本文整理汇总了Python中bokeh.models.widgets.DataTable方法的典型用法代码示例。如果您正苦于以下问题:Python widgets.DataTable方法的具体用法?Python widgets.DataTable怎么用?Python widgets.DataTable使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类bokeh.models.widgets
的用法示例。
在下文中一共展示了widgets.DataTable方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: modify_document
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def modify_document(self, doc):
controller = self.network.notes[0]
notes_df = pd.DataFrame(self.network.notes[1]).reset_index()
notes_df.columns = ["index", "notes"]
notes = ColumnDataSource(notes_df)
self.columns = [
TableColumn(field="index", title="Timestamp"),
TableColumn(field="notes", title="Notes"),
]
self.data_table = DataTable(source=notes, columns=self.columns)
layout = row([self.data_table])
doc.add_root(layout)
doc.title = "Notes for {}".format(controller)
# doc.add_periodic_callback(self.update_data,100)
return doc
示例2: pad_plots
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def pad_plots(plots):
"""
Accepts a grid of bokeh plots in form of a list of lists and
wraps any DataTable or Tabs in a WidgetBox with appropriate
padding. Required to avoid overlap in gridplot.
"""
widths = []
for row in plots:
row_widths = []
for p in row:
width = pad_width(p)
row_widths.append(width)
widths.append(row_widths)
plots = [[WidgetBox(p, width=w) if isinstance(p, (DataTable, Tabs)) else p
for p, w in zip(row, ws)] for row, ws in zip(plots, widths)]
return plots
示例3: _create_data_table
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def _create_data_table(
source: ColumnDataSource, schema: ProcSchema, legend_col: str = None
):
"""Return DataTable widget for source."""
column_names = [
schema.user_name,
schema.user_id,
schema.logon_id,
schema.process_id,
schema.process_name,
schema.cmd_line,
schema.parent_id,
schema.parent_name,
schema.target_logon_id,
]
if legend_col and legend_col not in column_names:
column_names.append(legend_col)
date_fmt = "%F %T"
columns = [
TableColumn(
field=schema.time_stamp,
title=schema.time_stamp,
formatter=DateFormatter(format=date_fmt),
)
]
columns2 = [
TableColumn(field=col, title=col)
for col in column_names
if col in source.column_names
]
data_table = DataTable(
source=source, columns=columns + columns2, width=950, height=150
)
return data_table
示例4: make_plot
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
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)
示例5: _build_optresult_selector
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
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
示例6: get_logged_messages
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def get_logged_messages(logged_messages, plot_width):
"""
get a bokeh widgetbox object with a table of the logged text messages
:param logged_messages: ulog.logged_messages
"""
log_times = []
log_levels = []
log_messages = []
for m in logged_messages:
m1, s1 = divmod(int(m.timestamp/1e6), 60)
h1, m1 = divmod(m1, 60)
log_times.append("{:d}:{:02d}:{:02d}".format(h1, m1, s1))
log_levels.append(m.log_level_str())
log_messages.append(m.message)
log_data = dict(
times=log_times,
levels=log_levels,
messages=log_messages)
source = ColumnDataSource(log_data)
columns = [
TableColumn(field="times", title="Time",
width=int(plot_width*0.15), sortable=False),
TableColumn(field="levels", title="Level",
width=int(plot_width*0.1), sortable=False),
TableColumn(field="messages", title="Message",
width=int(plot_width*0.75), sortable=False),
]
data_table = DataTable(source=source, columns=columns, width=plot_width,
height=300, sortable=False, selectable=False)
div = Div(text="""<b>Logged Messages</b>""", width=int(plot_width/2))
return widgetbox(div, data_table, width=plot_width)
示例7: compute_plot_size
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def compute_plot_size(plot):
"""
Computes the size of bokeh models that make up a layout such as
figures, rows, columns, widgetboxes and Plot.
"""
if isinstance(plot, GridBox):
ndmapping = NdMapping({(x, y): fig for fig, y, x in plot.children}, kdims=['x', 'y'])
cols = ndmapping.groupby('x')
rows = ndmapping.groupby('y')
width = sum([max([compute_plot_size(f)[0] for f in col]) for col in cols])
height = sum([max([compute_plot_size(f)[1] for f in row]) for row in rows])
return width, height
elif isinstance(plot, (Div, ToolbarBox)):
# Cannot compute size for Div or ToolbarBox
return 0, 0
elif isinstance(plot, (Row, Column, WidgetBox, Tabs)):
if not plot.children: return 0, 0
if isinstance(plot, Row) or (isinstance(plot, ToolbarBox) and plot.toolbar_location not in ['right', 'left']):
w_agg, h_agg = (np.sum, np.max)
elif isinstance(plot, Tabs):
w_agg, h_agg = (np.max, np.max)
else:
w_agg, h_agg = (np.max, np.sum)
widths, heights = zip(*[compute_plot_size(child) for child in plot.children])
return w_agg(widths), h_agg(heights)
elif isinstance(plot, (Figure, Chart)):
if plot.plot_width:
width = plot.plot_width
else:
width = plot.frame_width + plot.min_border_right + plot.min_border_left
if plot.plot_height:
height = plot.plot_height
else:
height = plot.frame_height + plot.min_border_bottom + plot.min_border_top
return width, height
elif isinstance(plot, (Plot, DataTable, Spacer)):
return plot.width, plot.height
else:
return 0, 0
示例8: pad_width
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def pad_width(model, table_padding=0.85, tabs_padding=1.2):
"""
Computes the width of a model and sets up appropriate padding
for Tabs and DataTable types.
"""
if isinstance(model, Row):
vals = [pad_width(child) for child in model.children]
width = np.max([v for v in vals if v is not None])
elif isinstance(model, Column):
vals = [pad_width(child) for child in model.children]
width = np.sum([v for v in vals if v is not None])
elif isinstance(model, Tabs):
vals = [pad_width(t) for t in model.tabs]
width = np.max([v for v in vals if v is not None])
for model in model.tabs:
model.width = width
width = int(tabs_padding*width)
elif isinstance(model, DataTable):
width = model.width
model.width = int(table_padding*width)
elif isinstance(model, (WidgetBox, Div)):
width = model.width
elif model:
width = model.plot_width
else:
width = 0
return width
示例9: EpitopeTable
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def EpitopeTable(self):
Columns = [TableColumn(field=Ci, title=Ci) for Ci in self.neosData.columns] # bokeh columns
data_table = DataTable(columns=Columns, source=ColumnDataSource(self.neosData) ,width=1200, height=200) # bokeh table
return(data_table)
示例10: SummaryTable
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def SummaryTable(self):
Columns = [TableColumn(field=Ci, title=Ci) for Ci in self.summaryData.columns] # bokeh columns
data_table = DataTable(columns=Columns, source=ColumnDataSource(self.summaryData) ,width=1200, height=200) # bokeh table
return(data_table)
示例11: test_array_to_bokeh_table
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def test_array_to_bokeh_table(self):
dataframe = DataFrame(self.rng.rand(2, 3), columns=[str(i) for i in range(3)])
self.assertTrue(isinstance(array_to_bokeh_table(dataframe), DataTable))
# Pass logger
self.assertTrue(isinstance(array_to_bokeh_table(dataframe, logger=logging.getLogger('test')), DataTable))
# Pass sortable and width
self.assertTrue(isinstance(array_to_bokeh_table(dataframe,
sortable={'1' : True, '2' : True},
width={'1' : 100, '0' : 200}),
DataTable))
# Pass invalid specifications
self.assertRaises(ValueError, array_to_bokeh_table, dataframe, sortable={'7' : True, '2' : True})
self.assertRaises(ValueError, array_to_bokeh_table, dataframe, width={'1' : 100, 10 : 200})
示例12: plot_Scatterplot
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def plot_Scatterplot():
plotname = inspect.stack()[0][3][5:]
pandas_bokeh.output_file(os.path.join(PLOT_DIR, f"{plotname}.html"))
df = df_iris()
df = df.sample(frac=1)
# Create Bokeh-Table with DataFrame:
from bokeh.models.widgets import DataTable, TableColumn
from bokeh.models import ColumnDataSource
data_table = DataTable(
columns=[TableColumn(field=Ci, title=Ci) for Ci in df.columns],
source=ColumnDataSource(df.head(10)),
)
# Create Scatterplot:
p_scatter = df.plot_bokeh.scatter(
x="petal length (cm)",
y="sepal width (cm)",
category="species",
title="Iris DataSet Visualization",
show_figure=False,
)
# Combine Div and Scatterplot via grid layout:
pandas_bokeh.plot_grid([[data_table, p_scatter]], plot_width=400, plot_height=350)
示例13: _create_events_table
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def _create_events_table() -> DataTable:
"""Utility function for creating and styling the events table."""
formatter = HTMLTemplateFormatter(
template="""
<style>
.AS_POS {color: #0000FF; font-weight: bold;}
.AS_NEG {color: #0000FF; font-weight: bold;}
.OP_POS {color: #1aaa0d; font-style: bold;}
.OP_NEG {color: #f40000;font-style: bold;}
.NEG_POS {font-style: italic;}
.NEG_NEG {color: #f40000; font-style: italic;}
.INT_POS {color: #1aaa0d; font-style: italic;}
.INT_NEG {color: #f40000; font-style: italic;}
</style>
<%= value %>"""
)
columns = [
TableColumn(field="POS_events", title="Positive Examples", formatter=formatter),
TableColumn(field="NEG_events", title="Negative Examples", formatter=formatter),
]
return DataTable(
source=ColumnDataSource(),
columns=columns,
height=400,
index_position=None,
width=2110,
sortable=False,
editable=True,
reorderable=False,
)
示例14: _update_events
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def _update_events(events: DataTable, in_domain: bool) -> None:
"""Utility function for updating the content of the events table."""
i = source.selected.indices
events.source.data.update(
{
pol + "_events": stats.loc[aspects[i[0]], pol, in_domain]["Sent_1":].replace(np.nan, "")
if i
else []
for pol in POLARITIES
}
)
示例15: _create_examples_table
# 需要导入模块: from bokeh.models import widgets [as 别名]
# 或者: from bokeh.models.widgets import DataTable [as 别名]
def _create_examples_table() -> DataTable:
"""Utility function for creating and styling the events table."""
formatter = HTMLTemplateFormatter(
template="""
<style>
.AS {color: #0000FF; font-weight: bold;}
.OP {color: #0000FF; font-weight: bold;}
</style>
<div><%= value %></div>"""
)
columns = [
TableColumn(
field="Examples", title='<span class="header">Examples</span>', formatter=formatter
)
]
empty_source = ColumnDataSource()
empty_source.data = {"Examples": []}
return DataTable(
source=empty_source,
columns=columns,
height=500,
index_position=None,
width=1500,
sortable=False,
editable=False,
reorderable=False,
header_row=True,
)