def adapt_yranges(y_range, data_min, data_max=None):
dmin = min(nanfilt(data_min), default=None)
dmax = max(nanfilt(data_max if data_max is not None else data_min), default=None)
if dmin is None or dmax is None:
return
diff = ((dmax - dmin) or dmin) * 0.1
dmin -= diff
dmax += diff
if y_range.start is not None:
dmin = min(dmin, y_range.start)
y_range.start = dmin
if y_range.end is not None:
dmax = max(dmax, y_range.end)
y_range.end = dmax
def plot_volume(self, obj, alpha, extra_axis=False):
src_prefix = sanitize_source_name(obj._name)
df = convert_to_pandas(obj, self._start, self._end)
if len(nanfilt(df.volume)) == 0:
return
colorup = convert_color(self._scheme.volup)
colordown = convert_color(self._scheme.voldown)
is_up = df.close > df.open
colors = [colorup if x else colordown for x in is_up]
self._add_to_cds(df.volume, src_prefix + 'volume')
self._add_to_cds(colors, src_prefix + 'volume_colors')
kwargs = {
'fill_alpha': alpha,
'line_alpha': alpha,
'name': 'Volume',
'legend': 'Volume'
}
ax_formatter = NumeralTickFormatter(format='0.000 a')
if extra_axis:
self.figure.extra_y_ranges = {'axvol': DataRange1d()}
adapt_yranges(self.figure.extra_y_ranges['axvol'], df.volume)
self.figure.extra_y_ranges['axvol'].end /= self._scheme.volscaling
ax_color = colorup
ax = LinearAxis(y_range_name="axvol",
formatter=ax_formatter,
axis_label_text_color=ax_color,
axis_line_color=ax_color,
major_label_text_color=ax_color,
major_tick_line_color=ax_color,
minor_tick_line_color=ax_color)
self.figure.add_layout(ax, 'left')
kwargs['y_range_name'] = "axvol"
else:
self.figure.yaxis.formatter = ax_formatter
adapt_yranges(self.figure.y_range, df.volume)
self.figure.y_range.end /= self._scheme.volscaling
self.figure.vbar('datetime',
get_bar_length_ms(obj) * 0.7,
src_prefix + 'volume',
0,
source=self._cds,
fill_color=src_prefix + 'volume_colors',
line_color="black",
**kwargs)
self._hoverc.add_hovertip("Volume", f"@{src_prefix}volume{{(0.00 a)}}")
def plot_volume(self, data: bt.feeds.DataBase, strat_clk: array, alpha, extra_axis=False):
source_id = Figure._source_id(data)
df = convert_to_pandas(strat_clk, data, self._start, self._end)
if len(nanfilt(df.volume)) == 0:
return
colorup = convert_color(self._scheme.volup)
colordown = convert_color(self._scheme.voldown)
is_up = df.close > df.open
colors = [colorup if x else colordown for x in is_up]
self._add_to_cds(df.volume, f'{source_id}volume')
self._add_to_cds(colors, f'{source_id}volume_colors')
kwargs = {'fill_alpha': alpha,
'line_alpha': alpha,
'name': 'Volume',
'legend': 'Volume'}
ax_formatter = NumeralTickFormatter(format=self._scheme.number_format)
if extra_axis:
self.figure.extra_y_ranges = {'axvol': DataRange1d()}
adapt_yranges(self.figure.extra_y_ranges['axvol'], df.volume)
self.figure.extra_y_ranges['axvol'].end /= self._scheme.volscaling
ax_color = colorup
ax = LinearAxis(y_range_name="axvol", formatter=ax_formatter,
axis_label_text_color=ax_color, axis_line_color=ax_color, major_label_text_color=ax_color,
major_tick_line_color=ax_color, minor_tick_line_color=ax_color)
self.figure.add_layout(ax, 'left')
kwargs['y_range_name'] = "axvol"
else:
self.figure.yaxis.formatter = ax_formatter
adapt_yranges(self.figure.y_range, df.volume)
self.figure.y_range.end /= self._scheme.volscaling
self.figure.vbar('index', get_bar_width(), f'{source_id}volume', 0, source=self._cds, fill_color=f'{source_id}volume_colors', line_color="black", **kwargs)
hover_target = None if self._scheme.merge_data_hovers else self.figure
self._hoverc.add_hovertip("Volume", f"@{source_id}volume{{({self._scheme.number_format})}}", hover_target)
def adapt_yranges(y_range, data, padding_factor=200.0):
nnan_data = nanfilt(data)
dmin = min(nnan_data, default=None)
dmax = max(nnan_data, default=None)
if dmin is None or dmax is None:
return
diff = ((dmax - dmin) or dmin) * padding_factor
dmin -= diff
dmax += diff
if y_range.start is not None:
dmin = min(dmin, y_range.start)
y_range.start = dmin
if y_range.end is not None:
dmax = max(dmax, y_range.end)
y_range.end = dmax