def make_correlation_datatable(correl_df):
"""
the input datframe must have columns ['Target (as string)', 'Hedge (as string)', 'Correlation ( as float )']
:param correl_df:
:return:
"""
correl_df.reset_index(inplace=True)
source = ColumnDataSource(correl_df)
target_ts_asset = sorted(correl_df["Target"].unique())
hedge_ts_asset = sorted(correl_df["Hedge"].unique())
columns = [
TableColumn(field="Target",
title="Target Timeseries",
formatter=StringFormatter(font_style="bold",
text_color='red')),
TableColumn(field="Hedge",
title="Hedge Timeseries",
formatter=StringFormatter(font_style="bold",
text_color='blue')),
TableColumn(field="Correlation",
title="Correlation",
formatter=StringFormatter(font_style="bold",
text_color='darkgreen'))
]
data_table = DataTable(source=source,
columns=columns,
editable=False,
width=1000)
plot = Plot(title=Title(
text="Correlations, Target vs. Hedge Timeseries)", align="center"),
x_range=DataRange1d(),
y_range=DataRange1d(),
plot_width=1000,
plot_height=300)
# Set up x & y axis
plot.add_layout(LinearAxis(), 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
# Add Glyphs
correlation_glyph = Circle(x="index",
y="Correlation",
fill_color="#396285",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
target_glyph = Circle(x="index",
y="Target",
fill_color="#396285",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
hedge_glyph = Circle(x="index",
y="Hedge",
fill_color="#396285",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
correlation = plot.add_glyph(source, correlation_glyph)
target = plot.add_glyph(source, target_glyph)
hedge = plot.add_glyph(source, hedge_glyph)
# Add the tools
tooltips = [("Correlation", "@Correlation"), ("Target", "@Target"),
("Hedge", "@Hedge")]
correlation_hover_tool = HoverTool(renderers=[correlation],
tooltips=tooltips)
target_hover_tool = HoverTool(renderers=[target], tooltips=tooltips)
hedge_hover_tool = HoverTool(renderers=[hedge], tooltips=tooltips)
select_tool = BoxSelectTool(renderers=[target, hedge, correlation],
dimensions='width')
plot.add_tools(target_hover_tool, hedge_hover_tool,
correlation_hover_tool, select_tool)
layout = Column(plot, data_table)
the_doc = Document()
the_doc.add_root(layout)
return the_doc
from bokeh.document import Document
from bokeh.models import (ColumnDataSource, DataRange1d, Plot, Circle,
WidgetBox, Row, Button, TapTool)
document = Document()
session = push_session(document)
N = 9
x = np.linspace(-2, 2, N)
y = x**2
source1 = ColumnDataSource(dict(x=x, y=y, size=[20] * N))
xdr1 = DataRange1d()
ydr1 = DataRange1d()
plot1 = Plot(x_range=xdr1, y_range=ydr1, plot_width=400, plot_height=400)
plot1.title.text = "Plot1"
plot1.tools.append(TapTool(plot=plot1))
plot1.add_glyph(source1, Circle(x="x", y="y", size="size", fill_color="red"))
source2 = ColumnDataSource(dict(x=x, y=y, color=["blue"] * N))
xdr2 = DataRange1d()
ydr2 = DataRange1d()
plot2 = Plot(x_range=xdr2, y_range=ydr2, plot_width=400, plot_height=400)
plot2.title.text = "Plot2"
plot2.tools.append(TapTool(plot=plot2))
plot2.add_glyph(source2, Circle(x="x", y="y", size=20, fill_color="color"))
def on_selection_change1(attr, _, inds):
color = ["blue"] * N
def create(palm):
fit_max = 1
fit_min = 0
doc = curdoc()
# THz calibration plot
scan_plot = Plot(
title=Title(text="THz calibration"),
x_range=DataRange1d(),
y_range=DataRange1d(),
plot_height=PLOT_CANVAS_HEIGHT,
plot_width=PLOT_CANVAS_WIDTH,
toolbar_location="right",
)
# ---- tools
scan_plot.toolbar.logo = None
scan_plot.add_tools(PanTool(), BoxZoomTool(), WheelZoomTool(), ResetTool())
# ---- axes
scan_plot.add_layout(LinearAxis(axis_label="Stage delay motor"),
place="below")
scan_plot.add_layout(LinearAxis(axis_label="Energy shift, eV",
major_label_orientation="vertical"),
place="left")
# ---- grid lines
scan_plot.add_layout(Grid(dimension=0, ticker=BasicTicker()))
scan_plot.add_layout(Grid(dimension=1, ticker=BasicTicker()))
# ---- circle cluster glyphs
scan_circle_source = ColumnDataSource(dict(x=[], y=[]))
scan_plot.add_glyph(scan_circle_source,
Circle(x="x", y="y", line_alpha=0, fill_alpha=0.5))
# ---- circle glyphs
scan_avg_circle_source = ColumnDataSource(dict(x=[], y=[]))
scan_plot.add_glyph(
scan_avg_circle_source,
Circle(x="x", y="y", line_color="purple", fill_color="purple"))
# ---- line glyphs
fit_line_source = ColumnDataSource(dict(x=[], y=[]))
scan_plot.add_glyph(fit_line_source, Line(x="x",
y="y",
line_color="purple"))
# THz calibration folder path text input
def path_textinput_callback(_attr, _old_value, _new_value):
update_load_dropdown_menu()
path_periodic_update()
path_textinput = TextInput(title="THz calibration path:",
value=os.path.join(os.path.expanduser("~")),
width=510)
path_textinput.on_change("value", path_textinput_callback)
# THz calibration eco scans dropdown
def scans_dropdown_callback(_attr, _old_value, new_value):
scans_dropdown.label = new_value
scans_dropdown = Dropdown(label="ECO scans",
button_type="default",
menu=[])
scans_dropdown.on_change("value", scans_dropdown_callback)
# ---- eco scans periodic update
def path_periodic_update():
new_menu = []
if os.path.isdir(path_textinput.value):
for entry in os.scandir(path_textinput.value):
if entry.is_file() and entry.name.endswith(".json"):
new_menu.append((entry.name, entry.name))
scans_dropdown.menu = sorted(new_menu, reverse=True)
doc.add_periodic_callback(path_periodic_update, 5000)
# Calibrate button
def calibrate_button_callback():
palm.calibrate_thz(
path=os.path.join(path_textinput.value, scans_dropdown.value))
fit_max_spinner.value = np.ceil(palm.thz_calib_data.index.values.max())
fit_min_spinner.value = np.floor(
palm.thz_calib_data.index.values.min())
update_calibration_plot()
def update_calibration_plot():
scan_plot.xaxis.axis_label = f"{palm.thz_motor_name}, {palm.thz_motor_unit}"
scan_circle_source.data.update(
x=np.repeat(palm.thz_calib_data.index,
palm.thz_calib_data["peak_shift"].apply(len)).tolist(),
y=np.concatenate(
palm.thz_calib_data["peak_shift"].values).tolist(),
)
scan_avg_circle_source.data.update(
x=palm.thz_calib_data.index.tolist(),
y=palm.thz_calib_data["peak_shift_mean"].tolist())
x = np.linspace(fit_min, fit_max, 100)
y = palm.thz_slope * x + palm.thz_intersect
fit_line_source.data.update(x=np.round(x, decimals=5),
y=np.round(y, decimals=5))
calib_const_div.text = f"""
thz_slope = {palm.thz_slope}
"""
calibrate_button = Button(label="Calibrate THz",
button_type="default",
width=250)
calibrate_button.on_click(calibrate_button_callback)
# THz fit maximal value text input
def fit_max_spinner_callback(_attr, old_value, new_value):
nonlocal fit_max
if new_value > fit_min:
fit_max = new_value
palm.calibrate_thz(
path=os.path.join(path_textinput.value, scans_dropdown.value),
fit_range=(fit_min, fit_max),
)
update_calibration_plot()
else:
fit_max_spinner.value = old_value
fit_max_spinner = Spinner(title="Maximal fit value:",
value=fit_max,
step=0.1)
fit_max_spinner.on_change("value", fit_max_spinner_callback)
# THz fit maximal value text input
def fit_min_spinner_callback(_attr, old_value, new_value):
nonlocal fit_min
if new_value < fit_max:
fit_min = new_value
palm.calibrate_thz(
path=os.path.join(path_textinput.value, scans_dropdown.value),
fit_range=(fit_min, fit_max),
)
update_calibration_plot()
else:
fit_min_spinner.value = old_value
fit_min_spinner = Spinner(title="Minimal fit value:",
value=fit_min,
step=0.1)
fit_min_spinner.on_change("value", fit_min_spinner_callback)
# Save calibration button
def save_button_callback():
palm.save_thz_calib(path=path_textinput.value)
update_load_dropdown_menu()
save_button = Button(label="Save", button_type="default", width=250)
save_button.on_click(save_button_callback)
# Load calibration button
def load_dropdown_callback(_attr, _old_value, new_value):
palm.load_thz_calib(os.path.join(path_textinput.value, new_value))
update_calibration_plot()
def update_load_dropdown_menu():
new_menu = []
calib_file_ext = ".palm_thz"
if os.path.isdir(path_textinput.value):
for entry in os.scandir(path_textinput.value):
if entry.is_file() and entry.name.endswith((calib_file_ext)):
new_menu.append(
(entry.name[:-len(calib_file_ext)], entry.name))
load_dropdown.button_type = "default"
load_dropdown.menu = sorted(new_menu, reverse=True)
else:
load_dropdown.button_type = "danger"
load_dropdown.menu = new_menu
doc.add_next_tick_callback(update_load_dropdown_menu)
doc.add_periodic_callback(update_load_dropdown_menu, 5000)
load_dropdown = Dropdown(label="Load", menu=[], width=250)
load_dropdown.on_change("value", load_dropdown_callback)
# Calibration constants
calib_const_div = Div(text=f"""
thz_slope = {0}
""")
# assemble
tab_layout = column(
row(
scan_plot,
Spacer(width=30),
column(
path_textinput,
scans_dropdown,
calibrate_button,
fit_max_spinner,
fit_min_spinner,
row(save_button, load_dropdown),
calib_const_div,
),
))
return Panel(child=tab_layout, title="THz Calibration")
def test_lodend_constructor_plot():
model = Plot()
event = events.LODEnd(model)
assert event._model_id == model.id
PanTool, WheelZoomTool)
from bokeh.resources import INLINE
x = arange(-2 * pi, 2 * pi, 0.1)
y = sin(x)
# Create an array of times, starting at the current time, and extending
# for len(x) number of hours.
times = np.arange(len(x)) * 3600000 + time.time()
source = ColumnDataSource(data=dict(x=x, y=y, times=times))
xdr = DataRange1d()
ydr = DataRange1d()
plot = Plot(x_range=xdr, y_range=ydr, min_border=80)
circle = Circle(x="times", y="y", fill_color="red", size=5, line_color="black")
plot.add_glyph(source, circle)
plot.add_layout(DatetimeAxis(), 'below')
plot.add_layout(DatetimeAxis(), 'left')
plot.add_tools(PanTool(), WheelZoomTool())
doc = Document()
doc.add(plot)
if __name__ == "__main__":
filename = "dateaxis.html"
with open(filename, "w") as f:
def __init__(self, **kwargs):
names = [
'processes', 'disk-read', 'cores', 'cpu', 'disk-write', 'memory',
'last-seen', 'memory_percent', 'host'
]
self.source = ColumnDataSource({k: [] for k in names})
columns = {
name: TableColumn(field=name, title=name.replace('_percent', ' %'))
for name in names
}
cnames = [
'host', 'cores', 'processes', 'memory', 'cpu', 'memory_percent'
]
formatters = {
'cpu': NumberFormatter(format='0.0 %'),
'memory_percent': NumberFormatter(format='0.0 %'),
'memory': NumberFormatter(format='0 b'),
'latency': NumberFormatter(format='0.00000'),
'last-seen': NumberFormatter(format='0.000'),
'disk-read': NumberFormatter(format='0 b'),
'disk-write': NumberFormatter(format='0 b'),
'net-send': NumberFormatter(format='0 b'),
'net-recv': NumberFormatter(format='0 b')
}
table = DataTable(
source=self.source,
columns=[columns[n] for n in cnames],
)
for name in cnames:
if name in formatters:
table.columns[cnames.index(name)].formatter = formatters[name]
mem_plot = Plot(title=Title(text="Memory Usage (%)"),
toolbar_location=None,
x_range=Range1d(start=0, end=1),
y_range=Range1d(start=-0.1, end=0.1),
**kwargs)
mem_plot.add_glyph(
self.source,
Circle(x='memory_percent', y=0, size=10, fill_alpha=0.5))
mem_plot.add_layout(LinearAxis(), 'below')
hover = HoverTool(point_policy="follow_mouse",
tooltips="""
<div>
<span style="font-size: 10px; font-family: Monaco, monospace;">@host: </span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory_percent</span>
</div>
""")
mem_plot.add_tools(hover, BoxSelectTool())
if 'sizing_mode' in kwargs:
sizing_mode = {'sizing_mode': kwargs['sizing_mode']}
else:
sizing_mode = {}
self.root = column(mem_plot,
table,
id='bk-worker-table',
**sizing_mode)
def test_buttonclick_constructor_plot():
with pytest.raises(ValueError):
events.ButtonClick(Plot())
def test_server_callback_resolve_attr_spec_tap_event(self):
plot = Plot()
event = Tap(plot, x=42)
msg = Callback.resolve_attr_spec('cb_obj.x', event, plot)
self.assertEqual(msg, {'id': plot.ref['id'], 'value': 42})
def test_setting_logo_on_plot_declaration_sets_them_on_toolbar():
plot = Plot(logo='grey')
assert plot.toolbar.logo == 'grey', "Remove this test when deprecation cycle is over"
plot.title = "%s vs. taylor(%s, n=%d)" % (expr, expr, order)
legend.legends = [
("%s" % expr, [line_f_glyph]),
("taylor(%s)" % expr, [line_t_glyph]),
]
source.data = dict(x=x, fy=fy, ty=ty)
slider.value = order
source = ColumnDataSource(data=dict(x=[], fy=[], ty=[]))
xdr = Range1d(-7, 7)
ydr = Range1d(-20, 200)
plot = Plot(x_range=xdr, y_range=ydr, plot_width=800, plot_height=400)
line_f = Line(x="x", y="fy", line_color="blue", line_width=2)
line_f_glyph = plot.add_glyph(source, line_f)
plot.add_layout(line_f_glyph)
line_t = Line(x="x", y="ty", line_color="red", line_width=2)
line_t_glyph = plot.add_glyph(source, line_t)
plot.add_layout(line_t_glyph)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
d3 = summer_end + (calendar_end - summer_end) / 2
text_source = ColumnDataSource(
dict(
dates=[d1, d2, d3],
times=[dt.time(11, 30)] * 3,
texts=["CST (UTC+1)", "CEST (UTC+2)", "CST (UTC+1)"],
))
xdr = DataRange1d()
ydr = DataRange1d()
title = "Daylight Hours - Warsaw, Poland"
plot = Plot(title=title,
x_range=xdr,
y_range=ydr,
plot_width=800,
plot_height=400)
patch1 = Patch(x="dates", y="times", fill_color="skyblue", fill_alpha=0.8)
plot.add_glyph(patch1_source, patch1)
patch2 = Patch(x="dates", y="times", fill_color="orange", fill_alpha=0.8)
plot.add_glyph(patch2_source, patch2)
line1 = Line(x="dates", y="sunrises", line_color="yellow", line_width=2)
line1_glyph = plot.add_glyph(source, line1)
line2 = Line(x="dates", y="sunsets", line_color="red", line_width=2)
line2_glyph = plot.add_glyph(source, line2)
from bokeh.browserlib import view
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.models.glyphs import Circle
from bokeh.models import (Plot, LinearAxis, ColumnDataSource, Range1d, PanTool,
WheelZoomTool)
from bokeh.resources import INLINE
x = arange(-2 * pi, 2 * pi, 0.1)
y = sin(x)
y2 = linspace(0, 100, len(y))
source = ColumnDataSource(data=dict(x=x, y=y, y2=y2))
plot = Plot(x_range=Range1d(start=-6.5, end=6.5),
y_range=Range1d(start=-1.1, end=1.1),
min_border=80)
plot.extra_y_ranges = {"foo": Range1d(start=0, end=100)}
circle = Circle(x="x", y="y", fill_color="red", size=5, line_color="black")
plot.add_glyph(source, circle)
plot.add_layout(LinearAxis(), 'below')
plot.add_layout(LinearAxis(), 'left')
circle2 = Circle(x="x", y="y2", fill_color="blue", size=5, line_color="black")
plot.add_glyph(source, circle2, y_range_name="foo")
plot.add_layout(LinearAxis(y_range_name="foo"), 'left')
nx.draw(G, with_labels=True,
node_size=nodeSize2,
node_color='#EFC9AF',
node_shape='h', #node_shape="d,h,o,p,s,v,x,"
alpha=0.7, #node transparancy rate out of '1'
linewidths=4,
font_size=10,
font_color='#104C91',
font_weight='bold',
width=1,
edge_color='#1F8AC0'
)
# -------------------- Setting a Plot option part --------------------
plot = Plot(plot_width=1000, plot_height=750,
x_range=Range1d(-1.2, 1.2), y_range=Range1d(-1.2, 1.2))
plot.title.text = "My Positive Words Graph (hold 'shift' key for multi-clicking)"
plot.add_tools(HoverTool(tooltips=None), TapTool(), BoxSelectTool())
# -------------------- Edge adding in Graph part --------------------
popular = dict()
G = nx.DiGraph()
for line in posWordsList:
words = line.split()
# adding edge
G.add_edge(words[0], words[1])
G.add_edge(words[1], words[2])
# word-frequency
for word in words:
def make_example_datatable():
source = ColumnDataSource(mpg)
print(source.column_names)
manufacturers = sorted(mpg["manufacturer"].unique())
models = sorted(mpg["model"].unique())
transmissions = sorted(mpg["trans"].unique())
drives = sorted(mpg["drv"].unique())
classes = sorted(mpg["class"].unique())
columns = [
TableColumn(field="manufacturer",
title="Manufacturer",
editor=SelectEditor(options=manufacturers),
formatter=StringFormatter(font_style="bold")),
TableColumn(field="model",
title="Model",
editor=StringEditor(completions=models)),
TableColumn(field="displ",
title="Displacement",
editor=NumberEditor(step=0.1),
formatter=NumberFormatter(format="0.0")),
TableColumn(field="year", title="Year", editor=IntEditor()),
TableColumn(field="cyl", title="Cylinders", editor=IntEditor()),
TableColumn(field="trans",
title="Transmission",
editor=SelectEditor(options=transmissions)),
TableColumn(field="drv",
title="Drive",
editor=SelectEditor(options=drives)),
TableColumn(field="class",
title="Class",
editor=SelectEditor(options=classes)),
TableColumn(field="cty", title="City MPG", editor=IntEditor()),
TableColumn(field="hwy", title="Highway MPG", editor=IntEditor()),
]
data_table = DataTable(source=source,
columns=columns,
editable=True,
width=1000)
plot = Plot(title=None,
x_range=DataRange1d(),
y_range=DataRange1d(),
plot_width=1000,
plot_height=300)
# Set up x & y axis
plot.add_layout(LinearAxis(), 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
# Add Glyphs
cty_glyph = Circle(x="index",
y="cty",
fill_color="#396285",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
hwy_glyph = Circle(x="index",
y="hwy",
fill_color="#CE603D",
size=8,
fill_alpha=0.5,
line_alpha=0.5)
cty = plot.add_glyph(source, cty_glyph)
hwy = plot.add_glyph(source, hwy_glyph)
# Add the tools
tooltips = [
("Manufacturer", "@manufacturer"),
("Model", "@model"),
("Displacement", "@displ"),
("Year", "@year"),
("Cylinders", "@cyl"),
("Transmission", "@trans"),
("Drive", "@drv"),
("Class", "@class"),
]
cty_hover_tool = HoverTool(renderers=[cty],
tooltips=tooltips + [("City MPG", "@cty")])
hwy_hover_tool = HoverTool(renderers=[hwy],
tooltips=tooltips +
[("Highway MPG", "@hwy")])
select_tool = BoxSelectTool(renderers=[cty, hwy], dimensions='width')
plot.add_tools(cty_hover_tool, hwy_hover_tool, select_tool)
layout = Column(plot, data_table)
doc = Document()
doc.add_root(layout)
return doc
def __init__(self, **kwargs):
data = progress_quads(dict(all={}, memory={}, erred={}, released={}))
self.source = ColumnDataSource(data=data)
x_range = DataRange1d()
y_range = Range1d(-8, 0)
self.root = Plot(id='bk-task-progress-plot',
x_range=x_range,
y_range=y_range,
toolbar_location=None,
**kwargs)
self.root.add_glyph(
self.source,
Quad(top='top',
bottom='bottom',
left='left',
right='right',
fill_color="#aaaaaa",
line_color="#aaaaaa",
fill_alpha=0.2))
self.root.add_glyph(
self.source,
Quad(top='top',
bottom='bottom',
left='left',
right='released-loc',
fill_color="color",
line_color="color",
fill_alpha=0.6))
self.root.add_glyph(
self.source,
Quad(top='top',
bottom='bottom',
left='released-loc',
right='memory-loc',
fill_color="color",
line_color="color",
fill_alpha=1.0))
self.root.add_glyph(
self.source,
Quad(top='top',
bottom='bottom',
left='erred-loc',
right='erred-loc',
fill_color='#000000',
line_color='#000000',
fill_alpha=0.3))
self.root.add_glyph(
self.source,
Text(text='show-name',
y='bottom',
x='left',
x_offset=5,
text_font_size=value('10pt')))
self.root.add_glyph(
self.source,
Text(text='done',
y='bottom',
x='right',
x_offset=-5,
text_align='right',
text_font_size=value('10pt')))
hover = HoverTool(point_policy="follow_mouse",
tooltips="""
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">All:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@all</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Memory:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Erred:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@erred</span>
</div>
""")
self.root.add_tools(hover)
def test_setting_tools_on_plot_declaration_sets_them_on_toolbar():
pan = PanTool()
plot = Plot(tools=[pan])
assert plot.toolbar.tools == [
pan
], "Remove this test when deprecation cycle is over"
def __init__(self, **kwargs):
self.source = ColumnDataSource(
data={
'time': [],
'cpu': [],
'memory_percent': [],
'network-send': [],
'network-recv': []
})
x_range = DataRange1d(follow='end',
follow_interval=30000,
range_padding=0)
resource_plot = Plot(x_range=x_range,
y_range=Range1d(start=0, end=1),
toolbar_location=None,
min_border_bottom=10,
**kwargs)
line_opts = dict(line_width=2, line_alpha=0.8)
g1 = resource_plot.add_glyph(
self.source,
Line(x='time',
y='memory_percent',
line_color="#33a02c",
**line_opts))
g2 = resource_plot.add_glyph(
self.source,
Line(x='time', y='cpu', line_color="#1f78b4", **line_opts))
resource_plot.add_layout(
LinearAxis(formatter=NumeralTickFormatter(format="0 %")), 'left')
legend_opts = dict(location='top_left',
orientation='horizontal',
padding=5,
margin=5,
label_height=5)
resource_plot.add_layout(
Legend(items=[('Memory', [g1]), ('CPU', [g2])], **legend_opts))
network_plot = Plot(x_range=x_range,
y_range=DataRange1d(start=0),
toolbar_location=None,
**kwargs)
g1 = network_plot.add_glyph(
self.source,
Line(x='time', y='network-send', line_color="#a6cee3",
**line_opts))
g2 = network_plot.add_glyph(
self.source,
Line(x='time', y='network-recv', line_color="#b2df8a",
**line_opts))
network_plot.add_layout(DatetimeAxis(axis_label="Time"), "below")
network_plot.add_layout(LinearAxis(axis_label="MB/s"), 'left')
network_plot.add_layout(
Legend(items=[('Network Send', [g1]), ('Network Recv', [g2])],
**legend_opts))
tools = [
PanTool(dimensions='width'),
WheelZoomTool(dimensions='width'),
BoxZoomTool(),
ResetTool()
]
if 'sizing_mode' in kwargs:
sizing_mode = {'sizing_mode': kwargs['sizing_mode']}
else:
sizing_mode = {}
combo_toolbar = ToolbarBox(tools=tools,
logo=None,
toolbar_location='right',
**sizing_mode)
self.root = row(column(resource_plot, network_plot, **sizing_mode),
column(combo_toolbar, **sizing_mode),
id='bk-resource-profiles-plot',
**sizing_mode)
# Required for update callback
self.resource_index = [0]
def test_plot_raises_error_if_toolbar_and_logo_are_set():
with pytest.raises(ValueError):
Plot(logo='grey', toolbar=Toolbar())
def __init__(self, n_rectangles=1000, clear_interval=20000, **kwargs):
"""
kwargs are applied to the bokeh.models.plots.Plot constructor
"""
self.n_rectangles = n_rectangles
self.clear_interval = clear_interval
self.last = 0
self.source = ColumnDataSource(data=dict(start=[],
duration=[],
key=[],
name=[],
color=[],
worker=[],
y=[],
worker_thread=[],
alpha=[]))
x_range = DataRange1d()
y_range = DataRange1d(range_padding=0)
self.root = Plot(title=Title(text="Task Stream"),
id='bk-task-stream-plot',
x_range=x_range,
y_range=y_range,
toolbar_location="above",
min_border_right=35,
**kwargs)
self.root.add_glyph(
self.source,
Rect(x="start",
y="y",
width="duration",
height=0.8,
fill_color="color",
line_color="color",
line_alpha=0.6,
fill_alpha="alpha",
line_width=3))
self.root.add_layout(DatetimeAxis(axis_label="Time"), "below")
ticker = BasicTicker(num_minor_ticks=0)
self.root.add_layout(
LinearAxis(axis_label="Worker Core", ticker=ticker), "left")
self.root.add_layout(
Grid(dimension=1, grid_line_alpha=0.4, ticker=ticker))
hover = HoverTool(point_policy="follow_mouse",
tooltips="""
<div>
<span style="font-size: 12px; font-weight: bold;">@name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@duration</span>
<span style="font-size: 10px;">ms</span>
</div>
""")
# export = ExportTool()
# export.register_plot(self.root)
self.root.add_tools(
hover,
# export,
BoxZoomTool(),
ResetTool(reset_size=False),
PanTool(dimensions="width"),
WheelZoomTool(dimensions="width"))
# Required for update callback
self.task_stream_index = [0]
def test_plot_raises_error_if_toolbar_and_tools_are_set():
with pytest.raises(ValueError):
Plot(tools=[PanTool()], toolbar=Toolbar())
def test_lodstart_constructor_plot():
model = Plot()
event = events.LODStart(model)
assert event._model_id == model.id
def test_plot_with_no_title_specified_creates_an_empty_title():
plot = Plot()
assert plot.title.text == ""
def test_event_constructor_plot():
model = Plot()
event = events.Event(model)
assert event._model_id == model.id
def verify_axis(self, axis_name):
plot = Plot() # no need for setUp()
range_obj = getattr(plot, 'extra_{}_ranges'.format(axis_name))
range_obj['foo_range'] = self.get_range_instance()
self.assertTrue(range_obj['foo_range'])
import numpy as np
from bokeh.io import curdoc, show
from bokeh.models import ColumnDataSource, Grid, InvertedTriangle, LinearAxis, Plot
N = 9
x = np.linspace(-2, 2, N)
y = x**2
sizes = np.linspace(10, 20, N)
source = ColumnDataSource(dict(x=x, y=y, sizes=sizes))
plot = Plot(title=None,
plot_width=300,
plot_height=300,
min_border=0,
toolbar_location=None)
glyph = InvertedTriangle(x="x",
y="y",
size="sizes",
line_color="#de2d26",
line_width=2,
fill_color=None)
plot.add_glyph(source, glyph)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
x1=np.linspace(0, 150, N),
y1=np.linspace(0, 150, N),
w1=np.linspace(10, 50, N),
h1=np.linspace(10, 50, N),
x2=np.linspace(-50, 150, N),
y2=np.linspace(0, 200, N),
))
xdr = Range1d(start=-100, end=200)
ydr = Range1d(start=-100, end=200)
plot = Plot(title=None,
x_range=xdr,
y_range=ydr,
plot_width=300,
plot_height=300,
h_symmetry=False,
v_symmetry=False,
min_border=0,
toolbar_location=None)
image1 = ImageURL(url="url", x="x1", y="y1", w="w1", h="h1", anchor="center")
plot.add_glyph(source, image1)
image2 = ImageURL(url="url", x="x2", y="y2", w=20, h=20, anchor="top_left")
plot.add_glyph(source, image2)
image3 = ImageURL(url=dict(value=url), x=200, y=-100, anchor="bottom_right")
plot.add_glyph(source, image3)
xaxis = LinearAxis()
from bokeh.models import WheelZoomTool, ResizeTool, PanTool, BoxZoomTool
from bokeh.models import WMTSTileSource
output_file("tile_source_example.html", title="Tile Source Example")
# set to roughly full extent of web mercator projection
x_range = Range1d(start=-20000000, end=20000000)
y_range = Range1d(start=-20000000, end=20000000)
# create tile source from templated url
tile_options = {}
tile_options['url'] = 'http://c.tile.openstreetmap.org/{z}/{x}/{y}.png'
tile_source = WMTSTileSource(**tile_options)
# instantiate plot and add tile source
p = Plot(x_range=x_range, y_range=y_range, plot_height=800, plot_width=800)
p.add_tools(ResizeTool(), WheelZoomTool(), PanTool(),
BoxZoomTool(match_aspect=True))
tile_renderer_options = {}
p.add_tile(tile_source, **tile_renderer_options)
doc = Document()
doc.add_root(p)
if __name__ == "__main__":
filename = "tile_source.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Tile Source Example"))
print("Wrote %s" % filename)
view(filename)
def write_bokeh_graph(data_frame, html_output, project_code):
df_tp = data_frame.T
df_tp.index = pd.to_datetime(df_tp.index)
df_tp.sort_index(inplace=True)
df_columns_count = df_tp.shape[0]
df_rows_count = df_tp.shape[1]
colors = viridis(len(df_tp.columns))
# option_sets
hover = HoverTool(tooltips=[("name", "@name"),
("time", "@time"),
("count", "@count"),
]
)
tools_opt = ["resize", hover, "save", "pan", "wheel_zoom", "reset"]
graph_opt = dict(width=900, x_axis_type="datetime",
toolbar_location="left", tools=tools_opt, toolbar_sticky=False,
background_fill_alpha=0, border_fill_alpha=0,
)
line_opt = dict(line_width=3, alpha=0.8)
output_file(html_output, mode="inline")
legend_items = []
# figure and line glyphs
warning_figure = figure(title=project_code + " rvt warnings",
**graph_opt,
)
for i, warning_type in enumerate(df_tp.columns):
# print(f"df_tp.index is: \n{df_tp.index}")
line_name_dict = [warning_type for _ in range(df_columns_count)]
cds = ColumnDataSource(data=dict(x=df_tp.index,
y=df_tp[warning_type],
name=line_name_dict,
count=df_tp[warning_type],
time=df_tp.index.strftime("%Y-%m-%d %H:%M:%S"),
)
)
warning_figure.line("x",
"y",
color=colors[i],
name="name",
source=cds,
**line_opt
)
legend_items.append((warning_type, colors[i]))
square_size, legend_sq_offset = 20, 20
legend_plot_height = df_rows_count * (legend_sq_offset + square_size)
# print(f"plot height is: {legend_plot_height}")
legend = Plot(plot_width=900,
plot_height=legend_plot_height,
x_range=Range1d(0, 300),
y_range=Range1d(0, legend_plot_height),
toolbar_location="left",
background_fill_alpha=0,
border_fill_alpha=0,
outline_line_alpha=0,
)
for i, item in enumerate(legend_items):
warn_type = item[0]
color = item[1]
square_y_pos = legend_plot_height - legend_sq_offset - i * (legend_sq_offset + square_size)
square = Square(x=square_size,
y=square_y_pos,
size=square_size,
fill_color=color,
line_alpha=0,
)
legend.add_glyph(square)
warning_count_text = str(df_tp[warn_type][-1]).rjust(5)
warning_text = warn_type
count_txt = Text(x=square_size + 15,
y=square_y_pos,
text_align="right",
text_baseline="middle",
text=[warning_count_text],
text_font_size="10pt",
)
legend.add_glyph(count_txt)
warn_txt = Text(x=square_size + 16,
y=square_y_pos,
text_align="left",
text_baseline="middle",
text=[warning_text[:120]],
text_font_size="10pt",
)
legend.add_glyph(warn_txt)
save(column(style_plot(warning_figure), legend))
print(colorful.bold_green(f" {html_output}\n updated successfully."))
return df_tp
ResetTool,
SaveTool,
Select,
Spacer,
Spinner,
Title,
WheelZoomTool,
)
doc = curdoc()
stats = doc.stats
doc.title = f"{doc.title} ROI Projections"
plot = Plot(
title=Title(text="ROI Projections"),
x_range=DataRange1d(),
y_range=DataRange1d(),
toolbar_location="left",
)
plot.toolbar.logo = None
plot.add_tools(PanTool(), BoxZoomTool(), WheelZoomTool(), SaveTool(),
ResetTool())
plot.add_layout(LinearAxis(), place="below")
plot.add_layout(LinearAxis(), place="left")
plot.add_layout(Grid(dimension=0, ticker=BasicTicker()))
plot.add_layout(Grid(dimension=1, ticker=BasicTicker()))
line_off_source = ColumnDataSource(dict(x=[], y=[]))
line_off = plot.add_glyph(line_off_source,
document = Document()
session = Session()
session.use_doc('linked_tap_server')
session.load_document(document)
N = 9
x = np.linspace(-2, 2, N)
y = x**2
source1 = ColumnDataSource(dict(x=x, y=y, size=[20] * N))
xdr1 = DataRange1d(sources=[source1.columns("x")])
ydr1 = DataRange1d(sources=[source1.columns("y")])
plot1 = Plot(title="Plot1",
x_range=xdr1,
y_range=ydr1,
plot_width=400,
plot_height=400)
plot1.tools.append(TapTool(plot=plot1))
plot1.add_glyph(source1, Circle(x="x", y="y", size="size", fill_color="red"))
plot1.toolbar_location = None
source2 = ColumnDataSource(dict(x=x, y=y, color=["blue"] * N))
xdr2 = DataRange1d(sources=[source2.columns("x")])
ydr2 = DataRange1d(sources=[source2.columns("y")])
plot2 = Plot(title="Plot2",
x_range=xdr2,
y_range=ydr2,
plot_width=400,
plot_height=400)
plot2.tools.append(TapTool(plot=plot2))
