:refs: :ref:`userguide_plotting` > :ref:`userguide_plotting_twin_axes`
:keywords: add_layout, axis, axis_label, axis_label_text_color, cirlce, extra_y_ranges, LinearAxis
'''
from numpy import arange, linspace, pi, sin
from bokeh.models import LinearAxis, Range1d
from bokeh.plotting import figure, output_file, show
x = arange(-2 * pi, 2 * pi, 0.2)
y = sin(x)
y2 = linspace(0, 100, len(x))
p = figure(x_range=(-6.5, 6.5), y_range=(-1.1, 1.1), min_border=80)
p.background_fill_color = "#fafafa"
p.circle(x, y, color="crimson", size=8)
p.yaxis.axis_label = "red circles"
p.yaxis.axis_label_text_color = "crimson"
p.extra_y_ranges['foo'] = Range1d(0, 100)
p.circle(x, y2, color="navy", size=8, y_range_name="foo")
ax2 = LinearAxis(y_range_name="foo", axis_label="blue circles")
ax2.axis_label_text_color = "navy"
p.add_layout(ax2, 'left')
output_file("twin_axis.html", title="twin_axis.py example")
show(p)
# Create a new plot and add a renderer
top = Figure(tools=tools, title=None, x_range=day_range,
**figure_style_kws)
top.line('day', 'S', source=source,
line_color=colors[0], line_width=3, line_cap='round')
top.y_range = Range1d(0., 40.)
top.yaxis.axis_label = "Salinity (g/kg)"
top.xaxis.axis_label_text_font_size = label_fontsize
top.yaxis.axis_label_text_font_size = label_fontsize
# overlay volume level chart to salinity
tc = "MediumBlue" # tide color
tide_range = Range1d(start=0, end=15)
tide_axis = LinearAxis(y_range_name="Z")
tide_axis.axis_label = "Tidal Height (m)"
tide_axis.axis_label_text_color = tc
tide_axis.axis_label_text_font_size = label_fontsize
tide_axis.major_tick_line_color = tc
tide_axis.major_label_text_color = tc
tide_axis.minor_tick_line_alpha = 0.
top.extra_y_ranges = {"Z": tide_range}
# top.line('day', 'Z', source=source,
# line_color=tc, line_width=2, line_cap='round')
top.add_layout(tide_axis, "right")
top.line('day', 'Z', source=source,
line_color=tc, line_width=2, line_cap='round',
y_range_name="Z")
mid = Figure(title=None, x_range=top.x_range,
toolbar_location=None, **figure_style_kws)
def home():
ref_date = UtilsDatetime(Settings.query.first().current_month_date)
# Add day(s) to database if it does not exist yet.
days = Days.query.filter(Days.id >= ref_date.month_first_date).filter(
Days.id <= ref_date.month_last_date).all()
days_in_db = [day.id for day in days]
for day_index in ref_date.month_all_dates:
if day_index not in days_in_db:
db.session.add(Days(id=day_index))
db.session.commit()
days = Days.query.filter(Days.id >= ref_date.month_first_date).filter(
Days.id <= ref_date.month_last_date).all()
# Extra fields to display in row summary (_s)
row_with_totals = {
'ds': timedelta(),
'dev': timedelta(),
'pol': timedelta(),
'ge': timedelta(),
'crt': timedelta(),
'hs': timedelta()
}
cum_TargetHours = timedelta()
cum_TargetHours_till_today = timedelta()
cum_TotalProductive = timedelta()
cum_TotalNegative = timedelta()
cum_alk = 0
cum_days0 = 0
for i, day in enumerate(days, start=1):
# Target Productive Hours depending on weekday
day.s_TargetHours = Defaults.productive_hours_by_weekday(day.id)
# Total Productive Time
day.s_TotalProductive = timedelta(seconds=0)
for col in row_with_totals:
value = getattr(day, col)
if value is not None:
row_with_totals[col] += value
day.s_TotalProductive += value
# Total Negative from Alk
day.s_TotalNegative = timedelta(seconds=0)
if day.alk is not None:
day.s_TotalNegative = max(day.alk - 2.86,
0) * timedelta(minutes=20)
cum_alk += day.alk
if day.id <= date.today() and day.alk <= 0:
cum_days0 += 1
else:
if day.id <= date.today():
cum_days0 += 1
# % of target
day.s_PercOfTarget = (day.s_TotalProductive -
day.s_TotalNegative) / day.s_TargetHours
# Cummulative values
cum_TargetHours += day.s_TargetHours
if day.id <= date.today():
cum_TargetHours_till_today += day.s_TargetHours
cum_TotalProductive += day.s_TotalProductive
cum_TotalNegative += day.s_TotalNegative
day.cum_PercOfTarget = (cum_TotalProductive -
cum_TotalNegative) / cum_TargetHours
day.cum_alk = (cum_alk / i) / 7.8 * 750
# Styles:
# Rows with today's date
day.style_today_tr_hd = ""
day.style_today_tr_td = ""
if day.id == date.today():
day.style_today_tr_hd = "today_header"
day.style_today_tr_td = "today_cell"
day_of_month_for_statistics = get_day_of_month_for_avg_sja(
ref_date.month_first_date, ref_date.month_last_date)
row_with_totals['targethours'] = cum_TargetHours
row_with_totals['totalproductive'] = cum_TotalProductive
row_with_totals['totalnegative'] = cum_TotalNegative
row_with_totals['totalsja'] = round(cum_alk / day_of_month_for_statistics,
2)
row_with_totals['totalml'] = int(
round(row_with_totals['totalsja'] / 7.8 * 750, 0))
row_with_totals['totaldays0'] = cum_days0
# Planned till today
row_with_totals['targethours_tilltoday'] = cum_TargetHours_till_today
# Change current month settings
form_settings = EditSettings()
settings = Settings.query.first(
) # There is only one setting (one date of current month)
# MonthlyTargets
monthlytargets = MonthlyTargets.query.get(
date(year=settings.current_month_date.year,
month=settings.current_month_date.month,
day=1))
monthlytargets.ml = int(round(monthlytargets.alk / 7.8 * 750, 0))
monthlytargets.total_allocated = timedelta(seconds=sum([
getattr(monthlytargets, hrscol).total_seconds()
for hrscol in ['ds', 'dev', 'pol', 'ge', 'crt', 'hs']
]))
row_with_totals['ds_tilltoday'] = monthlytargets.ds * (
day_of_month_for_statistics / ref_date.month_last_date.day)
row_with_totals['dev_tilltoday'] = monthlytargets.dev * (
day_of_month_for_statistics / ref_date.month_last_date.day)
row_with_totals['pol_tilltoday'] = monthlytargets.pol * (
day_of_month_for_statistics / ref_date.month_last_date.day)
row_with_totals['ge_tilltoday'] = monthlytargets.ge * (
day_of_month_for_statistics / ref_date.month_last_date.day)
row_with_totals['crt_tilltoday'] = monthlytargets.crt * (
day_of_month_for_statistics / ref_date.month_last_date.day)
row_with_totals['hs_tilltoday'] = monthlytargets.hs * (
day_of_month_for_statistics / ref_date.month_last_date.day)
row_with_totals['total_tilltoday'] = timedelta(seconds=sum([
row_with_totals[f"{hrscol}_tilltoday"].total_seconds()
for hrscol in ['ds', 'dev', 'pol', 'ge', 'crt', 'hs']
]))
# Backlog (normal subtraction of timedelta does not work correctly if bigger is subtrackted from smaller object)
row_with_totals[
'ds_backlog'] = UtilsDataConversion.string_from_timedelta_subtraction(
row_with_totals['ds'], row_with_totals['ds_tilltoday'])
row_with_totals[
'dev_backlog'] = UtilsDataConversion.string_from_timedelta_subtraction(
row_with_totals['dev'], row_with_totals['dev_tilltoday'])
row_with_totals[
'pol_backlog'] = UtilsDataConversion.string_from_timedelta_subtraction(
row_with_totals['pol'], row_with_totals['pol_tilltoday'])
row_with_totals[
'ge_backlog'] = UtilsDataConversion.string_from_timedelta_subtraction(
row_with_totals['ge'], row_with_totals['ge_tilltoday'])
row_with_totals[
'crt_backlog'] = UtilsDataConversion.string_from_timedelta_subtraction(
row_with_totals['crt'], row_with_totals['crt_tilltoday'])
row_with_totals[
'hs_backlog'] = UtilsDataConversion.string_from_timedelta_subtraction(
row_with_totals['hs'], row_with_totals['hs_tilltoday'])
row_with_totals[
'total_backlog'] = UtilsDataConversion.string_from_timedelta_subtraction(
row_with_totals['totalproductive'],
row_with_totals['total_tilltoday'])
# Change displayed month
if request.method == 'POST':
settings.current_month_date = form_settings.current_month_date.data
# Check if monthly targets exist
targets_date = date(year=settings.current_month_date.year,
month=settings.current_month_date.month,
day=1)
if MonthlyTargets.query.get(targets_date) is None:
db.session.add(MonthlyTargets(id=targets_date))
db.session.commit()
return redirect(url_for('home'))
# Daily graph
y_alk_cum = [row.cum_alk for row in days]
y_alk_cum_text = [str(int(row.cum_alk)) for row in days]
y_score_cum = [row.cum_PercOfTarget for row in days]
y_score_cum_text = [
str(int(round(row.cum_PercOfTarget, 2) * 100)) for row in days
]
x_days = [i for i, day in enumerate(ref_date.month_all_dates, start=1)]
y_todaybar_top = [
max(y_alk_cum) if day == date.today() else None
for day in ref_date.month_all_dates
]
source = ColumnDataSource(data=dict(x_days=x_days,
y_alk_cum=y_alk_cum,
y_score_cum=y_score_cum,
y_score_cum_text=y_score_cum_text,
y_alk_cum_text=y_alk_cum_text,
y_todaybar_top=y_todaybar_top))
plot = figure(title='Daily Progress',
x_axis_label='day',
y_axis_label='ml cumm.%',
plot_width=600,
plot_height=400,
toolbar_location=None)
# Today selection
plot.vbar(x='x_days',
width=1,
top='y_todaybar_top',
source=source,
color='#98FB98',
alpha=0.5)
# Alk
plot.line(x='x_days', y='y_alk_cum', color="maroon", source=source)
plot.circle(x='x_days',
y='y_alk_cum',
color="maroon",
fill_color="white",
size=5,
source=source)
labels_alk = LabelSet(x='x_days',
y='y_alk_cum',
text='y_alk_cum_text',
text_font_size='10px',
text_color='maroon',
y_offset=5,
level='annotation',
source=source,
render_mode='canvas')
# Score
plot.extra_y_ranges['y_axis_for_target_perc'] = Range1d(
min(0, min(source.data.get('y_score_cum'))),
max(max(source.data.get('y_score_cum')), 1) * 1.05)
plot.line(x='x_days',
y='y_score_cum',
source=source,
color="cornflowerblue",
y_range_name='y_axis_for_target_perc')
plot.circle(x='x_days',
y='y_score_cum',
source=source,
color="cornflowerblue",
fill_color="white",
size=5,
y_range_name='y_axis_for_target_perc')
labels_score = LabelSet(x='x_days',
y='y_score_cum',
text='y_score_cum_text',
text_font_size='10px',
text_color='cornflowerblue',
y_offset=5,
y_range_name='y_axis_for_target_perc',
level='annotation',
source=source,
render_mode='canvas')
ax_right = LinearAxis(y_range_name="y_axis_for_target_perc",
axis_label="% of target cum.")
ax_right.axis_label_text_color = "blue"
plot.add_layout(ax_right, 'right')
plot.add_layout(labels_score)
plot.add_layout(labels_alk)
bokeh_daily_script, bokeh_daily_div = components(plot)
# Monthly graph
month_summary_table = MonthlyGraph(Days).df_months.to_html()
bokeh_monthly_script, bokeh_monthly_div = MonthlyGraph(
Days).bokeh_monthly_components
dataset_for_daily_tracking = DataSet(ref_date)
bokeh_tracking_time_script, bokeh_bracking_time_div = Graph.get_graph_components_tracking_daily_time(
dataset_for_daily_tracking.tracking_df_daily_datetime,
dataset_for_daily_tracking.tracking_current_score_series)
return render_template(
'home.html',
days=days,
f_string_from_duration=UtilsDataConversion.string_from_timedelta,
f_string_from_float=UtilsDataConversion.string_from_float_none,
form_settings=form_settings,
settings=settings,
monthlytargets=monthlytargets,
row_with_totals=row_with_totals,
bokeh_daily_script=bokeh_daily_script,
bokeh_daily_div=bokeh_daily_div,
f_round=round,
month_summary_table=month_summary_table,
bokeh_monthly_script=bokeh_monthly_script,
bokeh_monthly_div=bokeh_monthly_div,
bokeh_tracking_time_script=bokeh_tracking_time_script,
bokeh_bracking_time_div=bokeh_bracking_time_div)
