def _plot_indicators():
"""Strategy indicators"""
def _too_many_dims(value):
assert value.ndim >= 2
if value.ndim > 2:
warnings.warn(
f"Can't plot indicators with >2D ('{value.name}')",
stacklevel=5)
return True
return False
class LegendStr(str):
# The legend string is such a string that only matches
# itself if it's the exact same object. This ensures
# legend items are listed separately even when they have the
# same string contents. Otherwise, Bokeh would always consider
# equal strings as one and the same legend item.
def __eq__(self, other):
return self is other
ohlc_colors = colorgen()
indicator_figs = []
for i, value in enumerate(indicators):
value = np.atleast_2d(value)
# Use .get()! A user might have assigned a Strategy.data-evolved
# _Array without Strategy.I()
if not value._opts.get('plot') or _too_many_dims(value):
continue
is_overlay = value._opts['overlay']
is_scatter = value._opts['scatter']
if is_overlay:
fig = fig_ohlc
else:
fig = new_indicator_figure()
indicator_figs.append(fig)
tooltips = []
colors = value._opts['color']
colors = colors and cycle(_as_list(colors)) or (cycle(
[next(ohlc_colors)]) if is_overlay else colorgen())
legend_label = LegendStr(value.name)
for j, arr in enumerate(value, 1):
color = next(colors)
source_name = f'{legend_label}_{i}_{j}'
if arr.dtype == bool:
arr = arr.astype(int)
source.add(arr, source_name)
tooltips.append(f'@{{{source_name}}}{{0,0.0[0000]}}')
if is_overlay:
ohlc_extreme_values[source_name] = arr
if is_scatter:
fig.scatter('index',
source_name,
source=source,
legend_label=legend_label,
color=color,
line_color='black',
fill_alpha=.8,
marker='circle',
radius=BAR_WIDTH / 2 * 1.5)
else:
fig.line('index',
source_name,
source=source,
legend_label=legend_label,
line_color=color,
line_width=1.3)
else:
if is_scatter:
r = fig.scatter('index',
source_name,
source=source,
legend_label=LegendStr(legend_label),
color=color,
marker='circle',
radius=BAR_WIDTH / 2 * .9)
else:
r = fig.line('index',
source_name,
source=source,
legend_label=LegendStr(legend_label),
line_color=color,
line_width=1.3)
# Add dashed centerline just because
mean = float(pd.Series(arr).mean())
if not np.isnan(mean) and (
abs(mean) < .1 or round(abs(mean), 1) == .5
or round(abs(mean), -1) in (50, 100, 200)):
fig.add_layout(
Span(location=float(mean),
dimension='width',
line_color='#666666',
line_dash='dashed',
line_width=.5))
if is_overlay:
ohlc_tooltips.append((legend_label, NBSP.join(tooltips)))
else:
set_tooltips(fig, [(legend_label, NBSP.join(tooltips))],
vline=True,
renderers=[r])
# If the sole indicator line on this figure,
# have the legend only contain text without the glyph
if len(value) == 1:
fig.legend.glyph_width = 0
return indicator_figs
def _plot_indicators():
"""Strategy indicators"""
def _too_many_dims(value):
assert value.ndim >= 2
if value.ndim > 2:
warnings.warn("Can't plot indicators with >2D ('{}')".format(
value.name),
stacklevel=5)
return True
return False
class LegendStr(str):
# The legend string is such a string that only matches
# itself if it's the exact same object. This ensures
# legend items are listed separately even when they have the
# same string contents. Otherwise, Bokeh would always consider
# equal strings as one and the same legend item.
# This also prevents legend items named the same as some
# ColumnDataSource's column to be replaced with that column's
# values.
def __eq__(self, other):
return self is other
ohlc_colors = colorgen()
for value in indicators:
value = np.atleast_2d(value)
# Use .get()! A user might have assigned a Strategy.data-evolved
# _Array without Strategy.I()
if not value._opts.get('plot') or _too_many_dims(value):
continue
tooltips = []
# Overlay indicators on the OHLC figure
if value._opts['overlay']:
color = value._opts['color']
color = color and _as_list(color)[0] or next(ohlc_colors)
legend = LegendStr(value.name)
for i, arr in enumerate(value):
source_name = '{}_{}'.format(value.name, i)
source.add(arr, source_name)
if value._opts.get('scatter'):
fig_ohlc.scatter('index',
source_name,
source=source,
color=color,
line_color='black',
fill_alpha=.8,
marker='circle',
radius=bar_width / 2 * 1.5,
legend=legend)
else:
fig_ohlc.line('index',
source_name,
source=source,
line_width=1.3,
line_color=color,
legend=legend)
ohlc_extreme_values[source_name] = arr
tooltips.append(
'@{{{}}}{{0,0.0[0000]}}'.format(source_name))
ohlc_tooltips.append((value.name, NBSP.join(tooltips)))
else:
# Standalone indicator sections at the bottom
color = value._opts['color']
color = color and cycle(_as_list(color)) or colorgen()
fig = new_indicator_figure()
for i, arr in enumerate(value, 1):
legend = '{}-{}'.format(
value.name, i) if len(value) > 1 else value.name
name = legend + '_' # Otherwise fig.line(legend=) is interpreted as col of source # noqa: E501
tooltips.append('@{{{}}}'.format(name))
source.add(arr.astype(int if arr.dtype == bool else float),
name)
if value._opts.get('scatter'):
r = fig.scatter('index',
name,
source=source,
color=next(color),
marker='circle',
radius=bar_width / 2 * .9,
legend=LegendStr(legend))
else:
r = fig.line('index',
name,
source=source,
line_color=next(color),
line_width=1.3,
legend=LegendStr(legend))
# Add dashed centerline just because
mean = float(pd.Series(arr).mean())
if not np.isnan(mean) and (abs(mean) < .1 or round(
abs(mean), -1) in (50, 100, 200)):
fig.add_layout(
Span(location=float(mean),
dimension='width',
line_color='#666666',
line_dash='dashed',
line_width=.5))
set_tooltips(fig, [(value.name, NBSP.join(tooltips))],
vline=True,
renderers=[r])
# If the sole indicator line on this figure,
# have the legend only contain text without the glyph
if len(value) == 1:
fig.legend.glyph_width = 0
figs_below_ohlc.append(fig)
