def _get_columns(self, element, data):
columns = []
for d in element.dimensions():
col = dimension_sanitizer(d.name)
kind = data[col].dtype.kind
if kind == 'i':
formatter = NumberFormatter()
editor = IntEditor()
elif kind == 'f':
formatter = NumberFormatter(format='0,0.0[00000]')
editor = NumberEditor()
elif kind == 'M' or (kind == 'O' and len(data[col])
and type(data[col][0]) in datetime_types):
dimtype = element.get_dimension_type(0)
dformat = Dimension.type_formatters.get(
dimtype, '%Y-%m-%d %H:%M:%S')
formatter = DateFormatter(format=dformat)
editor = DateEditor()
else:
formatter = StringFormatter()
editor = StringEditor()
column = TableColumn(field=dimension_sanitizer(d.name),
title=d.pprint_label,
editor=editor,
formatter=formatter)
columns.append(column)
return columns
def create(self):
self.sources['table'] = ColumnDataSource(dict(x=[], y=[]))
self.sources['background'] = ColumnDataSource(dict(x=[], y=[]))
columns = [
TableColumn(field="x", title="ppm", formatter=NumberFormatter(format="0.00")),
TableColumn(field="y", title="y", formatter=NumberFormatter(format="0.00"))
]
self.dataTable = DataTable(source=self.sources['table'], columns=columns, reorderable=False, width=500)
self.sources['table'].on_change('selected', lambda attr, old, new: self.rowSelect(new['1d']['indices']))
self.sources['table'].on_change('data', lambda attr, old, new: self.dataChanged(old, new))
self.manual = CustomButton(label="Manual Peaks", button_type="success", width=500, error="Please select area using the peak picking tool.")
self.manual.on_click(self.manualPeakPicking)
self.peak = CustomButton(label="Peak By Peak", button_type="primary", width=250, error="Please select area using the peak by peak tool.")
self.peak.on_click(self.peakByPeakPicking)
self.peakTool = CustomTapTool.Create(self.peak, tapTool=PeakByPeakTapTool, auto=True, id="peakByPeakTool")
self.createManualTool()
self.createDeselectButton()
self.createDeleteButton()
self.chemicalShiftReportTitle = Div(text="<strong>Chemical Shift Report</strong>" if getLabel(self.udic) == "13C" else "")
self.chemicalShiftReport = Paragraph(text=self.getChemicalShiftReport(), width=500)
def create(self):
self.sources['table'] = ColumnDataSource(
dict(xStart=[], xStop=[], top=[], bottom=[], integral=[]))
columns = [
TableColumn(field="xStart",
title="start",
editor=NumberEditor(step=0.01),
formatter=NumberFormatter(format="0.00")),
TableColumn(field="xStop",
title="stop",
editor=NumberEditor(step=0.01),
formatter=NumberFormatter(format="0.00")),
TableColumn(field="integral",
title="integral",
editor=NumberEditor(step=0.01),
formatter=NumberFormatter(format="0.00"))
]
self.dataTable = DataTable(source=self.sources['table'],
columns=columns,
reorderable=False,
width=500,
editable=True)
self.sources['table'].on_change(
'selected',
lambda attr, old, new: self.rowSelect(new['1d']['indices']))
self.sources['table'].on_change(
'data', lambda attr, old, new: self.changeData(old, new))
self.manual = CustomButton(
label="Manual Integration",
button_type="primary",
width=250,
error="Please select area using the integration tool.")
self.manual.on_click(self.manualIntegration)
self.createDeselectButton()
self.createDeleteButton()
callback = CustomJS(args=dict(button=self.manual),
code="""
/// get BoxSelectTool dimensions from cb_data parameter of Callback
var geometry = cb_data['geometry'];
button.data = {
x0: geometry['x0'],
x1: geometry['x1'],
y0: geometry['y0'],
y1: geometry['y1']
};
// Callback to the backend
button.clicks++;
""")
self.tool = CustomBoxSelectTool(tool_name="Integration",
icon="my_icon_integration",
dimensions="width",
callback=callback,
id="integrationTool")
def initialize_plot(self, ranges=None, plot=None, plots=None, source=None):
"""
Initializes a new plot object with the last available frame.
"""
# Get element key and ranges for frame
element = self.hmap.last
key = self.keys[-1]
self.current_frame = element
self.current_key = key
style = self.lookup_options(element, 'style')[self.cyclic_index]
data, _, style = self.get_data(element, ranges, style)
if source is None:
source = self._init_datasource(data)
self.handles['source'] = source
columns = []
dims = element.dimensions()
for d in dims:
col = dimension_sanitizer(d.name)
kind = data[col].dtype.kind
if kind == 'i':
formatter = NumberFormatter()
editor = IntEditor()
elif kind == 'f':
formatter = NumberFormatter(format='0,0.0[00000]')
editor = NumberEditor()
elif kind == 'M' or (kind == 'O' and len(data[col])
and type(data[col][0]) in datetime_types):
dimtype = element.get_dimension_type(0)
dformat = Dimension.type_formatters.get(
dimtype, '%Y-%m-%d %H:%M:%S')
formatter = DateFormatter(format=dformat)
editor = DateEditor()
else:
formatter = StringFormatter()
editor = StringEditor()
column = TableColumn(field=d.name,
title=d.pprint_label,
editor=editor,
formatter=formatter)
columns.append(column)
style['reorderable'] = False
table = DataTable(source=source,
columns=columns,
height=self.height,
width=self.width,
**style)
self.handles['plot'] = table
self.handles['glyph_renderer'] = table
self._execute_hooks(element)
self.drawn = True
for cb in self.callbacks:
cb.initialize()
return table
def get_leaderboard(self):
source = ColumnDataSource(self.ratings)
float_formatter = NumberFormatter(format='0,0.00')
percentage_formatter = NumberFormatter(format='0.0%')
columns = []
for col_name in self.ratings.columns:
col_title = col_name
formatter = float_formatter
if col_name == 'num_games':
col_title = '# Games'
elif col_name == 'rating_lb':
col_title = 'Rating (Lowerbound)'
elif col_name == 'rating':
col_title = 'Rating'
elif 'vs_' in col_name:
continue
elif col_name == 'vs_med':
col_title = "Expected point diff vs median"
formatter = percentage_formatter
elif col_name == 'vs_mean':
col_title = "Expected point diff vs mean"
formatter = percentage_formatter
elif col_name == 'vs_best':
col_title = "Expected point diff vs best"
formatter = percentage_formatter
elif col_name == 'ppg_vs_mean':
col_title = 'Expected points per game vs mean'
formatter = percentage_formatter
elif col_name == 'avg_rating_diff':
col_title = 'Average ratings advantage'
elif col_name == 'rank_lb':
col_title = 'Rank (Lowerbound)'
elif col_name == 'rank_pure':
col_title = 'Rank (Pure)'
col_type = self.ratings[col_name].dtype
if str(col_type) == 'int64':
column = TableColumn(field=col_name, title=col_title)
elif str(col_type) == 'float64':
column = TableColumn(field=col_name,
title=col_title,
formatter=formatter)
else:
raise Exception("Unknown column type!")
columns.append(column)
columns = [TableColumn(field='name', title='Username')] + columns
data_table = DataTable(columns=columns,
index_position=None,
source=source,
width=1620)
return data_table
def __init__(self, **kwargs):
names = ['processes', 'disk-read', 'cores', 'cpu', 'disk-write',
'memory', 'last-seen', 'memory_percent', 'host']
self.source = ColumnDataSource({k: [] for k in names})
columns = {name: TableColumn(field=name,
title=name.replace('_percent', ' %'))
for name in names}
cnames = ['host', 'cores', 'processes', 'memory', 'cpu', 'memory_percent']
formatters = {'cpu': NumberFormatter(format='0.0 %'),
'memory_percent': NumberFormatter(format='0.0 %'),
'memory': NumberFormatter(format='0 b'),
'latency': NumberFormatter(format='0.00000'),
'last-seen': NumberFormatter(format='0.000'),
'disk-read': NumberFormatter(format='0 b'),
'disk-write': NumberFormatter(format='0 b'),
'net-send': NumberFormatter(format='0 b'),
'net-recv': NumberFormatter(format='0 b')}
table = DataTable(
source=self.source, columns=[columns[n] for n in cnames],
)
for name in cnames:
if name in formatters:
table.columns[cnames.index(name)].formatter = formatters[name]
mem_plot = Plot(
title=Title(text="Memory Usage (%)"), toolbar_location=None,
x_range=Range1d(start=0, end=1), y_range=Range1d(start=-0.1, end=0.1),
**kwargs
)
mem_plot.add_glyph(
self.source,
Circle(x='memory_percent', y=0, size=10, fill_alpha=0.5)
)
mem_plot.add_layout(LinearAxis(), 'below')
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
<div>
<span style="font-size: 10px; font-family: Monaco, monospace;">@host: </span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory_percent</span>
</div>
"""
)
mem_plot.add_tools(hover, BoxSelectTool())
if 'sizing_mode' in kwargs:
sizing_mode = {'sizing_mode': kwargs['sizing_mode']}
else:
sizing_mode = {}
self.root = column(mem_plot, table, id='bk-worker-table', **sizing_mode)
def make_statistics_table(metrics):
with open (join(dirname(__file__), 'data/metrics.j')) as filehandle:
metrics = json.load(filehandle)
source = ColumnDataSource(data=dict())
source.data = metrics
columns = [
TableColumn(field="Metric", title="Metric"),
TableColumn(field="Reads", title="Reads", formatter=NumberFormatter(format="0,0")),
TableColumn(field="Contigs", title="Contigs", formatter=NumberFormatter(format="0,0")),
TableColumn(field="Genes", title="Genes", formatter=NumberFormatter(format="0,0"))
]
data_table = DataTable(source=source, columns=columns, width=600)
return data_table
def metrics_to_table(metrics_df):
metric_formats = OrderedDict([('n_trades', '0'), ('n_win', '0'),
('n_loss', '0'), ('hit_ratio', '0.000'),
('avg_trade_win', '0.0000'),
('avg_trade_loss', '0.0000'),
('unit_return', '0.000'),
('total_pnl', '0.00'), ('cr_trade', '0.000'),
('cr_day', '0.000'), ('cum_ret', '0.000'),
('vol_not_ann', '0.000'),
('sharpe_ratio', '0.000'),
('max_drawdown', '0.000'),
('drawdown_days', '0'),
('max_runup', '0.000'), ('runup_days', '0'),
('time_in_market', '0.000'),
('rina', '0.000')])
# Add table of metrics
s = ColumnDataSource(metrics_df)
tbl_columns = [TableColumn(field='run_label', title='run', width=100)]
tbl_columns += [
TableColumn(field=mm,
title=mm,
width=100,
formatter=NumberFormatter(format=fmt))
for mm, fmt in metric_formats.iteritems() if mm in metrics_df.columns
]
data_table = DataTable(source=s,
columns=tbl_columns,
width=900,
height=200,
fit_columns=False)
return data_table
def make_page_flow(doc):
# return make_document(doc)
# if __name__=='__main__':
# df = pd.read_csv('salary_data.csv')
# else:
# # df = pd.read_csv('./bokeh_pages/salary_data.csv')
df = pd.read_csv(fileName_csv_source)
#
source = ColumnDataSource(data=dict())
def update():
print ("slider update")
# current = df[df['salary'] <= slider.value].dropna() # df ##
# adjustment by https://groups.google.com/a/continuum.io/forum/#!topic/bokeh/fPAoHTyMcuQ
current = df[df['salary'] <= slider.value].dropna() # df ##
# print (list(current.name))
# print (type(current.salary)) # <class 'pandas.core.series.Series'>
# print (type(current.years_experience))
source.data = {
'name' : list(current.name),
'salary' : list(current.salary),
'years_experience' : list(current.years_experience),
}
slider = Slider(title="values range", start=0, end=100000, value=20000, step=1)
slider.on_change('value', lambda attr, old, new: update())
def on_button_change():
print("visiting on button change")
button = Button(label="Phase #1 ", button_type="success") # button_type: ‘default’, ‘primary’, ‘success’, ‘warning’, ‘danger’, ‘link’
button.on_click(on_button_change)
# button.callback = CustomJS(args=dict(source=source),
# code=open(join(dirname(__file__), "download.js")).read())
columns = [
TableColumn(field="name", title="Employee Name"),
TableColumn(field="salary", title="Income", formatter=NumberFormatter(format="$0,0.00")),
TableColumn(field="years_experience", title="Experience (years)")
]
data_table = DataTable(source=source, columns=columns, width=800)
controls = widgetbox(slider, button)
table = widgetbox(data_table)
total_row = row(controls, table)
doc_add_root(doc, total_row, title = 'work flow page')
# if __name__!='__main__':
# print("doc : ", str(doc))
# print("name : ",__name__)
# doc().add_root(row(controls, table))
# doc().title = "work flow page, from caller"
# elif __name__=='__main__':
# print("doc : ", str(doc))
# doc.add_root(row(controls, table))
# doc.title = "work flow page, from main"
update()
def outcome(width, height):
df = pd.read_sql(
"""SELECT [A].[COL], [A].[VALUE]
FROM
(
SELECT [T1].[Koszt], [T1].[Wartość], [T2].[Przychody], [T3].[Premium]
FROM
(SELECT -SUM([CURR_COST]) AS [Koszt], SUM([CURR_VALUE]) AS [Wartość] FROM [PORTFEL_VW]) AS [T1],
(SELECT SUM([SEC_VALUE]) AS [Przychody] FROM [TRANSAKCJE] WHERE [POZYCJA] IN (2,3)) AS [T2],
(SELECT [ROK], SUM([VAL]) AS [Premium] FROM [PREMIUM_VW] WHERE [ROK] = YEAR(GETDATE()) GROUP BY [ROK]) AS [T3]) AS [T]
CROSS APPLY (VALUES ('Koszt', [Koszt]),
('Wartość',[Wartość]),
('Bilans',[Koszt] + [Wartość]),
('Przychody',[Przychody]),
('Wynik',[Koszt] + [Wartość] + [Przychody]),
('Przychody w tym roku',[Premium]),
('ROI',-[Premium]/[Koszt]*100)
) AS [A] ([COL],[VALUE])""", conn)
#dane
source = ColumnDataSource(data=df)
#kolumny
columns = [
TableColumn(field="COL", title='Podsumowanie'),
TableColumn(field="VALUE",
title='',
width=int(width / 2 * 3),
formatter=NumberFormatter(format='(0,0.00)'))
]
#tabela
t = DataTable(source=source, columns=columns, width=width, height=height)
t = finalize_table(t, True, False, False, False)
return t
def plot_data(train_loss, test_loss, lr_values, file_name):
output_file(file_name)
f = figure()
f.title.text = "Loss"
f.plot_width = 640
f.plot_height = 480
epoches, train_losses = zip(*train_loss)
_, test_losses = zip(*test_loss)
_, learning_rates = zip(*lr_values)
f.line(epoches, train_losses, color='blue', legend="Train loss", line_width=2)
f.line(epoches, test_losses, color='red', legend="Test loss", line_width=2)
f.xaxis.axis_label = "Epoch"
f.yaxis.axis_label = "LogLoss"
f_lr = figure()
f_lr.title.text = "Learning rate"
f_lr.plot_width = 640
f_lr.plot_height = 480
f_lr.line(epoches, learning_rates, color='blue', legend="LR", line_width=2)
f_lr.xaxis.axis_label = "Epoch"
# table with data
source = ColumnDataSource({
'epoch': epoches,
'train_loss': train_losses,
'test_loss': test_losses,
'lr': learning_rates
})
columns = [
TableColumn(field='epoch', title='Epoch'),
TableColumn(field='train_loss', title='Train loss', formatter=NumberFormatter(format="0.0000")),
TableColumn(field='test_loss', title='Test loss', formatter=NumberFormatter(format="0.0000")),
TableColumn(field='lr', title='LR', formatter=NumberFormatter(format="0.0000")),
]
data_table = DataTable(source=source, columns=columns, width=1200, height=600)
save(column(row(f, f_lr), data_table))
def tabular(self): os.chdir(self.sa) DF_ag=NumberFormatter(format="0.00") columns = [ TableColumn(field="t", title="Tiempo"), TableColumn(field="al",title="Elevación (Grados)",formatter=DF_ag,sortable=True), TableColumn(field="az",title="Azimut (Grados)",formatter=DF_ag,sortable=True) ] data_table = DataTable(source=self.source, columns=columns ,width=450, height=450) save(data_table,"data_table.html",validate=True) os.chdir(self.raiz)
def _create_top_services_tbl():
"""Creates top services table"""
global GLOBAL_SUB_SERVICE_GRP
global GLOBAL_TOP_SERVICE_SOURCE
# Top services table
cols = []
for col in GLOBAL_SUB_SERVICE_GRP.columns:
if col == CONST_COL_NAME_COST:
cols.append(
TableColumn(
field=col,
title=col,
formatter=NumberFormatter(format="$0,0[.]00",
text_align="right",
language="it"),
width=100,
))
elif col == CONST_COL_NAME_PERC:
cols.append(
TableColumn(
field=col,
title=col,
formatter=NumberFormatter(format="0,0[.]00%",
text_align="right",
language="it"),
width=50,
))
elif col in [CONST_COL_NAME_ANGLE, "color"]:
continue
else:
cols.append(TableColumn(field=col, title=col))
top_services_table = DataTable(columns=cols,
source=GLOBAL_TOP_SERVICE_SOURCE,
width=400)
return top_services_table
def _get_columns(self):
if self.value is None:
return []
index = [self.value.index.name or 'index']
col_names = index + list(self.value.columns)
columns = []
for col in col_names:
if col in self.value.columns:
data = self.value[col]
else:
data = self.value.index
kind = data.dtype.kind
if kind == 'i':
formatter = NumberFormatter()
editor = IntEditor()
elif kind == 'f':
formatter = NumberFormatter(format='0,0.0[00000]')
editor = NumberEditor()
elif isdatetime(data) or kind == 'M':
formatter = DateFormatter(format='%Y-%m-%d %H:%M:%S')
editor = DateEditor()
else:
formatter = StringFormatter()
editor = StringEditor()
if col in self.editors:
editor = self.editors[col]
if col in self.formatters:
formatter = self.formatters[col]
if str(col) != col:
self._renamed_cols[str(col)] = col
width = self.widths.get(str(col))
column = TableColumn(field=str(col),
title=str(col),
editor=editor,
formatter=formatter,
width=width)
columns.append(column)
return columns
def divdeamon(width, height):
df = pd.read_sql(
"""WITH [N] AS (
SELECT [ISIN], [ZAMKNIECIE] FROM [NOTOWANIA_GPW]
WHERE [DATA] = (SELECT MAX(DATA) FROM [NOTOWANIA_GPW])
)
SELECT [D].[DATA_PRAW] AS [TERMIN], [D].[NAZWA], [D].[ISIN], [D].[DATA_WYP] AS [WYPŁATA], [D].[VAL] AS [DYWIDENDA], [N].[ZAMKNIECIE] AS [KURS], [D].[VAL] / [N].[ZAMKNIECIE] AS [%]
FROM [DYWIDENDY] AS [D], [N]
WHERE [D].[ISIN] = [N].[ISIN]
AND [D].[DATA_PRAW] < DATEADD(DAY, 30, GETDATE())
AND [D].[DATA_PRAW] > DATEADD(DAY, 3, GETDATE())
ORDER BY [D].[DATA_PRAW]""", conn)
#dane
source = ColumnDataSource(data=df)
#kolumny
columns = [
TableColumn(field="TERMIN", title="Termin", width=125),
TableColumn(field="NAZWA", title="Spółka"),
TableColumn(field="ISIN", title="ISIN", width=200),
TableColumn(field="WYPŁATA", title="Data wypłaty", width=125),
TableColumn(field="DYWIDENDA",
title="Dywidenda",
formatter=NumberFormatter(format='0.00'),
width=85),
TableColumn(field="KURS",
title="Kurs",
formatter=NumberFormatter(format='0.00'),
width=65),
TableColumn(field="%",
title="%",
formatter=NumberFormatter(format='0.00%'),
width=65),
]
#tabela
t = DataTable(source=source, columns=columns, width=width, height=height)
t = finalize_table(t, True, False, False, True)
return t
def gen_data_table(df, chart_width):
'''
Generate data into DataTable format
'''
# Uniquify by real_time and op_group page
df = df.loc[df.sub_type == 'FullOp', [
'op_group', 'sub_type', 'cpu_time', 'real_time', 'runtime_ratio',
'scale_factor', 'lvheap_used', 'lvheap_allocated', 'shared_used'
]]
df = df.drop_duplicates()
# Show Top 20 rows
df = df.sort_values(by="real_time", ascending=False)
df = df.head(20)
data = dict(df[[
'op_group', 'sub_type', 'cpu_time', 'real_time', 'runtime_ratio',
'scale_factor', 'lvheap_used', 'lvheap_allocated', 'shared_used'
]]) #, 'fec', 'fgc', 'hec', 'hgc']])
source = ColumnDataSource(data)
columns = [
TableColumn(field='op_group', title='Name'),
TableColumn(field='sub_type', title='Sub-Op Type'),
TableColumn(field='cpu_time', title='CPU time'),
TableColumn(field='real_time', title='Real time'),
TableColumn(field='runtime_ratio',
title='Runtime ratio',
formatter=NumberFormatter(format="0.00")),
TableColumn(field='scale_factor',
title='Scale factor',
formatter=NumberFormatter(format="0.00")),
TableColumn(field='lvheap_used', title='LVHEAP used'),
TableColumn(field='lvheap_allocated', title='LVHEAP allocated'),
TableColumn(field='shared_used', title='Shared used'),
]
return DataTable(source=source, columns=columns, width=chart_width)
def tabela_orcamento(source_gastos, gastos_cols, gastos_cols_titles,
plot_width):
columns_gastos = [
TableColumn(field=col, title=title) for col, title in zip(
gastos_cols,
gastos_cols_titles,
)
]
columns_gastos[-1].formatter = NumberFormatter(format='0,0.00',
language='pt-br',
text_align='right')
columns_gastos[-2].formatter = NumberFormatter(format='0,0.00',
language='pt-br',
text_align='right')
tabela = DataTable(
source=source_gastos,
columns=columns_gastos,
row_headers=False,
fit_columns=True,
width=plot_width,
)
return tabela
def create_table(source_data):
""" Creates a table from the source data """
decimal_formatter = NumberFormatter(format='0.0')
columns = [
TableColumn(field="ids", title="Id"),
TableColumn(field="x", title="X", formatter=decimal_formatter),
TableColumn(field="y", title="Y", formatter=decimal_formatter),
TableColumn(field="names", title="Name"),
TableColumn(field="phones", title="Phone"),
TableColumn(field="color", title="Color"),
]
data_table = DataTable(source=source_data, columns=columns, width=400, height=280)
return data_table
def make_page_flow(doc):
# return make_document(doc)
# if __name__=='__main__':
# df = pd.read_csv('salary_data.csv')
# else:
# # df = pd.read_csv('./bokeh_pages/salary_data.csv')
df = pd.read_csv(fileName)
#
source = ColumnDataSource(data=dict())
def update():
print ("slider update")
current = df[df['salary'] <= slider.value].dropna() # df ##
source.data = {
'name' : current.name,
'salary' : current.salary,
'years_experience' : current.years_experience,
}
slider = Slider(title="values range", start=0, end=100000, value=50000, step=1)
slider.on_change('value', lambda attr, old, new: update())
def on_button_change():
print("visiting on button change")
button = Button(label="phase #1 ", button_type="success") # button_type: ‘default’, ‘primary’, ‘success’, ‘warning’, ‘danger’, ‘link’
button.on_click(on_button_change)
# button.callback = CustomJS(args=dict(source=source),
# code=open(join(dirname(__file__), "download.js")).read())
columns = [
TableColumn(field="name", title="Employee Name"),
TableColumn(field="salary", title="Income", formatter=NumberFormatter(format="$0,0.00")),
TableColumn(field="years_experience", title="Experience (years)")
]
data_table = DataTable(source=source, columns=columns, width=800)
controls = widgetbox(slider, button)
table = widgetbox(data_table)
if __name__!='__main__':
print("doc : ", doc)
print("name : ",__name__)
doc().add_root(row(controls, table))
doc().title = "work flow page, from caller"
elif __name__=='__main__':
doc.add_root(row(controls, table))
doc.title = "work flow page, from main"
# if __name__=='__main__':
update()
def __define_layout_objects(self):
# Report heading data
self.select_plan = Select(title='Plan:', width=400)
self.button_refresh_plans = Button(label='Scan DICOM Inbox', button_type='primary')
self.select_protocol = Select(title='Protocol:', options=self.protocols.protocol_names, value='TG101', width=150)
self.select_fx = Select(title='Fractions:', value='3', options=self.fractionation_options, width=60)
self.button_calculate = Button(label='Calculate Scorecard', button_type='primary')
self.button_delete_roi = Button(label='Delete Constraint', button_type='warning')
self.button_calculate_dvhs = Button(label='Calculate DVHs', button_type='primary', width=200)
self.select_roi_template = Select(title='Template ROI:')
self.select_roi = Select(title='Plan ROI:')
self.max_dose_volume = Div(text="<b>Point defined as %scc" % MAX_DOSE_VOLUME)
self.columns = [TableColumn(field="roi_template", title="Template ROI"),
TableColumn(field="roi_name", title="ROI"),
TableColumn(field='volume', title='Volume (cc)', formatter=NumberFormatter(format="0.00")),
TableColumn(field='min_dose', title='Min Dose (Gy)', formatter=NumberFormatter(format="0.00")),
TableColumn(field='mean_dose', title='Mean Dose (Gy)', formatter=NumberFormatter(format="0.00")),
TableColumn(field='max_dose', title='Max Dose (Gy)', formatter=NumberFormatter(format="0.00")),
TableColumn(field='constraint', title='Constraint'),
TableColumn(field='constraint_calc', title='Value', formatter=NumberFormatter(format="0.00")),
TableColumn(field='pass_fail', title='Pass/Fail', formatter=self.__pass_fail_formatter)]
self.data_table = DataTable(source=self.source_data, columns=self.columns, index_position=None,
width=1000, height=300)
tools = "pan,wheel_zoom,box_zoom,reset,crosshair,save"
self.plot = figure(plot_width=800, plot_height=475, tools=tools, active_drag="box_zoom")
# Set x and y axis labels
self.plot.xaxis.axis_label = "Dose (Gy)"
self.plot.yaxis.axis_label = "Normalized Volume"
self.plot.min_border_left = 60
self.plot.min_border_bottom = 60
self.plot.add_tools(HoverTool(show_arrow=False, line_policy='next',
tooltips=[('Plan ROI', '@roi'),
('Dose', '$x'),
('Volume', '$y')]))
self.plot.xaxis.axis_label_text_font_size = "12pt"
self.plot.yaxis.axis_label_text_font_size = "12pt"
self.plot.xaxis.major_label_text_font_size = "10pt"
self.plot.yaxis.major_label_text_font_size = "10pt"
self.plot.yaxis.axis_label_text_baseline = "bottom"
self.plot.lod_factor = 100 # level of detail during interactive plot events
self.plot.multi_line('x', 'y', source=self.source_plot,
selection_color='color', line_width=3, alpha=0,
line_dash='solid', nonselection_alpha=0, selection_alpha=1)
columns = [TableColumn(field="roi", title="Select Structures to Plot")]
self.plot_rois = DataTable(source=self.source_plot, columns=columns, index_position=None,
width=200, height=350)
def __init__(self,data):
tfmt = DateFormatter(format="%M:%S")
tfmt = NumberFormatter(format="00:00:00")
self.metadata = [
self.generateTableMetadataEntry(field="name", title="Time",width=3,formatter=tfmt),
self.generateTableMetadataEntry(field="lyrics", title="Lyrics",width=50),
]
dictionary = {
"title":"Lyrics",
"data":data,
"metadata":self.metadata
}
self.createTable(dictionary)
def convert_df(df):
columns = []
for column in df.columns:
if df.dtypes[column].kind == 'f':
formatter = NumberFormatter(format='0.000')
else:
formatter = None
table_col = TableColumn(field=column,
title=column,
formatter=formatter)
columns.append(table_col)
data_table = DataTable(columns=columns,
source=ColumnDataSource(df),
height=200)
return data_table
def worker_table_plot(width=600, height="auto", **kwargs):
""" Column data source and plot for host table """
names = [
'workers', 'cpu', 'memory-percent', 'memory', 'cores', 'processes',
'processing', 'latency', 'last-seen', 'disk-read', 'disk-write',
'network-send', 'network-recv'
]
source = ColumnDataSource({k: [] for k in names})
columns = {name: TableColumn(field=name, title=name) for name in names}
slow_names = [
'workers', 'cores', 'processes', 'memory', 'latency', 'last-seen'
]
slow = DataTable(source=source,
columns=[columns[n] for n in slow_names],
width=width,
height=height,
**kwargs)
slow.columns[3].formatter = NumberFormatter(format='0.0 b')
slow.columns[4].formatter = NumberFormatter(format='0.00000')
slow.columns[5].formatter = NumberFormatter(format='0.000')
fast_names = [
'workers', 'cpu', 'memory-percent', 'processing', 'disk-read',
'disk-write', 'network-send', 'network-recv'
]
fast = DataTable(source=source,
columns=[columns[n] for n in fast_names],
width=width,
height=height,
**kwargs)
fast.columns[1].formatter = NumberFormatter(format='0.0 %')
fast.columns[2].formatter = NumberFormatter(format='0.0 %')
fast.columns[4].formatter = NumberFormatter(format='0 b')
fast.columns[5].formatter = NumberFormatter(format='0 b')
fast.columns[6].formatter = NumberFormatter(format='0 b')
fast.columns[7].formatter = NumberFormatter(format='0 b')
table = vplot(slow, fast)
return source, table
def make_plot(self, dataframe):
self.source = ColumnDataSource(data=dataframe)
self.title = Paragraph(text=TITLE)
self.data_table = DataTable(
source=self.source,
width=390,
height=275,
columns=[
TableColumn(field="zipcode", title="Zipcodes", width=100),
TableColumn(field="population",
title="Population",
width=100,
formatter=NumberFormatter(format="0,0")),
TableColumn(field="city", title="City")
])
return column(self.title, self.data_table)
def update():
var = 'newsalaryperfte'
if selectVariable.value == 'Previous Salary (AY 2016-2017)':
var = 'cursalaryperfte'
campus = selectCampus.value
if campus == 'All': campusSelection = (salaries.campus == salaries.campus)
else: campusSelection = (salaries.campus == campus)
college = selectCollege.value
if college == 'All':
collegeSelection = (salaries.college == salaries.college)
else:
collegeSelection = (salaries.college == college)
def p25(x):
return x.quantile(0.25)
def p75(x):
return x.quantile(0.75)
df = salaries.loc[campusSelection & collegeSelection].groupby([
'campus', 'college', 'dept'
])[var].agg(['size', 'count', 'min', p25, 'median', p75, 'max',
gini]).reset_index()
columns = [
TableColumn(field='campus', title='Campus'),
TableColumn(field='college', title='College'),
TableColumn(field='dept', title='Department'),
TableColumn(field='size', title='# of Employees'),
TableColumn(field='count', title='# with Data'),
TableColumn(field='min',
title='Min',
formatter=NumberFormatter(format="$0,0")),
TableColumn(field='p25',
title='25th Percentile',
formatter=NumberFormatter(format="$0,0")),
TableColumn(field='median',
title='Median',
formatter=NumberFormatter(format="$0,0")),
TableColumn(field='p75',
title='75th Percentile',
formatter=NumberFormatter(format="$0,0")),
TableColumn(field='max',
title='Max',
formatter=NumberFormatter(format="$0,0")),
TableColumn(field='gini',
title='Gini Coefficient',
formatter=NumberFormatter(format="0.000")),
]
# Note: there is a bug where the last row of the DataTable cuts off. This appears to be a bug in Bokeh to which there is currently no workaround.
l.children[2] = DataTable(source=ColumnDataSource(df),
columns=columns,
height=650,
width=1600,
selectable=True,
scroll_to_selection=True)
def _build_optresult_selector(self, optresults):
# 1. build a dict with all params and all user columns
data_dict = defaultdict(list)
for optres in optresults:
for param_name, _ in optres[0].params._getitems():
param_val = optres[0].params._get(param_name)
data_dict[param_name].append(param_val)
for usercol_label, usercol_fnc in self._usercolumns.items():
data_dict[usercol_label].append(usercol_fnc(optres))
# 2. build a pandas DataFrame
df = DataFrame(data_dict)
# 3. now sort and limit result
if self._sortcolumn is not None:
df = df.sort_values(by=[self._sortcolumn], ascending=self._sortasc)
if self._num_result_limit is not None:
df = df.head(self._num_result_limit)
# 4. build column info for Bokeh table
tab_columns = []
for colname in data_dict.keys():
formatter = NumberFormatter(format='0.000')
if (len(data_dict[colname]) > 0
and isinstance(data_dict[colname][0], int)):
formatter = StringFormatter()
tab_columns.append(
TableColumn(field=colname,
title=f'{colname}',
sortable=False,
formatter=formatter))
cds = ColumnDataSource(df)
selector = DataTable(
source=cds,
columns=tab_columns,
height=150, # fixed height for selector
width=0, # set width to 0 so there is no min_width
sizing_mode='stretch_width',
fit_columns=True)
return selector, cds
def make_table():
if __name__ == '__main__':
df = pd.read_csv('salary_data.csv')
else:
# df = pd.read_csv('./bokeh_pages/salary_data.csv')
df = pd.read_csv('salary_data.csv')
source = ColumnDataSource(data=dict())
def update():
current = df[df['salary'] <= slider.value].dropna()
source.data = {
'name': current.name,
'salary': current.salary,
'years_experience': current.years_experience,
}
slider = Slider(title="Max Salary",
start=10000,
end=250000,
value=150000,
step=1000)
slider.on_change('value', lambda attr, old, new: update())
button = Button(label="Download", button_type="success")
button.callback = CustomJS(args=dict(source=source),
code=open(join(dirname(__file__),
"download.js")).read())
columns = [
TableColumn(field="name", title="Employee Name"),
TableColumn(field="salary",
title="Income",
formatter=NumberFormatter(format="$0,0.00")),
TableColumn(field="years_experience", title="Experience (years)")
]
data_table = DataTable(source=source, columns=columns, width=800)
controls = widgetbox(slider, button)
table = widgetbox(data_table)
curdoc().add_root(row(controls, table))
curdoc().title = "Export CSV"
update()
def wallettable(width, height):
#kwerenda do wyciągania przychodów
df = pd.read_sql("""SELECT * FROM [PORTFEL_VW]""", conn)
#dane
source = ColumnDataSource(data=df)
#formatowanie warunkowe
cndtemplate = """
<div style="color:<%=
(function colorfromint(){
if(value < 0){
return("red")}
else{return("green")}
}()) %>">
<%= (value).toFixed(2) %></div>
"""
cndformatter = HTMLTemplateFormatter(template=cndtemplate)
#kolumny
columns = [
TableColumn(field="NAZWA", title="Nazwa"),
TableColumn(field="CURR_COUNT", title="Pakiet"),
TableColumn(field="PUR_PRICE",
title="Zakup",
formatter=NumberFormatter(format='0,0.00')),
TableColumn(field="PRICE_TODAY",
title="Obecnie",
formatter=NumberFormatter(format='0,0.00')),
TableColumn(field="PRICE_MIN",
title="Próg",
formatter=NumberFormatter(format='0,0.00')),
TableColumn(field="CURR_COST",
title="Koszt całk.",
formatter=NumberFormatter(format='0,0.00')),
TableColumn(field="CURR_VALUE",
title="Wart. całk.",
formatter=NumberFormatter(format='0,0.00')),
TableColumn(field="TAX",
title="Podatek",
formatter=NumberFormatter(format='0,0.00')),
TableColumn(field="YIELD", title="Zysk", formatter=cndformatter),
TableColumn(field="%",
title="%",
formatter=NumberFormatter(format='0,0.00%'))
]
#tabela
t = DataTable(source=source, columns=columns, width=width, height=height)
t = finalize_table(t, True, False, False, False)
return t
def _build_optresult_selector(
self, optresults) -> Tuple[DataTable, ColumnDataSource]:
# 1. build a dict with all params and all user columns
data_dict = defaultdict(list)
for optres in optresults:
for param_name, _ in optres[0].params._getitems():
param_val = optres[0].params._get(param_name)
data_dict[param_name].append(param_val)
for usercol_label, usercol_fnc in self._usercolumns.items():
data_dict[usercol_label].append(usercol_fnc(optres))
# 2. build a pandas DataFrame
df = DataFrame(data_dict)
# 3. now sort and limit result
if self._sortcolumn is not None:
df = df.sort_values(by=[self._sortcolumn], ascending=self._sortasc)
if self._num_result_limit is not None:
df = df.head(self._num_result_limit)
# 4. build column info for Bokeh table
tab_columns = []
for colname in data_dict.keys():
formatter = NumberFormatter(format='0.000')
if len(data_dict[colname]) > 0 and isinstance(
data_dict[colname][0], int):
formatter = StringFormatter()
tab_columns.append(
TableColumn(field=colname,
title=f'{colname}',
sortable=False,
formatter=formatter))
# TODO: currently table size is hardcoded
cds = ColumnDataSource(df)
selector = DataTable(source=cds,
columns=tab_columns,
width=1600,
height=150)
return selector, cds
def common_table(df: DataFrame):
logger.debug('Common table')
ddf = df.Игра.groupby(df.Результат).count().to_frame()
source = ColumnDataSource(
data=dict(y=ddf.index.values,
fights_count=ddf.values,
skill_sum=df.Скилл.groupby(df.Результат).sum().values))
columns = [
TableColumn(field="y", title="Результат"),
TableColumn(field="fights_count", title="Количество"),
TableColumn(field="skill_sum",
title="Суммарный скилл",
formatter=NumberFormatter(format="0.0"))
]
data_table = DataTable(source=source, columns=columns, width=800)
return data_table