def test_js_on_change_executes(self, bokeh_model_page):
group = CheckboxGroup(labels=LABELS, css_classes=["foo"])
group.js_on_click(CustomJS(code=RECORD("active", "cb_obj.active")))
page = bokeh_model_page(group)
el = page.driver.find_element_by_css_selector('.foo input[value="2"]')
el.click()
results = page.results
assert results['active'] == [2]
el = page.driver.find_element_by_css_selector('.foo input[value="0"]')
el.click()
results = page.results
assert results['active'] == [0, 2]
el = page.driver.find_element_by_css_selector('.foo input[value="2"]')
el.click()
results = page.results
assert results['active'] == [0]
assert page.has_no_console_errors()
def test_js_on_change_executes(self,
bokeh_model_page: BokehModelPage) -> None:
group = CheckboxGroup(labels=LABELS)
group.js_on_click(CustomJS(code=RECORD("active", "cb_obj.active")))
page = bokeh_model_page(group)
el = find_element_for(page.driver, group, 'input[value="2"]')
el.click()
results = page.results
assert results['active'] == [2]
el = find_element_for(page.driver, group, 'input[value="0"]')
el.click()
results = page.results
assert results['active'] == [0, 2]
el = find_element_for(page.driver, group, 'input[value="2"]')
el.click()
results = page.results
assert results['active'] == [0]
assert page.has_no_console_errors()
def one_filter(plot, filter_col, filter_vals, filters_state, max_items):
# Remove (FX) from column name; probaby temporary
title = re.sub(r'\s*[(]F[0-9]+[)]\s*', '', filter_col)
# Deduplicate and turn into name-value pairs, as required by MultiSelect.
#options = [(opt,) * 2 for opt in sorted(filter_vals)]
options = list(filter_vals)
multi_select = CheckboxGroup(name=title, labels=options, active=[0, 1])
# The state of each multi-select is stored in an intermediate
# table; when a given multi-select is changed, the table is updated.
# The change to the table triggers a second update, defined below
# in `point_plot`. That second update modifies the map based on
# the state of all multi-selects simultaneously. This way, individual
# multi-select widgets can operate independently without knowing
# anything about one another.
multi_select.js_on_click(
CustomJS(args=dict(filter_col=filter_col, filters_state=filters_state),
code="""
console.log(this.active);
let select_vals = this.active;
let state_col = filters_state.data[filter_col];
for (let i = 0; i < state_col.length; i++) {
if (i < select_vals.length) {
state_col[i] = select_vals[i];
} else {
state_col[i] = '';
}
}
filters_state.properties.data.change.emit();
"""))
return multi_select
def trend_chart(self, target_stock: str):
"""Trend chart of the result using Bokeh."""
result = self.__check_result(target_stock)
tabs = []
for i in result.keys():
label_name = i
tickers = result[i]
cumprod = (self.daily_return[tickers] + 1).cumprod()
source = ColumnDataSource(data=cumprod)
p = figure(x_axis_type="datetime",
title="Trend Line",
plot_height=350,
plot_width=800)
p.xgrid.grid_line_color = None
p.ygrid.grid_line_alpha = 0.5
p.xaxis.axis_label = 'Time'
p.yaxis.axis_label = 'Total Return'
lines = []
for i in range(len(cumprod.columns)):
lines.append(
p.line("Date",
cumprod.columns[i],
source=source,
line_width=2,
line_alpha=0.8,
line_color=Spectral10[i % 10],
legend_label=cumprod.columns[i],
muted_color=Spectral10[i % 10],
muted_alpha=0.1))
p.legend.location = "top_left"
p.legend.click_policy = "mute"
LABELS = list(cumprod.columns)
checkbox_group = CheckboxGroup(labels=LABELS)
checkbox_group.active = list(range(len(LABELS)))
code = """ for (var i = 0; i < lines.length; i++) {
lines[i].visible = false;
if (cb_obj.active.includes(i)){lines[i].visible = true;}
}
"""
callback = CustomJS(code=code, args={'lines': lines})
checkbox_group.js_on_click(callback)
layout = row(p, checkbox_group)
tabs.append(Panel(child=layout, title=label_name))
tabs = Tabs(tabs=tabs)
show(tabs)
def one_filter(plot, filter_col, filter_vals, filters_state, max_items):
# Remove (FX) from column name; probaby temporary
title = re.sub(r'\s*[(]F[0-9]+[)]\s*', '', filter_col)
title = title.replace(" ", "")
options = list(filter_vals)
multi_select = CheckboxGroup(
name=title,
labels=options,
css_classes=[title],
default_size=150,
height_policy='min',
visible=True
)
# The state of each multi-select is stored in an intermediate
# table; when a given multi-select is changed, the table is updated.
# The change to the table triggers a second update, defined below
# in `point_plot`. That second update modifies the map based on
# the state of all multi-selects simultaneously. This way, individual
# multi-select widgets can operate independently without knowing
# anything about one another.
multi_select.js_on_click(CustomJS(
args=dict(filter_col=filter_col,
filters_state=filters_state),
code="""
// Turn the list of active indices into a list of labels.
let select_vals = this.active.map((act) => this.labels[act]);
let state_col = filters_state.data[filter_col];
for (let i = 0; i < state_col.length; i++) {
if (i < select_vals.length) {
state_col[i] = select_vals[i];
} else {
state_col[i] = '';
}
}
filters_state.properties.data.change.emit();
""")
)
return multi_select
def trend_chart(self,
policy_names: list,
compounding: bool = False,
height: int = 350,
width: int = 800):
"""Trend chart of the result using Bokeh.
Parameters
----------
policy_names : list
List of selected policy names
compounding : bool, default False
Whether returns are reinvested back into the account.
height : int
Height of the plot
width : int
Width of the plot
Returns
-------
None
"""
selected_rst_dict = {key: self.rst_dict[key] for key in policy_names}
data = pd.DataFrame(selected_rst_dict)
data["strategy_return"] = self.strategy_return
if compounding:
cum = (data + 1).cumprod()
else:
cum = data.cumsum() + 1
if compounding:
mdd = (cum / cum.cummax() - 1)
else:
mdd = cum - cum.cummax()
source = ColumnDataSource(data=cum)
source_mdd = ColumnDataSource(data=mdd)
p = figure(x_axis_type="datetime",
title="Trend Line",
plot_height=height,
plot_width=width)
p.xgrid.grid_line_color = None
p.ygrid.grid_line_alpha = 0.5
p.xaxis.axis_label = 'Time'
p.yaxis.axis_label = 'Total Return'
p_mdd = figure(x_axis_type="datetime",
title="Max Drawdown",
plot_height=height,
plot_width=width,
x_range=p.x_range)
p_mdd.xgrid.grid_line_color = None
p_mdd.ygrid.grid_line_alpha = 0.5
p_mdd.xaxis.axis_label = 'Time'
p_mdd.yaxis.axis_label = 'MDD'
lines = []
for i in range(len(cum.columns)):
lines.append(
p.line("Date",
cum.columns[i],
source=source,
line_width=2,
line_alpha=0.8,
line_color=Spectral10[i % 10],
legend_label=cum.columns[i],
muted_color=Spectral10[i % 10],
muted_alpha=0.1))
lines_mdd = []
for i in range(len(mdd.columns)):
lines_mdd.append(
p_mdd.line("Date",
mdd.columns[i],
source=source_mdd,
line_width=2,
line_alpha=0.8,
line_color=Spectral10[i % 10],
legend_label=mdd.columns[i],
muted_color=Spectral10[i % 10],
muted_alpha=0.1))
p.legend.location = "top_left"
p.legend.click_policy = "mute"
p_mdd.legend.location = "bottom_left"
p_mdd.legend.click_policy = "mute"
LABELS = list(cum.columns)
checkbox_group = CheckboxGroup(labels=LABELS)
checkbox_group.active = list(range(len(LABELS)))
code = """ for (var i = 0; i < lines.length; i++) {
lines[i].visible = false;
if (cb_obj.active.includes(i)){lines[i].visible = true;}
}
"""
callback = CustomJS(code=code, args={'lines': lines})
checkbox_group.js_on_click(callback)
callback = CustomJS(code=code, args={'lines': lines_mdd})
checkbox_group.js_on_click(callback)
grid = gridplot([[p, checkbox_group], [p_mdd]])
show(grid)
def create_water_tanks_iplot(data_df, logger):
columns = ['L_T' + str(i) for i in range(1, 8)]
max_y = max([data_df[col].max() for col in columns])
source = ColumnDataSource({
'x_t1': data_df.index,
'y_t1': data_df['L_T1'],
'x_t2': data_df.index,
'y_t2': data_df['L_T2'],
'x_t3': data_df.index,
'y_t3': data_df['L_T3'],
'x_t4': data_df.index,
'y_t4': data_df['L_T4'],
'x_t5': data_df.index,
'y_t5': data_df['L_T5'],
'x_t6': data_df.index,
'y_t6': data_df['L_T6'],
'x_t7': data_df.index,
'y_t7': data_df['L_T7'],
})
p = figure(plot_width=1000,
plot_height=750,
title="Water tanks",
tools="pan,wheel_zoom,save,reset",
x_axis_type="datetime",
y_range=[0, max_y + 2.5],
x_axis_label="Time",
y_axis_label="Water level (m)")
p.xaxis.axis_label_text_font_size = "18pt"
p.yaxis.axis_label_text_font_size = "18pt"
p_t1 = p.line('x_t1',
'y_t1',
source=source,
color='red',
alpha=0.9,
line_width=2,
legend="Tank1")
p_t2 = p.line('x_t2',
'y_t2',
source=source,
color='gold',
alpha=0.9,
line_width=2,
legend="Tank2")
p_t3 = p.line('x_t3',
'y_t3',
source=source,
color='blue',
alpha=0.9,
line_width=2,
legend="Tank3")
p_t4 = p.line('x_t4',
'y_t4',
source=source,
color='black',
alpha=0.9,
line_width=2,
legend="Tank4")
p_t5 = p.line('x_t5',
'y_t5',
source=source,
color='mediumspringgreen',
alpha=0.9,
line_width=2,
legend="Tank5")
p_t6 = p.line('x_t6',
'y_t6',
source=source,
color='salmon',
alpha=0.9,
line_width=2,
legend="Tank6")
p_t7 = p.line('x_t7',
'y_t7',
source=source,
color='navy',
alpha=0.9,
line_width=2,
legend="Tank7")
p.legend.location = "top_left"
tanks = ['Tank ' + str(i) for i in range(1, 8)]
checkboxes = CheckboxGroup(labels=tanks, active=[i for i in range(7)])
callback = CustomJS(args=dict(p_t1=p_t1,
p_t2=p_t2,
p_t3=p_t3,
p_t4=p_t4,
p_t5=p_t5,
p_t6=p_t6,
p_t7=p_t7),
code="""
f = cb_obj.active;
p_t1.visible = false;
p_t2.visible = false;
p_t3.visible = false;
p_t4.visible = false;
p_t5.visible = false;
p_t6.visible = false;
p_t7.visible = false;
if (f.includes(0)) { p_t1.visible = true; }
if (f.includes(1)) { p_t2.visible = true; }
if (f.includes(2)) { p_t3.visible = true; }
if (f.includes(3)) { p_t4.visible = true; }
if (f.includes(4)) { p_t5.visible = true; }
if (f.includes(5)) { p_t6.visible = true; }
if (f.includes(6)) { p_t7.visible = true; }
""")
checkboxes.js_on_click(callback)
output_file(logger.get_output_file("tanks.html"))
save(row(checkboxes, p))
def trend_chart(returns_series,
compounding: bool = False,
height: int = 350,
width: int = 800):
"""Trend chart of the result using Bokeh.
Parameters
----------
returns_series : Pandas Series
Series contains returns.
compounding : bool, default False
Whether returns are reinvested back into the account.
height : int
Height of the plot
width : int
Width of the plot
Returns
-------
None
"""
data = returns_series
if compounding:
cum = (data + 1).cumprod()
else:
cum = data.cumsum() + 1
cum = pd.DataFrame(cum)
source = ColumnDataSource(data=cum)
p = figure(x_axis_type="datetime",
title="Trend Line",
plot_height=height,
plot_width=width)
p.xgrid.grid_line_color = None
p.ygrid.grid_line_alpha = 0.5
p.xaxis.axis_label = 'Time'
p.yaxis.axis_label = 'Total Return'
lines = []
for i in range(len(cum.columns)):
lines.append(
p.line("Date",
cum.columns[i],
source=source,
line_width=2,
line_alpha=0.8,
line_color=Spectral10[i % 10],
legend_label=cum.columns[i],
muted_color=Spectral10[i % 10],
muted_alpha=0.1))
p.legend.location = "top_left"
p.legend.click_policy = "mute"
LABELS = list(cum.columns)
checkbox_group = CheckboxGroup(labels=LABELS)
checkbox_group.active = list(range(len(LABELS)))
code = """ for (var i = 0; i < lines.length; i++) {
lines[i].visible = false;
if (cb_obj.active.includes(i)){lines[i].visible = true;}
}
"""
callback = CustomJS(code=code, args={'lines': lines})
checkbox_group.js_on_click(callback)
layout = row(p, checkbox_group)
show(layout)
