selector")
"""Creates and configures each selector (drop-down menu)."""
col_names = [x['name'] for x in self.columns]
col_names.append('None')
self.plot_selector = Select.create(
title="PlotType",
name="plot_type",
value=self.plot_type,
options=["line", "scatter", "bar"],
)
self.x_selector = Select.create(
name="x",
value=self.x,
options=col_names,
)
self.y_selector = Select.create(
name="y",
value=self.y,
options=col_names,
)
self.agg_selector = Select.create(
name='agg',
value=self.agg,
options=['sum', 'mean', 'last', 'count', 'percent'],
)
def set_input_selector(self):
# print ("set_input_selector")
"""Creates and configures each selector (drop-down menu)."""
col_names = [x['name'] for x in self.columns]
col_names.append('None')
self.plot_selector = Select.create(
title="PlotType",
name="plot_type",
value=self.plot_type,
options=["line", "scatter", "bar"],
)
self.x_selector = Select.create(
name="x",
value=self.x,
options=col_names,
)
self.y_selector = Select.create(
name="y",
value=self.y,
options=col_names,
)
self.agg_selector = Select.create(
name='agg',
value=self.agg,
options=['sum', 'mean', 'last', 'count', 'percent'],
)
def create_layout(self):
# create figure
self.x_range = Range1d(start=self.model.map_extent[0],
end=self.model.map_extent[2], bounds=None)
self.y_range = Range1d(start=self.model.map_extent[1],
end=self.model.map_extent[3], bounds=None)
self.fig = Figure(tools='wheel_zoom,pan', x_range=self.x_range,
y_range=self.y_range)
self.fig.plot_height = 660
self.fig.plot_width = 990
self.fig.axis.visible = False
# add tiled basemap
self.tile_source = WMTSTileSource(url=self.model.basemap)
self.tile_renderer = TileRenderer(tile_source=self.tile_source)
self.fig.renderers.append(self.tile_renderer)
# add datashader layer
self.image_source = ImageSource(url=self.model.service_url,
extra_url_vars=self.model.shader_url_vars)
self.image_renderer = DynamicImageRenderer(image_source=self.image_source)
self.fig.renderers.append(self.image_renderer)
# add ui components
axes_select = Select.create(name='Axes',
options=self.model.axes)
axes_select.on_change('value', self.on_axes_change)
field_select = Select.create(name='Field', options=self.model.fields)
field_select.on_change('value', self.on_field_change)
aggregate_select = Select.create(name='Aggregate',
options=self.model.aggregate_functions)
aggregate_select.on_change('value', self.on_aggregate_change)
transfer_select = Select.create(name='Transfer Function',
options=self.model.transfer_functions)
transfer_select.on_change('value', self.on_transfer_function_change)
basemap_select = Select.create(name='Basemap', value='Toner',
options=self.model.basemaps)
basemap_select.on_change('value', self.on_basemap_change)
opacity_slider = Slider(title="Opacity", value=100, start=0,
end=100, step=1)
opacity_slider.on_change('value', self.on_opacity_slider_change)
controls = [axes_select, field_select, aggregate_select,
transfer_select, basemap_select, opacity_slider]
self.controls = HBox(width=self.fig.plot_width, children=controls)
self.layout = VBox(width=self.fig.plot_width,
height=self.fig.plot_height,
children=[self.controls, self.fig])
def line_config(app, df):
options = CheckboxGroup(
labels=['Show peaks', 'Show Std. Dev.', 'Bolinger Bands'],
name='new_chart_options')
title = TextInput(title="Chart Title",
name='new_chart_title',
value="Line")
new_chart_index = Select.create(options=['---'] + list(df.columns),
name='"new_chart_index"',
title="Chart index")
chart_values_select = MultiSelect.create(options=df.columns,
name="chart_values",
title="Values")
chart_data = AppHBox(
app=app, children=[new_chart_index, chart_values_select, options])
main_tab = AppVBox(app=app, children=[title, chart_data, 'select_palette'])
confirm_chart_button = Button(label="Confirm",
type="success",
name='confirm_add_chart')
return {
'dlg':
Dialog(buttons=[confirm_chart_button], content=main_tab, visible=True),
"new_chart_index":
new_chart_index,
'new_chart_title':
title,
'chart_values':
chart_values_select,
'new_chart_options':
options
}
def create_layout(self):
self.plot_selector = Select.create(
title="PlotType",
name="plot_type",
value='area',
options=['area', "line", "scatter", "bar"],
)
self.btn_confirm = Button(label='add plot')
self.layout = vplot(hplot(self.plot_selector, self.btn_confirm), self.plot)
def make_inst_date_input(self):
observations = self._ccf_interface.get_observations(self.star)
observations = ['/'.join(obs).ljust(20, ' ') for obs in observations]
self.inst_date = observations[0]
if isinstance(self.inst_date_select, Select):
self.inst_date_select.update(value=observations[0], options=observations)
else:
self.inst_date_select = Select.create(
name='Instrument/Date',
value=observations[0],
options=observations,
)
def line_config(app, df):
options = CheckboxGroup(
labels=['Show peaks', 'Show Std. Dev.', 'Bolinger Bands'],
name='new_chart_options'
)
title = TextInput(title="Chart Title", name='new_chart_title', value="Line")
new_chart_index = Select.create(options=['---']+list(df.columns), name='"new_chart_index"', title="Chart index")
chart_values_select = MultiSelect.create(options=df.columns, name="chart_values", title="Values")
chart_data = AppHBox(app=app, children=[new_chart_index, chart_values_select, options])
main_tab = AppVBox(app=app, children=[title, chart_data, 'select_palette'])
confirm_chart_button = Button(label="Confirm", type="success", name='confirm_add_chart')
return {
'dlg': Dialog(buttons=[confirm_chart_button], content=main_tab, visible=True),
"new_chart_index": new_chart_index,
'new_chart_title': title,
'chart_values': chart_values_select,
'new_chart_options': options
}
def dashboard():
"""
Creates the main app objects
"""
# TODO: Should find a better design and remove those global objs...
global source
global csource
source = ColumnDataSource(df)
source.tags = ['main_source']
csource = ColumnDataSource(cdf)
csource.tags = ['crash_source']
select_sec = Select.create(options=SECURITIES, name='select_sec', title="")
asel = Select.create(options=df.columns, name='field_to_add', title="")
chart_sel = Select.create(options=chart_types, name='chart_to_add', title="")
msel = MultiSelect.create(options=[], name='ms')
abutton = Button(label="add", type="success", name='add_button')
rbutton = Button(label="remove", type="danger", name='remove_button')
add_chart_button = Button(label="add chart", type="success", name='add_chart')
data_table = DataTable(source=source, editable=True, width=500, height=400)
ccolumns = [TableColumn(field=x, title=x, editor=NumberEditor()) for x in cdf.columns]
crashes_table = DataTable(source=csource, editable=True, width=1200, height=400, columns=ccolumns)
charts_box = AppVBox(children=[], name='charts_box')
counts = cdf['crashes']
crashes_hist = charts.Histogram({'crash_counts': counts}, bins=20, height=300, title="# Crashes per Symbol")
crashes_scatter = create_crashes_scatter()
main_tab = VBox(children=[], name='d_box')
dlg = Dialog(buttons=[], content=main_tab , visible=False)
options = CheckboxGroup(
labels=['Show peaks', 'Show Std. Dev.', 'Bolinger Bands'],
name='new_chart_options'
)
select_palette = Select.create(options=brewer.keys(), name='select_palette', title="Palette")
return {
# security tab
'select_sec': select_sec,
'field_to_add': asel,
'chart_to_add': chart_sel,
'ms': msel,
'dt': data_table,
'add_button': abutton,
'remove_button': rbutton,
'add_chart': add_chart_button,
'charts_box': charts_box,
'dlg': dlg,
# Crashes tab objs
'crashes_hist': crashes_hist,
'crashes_scatter': crashes_scatter,
'crashes_table': crashes_table,
'crash_stats': PreText(text="NO CRASHES FOR SYMBOL %s" % SYMBOL, width=300),
#
'chart_values': MultiSelect.create(options=df.columns, name="chart_values", title="Values"),
'new_chart_index': Select.create(options=['---']+list(df.columns), title="Chart index", name="new_chart_index"),
'new_chart_title': TextInput(title="Chart Title", name='new_chart_title', value=''),
'new_chart_options': options,
'select_palette': select_palette,
# ANNOTATIONS
"annotations": MultiSelect.create(options=[], name="annotations", title="Annotations"),
"add_annotation": Button(label="add", type="success", name='add_annotation'),
"delete_annotation": Button(label="remove", type="danger", name='delete_annotation'),
"show_annotation": Button(label="Show", type="link", name='show_annotation'),
'new_annotation_dlg': Dialog(buttons=[], content=main_tab , visible=False),
'annotation_txt': TextInput(title="New Annotation", name='annotation_txt', value=''),
'new_annotation_options': CheckboxGroup(labels=[], name='new_annotation_options'),
}
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()
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()