def create_buttons():
global button, download_button
# Play button
button = Button(label='► Play', button_type="success", width=60)
button.on_click(animate)
play_widget = widgetbox(button, width=80, height=50, sizing_mode='fixed')
spacer = Spacer(width=300, height=50)
# Download button
download_button1 = Button(label="Download Minimal HTML",
button_type="success",
width=150)
download_button2 = Button(label="Download With Structures",
button_type="success",
width=150)
download_button1.js_on_event(ButtonClick, download_simple())
download_button2.js_on_event(ButtonClick, download_extended())
download_widget1 = widgetbox(download_button1,
width=200,
height=50,
sizing_mode='fixed')
download_widget2 = widgetbox(download_button2,
width=200,
height=50,
sizing_mode='fixed')
dpanel = Row(Spacer(width=170),
download_widget1,
Spacer(width=10),
download_widget2,
width=600,
sizing_mode='fixed')
return play_widget, dpanel
def _get_model(self, doc, root=None, parent=None, comm=None):
if root is None:
return self._get_root(doc, comm)
if self.object is None:
model = BkSpacer()
else:
model = self.object
properties = {}
for p, value in self.param.values().items():
if (p not in Layoutable.param or p == 'name'
or value is self.param[p].default):
continue
properties[p] = value
model.update(**properties)
if comm:
self._wrap_bokeh_callbacks(root, model, doc, comm)
ref = root.ref['id']
for js in model.select({'type': CustomJS}):
js.code = js.code.replace(model.ref['id'], ref)
if model._document and doc is not model._document:
remove_root(model, doc)
self._models[ref] = (model, parent)
if self.theme:
doc.theme = self.theme
return model
def hdivider(line_thickness=2,
border_thickness=6,
top_border_thickness=6,
bottom_border_thickness=6,
line_color="white",
border_color=BASE_BACKGROUND_COLOR):
"""
Generates a horizontal divider (spacer with a line)
:param line_thickness: Thickness of the line
:param border_thickness: Thickness of the border, total thickness = `border_thickness * 2 + line_thickness`,
overrides top and bottom border thickness
:param top_border_thickness: Thickness of the top border
:param bottom_border_thickness: Thickness of the bottom border
:param line_color: Line color
:param border_color: Border color
:return: The layout
"""
if border_thickness != 6:
top = border_thickness
bottom = border_thickness
else:
top = top_border_thickness
bottom = bottom_border_thickness
divider_top = Spacer(height=top, background=border_color)
divider_bottom = Spacer(height=bottom, background=border_color)
divider = column([
divider_top,
Spacer(height=line_thickness, background=line_color), divider_bottom
],
sizing_mode="stretch_width")
return divider
def buildUnaggFigDict(x):
toRet = {}
for i in range(1,11):
toRet[i] = {'plot_width': i*x, 'plot_height': i*x,
'tools': 'hover', 'x_axis_location': 'above',
'toolbar_location': None}
toRet['MidSpacer'] = Spacer(**{'width':6*x, 'height':6*x})
toRet['BotSpacer'] = Spacer(**{'width':2*x, 'height':2*x})
return toRet
def compare_tab():
panel_title = Div(text="[Corridor Comparison]", css_classes = ["panel-title","text-center"])
panel_text = Div(text="""Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum has been the industry's standard dummy text ever since the 1500s,
when an unknown printer took a galley of type and scrambled it to make a type
specimen book.""", css_classes = ["panel-content"])
#Date Range
date_range = Div(text="Data References:<br>MMDDYYYY - MMDDYYYY",
css_classes = ["panel-content","text-center"])
#Panel Buttons
year_text = Div(text="<b>Year:", height=10)
year_v1 = RangeSlider(start = 2015, end= 2017,step=1, value=(2015, 2017), height=25,
bar_color="black",title = "View 1")
year_v2 = RangeSlider(start = 2015, end= 2017,step=1, value=(2015, 2017), height=25,
bar_color="black",title = "View 2")
season_text = Div(text="<b>Season</b><br> (1=Winter, 2=Fall, 3=Spring, 4=Summer):", height=25)
season_v1 = RangeSlider(start = 1, end= 4,step=1, value=(1, 2), height=25,
bar_color="black",title = "View 1")
season_v2 = RangeSlider(start = 1, end= 4,step=1, value=(1, 2), height=25,
bar_color="black",title = "View 2")
month_text = Div(text="<b>Month:", height=10)
month_v1 = RangeSlider(start = 1, end= 12,step=1, value=(1, 2), height=25,
bar_color="black",title = "View 1")
month_v2 = RangeSlider(start = 1, end= 12,step=1, value=(1, 2), height=25,
bar_color="black",title = "View 2")
week_text = Div(text="<b>Day of Week:", height=10)
week_v1 = RangeSlider(start = 1, end= 5,step=1, value=(1, 5), height=25,
bar_color="black",title = "View 1")
week_v2 = RangeSlider(start = 1, end= 5,step=1, value=(1, 5), height=25,
bar_color="black",title = "View 2")
time_of_day_text = Div(text="<b>Time of Day:", height=10)
time_of_day_v1 = RangeSlider(start = 1, end= 24,step=1, value=(1, 7),
bar_color="black", height=25)
time_of_day_v2 = RangeSlider(start = 1, end= 24,step=1, value=(1, 7),
bar_color="black", height=25)
l1 = Div(text="test", css_classes = ["text-center"])
return row(column(panel_title, panel_text, date_range,
year_text, year_v1, year_v2, Spacer(height=25),
season_text, season_v1, season_v2, Spacer(height=25),
month_text, month_v1, month_v2, Spacer(height=25),
week_text, week_v1, week_v2, Spacer(height=25),
time_of_day_text, time_of_day_v1, time_of_day_v2,
height = 1000, css_classes = ["panel","col-lg-4"]),
column(l1,css_classes = ["container-fluid","col-lg-8"]),
css_classes = ["container-fluid","col-lg-12"])
def abm_background():
b_title = Div(
text="""<h1>What is an Activity Based Model (ABM)?</h1><br>""",
width=column_width)
background = Div(
text=
"""<ul><li><h3>Travel demand model that simulates individual and household transportation decisions</h3></li><br>
<li><h3>Generates activities, identifies destinations for activities, determines mode of travel, and assigns routes on our network</h3></li><br>
<li><h3>Considers personal and household attributes to predict:</h3></li>
<ul><li>Types of activities a traveler participates in</li>
<li>The individual and/or household members participating in the activity</li>
<li>Where to participate in the activity</li>
<li>How activities are scheduled/prioritized</li>
<li>Time available to participate in those activities</li>
<li>Mode of travel reach each activity</li>
</ul><br>
<li><h3>Produces a behaviorally realistic representation of travel compared to the trip-based model</h3></li>
</ul>
""",
width=int(column_width * .4),
style={'font-size': '150%'})
model_tbl = pd.DataFrame({
'Travel Questions': [
'What activities do people want to participate in?',
'Where are these activities?', 'When are these activities?',
'What travel mode is used?', 'What route is used?'
],
'Trip-Based Model': [
'Trip generation', 'Trip distribution', 'None', 'Trip mode choice',
'Network assignment'
],
'Activity-Based Model': [
'Activity generation and scheduling',
'Tour and trip destination choice', 'Tour and trip time of day',
'Tour and trip mode choice', 'Network assignment'
]
})
div_tbl = Div(text=model_tbl.to_html(
index=False,
classes=["table-bordered", "table-hover"],
),
width=int(column_width * .6),
height=500,
style={'font-size': '120%'})
return row(
Spacer(width=margin),
column(
Spacer(height=25), b_title,
row(background, Spacer(width=int(column_width * .10)),
column(Spacer(height=80), div_tbl))))
def add_rank_table(self):
columns = [
TableColumn(field="tool", title="Tool"),
TableColumn(field="score",
title="Weighted Score",
formatter=NumberFormatter(format="0.00")),
TableColumn(field="rank", title="Rank")
]
self.data_table = DataTable(columns=columns,
source=self.source,
reorderable=True)
buttons = zip(
[self.ranking[k][0] for k in self.chosen_criteria],
[self.ranking[k][1] for k in self.chosen_criteria],
[self.weight_sliders[k] for k in self.weight_sliders.keys()])
self.app_layout.children.pop(1)
b_layout = [[t[0], t[1], t[2]] for t in buttons]
b_layout.append([self.rank_submit, self.b])
b_layout.append(widgetbox(self.data_table))
b_layout.append([self.clear_button])
b_layout.insert(0, [Spacer(width=300), self.swing_table])
self.app_layout.children.append(layout(b_layout))
def _addtodoc(self, ctrl, doc, *_): # pylint: disable=unused-argument
self.__src = [
ColumnDataSource(data=i) for i in self.__data(None, None, None)
]
label = (self._theme.ylabel if self._theme.dataformat != "norm" else
self._theme.ylabelnormalized)
self.__fig = fig = self.figure(y_range=Range1d,
x_range=Range1d,
y_axis_label=label,
name='Ramp:Cycles')
for i, j in zip(("beadarea", "beadline"), self.__src):
self.addtofig(fig, i, x='zmag', y='zbead', source=j)
for i, j in zip(("consensusarea", "consensusline", "beadcycles"),
self.__src):
self.addtofig(fig, i, x='zmag', y='z', source=j)
self.addtofig(fig, "frames", x='zmag', y='z', source=self.__src[-1])
self.linkmodeltoaxes(fig)
left = self.__widgets.create(self, ctrl, fig, self._theme.widgetwidth)
out = self._keyedlayout(ctrl, fig)
out.width = fig.plot_width
out.height = fig.plot_height
return stretchout(
layouts.row([left, Spacer(width=20, height=left.height), out],
width=left.width + out.width + 20,
height=max(left.height, out.height),
**self.defaultsizingmode()))
def days():
for i in Calendar().iterweekdays():
yield Div(text=f'<h2>{day_name[i]}</h2>')
day = month_start - dt.timedelta(days=month_start.weekday())
while day.replace(day=1) <= month_start:
for weekday in range(7):
if day.month == month_start.month:
contents = [Div(text=f'<h1>{day.strftime("%d")}</h1>')]
for a in s.query(ActivityJournal). \
filter(ActivityJournal.start >= local_date_to_time(day),
ActivityJournal.start < local_date_to_time(day + dt.timedelta(days=1))).all():
df = Statistics(s, activity_journal=a). \
by_name(ActivityReader, N.SPHERICAL_MERCATOR_X, N.SPHERICAL_MERCATOR_Y).df
contents.append(
map_thumbnail(map_size, map_size, df, title=False))
df = Statistics(s, activity_journal=a). \
by_name(ActivityCalculator, N.ACTIVE_DISTANCE, N.ACTIVE_TIME).df
contents.append(
Div(text=
f'{format_km(df[N.ACTIVE_DISTANCE][0])} {format_seconds(df[N.ACTIVE_TIME][0])}'
))
else:
contents = [Spacer()]
yield column(contents)
day += dt.timedelta(days=1)
def __do_layout(self):
# TODO: Generalize for 1 or 2 groups
self.layout = column(row(self.select_y, self.select_linac[1], self.select_linac[2], self.avg_len_input,
self.percentile_input, self.bins_input),
row(self.select_energies[1], self.select_energies[2]),
row(self.start_date_picker, self.end_date_picker),
row(Div(text='Gamma Criteria: '), self.checkbox_button_group),
self.div_summary[1],
self.div_summary[2],
row(Spacer(width=10), self.fig),
Spacer(height=50),
row(Spacer(width=10), self.histogram),
Spacer(height=50),
row(Spacer(width=10), self.ichart),
row(self.div_center_line[1], self.div_ucl[1], self.div_lcl[1]),
row(self.div_center_line[2], self.div_ucl[2], self.div_lcl[2]))
def overview_tab():
#image linke
#image = load_image(abm_flow,'CT-RAMP Structure and Sub-Models')
flow_image = Div(
text="<img src='abm_pres/static/images/abm_flow_chart.png'>")
overview_text = Div(text="""<h1>Activity Based Model Overview</h1>""",
width=column_width)
ctramp_text = Div(
text="""<h3>Coordinated Travel - Regional Activity Modeling Platform
(CT-RAMP) </h3><p>ABM model implements the CT-RAMP design and software platform.
Features microsimulation of travel decisions for individual households and persons
within a household as well as intra-household interactions
across a range of activity and travel dimensions.</p><br>
<ol><li><b>Population synthesis</b> creates and distributes households and persons
for use in the ABM</li><br>
<li><b>Long-Term Location Choice</b> - Models location of usual (mandatory) destinations</li><br>
<li><b>Mobility</b> - Models household attributes like free parking eligibility, car ownership,
transit pass, or toll transponder</li><br>
<li><b>Coordinated Daily Activity-Travel Pattern</b> - Generates and schedules mandatory
and non-mandatory activities for each household member.</li><br>
<li><b>Tour</b> - Daily activities are organized into tours, tour mode, number,
and location of stops are determined.</li><br>
<li><b>Trips</b> - Mode, parking, and location of trips making up tour is determined.</li><br>
<li><b>Network Simulation</b> - List of trips for each individual and/or travel party
is generated and trips routes are assigned on the modeling network for auto and transit.</li>
</ol>""",
width=int(column_width * .5),
style={'font-size': '150%'})
extra = Div(
text="""<hr><ul><li>Tour: Chain of trips that start and end at home</li>
<li>Person Types: 8 Person Types (1=Full time worker, 2=Part time worker, 3=University student,
4=Adult non-worker under 65, 5=retiree, 6=driving age school child, 7=pre-driving age school child, 8=preschool child)</li>
<li>Activities: 10 travel purposes (work, university, school, escorting,
shopping, other maintenance, eating out, visiting relatives and friends,
other discretionary, and atwork)</li>
<li>Modes = 21 modes at both tour and trip level</li>
</ul>""",
width=int(column_width * .5),
css_classes=['small'])
return (row(Spacer(width=margin), (column(
Spacer(width=margin, height=25), overview_text,
row(column(ctramp_text, extra), Spacer(width=100),
column(flow_image))))))
def _figure_rows(
model_evaluations: Sequence[Evaluation],
include_spacer: Optional[bool],
) -> Sequence[Row]:
# TODO check figure consistency
rows = []
for i_figure, _ in enumerate(model_evaluations[0].lazy_figures):
row_of_figures = [
evaluation.lazy_figures[i_figure]()
for i_model, evaluation in enumerate(model_evaluations)
]
if len(model_evaluations) == 1 and include_spacer in (None, True):
row_of_figures = row_of_figures + [Spacer()]
elif include_spacer is True:
row_of_figures = [Spacer()] + row_of_figures
rows.append(
bokeh.layouts.row(row_of_figures, sizing_mode="scale_width"))
return rows
def __init__(self, custom_title, data_tables):
self.layout = column(
Div(text="<b>DVH Analytics v%s</b>" % options.VERSION),
row(custom_title['1']['planning'], Spacer(width=50),
custom_title['2']['planning']),
Div(text="<b>Rxs</b>", width=1000), data_tables.rxs,
Div(text="<b>Plans</b>", width=1200), data_tables.plans,
Div(text="<b>Beams</b>", width=1500), data_tables.beams,
Div(text="<b>Beams Continued</b>", width=1500), data_tables.beams2)
def vdivider(line_thickness=1,
border_thickness=3,
line_color="white",
border_color=BASE_BACKGROUND_COLOR):
"""
Generates a vertical divider (spacer with a line)
:param line_thickness: Thickness of the line
:param border_thickness: Thickness of the border, total thickness = `border_thickness * 2 + line_thickness`
:param line_color: Line color
:param border_color: Border color
:return: The layout
"""
divider = Spacer(width=border_thickness, background=border_color)
divider = row([
divider,
Spacer(width=line_thickness, background=line_color), divider
],
sizing_mode="stretch_height")
return divider
def __do_layout(self):
self.layout = column(self.button_refresh_plans,
row(self.select_plan, self.select_protocol, self.select_fx),
row(self.button_calculate, self.button_delete_roi),
row(self.select_roi_template, self.select_roi),
self.max_dose_volume,
self.data_table,
row(self.plot, Spacer(width=10), column(self.button_calculate_dvhs,
self.plot_rois)))
def timings_plots(self):
rows = []
for r in range(self.grid_dims[0]):
for c in range(self.grid_dims[1] // 2):
rows.append(
row(widgetbox(*self.grid_controls[r, 2 * c]),
self.figures[r, 2 * c], self.figures[r, 2 * c + 1]))
rows.append(Spacer(height=10))
l = column(*rows)
curdoc().add_root(l)
curdoc().title = "Rippled eBPF Probes"
def __init__(self, sources, time_series, correlation, regression,
custom_title, data_tables):
self.sources = sources
self.time_series = time_series
self.correlation = correlation
self.regression = regression
self.eud_a_input = TextInput(value='', title='EUD a-value:', width=150)
self.gamma_50_input = TextInput(value='',
title=u"\u03b3_50:",
width=150)
self.td_tcd_input = TextInput(value='',
title='TD_50 or TCD_50:',
width=150)
self.apply_button = Button(label="Apply parameters",
button_type="primary",
width=150)
self.apply_filter = CheckboxButtonGroup(
labels=["Group 1", "Group 2", "Selected"], active=[0], width=300)
self.apply_button.on_click(self.apply_rad_bio_parameters)
self.layout = column(
Div(text="<b>DVH Analytics v%s</b>" % options.VERSION),
row(custom_title['1']['rad_bio'], Spacer(width=50),
custom_title['2']['rad_bio']),
Div(text="<b>Published EUD Parameters from Emami"
" et. al. for 1.8-2.0Gy fractions</b> (Click to apply)",
width=600), data_tables.emami,
Div(text="<b>Applied Parameters:</b>", width=150),
row(self.eud_a_input, Spacer(width=50), self.gamma_50_input,
Spacer(width=50), self.td_tcd_input, Spacer(width=50),
self.apply_filter, Spacer(width=50), self.apply_button),
Div(text="<b>EUD Calculations for Query</b>", width=500),
data_tables.rad_bio, Spacer(width=1000, height=100))
def _figure_rows(model_evaluations: Sequence[Evaluation],
include_spacer: bool) -> Sequence[Row]:
# TODO check figure consistency
rows = []
for i_figure, _ in enumerate(model_evaluations[0].lazy_figures):
row_of_figures = [
evaluation.lazy_figures[i_figure]()
for i_model, evaluation in enumerate(model_evaluations)
]
if include_spacer:
row_of_figures = [Spacer()] + row_of_figures
rows.append(
bokeh.layouts.row(row_of_figures, sizing_mode="scale_width"))
return rows
def test_tab():
left_col = Div(text="""<h4>place holder</h4>""")
right_col = Div(text="""<h4>figures</h4>""")
h_1 = Div(text = """<h1><center>Intro Text</center></h1>""")
l_1 = layout(children=[row(Spacer(height = 50)),
row(column(left_col, width= 200,css_classes = ["caption", "text-center"]),
column(intro),
column(right_col, width= 200, css_classes = ["caption", "text-center"]),
css_classes = ["container-fluid"], width = 2000)])
tab_1 = Panel(child=l_1, title = '# Introduction')
return tab_1
def add_weight_changes(self):
self.weight_calc()
buttons = zip(
[self.ranking[k][0] for k in self.chosen_criteria],
[self.ranking[k][1] for k in self.chosen_criteria],
[self.weight_sliders[k] for k in self.weight_sliders.keys()])
b_layout = [[t[0], t[1], t[2]] for t in buttons]
b_layout.append([self.rank_submit, self.b])
b_layout.append(self.clear_button)
b_layout.insert(0, [Spacer(width=300), self.swing_table])
self.app_layout.children.pop(1)
self.app_layout.children.append(layout(b_layout))
def _create_content(self):
title_area = []
title = Paragraph(text='Strategy Metadata Overview',
css_classes=['panel-title'])
title_area.append(row([title], width_policy='min'))
if self._client:
btn_refresh = Button(label='Refresh', width_policy='min')
btn_refresh.on_click(self._on_update_metadata_info)
title_area.append(Spacer())
title_area.append(row([btn_refresh], width_policy='min'))
# set content in self
return layout(
[
title_area,
# initialize with info
[self._get_metadata_info()]
],
sizing_mode='stretch_width')
def __init__(self, controller):
super(BokehView, self).__init__(controller)
# define elements
self.gen_data_button = Button(label="Generate Data", button_type="success")
self.kernel_select = Select(title='Kernel',
options=KERNELS,
value=INIT_ACTIVE_KERNEL)
self.reweighting_select = Select(title='Reweighting',
options=REWEIGHTINGS,
value=INIT_ACTIVE_REWEIGHTING)
self.classify_button = Button(label="Classify", button_type="success")
self.train_table = BokehTable([[0.4, 0.1], [0.4, 0.1]])
self.test_table = BokehTable([[0.4, 0.4], [0.1, 0.1]])
self.train_fig = figure(plot_height=400, plot_width=400,
title=template_title('Train', '-'), tools='',
x_range=[0, 100], y_range=[-50, 5])
self.test_fig = figure(plot_height=400, plot_width=400,
title=template_title('test', '-'), tools='',
x_range=[0, 100], y_range=[-50, 50])
# wire callbacks
self.gen_data_button.on_click(controller.generate_data)
self._kernel = INIT_ACTIVE_KERNEL
self.kernel_select.on_change('value', self._update_kernel)
self._reweighting = INIT_ACTIVE_REWEIGHTING
self.reweighting_select.on_change('value', self._update_reweighting)
self.classify_button.on_click(self._classify_callback)
desc = Div(text=open(join(dirname(__file__), "description.html")).read(), width=1024)
# set layout
inputs = widgetbox(self.kernel_select,
self.reweighting_select,
self.gen_data_button,
self.classify_button)
layout = column(row(desc),
row(column(row(inputs)), column(row(self.train_fig, self.test_fig),
row(self.train_table.get_layout_element(),
Spacer(width=100, height=100),
self.test_table.get_layout_element()))))
self.layout = layout
def ranking_label_callback(self, attr, old, new, k):
self.ranking[k][1].label = new
if self.ranking[k][1].button_type == "danger":
print("test")
self.ranking[k][1].button_type = "primary"
try:
self.ranking[k].pop(-1)
self.app_layout.children.pop(1)
self.app_layout.children.append(
layout([[Spacer(width=300), self.swing_table],
*[self.ranking[k] for k in self.ranking.keys()],
[self.rank_submit], [self.clear_button]]))
except IndexError:
pass
def choose_criteria_callback(self):
self.chosen_criteria = []
self.chosen_criteria = self.criteria_selection.value
if len(self.chosen_criteria) > 0:
self.ranking = OrderedDict()
self.rank_criteria()
self.swing_table = swing_table.create_swing_table(
self.chosen_criteria)
try:
self.app_layout.children.pop(1)
except IndexError:
pass
self.app_layout.children.append(
layout([[Spacer(width=300), self.swing_table],
*[self.ranking[k] for k in self.ranking.keys()],
[self.rank_submit], [self.clear_button]]))
#show(row(scatter1, pv))
# create bottom horizontal histogram
billed = md_data[
'Billed Units'].values # convert DataFrame column to numpy array
hhist, hedges = np.histogram(billed, bins=15)
hzeros = np.zeros(len(hedges) - 1)
hmax = max(hhist) * 1.1
ph = figure(toolbar_location=None,
plot_width=scatter1.plot_width,
plot_height=200,
x_range=scatter1.x_range,
y_range=(0, hmax),
min_border=10,
min_border_left=50,
y_axis_location="right")
ph.yaxis[0].formatter = NumeralTickFormatter(format='$0')
ph.quad(bottom=0,
left=hedges[:-1],
right=hedges[1:],
top=hhist,
color="blue",
line_color=None)
# lay out the plots as we would like
layout = column(row(scatter1, pv), row(ph, Spacer(width=200, height=200)))
#curdoc().add_root(layout)
show(layout)
week_slider.on_change('value', week_slider_handler)
team1_dd.on_change('value', team1_select_handler)
team2_dd.on_change('value', team2_select_handler)
comp_button.on_click(helper_handler)
year_input.on_change('value', season_handler)
# arrange layout
tab1 = Panel(child=plot1_wrap, title='Scores')
tab2 = Panel(child=plot2_wrap, title='Expected Wins')
tab3 = Panel(child=table_wrap, title='Summary')
figures = Tabs(tabs=[tab1, tab2, tab3], width=500)
compare_widgets = column(team1_dd, team2_dd, comp_button)
wid_spac1 = Spacer(height=30)
wid_spac2 = Spacer(height=30)
wid_spac3 = Spacer(height=30)
lg_id_message.text = '<b><p style="color: green;">League accessed successfully.</p></b>'
all_widgets = column(lg_id_input, lg_id_message, wid_spac1, compare_widgets,
wid_spac2, week_slider, wid_spac3, year_input)
page_title = Div(
text=
"""<strong><h1 style="font-size: 2.5em;">ESPN Fantasy Football League Explorer</h1></strong>""",
width=700,
height=50)
main_area = row(all_widgets, figures)
fill_alpha=PLOT10_ALPHA,
fill_color='red')
quadrant2 = BoxAnnotation(left=0,
right=1,
bottom=IC_LIM,
fill_alpha=PLOT10_ALPHA,
fill_color='orange')
plot10.add_layout(quadrant1)
plot10.add_layout(quadrant2)
plot10.add_layout(quadrant3)
plot10.add_layout(quadrant4)
# Set up layouts and add to document
notespacer = Spacer(width=TEXT_WIDTH,
height=10,
width_policy='auto',
height_policy='fixed')
# simplified set
inputs = column(intro, population, iinfections, period, latent, h1, p1, drate,
im, button2, button3, button, summary, stats, notespacer,
notes)
curdoc().title = PAGE_TITLE
if ENABLE_RISK:
last_plot = plot10
else:
last_plot = plot9
# useful for mobile scrolling on the left side
def KPI_projects_tab(panel_title, DAYS_TO_LOAD=90):
timeline_source = ColumnDataSource(data=dict(
Item=[], Start=[], End=[], Color=[], start=[], end=[], ID=[], ID1=[]))
class Thistab(KPI):
def __init__(self, table, cols=[]):
KPI.__init__(self, table, name='project', cols=cols)
self.table = table
self.df = None
self.df_pop = None
self.checkboxgroup = {}
self.period_to_date_cards = {}
self.ptd_startdate = datetime(datetime.today().year, 1, 1, 0, 0, 0)
self.timestamp_col = 'project_startdate_actual'
self.pym = PythonMongo('aion')
self.groupby_dict = {
'project': 'sum',
'project_duration': 'sum',
'project_start_delay': 'mean',
'project_end_delay': ' mean',
'milestone': 'sum',
'milestone_duration': 'sum',
'milestone_start_delay': 'mean',
'milestone_end_delay': ' mean',
'task': 'sum',
'task_duration': 'sum',
'task_start_delay': 'mean',
'task_end_delay': ' mean',
}
self.menus = {
'status': ['all', 'open', 'closed'],
'type': [
'all', 'research', 'reconciliation', 'audit', 'innovation',
'construction', 'manufacturing', 'conference'
],
'gender': ['all', 'male', 'female'],
'variables':
list(self.groupby_dict.keys()),
'history_periods':
['1', '2', '3', '4', '5', '6', '7', '8', '9', '10'],
}
self.status = 'all'
self.pm_gender = 'all'
self.m_gender = 'all'
self.t_gender = 'all'
self.type = 'all'
self.variables = sorted(list(self.groupby_dict.keys()))
self.variable = self.variables[0]
self.groupby_var = 'project'
self.chord_data = {
'rename': {
'project_owner': 'source',
'milestone_owner': 'target',
'remuneration': 'value'
},
'percentile_threshold': .75,
}
self.percentile_threshold = 10
# ------- DIVS setup begin
self.page_width = 1200
txt = """<hr/><div style="text-align:center;width:{}px;height:{}px;
position:relative;background:black;margin-bottom:200px">
<h1 style="color:#fff;margin-bottom:300px">{}</h1>
</div>""".format(self.page_width, 50,
'Welcome')
self.notification_div = {
'top': Div(text=txt, width=self.page_width, height=20),
'bottom': Div(text=txt, width=self.page_width, height=10),
}
self.section_divider = '-----------------------------------'
self.section_headers = {
'cards':
self.section_header_div(text='Period to date:{}'.format(
self.section_divider),
width=1000,
html_header='h2',
margin_top=50,
margin_bottom=5),
'pop':
self.section_header_div(text='Period over period:{}'.format(
self.section_divider),
width=600,
html_header='h2',
margin_top=5,
margin_bottom=-155),
'chord':
self.section_header_div(text='Relationships:{}'.format(
self.section_divider),
width=600,
html_header='h2',
margin_top=5,
margin_bottom=-155),
'timeline':
self.section_header_div(text='Project timeline:{}'.format(
self.section_divider),
width=600,
html_header='h2',
margin_top=5,
margin_bottom=-155),
}
self.KPI_card_div = self.initialize_cards(self.page_width,
height=350)
start = datetime(2014, 1, 1, 0, 0, 0)
end = datetime(2019, 5, 15, 0, 0, 0)
self.tools = [
BoxZoomTool(),
ResetTool(),
PanTool(),
SaveTool(),
WheelZoomTool()
]
self.timeline_vars = {
'projects':
'',
'project':
'',
'types': ['all', 'milestone', 'task', 'project'],
'type':
'all',
'DF':
None,
'G':
figure(title=None,
x_axis_type='datetime',
width=1200,
height=900,
y_range=[],
x_range=Range1d(start, end),
toolbar_location=None),
'toolbar_box':
ToolbarBox()
}
# ----- UPDATED DIVS END
# ---------------------- DIVS ----------------------------
def section_header_div(self,
text,
html_header='h2',
width=600,
margin_top=150,
margin_bottom=-150):
text = """<div style="margin-top:{}px;margin-bottom:-{}px;"><{} style="color:#4221cc;">{}</{}></div>"""\
.format(margin_top,margin_bottom,html_header, text, html_header)
return Div(text=text, width=width, height=15)
def information_div(self, width=400, height=300):
txt = """
<div {}>
<h4 {}>How to interpret sentiment score</h4>
<ul style='margin-top:-10px;'>
<li>
</li>
<li>
</li>
<li>
</li>
<li>
</li>
</ul>
</div>
""".format(self.div_style, self.header_style)
div = Div(text=txt, width=width, height=height)
return div
def initialize_cards(self, width, height=250):
try:
txt = ''
for period in ['year', 'quarter', 'month', 'week']:
design = random.choice(list(KPI_card_css.keys()))
txt += self.card(title='', data='', card_design=design)
text = """<div style="margin-top:100px;display:flex; flex-direction:row;">
{}
</div>""".format(txt)
div = Div(text=text, width=width, height=height)
return div
except Exception:
logger.error('initialize cards', exc_info=True)
def load_df(self, req_startdate, req_enddate, table, cols,
timestamp_col):
try:
# get min and max of loaded df
if self.df is not None:
loaded_min = self.df[timestamp_col].min()
loaded_max = self.df[timestamp_col].max()
if loaded_min <= req_startdate and loaded_max >= req_enddate:
df = self.df[(self.df[timestamp_col] >= req_startdate)
& (self.df[timestamp_col] <= req_enddate)]
return df
return self.pym.load_df(req_startdate,
req_enddate,
table=table,
cols=cols,
timestamp_col=timestamp_col)
except Exception:
logger.error('load_df', exc_info=True)
def filter_df(self, df1):
if self.status != 'all':
df1 = df1[df1.status == self.status]
if self.pm_gender != 'all':
df1 = df1[df1.project_owner_gender == self.pm_gender]
if self.m_gender != 'all':
df1 = df1[df1.milestone_owner_gender == self.m_gender]
if self.t_gender != 'all':
df1 = df1[df1.task_owner_gender == self.t_gender]
if self.type != 'all':
df1 = df1[df1.type == self.type]
return df1
def period_to_date(self,
df,
timestamp=None,
timestamp_filter_col=None,
cols=[],
period='week'):
try:
if timestamp is None:
timestamp = datetime.now()
timestamp = datetime(timestamp.year, timestamp.month,
timestamp.day, timestamp.hour, 0, 0)
start = self.first_date_in_period(timestamp, period)
# filter
df[timestamp_filter_col] = pd.to_datetime(
df[timestamp_filter_col], format=self.DATEFORMAT_PTD)
#logger.warning('df:%s', df[self.timestamp_col])
df = df[(df[timestamp_filter_col] >= start)
& (df[timestamp_filter_col] <= timestamp)]
if len(cols) > 0:
df = df[cols]
return df
except Exception:
logger.error('period to date', exc_info=True)
def period_over_period(self,
df,
start_date,
end_date,
period,
history_periods=2,
timestamp_col='timestamp_of_first_event'):
try:
# filter cols if necessary
string = '0 {}(s) prev(current)'.format(period)
# filter out the dates greater than today
df_current = df.copy()
df_current = self.filter_df(df_current)
logger.warning('df current:%s', df_current.head(10))
df_current['period'] = string
# label the days being compared with the same label
if len(df_current) > 0:
df_current = self.label_dates_pop(df_current, period,
timestamp_col)
cols = [self.variable, 'period', 'dayset']
if 'project' in self.variable:
if self.variable != 'project':
df_current = df_current[[
self.variable, 'period', 'dayset', 'project'
]]
elif 'milestone' in self.variable:
if self.variable != 'milestone':
df_current = df_current[[
self.variable, 'period', 'dayset', 'milestone',
'project'
]]
elif 'task' in self.variable:
if self.variable != 'task':
df_current = df_current[[
self.variable, 'period', 'dayset', 'task',
'milestone', 'project'
]]
# zero out time information
start = datetime(start_date.year, start_date.month,
start_date.day, 0, 0, 0)
end = datetime(end_date.year, end_date.month, end_date.day, 0,
0, 0)
cols = list(df.columns)
counter = 1
if isinstance(history_periods, str):
history_periods = int(history_periods)
# make dataframes for request no. of periods
start, end = self.shift_period_range(period, start, end)
while counter < history_periods and start >= self.initial_date:
# load data
df_temp = self.load_df(start,
end,
table=self.table,
cols=[],
timestamp_col=timestamp_col)
df_temp = self.filter_df(df_temp)
if df_temp is not None:
if len(df_temp) > 1:
df_temp[timestamp_col] = pd.to_datetime(
df_temp[timestamp_col])
string = '{} {}(s) prev'.format(counter, period)
# label period
df_temp['period'] = string
# relabel days to get matching day of week,doy, dom, for different periods
df_temp = self.label_dates_pop(
df_temp, period, timestamp_col)
df_temp = df_temp[cols]
# logger.warning('df temp loaded for %s previous: %s',counter,len(df_temp))
df_current = pd.concat([df_current, df_temp])
del df_temp
gc.collect()
# shift the loading window
counter += 1
start, end = self.shift_period_range(period, start, end)
return df_current
except Exception:
logger.error('period over period', exc_info=True)
# label dates for period over period (pop)
def pop_include_zeros(self, df_period, plotcols, period):
try:
# check for no data on original dates
tmp_title = '0 {}(s) prev(current)'.format(period)
if tmp_title not in plotcols:
df_period[tmp_title] = [0] * len(df_period)
plotcols.append(tmp_title)
logger.warning('line 218 cols to plot:%s', plotcols)
# do other periods
tmp = plotcols[0]
txt = tmp[1:]
if isinstance(self.pop_history_periods, str):
self.pop_history_periods = int(self.pop_history_periods)
for i in range(1, self.pop_history_periods):
tmp_txt = str(i) + txt
if tmp_txt not in plotcols:
df_period[tmp_txt] = [0] * len(df_period)
plotcols.append(tmp_txt)
clean_plotcols = []
for idx, col in enumerate(plotcols):
if 'prev' in col or 'curr' in col:
clean_plotcols.append(col)
logger.warning(
'LINE 340 plotcols at end of pop include zeros:%s',
clean_plotcols)
return df_period, sorted(clean_plotcols)
except Exception:
logger.error('pop include zeros', exc_info=True)
def label_dates_pop(self, df, period, timestamp_col):
#df[timestamp_col] = pd.to_datetime(df[timestamp_col])
def label_qtr_pop(y):
try:
curr_quarter = int((y.month - 1) / 3 + 1)
start = datetime(y.year, 3 * curr_quarter - 2, 1)
return abs((start - y).days)
except Exception:
logger.error('df label quarter', exc_info=True)
try:
logger.warning('df columns:%s', list(df.columns))
if period == 'week':
df['dayset'] = df[timestamp_col].dt.dayofweek
elif period == 'month':
df['dayset'] = df[timestamp_col].dt.day
elif period == 'year':
#logger.warning('LINE 218:%s', df.head(5))
df['dayset'] = df[timestamp_col].dt.dayofyear
elif period == 'quarter':
df['dayset'] = df[timestamp_col].apply(
lambda x: label_qtr_pop(x))
return df
except Exception:
logger.error('label data ', exc_info=True)
def get_groupby_pop_df(self, df, variable, groupby_cols):
try:
if df is not None:
if len(df) > 0:
if 'dayset' in df.columns:
if variable in ['project']:
df = df.groupby(groupby_cols).agg(
{variable: 'count'})
df = df.reset_index()
#logger.warning('LINE 286 df:%s',df)
elif variable in ['milestone']:
df = df.groupby(groupby_cols).agg(
{variable: 'count'})
df = df.reset_index()
#logger.warning('LINE 291 df:%s', df)
elif variable in ['task']:
df = df.groupby(groupby_cols).agg(
{variable: 'count'})
df = df.reset_index()
elif variable in ['remuneration']:
df = df.groupby(groupby_cols).agg(
{variable: 'sum'})
df = df.reset_index()
else:
#logger.warning('LINE 259:df:%s',df.head())
df = df.groupby(groupby_cols).agg(
{variable: 'mean'})
df = df.reset_index()
# clean up
if self.groupby_var in df.columns and self.variable != self.groupby_var:
df = df.drop([self.groupby_var], axis=1)
return df
except Exception:
logger.error('get groupby card data', exc_info=True)
def get_groupby_card_data(self, df, variable):
try:
if variable in ['project']:
data = len(df[variable].unique())
data = "{} {}s".format(data, variable)
elif variable in ['milestone']:
df = df.groupby(['project']).agg({variable: 'nunique'})
data = df[variable].sum()
data = "{} {}s".format(data, variable)
elif variable in ['task']:
df = df.groupby(['project',
'milestone']).agg({variable: 'count'})
data = df[variable].sum()
data = "{} {}s".format(data, variable)
elif variable in ['project_duration'] or 'delay' in variable:
df = df.groupby([self.groupby_var]).agg({variable: 'mean'})
df = df.reset_index()
data = "{} days".format(round(df[variable].sum(), 2))
elif variable in ['milestone_duration']:
df = df.groupby([self.groupby_var,
'project']).agg({variable: 'mean'})
df = df.reset_index()
data = "{} days".format(round(df[variable].sum(), 2))
elif variable in [
'task_duration', 'task_start_delay', 'task_start_end'
]:
df = df.groupby([self.groupby_var, 'project',
'milestone']).agg({variable: 'mean'})
df = df.reset_index()
data = "{} hours".format(round(df[variable].sum(), 2))
elif variable in ['remuneration']:
data = df[variable].sum()
data = "${:,.2f}".format(data)
return data
except Exception:
logger.error('get groupby card data', exc_info=True)
# -------------------- GRAPHS -------------------------------------------
def graph_periods_to_date(self, df2, timestamp_filter_col, variable):
df1 = df2.copy()
#self.section_header_updater(section='cards',label=variable,margin_top=159,html_header='h2')
try:
df1 = self.filter_df(df1)
dct = {}
for idx, period in enumerate(
['week', 'month', 'quarter', 'year']):
df = self.period_to_date(
df1,
timestamp=dashboard_config['dates']['last_date'],
timestamp_filter_col=timestamp_filter_col,
period=period)
df = df.drop_duplicates(keep='first')
# groupby to eliminate repetition
data = self.get_groupby_card_data(df, variable)
del df
gc.collect()
dct[period] = data
#title = "{} to date".format(period)
#p = self.card(title=title, data=data, card_design=random.choice(list(self.KPI_card_css.keys())))
#self.period_to_date_cards[period].text = p.text
self.update_cards(dct)
except Exception:
logger.error('graph periods to date', exc_info=True)
def graph_period_over_period(self, period):
try:
periods = [period]
start_date = self.pop_start_date
end_date = self.pop_end_date
if isinstance(start_date, date):
start_date = datetime.combine(start_date,
datetime.min.time())
if isinstance(end_date, date):
end_date = datetime.combine(end_date, datetime.min.time())
today = datetime.combine(datetime.today().date(),
datetime.min.time())
df = self.df_pop.copy()
df = self.filter_df(df)
#logger.warning('LINE 363 -df:%s',df.head())
cols = [self.variable, self.timestamp_col]
if self.variable != 'project':
cols.append('project')
if abs(start_date - end_date).days > 7:
if 'week' in periods:
periods.remove('week')
if abs(start_date - end_date).days > 31:
if 'month' in periods:
periods.remove('month')
if abs(start_date - end_date).days > 90:
if 'quarter' in periods:
periods.remove('quarter')
for idx, period in enumerate(periods):
df_period = self.period_over_period(
df,
start_date=start_date,
end_date=end_date,
period=period,
history_periods=self.pop_history_periods,
timestamp_col=self.timestamp_col)
groupby_cols = ['dayset', 'period']
if len(df_period) > 0:
logger.warning('LINE 473:%s', list(df_period.columns))
df_period = self.get_groupby_pop_df(
df_period,
variable=self.variable,
groupby_cols=groupby_cols)
df_period = df_period.reset_index()
else:
if not 'day' in df_period.columns:
df_period['dayset'] = ""
else:
df_period = df_period.rename(
index=str, columns={'day': 'dayset'})
logger.warning('LINE 478:%s', list(df_period.columns))
prestack_cols = list(df_period.columns)
df_period = self.split_period_into_columns(
df_period,
col_to_split='period',
value_to_copy=self.variable)
# short term fix: filter out the unnecessary first day added by a corrupt quarter functionality
if period == 'quarter':
if 'dayset' in df_period.columns:
min_day = df_period['dayset'].min()
df_period = df_period[
df_period['dayset'] > min_day]
poststack_cols = list(df_period.columns)
title = "{} over {}".format(period, period)
plotcols = list(np.setdiff1d(poststack_cols,
prestack_cols))
# include current period if not extant
df_period, plotcols = self.pop_include_zeros(
df_period, plotcols=plotcols, period=period)
if self.variable in [
'task_start_delay', 'task_end_delay',
'task_duration'
]:
ylabel = 'hours'
elif self.variable in [
'project_duration', 'milestone_duration',
'project_start_delay', 'project_end_delay',
'milestone_start_delay', 'milestone_end_delay'
]:
ylabel = 'days'
elif self.variable in ['project', 'task', 'milestone']:
ylabel = '#'
elif self.variable == 'remuneration':
ylabel = '$'
if 'dayset' not in df_period.columns:
leng = len(df_period)
if leng > 0:
df_period['dayset'] = 0
logger.warning('LINE 549')
else:
logger.warning('LINE 551')
df_period['dayset'] = ''
logger.warning('LINE 552: df columns:%s',
list(df_period.columns))
if idx == 0:
p = df_period.hvplot.bar('dayset',
plotcols,
rot=45,
title=title,
stacked=False,
width=1200,
height=400,
value_label=ylabel)
else:
p += df_period.hvplot.bar('dayset',
plotcols,
rot=45,
title=title,
stacked=False,
width=1200,
height=400,
value_label=ylabel)
return p
except Exception:
logger.error('period over period to date', exc_info=True)
def chord_diagram(self, launch):
try:
def normalize_value(x, total):
x = int((x / total) * 1000)
if x <= 0:
return 1
return x
df = self.df.copy()
# -------------- nodes
data = {}
data['nodes'] = []
source_list = df['milestone_owner'].tolist()
names = list(set(source_list))
person_type_dict = dict(zip(df.milestone_owner, df.type))
type_dict = {}
types = list(set(df['type'].tolist()))
name_dict = {}
for idx, name in enumerate(names):
name_dict[name] = idx
for idx, name in enumerate(names):
type_tmp = person_type_dict[name]
index = name_dict[name]
data['nodes'].append({
'OwnerID': index,
'index': idx,
'Type': type_tmp
})
nodes = hv.Dataset(pd.DataFrame(data['nodes']), 'index')
# --------- make the links
data['links'] = []
for idx, row in df.iterrows():
src = name_dict[row['project_owner']]
tgt = name_dict[row['milestone_owner']]
val = row['remuneration']
data['links'].append({
'source': src,
'target': tgt,
'value': val
})
links = pd.DataFrame(data['links'])
# get the individual links
links = links.groupby(['source', 'target'])['value'].sum()
links = links.reset_index()
total = links['value'].sum()
links['value'] = links['value'].apply(
lambda x: normalize_value(x, total))
# filter for top percentile
quantile_val = links['value'].quantile(
self.chord_data['percentile_threshold'])
links = links[links['value'] >= quantile_val]
#logger.warning('after quantile filter:%s',len(links))
chord_ = hv.Chord((links, nodes), ['source', 'target'],
['value'])
chord_.opts(
opts.Chord(cmap='Category20',
edge_cmap='Category20',
edge_color=dim('source').str(),
labels='Type',
node_color=dim('index').str(),
width=1000,
height=1000))
return chord_
except Exception:
logger.error('chord diagram', exc_info=True)
def timeline(self, project, type='milestone'):
try:
DF = self.df.copy()
if type != project:
DF = DF[DF['project'] == project]
if type == 'all':
rename_dct = {
'milestone_enddate_proposed': 'milestone_enddate',
'milestone_startdate_proposed': 'milestone_startdate',
'task_enddate_proposed': 'task_enddate',
'task_startdate_proposed': 'task_startdate',
}
DF = DF.rename(index=str, columns=rename_dct)
DF = DF.groupby(['milestone', 'task']).agg({
'milestone_startdate':
'min',
'milestone_enddate':
'max',
'task_startdate':
'min',
'task_enddate':
'max',
})
DF = DF.reset_index()
# melt to get milestone and task into one column
df = pd.melt(DF,
value_vars=['milestone', 'task'],
id_vars=[
'milestone_startdate',
'milestone_enddate', 'task_startdate',
'task_enddate'
],
value_name='Item',
var_name='type')
df = df.groupby(['Item', 'type']).agg({
'milestone_startdate':
'min',
'milestone_enddate':
'max',
'task_startdate':
'min',
'task_enddate':
'max'
}).reset_index()
df = pd.melt(
df,
id_vars=[
'Item', 'type', 'milestone_startdate',
'task_startdate'
],
value_vars=['milestone_enddate', 'task_enddate'],
value_name='End',
var_name='enddate_type')
# filter out where tasks label dates and vice versa
df1 = df[(df['type'] == 'task')
& (df['enddate_type'] == 'task_enddate')]
df = df[(df['type'] == 'milestone')
& (df['enddate_type'] == 'milestone_enddate')]
df = pd.concat([df1, df])
df = df.drop('enddate_type', axis=1)
# do startdate
df = pd.melt(
df,
id_vars=['Item', 'type', 'End'],
value_vars=['milestone_startdate', 'task_startdate'],
value_name='Start',
var_name='startdate_type')
# filter out where tasks label dates and vice versa
df1 = df[(df['type'] == 'task')
& (df['startdate_type'] == 'task_startdate')]
df = df[(df['type'] == 'milestone')
& (df['startdate_type'] == 'milestone_startdate')]
df = pd.concat([df1, df])
df = df.drop('startdate_type', axis=1)
# label colors
df['Color'] = df['type'].apply(
lambda x: 'black' if x == 'milestone' else 'green')
# organize by milestone and tasks belonging to milestone
df = df.sort_values(by=['Start']).reset_index()
df = df.drop('index', axis=1)
#logger.warning('LINE 605 - df:%s',df.head(50))
DF = df
print(
'##################################################################################'
)
else:
start_str = type + '_startdate_proposed'
end_str = type + '_enddate_proposed'
# group milestone
rename_dct = {
start_str: 'Start',
end_str: 'End',
type: 'Item'
}
DF = DF.rename(index=str, columns=rename_dct)
DF = DF[['Item', 'Start', 'End']]
DF = DF.groupby(['Item']).agg({
'Start': 'min',
'End': 'max'
})
DF = DF.reset_index()
color_list = []
for item in DF.Item.tolist():
color_list.append(
random.choice(dashboard_config['colors']))
DF['Color'] = np.array(color_list)
DF['start'] = DF['Start'].dt.strftime('%Y-%m-%d')
DF['end'] = DF['End'].dt.strftime('%Y-%m-%d')
DF['ID'] = DF.index + 0.6
DF['ID1'] = DF.index + 1.4
logger.warning('LINE 648 %s', DF)
self.timeline_vars['DF'] = DF
# update source
data = dict(Item=DF.Item.tolist(),
Start=DF.Start.tolist(),
End=DF.End.tolist(),
Color=DF.Color.tolist(),
start=DF.start.tolist(),
end=DF.end.tolist(),
ID=DF.ID.tolist(),
ID1=DF.ID1.tolist())
# <-- This is the trick, make the x_rage empty first, before assigning new value
self.timeline_vars['G'].y_range.factors = []
self.timeline_vars['G'].y_range.factors = DF.Item.tolist()
#self.timeline_vars['G'].x_range.factors = []
#self.timeline_vars['G'].x_range.factors = sorted(DF.Start.tolist())
timeline_source.data = data
except Exception:
logger.error('timeline', exc_info=True)
def timeline_plot(self, DF):
try:
hover = HoverTool(tooltips="Task: @Item<br>\
Start: @start<br>\
End: @end")
self.timeline_vars['G'].quad(left='Start',
right='End',
bottom='ID',
top='ID1',
source=timeline_source,
color="Color")
self.tools = [hover] + self.tools
self.timeline_vars['G'].tools = self.tools
self.timeline_vars['toolbar_box'] = ToolbarBox()
self.timeline_vars['toolbar_box'].toolbar = Toolbar(
tools=self.tools)
self.timeline_vars['toolbar_box'].toolbar_location = "above"
self.timeline_vars['G'].x_range.start = DF.Start.min(
) - timedelta(days=10)
self.timeline_vars['G'].x_range.start = DF.End.max(
) + timedelta(days=10)
return self.timeline_vars['G']
except Exception:
logger.error('timeline', exc_info=True)
def update(attrname, old, new):
thistab.notification_updater(
"Calculations underway. Please be patient")
thistab.pm_gender = pm_gender_select.value
thistab.m_gender = m_gender_select.value
thistab.t_gender = t_gender_select.value
thistab.type = type_select.value
thistab.variable = variable_select.value
if 'project' in thistab.variable:
thistab.groupby_var = 'project'
elif 'milestone' in thistab.variable:
thistab.groupby_var = 'milestone'
elif 'task' in thistab.variable:
thistab.groupby_var = 'task'
thistab.status = status_select.value
thistab.graph_periods_to_date(thistab.df,
thistab.timestamp_col,
variable=thistab.variable)
thistab.trigger += 1
stream_launch.event(launch=thistab.trigger)
thistab.notification_updater("ready")
def update_pop_dates():
thistab.notification_updater(
"Calculations underway. Please be patient")
thistab.pop_history_periods = pop_number_select.value
thistab.pop_start_date = datepicker_pop_start.value # trigger period over period
thistab.pop_end_date = datepicker_pop_end.value
thistab.df_pop = thistab.pym.load_df(start_date=thistab.pop_start_date,
end_date=thistab.pop_end_date,
cols=[],
table=thistab.table,
timestamp_col='startdate_actual')
thistab.trigger += 1
stream_launch.event(launch=thistab.trigger)
thistab.notification_updater("ready")
def update_history_periods(attrname, old, new):
thistab.notification_updater(
"Calculations underway. Please be patient")
thistab.pop_history_periods = pop_number_select.value
thistab.trigger += 1
stream_launch.event(launch=thistab.trigger)
thistab.notification_updater("ready")
def update_timeline(attrname, old, new):
thistab.notification_updater(
"Calculations underway. Please be patient")
thistab.timeline_vars['project'] = timeline_project_select.value
thistab.timeline_vars['type'] = timeline_type_select.value
thistab.timeline(thistab.timeline_vars['project'],
thistab.timeline_vars['type'])
thistab.notification_updater("ready")
try:
cols = []
thistab = Thistab(table='project_composite', cols=cols)
# ------------------------------------- SETUP ----------------------------
# format dates
first_date_range = thistab.initial_date
last_date_range = datetime.now().date()
last_date = dashboard_config['dates']['last_date']
first_date = datetime(last_date.year, 4, 1, 0, 0, 0)
thistab.df = thistab.pym.load_df(start_date=first_date,
end_date=last_date,
table=thistab.table,
cols=[],
timestamp_col=thistab.timestamp_col)
thistab.graph_periods_to_date(
thistab.df,
timestamp_filter_col=thistab.timestamp_col,
variable=thistab.variable)
thistab.pop_end_date = last_date
thistab.pop_start_date = last_date - timedelta(days=5)
thistab.df_pop = thistab.pym.load_df(
start_date=thistab.pop_start_date,
end_date=thistab.pop_end_date,
cols=[],
table=thistab.table,
timestamp_col=thistab.timestamp_col)
thistab.timeline_vars['projects'] = sorted(
list(set(thistab.df['project'].tolist())))
thistab.timeline_vars['project'] = thistab.timeline_vars['projects'][0]
# MANAGE STREAM
# date comes out stream in milliseconds
# --------------------------------CREATE WIDGETS ---------------------------------
stream_launch = streams.Stream.define('Launch', launch=-1)()
datepicker_pop_start = DatePicker(title="Period start",
min_date=first_date_range,
max_date=last_date_range,
value=thistab.pop_start_date)
datepicker_pop_end = DatePicker(title="Period end",
min_date=first_date_range,
max_date=last_date_range,
value=thistab.pop_end_date)
pop_number_select = Select(title='Select # of comparative periods',
value=str(thistab.pop_history_periods),
options=thistab.menus['history_periods'])
pop_dates_button = Button(label="Select dates, then click me!",
width=15,
button_type="success")
type_select = Select(title='Select project type',
value=thistab.type,
options=thistab.menus['type'])
status_select = Select(title='Select project status',
value=thistab.status,
options=thistab.menus['status'])
pm_gender_select = Select(title="Select project owner's gender",
value=thistab.pm_gender,
options=thistab.menus['gender'])
m_gender_select = Select(title="Select milestone owner's gender",
value=thistab.m_gender,
options=thistab.menus['gender'])
t_gender_select = Select(title="Select task owner's gender",
value=thistab.t_gender,
options=thistab.menus['gender'])
variable_select = Select(title='Select variable of interest',
value=thistab.variable,
options=thistab.menus['variables'])
timeline_project_select = Select(
title='Select project',
value=thistab.timeline_vars['project'],
options=thistab.timeline_vars['projects'])
timeline_type_select = Select(title='Select granularity',
value='all',
options=thistab.timeline_vars['types'])
# --------------------------------- GRAPHS ---------------------------
hv_pop_week = hv.DynamicMap(thistab.pop_week, streams=[stream_launch])
pop_week = renderer.get_plot(hv_pop_week)
hv_pop_month = hv.DynamicMap(thistab.pop_month,
streams=[stream_launch])
pop_month = renderer.get_plot(hv_pop_month)
hv_pop_quarter = hv.DynamicMap(thistab.pop_quarter,
streams=[stream_launch])
pop_quarter = renderer.get_plot(hv_pop_quarter)
hv_pop_year = hv.DynamicMap(thistab.pop_year, streams=[stream_launch])
pop_year = renderer.get_plot(hv_pop_year)
hv_chord = hv.DynamicMap(thistab.chord_diagram,
streams=[stream_launch])
chord = renderer.get_plot(hv_chord)
thistab.timeline(thistab.timeline_vars['project'],
thistab.timeline_vars['type'])
timeline = thistab.timeline_plot(DF=thistab.timeline_vars['DF'])
# -------------------------------- CALLBACKS ------------------------
type_select.on_change('value', update)
pop_dates_button.on_click(update_pop_dates) # lags array
status_select.on_change('value', update)
pm_gender_select.on_change('value', update)
m_gender_select.on_change('value', update)
t_gender_select.on_change('value', update)
variable_select.on_change('value', update)
pop_number_select.on_change('value', update_history_periods)
timeline_project_select.on_change('value', update_timeline)
timeline_type_select.on_change('value', update_timeline)
# -----------------------------------LAYOUT ----------------------------
# put the controls in a single element
controls_top = WidgetBox(
variable_select,
type_select,
status_select,
pm_gender_select,
m_gender_select,
t_gender_select,
)
controls_pop = WidgetBox(datepicker_pop_start, datepicker_pop_end,
pop_number_select)
controls_timeline = WidgetBox(thistab.timeline_vars['toolbar_box'],
timeline_project_select,
timeline_type_select)
grid = gridplot([[thistab.notification_div['top']],
[Spacer(width=20, height=70)],
[thistab.section_headers['cards']],
[thistab.KPI_card_div, controls_top],
[thistab.section_headers['pop']],
[Spacer(width=20, height=25)],
[pop_week.state, controls_pop], [pop_month.state],
[pop_quarter.state], [pop_year.state],
[thistab.section_headers['chord']],
[Spacer(width=20, height=25)], [chord.state],
[thistab.section_headers['timeline']],
[Spacer(width=20, height=25)],
[timeline, controls_timeline],
[thistab.notification_div['bottom']]])
# Make a tab with the layout
tab = Panel(child=grid, title=panel_title)
return tab
except Exception:
logger.error('rendering err:', exc_info=True)
return tab_error_flag(panel_title)
def empty_plot(width, height):
"""
Creates an empty and invisible plot of the specified size.
"""
return Spacer(width=width, height=height)
def on_session_created(session_context):
''' If present, this function is called when a session is created. '''
print("-----------------------------------------------")
start_time_database = timeit.default_timer()
print("on_session_created -- begin")
#import_data.setup_db_connection()
#import_data.retrieve_data(uHelper.connection)
import_data.retrieve_data()
#uHelper.database_que.put(import_data.retrieve_data(uHelper.connection))
#uHelper.all_connection_dict, uHelper.novos_connection_dict, \
#uHelper.all_connection_table, uHelper.novos_connection_table, \
#uHelper.novos_source, uHelper.rigs_list, \
#uHelper.jobs_list, uHelper.crewshift_list = uHelper.database_que.get()
print("on_session_created -- after")
print("\n retrieving time: ")
print(timeit.default_timer() - start_time_database)
default_rig_number, rigs_list = uHelper.get_default_value(
uHelper.all_connection_table, comboBx='Rigs')
default_rig_number = str(default_rig_number)
rigs_list = []
rigs_list = [str(item) for item in uHelper.rigs_list]
uHelper.rigs_combx = Select(title='Rigs:',
value=default_rig_number,
width=100,
sizing_mode=uHelper.sizing_mode,
options=uHelper.update_combBx_values(
'', rigs_list))
default_job_number, jobs_list = uHelper.get_default_value(
uHelper.all_connection_table,
comboBx='Jobs',
selectedRig=uHelper.rigs_combx.value
) # TODO: add condition to determine 0 exists or not
default_job_number = str(default_job_number)
jobs_list = []
jobs_list = [str(item) for item in uHelper.jobs_list]
uHelper.default_job_number = default_job_number
uHelper.jobs_list = jobs_list
uHelper.jobs_combx = Select(title='Jobs:',
value=default_job_number,
width=100,
sizing_mode=uHelper.sizing_mode,
options=uHelper.update_combBx_values(
'', jobs_list))
default_crew, crewshift_list = uHelper.get_default_value(
uHelper.all_connection_table,
comboBx='CrewShift',
selectedRig=uHelper.rigs_combx.value,
selectedJob=uHelper.jobs_combx.value)
default_crew = str(default_crew)
crewshift_list = [str(item) for item in crewshift_list]
uHelper.crewshift_combx = Select(title='CrewShift:',
value=default_crew,
width=100,
sizing_mode=uHelper.sizing_mode,
options=uHelper.update_combBx_values(
'', crewshift_list))
# 2. checkbox group
uHelper.checkbox_group_1 = CheckboxGroup(labels=["Build", "Lateral", "Vertical"], \
active=[], \
name = 'wellSelection')
uHelper.checkbox_group_2 = CheckboxGroup(labels=["Driller", "Novos", "Hybrid"], \
active=[], \
name = 'connectionType')
uHelper.checkbox_group_3 = CheckboxGroup(labels=["B2S", "S2S", "S2B", "Survey", "BackReam"], \
active=[], \
name = 'connectionPhase')
rig, job = uHelper.rigs_combx.value, uHelper.jobs_combx.value
# 1st chart
uHelper.update_drillingconn_wellsect_queue = queue.Queue()
uHelper.update_drillingconn_wellsect_event = threading.Event()
update_drillingconn_wellsect_thread = Thread(name='update_drillingconn_wellsect_thread', \
target = lambda q, arg1, arg2, arg3, arg4: \
q.put(drillingconn_wellsect_plot.update_well_selection_data(arg1, arg2, arg3, arg4)), \
args = (uHelper.update_drillingconn_wellsect_queue, \
uHelper.update_drillingconn_wellsect_event, \
uHelper.all_connection_dict, rig, job))
update_drillingconn_wellsect_thread.start()
uHelper.update_drillingconn_wellsect_event.wait()
well_connection_colors, x, well_connnection_counts, well_connnection_data = uHelper.update_drillingconn_wellsect_queue.get(
)
uHelper.well_connnection_source = ColumnDataSource(data=dict(colors = well_connection_colors, \
x = x, \
counts = well_connnection_counts))
well_connection_chart = figure(x_range = FactorRange(*x), \
plot_width = 1310, \
plot_height = 430, \
sizing_mode = uHelper.sizing_mode, \
title = "Drilling Connection Breakdown By Well Section")
#title = "Drilling Connection Breakdown By Well Section", \
#output_backend = "webgl")
well_connection_chart.vbar(x = 'x', \
width = 0.2, \
bottom = 0, \
top = 'counts', \
color = 'colors', \
source = uHelper.well_connnection_source)
total_connections = sum(well_connnection_counts)
uHelper.well_connection_textbox_source = ColumnDataSource(data=dict(x = [600,], \
y = [450,], \
txt= ['Total Connections: %d' % (total_connections),]))
well_connection_chart_textbox = LabelSet(x='x', y='y', x_units='screen', y_units='screen', \
text='txt', source = uHelper.well_connection_textbox_source,\
text_font_size="12pt", border_line_color='black', \
border_line_width=1, text_font_style='bold')
well_connection_chart.add_layout(well_connection_chart_textbox)
well_connection_chart.title.align = 'center'
well_connection_chart.title.text_font_size = '15pt'
well_connection_chart.toolbar.active_drag = None
well_connection_chart.toolbar.logo = None
well_connection_chart.toolbar_location = None
well_connection_chart.y_range.start = 0
well_connection_chart.x_range.range_padding = 0.1
well_connection_chart.xaxis.major_label_orientation = 1
well_connection_chart.xgrid.grid_line_color = None
for well_item in well_connnection_data['well_selection']:
for sub_item in well_connnection_data['Driller']:
well_connection_chart.add_tools(
HoverTool(tooltips=[(str(well_item), "@counts")]))
print("\n1st chart loading time \n")
### 2nd chart(b2s s2b)
start_time_2nd_chart = timeit.default_timer()
uHelper.update_b2s_s2b_queue = queue.Queue()
uHelper.update_b2s_s2b_event = threading.Event()
update_b2s_s2b_thread = threading.Thread(name='update_b2s_s2b_thread', \
target = lambda q, arg1, arg2, arg3, arg4: \
q.put(b2s_s2b_plot.update_b2s_s2b_data(arg1, arg2, arg3, arg4)), \
args = (uHelper.update_b2s_s2b_queue, uHelper.update_b2s_s2b_event, uHelper.novos_connection_table, rig, job))
update_b2s_s2b_thread.start()
uHelper.update_b2s_s2b_event.wait()
b2s_canceled_list, b2s_completed_list, \
b2s_exception_list,b2s_failed_list, \
s2b_canceled_list, s2b_completed_list, \
s2b_exception_list, s2b_failed_list = uHelper.update_b2s_s2b_queue.get()
b2s_s2b_status = ["Canceled", "Completed", "Exception", "Failed"]
b2s_s2b_colors = ["#F2C80F", "#00ff0d", "#F2C80F", "#ff4600"]
b2s_connection_phase = [
'OffBottom', 'UnWeightBit', 'ClearBit', 'CleanHole', 'SetBoxHeight',
'SetWeight'
]
b2s_figure = figure(x_range = b2s_connection_phase, \
plot_width = 600, \
plot_height = 300, \
sizing_mode = uHelper.sizing_mode, \
title="Bottom to Slip")
uHelper.b2s_datasource = ColumnDataSource(data=dict(b2s_connection_phase = b2s_connection_phase, \
Canceled = b2s_canceled_list, \
Completed = b2s_completed_list, \
Exception = b2s_exception_list, \
Failed = b2s_failed_list))
b2s_figure.vbar_stack(b2s_s2b_status, \
x='b2s_connection_phase', \
width = 0.2, \
color = b2s_s2b_colors, \
source = uHelper.b2s_datasource)
b2s_figure.title.align = 'center'
b2s_figure.toolbar.active_drag = None
b2s_figure.toolbar.logo = None
b2s_figure.toolbar_location = None
b2s_figure.y_range.start = 0
b2s_figure.x_range.range_padding = 0.1
b2s_figure.xaxis.major_label_orientation = 1
b2s_figure.xgrid.grid_line_color = None
b2s_figure.ygrid.grid_line_color = None
s2b_connection_phase = [
'AddStand', 'TakeWeight', 'FlowSetpoint', 'RotateDrill', 'TagBottom'
]
s2b_figure = figure(x_range = s2b_connection_phase, \
plot_width = 670, \
plot_height = 300, \
sizing_mode = uHelper.sizing_mode, \
title="Slip to Bottom")
uHelper.s2b_datasource = ColumnDataSource(data=dict(s2b_connection_phase = s2b_connection_phase, \
Canceled = s2b_canceled_list, \
Completed = s2b_completed_list, \
Exception = s2b_exception_list, \
Failed = s2b_failed_list))
s2b_figure.vbar_stack(b2s_s2b_status, \
x = 's2b_connection_phase', \
width = 0.2, \
color = b2s_s2b_colors, \
source = uHelper.s2b_datasource, \
legend= [value(x) for x in b2s_s2b_status])
s2b_figure.title.align = 'center'
s2b_figure.toolbar.active_drag = None
s2b_figure.toolbar.logo = None
s2b_figure.toolbar_location = None
s2b_figure.y_range.start = 0
s2b_figure.x_range.range_padding = 0.1
s2b_figure.xaxis.major_label_orientation = 1
s2b_figure.xgrid.grid_line_color = None
s2b_figure.ygrid.grid_line_color = None
s2b_figure.legend.location = "top_right"
s2b_figure.legend.orientation = "vertical"
new_legend = s2b_figure.legend[0]
s2b_figure.legend[0].plot = None
s2b_figure.add_layout(new_legend, 'right')
line_figure = figure(x_range=(0, 100), \
y_range=(0, 300), \
plot_width = 120, \
plot_height = 300)
line_figure.line(x=[50, 50], \
y= [0, 300], \
line_width = 3, \
line_color='black')
line_figure.xaxis.visible = None
line_figure.yaxis.visible = None
line_figure.toolbar.logo = None
line_figure.toolbar_location = None
line_figure.toolbar.active_drag = None
line_figure.min_border_left = 10
line_figure.min_border_right = 10
line_figure.min_border_top = 0
line_figure.min_border_bottom = 0
#summary_layout = layout(row(b2s_figure, line_figure, s2b_figure), sizing_mode = uHelper.sizing_mode)
print("\n 2nd chart loading time \n")
print(timeit.default_timer() - start_time_2nd_chart)
mTicker = uHelper.customize_ticker()
start_time_main_chart = timeit.default_timer()
uHelper.get_all_data_queue = queue.Queue()
uHelper.get_all_data_event = threading.Event()
uHelper.get_all_data_thread = threading.Thread(name = 'get_all_data_thread', \
target = lambda q, arg1, arg2: \
q.put(all_main_plot.get_all_data(arg1, arg2)), args = (uHelper.get_all_data_queue, uHelper.get_all_data_event, uHelper.all_connection_dict))
uHelper.get_all_data_thread.start()
uHelper.get_all_data_event.wait()
uHelper.mainplot_data_all, depth_list_all = uHelper.get_all_data_queue.get(
)
depth_list_all = [str(x) for x in depth_list_all]
uHelper.main_plot = figure(x_range=FactorRange(), \
y_range = (0, 50), \
plot_width = uHelper.plot_width, \
plot_height = 400, \
tools = "tap, pan, box_zoom, reset", \
sizing_mode = uHelper.sizing_mode, \
title="Overall Connection Times",\
id="main_plot_id")
uHelper.main_plot.xaxis.ticker = mTicker
uHelper.main_plot.title.align = 'center'
uHelper.main_plot.legend.click_policy = "hide"
uHelper.main_plot.title.text_font_size = '15pt'
uHelper.main_plot.x_range.factors = []
uHelper.main_plot.x_range.factors = depth_list_all
uHelper.mainplot_data_all['HoleDepth'] = [
"{0:.2f}".format(x) for x in uHelper.mainplot_data_all['HoleDepth']
]
#mainplot_data_all['HoleDepth'] = [str(x) for x in mainplot_data_all['HoleDepth']]
#TODO: 20181001
#dur = []
#for index, item in enumerate(uHelper.mainplot_data_all['VBarTop']):
# top_num = 0.0
# bottom_num = 0.0
# if uHelper.mainplot_data_all['VBarTop'][index] == '':
# top_num = 0.0
# else:
# top_num = float(uHelper.mainplot_data_all['VBarTop'][index])
#
# if uHelper.mainplot_data_all['VBarBottom'][index] == '':
# bottom_num = 0.0
# else:
# bottom_num = float( uHelper.mainplot_data_all['VBarBottom'][index])
# dur.append(str(top_num - bottom_num))
uHelper.mainplot_source = ColumnDataSource(data=dict(HoleDepthRef = uHelper.mainplot_data_all['HoleDepthRef'], \
HoleDepth = uHelper.mainplot_data_all['HoleDepth'], \
VBarTop = uHelper.mainplot_data_all['VBarTop'], \
VBarBottom = uHelper.mainplot_data_all['VBarBottom'], \
VBarColors = uHelper.mainplot_data_all['VBarColors'], \
VBarType = uHelper.mainplot_data_all['VBarType']))
main_plot_vbars = uHelper.main_plot.vbar(x = 'HoleDepth', \
width = 0.1, \
bottom = 'VBarBottom', \
top = 'VBarTop', \
color = 'VBarColors', \
source = uHelper.mainplot_source, \
legend = 'VBarType')
uHelper.main_plot.legend.location = "top_right"
uHelper.main_plot.legend.orientation = "vertical"
new_legend = uHelper.main_plot.legend[0]
uHelper.main_plot.legend[0].plot = None
uHelper.main_plot.add_layout(new_legend, 'right')
# layout
uHelper.m_well_selection = Div(text='Well Section:', height=1)
uHelper.m_well_connection = Div(text='Connection Type:', height=1)
uHelper.m_well_conn_phase = Div(text='Connection Phase:', height=1)
start_time_rest_chart = timeit.default_timer()
uHelper.version = Div(text='Version: 1.1.1', width=200, height=30)
uHelper.version.css_classes = ["version"]
#sidebar menu
uHelper.spacer_1 = Spacer(width=200, height=10)
uHelper.spacer_2 = Spacer(width=200, height=30)
uHelper.spacer_3 = Spacer(width=200, height=30)
uHelper.menu_column_1_layout = column(uHelper.spacer_3,
widgetbox(uHelper.rigs_combx),
widgetbox(uHelper.jobs_combx),
widgetbox(uHelper.crewshift_combx))
uHelper.menu_column_1_layout.css_classes = ["sidebarmenucombxlayout"]
uHelper.well_selection_layout = column(uHelper.m_well_selection,
uHelper.checkbox_group_1)
uHelper.well_connection_layout = column(uHelper.m_well_connection,
uHelper.checkbox_group_2)
uHelper.well_conn_phase_layout = column(uHelper.m_well_conn_phase,
uHelper.checkbox_group_3)
uHelper.menu_column_2_layout = column(uHelper.well_selection_layout,
uHelper.well_connection_layout,
uHelper.well_conn_phase_layout)
uHelper.menu_column_2_layout.css_classes = ["sidebarmenucheckbxlayout"]
uHelper.menu_middle_layout = layout(
column(uHelper.menu_column_1_layout, uHelper.menu_column_2_layout))
uHelper.menu_middle_layout.css_classes = ["sidebarmenumiddlelayout"]
uHelper.menu_top_layout = layout(column(uHelper.spacer_1, uHelper.version))
uHelper.menu_top_layout.css_classes = ["sidebarmenutoplayout"]
uHelper.menu_bottom_layout = layout(column(uHelper.spacer_2))
uHelper.menu_bottom_layout.css_classes = ["sidebarmenubottomlayout"]
uHelper.menu_layout = layout(
column(uHelper.menu_top_layout, uHelper.menu_middle_layout,
uHelper.menu_bottom_layout))
uHelper.menu_layout.css_classes = ["menulayout"]
#sub_plot
#sub_plot, subplot_source, subplot_dict = sub_novos_plot.create_sub_plot(doc)
subplot_dict = {}
subplot_dict['B2SText'] = [
'Cleanhole - Active', 'Cleanhole - Completed', 'Setboxheight - Active',
'Setboxheight - Completed', 'Setweight - Active',
'Setweight - Completed', 'Offbottom-Active', 'Unweightbit - Active',
'Unweightbit - Completed', 'Clearbit - Active', 'Clearbit - Completed',
'Offbottom - Completed'
]
subplot_dict['text_x'] = [2, 12, 22, 32, 42, 52, 2, 12, 22, 32, 42, 52]
subplot_dict['B2SColors'] = [
'white', 'white', 'white', 'white', 'white', 'white', 'white', 'white',
'white', 'white', 'white', 'white'
]
subplot_dict['B2STextColors'] = [
'black', 'black', 'black', 'black', 'black', 'black', 'black', 'black',
'black', 'black', 'black', 'black'
]
subplot_dict['B2SHideColors'] = [
'white', 'white', 'white', 'white', 'white', 'white', 'white', 'white',
'white', 'white', 'white', 'white'
]
subplot_dict['subplot_x'] = [5, 15, 25, 35, 45, 55, 5, 15, 25, 35, 45, 55]
subplot_dict['subplot_y'] = [
10, 10, 10, 10, 10, 10, 25, 25, 25, 25, 25, 25
]
subplot_dict['Text'] = ['', '', '', '', '', '', '', '', '', '', '', '']
uHelper.subplot_source = ColumnDataSource(data=subplot_dict)
# 3. plot
uHelper.sub_plot = figure(x_range = [0, 60], \
y_range = [0, 30], \
plot_width=1540, \
plot_height= 350, \
toolbar_location=None, \
sizing_mode='scale_both')
subplot_height = 40
subplot_weight = 175
uHelper.sub_plot.rect(x = 'subplot_x', \
y = 'subplot_y', \
width = subplot_weight, \
height = subplot_height, \
color = "B2SColors", \
width_units = "screen", \
height_units = "screen", \
source = uHelper.subplot_source)
b2s_text = Text(x = 'text_x', \
y = 'subplot_y', \
text_color = "B2STextColors", \
text = "Text", \
text_font_size = "10pt")
uHelper.sub_plot.add_glyph(uHelper.subplot_source, b2s_text)
uHelper.sub_plot.xaxis.visible = None
uHelper.sub_plot.yaxis.visible = None
uHelper.sub_plot.background_fill_color = "#01B8AA"
uHelper.sub_plot.background_fill_color = "white"
uHelper.m_color_white = uHelper.sub_plot.background_fill_color
uHelper.sub_plot.outline_line_color = None
uHelper.sub_plot.title.align = 'center'
uHelper.sub_plot.title.text_font_size = '15pt'
uHelper.m_color_white = "white"
uHelper.subplot_colors_length = len(subplot_dict['B2SColors'])
#hide_subplot_callback = CustomJS(args=dict(m_color=m_color_white, subplot=sub_plot, subplotColorsLength=subplot_colors_length, subplotSource=subplot_source), code="""
#hide_subplot_callback = CustomJS(args=dict(m_color = uHelper.m_color_white, \
# subplot = uHelper.sub_plot, \
# subplotColorsLength = subplot_colors_length, \
# subplotSource = uHelper.subplot_source), code="""
# for(i = 0; i < subplotColorsLength; i++) {
# subplotSource.data['B2SColors'][i] = 'white'
# subplotSource.data['B2STextColors'][i] = 'white'
#
# }
# subplotSource.change.emit()
# subplot.background_fill_color = 'white'
# """)
#
uHelper.main_plot.toolbar.logo = None
uHelper.main_plot.toolbar_location = "above"
uHelper.main_plot.css_classes = ["mainplot"]
#drillingConnectionBreakdown_column = column(well_connection_chart, uHelper.main_plot, uHelper.sub_plot)
drillingConnectionBreakdown_column = column(well_connection_chart)
drillingConnectionBreakdown_column.sizing_mode = uHelper.sizing_mode
drillingConnectionBreakdown_layout = layout(
drillingConnectionBreakdown_column, sizing_mode=uHelper.sizing_mode)
activity_type_stats_top = row(b2s_figure, line_figure, s2b_figure)
activity_type_stats_bottom = column(uHelper.main_plot, uHelper.sub_plot)
summary_layout = layout(
column(activity_type_stats_top, activity_type_stats_bottom))
right_layout = layout(row(summary_layout))
#taptool = uHelper.main_plot.select(type=TapTool)
#uHelper.main_plot.js_on_event(Tap, uHelper.tapcallback)
#novos_length = len(uHelper.novos_connection_dict[uHelper.depth_ft_str])
#uHelper.main_plot.js_on_event(Tap, CustomJS(args=dict(allSource = uHelper.mainplot_source, \
# novosSource = uHelper.novos_source, \
# subplotSource = uHelper.subplot_source, \
# subplotColorsLength = uHelper.subplot_colors_length, \
# novosLength = novos_length, \
# subplot = uHelper.sub_plot \
# ),\
# code = sub_novos_plot.m_code))
#20180727start
tabMain = Panel(title='Main', child=drillingConnectionBreakdown_layout)
tabMain.tags = ["MainTag"]
tabMain.name = "MainName"
tabActivitytypeStats = Panel(title='Over Connection Analysis',
child=right_layout)
tabActivitytypeStats.tags = ["activitytypestatsTag"]
tabActivitytypeStats.name = "ActivitytypeStatsName"
#####################################################
#start 20180928
#depth_list_all = [str(x) for x in depth_list_all]
uHelper.driller_vs_plot = figure(x_range=FactorRange(), \
y_range = (0, 50), \
plot_width = uHelper.plot_width, \
plot_height = 250, \
tools = "tap, pan, box_zoom, reset",\
sizing_mode = uHelper.sizing_mode)
uHelper.driller_vs_dataset, driller_vs_display_depth_list = all_main_plot.get_all_dataset(
uHelper.all_connection_dict)
driller_vs_display_depth_list = [
str(x) for x in driller_vs_display_depth_list
]
#uHelper.driller_vs_dataset['HoleDepth'] = ["{0:.2f}".format(x) for x in uHelper.driller_vs_dataset['HoleDepth']]
#uHelper.driller_vs_dataset['HoleDepth'] = [str(x) for x in uHelper.driller_vs_dataset['HoleDepth']]
uHelper.driller_vs_plot.toolbar.logo = None
uHelper.driller_vs_plot.toolbar_location = "above"
uHelper.driller_vs_plot.css_classes = ["DrillerVSPlot"]
uHelper.driller_vs_plot.xaxis.ticker = mTicker
uHelper.driller_vs_plot.title.align = 'center'
uHelper.driller_vs_plot.legend.click_policy = "hide"
uHelper.driller_vs_plot.x_range.factors = []
#uHelper.driller_vs_plot.x_range.factors = driller_vs_display_depth_list
uHelper.driller_vs_plot.yaxis.axis_label = "Driller"
uHelper.driller_vs_plot.axis.axis_label_text_font_style = "bold"
uHelper.driller_vs_plot_source = ColumnDataSource(data=dict(HoleDepthRef = [], \
HoleDepth = [],\
B2S = [], \
S2S = [], \
S2B = [], \
Survey = [], \
BackReam = []))
driller_vs_plot_vbars = uHelper.driller_vs_plot.vbar_stack(uHelper.connection_phase_list,\
x = 'HoleDepth', \
width = 0.1, \
color = uHelper.color_list, \
source = uHelper.driller_vs_plot_source, \
legend = [value(x) for x in uHelper.connection_phase_list])
uHelper.driller_vs_plot.legend.location = "top_left"
uHelper.driller_vs_plot.legend.orientation = "horizontal"
driller_vs_new_legend = uHelper.driller_vs_plot.legend[0]
uHelper.driller_vs_plot.legend[0].plot = None
uHelper.driller_vs_plot.add_layout(driller_vs_new_legend, 'above')
uHelper.hybrid_vs_plot = figure(x_range=FactorRange(), \
y_range = (0, 50), \
plot_width = uHelper.plot_width, \
plot_height = 250, \
tools = "tap, pan, box_zoom, reset", \
sizing_mode = uHelper.sizing_mode)
#uHelper.mainplot_data_all['HoleDepth'] = ["{0:.2f}".format(x) for x in uHelper.mainplot_data_all['HoleDepth']]
#mainplot_data_all['HoleDepth'] = [str(x) for x in mainplot_data_all['HoleDepth']]
uHelper.hybrid_vs_plot.toolbar.logo = None
uHelper.hybrid_vs_plot.toolbar_location = "above"
uHelper.hybrid_vs_plot.css_classes = ["HybridVSPlot"]
uHelper.hybrid_vs_plot.xaxis.ticker = mTicker
uHelper.hybrid_vs_plot.title.align = 'center'
uHelper.hybrid_vs_plot.x_range.factors = []
uHelper.hybrid_vs_plot.x_range.factors = driller_vs_display_depth_list
uHelper.hybrid_vs_plot.yaxis.axis_label = "Hybrid"
uHelper.hybrid_vs_plot.axis.axis_label_text_font_style = "bold"
uHelper.hybrid_vs_plot_source = ColumnDataSource(data=dict(HoleDepthRef = [], \
HoleDepth = [],\
B2S = [], \
S2S = [], \
S2B = [], \
Survey = [], \
BackReam = []))
hybrid_vs_plot_vbars = uHelper.hybrid_vs_plot.vbar_stack(uHelper.connection_phase_list,\
x = 'HoleDepth', \
width = 0.1, \
color = uHelper.color_list, \
source = uHelper.hybrid_vs_plot_source, \
legend = [value(x) for x in uHelper.connection_phase_list])
uHelper.hybrid_vs_plot.legend.location = "top_left"
uHelper.hybrid_vs_plot.legend.orientation = "horizontal"
hybrid_vs_plot_new_legend = uHelper.hybrid_vs_plot.legend[0]
uHelper.hybrid_vs_plot.legend[0].plot = None
uHelper.hybrid_vs_plot.add_layout(hybrid_vs_plot_new_legend, 'above')
uHelper.novos_vs_plot = figure(x_range=FactorRange(), \
y_range = (0, 50), \
plot_width = uHelper.plot_width, \
plot_height = 250, \
tools = "tap, pan, box_zoom, reset", \
sizing_mode = uHelper.sizing_mode)
#uHelper.mainplot_data_all['HoleDepth'] = ["{0:.2f}".format(x) for x in uHelper.mainplot_data_all['HoleDepth']]
#mainplot_data_all['HoleDepth'] = [str(x) for x in mainplot_data_all['HoleDepth']]
uHelper.novos_vs_plot.toolbar.logo = None
uHelper.novos_vs_plot.toolbar_location = "above"
uHelper.novos_vs_plot.css_classes = ["NovosVSPlot"]
uHelper.novos_vs_plot.xaxis.ticker = mTicker
uHelper.novos_vs_plot.title.align = 'center'
uHelper.novos_vs_plot.x_range.factors = []
uHelper.novos_vs_plot.x_range.factors = driller_vs_display_depth_list
uHelper.novos_vs_plot.yaxis.axis_label = "NOVOS"
uHelper.novos_vs_plot.axis.axis_label_text_font_style = "bold"
uHelper.novos_vs_plot_source = ColumnDataSource(data=dict(HoleDepthRef = [], \
HoleDepth = [],\
B2S = [], \
S2S = [], \
S2B = [], \
Survey = [], \
BackReam = []))
novos_vs_plot_vbars = uHelper.novos_vs_plot.vbar_stack(uHelper.connection_phase_list,\
x = 'HoleDepth', \
width = 0.1, \
color = uHelper.color_list, \
source = uHelper.novos_vs_plot_source, \
legend = [value(x) for x in uHelper.connection_phase_list])
uHelper.novos_vs_plot.legend.location = "top_left"
uHelper.novos_vs_plot.legend.orientation = "horizontal"
novos_vs_plot_new_legend = uHelper.novos_vs_plot.legend[0]
uHelper.novos_vs_plot.legend[0].plot = None
uHelper.novos_vs_plot.add_layout(novos_vs_plot_new_legend, 'above')
vs_driller_hybrid_novos_column = column(uHelper.driller_vs_plot,
uHelper.hybrid_vs_plot,
uHelper.novos_vs_plot)
vs_driller_hybrid_novos_column.sizing_mode = uHelper.sizing_mode
vs_driller_hybrid_novos_layout = layout(vs_driller_hybrid_novos_column,
sizing_mode=uHelper.sizing_mode)
vsDrillerHybridNOVOS = Panel(child=vs_driller_hybrid_novos_layout,
title="Driller vs Hybrid vs Novos")
vsDrillerHybridNOVOS.name = "vsDrillerHybridNOVOSName"
vsDrillerHybridNOVOS.tags = ["vsDrillerHybridNOVOSTag"]
#end 20180928
##################################
p3 = figure(plot_width=uHelper.plot_width,
plot_height=300,
toolbar_location=None)
#p3.line([1, 2, 3, 4, 5], [16, 17, 12, 10, 18], line_width=3, color="red", alpha=0.5)
#tabNovosConfigConnectionAnalysis = Panel(child=None, title="Novos Config Connection Analysis")
p3.text([65, 65, 65], [65, 65, 65],
text=["Coming Soon"],
alpha=0.5,
text_font_size="50pt",
text_baseline="middle",
text_align="center")
p3.xaxis.visible = None
p3.yaxis.visible = None
p3.background_fill_color = "white"
p3.outline_line_color = None
tabNovosConfigConnectionAnalysis = Panel(child=p3,
title="Activity type Stats")
tabNovosConfigConnectionAnalysis.name = "NovosConfigConnectionAnalysisName"
tabNovosConfigConnectionAnalysis.tags = [
"NovosConfigConnectionAnalysisTag"
]
p6 = figure(plot_width=uHelper.plot_width,
plot_height=300,
toolbar_location=None)
#p6.line([1, 2, 3, 4, 5], [16, 17, 12, 10, 18], line_width=3, color="orange", alpha=0.5)
p6.text([65, 65, 65], [65, 65, 65],
text=["Coming Soon"],
alpha=0.5,
text_font_size="50pt",
text_baseline="middle",
text_align="center")
p6.xaxis.visible = None
p6.yaxis.visible = None
p6.background_fill_color = "white"
p6.outline_line_color = None
#tabDistributioncharts = Panel(child=None, title="Distribution charts")
tabDistributioncharts = Panel(child=p6, title="Distribution charts")
tabDistributioncharts.name = "DistributionchartsName"
tabDistributioncharts.tags = ["DistributionchartsTag"]
p7 = figure(plot_width=uHelper.plot_width,
plot_height=300,
toolbar_location=None)
#p7.line([1, 2, 3, 4, 5], [16, 17, 12, 10, 18], line_width=3, color="black", alpha=0.5)
p7.text([65, 65, 65], [65, 65, 65],
text=["Coming Soon"],
alpha=0.5,
text_font_size="50pt",
text_baseline="middle",
text_align="center")
p7.xaxis.visible = None
p7.yaxis.visible = None
p7.background_fill_color = "white"
p7.outline_line_color = None
tabDuplicateofContinuousinDepth = Panel(child=p7,
title="Config Connection Analysis")
#tabDuplicateofContinuousinDepth = Panel(child=None, title="Duplicate of Continuous in Depth")
tabDuplicateofContinuousinDepth.name = "DuplicateofContinuousinDepthName"
tabDuplicateofContinuousinDepth.tags = ["DuplicateofContinuousinDepthTag"]
about_div = Div(text="""<p> Data Visualization <br>
Copyright 2018 Precision Drilling Corporation. All rights reserved.<br>
Version 1.1.1(Official Build)<br>
<br>
<h3>Technical Support</h3>
<h4>Email:</h4>
<ul style="list-style-type:circle">
<li>[email protected]</li>
<li>[email protected]</li>
</ul>
<h4>Phone:</h4>
<ul style="list-style-type:circle">
<li>403-716-4704</li>
<li>403-716-4631</li>
</ul>
<h4>Release Note:</h4>
<ul style="list-style-type:circle">
<li>Added "Driller vs Hybrid vs Novos" tab <br></li>
<li>Moved "main plot" from "Main" tab to "Over Connection Analysis" Tab</li>
<li>Deleted "Continuous in Depth" and "Driller vs Novos" tabs</li>
<li>"Connection Type" Checklist is greyed out, when "Driller vs Hybrid vs Novos" tab is activated</li>
<li>Colors are now consistent with what we have in "PowerBI"</li>
<li>"Wheel zoom" is removed from plot "tool bar"</li>
<li>Display the latest dataset, whenever user clicks "Reload this page" from browser</li>
</ul>
</p>""",
width=uHelper.plot_width,
height=900)
about_div.css_classes = ["aboutDiv"]
#about_figure = figure(plot_width=uHelper.plot_width, plot_height=300, toolbar_location=None)
#p7.line([1, 2, 3, 4, 5], [16, 17, 12, 10, 18], line_width=3, color="black", alpha=0.5)
#about_figure.text([65,65,65],[65,65,65], text=[ "Coming Soon"], alpha=0.5, text_font_size="50pt", text_baseline="middle", text_align="center")
#about_figure.xaxis.visible = None
#about_figure.yaxis.visible = None
#about_figure.background_fill_color = "white"
#about_figure.outline_line_color = None
tabAboutPanel = Panel(child=about_div,
title="About",
width=uHelper.plot_width,
height=900)
#tabDuplicateofContinuousinDepth = Panel(child=None, title="Duplicate of Continuous in Depth")
tabAboutPanel.name = "AboutPanelName"
tabAboutPanel.tags = ["AboutPanelTag"]
uHelper.tabs = Tabs(tabs=[tabMain, \
tabActivitytypeStats, \
vsDrillerHybridNOVOS, \
tabNovosConfigConnectionAnalysis, \
tabDistributioncharts, \
tabDuplicateofContinuousinDepth, \
tabAboutPanel], width= uHelper.plot_width, sizing_mode='scale_width')
uHelper.tabs.css_classes = ["tabsbackgroundcolorblack"]
print("\n main chart loading time \n")
print(timeit.default_timer() - start_time_rest_chart)
uHelper.spacer_4 = Spacer(width=120, height=350)
uHelper.sidebar_layout = layout(
column(uHelper.menu_layout, uHelper.spacer_4))
uHelper.sidebar_layout.css_classes = ["sidebarlayout"]
tabs_row = row(uHelper.tabs)
tabs_row.sizing_mode = uHelper.sizing_mode
main_row = row(uHelper.sidebar_layout, tabs_row)
main_row.sizing_mode = uHelper.sizing_mode
uHelper.main_row = main_row
uHelper.main_row.css_classes = ["mainrowlayout"]
uHelper.main_layout = layout(
uHelper.main_row, sizing_mode='scale_width') # uHelper.sizing_mode)
uHelper.main_layout.css_classes = ["mainlayout"]
#vbar_clicked_index_dict = {}
#vbar_clicked_index_dict['index'] = [-1, ]
#uHelper.selectedVbarIndexSource = ColumnDataSource(data = vbar_clicked_index_dict)
#taptool = uHelper.main_plot.select(type=TapTool)
##uHelper.main_plot.js_on_event(Tap, uHelper.tapcallback)
##novos_length = len(uHelper.novos_connection_dict[uHelper.depth_ft_str])
#
start_time_all = timeit.default_timer()
#uHelper.main_plot.js_on_event(Tap, CustomJS(args=dict(allSource = uHelper.mainplot_source,
# selectedVbarIndexSource = uHelper.selectedVbarIndexSource, \
# index2 = uHelper.index2), \
# code = sub_novos_plot.m_selected_index_code))
main_plot_vbars.data_source.on_change('selected', uHelper.handler)
#uHelper.main_plot.js_on_event(Tap, CustomJS.from_py_func(uHelper.update_subplot))
print("\nbk_plotter loading time \n")
print(timeit.default_timer() - start_time_all)