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 create_2d_plot(self) -> Figure:
fig = Figure(width=300, height=300, x_range=(-2, 2), y_range=(-2, 2))
fig.circle(x='x', y='y', color='color', source=self.data_source)
fig.segment(x0='x',
y0='y',
x1='xn',
y1='yn',
color='color',
line_dash='dotted',
source=self.data_source)
return fig
BUFSIZE = 200
MA12, MA26, EMA12, EMA26 = '12-tick Moving Avg', '26-tick Moving Avg', '12-tick EMA', '26-tick EMA'
source = ColumnDataSource(dict(
time=[], average=[], low=[], high=[], open=[], close=[],
ma=[], macd=[], macd9=[], macdh=[], color=[]
))
p = Figure(plot_height=600, tools="xpan,xwheel_zoom,xbox_zoom,reset", x_axis_type=None)
p.x_range.follow = "end"
p.x_range.follow_interval = 100
p.line(x='time', y='average', alpha=0.2, line_width=3, color='navy', source=source)
p.line(x='time', y='ma', alpha=0.8, line_width=2, color='orange', source=source)
p.segment(x0='time', y0='low', x1='time', y1='high', line_width=2, color='black', source=source)
p.segment(x0='time', y0='open', x1='time', y1='close', line_width=8, color='color', source=source)
p2 = Figure(plot_height=250, x_range=p.x_range, tools="xpan,xwheel_zoom,xbox_zoom,reset")
p2.line(x='time', y='macd', color='red', source=source)
p2.line(x='time', y='macd9', color='blue', source=source)
p2.segment(x0='time', y0=0, x1='time', y1='macdh', line_width=6, color='black', alpha=0.5, source=source)
mean = Slider(title="mean", value=0, start=-0.01, end=0.01, step=0.001)
stddev = Slider(title="stddev", value=0.04, start=0.01, end=0.1, step=0.01)
mavg = Select(value=MA12, options=[MA12, MA26, EMA12, EMA26])
curdoc().add_root(VBox(HBox(mean, stddev, mavg, width=800), GridPlot(children=[[p], [p2]])))
def create_random_corr_matrix(n):
BUFSIZE = 200
MA12, MA26, EMA12, EMA26 = '12-tick Moving Avg', '26-tick Moving Avg', '12-tick EMA', '26-tick EMA'
source = ColumnDataSource(dict(
time=[], average=[], low=[], high=[], open=[], close=[],
ma=[], macd=[], macd9=[], macdh=[], color=[]
))
p = Figure(plot_height=600, tools="xpan,xwheel_zoom,xbox_zoom,reset", x_axis_type=None)
p.x_range.follow = "end"
p.x_range.follow_interval = 100
p.x_range.range_padding = 0
p.line(x='time', y='average', alpha=0.2, line_width=3, color='navy', source=source)
p.line(x='time', y='ma', alpha=0.8, line_width=2, color='orange', source=source)
p.segment(x0='time', y0='low', x1='time', y1='high', line_width=2, color='black', source=source)
p.segment(x0='time', y0='open', x1='time', y1='close', line_width=8, color='color', source=source)
p2 = Figure(plot_height=250, x_range=p.x_range, tools="xpan,xwheel_zoom,xbox_zoom,reset")
p2.line(x='time', y='macd', color='red', source=source)
p2.line(x='time', y='macd9', color='blue', source=source)
p2.segment(x0='time', y0=0, x1='time', y1='macdh', line_width=6, color='black', alpha=0.5, source=source)
mean = Slider(title="mean", value=0, start=-0.01, end=0.01, step=0.001)
stddev = Slider(title="stddev", value=0.04, start=0.01, end=0.1, step=0.01)
mavg = Select(value=MA12, options=[MA12, MA26, EMA12, EMA26])
curdoc().add_root(VBox(HBox(mean, stddev, mavg, width=800), GridPlot(children=[[p], [p2]])))
def _create_prices(t):
last_average = 100 if t==0 else source.data['average'][-1]
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)
toolset = "crosshair,pan,reset,resize,save,wheel_zoom"
# Generate a figure container for the field
plot_field = Figure(plot_height=400,
plot_width=400,
tools=toolset,
title="Vector valued function",
x_range=[curveintegral_settings.x_min, curveintegral_settings.x_max],
y_range=[curveintegral_settings.y_min, curveintegral_settings.y_max]
)
# remove grid from plot
plot_field.grid[0].grid_line_alpha = 0.0
plot_field.grid[1].grid_line_alpha = 0.0
# Plot the direction field
plot_field.segment('x0', 'y0', 'x1', 'y1', source=source_segments)
plot_field.patches('xs', 'ys', source=source_patches)
plot_field.circle('x', 'y', source=source_basept, color='blue', size=1.5)
# Plot curve
plot_field.line('x', 'y', source=source_curve, color='black', legend='curve')
# Plot parameter point
plot_field.scatter('x', 'y', source=source_param, color='black', legend='c(t)')
# Plot corresponding tangent vector
plot_field.segment('x0', 'y0', 'x1', 'y1', source=source_param, color='black')
plot_field.patches('xs', 'ys', source=source_param, color='black')
# Generate a figure container for the integral value
plot_integral = Figure(title_text_font_size="12pt",
plot_height=200,
plot_width=400,
title="Integral along curve",
snr_plot.line('lam',
'Fo',
source=theobject,
line_width=2.0,
color="darkgreen",
alpha=0.7)
snr_plot.circle('lam',
'spec',
source=theobject,
fill_color='lightgreen',
line_color='black',
size=8)
snr_plot.segment('lam',
'downerr',
'lam',
'uperr',
source=theobject,
line_width=1,
line_color='grey',
line_alpha=0.5)
#text on plot
glyph = Text(x=0.25,
y=-0.19,
text="label",
text_font_size='9pt',
text_font_style='bold',
text_color='blue')
#attempting to outline the text here for ease of visibility...
glyph2 = Text(x=0.245,
y=-0.19,
text="label",
toolset = "crosshair,pan,reset,resize,save,wheel_zoom"
# Generate a figure container for the field
plot_field = Figure(
plot_height=400,
plot_width=400,
tools=toolset,
title="Vector valued function",
x_range=[curveintegral_settings.x_min, curveintegral_settings.x_max],
y_range=[curveintegral_settings.y_min, curveintegral_settings.y_max])
# remove grid from plot
plot_field.grid[0].grid_line_alpha = 0.0
plot_field.grid[1].grid_line_alpha = 0.0
# Plot the direction field
plot_field.segment('x0', 'y0', 'x1', 'y1', source=source_segments)
plot_field.patches('xs', 'ys', source=source_patches)
plot_field.circle('x', 'y', source=source_basept, color='blue', size=1.5)
# Plot curve
plot_field.line('x', 'y', source=source_curve, color='black', legend='curve')
# Plot parameter point
plot_field.scatter('x', 'y', source=source_param, color='black', legend='c(t)')
# Plot corresponding tangent vector
plot_field.segment('x0', 'y0', 'x1', 'y1', source=source_param, color='black')
plot_field.patches('xs', 'ys', source=source_param, color='black')
# Generate a figure container for the integral value
plot_integral = Figure(title_text_font_size="12pt",
plot_height=200,
plot_width=400,
title="Integral along curve",
# BOKEH PLOTTING
################################
snr_plot = Figure(plot_height=400, plot_width=750,
tools="crosshair,pan,reset,resize,save,box_zoom,wheel_zoom",
x_range=[0.3, 2.7], y_range=[0, 1], toolbar_location='right')
snr_plot.x_range = Range1d(0.3, 2.7, bounds=(0.3, 2.7))
snr_plot.y_range = Range1d(0.0, 1.2, bounds=(0.3, 5.0))
snr_plot.background_fill_color = "beige"
snr_plot.background_fill_alpha = 0.5
snr_plot.yaxis.axis_label='F_p/F_s (x10^9)'
snr_plot.xaxis.axis_label='Wavelength [micron]'
snr_plot.line('lam','cratio',source=planet,line_width=2.0, color="green", alpha=0.7)
snr_plot.circle('lam', 'spec', source=planet, fill_color='red', line_color='black', size=8)
snr_plot.segment('lam', 'downerr', 'lam', 'uperr', source=planet, line_width=1, line_color='grey', line_alpha=0.5)
def change_filename(attrname, old, new):
format_button_group.active = None
instruction0 = Div(text="""Choose a file rootname here
(no special characters):""", width=300, height=15)
text_input = TextInput(value="filename", title=" ", width=100)
instruction1 = Div(text="""Then choose a format here:""", width=300, height=15)
format_button_group = RadioButtonGroup(labels=["txt", "fits"])
instruction2 = Div(text="""Your file will be linked here:""", width=300, height=15)
link_box = Div(text=""" """, width=300, height=15)
def i_clicked_a_button(new):
def run(stock):
# Get stock
quote = get(stock, "quote")
stock_quote = {
"companyName": quote['companyName'],
"latestPrice": quote['latestPrice'],
"symbol": quote['symbol'],
"change": "{0:.2%}".format(quote['changePercent']),
"volume": "{:,}".format(quote['latestVolume']),
"logo": get(stock, 'logo')['url']
}
# Get stock related news
news = get(stock, "news/last/5")
stock_news = []
for article in news:
stock_news.append({
"headline": article['headline'],
"url": article['url']
})
# Get stock related company data
company = get(stock, "company")
company_data = {
"website": company['website'],
"CEO": company['CEO'],
"description": company['description']
}
# Get stock key stats
stats = get(stock, "stats")
key_stats = {
"latestEPS": stats['latestEPS'],
"day5Change": "{0:.2%}".format(stats['day5ChangePercent']),
"month3Change": "{0:.2%}".format(stats['month3ChangePercent']),
"year1Change": "{0:.2%}".format(stats['year1ChangePercent']),
}
# Get chart stats and make bokeh
chart = get(stock, "chart/5y")
chart_cds_df = get(stock, 'chart/1m')
chart = pd.DataFrame(chart)
chart = chart.set_index(pd.to_datetime(chart.date))
chart_cds = ColumnDataSource(chart)
p = Figure(x_axis_label="Date",
y_axis_label="Price",
x_axis_type="datetime",
title="{} - 5Y Graph".format(stock),
sizing_mode='scale_width')
# p.background_fill_color = '#8FBC8F'
# p.background_fill_alpha = 0.2
p.grid.grid_line_alpha = 0.3
p.line(x='date',
y='close',
source=chart_cds,
line_width=1,
color='#F2583E')
hover = HoverTool(mode='vline')
hover.tooltips = [('Date', '@label'), ('Open', '$@open{%0.2f}'),
('High', '$@high{%0.2f}'), ('Low', '$@low{%0.2f}'),
('Close', '$@close{%0.2f}')]
hover.formatters = {
'open': 'printf',
'high': 'printf',
'low': 'printf',
'close': 'printf'
}
p.add_tools(hover)
cdl = Figure(x_axis_label="Date",
y_axis_label="Price",
x_axis_type="datetime",
title="{} - Candlestick".format(stock),
sizing_mode='scale_width')
chart_cds_df = pd.DataFrame(chart_cds_df)
chart_cds_df = chart_cds_df.set_index(pd.to_datetime(chart_cds_df.date))
inc = chart_cds_df.close > chart_cds_df.open
dec = chart_cds_df.open > chart_cds_df.close
w = 12 * 60 * 60 * 1000
cdl.segment(chart_cds_df.index,
chart_cds_df.high,
chart_cds_df.index,
chart_cds_df.low,
color='black')
cdl.vbar(chart_cds_df.index[inc],
w,
chart_cds_df.open[inc],
chart_cds_df.close[inc],
fill_color='#D5E1DD',
line_color='black')
cdl.vbar(chart_cds_df.index[dec],
w,
chart_cds_df.open[dec],
chart_cds_df.close[dec],
fill_color='#F2583E',
line_color='black')
cdl.grid.grid_line_alpha = 0.3
cdl_s, cdl_div = components(cdl)
script, div = components(p)
return {
"stock_quote": stock_quote,
"stock_news": stock_news,
"company_data": company_data,
"key_stats": key_stats,
"chart_script": script,
"chart_div": div,
"s": cdl_s,
"d": cdl_div
}
source=shutter_positions,
size=15,
color='grey',
line_color=None,
fill_alpha=0.1)
cluster_points.selection_glyph = Square(fill_alpha=0.5,
fill_color="green",
line_color='green',
line_width=3)
cluster_points.nonselection_glyph = Square(fill_alpha=0.1,
fill_color="grey",
line_color=None)
cluster_errors = plot2.segment('mass',
'vmax_up_error',
'mass',
'vmax_down_error',
source=shutter_positions,
line_width=2,
line_color='grey',
line_alpha=0.1)
cluster_errors.selection_glyph = Segment(line_alpha=0.5,
line_color='green',
line_width=3)
cluster_errors.nonselection_glyph = Segment(line_alpha=0.1,
line_color='grey',
line_width=1)
# Set up control widgets
aperture = Slider(title="Aperture (meters)",
value=12.,
start=4.,
end=20.0,
