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 _get_columns(self, element, data):
columns = []
for d in element.dimensions():
col = dimension_sanitizer(d.name)
kind = data[col].dtype.kind
if kind == 'i':
formatter = NumberFormatter()
editor = IntEditor()
elif kind == 'f':
formatter = NumberFormatter(format='0,0.0[00000]')
editor = NumberEditor()
elif kind == 'M' or (kind == 'O' and len(data[col])
and type(data[col][0]) in datetime_types):
dimtype = element.get_dimension_type(0)
dformat = Dimension.type_formatters.get(
dimtype, '%Y-%m-%d %H:%M:%S')
formatter = DateFormatter(format=dformat)
editor = DateEditor()
else:
formatter = StringFormatter()
editor = StringEditor()
column = TableColumn(field=dimension_sanitizer(d.name),
title=d.pprint_label,
editor=editor,
formatter=formatter)
columns.append(column)
return columns
def initialize_plot(self, ranges=None, plot=None, plots=None, source=None):
"""
Initializes a new plot object with the last available frame.
"""
# Get element key and ranges for frame
element = self.hmap.last
key = self.keys[-1]
self.current_frame = element
self.current_key = key
style = self.lookup_options(element, 'style')[self.cyclic_index]
data, _, style = self.get_data(element, ranges, style)
if source is None:
source = self._init_datasource(data)
self.handles['source'] = source
columns = []
dims = element.dimensions()
for d in dims:
col = dimension_sanitizer(d.name)
kind = data[col].dtype.kind
if kind == 'i':
formatter = NumberFormatter()
editor = IntEditor()
elif kind == 'f':
formatter = NumberFormatter(format='0,0.0[00000]')
editor = NumberEditor()
elif kind == 'M' or (kind == 'O' and len(data[col])
and type(data[col][0]) in datetime_types):
dimtype = element.get_dimension_type(0)
dformat = Dimension.type_formatters.get(
dimtype, '%Y-%m-%d %H:%M:%S')
formatter = DateFormatter(format=dformat)
editor = DateEditor()
else:
formatter = StringFormatter()
editor = StringEditor()
column = TableColumn(field=d.name,
title=d.pprint_label,
editor=editor,
formatter=formatter)
columns.append(column)
style['reorderable'] = False
table = DataTable(source=source,
columns=columns,
height=self.height,
width=self.width,
**style)
self.handles['plot'] = table
self.handles['glyph_renderer'] = table
self._execute_hooks(element)
self.drawn = True
for cb in self.callbacks:
cb.initialize()
return table
def _get_columns(self):
if self.value is None:
return []
index = [self.value.index.name or 'index']
col_names = index + list(self.value.columns)
columns = []
for col in col_names:
if col in self.value.columns:
data = self.value[col]
else:
data = self.value.index
kind = data.dtype.kind
if kind == 'i':
formatter = NumberFormatter()
editor = IntEditor()
elif kind == 'f':
formatter = NumberFormatter(format='0,0.0[00000]')
editor = NumberEditor()
elif isdatetime(data) or kind == 'M':
formatter = DateFormatter(format='%Y-%m-%d %H:%M:%S')
editor = DateEditor()
else:
formatter = StringFormatter()
editor = StringEditor()
if col in self.editors:
editor = self.editors[col]
if col in self.formatters:
formatter = self.formatters[col]
if str(col) != col:
self._renamed_cols[str(col)] = col
width = self.widths.get(str(col))
column = TableColumn(field=str(col),
title=str(col),
editor=editor,
formatter=formatter,
width=width)
columns.append(column)
return columns
BoxSelectTool(),
LassoSelectTool(),
ResetTool()
])
p.circle("x",
"y",
size=20,
line_color="color",
fill_color="color",
fill_alpha=0.5,
source=source)
formatter = HTMLTemplateFormatter(template="<div><%= value %></div>")
table_source = ColumnDataSource(data=table_data)
columns = [TableColumn(field='IMGS', title='Structure', width=300, formatter=formatter),
TableColumn(field='SMILES', title='SMILES', width=300, editor=StringEditor())] + \
[TableColumn(field=prop, title=prop, width=150) for prop in properties.keys()]
table = HighTable(source=table_source,
columns=columns,
editable=True,
width=1200,
height=1200)
button = Button(label="Download", button_type="warning")
button.callback = CustomJS(args=dict(source=table_source),
code=open(
os.path.join(os.path.dirname(__file__),
"download.js")).read())
def colors_from_data(data):
from bokeh.embed import file_html
from bokeh.resources import INLINE
from bokeh.util.browser import view
from bokeh.sampledata.autompg2 import autompg2 as mpg
source = ColumnDataSource(mpg)
manufacturers = sorted(mpg["manufacturer"].unique())
models = sorted(mpg["model"].unique())
transmissions = sorted(mpg["trans"].unique())
drives = sorted(mpg["drv"].unique())
classes = sorted(mpg["class"].unique())
columns = [
TableColumn(field="manufacturer", title="Manufacturer", editor=SelectEditor(options=manufacturers), formatter=StringFormatter(font_style="bold")),
TableColumn(field="model", title="Model", editor=StringEditor(completions=models)),
TableColumn(field="displ", title="Displacement", editor=NumberEditor(step=0.1), formatter=NumberFormatter(format="0.0")),
TableColumn(field="year", title="Year", editor=IntEditor()),
TableColumn(field="cyl", title="Cylinders", editor=IntEditor()),
TableColumn(field="trans", title="Transmission", editor=SelectEditor(options=transmissions)),
TableColumn(field="drv", title="Drive", editor=SelectEditor(options=drives)),
TableColumn(field="class", title="Class", editor=SelectEditor(options=classes)),
TableColumn(field="cty", title="City MPG", editor=IntEditor()),
TableColumn(field="hwy", title="Highway MPG", editor=IntEditor()),
]
data_table = DataTable(source=source, columns=columns, editable=True, width=1000,
index_position=-1, index_header="row index", index_width=60)
plot = Plot(title=None, plot_width=1000, plot_height=300)
# Set up x & y axis
def create(self):
print("running create...")
manufacturers = sorted(mpg["manufacturer"].unique())
models = sorted(mpg["model"].unique())
transmissions = sorted(mpg["trans"].unique())
drives = sorted(mpg["drv"].unique())
classes = sorted(mpg["class"].unique())
manufacturer_select = Select(title="Manufacturer:",
value="All",
options=["All"] + manufacturers)
manufacturer_select.on_change('value', self.on_manufacturer_change)
model_select = Select(title="Model:",
value="All",
options=["All"] + models)
model_select.on_change('value', self.on_model_change)
transmission_select = Select(title="Transmission:",
value="All",
options=["All"] + transmissions)
transmission_select.on_change('value', self.on_transmission_change)
drive_select = Select(title="Drive:",
value="All",
options=["All"] + drives)
drive_select.on_change('value', self.on_drive_change)
class_select = Select(title="Class:",
value="All",
options=["All"] + classes)
class_select.on_change('value', self.on_class_change)
columns = [
TableColumn(field="manufacturer",
title="Manufacturer",
editor=SelectEditor(options=manufacturers),
formatter=StringFormatter(font_style="bold")),
TableColumn(field="model",
title="Model",
editor=StringEditor(completions=models)),
TableColumn(field="displ",
title="Displacement",
editor=NumberEditor(step=0.1),
formatter=NumberFormatter(format="0.0")),
TableColumn(field="year", title="Year", editor=IntEditor()),
TableColumn(field="cyl", title="Cylinders", editor=IntEditor()),
TableColumn(field="trans",
title="Transmission",
editor=SelectEditor(options=transmissions)),
TableColumn(field="drv",
title="Drive",
editor=SelectEditor(options=drives)),
TableColumn(field="class",
title="Class",
editor=SelectEditor(options=classes)),
TableColumn(field="cty", title="City MPG", editor=IntEditor()),
TableColumn(field="hwy", title="Highway MPG", editor=IntEditor()),
]
data_table = DataTable(source=self.source,
columns=columns,
editable=True,
width=1300)
plot = Plot(title=None,
x_range=DataRange1d(),
y_range=DataRange1d(),
plot_width=1000,
plot_height=300)
# Set up x & y axis
plot.add_layout(LinearAxis(), 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
# Add Glyphs
cty_glyph = Circle(x="index",
y="cty",
fill_color="#396285",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
hwy_glyph = Circle(x="index",
y="hwy",
fill_color="#CE603D",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
cty = plot.add_glyph(self.source, cty_glyph)
hwy = plot.add_glyph(self.source, hwy_glyph)
# Add the tools
tooltips = [
("Manufacturer", "@manufacturer"),
("Model", "@model"),
("Displacement", "@displ"),
("Year", "@year"),
("Cylinders", "@cyl"),
("Transmission", "@trans"),
("Drive", "@drv"),
("Class", "@class"),
]
cty_hover_tool = HoverTool(renderers=[cty],
tooltips=tooltips + [("City MPG", "@cty")])
hwy_hover_tool = HoverTool(renderers=[hwy],
tooltips=tooltips +
[("Highway MPG", "@hwy")])
select_tool = BoxSelectTool(renderers=[cty, hwy], dimensions='width')
plot.add_tools(cty_hover_tool, hwy_hover_tool, select_tool)
controls = WidgetBox(manufacturer_select, model_select,
transmission_select, drive_select, class_select)
top_panel = Row(controls, plot)
layout = Column(top_panel, data_table)
return layout
def create(self):
manufacturers = sorted(mpg["manufacturer"].unique())
models = sorted(mpg["model"].unique())
transmissions = sorted(mpg["trans"].unique())
drives = sorted(mpg["drv"].unique())
classes = sorted(mpg["class"].unique())
manufacturer_select = Select(title="Manufacturer:",
value="All",
options=["All"] + manufacturers)
manufacturer_select.on_change('value', self.on_manufacturer_change)
model_select = Select(title="Model:",
value="All",
options=["All"] + models)
model_select.on_change('value', self.on_model_change)
transmission_select = Select(title="Transmission:",
value="All",
options=["All"] + transmissions)
transmission_select.on_change('value', self.on_transmission_change)
drive_select = Select(title="Drive:",
value="All",
options=["All"] + drives)
drive_select.on_change('value', self.on_drive_change)
class_select = Select(title="Class:",
value="All",
options=["All"] + classes)
class_select.on_change('value', self.on_class_change)
columns = [
TableColumn(field="manufacturer",
title="Manufacturer",
editor=SelectEditor(options=manufacturers),
formatter=StringFormatter(font_style="bold")),
TableColumn(field="model",
title="Model",
editor=StringEditor(completions=models)),
TableColumn(field="displ",
title="Displacement",
editor=NumberEditor(step=0.1),
formatter=NumberFormatter(format="0.0")),
TableColumn(field="year", title="Year", editor=IntEditor()),
TableColumn(field="cyl", title="Cylinders", editor=IntEditor()),
TableColumn(field="trans",
title="Transmission",
editor=SelectEditor(options=transmissions)),
TableColumn(field="drv",
title="Drive",
editor=SelectEditor(options=drives)),
TableColumn(field="class",
title="Class",
editor=SelectEditor(options=classes)),
TableColumn(field="cty", title="City MPG", editor=IntEditor()),
TableColumn(field="hwy", title="Highway MPG", editor=IntEditor()),
]
data_table = DataTable(source=self.source,
columns=columns,
editable=True)
xdr = DataRange1d()
ydr = DataRange1d()
plot = Plot(title=None,
x_range=xdr,
y_range=ydr,
plot_width=800,
plot_height=300)
xaxis = LinearAxis(plot=plot)
plot.below.append(xaxis)
yaxis = LinearAxis(plot=plot)
ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker)
plot.left.append(yaxis)
cty_glyph = Circle(x="index",
y="cty",
fill_color="#396285",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
hwy_glyph = Circle(x="index",
y="hwy",
fill_color="#CE603D",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
cty = GlyphRenderer(data_source=self.source, glyph=cty_glyph)
hwy = GlyphRenderer(data_source=self.source, glyph=hwy_glyph)
tooltips = [
("Manufacturer", "@manufacturer"),
("Model", "@model"),
("Displacement", "@displ"),
("Year", "@year"),
("Cylinders", "@cyl"),
("Transmission", "@trans"),
("Drive", "@drv"),
("Class", "@class"),
]
cty_hover_tool = HoverTool(plot=plot,
renderers=[cty],
tooltips=tooltips + [("City MPG", "@cty")])
hwy_hover_tool = HoverTool(plot=plot,
renderers=[hwy],
tooltips=tooltips +
[("Highway MPG", "@hwy")])
select_tool = BoxSelectTool(plot=plot,
renderers=[cty, hwy],
dimensions=['width'])
plot.tools.extend([cty_hover_tool, hwy_hover_tool, select_tool])
plot.renderers.extend([cty, hwy, ygrid])
controls = VBox(children=[
manufacturer_select, model_select, transmission_select,
drive_select, class_select
],
width=200)
top_panel = HBox(children=[controls, plot])
layout = VBox(children=[top_panel, data_table])
return layout
source = ColumnDataSource(mpg)
manufacturers = sorted(mpg["manufacturer"].unique())
models = sorted(mpg["model"].unique())
transmissions = sorted(mpg["trans"].unique())
drives = sorted(mpg["drv"].unique())
classes = sorted(mpg["class"].unique())
columns = [
TableColumn(field="manufacturer",
title="Manufacturer",
editor=SelectEditor(options=manufacturers),
formatter=StringFormatter(font_style="bold")),
TableColumn(field="model",
title="Model",
editor=StringEditor(completions=models)),
TableColumn(field="displ",
title="Displacement",
editor=NumberEditor(step=0.1),
formatter=NumberFormatter(format="0.0")),
TableColumn(field="year", title="Year", editor=IntEditor()),
TableColumn(field="cyl", title="Cylinders", editor=IntEditor()),
TableColumn(field="trans",
title="Transmission",
editor=SelectEditor(options=transmissions)),
TableColumn(field="drv",
title="Drive",
editor=SelectEditor(options=drives)),
TableColumn(field="class",
title="Class",
editor=SelectEditor(options=classes)),
def mk_tab(color):
plot = figure(plot_width=300, plot_height=300)
plot.scatter(flowers["petal_length"], flowers["petal_width"], color=color, fill_alpha=0.2, size=12)
return Panel(title="Tab 1: %s" % color.capitalize(), child=plot)
tabs = Tabs(tabs=[mk_tab("red"), mk_tab("green"), mk_tab("blue")])
source = ColumnDataSource(data=mpg)
columns = [
TableColumn(field="manufacturer",
title="Manufacturer",
editor=SelectEditor(options=sorted(mpg["manufacturer"].unique())),
formatter=StringFormatter(font_style="bold")),
TableColumn(field="model",
title="Model",
editor=StringEditor(completions=sorted(mpg["model"].unique()))),
TableColumn(field="displ",
title="Displacement",
editor=NumberEditor(step=0.1),
formatter=NumberFormatter(format="0.0")),
TableColumn(field="year",
title="Year",
editor=IntEditor()),
TableColumn(field="cyl",
title="Cylinders",
editor=IntEditor()),
TableColumn(field="trans",
title="Transmission",
editor=SelectEditor(options=sorted(mpg["trans"].unique()))),
TableColumn(field="drv",
title="Drive",
def make_example_datatable():
source = ColumnDataSource(mpg)
print(source.column_names)
manufacturers = sorted(mpg["manufacturer"].unique())
models = sorted(mpg["model"].unique())
transmissions = sorted(mpg["trans"].unique())
drives = sorted(mpg["drv"].unique())
classes = sorted(mpg["class"].unique())
columns = [
TableColumn(field="manufacturer",
title="Manufacturer",
editor=SelectEditor(options=manufacturers),
formatter=StringFormatter(font_style="bold")),
TableColumn(field="model",
title="Model",
editor=StringEditor(completions=models)),
TableColumn(field="displ",
title="Displacement",
editor=NumberEditor(step=0.1),
formatter=NumberFormatter(format="0.0")),
TableColumn(field="year", title="Year", editor=IntEditor()),
TableColumn(field="cyl", title="Cylinders", editor=IntEditor()),
TableColumn(field="trans",
title="Transmission",
editor=SelectEditor(options=transmissions)),
TableColumn(field="drv",
title="Drive",
editor=SelectEditor(options=drives)),
TableColumn(field="class",
title="Class",
editor=SelectEditor(options=classes)),
TableColumn(field="cty", title="City MPG", editor=IntEditor()),
TableColumn(field="hwy", title="Highway MPG", editor=IntEditor()),
]
data_table = DataTable(source=source,
columns=columns,
editable=True,
width=1000)
plot = Plot(title=None,
x_range=DataRange1d(),
y_range=DataRange1d(),
plot_width=1000,
plot_height=300)
# Set up x & y axis
plot.add_layout(LinearAxis(), 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
# Add Glyphs
cty_glyph = Circle(x="index",
y="cty",
fill_color="#396285",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
hwy_glyph = Circle(x="index",
y="hwy",
fill_color="#CE603D",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
cty = plot.add_glyph(source, cty_glyph)
hwy = plot.add_glyph(source, hwy_glyph)
# Add the tools
tooltips = [
("Manufacturer", "@manufacturer"),
("Model", "@model"),
("Displacement", "@displ"),
("Year", "@year"),
("Cylinders", "@cyl"),
("Transmission", "@trans"),
("Drive", "@drv"),
("Class", "@class"),
]
cty_hover_tool = HoverTool(renderers=[cty],
tooltips=tooltips + [("City MPG", "@cty")])
hwy_hover_tool = HoverTool(renderers=[hwy],
tooltips=tooltips +
[("Highway MPG", "@hwy")])
select_tool = BoxSelectTool(renderers=[cty, hwy], dimensions='width')
plot.add_tools(cty_hover_tool, hwy_hover_tool, select_tool)
layout = Column(plot, data_table)
doc = Document()
doc.add_root(layout)
return doc
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()
