def after_write_file(self, args, filename, doc):
'''
'''
if args.show:
from bokeh.util.browser import view
view(filename)
def show(self, app_path, browser=None, new='tab'):
''' Opens an app in a browser window or tab.
Useful for testing server applications on your local desktop but
should not call when running bokeh-server on an actual server.
Args:
app_path (str) : the app path to open
The part of the URL after the hostname:port, with leading slash.
browser (str, optional) : browser to show with (default: None)
For systems that support it, the **browser** argument allows
specifying which browser to display in, e.g. "safari", "firefox",
"opera", "windows-default" (see the ``webbrowser`` module
documentation in the standard lib for more details).
new (str, optional) : window or tab (default: "tab")
If ``new`` is 'tab', then opens a new tab.
If ``new`` is 'window', then opens a new window.
Returns:
None
'''
if not app_path.startswith("/"):
raise ValueError("app_path must start with a /")
from bokeh.util.browser import view
url = "http://localhost:%d%s%s" % (self.port, self.prefix, app_path)
view(url, browser=browser, new=new)
def main():
p = argparse.ArgumentParser()
p.add_argument('infile', nargs='?', type=argparse.FileType('r'), default=sys.stdin)
p.add_argument('outfile', nargs='?', default="site/index.html")
p.add_argument('-t', '--template', default='template.jinja',
help="""Jinja2 Tempate file[default: %(default)]""")
p.add_argument('-v', '--view', default=False,
help="""Launch browser to view output: %(default)]""")
a = p.parse_args()
df = pd.read_csv(a.infile)
plots = mkplots(df)
script, div = components(plots)
js_resources = CDN.render_js()
css_resources = CDN.render_css()
env = Environment(loader=FileSystemLoader(THIS_DIR),
trim_blocks=True)
# Alias str.format to strformat in template
env.filters['strformat'] = str.format
template = env.get_template(a.template)
html = template.render( date=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
command=" ".join(sys.argv),
workdir=os.getcwd(),
user=getpass.getuser(),
title="Santa Performance Plots",
js_resources=js_resources,
css_resources=css_resources,
script=script,
div=div)
with open(a.outfile, "w") as f:
f.write(html.encode('utf-8'))
# to deploy to gh-pages, use the function `gh=deploy` defined in ~.bash_profile
# first copy index.html tp the `site/` directory
# Cribbed from https://gist.github.com/cobyism/4730490
# git subtree push --prefix site origin gh-pages
if a.view:
view(a.outfile)
def show(self, app_path, browser=None, new='tab'):
''' Opens an app in a browser window or tab.
This method is useful for testing or running Bokeh server applications
on a local machine but should not call when running Bokeh server for
an actual deployment.
Args:
app_path (str) : the app path to open
The part of the URL after the hostname:port, with leading slash.
browser (str, optional) : browser to show with (default: None)
For systems that support it, the **browser** argument allows
specifying which browser to display in, e.g. "safari", "firefox",
"opera", "windows-default" (see the ``webbrowser`` module
documentation in the standard lib for more details).
new (str, optional) : window or tab (default: "tab")
If ``new`` is 'tab', then opens a new tab.
If ``new`` is 'window', then opens a new window.
Returns:
None
'''
if not app_path.startswith("/"):
raise ValueError("app_path must start with a /")
address_string = 'localhost'
if self.address is not None and self.address != '':
address_string = self.address
url = "http://%s:%d%s%s" % (address_string, self.port, self.prefix,
app_path)
from bokeh.util.browser import view
view(url, browser=browser, new=new)
def show(self):
"""Display a figure (called by backtrader)."""
# as the plot() function only created the figures and the columndatasources with no data -> now we fill it
for idx in range(len(self.figurepages)):
model = self.generate_model(idx)
if self.p.output_mode in ['show', 'save']:
if self._iplot:
css = self._output_stylesheet()
display(HTML(css))
show(model)
else:
filename = self._output_plot_file(model, idx,
self.p.filename)
if self.p.output_mode == 'show':
view(filename)
elif self.p.output_mode == 'memory':
pass
else:
raise RuntimeError(
f'Invalid parameter "output_mode" with value: {self.p.output_mode}'
)
self._reset()
widgets = Column(children=[
Row(children=[
Column(children=[
click_button, disabled_button, toggle, dropdown, dropdown_split,
checkbox_group, radio_group,
checkbox_button_group, radio_button_group,
]),
Column(children=[
text_input, autocomplete_input,
select, multi_select,
slider, range_slider, date_slider, date_range_slider,
spinner, color_picker, date_picker,
paragraph, div, pre_text,
]),
tabs,
]),
table,
])
doc = Document()
doc.add_root(widgets)
if __name__ == "__main__":
doc.validate()
filename = "widgets.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Widgets"))
print("Wrote %s" % filename)
view(filename)
def plot_selected_country(self, name, output, module="bokeh"):
if self.selected is None:
raise ValueError("no country selected")
# create dictionary out of df that can be put into JS function
grouped_df_d = self.df_daily.groupby("Country/Region", sort=False)
grouped_df_t = self.df_total.groupby("Country/Region", sort=False)
grouped_list_d = grouped_df_d.apply(lambda x: x.to_dict(orient="list"))
grouped_list_t = grouped_df_t.apply(lambda x: x.to_dict(orient="list"))
df_dict_nested_d = grouped_list_d.to_dict()
df_dict_nested_t = grouped_list_t.to_dict()
df_dict_daily = {}
df_dict_total = {}
keys_to_ignore = ["Province/State", "Country/Region", "Lat", "Long"]
for key, value in df_dict_nested_d.items():
helper_list = []
for key_two, value_two in value.items():
if key_two in keys_to_ignore:
continue
else:
# sums up countries that occur multiple times
helper_list.append(sum(value_two))
df_dict_daily[key] = helper_list
for key, value in df_dict_nested_t.items():
helper_list = []
for key_two, value_two in value.items():
if key_two in keys_to_ignore:
continue
else:
# sums up countries that occur multiple times
helper_list.append(sum(value_two))
df_dict_total[key] = helper_list
dates = []
dates_str = []
for date_str in self.selected.index:
date_obj = datetime.strptime(date_str, '%m/%d/%y')
dates.append(date_obj)
date_str_new = datetime.strptime(date_str,
'%m/%d/%y').strftime('%d %b %Y')
dates_str.append(date_str_new)
df_dict_daily["dates"] = dates
df_dict_total["dates"] = dates
df_dict_daily["dates_str"] = dates_str
df_dict_total["dates_str"] = dates_str
if module == "bokeh":
# also necessary to make it compatible with JS function
df_dict_daily["selected"] = df_dict_daily[name]
df_dict_total["selected"] = df_dict_total[name]
source_daily = ColumnDataSource(data=df_dict_daily)
source_total = ColumnDataSource(data=df_dict_total)
# create two plots
XAXIS_LABEL = "Date"
YAXIS_LABEL = "Death Cases"
LEGEND_LOC = "top_left"
TOOLTIPS = [("Date", "@dates_str"),
("Cases of selected country", "@selected"),
("Cases worldwide", "@World")]
TOOLS = [
HoverTool(tooltips=TOOLTIPS), "pan", "wheel_zoom", "box_zoom",
"reset"
]
HEIGHT = 600
WIDTH = 760
SIZE = 1
CIRCLE_SIZE = 12
colors = ["lightgray", "red"]
pd = figure(x_axis_type="datetime",
title="Daily Infections",
plot_height=HEIGHT,
tools=TOOLS,
width=WIDTH,
css_classes=["we-need-this-for-manip"],
name="d_infections")
pt = figure(x_axis_type="datetime",
title="Total Infections",
plot_height=HEIGHT,
tools=TOOLS,
width=WIDTH,
css_classes=["we-need-this-for-manip-total"],
name="t_infections")
# pd.vbar(x='dates', top="World", color=colors[0], line_width=SIZE,
# source=source_daily, legend_label="Worldwide")
pd.vbar(x='dates',
top="selected",
color=colors[1],
line_width=SIZE,
source=source_daily,
legend_label="Selected Country")
# HoverTool does not work for vbar so invisible circles are necessary
# pd.circle(x='dates', y="World", color=colors[0], size=CIRCLE_SIZE,
# source=source_daily, legend_label="Worldwide", fill_alpha=0,
# line_alpha=0)
pd.circle(x='dates',
y="selected",
color=colors[1],
size=CIRCLE_SIZE,
source=source_daily,
legend_label="Selected Country",
fill_alpha=0,
line_alpha=0)
pd.legend.location = LEGEND_LOC
pd.yaxis.axis_label = YAXIS_LABEL
pd.xaxis.axis_label = XAXIS_LABEL
# pt.vbar(x='dates', top="World", color=colors[0], line_width=SIZE,
# source=source_total, legend_label="Worldwide")
pt.vbar(x='dates',
top="selected",
color=colors[1],
line_width=SIZE,
source=source_total,
legend_label="Selected Country")
# pt.circle(x='dates', y="World", color=colors[0], size=CIRCLE_SIZE,
# source=source_total, legend_label="Worldwide", fill_alpha=0,
# line_alpha=0)
pt.circle(x='dates',
y="selected",
color=colors[1],
size=CIRCLE_SIZE,
source=source_total,
legend_label="Selected Country",
fill_alpha=0,
line_alpha=0)
pt.legend.location = LEGEND_LOC
pt.yaxis.axis_label = YAXIS_LABEL
pt.xaxis.axis_label = XAXIS_LABEL
output_file(output)
# dropdown menu
# dates can't be sorted like this, so it has to be removed for this step
df_dict_total.pop("dates")
df_dict_total.pop("dates_str")
sort_options = sorted(df_dict_total.items(),
key=lambda x: x[1][-1],
reverse=True)
options = []
for tpl in sort_options:
total_cases_list = list(str(tpl[1][-1]))
total_cases_str_sep = ""
for i, num in enumerate(total_cases_list):
total_cases_str_sep += num
if i == len(total_cases_list) - 1:
continue
elif len(total_cases_list) % 3 == 0:
if i % 3 == 2:
total_cases_str_sep += ","
elif len(total_cases_list) % 3 == 1:
if i % 3 == 0:
total_cases_str_sep += ","
elif len(total_cases_list) % 3 == 2:
if i % 3 == 1:
total_cases_str_sep += ","
if tpl[0] == name:
selected_total_cases_sep = total_cases_str_sep
options.append(f"{tpl[0]}: {total_cases_str_sep} total cases")
options.remove(f"selected: {selected_total_cases_sep} total cases")
df_dict_total["dates"] = dates
df_dict_total["dates_str"] = dates_str
select = Select(
title="Select a country",
value=f"{name}: {selected_total_cases_sep} total cases",
options=options,
sizing_mode="scale_width")
with open("main.js", "r") as f:
select.js_on_change(
"value",
CustomJS(args=dict(
source_d=source_daily,
source_t=source_total,
df_dict_t=df_dict_total,
df_dict_d=df_dict_daily,
),
code=f.read()))
plots = column(pd, pt)
# show(column(select, plots))
with open("template.html", "r") as f:
template = f.read()
save(column(select, plots), template=template)
view(output)
if module == "mpl":
confirmed_cases = []
confirmed_cases_world = []
# cave: only for daily
for sub_arr in self.selected.values:
confirmed_cases.append(sub_arr[0])
for sub_arr in self.world_data_daily.values:
confirmed_cases_world.append(sub_arr[0])
fig, ax = plt.subplots()
date_format = DateFormatter("%d %b %Y")
world_plot = ax.bar(dates,
confirmed_cases_world,
bottom=0,
color="lightgray")
country_plot = ax.bar(dates, confirmed_cases, bottom=0)
ax.set(xlabel="Date", ylabel="Death Cases")
ax.xaxis.set_major_formatter(date_format)
fig.subplots_adjust(bottom=0.175)
plt.xticks(rotation=35, fontsize=7)
plt.legend((world_plot[0], country_plot[0]),
("Worldwide", "{}".format(name)))
plt.show()
def writeMapToFile(filename, doc):
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Google Maps Example"))
print "Wrote %s" % filename
view(filename)
def test_view_bad_new() -> None:
with pytest.raises(RuntimeError) as e:
bub.view("foo", new="junk")
assert str(
e
) == "invalid 'new' value passed to view: 'junk', valid values are: 'same', 'window', or 'tab'"
def test_view_args():
db = bub.DummyWebBrowser
bub.DummyWebBrowser = _RecordingWebBrowser
# test http locations used as-is
bub.view("http://foo", browser="none")
assert _open_args == (('http://foo',), {'autoraise': True, 'new': 0})
# test non-http locations treated as local files
bub.view("/foo/bar", browser="none")
assert _open_args == (('file:///foo/bar',), {'autoraise': True, 'new': 0})
# test autoraise passed to open
bub.view("http://foo", browser="none", autoraise=False)
assert _open_args == (('http://foo',), {'autoraise': False, 'new': 0})
# test handling of new values
bub.view("http://foo", browser="none", new="same")
assert _open_args == (('http://foo',), {'autoraise': True, 'new': 0})
bub.view("http://foo", browser="none", new="window")
assert _open_args == (('http://foo',), {'autoraise': True, 'new': 1})
bub.view("http://foo", browser="none", new="tab")
assert _open_args == (('http://foo',), {'autoraise': True, 'new': 2})
bub.DummyWebBrowser = db
def stop(PORT=EOD_HOSE_LISTEN_PORT):
view(f"http://localhost:{PORT}/shutdown")
def intplotter(data, isodata, nodata, y, hetclassintdf):
linewidth = 1.5
source = ColumnDataSource(data)
s2 = ColumnDataSource(data=dict(mz=data["mz"],
Error=data["Error"],
RA=data["RA"],
Formula=data["Formula"],
HeteroClass=data["HeteroClass"]))
isosource = ColumnDataSource(isodata)
nosource = ColumnDataSource(nodata)
url = "http://www.chemspider.com/Search.aspx?q=@Formula"
TOOLS = "crosshair,pan,wheel_zoom,box_zoom,reset,tap,save,box_select,poly_select,lasso_select,hover"
figdims = (900, 500) #pixel dimensions for the normal figures
msxlim = [200, 700] #x limits in m/z for the mass spectra
vkxlim = [0, 1]
vkylim = [0, 2]
p1 = figure(tools=TOOLS,
title=y[:-9] + " - Van Krevelen",
width=figdims[0],
height=figdims[1],
x_axis_label='O/C',
y_axis_label='H/C',
x_range=vkxlim,
y_range=vkylim)
color_mapper = LinearColorMapper(palette=glocmap,
low=msxlim[0],
high=msxlim[1])
p1.scatter(x='OC',
y='HC',
source=source,
size='VKsize',
fill_color={
'field': 'mz',
'transform': color_mapper
},
fill_alpha=0.75,
line_color=None) #use size not radius.
hover = p1.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),
('Mass', "@mz{1.11111}"),
('Error (ppm)', "@Error{1.11}")])
taptool = p1.select(type=TapTool)
taptool.callback = OpenURL(url=url)
color_bar = ColorBar(color_mapper=color_mapper,
title="m/z",
border_line_color=None,
location=(0, 0),
scale_alpha=0.7)
#orientation='horizontal',location='top_left', scale_alpha=0.7)#,ticker=FixedTicker(ticks=[2,6,10,14,18]))
p1.add_layout(color_bar, "right")
dbexlim = [0, 45]
dbeylim = [0, 40]
cmax = max(data["O"])
cmax = int(5 * round(float(cmax) / 5))
p2 = figure(tools=TOOLS,
title=y[:-9] + " - DBE vs C# Plot",
width=figdims[0],
height=figdims[1],
x_axis_label='C#',
y_axis_label='DBE',
x_range=dbexlim,
y_range=dbeylim)
color_mapper2 = LinearColorMapper(palette=glocmap2, low=0, high=cmax)
p2.scatter(x='C',
y='DBE',
source=source,
size='VKsize',
fill_color={
'field': 'O',
'transform': color_mapper2
},
fill_alpha=0.75,
line_color=None)
hover = p2.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),
('Mass', "@mz{1.11111}"),
('Error (ppm)', "@Error{1.11}")])
taptool = p2.select(type=TapTool)
taptool.callback = OpenURL(url=url)
color_bar2 = ColorBar(
color_mapper=color_mapper2,
title="O#",
border_line_color=None,
location=(0, 0),
scale_alpha=0.7,
ticker=FixedTicker(
ticks=[0, int(cmax / 4),
int(cmax / 2),
int(3 * cmax / 4), cmax]))
p2.add_layout(color_bar2, "right")
aixlim = [0, 45]
aiylim = [0, 1]
p3 = figure(tools=TOOLS,
title=y[:-9] + " - AI(mod) vs C# Plot",
width=figdims[0],
height=figdims[1],
x_axis_label='C#',
y_axis_label='AI(mod)',
x_range=aixlim,
y_range=aiylim)
color_mapper3 = LinearColorMapper(palette=glocmap2, low=0, high=cmax)
p3.scatter(x='C',
y='AImod',
source=source,
size='VKsize',
fill_color={
'field': 'O',
'transform': color_mapper3
},
fill_alpha=0.75,
line_color=None)
hover = p3.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),
('Mass', "@mz{1.11111}"),
('Error (ppm)', "@Error{1.11}")])
taptool = p3.select(type=TapTool)
taptool.callback = OpenURL(url=url)
color_bar3 = ColorBar(
color_mapper=color_mapper3,
title="O#",
border_line_color=None,
location=(0, 0),
scale_alpha=0.7,
ticker=FixedTicker(
ticks=[0, int(cmax / 4),
int(cmax / 2),
int(3 * cmax / 4), cmax]))
#orientation='horizontal',location='top_left', scale_alpha=0.7)#,ticker=FixedTicker(ticks=[2,6,10,14,18]))
p3.add_layout(color_bar3, "right")
p4 = figure(tools=TOOLS,
title=y[:-9] + " - Assigned Centroid MS",
width=figdims[0],
height=figdims[1],
x_axis_label='m/z',
y_axis_label='Abundance',
y_range=[min(data["RA"]), max(data["RA"])],
x_range=msxlim)
p4.segment(x0=0, x1=800, y0=0, y1=0, line_width=1, line_color="black")
p4.segment(x0='mz',
y0=0,
x1='mz',
y1='RA',
source=source,
line_width=linewidth,
line_color="black")
p4.scatter(x='mz',
y='RA',
source=source,
fill_color='black',
line_color=None)
hover = p4.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),
('Mass', "@mz{1.11111}"),
('Error (ppm)', "@Error{1.11}")])
taptool = p4.select(type=TapTool)
taptool.callback = OpenURL(url=url)
p4.yaxis[0].formatter = PrintfTickFormatter(format="%4.1e")
"""
#this is me trying to plot a barplot of heteroatomic class distributions...
p7 = figure(tools=TOOLS, title=y[:-9]+"",width=800, height=600, x_axis_label='HeteroClass',y_axis_label='Count',webgl=True)
p7.quad(left="HetClassInts",y=hetclassdf[0],source=source,width=5,height=)
t7 = layouts.Column(hist)
tab7 = Panel(child=t7,title="test")
"""
stretch = msxlim[0] * 0.1
p5 = figure(tools=TOOLS,
title=y[:-9] + " - Assigned Centroid MS",
width=1400,
height=600,
x_axis_label='m/z',
y_axis_label='Abundance',
y_range=[min(data["RA"]), max(data["RA"])],
x_range=(msxlim[0] - stretch, msxlim[1] + stretch))
p5.segment(x0=0, x1=800, y0=0, y1=0, line_width=1, line_color="black")
no1 = p5.segment(x0='mz',
y0=0,
x1='mz',
y1='RA',
source=nosource,
line_width=linewidth,
line_color="red",
legend_label="Unassigned Peaks")
#no2 =p5.scatter(x='mz', y='RA',source=nosource,fill_color='red',line_color=None,legend_label="Unassigned Peaks")
#p5.scatter(x='mz', y='RA',source=source,fill_color='black',line_color=None,legend_label="Assigned Peaks")
p5.segment(x0='mz',
y0=0,
x1='mz',
y1='RA',
source=source,
line_width=linewidth,
line_color="black",
legend_label="Assigned Peaks")
iso1 = p5.segment(x0='mz',
y0=0,
x1='mz',
y1='RA',
source=isosource,
line_width=linewidth,
line_color="green",
legend_label="Isotologue Peaks")
#iso2 =p5.scatter(x='mz', y='RA',source=isosource,fill_color='green',line_color=None, legend_label="Isotologue Peaks")
hover = p5.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),
('Mass', "@mz{1.11111}"),
('Error (ppm)', "@Error{1.11}")])
taptool = p5.select(type=TapTool)
taptool.callback = OpenURL(url=url)
p5.yaxis[0].formatter = PrintfTickFormatter(format="%4.1e")
#Bokeh 2 doesnt need JS buttons thanks to interactive legends
#js_code1 = "iso1.glyph.visible = false; iso2.glyph.visible = false; no1.glyph.visible = false; no2.glyph.visible = false;"
#cb1 = CustomJS(code=js_code1, args=dict(iso1=iso1,iso2=iso2,no1=no1,no2=no2))
#js_code2 = "iso1.glyph.visible = true; iso2.glyph.visible = true; no1.glyph.visible = true; no2.glyph.visible = true;"
#cb2 = CustomJS(code=js_code2, args=dict(iso1=iso1,iso2=iso2,no1=no1,no2=no2))
#toggleOn = Button(label="Hide", button_type="success")
#toggleOn.js_on_click(cb1)
#toggleOff = Button(label="Show", button_type="success")
#toggleOn.js_on_click(cb2)
#top = layouts.Row(toggleOn,toggleOff)
t3 = layouts.Column(p5)
p5.legend.location = "top_left"
p5.legend.click_policy = "hide"
tab3 = Panel(child=t3, title="Centroid MS with Isotopomers and No Hits")
downloadbutton = Button(label="Download", button_type="success")
cb3 = CustomJS(args=dict(s2=s2),
code="""
var data = s2.get('data');
var filetext = 'mz,Error,RA,Formula,HeteroClass\\n';
for (i=0; i < data['mz'].length; i++) {
var currRow = [data['mz'][i].toString(),
data['Error'][i].toString(),
data['RA'][i].toString(),
data['Formula'][i].toString(),
data['HeteroClass'][i].toString().concat('\\n')];
var joined = currRow.join();
filetext = filetext.concat(joined);
}
var filename = 'data_result.csv';
var blob = new Blob([filetext], { type: 'text/csv;charset=utf-8;' });
//addresses IE
if (navigator.msSaveBlob) {
navigator.msSaveBlob(blob, filename);
}
else {
var link = document.createElement("a");
link = document.createElement('a');
link.href = URL.createObjectURL(blob);
link.download = filename;
link.target = "_blank";
link.style.visibility = 'hidden';
link.dispatchEvent(new MouseEvent('click'))
}
""")
downloadbutton.js_on_event(ButtonClick, cb3)
columns = [
TableColumn(field="mz",
title="m/z",
formatter=NumberFormatter(format="0.00000")),
TableColumn(field="Error",
title="Error (ppm)",
formatter=NumberFormatter(format="0.00")),
TableColumn(field="RA", title="Abundance"),
TableColumn(field="Formula", title="Formula"),
TableColumn(field="HeteroClass", title="Heteroatomic Class")
]
data_table = DataTable(source=s2,
columns=columns,
width=1400,
header_row=False,
fit_columns=True)
t4 = layouts.Column(data_table, downloadbutton)
tab4 = Panel(child=t4, title="Selected Data Table")
cb4 = CustomJS(args=dict(s2=s2, dt=data_table),
code="""
var inds = cb_obj.get('selected')['1d'].indices;
var d1 = cb_obj.get('data');
var d2 = s2.get('data');
if (inds.length == 0) {
d2['mz'] = d1['mz']
d2['Error'] = d1['Error']
d2['RA'] = d1['RA']
d2['Formula'] = d1['Formula']
d2['HeteroClass'] = d1['HeteroClass']
}
else if (inds.length != 0) {
d2['mz'] = []
d2['Error'] = []
d2['RA'] = []
d2['Formula'] = []
d2['HeteroClass'] = []
for (i = 0; i < inds.length; i++) {
d2['mz'].push(d1['mz'][inds[i]])
d2['Error'].push(d1['Error'][inds[i]])
d2['RA'].push(d1['RA'][inds[i]])
d2['Formula'].push(d1['Formula'][inds[i]])
d2['HeteroClass'].push(d1['HeteroClass'][inds[i]])
}
}
s2.trigger('change');
dt.trigger('change');
""")
source.selected.js_on_change('indices', cb4)
"""
hetclasslist = hetclassintdf["HetClass"].tolist()
hetclasslistnew = []
for x in hetclasslist:
hetclasslistnew.append([x,x])
dropdown = Dropdown(label="Dropdown button", button_type="warning", menu=hetclasslistnew)
"""
t1 = layouts.Row(p1, p4)
t2 = layouts.Row(p2, p3)
t12 = layouts.Column(t1, t2)
tab1 = Panel(child=t12, title="Main")
tabs = Tabs(tabs=[tab1, tab3, tab4])
for figs in [p1, p2, p3, p4, p5]:
figs.xaxis.axis_label_text_font_size = "14pt"
figs.xaxis.major_label_text_font_size = "14pt"
figs.yaxis.axis_label_text_font_size = "14pt"
figs.yaxis.major_label_text_font_size = "14pt"
figs.title.text_font_size = "14pt"
figs.toolbar_location = "above"
with open(outputpath + 'templates/index.html', 'r') as f:
template = Template(f.read())
#js_resources = JSResources(mode='inline')
html = file_html(tabs, (CDN, CDN),
"Interactive Van Krevelen Diagrams",
template=template)
output_file2 = outputpath + y[:-9] + '-plot.html'
with open(output_file2, 'w') as f:
f.write(html)
view(output_file2)
def ShowGraph(graphDict):
if not graphDict['ShowGraph']:
logger.warning('%s is not shown.', graphDict['GraphTitle'])
return
if (len(graphDict['Yaxes']) <= 0) or (len(graphDict['items']) <= 0):
debug('No axes or no lines defined for graph "%s"',
graphDict['GraphTitle'])
return
if graphDict['DBHost'] not in DBHostDict.keys():
logger.warning('Unknown database host "%s" for plot "%s"' %
(graphDict['DBHost'], graphDict['GraphTitle']))
return
hostItem = DBHostDict[graphDict['DBHost']]
# Signal that we want to reference local files for html output.
res = Resources(mode='absolute')
# output_file(graphDict["outputFile"], title=graphDict['GraphTitle'])
plot = figure(title=graphDict['GraphTitle'],
tools="pan,wheel_zoom,box_zoom,reset,save,box_select",
x_axis_type='datetime',
plot_width=1600,
plot_height=800,
active_drag="box_zoom",
active_scroll="wheel_zoom")
plot.title.align = "center"
plot.title.text_font_size = "25px"
plot.xaxis.axis_label = graphDict['XaxisTitle']
# plot.xaxis.ticker = DatetimeTicker(num_minor_ticks = 4)
plot.xaxis.formatter = DatetimeTickFormatter(seconds=["%M:%S"],
minutes=["%R"],
minsec=["%M:%S"],
hours=["%R"],
hourmin=["%m/%d %R"],
days=['%m/%d'])
plot.toolbar.logo = None
legend = Legend()
# legend.items = [LegendItem(label="--- Left Axis ---" , renderers=[])]
legend.items = []
######### Setup Y axes
## Colors
plot.yaxis.visible = False
extra_y_ranges = {}
for i in range(len(graphDict['Yaxes'])):
ya = graphDict['Yaxes'][i]
eyrName = 'Y%s_axis' % i
clr = ya['color_map']
if clr is None: clr = graphDict["graph_color_map"]
ya["cmap"] = myPalette.Palette(clr,
graphDict['max_palette_len'],
loggingLevel=helperFunctionLoggingLevel)
clr = ya['color']
if clr is None: clr = "black"
side = ya['location']
extra_y_ranges[eyrName] = DataRange1d(range_padding=0.01)
plot.extra_y_ranges = extra_y_ranges
plot.add_layout(
LinearAxis(y_range_name=eyrName,
axis_label=ya['title'],
axis_line_color=clr,
major_label_text_color=clr,
axis_label_text_color=clr,
major_tick_line_color=clr,
minor_tick_line_color=clr), side)
for i in range(len(graphDict['items'])):
item = graphDict['items'][i]
info('-------------- %s ------------' % item['dataname'])
ya = graphDict['Yaxes'][item['axisNum']]
colorGroup = ya['title']
query = item['query'].format(
my_schema=hostItem['myschema'],
ha_schema=hostItem['haschema'],
BeginDate=
'{BeginDate}' # Leave {BeginDate} unmolested; it is for later replacement.
)
if item['dataTimeZone'] == 'UTC':
dataTimeOffsetUTC = 0
else:
dataTimeOffsetUTC = hostItem['ServerTimeFromUTC']
data = GetData(item['datafile'], query, dataTimeOffsetUTC, hostItem)
if data is None:
logger.warning(
'item "%s" of graph "%s" has no data and is skipped.' %
(item['dataname'], graphDict['GraphTitle']))
continue
else:
debug('Got %s rows of data.' % data.size)
data = ColumnDataSource(data)
debug('data column names are: %s; num rows is: %s' %
(data.column_names, data.to_df().size))
yRangeName = 'Y%s_axis' % item['axisNum']
for thisCol in data.column_names[1:]:
debug('Column "%s" is plotted against y axis: "%s"' %
(thisCol, yRangeName))
itemColor = item["color"]
if item["color"] is None:
itemColor = ya['cmap'].nextColor(colorGroup)
else:
debug('item color "%s" is defined in the item definition.' %
itemColor)
r = eval('''plot.%s(x=data.column_names[0]
, y = thisCol
, source=data
, color = itemColor, alpha=0.5
, muted_color = itemColor, muted_alpha=1
, name = thisCol
, y_range_name=yRangeName)''' % item['lineType'])
for (k, v) in item['lineMods'].items():
s = 'r.%s = %s' % (k, v)
debug('Executing line mod "%s"' % s)
exec(s)
extra_y_ranges[yRangeName].renderers.append(r)
if item['includeInLegend']:
legend.items.append(LegendItem(label=thisCol, renderers=[r]))
plot.add_layout(legend)
plot.legend.location = "top_left"
plot.legend.click_policy = "mute"
plot.add_tools(
HoverTool(
tooltips=[
('', '$name') # use @{ } for field names with spaces
,
('', '$y{0.0}') # use @{ } for field names with spaces
,
('', '@Time{%F %T}')
],
formatters={
'@Time': 'datetime' # use 'datetime' formatter for 'x' field
# use default 'numeral' formatter for other fields
}))
# show(plot)
html = file_html(plot, res, graphDict['GraphTitle'])
f = open(graphDict["outputFile"], mode='w')
f.write(html)
f.close()
view(graphDict["outputFile"], new='tab')
def create_bokeh_plot(df, s_source_dummy, s_source_full, s_sources,
g_source_dummy, g_source_full, g_sources,
selection_dates, selection_day_range):
# assign unique variables for each DataSource required for each date within
# the data timeline
s_source1 = s_sources[0]
s_source2 = s_sources[1]
s_source3 = s_sources[2]
s_source4 = s_sources[3]
s_source5 = s_sources[4]
s_source6 = s_sources[5]
g_source1 = g_sources[0]
g_source2 = g_sources[1]
g_source3 = g_sources[2]
g_source4 = g_sources[3]
g_source5 = g_sources[4]
g_source6 = g_sources[5]
# create sentiment polarity-subjectivity scatter plot
s_p = figure(plot_width=450,
plot_height=450,
x_axis_label='Polarity',
y_axis_label='Subjectivity',
tools=["crosshair", "pan", "box_zoom", "reset"])
# adjusting title text properties of the polarity-subjectivity scatter plot
s_p.title.text = "Tweet Text Sentiment Analysis"
s_p.title.align = "center"
s_p.title.text_color = text_color
s_p.title.text_font_size = title_font_size
s_p.title.text_font = font
s_p.title.text_font_style = font_style
# adjusting axis properties of the polarity-subjectivity scatter plot
s_p.axis.axis_label_text_font_style = font_style
s_p.axis.axis_label_text_font_size = axis_label_font_size
s_p.axis.axis_label_text_font = font
s_p.axis.axis_label_text_color = text_color
s_p.axis.major_label_text_font_size = major_label_font_size
s_p.axis.major_label_text_font = font
s_p.axis.major_label_text_color = text_color
s_p.axis.axis_line_color = text_color
s_p.xaxis.minor_tick_line_color = None
s_p.yaxis.minor_tick_line_color = None
# configure fixed axis numbers for consistent axis properties along
# different scaled data
s_p.y_range.start = -0.1
s_p.y_range.end = 1.1
s_p.x_range.start = -1.1
s_p.x_range.end = 1.1
# configure color palettes low-high for scatters resembling positive or
# negative sentiments
PiYG_reverse = tuple(reversed(PiYG[5]))
mapper = LinearColorMapper(palette=PiYG_reverse, low=-1, high=1)
# add scatter points to polarity-subjectivity scatter plot
circle_glyph = s_p.circle(x='s_x',
y='s_y',
source=s_source_dummy,
size=7,
line_color='grey',
fill_color=transform('s_x', mapper),
fill_alpha=0.5,
hover_color="pink")
# add hover tool to polarity-subjectivity scatter plot
s_p.add_tools(
HoverTool(renderers=[circle_glyph],
tooltips=[("Polarity", "@s_x"), ("Subjectivity", "@s_y"),
("User", "@user"), ("Date", "@created"),
("Location", "@location"), ("Tweet", "@tweet")]))
# load shapefile of germany
sf = gpd.read_file(
os.path.join(resources_dir, 'shapefiles_ger', 'DEU_adm1.shp'))
# Input GeoJSON source that contains features for plotting. This format
# is required for plotting shapefiles in bokeh plots
geosource = GeoJSONDataSource(geojson=sf.to_json())
# create empty map figure object
g_p = figure(title='Tweet Locations',
plot_height=450,
plot_width=400,
tools=["crosshair", "pan", "box_zoom", "reset"])
# adjusting title text properties of the geo plot
g_p.title.text = "Tweet Locations"
g_p.title.align = "center"
g_p.title.text_color = text_color
g_p.title.text_font_size = title_font_size
g_p.title.text_font = font
g_p.title.text_font_style = font_style
# adjusting axis properties of the geo plot
g_p.xgrid.grid_line_color = None
g_p.ygrid.grid_line_color = None
g_p.xaxis.minor_tick_line_color = None
g_p.yaxis.minor_tick_line_color = None
g_p.xaxis.major_tick_line_color = None
g_p.yaxis.major_tick_line_color = None
g_p.axis.axis_label_text_color = None
g_p.axis.major_label_text_color = None
g_p.axis.axis_line_color = None
# create patches of the german states using the geosources
g_p.patches('xs',
'ys',
source=geosource,
fill_color='#ffbaba',
line_color='#f5f5f5',
line_width=1,
fill_alpha=1)
# geo source scatter plot of city counts
scatter = g_p.scatter('g_x',
'g_y',
source=g_source_dummy,
line_color='white',
fill_color='teal',
fill_alpha=0.5,
radius='bins')
# create hover tool
g_p.add_tools(
HoverTool(renderers=[scatter],
tooltips=[("City", "@name"), ("Tweets", "@count"),
("Coordinates", "@g_x, @g_y")]))
# requires to add extra quotes to the selection dates for the if queries
# inside the js callback syntax
selection_dates_js = ["'" + option + "'" for option in selection_dates]
# add custom JS callback for changing data based on date range
callback = CustomJS(args={
'source1': s_source_dummy,
'source2': s_source1,
'source3': s_source2,
'source4': s_source3,
'source5': s_source4,
'source6': s_source5,
'source7': s_source6,
'source8': s_source_full,
'source9': g_source_dummy,
'source10': g_source1,
'source11': g_source2,
'source12': g_source3,
'source13': g_source4,
'source14': g_source5,
'source15': g_source6,
'source16': g_source_full
},
code="""
var data1 = source1.data;
var data2 = source2.data;
var data3 = source3.data;
var data4 = source4.data;
var data5 = source5.data;
var data6 = source6.data;
var data7 = source7.data;
var data8 = source8.data;
var data9 = source9.data;
var data10 = source10.data;
var data11 = source11.data;
var data12 = source12.data;
var data13 = source13.data;
var data14 = source14.data;
var data15 = source15.data;
var data16 = source16.data;
var f = cb_obj.value;
if (f == %s) {
for (var e in data1) delete data1[e];
for (var g in data9) delete data9[g];
data1['s_x'] = data2['s_x'];
data1['s_y'] = data2['s_y'];
data1['user'] = data2['user'];
data1['created'] = data2['created'];
data1['location'] = data2['location'];
data1['tweet'] = data2['tweet'];
data9['g_x'] = data10['g_x'];
data9['g_y'] = data10['g_y'];
data9['name'] = data10['name'];
data9['count'] = data10['count'];
data9['bins'] = data10['bins'];
}
if (f == %s) {
for (var e in data1) delete data1[e];
for (var g in data9) delete data9[g];
data1['s_x'] = data3['s_x'];
data1['s_y'] = data3['s_y'];
data1['user'] = data3['user'];
data1['created'] = data3['created'];
data1['location'] = data3['location'];
data1['tweet'] = data3['tweet'];
data9['g_x'] = data11['g_x'];
data9['g_y'] = data11['g_y'];
data9['name'] = data11['name'];
data9['count'] = data11['count'];
data9['bins'] = data11['bins'];
}
if (f == %s) {
for (var e in data1) delete data1[e];
for (var g in data9) delete data9[g];
data1['s_x'] = data4['s_x'];
data1['s_y'] = data4['s_y'];
data1['user'] = data4['user'];
data1['created'] = data4['created'];
data1['location'] = data4['location'];
data1['tweet'] = data4['tweet'];
data9['g_x'] = data12['g_x'];
data9['g_y'] = data12['g_y'];
data9['name'] = data12['name'];
data9['count'] = data12['count'];
data9['bins'] = data12['bins'];
}
if (f == %s) {
for (var e in data1) delete data1[e];
for (var g in data9) delete data9[g];
data1['s_x'] = data5['s_x'];
data1['s_y'] = data5['s_y'];
data1['user'] = data5['user'];
data1['created'] = data5['created'];
data1['location'] = data5['location'];
data1['tweet'] = data5['tweet'];
data9['g_x'] = data13['g_x'];
data9['g_y'] = data13['g_y'];
data9['name'] = data13['name'];
data9['count'] = data13['count'];
data9['bins'] = data13['bins'];
}
if (f == %s) {
for (var e in data1) delete data1[e];
for (var g in data9) delete data9[g];
data1['s_x'] = data6['s_x'];
data1['s_y'] = data6['s_y'];
data1['user'] = data6['user'];
data1['created'] = data6['created'];
data1['location'] = data6['location'];
data1['tweet'] = data6['tweet'];
data9['g_x'] = data14['g_x'];
data9['g_y'] = data14['g_y'];
data9['name'] = data14['name'];
data9['count'] = data14['count'];
data9['bins'] = data14['bins'];
}
if (f == %s) {
for (var e in data1) delete data1[e];
for (var g in data9) delete data9[g];
data1['s_x'] = data7['s_x'];
data1['s_y'] = data7['s_y'];
data1['user'] = data7['user'];
data1['created'] = data7['created'];
data1['location'] = data7['location'];
data1['tweet'] = data7['tweet'];
data9['g_x'] = data15['g_x'];
data9['g_y'] = data15['g_y'];
data9['name'] = data15['name'];
data9['count'] = data15['count'];
data9['bins'] = data15['bins'];
}
if (f == %s) {
for (var e in data1) delete data1[e];
for (var g in data9) delete data9[g];
data1['s_x'] = data8['s_x'];
data1['s_y'] = data8['s_y'];
data1['user'] = data8['user'];
data1['created'] = data8['created'];
data1['location'] = data8['location'];
data1['tweet'] = data8['tweet'];
data9['g_x'] = data16['g_x'];
data9['g_y'] = data16['g_y'];
data9['name'] = data16['name'];
data9['count'] = data16['count'];
data9['bins'] = data16['bins'];
}
source1.change.emit();
source9.change.emit();
""" % (selection_dates_js[0], selection_dates_js[1], selection_dates_js[2],
selection_dates_js[3], selection_dates_js[4], selection_dates_js[5],
selection_dates_js[6]))
select = Select(title='Choose date from timeline:',
value=selection_dates[0],
options=selection_dates,
sizing_mode="stretch_width")
select.js_on_change('value', callback)
color_bar = ColorBar(color_mapper=mapper,
label_standoff=10,
width=12,
major_label_text_font_size='14px',
major_label_text_font=font,
location=(0, 0))
s_p.add_layout(color_bar, 'right')
# fixed widgets column contains select dropdown menu
dropdown = column(select, sizing_mode="fixed", height=50, width=800)
# placeholder div containers
ph_fig_sep = Div(text="", height=50, width=20)
ph_widget_sep = Div(text="", height=20, width=500)
# create whisker sentiment plots for polarity and subjectivity
# import whisker_plot to avoid import exceptions due to circular
# dependencies
from whisker_plot import whisker_sentiment, whisker_city_count
w_pol = whisker_sentiment(df, 'polarity')
w_sub = whisker_sentiment(df, 'subjectivity')
w_count = whisker_city_count(df, selection_day_range)
# assembling layout together
layout = column(row(ph_fig_sep, ph_fig_sep, dropdown),
row(ph_widget_sep),
row(s_p, ph_fig_sep, g_p),
row(ph_widget_sep),
row(w_pol, ph_fig_sep, w_sub),
row(ph_widget_sep),
row(w_count),
row(ph_widget_sep),
sizing_mode="stretch_both")
# if required plot can be exported as png
#export_png(layout, filename="plot.png")
# calling create_html_template function to assemble bokeh plots into
# custom styled html/css templates
html = create_html_template(layout)
filename = 'index.html'
# generate output file as html
with open((os.path.join(docs_dir, filename)), "w", encoding="utf-8") as f:
f.write(html)
view(filename)
def show(self):
filename = self._generate_output(self._fp)
view(filename)
self._reset()
self._num_plots += 1
def test_view_bad_new():
with pytest.raises(RuntimeError) as e:
bub.view("foo", new="junk")
assert str(e) == "invalid 'new' value passed to view: 'junk', valid values are: 'same', 'window', or 'tab'"
# data, ptid_md = filterData(data, ptid_md, method='pass')
isError, err_html = _errorDisplay(data, ptid_md, measures_md)
if isError is False:
data, ptid_md, measures_md, rowDend, colDend = clusterData(
data,
ptid_md,
measures_md,
metric='euclidean',
method='ward',
standardize=False,
impute=True)
# Creating overall data source
sources = initSources(data,
ptid_md,
measures_md,
raw_data,
transform="b'none'",
params=["0", "2, 2", "1, 1"])
cbDict = initCallbacks(sources)
p = generateLayout(sources, cbDict, rowDend, colDend)
else:
with io.open('MetaVisError.html', mode='w', encoding='utf-8') as g:
g.write(err_html)
view('MetaVisError.html')
print(isError)
<!-- Custom Added Code To Provide External Resources -->
<script src="https://code.jquery.com/jquery-3.4.1.min.js"></script>
<!-- ############################################### -->
{% endblock %}
{% endblock %}
</head>
{% endblock %}
{% block body %}
<body>
{% block inner_body %}
{% block contents %}
{% for doc in docs %}
{{ embed(doc) if doc.elementid }}
{% for root in doc.roots %}
{% block root scoped %}
{{ embed(root) | indent(10) }}
{% endblock %}
{% endfor %}
{% endfor %}
{% endblock %}
{{ plot_script | indent(8) }}
{% endblock %}
</body>
{% endblock %}
</html>
"""
layout = column(p, tbutton)
save(layout, template=external_src_template)
view(output_filename + '.html')
def stop(PORT=FAKE_LISTENER_PORT):
view(f"http://localhost:{PORT}/shutdown")
if "docs" not in globals():
docs = []
page = column()
sourceBuySell: ColumnDataSource = ColumnDataSource({ # ['buyPressure', 'index', 'sellPressure', 'time']
'buyPressure':[],
'sellPressure':[],
'index': [], })
sourceVolume:ColumnDataSource = ColumnDataSource({ # ['index', 'nnBuy', 'nnSell', 'time', 'totalValue']
'index': [],
'nnBuy': [],
'nnSell': [],
'totalValue': [],})
def attachDocToServer(doc: Document):
global page, sourceVolume, sourceBuySell
page, activate, sourceBuySell, sourceVolume = makeMasterPlot()
doc.add_root(column(page))
docs.append(doc)
activate()
if __name__ == "__main__":
s = Server({'/': Application(FunctionHandler(attachDocToServer))},
num_proc=16,
port=BOKEH_PORT,
allow_websocket_origin=["*"])
s.start()
threading_func_wrapper(s.io_loop.start, delay=0.01)
threading_func_wrapper(lambda: view(f"http://localhost:{BOKEH_PORT}"), 0.5)
def test_view_args():
db = bub.DummyWebBrowser
bub.DummyWebBrowser = _RecordingWebBrowser
# test http locations used as-is
bub.view("http://foo", browser="none")
assert _open_args == (('http://foo',), {'autoraise': True, 'new': 0})
# test non-http locations treated as local files
bub.view("/foo/bar", browser="none")
if sys.platform == "win32":
assert _open_args == (('file://' + os.path.splitdrive(os.getcwd())[0] + '\\foo\\bar',), {'autoraise': True, 'new': 0})
else:
assert _open_args == (('file:///foo/bar',), {'autoraise': True, 'new': 0})
# test autoraise passed to open
bub.view("http://foo", browser="none", autoraise=False)
assert _open_args == (('http://foo',), {'autoraise': False, 'new': 0})
# test handling of new values
bub.view("http://foo", browser="none", new="same")
assert _open_args == (('http://foo',), {'autoraise': True, 'new': 0})
bub.view("http://foo", browser="none", new="window")
assert _open_args == (('http://foo',), {'autoraise': True, 'new': 1})
bub.view("http://foo", browser="none", new="tab")
assert _open_args == (('http://foo',), {'autoraise': True, 'new': 2})
bub.DummyWebBrowser = db
def after_write_file(self, args, filename, doc):
if args.show:
from bokeh.util.browser import view
view(filename)
def test_view_args():
db = bub.DummyWebBrowser
bub.DummyWebBrowser = _RecordingWebBrowser
# test http locations used as-is
bub.view("http://foo", browser="none")
assert _open_args == (('http://foo', ), {'autoraise': True, 'new': 0})
# test non-http locations treated as local files
bub.view("/foo/bar", browser="none")
assert _open_args == (('file:///foo/bar', ), {'autoraise': True, 'new': 0})
# test autoraise passed to open
bub.view("http://foo", browser="none", autoraise=False)
assert _open_args == (('http://foo', ), {'autoraise': False, 'new': 0})
# test handling of new values
bub.view("http://foo", browser="none", new="same")
assert _open_args == (('http://foo', ), {'autoraise': True, 'new': 0})
bub.view("http://foo", browser="none", new="window")
assert _open_args == (('http://foo', ), {'autoraise': True, 'new': 1})
bub.view("http://foo", browser="none", new="tab")
assert _open_args == (('http://foo', ), {'autoraise': True, 'new': 2})
bub.DummyWebBrowser = db
def test_view_args() -> None:
db = bub.DummyWebBrowser
bub.DummyWebBrowser = _RecordingWebBrowser
# test http locations used as-is
bub.view("http://foo", browser="none")
assert _open_args == (('http://foo', ), {'autoraise': True, 'new': 0})
# test non-http locations treated as local files
bub.view("/foo/bar", browser="none")
if sys.platform == "win32":
assert _open_args == (('file://' + os.path.splitdrive(os.getcwd())[0] +
'\\foo\\bar', ), {
'autoraise': True,
'new': 0
})
else:
assert _open_args == (('file:///foo/bar', ), {
'autoraise': True,
'new': 0
})
# test autoraise passed to open
bub.view("http://foo", browser="none", autoraise=False)
assert _open_args == (('http://foo', ), {'autoraise': False, 'new': 0})
# test handling of new values
bub.view("http://foo", browser="none", new="same")
assert _open_args == (('http://foo', ), {'autoraise': True, 'new': 0})
bub.view("http://foo", browser="none", new="window")
assert _open_args == (('http://foo', ), {'autoraise': True, 'new': 1})
bub.view("http://foo", browser="none", new="tab")
assert _open_args == (('http://foo', ), {'autoraise': True, 'new': 2})
bub.DummyWebBrowser = db
def write_to_html(plots, type=0, filename='output.html', title='Title'):
'''
Outputs the files into an html file
:param filename:
:param labels:
:param plots:
:return:
'''
# Define our html template for out plots
template = Template('''
<!DOCTYPE html>
<html lang="en">
<head>
<title>{{ title }}</title>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" href="http://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/css/bootstrap.min.css">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.12.0/jquery.min.js"></script>
<script src="http://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js"></script>
{{ js_resources }}
{{ css_resources }}
</head>
<body>
<div class="container-fluid">
<!-- <div class="jumbotron">
<h1>Title</h1>
<p>Description</p>
</div> --!>
<h1>{{ title }}</h1>
<div class="row">
<div class="col-8">
<h3>Manhattan plots</h3>
<p>Group 1</p>
{{ plot_div.p0 }}
<p>Group 2</p>
{{ plot_div.p1 }}
<p class="text-muted"><a href="https://github.com/khramts/assocplots">Generated with ASSOCPLOTS package</a></p>
</div>
<div class="col-4">
<h3>Quantile-Quantile Plot</h3>
{{ plot_div.p2 }}
<p>Selected elements</p>
{{ plot_div.p3 }}
</div>
</div>
</div>
<!-- <footer class="footer">
<div class="container-fluid">
<p class="text-muted"><a href="https://github.com/khramts/assocplots">Generated with ASSOCPLOTS package</a></p>
</div>
</footer> --!>
{{ plot_script }}
</body>
</html>
''')
resources = INLINE
js_resources = resources.render_js()
css_resources = resources.render_css()
script, div = components({'p0': plots[0],'p1': plots[1],'p2': plots[2],'p3': plots[3]})
html = template.render(js_resources=js_resources,
css_resources=css_resources,
plot_script=script,
plot_div=div,
title = title)
with open(filename, 'w') as f:
f.write(html)
view(filename)
<p> This Bokeh Div adds the style classes:<p>
<pre>
.bk.custom {
border-radius: 0.5em;
padding: 1em;
}
.bk.custom-1 {
border: 3px solid #2397D8;
}
</pre>
""")
div1.css_classes = ["custom", "custom-1"]
div2 = Div(text="""
<p> This Bokeh Div adds the style classes:<p>
<pre>
.bk.custom {
border-radius: 0.5em;
padding: 1em;
}
.bk.custom-2 {
border: 3px solid #14999A;
background-color: whitesmoke;
}
</pre>
""")
div2.css_classes = ["custom", "custom-2"]
save(column(p, div1, div2), template=template)
view("css_classes.html")
<p> This Bokeh Div adds the style classes:<p>
<pre>
.bk.custom {
border-radius: 0.5em;
padding: 1em;
}
.bk.custom-1 {
border: 3px solid #2397D8;
}
</pre>
""")
div1.css_classes = ["custom", "custom-1"]
div2 = Div(text="""
<p> This Bokeh Div adds the style classes:<p>
<pre>
.bk.custom {
border-radius: 0.5em;
padding: 1em;
}
.bk.custom-2 {
border: 3px solid #14999A;
background-color: whitesmoke;
}
</pre>
""")
div2.css_classes = ["custom", "custom-2"]
save(column(p, div1, div2), template=template)
view("css_classes.html")
var year = slider.value,
sources = %s,
new_source_data = sources[year].data;
renderer_source.data = new_source_data;
text_source.data = {'year': [String(year)]};
""" % js_source_array
callback = CustomJS(args=sources, code=code)
slider = Slider(start=years[0], end=years[-1], value=1, step=1, title="Year", callback=callback, name='testy')
callback.args["renderer_source"] = renderer_source
callback.args["slider"] = slider
callback.args["text_source"] = text_source
# Stick the plot and the slider together
layout = column(plot, slider)
# Open our custom template
with open('gapminder_template.jinja', 'r') as f:
template = Template(f.read())
# Use inline resources, render the html and open
js_resources = JSResources(mode='inline')
title = "Bokeh - Gapminder Bubble Plot"
html = file_html(layout, resources=(js_resources, None), title=title, template=template)
output_file = 'gapminder.html'
with io.open(output_file, mode='w', encoding='utf-8') as f:
f.write(html)
view(output_file)
def write_to_html(plots, type=0, filename='output.html', title='Title'):
'''
Outputs the files into an html file
:param filename:
:param labels:
:param plots:
:return:
'''
# Define our html template for out plots
template = Template('''
<!DOCTYPE html>
<html lang="en">
<head>
<title>{{ title }}</title>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" href="http://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/css/bootstrap.min.css">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.12.0/jquery.min.js"></script>
<script src="http://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js"></script>
{{ js_resources }}
{{ css_resources }}
</head>
<body>
<div class="container-fluid">
<!-- <div class="jumbotron">
<h1>Title</h1>
<p>Description</p>
</div> --!>
<h1>{{ title }}</h1>
<div class="row">
<div class="col-sm-8">
<h3>Manhattan plots</h3>
<p>Group 1</p>
{{ plot_div.p0 }}
<p>Group 2</p>
{{ plot_div.p1 }}
<p class="text-muted"><a href="https://github.com/khramts/assocplots">Generated with ASSOCPLOTS package</a></p>
</div>
<div class="col-sm-4">
<h3>Quantile-Quantile Plot</h3>
{{ plot_div.p2 }}
<p>Selected elements</p>
{{ plot_div.p3 }}
</div>
</div>
</div>
<!-- <footer class="footer">
<div class="container-fluid">
<p class="text-muted"><a href="https://github.com/khramts/assocplots">Generated with ASSOCPLOTS package</a></p>
</div>
</footer> --!>
{{ plot_script }}
</body>
</html>
''')
resources = INLINE
js_resources = resources.render_js()
css_resources = resources.render_css()
script, div = components({'p0': plots[0],'p1': plots[1],'p2': plots[2],'p3': plots[3]})
html = template.render(js_resources=js_resources,
css_resources=css_resources,
plot_script=script,
plot_div=div,
title = title)
with open(filename, 'w') as f:
f.write(html)
view(filename)
LegendItem(label="CR2", renderers=[cr2, ln2]),
LegendItem(label="CR3", renderers=[cr3]),
]
legend = lambda **kwargs: Legend(
background_fill_alpha=0.7, items=legends(), click_policy="hide", **kwargs)
plot.add_layout(legend(location="center_left", orientation="vertical"))
plot.add_layout(legend(location="center", orientation="vertical"))
plot.add_layout(legend(location="top_center", orientation="horizontal"))
plot.add_layout(legend(location="top_right", orientation="horizontal"))
plot.add_layout(legend(location="bottom_right", orientation="horizontal"))
plot.add_layout(legend(location=(0, 0), orientation="vertical", name="(0, 0)"))
plot.add_layout(
legend(location="center", orientation="horizontal", name="above"), 'above')
plot.add_layout(
legend(location="center", orientation="horizontal", name="below"), 'below')
plot.add_layout(legend(location="center", orientation="vertical", name="left"),
'left')
plot.add_layout(
legend(location="center", orientation="vertical", name="right"), 'right')
doc = Document()
doc.add_root(plot)
if __name__ == "__main__":
filename = "synthetic.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "A synthetic example"))
print("Wrote %s" % filename)
view(filename)
<pre>
.p { width: 33.3%; padding: 50px; }
.p:nth-child(1) { background-color: red; }
.p:nth-child(2) { background-color: green; }
.p:nth-child(3) { background-color: blue; }
</pre>
</p>
</div>
<div class="plots">
<div class="p">{{ embed(roots.p0) }}</div>
<div class="p">{{ embed(roots.p1) }}</div>
<div class="p">{{ embed(roots.p2) }}</div>
</div>
</div>
{% endblock %}
"""
x = [1, 2, 3]
y = [1, 2, 3]
p0 = figure(name="p0", sizing_mode="scale_width")
p0.scatter(x, y, size=20, fill_color="red")
p1 = figure(name="p1", sizing_mode="scale_width")
p1.scatter(x, y, size=20, fill_color="green")
p2 = figure(name="p2", sizing_mode="scale_width")
p2.scatter(x, y, size=20, fill_color="blue")
save([p0, p1, p2], template=template)
view("custom_layout.html")