def plot_benchmark_returns(benchmark_data, etf_data, title):
config = helper.generate_config()
index_trace = go.Scatter(
name="Index",
x=benchmark_data.index,
y=benchmark_data,
line={"color": helper.color_scheme["index"]},
)
etf_trace = go.Scatter(
name="ETF",
x=etf_data.index,
y=etf_data,
line={"color": helper.color_scheme["etf"]},
)
layout = go.Layout(
title=title,
xaxis={"title": "Date"},
yaxis={
"title": "Cumulative Returns",
"range": [0, 3]
},
)
fig = go.Figure(data=[index_trace, etf_trace], layout=layout)
offline_py.iplot(fig, config=config)
def plot_stock(prices, title):
config = helper.generate_config()
layout = go.Layout(title=title)
stock_trace = _generate_stock_trace(prices)
offline_py.iplot({"data": [stock_trace], "layout": layout}, config=config)
def plot_price_returns(prices, lookahead_returns_list, title):
config = helper.generate_config()
layout = go.Layout(title=title,
yaxis2={
'title': 'Returns',
'titlefont': {
'color':
helper.color_scheme['y_axis_2_text_color']
},
'tickfont': {
'color':
helper.color_scheme['y_axis_2_text_color']
},
'overlaying': 'y',
'side': 'right'
})
colors = Color(helper.color_scheme['low_value'])\
.range_to(Color(helper.color_scheme['high_value']), len(lookahead_returns_list))
traces = [_generate_stock_trace(prices)]
for (lookahead_returns,
lookahead_days), color in zip(lookahead_returns_list, colors):
traces.append(
go.Scatter(x=lookahead_returns.index,
y=lookahead_returns,
name='{} Day Lookahead'.format(lookahead_days),
line={'color': str(color)},
yaxis='y2'))
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_signal_histograms(signal_list, title, subplot_titles):
assert len(signal_list) == len(subplot_titles)
signal_series_list = [signal.stack() for signal in signal_list]
all_values = pd.concat(signal_series_list)
x_range = [all_values.min(), all_values.max()]
y_range = [0, 1500]
config = helper.generate_config()
colors = Color(helper.color_scheme["low_value"]).range_to(
Color(helper.color_scheme["high_value"]), len(signal_series_list))
fig = py.tools.make_subplots(
rows=1,
cols=len(signal_series_list),
subplot_titles=subplot_titles,
print_grid=False,
)
fig["layout"].update(title=title, showlegend=False)
for series_i, (signal_series,
color) in enumerate(zip(signal_series_list, colors), 1):
filtered_series = signal_series[signal_series != 0].dropna()
trace = go.Histogram(x=filtered_series, marker={"color": str(color)})
fig.append_trace(trace, 1, series_i)
fig["layout"]["xaxis{}".format(series_i)].update(range=x_range)
fig["layout"]["yaxis{}".format(series_i)].update(range=y_range)
offline_py.iplot(fig, config=config)
def plot_signal_returns(prices, signal_return_list, titles):
config = helper.generate_config()
layout = go.Layout(
yaxis2={
'title': 'Signal Returns',
'titlefont': {'color': helper.color_scheme['y_axis_2_text_color']},
'tickfont': {'color': helper.color_scheme['y_axis_2_text_color']},
'overlaying': 'y',
'side': 'right'})
colors = Color(helper.color_scheme['low_value'])\
.range_to(Color(helper.color_scheme['high_value']), len(signal_return_list))
stock_trace = _generate_stock_trace(prices)
for (signal_return, signal, lookahead_days), color, title in zip(signal_return_list, colors, titles):
non_zero_signals = signal_return[signal_return != 0]
signal_return_trace = go.Scatter(
x=non_zero_signals.index,
y=non_zero_signals,
name='{} Day Lookahead'.format(lookahead_days),
line={'color': str(color)},
yaxis='y2')
buy_annotations = _generate_buy_annotations(prices, signal)
sell_annotations = _generate_sell_annotations(prices, signal)
layout['title'] = title
layout['annotations'] = buy_annotations + sell_annotations
offline_py.iplot({'data': [stock_trace, signal_return_trace], 'layout': layout}, config=config)
def print_dataframe(df, n_rows=10, n_columns=3):
missing_val_str = '...'
config = helper.generate_config()
formatted_df = df.iloc[:n_rows, :n_columns]
formatted_df = formatted_df.applymap('{:.3f}'.format)
if len(df.columns) > n_columns:
formatted_df[missing_val_str] = [missing_val_str]*len(formatted_df.index)
if len(df.index) > n_rows:
formatted_df.loc[missing_val_str] = [missing_val_str]*len(formatted_df.columns)
trace = go.Table(
type='table',
columnwidth=[1, 3],
header={
'values': [''] + list(formatted_df.columns.values),
'line': {'color': helper.color_scheme['df_line']},
'fill': {'color': helper.color_scheme['df_header']},
'font': {'size': 13}},
cells={
'values': formatted_df.reset_index().values.T,
'line': {'color': helper.color_scheme['df_line']},
'fill': {'color': [helper.color_scheme['df_header'], helper.color_scheme['df_value']]},
'font': {'size': 13}})
offline_py.iplot([trace], config=config)
def plot_signal_to_normal_histograms(signal_list, title, subplot_titles):
assert len(signal_list) == len(subplot_titles)
signal_series_list = [signal.stack() for signal in signal_list]
all_values = pd.concat(signal_series_list)
x_range = [all_values.min(), all_values.max()]
y_range = [0, 1500]
config = helper.generate_config()
fig = py.tools.make_subplots(rows=1, cols=len(signal_series_list), subplot_titles=subplot_titles, print_grid=False)
fig['layout'].update(title=title)
for series_i, signal_series in enumerate(signal_series_list, 1):
filtered_series = signal_series[signal_series != 0].dropna()
filtered_series_trace = go.Histogram(
x=filtered_series,
marker={'color': helper.color_scheme['low_value']},
name='Signal Return Distribution',
showlegend=False)
normal_trace = go.Histogram(
x=np.random.normal(np.mean(filtered_series), np.std(filtered_series), len(filtered_series)),
marker={'color': helper.color_scheme['shadow']},
name='Normal Distribution',
showlegend=False)
fig.append_trace(filtered_series_trace, 1, series_i)
fig.append_trace(normal_trace, 1, series_i)
fig['layout']['xaxis{}'.format(series_i)].update(range=x_range)
fig['layout']['yaxis{}'.format(series_i)].update(range=y_range)
# Show legened
fig['data'][0]['showlegend'] = True
fig['data'][1]['showlegend'] = True
offline_py.iplot(fig, config=config)
def plot_stock(prices, title):
config = helper.generate_config()
layout = go.Layout(title=title)
stock_trace = _generate_stock_trace(prices)
offline_py.iplot({'data': [stock_trace], 'layout': layout}, config=config)
def print_dataframe(df, n_rows=10, n_columns=3):
missing_val_str = '...'
config = helper.generate_config()
formatted_df = df.iloc[:n_rows, :n_columns]
formatted_df = formatted_df.applymap('{:.3f}'.format)
if len(df.columns) > n_columns:
formatted_df[missing_val_str] = [missing_val_str]*len(formatted_df.index)
if len(df.index) > n_rows:
formatted_df.loc[missing_val_str] = [missing_val_str]*len(formatted_df.columns)
trace = go.Table(
type='table',
columnwidth=[1, 3],
header={
'values': [''] + list(formatted_df.columns.values),
'line': {'color': helper.color_scheme['df_line']},
'fill': {'color': helper.color_scheme['df_header']},
'font': {'size': 13}},
cells={
'values': formatted_df.reset_index().values.T,
'line': {'color': helper.color_scheme['df_line']},
'fill': {'color': [helper.color_scheme['df_header'], helper.color_scheme['df_value']]},
'font': {'size': 13}})
offline_py.iplot([trace], config=config)
def plot_price_returns(prices, lookahead_returns_list, title):
config = helper.generate_config()
layout = go.Layout(
title=title,
yaxis2={
"title": "Returns",
"titlefont": {
"color": helper.color_scheme["y_axis_2_text_color"]
},
"tickfont": {
"color": helper.color_scheme["y_axis_2_text_color"]
},
"overlaying": "y",
"side": "right",
},
)
colors = Color(helper.color_scheme["low_value"]).range_to(
Color(helper.color_scheme["high_value"]), len(lookahead_returns_list))
traces = [_generate_stock_trace(prices)]
for (lookahead_returns,
lookahead_days), color in zip(lookahead_returns_list, colors):
traces.append(
go.Scatter(
x=lookahead_returns.index,
y=lookahead_returns,
name="{} Day Lookahead".format(lookahead_days),
line={"color": str(color)},
yaxis="y2",
))
offline_py.iplot({"data": traces, "layout": layout}, config=config)
def plot_returns(returns, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([('Returns', returns,
helper.color_scheme['major_line'])])
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_returns(returns, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([("Returns", returns,
helper.color_scheme["major_line"])])
offline_py.iplot({"data": traces, "layout": layout}, config=config)
def plot_returns(returns, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
('Returns', returns, helper.color_scheme['major_line'])])
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_resampled_prices(df_resampled, df, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
('Monthly Close', df_resampled, helper.color_scheme['major_line']),
('Close', df, helper.color_scheme['minor_line'])
])
def plot_shifted_returns(df_shited, df, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
('Shifted Returns', df_shited, helper.color_scheme['major_line']),
('Returns', df, helper.color_scheme['minor_line'])
])
def plot_stock(prices, title):
configure_plotly_browser_state()
config = helper.generate_config()
layout = go.Layout(title=title)
stock_trace = _generate_stock_trace(prices)
offline_py.iplot({'data': [stock_trace], 'layout': layout}, config=config)
def plot_shifted_returns(df_shited, df, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
('Shifted Returns', df_shited, helper.color_scheme['major_line']),
('Returns', df, helper.color_scheme['minor_line'])])
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_resampled_prices(df_resampled, df, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
('Monthly Close', df_resampled, helper.color_scheme['major_line']),
('Close', df, helper.color_scheme['minor_line'])])
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_shifted_returns(df_shited, df, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
('Shifted Returns', df_shited, helper.color_scheme['major_line']),
('Returns', df, helper.color_scheme['minor_line'])])
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_xty(xty, title):
config = helper.generate_config()
trace = go.Bar(x=xty.index, y=xty.values)
layout = go.Layout(title=title,
xaxis={'title': 'Tickers'},
yaxis={'title': 'Covariance'})
fig = go.Figure(data=[trace], layout=layout)
offline_py.iplot(fig, config=config)
def plot_shifted_returns(df_shited, df, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
("Shifted Returns", df_shited, helper.color_scheme["major_line"]),
("Returns", df, helper.color_scheme["minor_line"]),
])
offline_py.iplot({"data": traces, "layout": layout}, config=config)
def plot_signal(price, signal, title):
config = helper.generate_config()
buy_annotations = _generate_buy_annotations(price, signal)
sell_annotations = _generate_sell_annotations(price, signal)
layout = go.Layout(title=title,
annotations=buy_annotations + sell_annotations)
stock_trace = _generate_stock_trace(price)
offline_py.iplot({'data': [stock_trace], 'layout': layout}, config=config)
def plot_resampled_prices(df_resampled, df, title):
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
("Monthly Close", df_resampled, helper.color_scheme["major_line"]),
("Close", df, helper.color_scheme["minor_line"]),
])
offline_py.iplot({"data": traces, "layout": layout}, config=config)
def plot_resampled_prices(df_resampled, df, title):
configure_plotly_browser_state()
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
('Monthly Close', df_resampled, helper.color_scheme['major_line']),
('Close', df, helper.color_scheme['minor_line'])])
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_stock(prices, title):
"""
A utility function to plot the stock data.
"""
config = helper.generate_config()
layout = go.Layout(title=title)
stock_trace = _generate_stock_trace(prices)
offline_py.iplot({'data': [stock_trace], 'layout': layout}, config=config)
def plot_signal(price, signal, title):
config = helper.generate_config()
buy_annotations = _generate_buy_annotations(price, signal)
sell_annotations = _generate_sell_annotations(price, signal)
layout = go.Layout(
title=title,
annotations=buy_annotations + sell_annotations)
stock_trace = _generate_stock_trace(price)
offline_py.iplot({'data': [stock_trace], 'layout': layout}, config=config)
def plot_returns(returns, title):
"""
A utility function to plot the stock returns.
"""
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([('Returns', returns,
helper.color_scheme['major_line'])])
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_tracking_error(tracking_error, title):
config = helper.generate_config()
trace = go.Scatter(x=tracking_error.index,
y=tracking_error,
line={'color': helper.color_scheme['tracking_error']})
layout = go.Layout(title=title,
xaxis={'title': 'Date'},
yaxis={'title': 'Error'})
fig = go.Figure(data=[trace], layout=layout)
offline_py.iplot(fig, config=config)
def plot_returns(returns, title):
config = helper.generate_config()
graph_path = 'graphs/{}.html'.format(_sanatize_string(title))
trace = _generate_heatmap_trace(returns.sort_index(axis=1, ascending=False), 'Date', 'Ticker', 'Weight', -0.3, 0.3)
layout = go.Layout(
title=title,
xaxis={'title': 'Dates'},
yaxis={'title': 'Tickers'})
fig = go.Figure(data=[trace], layout=layout)
offline_py.plot(fig, config=config, filename=graph_path, auto_open=False)
display(HTML('The graph for {} is too large. You can view it <a href="{}" target="_blank">here</a>.'
.format(title, graph_path)))
def plot_resampled_prices(df_resampled, df, title):
"""
A utility function to plot the prices after resample.
"""
config = helper.generate_config()
layout = go.Layout(title=title)
traces = _generate_traces([
('Monthly Close', df_resampled, helper.color_scheme['major_line']),
('Close', df, helper.color_scheme['minor_line'])
])
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_lookahead_prices(prices, lookahead_price_list, title):
config = helper.generate_config()
layout = go.Layout(title=title)
colors = Color(helper.color_scheme['low_value'])\
.range_to(Color(helper.color_scheme['high_value']), len(lookahead_price_list))
traces = [_generate_stock_trace(prices)]
for (lookahead_prices, lookahead_days), color in zip(lookahead_price_list, colors):
traces.append(
go.Scatter(
x=lookahead_prices.index,
y=lookahead_prices,
name='{} Day Lookahead'.format(lookahead_days),
line={'color': str(color)}))
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def plot_lookahead_prices(prices, lookahead_price_list, title):
config = helper.generate_config()
layout = go.Layout(title=title)
colors = Color(helper.color_scheme['low_value'])\
.range_to(Color(helper.color_scheme['high_value']), len(lookahead_price_list))
traces = [_generate_stock_trace(prices)]
for (lookahead_prices, lookahead_days), color in zip(lookahead_price_list, colors):
traces.append(
go.Scatter(
x=lookahead_prices.index,
y=lookahead_prices,
name='{} Day Lookahead'.format(lookahead_days),
line={'color': str(color)}))
offline_py.iplot({'data': traces, 'layout': layout}, config=config)
def print_dataframe(df, n_rows=10, n_columns=3):
missing_val_str = "..."
config = helper.generate_config()
formatted_df = df.iloc[:n_rows, :n_columns]
formatted_df = formatted_df.applymap("{:.3f}".format)
if len(df.columns) > n_columns:
formatted_df[missing_val_str] = [missing_val_str] * len(
formatted_df.index)
if len(df.index) > n_rows:
formatted_df.loc[missing_val_str] = [missing_val_str] * len(
formatted_df.columns)
trace = go.Table(
type="table",
columnwidth=[1, 3],
header={
"values": [""] + list(formatted_df.columns.values),
"line": {
"color": helper.color_scheme["df_line"]
},
"fill": {
"color": helper.color_scheme["df_header"]
},
"font": {
"size": 13
},
},
cells={
"values": formatted_df.reset_index().values.T,
"line": {
"color": helper.color_scheme["df_line"]
},
"fill": {
"color": [
helper.color_scheme["df_header"],
helper.color_scheme["df_value"],
]
},
"font": {
"size": 13
},
},
)
offline_py.iplot([trace], config=config)
def plot_high_low(prices, lookback_high, lookback_low, title):
config = helper.generate_config()
layout = go.Layout(title=title)
stock_trace = _generate_stock_trace(prices)
high_trace = go.Scatter(
x=lookback_high.index,
y=lookback_high,
name='Column lookback_high',
line={'color': helper.color_scheme['major_line']})
low_trace = go.Scatter(
x=lookback_low.index,
y=lookback_low,
name='Column lookback_low',
line={'color': helper.color_scheme['minor_line']})
offline_py.iplot({'data': [stock_trace, high_trace, low_trace], 'layout': layout}, config=config)
def plot_high_low(prices, lookback_high, lookback_low, title):
config = helper.generate_config()
layout = go.Layout(title=title)
stock_trace = _generate_stock_trace(prices)
high_trace = go.Scatter(
x=lookback_high.index,
y=lookback_high,
name='Column lookback_high',
line={'color': helper.color_scheme['major_line']})
low_trace = go.Scatter(
x=lookback_low.index,
y=lookback_low,
name='Column lookback_low',
line={'color': helper.color_scheme['minor_line']})
offline_py.iplot({'data': [stock_trace, high_trace, low_trace], 'layout': layout}, config=config)
def plot_lookahead_prices(prices, lookahead_price_list, title):
config = helper.generate_config()
layout = go.Layout(title=title)
colors = Color(helper.color_scheme["low_value"]).range_to(
Color(helper.color_scheme["high_value"]), len(lookahead_price_list))
traces = [_generate_stock_trace(prices)]
for (lookahead_prices,
lookahead_days), color in zip(lookahead_price_list, colors):
traces.append(
go.Scatter(
x=lookahead_prices.index,
y=lookahead_prices,
name="{} Day Lookahead".format(lookahead_days),
line={"color": str(color)},
))
offline_py.iplot({"data": traces, "layout": layout}, config=config)
def plot_signal_to_normal_histograms(signal_list, title, subplot_titles):
assert len(signal_list) == len(subplot_titles)
signal_series_list = [signal.stack() for signal in signal_list]
all_values = pd.concat(signal_series_list)
x_range = [all_values.min(), all_values.max()]
y_range = [0, 1500]
config = helper.generate_config()
fig = py.tools.make_subplots(
rows=1,
cols=len(signal_series_list),
subplot_titles=subplot_titles,
print_grid=False,
)
fig["layout"].update(title=title)
for series_i, signal_series in enumerate(signal_series_list, 1):
filtered_series = signal_series[signal_series != 0].dropna()
filtered_series_trace = go.Histogram(
x=filtered_series,
marker={"color": helper.color_scheme["low_value"]},
name="Signal Return Distribution",
showlegend=False,
)
normal_trace = go.Histogram(
x=np.random.normal(np.mean(filtered_series),
np.std(filtered_series), len(filtered_series)),
marker={"color": helper.color_scheme["shadow"]},
name="Normal Distribution",
showlegend=False,
)
fig.append_trace(filtered_series_trace, 1, series_i)
fig.append_trace(normal_trace, 1, series_i)
fig["layout"]["xaxis{}".format(series_i)].update(range=x_range)
fig["layout"]["yaxis{}".format(series_i)].update(range=y_range)
# Show legened
fig["data"][0]["showlegend"] = True
fig["data"][1]["showlegend"] = True
offline_py.iplot(fig, config=config)
def plot_signal_returns(prices, signal_return_list, titles):
config = helper.generate_config()
layout = go.Layout(
yaxis2={
"title": "Signal Returns",
"titlefont": {
"color": helper.color_scheme["y_axis_2_text_color"]
},
"tickfont": {
"color": helper.color_scheme["y_axis_2_text_color"]
},
"overlaying": "y",
"side": "right",
})
colors = Color(helper.color_scheme["low_value"]).range_to(
Color(helper.color_scheme["high_value"]), len(signal_return_list))
stock_trace = _generate_stock_trace(prices)
for (signal_return, signal,
lookahead_days), color, title in zip(signal_return_list, colors,
titles):
non_zero_signals = signal_return[signal_return != 0]
signal_return_trace = go.Scatter(
x=non_zero_signals.index,
y=non_zero_signals,
name="{} Day Lookahead".format(lookahead_days),
line={"color": str(color)},
yaxis="y2",
)
buy_annotations = _generate_buy_annotations(prices, signal)
sell_annotations = _generate_sell_annotations(prices, signal)
layout["title"] = title
layout["annotations"] = buy_annotations + sell_annotations
offline_py.iplot(
{
"data": [stock_trace, signal_return_trace],
"layout": layout
},
config=config,
)
def plot_benchmark_returns(benchmark_data, etf_data, title):
config = helper.generate_config()
index_trace = go.Scatter(name='Index',
x=benchmark_data.index,
y=benchmark_data,
line={'color': helper.color_scheme['index']})
etf_trace = go.Scatter(name='ETF',
x=etf_data.index,
y=etf_data,
line={'color': helper.color_scheme['etf']})
layout = go.Layout(title=title,
xaxis={'title': 'Date'},
yaxis={
'title': 'Cumulative Returns',
'range': [0, 3]
})
fig = go.Figure(data=[index_trace, etf_trace], layout=layout)
offline_py.iplot(fig, config=config)
def plot_signal_returns(prices, signal_return_list, titles):
configure_plotly_browser_state()
config = helper.generate_config()
layout = go.Layout(
yaxis2={
'title': 'Signal Returns',
'titlefont': {
'color': helper.color_scheme['y_axis_2_text_color']
},
'tickfont': {
'color': helper.color_scheme['y_axis_2_text_color']
},
'overlaying': 'y',
'side': 'right'
})
colors = Color(helper.color_scheme['low_value'])\
.range_to(Color(helper.color_scheme['high_value']), len(signal_return_list))
stock_trace = _generate_stock_trace(prices)
for (signal_return, signal,
lookahead_days), color, title in zip(signal_return_list, colors,
titles):
non_zero_signals = signal_return[signal_return != 0]
signal_return_trace = go.Scatter(
x=non_zero_signals.index,
y=non_zero_signals,
name='{} Day Lookahead'.format(lookahead_days),
line={'color': str(color)},
yaxis='y2')
buy_annotations = _generate_buy_annotations(prices, signal)
sell_annotations = _generate_sell_annotations(prices, signal)
layout['title'] = title
layout['annotations'] = buy_annotations + sell_annotations
offline_py.iplot(
{
'data': [stock_trace, signal_return_trace],
'layout': layout
},
config=config)
def plot_signal_histograms(signal_list, title, subplot_titles):
assert len(signal_list) == len(subplot_titles)
signal_series_list = [signal.stack() for signal in signal_list]
all_values = pd.concat(signal_series_list)
x_range = [all_values.min(), all_values.max()]
y_range = [0, 1500]
config = helper.generate_config()
colors = Color(helper.color_scheme['low_value']).range_to(Color(helper.color_scheme['high_value']), len(signal_series_list))
fig = py.tools.make_subplots(rows=1, cols=len(signal_series_list), subplot_titles=subplot_titles, print_grid=False)
fig['layout'].update(title=title, showlegend=False)
for series_i, (signal_series, color) in enumerate(zip(signal_series_list, colors), 1):
filtered_series = signal_series[signal_series != 0].dropna()
trace = go.Histogram(x=filtered_series, marker={'color': str(color)})
fig.append_trace(trace, 1, series_i)
fig['layout']['xaxis{}'.format(series_i)].update(range=x_range)
fig['layout']['yaxis{}'.format(series_i)].update(range=y_range)
offline_py.iplot(fig, config=config)
def plot_price_returns(prices, lookahead_returns_list, title):
config = helper.generate_config()
layout = go.Layout(
title=title,
yaxis2={
'title': 'Returns',
'titlefont': {'color': helper.color_scheme['y_axis_2_text_color']},
'tickfont': {'color': helper.color_scheme['y_axis_2_text_color']},
'overlaying': 'y',
'side': 'right'})
colors = Color(helper.color_scheme['low_value'])\
.range_to(Color(helper.color_scheme['high_value']), len(lookahead_returns_list))
traces = [_generate_stock_trace(prices)]
for (lookahead_returns, lookahead_days), color in zip(lookahead_returns_list, colors):
traces.append(
go.Scatter(
x=lookahead_returns.index,
y=lookahead_returns,
name='{} Day Lookahead'.format(lookahead_days),
line={'color': str(color)},
yaxis='y2'))
offline_py.iplot({'data': traces, 'layout': layout}, config=config)